11.02 Fair Housing Choice 4 - Orange County AI
ORANGE COUNTY ANALYSIS OF IMPEDIMENTS TO FAIR HOUSING CHOICE
Prepared by the Orange County Jurisdictions and the Lawyers’ Committee for
Civil Rights Under Law
May 19, 2020
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Orange County Analysis of Impediments to Fair Housing Choice Table of Contents
I. Cover Sheet
II. Executive Summary………………………………………………………………………...3
III. Community Participation Process……………………………………………………….20
IV. Assessment of Past Goals and Actions…………………………………………………....21
V. Fair Housing Analysis
A. Demographic Summary……………………………………………………………43
B. General Issues
i. Segregation/Integration…………………………………………….……....103
ii. Racially or Ethnically Concentrated Areas of Poverty (R/ECAPs) ...….135
iii. Disparities in Access to Opportunity…………………………………….143
iv. Disproportionate Housing Needs………………………...…………….…174
C. Publicly Supported Housing Analysis………...…………………………………215
D. Disability and Access Analysis……………………………………………………242
E. Fair Housing Enforcement, Outreach Capacity, and Resources Analysis….…267
VI. Fair Housing Goals and Priorities…………………………………………………...…273
VII. Contributing Factors Appendix…………………………………….……....................292
VIII. Publicly Supported Housing Appendix…………….………………………….……...313
IX. Glossary …....………………………………………………………….…………………329
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II. EXECUTIVE SUMMARY
Orange County’s Analysis of Impediments to Fair Housing Choice (AI) is a thorough examination
of structural barriers to fair housing choice and access to opportunity for members of historically
marginalized groups protected from discrimination by the federal Fair Housing Act (FHA). The
AI also outlines fair housing priorities and goals to overcome fair housing issues. In addition, the
AI lays out meaningful strategies that can be implemented to achieve progress towards the
County’s obligation to affirmatively furthering fair housing. The Lawyers’ Committee for Civil
Rights Under Law (Lawyers’ Committee), in consultation with Orange County jurisdictions and
with input from a wide range of stakeholders through a community participation process, prepared
this AI. To provide a foundation for the conclusions and recommendations presented in this AI,
the following information was reviewed and analyzed:
Data from the U.S. Census Bureau, American Community Survey 2013-2017 and other
sources about the demographic, housing, economic, and educational landscape of the
County, nearby communities, and the broader Region;
Various County and city planning documents and ordinances;
Data reflecting housing discrimination complaints;
The input of a broad range of stakeholders that deal with the realities of the housing
market and the lives of members of protected classes in Orange County.
As required by federal regulations, the AI draws from the sources listed above to conduct an
anal ysis of fair housing issues such as patterns of integration and segregation of members of
protected classes, racially or ethnically concentrated areas of poverty regionally, disparities in
access to opportunity for protected classes, and disproportionate housing needs. The analysis also
examines publicly supported housing in the County as well as fair housing issues for persons with
disabilities. Private and public fair housing enforcement, outreach capacity, and resources are
evaluated as well. The AI identifies contributing factors to fair housing issues and steps that should
be taken to overcome these barriers.
The Orange County AI is a collaborative effort between the following jurisdictions: Aliso Viejo,
Anaheim, Buena Park, Costa Mesa, Fountain Valley, Fullerton, Garden Grove, Huntington Beach,
Irvine, Laguna Niguel, La Habra, Lake Forest, La Palma, Mission Viejo, Orange, Rancho San
Margarita, San Clemente, San Juan Capistrano, Santa Ana, Tustin, Westminster, and the County
of Orange. Although this is a county-wide AI, there are jurisdiction-specific versions that include
goals specific to each jurisdiction.
Overview of Orange County
According to U.S. Census data, the population of Orange County has changed considerably from
1990 to present day. The population has grown from just over 2.4 million in 1990 to nearly 3.2
million people today. The demographics of the County have undergone even more dramatic shifts
over this time period: the white population has gone from 76.2% in 1990 to 57.8% in the 2010
Census, with corresponding increases in Hispanic (from 13.5% to 21.2%) and Asian (from 8.6%
to 18.3%) populations in that same time period. These trends represent accelerations of the broader
Los-Angeles-Long Beach-Anaheim, CA Metropolitan Statistical Area (the Region). In the Region,
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white population percentage has declined from 45.9% percent to under 31.6%, with substantial
increases in the percentages of Hispanic (from 34.7% to 44.4%) and Asian (from 10.2% to 16%)
from the 1990 to 2010 Censuses.
There are numerous ethnic enclaves of Hispanic, Vietnamese, Chinese and other groups
throughout Orange County. These enclaves provide a sense of community and a social network
that may help newcomers preserve their cultural identities. However, these active choices should
not obscure the significant impact of structural barriers to fair housing choice and discrimination.
Within both Orange County and the broader Region, most racial or ethnic minority groups
experience higher rates of housing problems, including but not limited to severe housing cost
burden, with monthly housing costs exceeding 50 percent of monthly income, than do non-
Hispanic White households. In Orange County, Hispanic households are most likely to experience
severe housing cost burden; in the Region, it is Black households.
There are 194,569 households in Orange County experiencing housing cost burden, with monthly
housing costs exceeding 30 percent of monthly income. 104,196 of these households are families.
However, Orange County has only 429 Project-Based Section 8 units and 33 Other Multifamily
units with more than one bedroom capable of housing these families. Housing Choice Vouchers
are the most utilized form of publicly supported housing for families, with 2,286 multi-bedroom
units accessed. Large family households are also disproportionately affected by housing problems
as compared with non-family households. Some focus groups have communicated that regulations
and cost issues can make Orange County too expensive for families. The high percentage of 0-1-
bedroom units in publicly supported housing and the low percentage of households with children
in publicly supported housing support this observation.
The federal Fair Housing Act and the California Fair Employment and Housing Act provide
Orange County residents with some protections from displacement and work to increase the supply
of affordable housing. In addition, jurisdictions throughout Orange County have worked diligently
to provide access to fair housing through anti-housing discrimination work, creating housing
opportunities designed to enhance resident mobility, providing zoning flexibility where necessary,
and working to reduce hate crimes. Even so, these protections and incentives are not enough to
stem the loss of affordable housing and meet the housing needs of low- and moderate-income
residents.
Contributing Factors to Fair Housing Issues
The AI includes a discussion and analysis of the following contributing factors to fair housing
issues:
1. Access to financial services
2. Access for persons with disabilities to proficient schools
3. Access to publicly supported housing for persons with disabilities
4. Access to transportation for persons with disabilities
5. Admissions and occupancy policies and procedures, including preferences in publicly
supported housing
6. Availability of affordable units in a range of sizes
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7. Availability, type, frequency, and reliability of public transportation
8. Community opposition
9. Deteriorated and abandoned properties
10. Displacement of and/or lack of housing support for victims of domestic violence, dating
violence, sexual assault, and stalking
11. Displacement of residents due to economic pressures
12. Impediments to mobility
13. Inaccessible public or private infrastructure
14. Inaccessible government facilities or services
15. Lack of access to opportunity due to high housing costs
16. Lack of affordable, accessible housing in a range of unit sizes
17. Lack of affordable in-home or community-based supportive services
18. Lack of affordable, integrated housing for individuals who need supportive services
19. Lack of assistance for housing accessibility modifications
20. Lack of assistance for transitioning from institutional settings to integrated housing
21. Lack of community revitalization strategies
22. Lack of local private fair housing outreach and enforcement
23. Lack of local public fair housing enforcement
24. Lack of local or regional cooperation
25. Lack of meaningful language access for individuals with limited English proficiency
26. Lack of private investment in specific neighborhoods
27. Lack of public investment in specific neighborhoods, including services or amenities
28. Lack of resources for fair housing agencies and organizations
29. Lack of state or local fair housing laws
30. Land use and zoning laws
31. Lending discrimination
32. Location of accessible housing
33. Location of employers
34. Location of environmental health hazards
35. Location of proficient schools and school assignment policies
36. Location and type of affordable housing
37. Loss of affordable housing
38. Occupancy codes and restrictions
39. Private discrimination
40. Quality of affordable housing information programs
41. Regulatory barriers to providing housing and supportive services for persons with
disabilities
42. Siting selection policies, practices, and decisions for publicly supported housing,
including discretionary aspects of Qualified Allocation Plans and other programs
43. Source of income discrimination
44. State or local laws, policies, or practices that discourage individuals with disabilities from
living in apartments, family homes, supportive housing and other integrated settings
45. Unresolved violations of fair housing or civil rights law.
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Proposed Goals and Strategies
To address the contributing factors described above, the AI plan proposes the following goals and
actions:
Regional Goals and Strategies
Goal 1: Increase the supply of affordable housing in high opportunity areas.1
Strategies:
1. Explore the creation of a new countywide source of affordable housing.
2. Using best practices from other jurisdictions, explore policies and programs that increase
the supply affordable housing, such as linkage fees, housing bonds, inclusionary housing,
public land set-aside, community land trusts, transit-oriented development, and expedited
permitting and review.
3. Explore providing low-interest loans to single-family homeowners and grants to
homeowners with household incomes of up to 80% of the Area Median Income to develop
accessory dwelling units with affordability restriction on their property.
4. Review existing zoning policies and explore zoning changes to facilitate the development
of affordable housing.
5. Align zoning codes to conform to recent California affordable housing legislation.
Goal 2: Prevent displacement of low- and moderate-income residents with protected
characteristics, including Hispanic residents, Vietnamese residents, other seniors, and people with
disabilities.
Strategies:
1. Explore piloting a Right to Counsel Program to ensure legal representation for tenants in
landlord-tenant proceedings, including those involving the application of new laws like
A.B. 1482.
Goal 3: Increase community integration for persons with disabilities.
Strategies:
1. Conduct targeted outreach and provide tenant application assistance and support to persons
with disabilities, including individuals transitioning from institutional settings and
individuals who are at risk of institutionalization. As part of that assistance, maintain a
database of housing that is accessible to persons with disabilities.
2. Consider adopting the accessibility standards adopted by the City of Los Angeles, which
require at least 15 percent of all new units in city-supported Low-Income Housing Tax
Credit (LIHTC) projects to be ADA-accessible with at least 4 percent of total units to be
accessible for persons with hearing and/or vision disabilities.
1 The term “high opportunity areas” generally means locations where there are economic and social factors and
amenities that provide a positive impact on a person’s life outcome. This is described in more detail in Section iii,
Disparities in Access to Opportunity.
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Goal 4: Ensure equal access to housing for persons with protected characteristics, who are
disproportionately likely to be lower-income and to experience homelessness.
Strategies:
1. Reduce barriers to accessing rental housing by exploring eliminating application fees for
voucher holders and encouraging landlords to follow HUD’s guidance on the use of
criminal backgrounds in screening tenants.
2. Consider incorporating a fair housing equity analysis into the review of significant
rezoning proposals and specific plans.
Goal 5: Expand access to opportunity for protected classes.
Strategies:
1. Explore the voluntary adoption of Small Area Fair Market Rents or exception payment
standards in order to increase access to higher opportunity areas for Housing Choice
Voucher holders.
2. Continue implementing a mobility counseling program that informs Housing Choice
Voucher holders about their residential options in higher opportunity areas and provides
holistic supports to voucher holders seeking to move to higher opportunity areas.
3. Study and make recommendations to improve and expand Orange County’s public
transportation to ensure that members of protected classes can access jobs in employment
centers in Anaheim, Santa Ana, and Irvine.
4. Increase support for fair housing enforcement, education, and outreach.
Individual Jurisdictions’ Proposed Goals and Strategies
City of Aliso Viejo
1. In collaboration with the Orange County Housing Authority (OCHA):
a. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange of
information regarding the availability, procedures, and policies related to the Housing
Assistance Voucher program and regional housing issues.
b. Support OCHA's affirmative fair marketing plan and de-concentration policies by
providing five-year and annual PHA plan certifications.
c. In coordination with OCHA and fair housing services provider, conduct landlord
education campaign to educate property owners about State law prohibiting
discrimination based on household income.
2. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and homeowner
associations on why denial of reasonable modifications/accommodations is unlawful.
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property owners,
realtors, and property management companies. Methods of outreach may include
workshops, informational booths, presentations to community groups, and distribution of
multi-lingual fair housing literature.
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City of Anaheim
1. Increase the supply of affordable housing through the following strategies:
a. Explore creative land use and zoning policies that facilitate the development of
affordable housing, examples include a housing overlay zone or religious institutions
amendment.
b. Review Anaheim’s current Density Bonus and Accessory Dwelling Unit (ADU)
Ordinances to ensure compliance with state requirements.
c. Support legislation that removes CEQA requirements for affordable housing.
d. Identify and explore allocating city-owned sites that may be well suited for housing for
which there are no other development plans.
e. Continue to support tenant based rental assistance programs that facilitates additional
affordable housing for homeless and low-income individuals.
2. Preserve the existing stock of affordable rental housing and rent stabilized housing through
the following strategies:
a. Strengthen and expand education and outreach of tenants and owner of affordable rental
housing at risk of conversion to market rents.
b. Extend affordability restrictions through loan extensions, workouts and buy-downs of
affordability.
c. Preserve at-risk housing through the issuance of Tax-Exempt Bond financing.
d. Explore the development of a rental rehabilitation loan program.
3. Expand the access to fair housing services and other housing services through the following
strategies:
a. Dedicate eligible entitlement dollars (CDBG, HOME, etc.) and explore local, state and
federal resources to expand fair housing services.
b. Continue to support fair housing testing and investigation to look for evidence of
differential treatment and disparate impact, including providing services to low income
tenants reporting fair housing violations.
c. Continue to support fair housing presentations, mass media communications, and multi-
lingual literature distribution; conduct fair housing presentations at accessible locations
and conduct fair housing presentations for housing providers.
d. Explore alternative formats for fair housing education workshops such as pre-taped videos
and/ or recordings. Such formats could serve persons with one or more than one job,
families with you children and other who find it difficult to attend meetings in person.
4. Continue efforts to build complete communities through the following strategies:
a. Maximize and secure funding from State of California’s Cap and Trade Program
(Greenhouse Gas Reduction Fund), to improve housing opportunities, increase economic
investments and address environmental factors in disadvantaged communities.
b. The City will continue to work with local transit agencies and other appropriate agencies
to facilitate safe and efficient routes of transportation, including public transit, walking
and biking.
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c. Explore development of a policy to encourage developers to provide residents with
incentives to use non-auto means of transportation, including locating new developments
near public transportation and providing benefits such as bus passes.
d. Prioritize workforce development resources in racially or ethnically concentrated areas of
poverty to improve economic mobility.
City of Buena Park
1. In collaboration with the Orange County Housing Authority (OCHA):
a. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange of
information regarding the availability, procedures, and policies related to the Housing
Assistance Voucher program and regional housing issues.
b. Support OCHA's affirmative fair marketing plan and de-concentration policies by
providing five-year and annual PHA plan certifications.
c. In coordination with OCHA and fair housing services provider, conduct landlord
education campaign to educate property owners about State law prohibiting
discrimination based on household income.
2. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and homeowner
associations on why denial of reasonable modifications/accommodations is unlawful.
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property owners,
realtors, and property management companies. Methods of outreach may include
workshops, informational booths, presentations to community groups, and distribution of
multi-lingual fair housing literature.
City of Costa Mesa
1. In collaboration with the Orange County Housing Authority (OCHA):
a. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange of
information regarding the availability, procedures, and policies related to the Housing
Assistance Voucher program and regional housing issues.
b. Support OCHA's affirmative fair marketing plan and de-concentration policies by
providing five-year and annual PHA plan certifications.
c. In coordination with OCHA and fair housing services provider, conduct landlord
education campaign to educate property owners about State law prohibiting
discrimination based on household income.
2. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and homeowner
associations on why denial of reasonable modifications/accommodations is unlawful.
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property owners,
realtors, and property management companies. Methods of outreach may include
workshops, informational booths, presentations to community groups, and distribution of
multi-lingual fair housing literature.
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City of Fountain Valley
1. Explore an inclusionary zoning requirement for all new housing developments that requires at
least 10-15 percent of for-sale units be affordable to households with incomes 80 percent or
below and rental units be affordable to households with incomes 60 percent or below.
2. Consider adopting an expedited permitting and review process for new developments with an
affordable housing set-aside.
City of Fullerton
1. Create a Housing Incentive Overlay Zone (HOIZ).
2. Draft and Approve an Affordable Housing and Religious Institutions Amendment to the
Municipal Code.
3. Work with the State to streamline or remove CEQA Requirements for Affordable Housing.
4. Require Affordable Housing in Surplus Property Sales.
City of Garden Grove
1. Update Density Bonus Ordinance – Garden Grove will update the 2011 Density Bonus
Ordinance to comply with current State law. The update will streamline the approval process,
increase feasibility, and facilitate future housing development at all affordability levels.
2. Create Objective Residential Development Standards to allow for streamlined housing
development in all residential zones.
3. Create Objective Development Standards for Supportive Housing. These standards would be
for new construction of Supportive Housing.
4. Evaluate the creation of Objective Development Standards for Hotel/Motel/Office Conversion
to Supportive Housing.
5. Review and amend Garden Grove’s current Accessory Dwelling Unit (ADU) Ordinance to
comply with State requirements and further increase housing supply.
6. Continue to invest in landlord and tenant counseling and mediation services, unlawful detainer
assistance, housing discrimination services, homebuyer education and outreach, and local
eviction prevention strategies.
City of Huntington Beach
1. Modify the existing Inclusionary Housing Ordinance to increase the supply of affordable
housing opportunities available to lower income persons and households.
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a. Study the current methodology of setting the maximum sales price and down payment
requirements of an affordable home for ownership.
b. Study requirements for the provision of inclusionary units through on-site units, dedication
of land, in-lieu fees, and off-site development.
c. Study the in-lieu fee structure.
d. Explore the provision of incentives for developments that exceed inclusionary requirements
and/or provide extremely low-income units on site. Incentives can be through the provision
of fee waivers and deferrals, financial assistance, regulatory relief, and flexible
development standards.
2. Update the density bonus ordinance to be consistent with state law,
3. Expand the TBRA program to help tenants impacted by Covid-19. Currently, an eviction
moratorium is in place to prevent evictions due to lack of non-payment of rent due to Covid-
19. This moratorium ends on May 31, 2020. The moratorium does not end the obligation to
pay the rent eventually. On June 1, 2020, there most likely will be an increased need from
persons to receive rental assistance for the rents due prior to May 31 and going forward. The
City would work with its current service providers to help tenants impacted by Covid-19.
City of Irvine
1. Ensure compliance with their HCD-certified Housing Element.
2. Update Density Bonus Ordinance – Irvine will update the Density Bonus Ordinance to comply
with current State law.
3. Review and amend Irvine’s Inclusionary Housing Ordinance, as necessary, to increase its
effectiveness.
4. Review and amend Irvine’s current Accessory Dwelling Unit (ADU) Ordinance to comply with
State requirements and further increase housing supply.
5. Create Objective Development Standards for Supportive Housing. These standards would be
for new construction of Supportive Housing.
6. Working with the City’s fair housing services provider, continue to invest in local eviction
prevention strategies to reduce the number of homeless individuals and families in Irvine.
7. Working with the City’s fair housing services provider, continue to invest in landlord and
tenant counseling and mediation services, unlawful detainer assistance, housing
discrimination services, and homebuyer education and outreach.
City of La Habra
1. Explore the creation of an inclusionary housing ordinance to increase the number of
affordable housing units.
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2. Advocate for increasing the minimum percentage of affordable units at Park La Habra Mobile
Home and View Park Mobile Home Estates from 20 percent to 50 percent.
City of Laguna Niguel
1. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange of information
regarding the availability, procedures, and policies related to the Housing Assistance Voucher
program and regional housing issues.
2. In collaboration with the Orange County Housing Authority (OCHA):
a. Support OCHA's affirmative fair marketing plan and de-concentration policies by
providing five-year and annual PHA plan certifications.
b. In coordination with OCHA and fair housing services provider, conduct landlord
education campaign to educate property owners about State law prohibiting
discrimination based on household income.
3. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and homeowner
associations on why denial of reasonable modifications/accommodations is unlawful.
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property owners,
realtors, and property management companies. Methods of outreach may include
workshops, informational booths, presentations to community groups, and distribution of
multi-lingual fair housing literature.
c. Provide general fair housing counseling and referrals services to address tenant-landlord
issues, and investigate allegations of fair housing discrimination and take appropriate
actions to conciliate cases or refer to appropriate authorities.
d. Periodically monitor local newspapers and online media outlets to identify potentially
discriminatory housing advertisements.
e. Include testing/audits within the scope of work with fair housing provider.
4. Prepare a new Housing Element that is compliant with all current State laws and is certified
by the California Department of Housing and Community Development.
5. Update zoning ordinance to comply with current State law.
6. In cooperation with the Orange County Transportation Authority, provide community
education regarding transport services for persons with disabilities.
7. Support local eviction prevention strategies to reduce the number of homeless individuals and
families (homelessness prevention services).
City of Lake Forest
1. In collaboration with the Orange County Housing Authority (OCHA):
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a. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange of
information regarding the availability, procedures, and policies related to the Housing
Assistance Voucher program and regional housing issues.
b. Support OCHA's affirmative fair marketing plan and de-concentration policies by
providing five-year and annual PHA plan certifications.
c. In coordination with OCHA and fair housing services provider, conduct landlord
education campaign to educate property owners about State law prohibiting
discrimination based on household income.
2. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and homeowner
associations on why denial of reasonable modifications/accommodations is unlawful.
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property owners,
realtors, and property management companies. Methods of outreach may include
workshops, informational booths, presentations to community groups, and distribution of
multi-lingual fair housing literature.
c. Provide general fair housing counseling and referrals services to address tenant-landlord
issues, and investigate allegations of fair housing discrimination and take appropriate
actions to conciliate cases or refer to appropriate authorities.
d. Periodically monitor local newspapers and online media outlets to identify potentially
discriminatory housing advertisements.
e. Include testing/audits within the scope of work with fair housing provider.
f. Regularly consult with the City's fair housing contractor on potential strategies for
affirmatively furthering fair housing on an on-going basis.
3. In cooperation with the Orange County Transportation Authority:
a. Provide community education regarding transport services for persons with disabilities.
b. Explore bus route options to ensure neighborhoods with concentration of low-income or
protected class populations have access to transportation services.
4. Support local eviction prevention strategies to reduce the number of homeless individuals and
families (homelessness prevention services).
5. Prepare a new Housing Element that is compliant with all current State laws and is certified
by the California Department of Housing and Community Development.
6. Update zoning ordinance to comply with current State law.
City of Mission Viejo
1. In collaboration with the Orange County Housing Authority (OCHA):
a. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange of
information regarding the availability, procedures, and policies related to the Housing
Assistance Voucher program and regional housing issues.
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b. Support OCHA's affirmative fair marketing plan and de-concentration policies by
providing five-year and annual PHA plan certifications.
c. In coordination with OCHA and fair housing services provider, conduct landlord
education campaign to educate property owners about State law prohibiting
discrimination based on household income.
2. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and homeowner
associations on why denial of reasonable modifications/accommodations is unlawful.
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property owners,
realtors, and property management companies. Methods of outreach may include
workshops, informational booths, presentations to community groups, and distribution of
multi-lingual fair housing literature.
c. Provide general fair housing counseling and referrals services to address tenant-landlord
issues, and investigate allegations of fair housing discrimination and take appropriate
actions to conciliate cases or refer to appropriate authorities.
d. Periodically monitor local newspapers and online media outlets to identify potentially
discriminatory housing advertisements.
e. Include testing/audits within the scope of work with fair housing provider.
3. In cooperation with the Orange County Transportation Authority:
a. Provide community education regarding transport services for persons with disabilities.
b. Explore bus route options to ensure neighborhoods with concentration of low-income or
protected class populations have access to transportation services.
4. Monitor FBI data to determine if any hate crimes are housing related and if there are actions
that may be taken by the City’s fair housing service provider to address potential
discrimination linked to the bias motivations of hate crimes.
5. Support local eviction prevention strategies to reduce the number of homeless individuals and
families (homelessness prevention services).
6. Seek funding through State programs (SB2/PLHA) to expand affordable housing and or
homelessness prevention services.
7. Prepare a new Housing Element that is compliant with all current State laws and is certified
by the California Department of Housing and Community Development.
8. Update zoning ordinance to comply with current State law.
City of Orange
1. Continue to follow current State Density Bonus law and further its implementation through a
Density Bonus ordinance update.
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2. Prepare a Transfer of Development Rights Ordinance to provide opportunities for
development rights transfers to accommodate higher density housing in transit and
employment-rich areas of the city.
3. Continue providing financial assistance to the affordable housing projects.
4. Amend the City’s Accessory Dwelling Unit Ordinance to be consistent with State Junior
Accessory Dwelling Unit (JADU) and Accessory Dwelling Unit (ADU) laws.
5. Facilitate the development of housing along the North Tustin corridor by the way of a specific
plan or rezoning measures.
6. Continue providing CDBG funds to the Fair Housing Foundation to provide fair housing
activities to the community.
City of Rancho Santa Margarita
1. In collaboration with the Orange County Housing Authority (OCHA):
a. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange of
information regarding the availability, procedures, and policies related to the Housing
Assistance Voucher program and regional housing issues.
b. Support OCHA's affirmative fair marketing plan and de-concentration policies by
providing five-year and annual PHA plan certifications.
c. In coordination with OCHA and fair housing services provider, conduct landlord
education campaign to educate property owners about State law prohibiting
discrimination based on household income.
2. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and homeowner
associations on why denial of reasonable modifications/accommodations is unlawful.
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property owners,
realtors, and property management companies. Methods of outreach may include
workshops, informational booths, presentations to community groups, and distribution of
multi-lingual fair housing literature.
c. Provide general fair housing counseling and referrals services to address tenant-landlord
issues, and investigate allegations of fair housing discrimination and take appropriate
actions to conciliate cases or refer to appropriate authorities.
d. Periodically monitor local newspapers and online media outlets to identify potentially
discriminatory housing advertisements.
e. Include testing/audits within the scope of work with fair housing provider.
3. In cooperation with the Orange County Transportation Authority:
a. Provide community education regarding transport services for persons with disabilities.
b. Explore bus route options to ensure neighborhoods with concentration of low-income or
protected class populations have access to transportation services.
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4. Monitor FBI data to determine if any hate crimes are housing related and if there are actions
that may be taken by the City’s fair housing service provider to address potential
discrimination linked to the bias motivations of hate crimes.
5. Support local eviction prevention strategies to reduce the number of homeless individuals and
families (homelessness prevention services).
6. Seek funding through State programs (SB2/PLHA) to expand affordable housing and or
homelessness prevention services.
7. Prepare a new Housing Element that is compliant with all current State laws and is certified
by the California Department of Housing and Community Development.
8. Update zoning ordinance to comply with current State law.
City of San Clemente
1. In collaboration with the Orange County Housing Authority (OCHA):
a. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange of
information regarding the availability, procedures, and policies related to the Housing
Assistance Voucher program and regional housing issues.
b. Support OCHA's affirmative fair marketing plan and de-concentration policies by
providing five-year and annual PHA plan certifications.
c. In coordination with OCHA and fair housing services provider, conduct landlord
education campaign to educate property owners about State law prohibiting
discrimination based on household income.
2. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and homeowner
associations on why denial of reasonable modifications/accommodations is unlawful.
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property owners,
realtors, and property management companies. Methods of outreach may include
workshops, informational booths, presentations to community groups, and distribution
of multi-lingual fair housing literature.
c. Provide general fair housing counseling and referrals services to address tenant-
landlord issues, and investigate allegations of fair housing discrimination and take
appropriate actions to conciliate cases or refer to appropriate authorities.
d. Periodically monitor local newspapers and online media outlets to identify potentially
discriminatory housing advertisements.
e. Include testing/audits within the scope of work with fair housing provider.
3. Support local eviction prevention strategies to reduce the number of homeless individuals and
families (homelessness prevention services).
4. Prepare a new Housing Element that is compliant with all current State laws and is certified
by the California Department of Housing and Community Development.
17
5. Update zoning ordinance to comply with current State law.
6. Offer a variety of housing opportunities to enhance mobility among residents of all races and
ethnicities by facilitating affordable housing throughout the community through 1) flexible
development standards; 2) density bonuses; and 3) other zoning tools.
7. Review the type and effectiveness of current affordable housing development incentives, and
amend/augment as may be necessary to increase the production of affordable housing units.
City of San Juan Capistrano
1. Develop Strategies to Address Lack of Affordability and Insufficient Income
a. Work with developers, and non-profit organizations to expand the affordable housing stock
within San Juan Capistrano.
b. Increase production of new affordable units an d assistance towards the purchase and
renovation of housing in existing neighborhoods.
c. Seek housing program resources through the County of Orange Urban County CDBG
Program, and others which may become available.
2. Increase Public Awareness of Fair Housing
a. Increase fair housing education and outreach efforts.
b. Investigate options for enforcement including local enforcement conducted by neighboring
jurisdictions.
3. Develop Strategies to Address Poverty and Low-Incomes Among Minority Populations
a. Expand job opportunities through encouragement of corporations relocating to the city,
local corporations seeking to expand, assistance with small business loans, and other
activities.
b. Support agencies that provide workforce development programs and continuing education
courses to increase educational levels and job skills of residents.
4. Develop Strategies to Address Limited Resources to Assist Lower-Income, Elderly, and
Indigent Homeowners Maintain their Homes and Stability in Neighborhoods
a. Consider implementing a volunteer program for providing housing assistance to elderly
and indigent property owners, including assistance in complying with municipal housing
codes.
b. Encourage involvement from volunteers, community organizations, religious
organizations, and businesses as a means of supplementing available financial resources
for housing repair and neighborhood cleanup.
City of Santa Ana
1. Review and amend Santa Ana’s inclusionary housing ordinance to increase its effectiveness.
2. Evaluate the creation of a motel conversion ordinance to increase the supply of permanent
supportive housing similar to the City of Anaheim and Los Angeles.
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3. Review Santa Ana’s density bonus ordinance and explore adding a density bonus for transit-
oriented development (TOD) similar to the City of Los Angeles.
4. Explore establishing a dedicated source of local funding for a Right to Counsel program for
residents of Santa Ana to ensure that they have access to legal representation during eviction
proceedings similar to the City of New York.
5. Continue to invest in local eviction prevention strategies to reduce the number of homeless
individuals and families in Santa Ana.
City of Tustin
1. In collaboration with the Orange County Housing Authority (OCHA):
a. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange
of information regarding the availability, procedures, and policies related to the
Housing Assistance Voucher program and regional housing issues.
b. Support OCHA's affirmative fair marketing plan and de-concentration policies
by providing five-year and annual PHA plan certifications.
c. In coordination with OCHA and fair housing services provider, conduct
landlord education campaign to educate property owners about State law
prohibiting discrimination based on household income.
2. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and
homeowner associations on why denial of reasonable modifications/accommodations is
unlawful.
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property
owners, realtors, and property management companies. Methods of outreach may
include workshops, informational booths, presentations to community groups, and
distribution of multi-lingual fair housing literature.
c. Provide general fair housing counseling and referrals services to address tenant-
landlord issues, and investigate allegations of fair housing discrimination and
take appropriate actions to conciliate cases or refer to appropriate authorities.
d. Periodically monitor local newspapers and online media outlets to identify
potentially discriminatory housing advertisements.
e. Include testing/audits within the scope of work with fair housing provider.
3. Prepare a new Housing Element that is compliant with all current State laws and is certified
by the California Department of Housing and Community Development.
4. Utilize funding through State programs (SB2) to support affordable housing and/or
homeless prevention services.
5. Update zoning ordinance to comply with current State law.
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The AI lays out a series of achievable action steps that will help jurisdictions in Orange County to
not only meet its obligation to affirmatively fair housing but to continue to be a model for equity
and inclusion in Orange County.
20
III. COMMUNITY PARTICIPATION PROCESS
1. Describe outreach activities undertaken to encourage and broaden meaningful
community participation in the AI process, including the types of outreach activities and
dates of public hearings or meetings. Identify media outlets used and include a description
of efforts made to reach the public, including those representing populations that are
typically underrepresented in the planning process such as persons who reside in areas
identified as R/ECAPs, persons who are limited English proficient (LEP), and persons with
disabilities. Briefly explain how these communications were designed to reach the broadest
audience possible. For PHAs, identify your meetings with the Resident Advisory Board.
In order to ensure that the analysis contained in an AI truly reflects conditions in a community and
that the goals and strategies are targeted and feasible, the participation of a wide range of
stakeholders is of critical importance. A broad array of outreach was conducted through
community meetings, focus groups, and public hearings.
In preparing this AI, the Lawyers’ Committee reached out to tenants, landlords, homeowners, fair
housing organizations, civil rights and advocacy organizations, legal services provers, social
services providers, housing developers, and industry groups to hear directly about fair housing
issues affecting residents of Orange County.
Beginning in October, 2019, the Lawyers’ Committee held meetings with individual stakeholders
throughout the County. In January and February 2020, evening community meetings were held in
Mission Viejo, Westminster/Garden Grove, Santa Ana, and Fullerton. Also in February, the
Lawyers’ Committee held a focus group with a wide array of nonprofit organizations and
government officials.
Geographically specific community meetings were held across Orange County, including the
South, West, Central, and North parts of the County. Additional outreach was conducted for
members of protected classes, including the Latino and Vietnamese communities. All community
meetings had translation services available if requested in Spanish and Vietnamese. In addition,
all meetings were held in locations accessible to people with mobility issues. The Executive
Summary of the AI will be translated into Spanish and Vietnamese.
Public hearings and City Council meetings were held throughout the County during the Spring.
Due to the prohibition of gatherings due to COVID, hearings and meetings were held remotely.
There have been no written comments to date but any comments received will be either
incorporated into the document or addressed as to why they were not incorporated in the Appendix.
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IV. ASSESSMENT OF PAST GOALS, ACTIONS AND STRATEGIES
a. Indicate what fair housing goals were selected by program participant(s) in recent
Analyses of Impediments, Assessments of Fair Housing, or other relevant planning
documents.
City of Aliso Viejo (the City became an entitlement community in 2018)
Housing Discrimination
The City of Aliso Viejo contracted with the Fair Housing Foundation and jointly participated
in fair housing outreach and education to renters, homebuyers, lenders, and property managers.
Unfair Lending
The City contracted with the Fair Housing Foundation to identify lenders and transmit findings
to HUD and the Consumer Financial Protection Bureau.
Discriminatory Advertising
The City contracted with the Fair Housing Foundation to support efforts to identify online
discriminatory advertising and request that Craigslist and the OC register publish fair housing
and reasonable accommodation notices.
City of Anaheim
Housing Discrimination
The City allocated CDBG funds to the Fair Housing Foundation (FHF) to provide fair housing
services to the Anaheim residents and operators of rental properties. These services include
holding tenant and landlord workshops, counseling, and resolving any housing issues and
allegations of discrimination
Reasonable Accommodations
In June of 2018, the City's Planning and Building Department amended its fee schedule and
removed the reasonable accommodations application fee.
Zoning
Community Development and Planning staff will continue its review of AB 222 and AB 744
and plan to incorporate the necessary standards and provisions into the next zoning code
update.
City of Buena Park
Housing Discrimination
The Fair Housing Foundation (FHF) conducted 4 tenant, 4 landlord and 4 property manager
training.
FHF participated in the Buena Park Collaborative, North Orange County Chamber of
Conference, Annual Super Senior Saturday, Buena Park School District Annual Kinder Faire,
and the inaugural Open House and Resource Fair.
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FHF addressed 602 “Housing” issues during the report period. The most common issues were
notices, habitability, rent increases, security deposits, lease terms, and rights and
responsibilities.
Racial and Ethnic Segregation
FHF provided fair housing literature in both English and Spanish.
PSAs were aired on the City’s cable station.
Participated in quarterly OCHA (PHA) Housing Advisory Committee meetings.
The City does not offer homebuyer assistance programs.
Reasonable Accommodations
FHF provided fair housing related serves to 490 unduplicated households from tenants,
landlords and managers, and property owners.
33 fair housing allegations were received by FHF. Protected classes included race (8), familial
status (1), and mental and physical disability (22). 22 allegations were resolved – 11 cases were
opened and 2 are pending. No evidence was found in 4 cases to sustain allegations; however,
4 cases were opened and ultimately resolved via conciliation.
FHF conducted 3 landlord and 3 certified property managers trainings.
FHF developed an “Accommodation & Modification 101 Workshop” for housing providers
that covers the legal parameters that housing providers need to know in order to make an
informed decision when addressing accommodation & modification requests.
Unfair Lending
The City no longer offers homebuyer assistance. FHF utilizes the City’s quarterly magazine to
promote housing rehabilitation programs. The magazine is distributed to each housing unit
city-wide.
Density Bonus Incentives
The City’s Zoning code was amended to comply with current state density bonus law during
prior report period.
City of Costa Mesa
During the report period the City took the following actions in an effort to overcome the
impediments to fair housing choice identified in the AI:
Housing Discrimination
Fair housing services was provided to 902 Costa Mesa households dealing with general
housing issues and allegations of discrimination. Over 669 issues, disputes, and/or inquiries
were addressed. The majority of general housing issues addressed by the FHF included notices,
habitability issues, security deposits, and rent increases.
65 housing discrimination inquiries were received by the FHF: 9 based on physical or mental
disability, 8 related to race, 2 related to national origin, 2 related to gender, 1 related to sexual
orientation, and 5 related to familial status. 45 were counseled/resolved, and 15 cases were
opened. Investigations found no evidence of discrimination in 9 cases; 2 were inconclusive;
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and in 4 cases the allegations were sustained and the investigation is pending for 2 cases and
resolved for 2 cases.
The City worked closely with the FHF to provide certified fair housing training for housing
industry realtors and property managers – 7 workshops were conducted during the report
period. Additionally, 7 tenant and 7 landlord workshops were conducted in Costa Mesa.
Racial and Ethnic Segregation
Literature related to fair housing were distributed at these events, at City Hall, community
centers, and community events. Literature was provided to the community in English, Spanish
and Vietnamese. City staff distributed large numbers of this literature in target neighborhoods
in conjunction with other neighborhood improvement efforts.
Reasonable Accommodations
FHF developed an “Accommodation & Modification 101 Workshop” for housing providers
that covers the legal parameters that housing providers need to know in order to make an
informed decision when addressing accommodation and modification requests.
Unfair Lending
The City does not offer homebuyer assistance. Housing Rehab programs are marketed citywide
in English and Spanish.
Density Bonus Incentive
The City’s Zone Codes are compliant with current State density bonus laws.
City of Fountain Valley
Housing Discrimination
Fair housing outreach and training, general counseling and referrals, and testing/audits
provided by Fair Housing Council of Orange County (FHCOC).
Racial and Ethnic Segregation
Fair housing services, education/outreach, and testing in areas of racial/et hnic concentrations
provided by FHCOC.
Grants, rebates and loans are available to low -income, owner-occupied households for repair
and rehabilitation through the City’s Home Improvement Program.
The zoning code was updated in 2018 to remain consistent with the California density bonus
law.
The city and FHCOC provide fair housing and neighborhood improvement program
information in multiple languages.
Housing rehabilitation programs are marketed to low income households which include areas
of racial/ethnic concentration
Reasonable Accommodations
Fair housing education and information on reasonable modifications/accommodations are
provided to apartment managers and homeowners association by FHCOC.
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Discriminatory Advertising
FHCOC periodically monitors local newspapers and online media outlets to identify
potentially discriminatory housing advertisements.
Unfair Lending
Housing rehabilitation programs are marketed to low income households which include high
minority concentrations and limited English-speaking proficiency areas.
Zoning
Fountain Valley’s Zoning Code was updated in 2016 to treat transitional and supportive
housing as a residential use, subject to the same standards as other residential uses of the same
type in the same zone.
Density Bonus Incentives
Fountain Valley’s Zoning Code was updated in 2018 to continually remain consistent with
State density bonus law.
City of Fullerton
Addressing cost burden: To relieve the cost of rent, the City operates a rental assistance program
for seniors over 55. Programs have assisted seniors living in mobile homes (53 residents) and
seniors renting residential units (58 residents). The program was expanded to assist senior veterans
renting citywide.
New construction: Compass Ross Apartments provides 46 affordable units ranging from one to 3
bedrooms in the Richman Park area.
New construction: Ventana Apartments offers one and two-bedrooms units for low-income
seniors. The facility is central to dining, retail and local entertainment. Several amenities are
offered including a fitness center and social activities.
Addressing affordable homeownership: The City in collaboration with Habitat for Humanity will
provide 12 new housing units with affordability restrictions on the property.
Addressing accessibility: Fullerton Heights Apartments were developed with 24
affordable/accessible unit for special needs residence with mental disabilities. Units range from
one to three bedrooms. The units sit on top of 2,000 square feet of commercial use which is
proposed to provide services such as food/coffee that will be easily accessible to the residents. In
addition, the facility offers amenities such as laundry facilities, computer lab, and community areas
including a garden and large kitchen area that encourages socialization amongst the tenants and
their extended families. Accessibility to transit is within 1.2 miles offering bus and train service.
Addressing fair housing/discrimination: All developers and landlords of affordable housing
projects in the City are invited to workshops related to fair housing and must provide a Housing
Plan to the City. The Plan states that all applications will be reviewed without bias and all
25
applicants will be treated equally. In addition, Fair Housing flyers are provided in multiple
languages to the apartment sites.
General fair housing related literature and workshop advertisement was available at City Hall, the
Library, community centers, and community events. The lists below summarize accomplishments
from July 1, 2015 – January 31, 2020. The accomplishments are summarized as follows: 1) the
workshops provide by the Fair Housing Foundation and the number of participants at each
workshop, 2) the types of clients and the number of clients in each category (totaling 1,128
unduplicated individuals), and 3) the types of cases and the number of cases in each category.
WORKSHOPS
Fullerton Agency Meetings:
Fullerton Agencies: 3,737
Fullerton Mobile Home Tenant Meetings:
Rancho La Paz Community Meeting: 100 Fullerton residents
Workshops: Held at Fullerton Public Library
Tenant’s Rights Workshop: 44
Certificate Management Training: 70
Landlord Rights Workshop: 32
Tester Training: 6
City Staff Tenant Landlord Training: 20
Accommodations and Modifications 101 Workshop: 2
Walk-In Clinic: 13
Rental Counseling: 12
Fair Housing Workshop: 10
CLIENTS
In-Place Tenant: 904
Landlord/Management: 81
Other: 58
Property Owner: 61
Rental Home Seeker: 14
Community Organization: 5
Realtor: 5
CASES
Familial Status: 3
Mental Disability: 6
Physical Disability: 2
Race: 6
Age: 1
National Origin: 1
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LAND USE – City amended SB 2 Zone and Density Bonus Incentives
City of Garden Grove
Housing Discrimination
In partnership with the Fair Housing Foundation, the City conducted multi-faceted fair housing
outreach to tenants, landlords, property owners, realtors, and property management companies.
Methods of outreach included workshops, informational booths at community events,
presentations to community groups, staff trainings, and distribution of multi-lingual fair
housing literature.
Conducted focused outreach and education to small property owners/landlords on fair housing,
and race, reasonable accommodation and familial status issues in particular. Conducted
property manager trainings on a regular basis, targeting managers of smaller properties, and
promoted fair housing certificate training.
Provided general counseling and referrals to address tenant-landlord issues and provided
periodic tenant-landlord walk-in clinics at City Hall and other community locations.
Racial and Ethnic Segregation
Coordinated with the Fair Housing Foundation to focus fair housing services,
education/outreach, and/or additional testing in identified areas of racial/ethnic concentrations.
Offered a variety of housing opportunities to enhance mobility among residents of all races
and ethnicities. Facilitate the provision of affordable housing throughout the community
through: 1) available financial assistance; 2) flexible development standards; 3) density
bonuses; and 4) other zoning tools.
Promoted equal access to information on the availability of affordable housing by providing
information in multiple languages, and through methods that have proven successful in
outreaching to the community, particularly those hard-to-reach groups.
Affirmatively marketed first-time homebuyer and/or housing rehabilitation programs to low-
and moderate-income areas, and areas of racial/ethnic concentration.
Worked collaboratively with local housing authorities to ensure affirmative fair marketing
plans and de-concentration policies were implemented.
Reasonable Accommodations
In partnership with the Fair Housing Foundation, continued to provide fair housing education
and information to apartment managers and homeowner associations on why denial of
reasonable modifications/accommodations is unlawful.
Discriminatory Advertising
In partnership with the Fair Housing Foundation, periodically monitored local newspapers and
online media outlets to identify potentially discriminatory housing advertisements.
Took steps to encourage the Orange County Register to publish a Fair Housing Notice and a
"no pets" disclaimer that indicates rental housing owners must provide reasonable
accommodations, including "service animals" and "companion animals" for disabled persons.
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Hate Crimes
Continued to coordinate with various City and County housing, building and safety, health and
sanitation, law enforcement and legal aid offices to offer support services for victims of hate
crimes or other violent crimes – inclusive of housing resources.
Unfair Lending
In partnership with the Fair Housing Foundation, identified potential issues regarding
redlining, predatory lending and other illegal lending activities. In addition, the City reviewed
agreements annually to make sure that increased and comprehensive services are being
provided, and that education and outreach efforts are expanded and affirmatively marketed in
low and moderate income and racial concentrated areas.
Collaborated with local lenders and supported lenders’ efforts to work with community groups
to help minority households purchase their homes. Ensured that minority groups have access
and knowledge of City programs, supportive services, and provide for networking
opportunities with these groups.
Coordinated with local lenders to expand outreach efforts to first time homebuyers in minority
neighborhoods.
Affirmatively marketed first-time homebuyer and/or housing rehabilitation programs in
neighborhoods with high denial rates, high minority population concentrations and limited
English-speaking proficiency to help increase loan approval rates.
Housing for Persons with Disabilities
The City has adopted formal policies and procedures in the Municipal Code to reasonably
accommodate the housing needs of disabled residents.
Zoning Regulations
The City has an Accessory Dwelling Unit (ADU) ordinance that allows for the production in
all residential zones.
Single-Room Occupancy Housing: the City has specific provisions for SROs in our Zoning
Ordinances and has clarified in our Housing Elements how SROs are provided for under other
zoning classifications.
Transitional/Supportive Housing: the City has ordinances and development standards that
allow transitional and supportive housing in the manner prescribed by State law, regulated as
a residential use and subject to the same permitting and standards as similar residential uses of
the same type in the same zone.
Density Bonus Incentives
The City is amending the Zoning Code to reflect current State density bonus law.
City of Huntington Beach
Housing Discrimination
The City’s Code Enforcement staff provides fair housing information and referrals to tenants
in the field.
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Racial and Ethnic Segregation
The City’s Inclusionary Housing Ordinance allows for developers to be eligible for reduced
City fees if projects exceed the minimum (10%) inclusionary requirements on-site.
In early 2020, the City established an Affordable Housing Overlay within the Beach and
Edinger Corridors Specific Plan that allows for ministerial (by-right) project approval and
other development incentives for projects providing a minimum of 20% of the total units
affordable to lower income households on-site.
Since 2016, the City has approved four density bonus projects.
In fiscal year 2015/16, the City established a tenant based rental assistance program (TBRA);
program assistance includes security deposit and rental assistance paid directly to the landlord
as well as housing relocation and stabilization services, case managements, outreach, housing
search and placement, legal services, and financial management/credit repair.
Density Bonus Incentives
The City of Huntington Beach has not updated its zoning code to reflect current state regarding
density bonus. However, practically speaking, the City has implemented the state law
regarding density bonus.
Since 2016, the City has received four density bonus requests; all four projects were approved.
All four projects were reviewed for compliance with state density bonus law (including the
two that have not been incorporated into the City’s zoning code).
City of Irvine
Housing Discrimination
The City provided general housing services to address tenant‐landlord issues.
The City provided fair housing education services in Irvine, including informational booths at
community events, overview presentations to community-based organizations, resident
associations and government agencies and more detailed workshops tailored to specific
audiences such as housing consumers or housing providers.
The City and its fair housing provider, Fair Housing Foundation, investigated all allegations
of housing discrimination to determine if discrimination has occurred and continue advising
complainants of their rights and options under the law.
Discriminatory Advertising
The City monitored local newspapers and online media outlets periodically to identify
potentially discriminatory housing advertisements. When identified, contact the individual or
firm and provide fair housing education with the goal of eliminating this practice.
The City, through its fair housing provider, provided fair housing education services in Irvine,
including the Certificate Management Training Certificate Management training classes for
property owners, managers, management companies and real estate professionals.
Reasonable Accommodations
The City provided fair housing education workshops such as the “Accommodation and
Modification 101 Workshop” to Irvine housing providers on an annual basis.
The City provided access to Certificate Management classes for rental property owners and
managers from Irvine on an annual basis.
29
Hate Crimes
Continue to monitor FBI data to determine if there are actions that may be taken by the City
or its fair housing service provider to address potential discrimination linked to the bias
motivations of hate crimes.
Continue to coordinate with various City and County housing, building and safety, health and
sanitation, law enforcement and legal aid offices to maintain a comprehensive referral list of
support services for victims of hate crimes or other violent crimes – inclusive of housing
resources.
Unfair Lending
The City monitors Home Mortgage Disclosure Act data to determine if there are significant
shifts in the approval rates for applicants of different race or ethnicities from year to year.
The City provided/participated in homebuyer workshops in Irvine or the Orange County region
to educate potential homebuyers on their rights under the Fair Housing Act with respect to
lenders and fair lending practices.
City of Laguna Niguel
Fair Housing Education
FHCOC regionally conducted/participated in 10 education and outreach activities in Laguna
Niguel, reaching a culturally and ethnically diverse audience.
85 residents were made aware of fair housing laws and counseling services.
2 landlord and 3 tenant workshops on fair housing were held in Laguna Niguel.
4 workshops were conducted for consumers and providers in Laguna Nigel.
The FHCOC produced and provided written fair housing related materials in English, Spanish
and Vietnamese to the City of Laguna Niguel.
Fair Housing Enforcement
FHOC staff received 10 allegations of housing discrimination and opened 3 cases involving
Laguna Niguel. FHCOC also conducted 18 paired, on-site, systemic tests for discriminatory
rental housing practices in Laguna Niguel.
Housing Dispute Evaluation & Resolution –FHOC assisted 367 unduplicated households
involving 1,151 issues from Laguna Niguel.
Reasonable Accommodations
3 inquiries regarding reasonable accommodations and modifications were received by FHCOC
that resulted in casework beyond basic counseling.
Web-based Outreach
FHCOC’s multi-language website currently has an on-line housing discrimination complaint-
reporting tool that generates an email to FHCOC. It is also used for other, non-discrimination,
housing-related issues. The City of Laguna Niguel has a link to the FHCOC website where
residents can access this information.
30
Discriminatory Advertising
Orange County rentals listed on Craigslist were monitored by FHCOC for discriminatory
content (as permitted by staffing limitations). Discriminatory advertisements were flagged and
FHCOC responded to these ads in order to inform the poster of possible discriminatory content.
FHCOC also brought these ads to the attention of Craigslist via abuse@craigslist.org, or in
some cases, the ad was referred to FHCOC’s investigators for possible enforcement action.
Other on-line rental sites (e.g., OC Register, LA Times) were sporadically monitored; however,
the lack of a text search function made monitoring of other sites less efficient. Without
exception, identified problematic postings indicated restrictions with regard to children under
the age of 18 or improper preference for seniors or ‘older adults’ for housing opportunities that
did not appear qualify as housing for older persons (age 55 and over).
City of La Habra
Housing Discrimination
La Habra worked with the Fair Housing Foundation (FHF) and previously worked with Fair
Housing Council of Orange County to provide education and outreach activities, trainings to
owners and managers, general counseling and referrals, and tenant-landlord walk-in clinics.
Racial and Ethnic Segregation
La Habra has a grant/loan program available for low-income residents to receive assistance in
the rehabilitation of owner-occupied properties.
La Habra’s Zone Codes allow for use of density bonus in order to encourage developers to
include units with restricted rents or reduced sales prices for low and moderate-income
households.
La Habra along with the Fair Housing Council of Orange County (2015) and the Fair Housing
Foundation (2016-current) provides information in both English and Spanish. La Habra also
provides bilingual pay to employees that speak other non-English languages. Finally, La Habra
has a contract with Links Sign Language & Interpreting Service to provide translation service
for languages in which bilingual staff cannot provide in house including American Sign
Language.
La Habra participates in the Cities Advisory Committee hosted by Orange County Housing
Authority to discuss housing issues and housing choice vouchers within the County.
Although La Habra does not have a down payment assistance program, residents are referred
to NeighborWorks of Orange County for down payment assistance.
La Habra also hosted a homebuyer education workshop with NeighborWorks of Orange
County to provide education and training to first-time homebuyers, lenders and realtors. These
workshops are marketed to areas of racial/ethnic concentrations within La Habra.
Reasonable Accommodations
La Habra worked with Fair Housing Council of Orange County and now the Fair Housing
Foundation to conduct seminars on reasonable accommodation. n=during Fiscal Year 2015 to
provide these services. During Fiscal Year 2016 until current, Fair Housing Foundation
provides these services for La Habra.
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Discriminatory Advertising
La Habra worked with both Fair Housing Council of Orange County and the Fair Housing
Foundation to monitor local newspapers and online media outlets to identify potentially
discriminatory housing advertisements.
Unfair Lending
La Habra worked with NeighborWorks of Orange County to market first-time homebuyers
counseling and other programs. NeighborWorks also provides lender trainings so that lenders
make loans available to minorities and limited English-speaking persons.
Density Bonus Incentives
La Habra’s Density Bonus Ordinance was updated in 2010, and per City Attorney, the City’s
Ordinance remains consistent with State density bonus law.
City of Lake Forest
Fair Housing Education
FHCOC conducted/participated in 78 education and outreach activities. Individuals were made
aware of fair housing laws and services
3 landlord and 5 tenant workshops on fair housing were held in Lake Forest.
Fair Housing Enforcement
FHCOC received 11 allegations of housing discrimination and opened 4 cases involved Lake
Forest. FHCOC also conducted 18 paired, on-site, systemic tests for discriminatory rental
housing practices in Lake Forest.
Housing Dispute Evaluation & Resolution –FHCOC assisted 314 unduplicated households
addressed 983 issues from Lake Forest.
Reasonable Accommodations
1 inquiry regarding reasonable accommodations and modifications was received by FHCOC.
4 landlord & 6 tenant fair housing workshops were held in Lake Forest. Topics covered
included information regarding reasonable modifications/accommodations.
Web-based Outreach
FHCOC’s multi-language website has an online housing discrimination complaint-reporting
tool. The City has a link to the FHCOC website where residents can access this information.
Monitoring Advertising
A limited number of Orange County rentals listed on Craigslist were monitored by FHCOC.
Discriminatory ads were flagged and FHCOC informed the poster of possible discriminatory
content. FHCOC also brought ads to the attention of Craigslist or referred the ad to FHCOC’s
investigators for possible action. Other on-line sites (OC Register, LA Times) were
sporadically monitored. Problematic postings indicated restrictions regarding children under
the age of 18 or improper preference for seniors for housing that did not appear qualified as
housing for persons age 55 and over.
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Unfair Lending
Monitor Home Mortgage Disclosure Act Data – analysis of 2008 HMDA data was included in
the 2010-2015 Regional AI. Although subsequent data was available, lack of resources
prevented FHCOC from updating the analysis. Analyses of HMDA data from 2008 to 2013,
and other mortgage lending practices, were included in the 2016 Multi-Jurisdictional AI, in
which Lake Forest was a participant.
Racial and Ethnic Segregation
FHCOC produced and disseminated written fair housing related materials in English, Spanish
and Vietnamese to the City of Lake Forest. Materials were placed in public areas of City Hall.
FHCOC also took specific outreach efforts to immigrant populations in low-income
neighborhoods.
Under its Fair Housing Initiatives Program grant, FHCOC targeted fair housing services to the
disabled, minority groups, and limited English proficiency immigrants.
Through its foreclosure prevention activities FHCOC assisted individuals with limited English
proficiency.
City of Mission Viejo
During the report period the City took the following actions in an effort to overcome the
impediments to fair housing choice identified in the AI:
The City’s website provides links to the City’s fair housing provider.
The City continued to collaborate with the Fair Housing Foundation (FHF) to ensure
comprehensive fair housing outreach is carried out in the community and to affirmatively
market services:
o Fair housing services was provided to 292 Mission Viejo households dealing with general
housing issues and allegations of discrimination.
o 10 housing discrimination inquiries were received by the FHF. 4 inquires alleged
discrimination based on a physical disability, 1 based on a mental disability, 1 based on
race, 3 based on national origin, and 1 based on gender discrimination. 8 cases were
counseled and resolved, but 2 cases were opened. Upon further investigation, 2 case were
closed due to a lack of evidence. With respect to general housing issues addressed by the
FHF, the majority of housing issues related rights and responsibilities, notices, and
habitability issues.
o The City worked closely with the FHF to provide certified fair housing training for housing
industry realtors and property managers – 6 workshops were conducted during the report
period. Additionally, 10 tenant and 10 landlord workshops were conducted in Mission
Viejo. Additionally, four Fair Housing Walk-in Clinics were held in the City during the
report period. Literature related to fair housing were distributed at these events, at City
Hall, community centers, and community events. Literature was provided to the
community in English and Spanish.
o Due to the loss of significant revenue (e.g., redevelopment) and continued reductions in
HUD funding, the City did not have the opportunity to collaborate with local lenders to
target marketing efforts and services in Low- and Moderate-Income areas of the City.
33
o The consultant preparing the updated multi-jurisdictional AI provided technical assistance
to cities that had identified public sector impediments such as:
Family definition inconsistent with fair housing laws;
Lack of a definition of disability;
Lack of a reasonable accommodation procedure;
Lack of zoning regulations for special needs housing;
Lack of a fair housing discussion in zoning and planning documents.
City of Orange
Housing Discrimination
During FY 2015-19, the Fair Housing Foundation (FHF) conducted multi-faceted fair
housing outreach activities within the City of Orange to provide fair housing education to
tenants, landlords, rental property owners, realtors, and property management companies.
Each activity was promoted utilizing multiple marketing channels including social media,
event flyer distribution, and press releases with the local cable channel. Activities included:
o Conducted 8 Tenant Workshops (2-Hours each) to 20 attendees total.
o Conducted 8 Landlord Workshops (2-Hours each) to 43 attendees total.
o Staffed 10 Community Event Informational Booths (8-Hours total) making fair housing
information available to 2,820 attendees at the 2015 Friendly Center Health and Resource
Fair, 2016 Friendly Center Resource Fair, 2016 25th Anniversary Health Fair, 2016
Orange Senior Wellness Fair, 2017 Rideshare & Health Fair, 2017 Health and Wellness
Fair, 2017 Friendly Center Community Resource Fair, 2018 CalOptima's Community
Resource Fair, 2018 City of Orange Rideshare & Health Fair, and 2019 CalOptima
Community Resource Fair.
o Conducted 29 FHF 101 presentations to civic leaders and community organizations
including the Heart to Heart Collaborative, West Orange Elementary English Learner
Advisory Committee Meeting, Office of Assembly member Tom Daly, Friendly Center,
CDBG Program Committee, Women’s Transitional Living Center OC Senior Roundtable
Networking Group, Fristers, OC Adult Protective Services, Vietnamese American
Human Services Network, Heart to Heart, Patriots and Paws, Realtors Group, Orange
Children & Parents Together (OCPT), Planned Parenthood, El Modena Family Resource
Center, Santiago Canyon College - Student Services, Youth Centers of Orange, Orange
Code Enforcement, Rehabilitation Institute of So Cal, Mariposa Center, and OCPT Head
Start. There was a total of 457 attendees.
o Distributed 26,094 pieces of Fair Housing Literature in English, Spanish, and
Vietnamese during outreach activities and mass mailings.
To promote education opportunities to rental housing providers, FHF conducted focused
outreach efforts such as mailings, presentations, and trainings to 608 small property
owners/landlords, and 203 Property Management Companies in the City of Orange
promoting our fair housing certificate training. Thus, FHF conducted 9 Certificate
Management Trainings (4 Hours each) to 65 attendees, all successfully passing the post Fair
Housing Exam.
FHF provided ongoing Landlord/Tenant Counseling, Mediation, and Assistance to 894
Households resulting in 1334 Landlord/Tenant Issues.
34
FHF counseled and screened 79 households for potential fair housing violations,. These
included allegations of housing discrimination based on Disability-48, Race-19, Familial
Status -5, Age – 2, Arbitrary – 1, National Origin – 2, and Gender -2. FHF opened 26
Bonafide Fair Housing Cases based on: Arbitrary – 1, Disability -8, Gender -1, Familial
Status-3, National Origin -1, and Race-12. FHF conducted 17 Onsite Tests, 207 Property
Surveys, collected 52 Witness Statements, 315 documents, and 71 photos. Of these cases, 8
Sustained Allegations were successfully conciliated, 4 Inconclusive cases were provide
educational information and provided additional options to the client, such as filing with
DFEH or small claims, 14 No Evidence cases were provided educational information and
provided additional options to the client, such as filing with DFEH or small claims.
County of Orange
During the 2015-19 reporting period the County of Orange Urban County Jurisdiction took the
following actions (on its own or in cooperation with regional partners and the Fair Housing Council
of Orange County (FHCOC)) to overcome impediments to fair housing choice identified in the
regional AI:
Fair Housing Community Education – During 2015-19, the FHCOC regionally conducted or
participated in 467 education and/or outreach activities. Regionally, over 9,550 people were served
by these activities. Through its various regional outreach efforts FHCOC distributed over 82,130
pieces of literature on fair housing, its services and other housing-related topics. Additionally,
throughout Orange County FHCOC held 32 training sessions for rental property owners/managers.
FHCOC presented 16 fair housing seminars, 70 general fair housing workshops.
Fair Housing Enforcement – On a regional basis, FHCOC staff received 363 allegations of housing
discrimination and opened 179 cases where the allegations seemed sufficiently meritorious to
warrant further investigation and/or action. FHCOC also conducted 362 systemic onsite tests,
either paired or ‘sandwich’, 51 tests occurring in the jurisdiction and 215 other testing activities.
Housing Dispute Evaluation & Resolution – On a regional basis, activities provided by FHCOC
included assisting 7,664 unduplicated households addressing 24,766 issues, disputes and/or
inquires.
City of Rancho Santa Margarita
Fair Housing Outreach and Education
FHCOC held one education and outreach activity in Rancho Santa Margarita (RSM), reaching
a culturally and ethnically diverse audience.
Fair Housing Enforcement
FHCOC staff received 6 allegations of housing discrimination and opened 4 cases involved
housing in RSM. FHCOC also conducted 6 paired, on-site, systemic tests for discriminatory
rental housing practices in RSM.
35
Housing Dispute Evaluation & Resolution
Services provided by FHCOC included assisting approximately 188 unduplicated Rancho
Santa Margarita households.
Racial and Ethnic Segregation
Literature regarding fair housing was distributed in English, Spanish & Vietnamese.
FHCOC’s website has an online housing discrimination complaint reporting tool that generates
an email to FHCOC. It is also used for other, non-discrimination, housing-related issues. RSM
has a link to the FHCOC website where residents can access this information.
The City does not offer homebuyer assistance programs. Housing rehabilitation programs are
advertised citywide.
City attended quarterly meetings the OCHA to discuss a variety of housing issues and assisted
housing policies – FHCOC staff also attends quarterly meetings.
Reasonable Accommodations
On a regional basis, 53 inquiries regarding reasonable accommodations and modifications
were received by FHCOC that resulted in casework beyond basic counseling, including 1 from
RSM. 8 households received accommodations. FHCOC assisted those denied an
accommodation by filing an administrative housing discrimination complaint with the HUD
Fair Housing and Equal Opportunity. None of these cases involved RSM residents or
properties.
1 fair housing workshop was held in RSM. Topics covered included information regarding
reasonable modifications/accommodations.
Web-based Outreach
FHCOC’s multi-language website currently has an on-line housing discrimination complaint-
reporting tool that generates an email to FHCOC. The City of Rancho Santa Margarita has a
link to the FHCOC website where residents can access this information.
Monitoring On-line Advertising
As permitted by staffing limitations, Orange County rentals listed on Craigslist were monitored
by FHCOC for discriminatory content. Discriminatory advertisements were flagged and
brought to the attention of Craigslist. Some ads were referred to FHCOC’s investigators for
possible enforcement action. Other on-line rental sites (e.g., OC Register, LA Times) were
intermittently monitored. Without exception, problematic postings indicated restrictions
regarding children under the age of 18 or improper preference for ‘older adults’ for housing
opportunities that did not appear qualify as housing for individuals age 55 plus.
Unfair Lending
FHCOC reports that ongoing monitoring of Home Mortgage Disclosure Act (HMDA) data
continues to be infeasible due to limited resources. Analysis of updated HMDA data from 2008
to 2013, as well as other mortgage lending practices, was included part of the 16 Orange
County Cities Regional Analysis of Impediments to Fair Housing Choice (2015), in which the
City of RSM was a participant.
36
Presently, the City of RSM does not offer homebuyer assistance programs; however, program
staff provides referrals to the Orange County Affordable Housing Clearinghouse and
NeighborWorks Orange County.
FHCOC continued efforts to promote housing affordability within Orange County. It provided
services and outreach to organizations involved in the creation and preservation of affordable
housing. These groups included the Kennedy Commission, Mental Health Association of
Orange County, AIDS Services Foundation, Affordable Housing Clearinghouse, Jamboree
Housing Corporation, Orange County Congregations Community Organizations, and Orange
County Community Housing Corporation.
Density Bonus Incentives
City Planning staff has confirmed that current zoning code is consistent with current State
density bonus law.
City of San Clemente
Housing Discrimination
The Fair Housing Foundation (FHF) provided fair housing services to 261 San Clemente
households, most of whom were Hispanic. Issues included housing discrimination, notices
received, habitability issues, security deposit disputes, and lease terms.
5 housing discrimination inquiries were received and investigated, 4 related to physical or
mental disability discrimination and 1 related to marital status. 2 were resolved, 2 cases were
opened and then resolved.
FHF provided 4 property management trainings, 4 landlord trainings, 3 tenant workshops, and
4 walk-in clinics.
FHF participated in 11 community events.
Racial and Ethnic Segregation
FHF provided fair housing literature in both English and Spanish.
PSAs were aired on the City’s cable station.
Participated in quarterly OCHA (PHA) Housing Advisory Committee meetings.
Reasonable Accommodations
FHF conducted 3 landlord and 3 certified property managers trainings.
City of Santa Ana
Housing Discrimination
In partnership with the Orange County Fair Housing Council, Inc., the City conducted multi-
faceted fair housing outreach to tenants, landlords, property owners, realtors, and property
management companies on an annual basis. Methods of outreach included workshops,
informational booths, presentations to civic leaders and community groups, staff trainings, and
distribution of multi-lingual fair housing literature.
o The City contracted with the Orange County Fair Housing Council for up to $60,000 per
year from 2015-2019 to conduct this outreach. The funds came from the City’s
administrative funds for the implementation of the CDBG Program.
37
The City conducted focused outreach to small property owners/ landlords; conducted property
manager trainings on an annual basis and promoted fair housing certificate training.
o The City held an annual property manager training in February or March of each year.
o The City sent information on fair housing to property owners and managers who participate
in the Housing Choice Voucher Program.
o In August of each year, the City provided an annual mandatory training on fair housing for
all employees in the City’s Housing Division in partnership with the Orange County Fair
Housing Council.
The City provided tenant counseling and referrals to address specific tenant-landlord issues.
o Fair Housing programs and resources were included in all voucher issuance briefings and
reasonable accommodation tracking logs updated. Communication was maintained with
the Orange County Fair Housing Council, Public Law Center, and Legal Aid, to ensure
proper referrals for anyone alleging discrimination.
o A new DVD on Fair Housing was implemented for all voucher issuance meetings.
Racial and Ethnic Segregation
The City coordinated with the Orange County Fair Housing Council to focus fair housing
services, education/outreach, and additional testing in areas of racial/ethnic concentrations.
o In addition to its fair housing services funded by the City, the Orange County Fair Housing
Council, engaged in additional work to affirmatively further fair housing through its HUD
Fair Housing Initiative Program (FHIP) enforcement and education and outreach grants.
o The City provided an annual mandatory training on fair housing for all employees in the
City’s Housing Division in partnership with the Orange County Fair Housing Council.
The City offered a variety of housing opportunities to enhance mobility among residents of all
races and ethnicities. The City facilitated the p rovision of affordable housing throughout the
community through: 1) the provision of financial assistance; 2) approving flexible
development standards; 3) approving density bonuses; and 4) other zoning tools.
o In regards to the provision of financial assistance, the City provided rental assistance
through the Housing Choice Voucher Program. Specifically:
The City administered over $30 million per year in funding from HUD for the Housing
Choice Voucher Program. The City also administered additional funding and vouchers
as discussed below.
In FY 2018, SAHA received an award of 75 HUD-Veterans Affairs Supportive
Housing Project-Based Vouchers (HUD-VASH PBVs) under PIH Notice 2016-11.
Following the award, SAHA issued an RFP and awarded the 75 HUD-VASH PBVs to
Jamboree Housing for the development of Santa Ana Veterans Village. The Santa Ana
Veterans Village is the development of 75 permanent supportive housing units in the
City of Santa Ana for homeless veterans. The project includes an investment of 75
HUD-Veterans Affairs Supportive Housing (VASH) Project-Based Vouchers from the
Santa Ana Housing Authority and $477,345 in HOME Investment Partnerships
Program funds. The 62,248 square foot development will provide 70 one-bedroom
units and 6 two-bedroom units (of which one will be a manager’s unit) serving HUD-
VASH eligible residents earning at or below 30% of the Area Median Income. All
residents will receive wrap-around supportive services from the Department of
Veterans Affairs and Step Up on Second as the service provider. Following the
38
execution of the PBV HAP Contract with Jamboree for this project, the Annual
Contributions Contract for SAHA was increased from 2,699 to 2,774.
On October 9, 2017, SAHA submitted a Registration of Interest for one hundred (100)
HUD-VASH vouchers in response to PIH Notice 2017-17. In FY 2019, SAHA,
received an award of 100 HUD-Veterans Affairs Supportive Housing Project-Based
Vouchers (HUD-VASH PBVs) under PIH Notice 2017-17 and an additional award of
105 HUD-VASH tenant-based vouchers under PIH Notice 2018-07. Following the
award of HUD-VASH PBVs under PIH Notice 2017-17, SAHA issued an RFP and
committed the 100 HUD-VASH PBVs to three affordable housing projects including:
8 HUD-VASH PBVs committed to National CORE for the development of the Legacy
Square project which will include 93 total units of which 33 will be permanent
supportive housing; 3 HUD-VASH PBVs committed to HomeAid Orange County for
the development of the FX Residences project which will include 11 units of permanent
supportive housing; and 89 HUD-VASH PBVs committed to Jamboree Housing for
the rehabilitation of the North Harbor Village project to create 89 permanent supportive
housing units for qualified and eligible homeless veterans. In September 2018, SAHA
also received an award of 50 Mainstream Vouchers following a competitive application
process under 2017 Mainstream Voucher Program NOFA FR-6100-N-43.
In November 2019, SAHA received an additional award of seventy (70) Mainstream
Vouchers following a competitive application process under the Mainstream Voucher
Program NOFA FR-6300-N-43. In November 2019, SAHA also received an award of
twenty-five (25) Foster Youth to Independence Tenant-Protection Vouchers following
a competitive application process under Notice PIH 2019 -20.
o In regards to financial assistance, flexible development standards, density bonuses; and
other zoning tools, the City approved various forms of financial assistance (Housing
Successor Agency, CDBG, HOME, Project-Based Vouchers, Inclusionary Housing Funds)
and variances to development standards and density bonus agreements for affordable
housing projects.
In addition, the City also approved a Density Bonus Agreement for each of the following
affordable housing projects:
o Villa Court Senior Apartments – a 418-unit affordable rental project at 2222 East First
Street.
o First Point I and II - a 552-unit affordable rental project at 2110, 2114, and 2020 East First
Street
o First American – a 220-unit residential project which will include 11 affordable units at
114 and 117 East Fifth Street.
o A Density Bonus Agreement was also approved for the Legacy Square project mentioned
above – a 92-unit affordable rental project at 609 North Spurgeon Street.
The City promoted equal access to information on the availability of affordable housing by
providing information in multiple languages, and through methods that have proven successful
in outreaching to the community, particularly those hard-to-reach groups.
o The City provided this information in the office, on it’s website and in informational
materials provided to residents.
The City affirmatively marketed first-time homebuyer and/or housing rehabilitation programs
to low- and moderate-income areas, and areas of racial/ethnic concentration.
39
o The City held a first-time homebuyer workshop on a quarterly basis and promoted the
information widely to all residents in the City.
The City worked collaboratively with local housing authorities to ensure affirmative fair
marketing plans and de-concentration policies are implemented.
o The City convened a quarterly meeting of local housing authorities to discuss efforts and
initiatives to reduce homelessness.
Reasonable Accommodations
Through the Orange County Fair Housing Council, Inc., the City continued to provide fair
housing education and information to apartment managers and homeowner associations on
why denial of necessary reasonable modifications/accommodations is unlawful.
o The City held an annual property manager training in February or March of each year.
o The City sent information on fair housing to property owners and managers who participate
in the Housing Choice Voucher Program.
o The City provided an annual mandatory training on fair housing for all employees in the
City’s Housing Division in partnership with the Orange County Fair Housing Council.
o Through its HUD Fair Housing Initiative Program (FHIP) grant Orange County Fair
Housing Council actively assists disabled persons in requesting and obtaining reasonable
accommodations or modifications.
Discriminatory Advertising
Through a contract with the Orange County Fair Housing Council, the City periodically
monitored local print publications and online platforms to identify potentially discriminatory
housing advertisements. When identified, the Orange County Fair Housing Council contacted
the individual or firm and provided fair housing education or took appropriate enforcement
action.
Hate Crimes
The City monitored FBI data to determine if any hate crimes are housing-related and if there
are actions that may be taken by the City. The Orange County Fair Housing Council was
available to address any possible issues of housing discrimination linked to the bias
motivations of hate crimes.
The City coordinated with various City and County housing, building and safety, health and
sanitation, law enforcement and legal aid offices to maintain a comprehensive referral list of
support services for victims of hate crimes or other violent crimes –inclusive of housing
resources.
o For FY 2016, the Santa Ana Housing Authority (SAHA):
Updated the definition of the Violence Against Women Act to include sexual assault.
Coordinated with the County of Orange Domestic Violence office for referrals and to
ensure applicants and participants are informed on all available services.
Provided information on VAWA in regards to owner/tenant responsibilities and
evictions to all program applicants and participants and also mailed to all owners.
SAHA’s HCV Administrative Plan details restrictions on terminating assistance for
victims of domestic violence, as well as guidelines on terminating assistance for
perpetrators of domestic violence.
SAHA discussed VAWA with staff at least once annually.
40
o For FY 2017, FY 2018, FY 2019, and FY 2020, SAHA:
In accordance with the Violence against Women Reauthorization Act of 2013 (VAWA
2013), SAHA implemented an Emergency Transfer Plan for Victims of Domestic
Violence, Dating Violence, Sexual Assault, or Stalking.
Implemented HUD-5380, Notice of Occupancy Rights under the Violence Against
Women Act, HUD-5382, Certification of Domestic Violence, Dating Violence, Sexual
Assault, or Stalking, and Alternate Documentation, and HUD-5383, Emergency
Transfer Request for Certain Victims of Domestic Violence, Dating Violence, Sexual
Assault, or Stalking.
Coordinated with the County of Orange Domestic Violence office for referrals and to
ensure applicants and participants are informed on all available services.
Provided information on VAWA in regards to owner/tenant responsibilities and
evictions to all program applicants and participants; e-mailed the information to all
owners.
SAHA trained staff on VAWA at least once annually. Staff also proactively provided
information on VAWA to any program participant or applicant who may show any
evidence that information on VAWA is needed.
Unfair Lending
As resources permitted, the City monitored HMDA data annually using the 2013 HMDA
analysis as a benchmark.
The City, through its contract with the Orange County Fair Housing Council, had access to
resources to identify and/or address any potential issues regarding redlining, predatory lending
and other illegal lending activities. Through HUD-funded enforcement activities, Orange
County Fair Housing Council has engaged in regional paired pre-application testing to uncover
possibly discriminatory mortgage lending practices. In addition, the city reviewed their
agreements annually to make sure that increased and comprehensive services are being
provided, and that education and outreach efforts are expanded and affirmatively marketed in
low and moderate income and racial concentrated areas.
The City ensured that minority groups have access and knowledge of City programs,
supportive services by providing information as widely as possible to the community in
multiple languages.
The City coordinate with local lenders to expand outreach efforts to first time homebuyers in
minority neighborhoods by providing quarterly workshops to first time homebuyers in
partnership with NeighborWorks Orange County.
The City affirmatively marketed first-time homebuyer and/or housing rehabilitation programs
in neighborhoods with high denial rates, high minority population concentrations and limited
English-speaking proficiency to help increase loan approval rates by providing quarterly
workshops to first time homebuyers in partnership with NeighborWorks Orange County and
providing information as widely as possible to the community in multiple languages.
Zoning Codes
The City complied with current State density bonus law even though the municipal code was
not updated to reflect current State law for the following projects:
o Villa Court Senior Apartments, 418-unit affordable rental project.
o First Point I and II, a 552-unit affordable rental project.
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o First American , a 220-unit residential project with 11 affordable units.
o Legacy Square, a 92-unit affordable rental project.
City of Tustin
Housing Discrimination
Although the 2015-2020 AI documentation refers to the Fair Housing Council of OC to provide
fair housing assistance, the City of Tustin contracts with the Fair Housing Foundation to
provide such services. During the 2018-2019 Fiscal Year, the Fair Housing Foundation assisted
the City of Tustin with combatting housing discrimination through managing twelve (12)
allegation cases and one (1) discrimination case for Tustin residents, providing services to
those individuals throughout the case management process. They also provided ample fair
housing education and outreach to further prevent discrimination, assisting 127 Tustin
landlords/tenants who were provided with either landlord/tenant counseling, mediation, UD
assistance, and/or referral services during the last fiscal year. Overall, the Fair Housing
Foundation’s outreach efforts assisted 672 individuals within City of Tustin limits during the
2018-2019 Fiscal Year.
Discriminatory Advertising
The City of Tustin partners with the Fair Housing Foundation to address issues such as
discriminatory advertising. As allowed by resources, FHF reviews advertising for Orange
County rentals and Los Angeles County rentals listed in media such as The Orange County
Register, La Opinion, Los Angeles Sentinel, local weekly newspapers, Craigslist and The
Penny Saver for discriminatory content. Potential discriminatory advertisements were referred
for further investigation and possible enforcement action.
Reasonable Accommodations
Similarly, the City of Tustin has actively contracted and engaged with the Fair Housing
Foundation to provide educational services to owners and managers of apartment complexes
on why this practice is unlawful. The Fair Housing Foundation partners with a wide variety of
agencies, notably the Tustin Effective Apartment Managers (TEAM) group to provide
resources and services directed to affirmatively furthering fair housing. The Fair Housing
Foundation has also implemented the “Accommodation & Modification 101 Workshop” to
continue strengthening the bonds between the Fair Housing Foundation and housing providers,
and to continue to provide education on their fair housing rights. The housing providers who
attended this workshop stated that they had a better understanding and a greater sense of
knowledge and confidence in knowing the difference in identifying a reasonable an
unreasonable accommodation or modification request. As a result of this workshop, housing
providers have a better understanding of their responsibilities and disabled residents or rental
home seekers will most likely benefit from having requests reviewed and evaluated in a fair
manner.
Hate Crimes
The Fair Housing Foundation has not received notification of any hate crimes within the City
of Tustin during the recent reporting period. When the Fair Housing Foundation is contacted
by a victim of a hate crime occurring at their place of residence, the Fair Housing Foundation
42
refers them to the O.C. Human Relations Commission, and assists with their fair housing
complaint. The Fair Housing Foundation assists by counseling, completing an intake, opening
a case, and investigating the allegation(s).
Unfair Lending
As part of its outreach efforts the Fair Housing Foundation informs individuals and
organizations of its services, which include housing counseling for individuals seeking to
become read y for a home purchase. The Fair Housing Foundation participates in numerous
education and/or outreach activities, reaching a culturally and ethnically diverse audience, in
Cities of Costa Mesa, Mission Viejo, San Clemente, and Tustin) which they inform participants
of fair housing laws and of their counseling services
City of Westminster
Education and Outreach Activities
Progress: The Fair Housing Foundation (FHF) provided a comprehensive, extensive and viable
education and outreach program. The purpose of this program was to educate managers,
tenants, landlords, owners, realtors and property management companies on fair housing laws,
to promote media and consumer interest, and to secure grass roots involvement within the
communities. FHF specifically aimed its outreach to persons and protected classes that are
most likely to encounter housing discrimination.
The FHF developed new, dynamic, and more effective approaches to bringing fair housing
information to residents; including brochures that focused on specific fair housing issues,
including discrimination against people with disabilities, discrimination based on national
origin, sexual orientation, discrimination against families with children, and sexual
harassment. All of FHF’s announcements and literature was available in various languages.
Reasonable Accommodations – On a regional basis, 52 inquiries regarding reasonable
accommodations and modifications were received by FHCOC that resulted in casework beyond
basic counseling.
Web-based Outreach - FHCOC’s website currently has an on-line housing discrimination
complaint-reporting tool that generates an email to FHCOC.
Monitoring On-line Advertising – Orange County rentals listed on Craigslist were monitored by
FHCOC for discriminatory content (as permitted by staffing limitations). Discriminatory
advertisements were flagged and FHCOC responded to these ads in order to inform the poster of
possible discriminatory content.
Monitor Home Mortgage Disclosure Act Data - Ongoing monitoring of Home Mortgage
Disclosure Act (HMDA) data continues to be infeasible due to limited resources at
FHCOC. During 2015-19, FHCOC continued efforts to promote housing affordability within
Orange County. These groups included the Kenned y Commission, Mental Health Association of
Orange County, Aids Services Foundation, Affordable Housing Clearinghouse, Jamboree Housing
Corporation, Orange County Community Housing Corporation, Innovative Housing
Opportunities, and Orange County Congregations Community Organizations, among others.
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V. FAIR HOUSING ANALYSIS
A. Demographic Summary
This Demographic Summary provides an overview of data concerning race and ethnicity, sex, familial
status, disability status, limited English proficiency, national origin, and age. The data included reflects the
composition of the Los Angeles-Long Beach-Anaheim Region, Orange County itself, and thirty-four
jurisdictions within it.
1. Describe demographic patterns in the jurisdiction and region, and describe trends over time (since
1990).
Orange County is located in Southern California, just south of Los Angeles, with some of the county
touching the Pacific Ocean. The county has a plurality white population, with sizable Hispanic and Asian
populations.
Table 1.1: Demographics, Orange County
(Orange County, CA CDBG, ESG)
Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 1,306,398 41.40% 4,056,820 31.62%
Black, Non-Hispanic 49,560 1.57% 859,086 6.70%
Hispanic 1,079,172 34.20% 5,700,860 44.44%
Asian/Pacific Is., Non-
Hispanic 624,373 19.78% 1,888,969 14.72%
Native American, Non-Hisp. 6,584 0.21% 25,102 0.20%
Two+ Races, Non-Hispanic 15,367 2.71% 267,038 2.08%
Other, Non-Hispanic 1,174 0.21% 30,960 0.24%
#1 country of origin Mexico 345,637 11.21% Mexico 1,735,902 14.34%
#2 country of origin Vietnam 146,672 4.75% Philippines 288,529 2.38%
#3 country of origin Korea 65,579 2.13% El Salvador 279,381 2.31%
#4 country of origin Philippines 53,707 1.74% Vietnam 234,251 1.93%
#5 country of origin
China excl.
Hong Kong
& Taiwan 33,226 1.01% Korea 224,370 1.85%
#6 country of origin India 31,063 1.01% Guatemala 188,854 1.56%
#7 country of origin Iran 27,718 1.01%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin Taiwan 22,918 0.90% Iran 133,596 1.10%
#9 country of origin El Salvador 17,785 0.58% Taiwan 87,643 0.72%
#10 country of origin Canada 14,179 0.46% India 79,608 0.66%
#1 LEP Language Spanish 30,862 5.69% Spanish 2,033,088 16.79%
#2 LEP Language Korean 9,810 1.81% Chinese 239,576 1.98%
#3 LEP Language Vietnamese 9,411 1.73% Korean 156,343 1.29%
#4 LEP Language Chinese 5,868 1.08% Vietnamese 147,472 1.22%
#5 LEP Language Persian 2,230 0.41% Armenian 87,201 0.72%
#6 LEP Language Tagalog 2,146 0.40% Tagalog 86,691 0.72%
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#7 LEP Language Japanese 1,167 0.22% Persian 41,051 0.34%
#8 LEP Language Arabic 1,054 0.19% Japanese 32,457 0.27%
#9 LEP Language Urdu 644 0.12% Russian 28,358 0.23%
#10 LEP Language Russian 587 0.11% Arabic 23,275 0.19%
Hearing difficulty 81,297 2.59% 81,297 2.59%
Vision difficulty 51,196 1.63% 51,196 1.63%
Cognitive difficulty 99,317 3.16% 99,317 3.16%
Ambulatory difficulty 133,232 4.24% 133,232 4.24%
Self-care difficulty 61,615 1.96% 61,615 1.96%
Independent living difficulty 104,705 3.34% 104,705 3.34%
Male 274,258 48.38% 6,328,434 49.33%
Female 292,676 51.62% 6,500,403 50.67%
Under 18 132,454 23.36% 3,138,867 24.47%
18-64 349,144 61.58% 8,274,594 64.50%
65+ 85,336 15.05% 1,415,376 11.03%
Families with children 65,179 44.98% 1,388,564 47.84%
Race and Ethnicity
Orange County has a plurality non-Hispanic White population (41.40%), with large populations of
Hispanics (34.20%) and non-Hispanic Asians (19.78%). Black residents comprise only 1.57% of the
population, and the non-Hispanic Native American population is 0.21%. The percentage of multi-race non-
Hispanic population is 2.71%, and the other non-Hispanic population is 0.21%.
National Origin
The most common country of origin within the County is Mexico, with 11.21% of the county population
comprised of residents from Mexico. The remaining most countries of origin are, in order, Vietnam, Korea,
Philippines, China excluding Hong Kong & Taiwan, India, Iran, Taiwan, El Salvador, and Canada.
Limited English Proficiency
The most commonly spoken language for those in the County with Limited English Proficiency (LEP) is
Spanish. The remaining most common languages for those with LEP are, in order, Korean, Vietnamese,
Chinese, Persian, Tagalog, Japanese, Arabic, Urdu, and Russian.
Disability
The most common type of disability experienced by county residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, independent living difficulty, cognitive
difficulty, hearing difficulty, self-care difficulty, and vision difficulty.
Sex
County residents are 49.33% male and 50.67% female.
45
Age
The majority of county residents are between 18-64, with 61.58% of residents falling in this group. 23.36%
of county residents are under 18, and 15.05% are 65 or older.
Familial Status
Families with children constitute 44.98% of the total county population.
Table 1.2: Demographic Trends, Orange County
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 333,978 76.15% 343,270 65.91% 327,498 57.77%
Black, Non-
Hispanic 5,751 1.31% 9,452 1.81% 11,226 1.98%
Hispanic 59,040 13.46% 92,933 17.84% 119,893 21.15%
Asian or Pacific
Islander, Non-
Hispanic 37,583 8.57% 68,197 13.09% 103,614 18.28%
Native American,
Non-Hispanic 1,445 0.33% 3,462 0.66% 3,137 0.55%
National Origin
Foreign-born 69,203 15.77% 106,966 20.54% 127,864 22.55%
LEP
Limited English
Proficiency 36,786 8.38% 59,765 11.48% 68,436 12.07%
Sex
Male 213,945 48.75% 251,328 48.27% 274,258 48.38%
Female 224,946 51.25% 269,332 51.73% 292,676 51.62%
Age
Under 18 98,846 22.52% 132,717 25.49% 132,454 23.36%
18-64 281,911 64.23% 317,214 60.93% 349,144 61.58%
65+ 58,135 13.25% 70,729 13.58% 85,336 15.05%
Family Type
Families with
children 51,109 44.18% 51,615 48.55% 65,179 44.98%
46
Table 2.1: Demographics, Aliso Viejo
(Aliso Viejo, Orange County)
Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 30,503 60.17% 4,056,820 31.62%
Black, Non-Hispanic 856 1.69% 859,086 6.70%
Hispanic 8,932 17.62% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 7831 15.45% 1,888,969 14.72%
Native American, Non-
Hispanic 218 0.43% 25,102 0.20%
Two+ Races, Non-Hispanic 2,274 4.49% 267,038 2.08%
Other, Non-Hispanic 77 0.15% 30,960 0.24%
#1 country of origin Mexico 1,530 13.90% Mexico 1,735,902 14.34%
#2 country of origin Iran 1,308 11.89% Philippines 288,529 2.38%
#3 country of origin Philippines 894 8.12% El Salvador 279,381 2.31%
#4 country of origin Korea 870 7.91% Vietnam 234,251 1.93%
#5 country of origin Vietnam 749 6.81% Korea 224,370 1.85%
#6 country of origin India 738 6.71% Guatemala 188,854 1.56%
#7 country of origin
China,
excluding
Hong Kong
and Taiwan
562
5.11%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin Canada 290 2.64% Iran 133,596 1.10%
#9 country of origin Taiwan 252 2.29% Taiwan 87,643 0.72%
#10 country of origin Peru 233 2.12% India 79,608 0.66%
#1 LEP Language
Spanish or
Spanish
Creole
943
2.04% Spanish 2,033,088 16.79%
#2 LEP Language Korean 545 1.18% Chinese 239,576 1.98%
#3 LEP Language Persian 524 1.14% Korean 156,343 1.29%
#4 LEP Language Vietnamese 339 0.74% Vietnamese 147,472 1.22%
#5 LEP Language Tagalog 133 0.29% Armenian 87,201 0.72%
#6 LEP Language Japanese 127 0.28% Tagalog 86,691 0.72%
#7 LEP Language
Other Asian
languages
83
0.18% Persian 41,051 0.34%
#8 LEP Language Russian 77 0.17% Japanese 32,457 0.27%
#9 LEP Language
French (incl.
Patois,
Cajun)
69
0.15% Russian 28,358 0.23%
#10 LEP Language
Other
Pacific Island
languages
61
0.13% Arabic 23,275 0.19%
Hearing difficulty 914 1.8% 303,390 2.52%
Vision difficulty 503 1.0% 227,927 1.90%
Cognitive difficulty 1,140 2.4% 445,175 3.70%
Ambulatory difficulty 1,148 2.4% 641,347 5.34%
Self-care difficulty 669 1.4% 312,961 2.60%
47
Independent living difficulty 913 2.4% 496,105 4.13%
Male 23,780 46.94% 6,328,434 49.33%
Female 26,881 53.06% 6,500,403 50.67%
Under 18 12,868 25.40% 3,138,867 24.47%
18-64 33,682 66.49% 8,274,594 64.50%
65+ 4,111 8.11% 1,415,376 11.03%
Families with children 13,010 69.7% 1,388,564 47.84%
Race and Ethnicity
Aliso Viejo has a majority White population (53.85%), with significant populations of Hispanic (17.62%)
and Asian or Pacific Islander (15.45%) residents as well. Black and Native American populations are
extremely low in the city, at 1.69% and 0.43% respectively.
National Origin
The most common countries of origin for foreign-born residents in the city are Mexico, at 13.90% and Iran,
at 11.89%. The remaining most common countries for foreign -born residents, in order, are the Philippines,
Korea, Vietnam, India, China excluding Hong Kong and Taiwan, Canada, Taiwan, and Peru.
Limited English Proficiency
The most commonly spoken language for those in Aliso Viejo with Limited English Proficiency (LEP) is
Spanish or Spanish Creole. The remaining most common languages for those with LEP are, in order,
Korean, Persian, Vietnamese, Tagalog, Japanese, other Asian Languages, Russian, French, and Other
Pacific Island Languages.
Disability
The most common type of disability experienced by Aliso Viejo residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, cognitive difficulty, independent living
difficulty, hearing difficulty, self-care difficulty, and vision difficulty.
Sex
Aliso Viejo residents are 46.94% male and 53.06% female.
Age
The majority of Aliso Viejo residents are between 18-64, with 66.49% of residents falling in this group.
25.40% of city residents are under 18, and 8.11% are 65 or older.
Familial Status
Families with children constitute 69.7% of Aliso Viejo’s population.
48
Table 3.1: Demographics, Anaheim
(Anaheim, CA CDBG, HOME,
ESG) Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 87,991 25.21% 4,056,820 31.62%
Black, Non-Hispanic 7,843 2.25% 859,086 6.70%
Hispanic 187,931 53.85% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 57,829 16.57% 1,888,969 14.72%
Native American, Non-Hisp. 401 0.11% 25,102 0.20%
Two+ Races, Non-Hispanic 6,137 1.82% 267,038 2.08%
Other, Non-Hispanic 623 0.18% 30,960 0.24%
#1 country of origin Mexico 68,225 19.55% Mexico 1,735,902 14.34%
#2 country of origin Vietnam 13,233 3.79% Philippines 288,529 2.38%
#3 country of origin Philippines 8,968 2.57% El Salvador 279,381 2.31%
#4 country of origin Korea 5,674 1.63% Vietnam 234,251 1.93%
#5 country of origin India 2,725 0.78% Korea 224,370 1.85%
#6 country of origin Guatemala 2,674 0.77% Guatemala 188,854 1.56%
#7 country of origin El Salvador 2,646 0.76%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin
China excl.
Hong Kong
& Taiwan 1,788 0.51% Iran 133,596 1.10%
#9 country of origin Iran 1,313 0.38% Taiwan 87,643 0.72%
#10 country of origin Taiwan 1,001 0.29% India 79,608 0.66%
#1 LEP Language Spanish 63,760 20.31% Spanish 2,033,088 16.79%
#2 LEP Language Vietnamese 7,273 2.32% Chinese 239,576 1.98%
#3 LEP Language Korean 4,117 1.31% Korean 156,343 1.29%
#4 LEP Language Tagalog 2,591 0.83% Vietnamese 147,472 1.22%
#5 LEP Language Chinese 2,390 0.76% Armenian 87,201 0.72%
#6 LEP Language Arabic 1,276 0.41% Tagalog 86,691 0.72%
#7 LEP Language Persian 644 0.21% Persian 41,051 0.34%
#8 LEP Language
Other Indic
Language 533 0.17% Japanese 32,457 0.27%
#9 LEP Language Gujarati 481 0.15% Russian 28,358 0.23%
#10 LEP Language
Other Indo-
European
Language 479 0.15% Arabic 23,275 0.19%
Hearing difficulty 7,308 2.11% 303,390 2.52%
Vision difficulty 4,967 1.43% 227,927 1.90%
Cognitive difficulty 11,360 3.27% 445,175 3.70%
Ambulatory difficulty 15,684 4.52% 641,347 5.34%
Self-care difficulty 7,324 2.11% 312,961 2.60%
Independent living difficulty 12,332 3.55% 496,105 4.13%
Male 168,317 49.85% 6,328,434 49.33%
49
Female 169,326 50.15% 6,500,403 50.67%
Under 18 92,481 27.39% 92,481 27.39%
18-64 213,574 63.25% 213,574 63.25%
65+ 31,589 9.36% 31,589 9.36%
Families with children 38,282 51.43% 1,388,564 47.84%
Race and Ethnicity
Anaheim has a majority Hispanic population (53.85%), with large populations of non-Hispanic Whites
(25.21%) and non-Hispanic Asian residents (16.57%). This represents a much larger Hispanic population
than the county as a whole (34.20%). Black residents comprise 2.25% of the population, and the non-
Hispanic Native American population is 0.11%. The percentage of multi-race non-Hispanic population is
1.82%, and the other non-Hispanic population is 0.18%.
National Origin
The most common country of origin for those in Anaheim is Mexico, with 19.55% of the city population
comprised of residents from Mexico. The remaining most common countries of origin are, in order,
Vietnam, Philippines, Korea, India, Guatemala, El Salvador, China excluding Hong Kong & Taiwan, Iran,
and Taiwan.
Limited English Proficiency
The most commonly spoken language for those in Anaheim with Limited English Proficiency (LEP) is
Spanish. The remaining most common languages for those with LEP are, in order, Vietnamese, Korean,
Tagalog, Chinese, Arabic, Persian, other Indic Languages, Gujarati, and Other Indo-European Languages.
Disability
The most common type of disability experienced by Anaheim residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, independent living difficulty, cognitive
difficulty, self-care difficulty, hearing difficulty, and vision difficulty.
Sex
Anaheim residents are 49.85% male and 50.15% female.
Age
The majority of Anaheim residents are between 18-64, with 63.25% of residents falling in this group.
27.39% of city residents are under 18, and 9.36% are 65 or older.
Familial Status
Families with children constitute 51.43% of Anaheim’s population.
50
Table 3.2: Demographic Trends, Anaheim
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 151,166 56.06% 117,551 35.85% 93,266 27.62%
Black, Non-
Hispanic 6,098 2.26% 8,791 2.68% 9,222 2.73%
Hispanic 86,359 32.03% 153,420 46.78% 177,540 52.58%
Asian or Pacific
Islander, Non-
Hispanic 24,457 9.07% 43,642 13.31% 55,306 16.38%
Native American,
Non-Hispanic 975 0.36% 2,007 0.61% 1,532 0.45%
National Origin
Foreign-born 76,795 28.49% 123,353 37.62% 127,512 37.77%
LEP
Limited English
Proficiency 56,117 20.82% 93,273 28.45% 92,680 27.45%
Sex
Male 136,823 50.75% 164,072 50.04% 168,317 49.85%
Female 132,766 49.25% 163,809 49.96% 169,326 50.15%
Age
Under 18 70,689 26.22% 101,574 30.98% 92,481 27.39%
18-64 176,977 65.65% 199,651 60.89% 213,574 63.25%
65+ 21,923 8.13% 26,656 8.13% 31,589 9.36%
Family Type
Families with
children 32,321 50.08% 37,351 57.02% 38,282 51.43%
Table 4.1: Demographics, Buena Park
(Buena Park, CA CDBG)
Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 20,670 24.90% 4,056,820 31.62%
Black, Non-Hispanic 2,685 3.23% 859,086 6.70%
Hispanic 33,180 39.97% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 24,447 29.45% 1,888,969 14.72%
Native American, Non-Hisp. 201 0.24% 25,102 0.20%
Two+ Races, Non-Hispanic 1,794 2.24% 267,038 2.08%
Other, Non-Hispanic 135 0.17% 30,960 0.24%
51
#1 country of origin Mexico 9,682 11.66% Mexico 1,735,902 14.34%
#2 country of origin Korea 6,168 7.43% Philippines 288,529 2.38%
#3 country of origin Philippines 4,998 6.02% El Salvador 279,381 2.31%
#4 country of origin India 1,585 1.91% Vietnam 234,251 1.93%
#5 country of origin Vietnam 1,163 1.40% Korea 224,370 1.85%
#6 country of origin Peru 623 0.75% Guatemala 188,854 1.56%
#7 country of origin Thailand 499 0.60%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin El Salvador 436 0.53% Iran 133,596 1.10%
#9 country of origin Taiwan 369 0.44% Taiwan 87,643 0.72%
#10 country of origin Afghanistan 368 0.44% India 79,608 0.66%
#1 LEP Language Spanish 11,829 15.49% Spanish 2,033,088 16.79%
#2 LEP Language Korean 6,120 8.01% Chinese 239,576 1.98%
#3 LEP Language Tagalog 1,848 2.42% Korean 156,343 1.29%
#4 LEP Language Chinese 749 0.98% Vietnamese 147,472 1.22%
#5 LEP Language Vietnamese 499 0.65% Armenian 87,201 0.72%
#6 LEP Language
Other Indic
Language 410 0.54% Tagalog 86,691 0.72%
#7 LEP Language Thai 409 0.54% Persian 41,051 0.34%
#8 LEP Language Gujarati 380 0.50% Japanese 32,457 0.27%
#9 LEP Language
Other Pacific
Island
Language 276 0.36% Russian 28,358 0.23%
#10 LEP Language Urdu 213 0.28% Arabic 23,275 0.19%
Hearing difficulty 2,403 2.90% 303,390 2.52%
Vision difficulty 1,387 1.68% 227,927 1.90%
Cognitive difficulty 2,290 2.77% 445,175 3.70%
Ambulatory difficulty 4,242 5.13% 641,347 5.34%
Self-care difficulty 1,843 2.23% 312,961 2.60%
Independent living difficulty 2,793 3.38% 496,105 4.13%
Male 39,425 49.25% 6,328,434 49.33%
Female 40,622 50.75% 6,500,403 50.67%
Under 18 20,320 25.39% 3,138,867 24.47%
18-64 51,322 64.11% 8,274,594 64.50%
65+ 8,404 10.50% 1,415,376 11.03%
Families with children 8,916 46.83% 1,388,564 47.84%
Race and Ethnicity
Buena Park has a plurality Hispanic population (39.97%), with large populations of non -Hispanic Asian
residents (29.45%) and non-Hispanic Whites (24.90%). Black residents comprise 3.23% of the population,
and non-Hispanic Native American population is 0.24%. The percentage of multi -race non-Hispanic
population is 2.24%, and the other non-Hispanic population is 0.17%.
52
National Origin
The most common country of origin for Buena Park residents is Mexico, with 11.66% of the city population
comprised of residents from Mexico. The remaining most common countries of origin are, in order, Korea,
Philippines, India, Vietnam, Peru, Thailand, El Salvador, Taiwan, and Afghanistan.
Limited English Proficiency
The most commonly spoken language for those in Buena Park with Limited English Proficiency (LEP) is
Spanish. The remaining most common languages for those with LEP are, in order, Korean, Tagalog,
Chinese, Vietnamese, Other Indic Languages, Thai, Gujarati, Other Pacific Island Languages, and Urdu.
Disability
The most common type of disability experienced by Buena Park residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, indepe ndent living difficulty, hearing
difficulty, cognitive difficulty, self-care difficulty, and vision difficulty.
Sex
Buena Park residents are 49.25% male and 50.75% female.
Age
The majority of Buena Park residents are between 18-64, with 64.11% of residents falling in this group.
25.39% of city residents are under 18, and 10.50% are 65 or older.
Familial Status
Families with children constitute 46.83% of Buena Park’s population.
Table 4.2: Demographic Trends, Buena Park
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 39,286 58.15% 29,077 37.27% 21,298 26.61%
Black, Non-
Hispanic 1,774 2.63% 3,290 4.22% 3,272 4.09%
Hispanic 16,909 25.03% 26,955 34.55% 32,288 40.34%
Asian or Pacific
Islander, Non-
Hispanic 9,116 13.49% 17,392 22.29% 22,574 28.20%
Native American,
Non-Hispanic 327 0.48% 642 0.82% 431 0.54%
National Origin
Foreign-born 15,358 22.79% 26,072 33.42% 29,903 37.36%
53
LEP
Limited English
Proficiency 9,978 14.80% 17,635 22.61% 20,822 26.01%
Sex
Male 33,549 49.78% 38,549 49.42% 39,425 49.25%
Female 33,852 50.22% 39,460 50.58% 40,622 50.75%
Age
Under 18 17,690 26.25% 23,458 30.07% 20,320 25.39%
18-64 44,385 65.85% 47,533 60.93% 51,322 64.11%
65+ 5,325 7.90% 7,018 9.00% 8,404 10.50%
Family Type
Families with
children 8,496 49.42% 8,540 53.86% 8,916 46.83%
Table 5.1: Demographics, Costa Mesa
(Costa Mesa, CA CDBG, HOME)
Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 55,764 49.38% 4,056,820 31.62%
Black, Non-Hispanic 1,790 1.59% 859,086 6.70%
Hispanic 41,201 36.48% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 10,613 9.40% 1,888,969 14.72%
Native American, Non-Hisp. 208 0.18% 25,102 0.20%
Two+ Races, Non-Hispanic 2,725 2.48% 267,038 2.08%
Other, Non-Hispanic 246 0.22% 30,960 0.24%
#1 country of origin Mexico 14,995 13.28% Mexico 14,995 13.28%
#2 country of origin El Salvador 1,418 1.26% El Salvador 1,418 1.26%
#3 country of origin Vietnam 1,351 1.20% Vietnam 1,351 1.20%
#4 country of origin Philippines 1,219 1.08% Philippines 1,219 1.08%
#5 country of origin Japan 954 0.84% Japan 954 0.84%
#6 country of origin Guatemala 684 0.61% Guatemala 684 0.61%
#7 country of origin Iran 620 0.55% Iran 620 0.55%
#8 country of origin Canada 566 0.50% Canada 566 0.50%
#9 country of origin India 501 0.44% India 501 0.44%
#10 country of origin Korea 477 0.42% Korea 477 0.42%
#1 LEP Language Spanish 12,486 12.05% Spanish 2,033,088 16.79%
#2 LEP Language Vietnamese 835 0.81% Chinese 239,576 1.98%
#3 LEP Language Japanese 444 0.43% Korean 156,343 1.29%
#4 LEP Language Chinese 292 0.28% Vietnamese 147,472 1.22%
#5 LEP Language Tagalog 205 0.20% Armenian 87,201 0.72%
#6 LEP Language Korean 184 0.18% Tagalog 86,691 0.72%
54
#7 LEP Language
Other Pacific
Island
Language 122 0.12% Persian 41,051 0.34%
#8 LEP Language Cambodian 107 0.10% Japanese 32,457 0.27%
#9 LEP Language Arabic 97 0.09% Russian 28,358 0.23%
#10 LEP Language German 82 0.08% Arabic 23,275 0.19%
Hearing difficulty 2,462 2.19% 303,390 2.52%
Vision difficulty 1,967 1.75% 227,927 1.90%
Cognitive difficulty 3,899 3.47% 445,175 3.70%
Ambulatory difficulty 4,401 3.91% 641,347 5.34%
Self-care difficulty 1,737 1.54% 312,961 2.60%
Independent living difficulty 3,278 2.91% 496,105 4.13%
Male 55,886 50.87% 6,328,434 49.33%
Female 53,971 49.13% 6,500,403 50.67%
Under 18 23,729 21.60% 3,138,867 24.47%
18-64 75,989 69.17% 8,274,594 64.50%
65+ 10,139 9.23% 1,415,376 11.03%
Families with children 11,152 48.03% 1,388,564 47.84%
Race and Ethnicity
Costa Mesa has a near-majority White population (49.38%), with a large population of Hispanic residents
(36.48%) and a sizable population of non-Hispanic Asian residents (9.40%). Black residents comprise
1.59% of the population, and non-Hispanic Native American population is 0.18%. The percentage of multi-
race non-Hispanic population is 2.48%, and the other non-Hispanic population is 0.22%.
National Origin
The most common country of origin for Costa Mesa residents is Mexico, with 13.28% of the city population
comprised of residents from Mexico. The remaining most common countries of origin are, in order, El
Salvador, Vietnam, Philippines, Japan, Guatemala, Iran, Canada, India, and Korea.
Limited English Proficiency
The most commonly spoken language for those in Costa Mesa with Limited English Proficiency (LEP) is
Spanish. The remaining most common languages for those with LEP are, in order, Vietnamese, Jap anese,
Chinese, Tagalog, Korean, Other Pacific Island Languages, Cambodian, Arabic, and German.
Disability
The most common type of disability experienced by Costa Mesa residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, cognitive difficulty, independent living
difficulty, hearing difficulty, vision difficulty, and self-care difficulty.
55
Sex
Costa Mesa residents are 50.87% male and 49.13% female.
Age
The majority of Costa Mesa residents are between 18-64, with 69.17% of residents falling in this group.
21.60% of city residents are under 18, and 9.23% are 65 or older.
Familial Status
Families with children constitute 48.03% of Costa Mesa’s population.
Table 5.2: Demographic Trends, Costa Mesa
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 70,120 72.26% 62,285 56.96% 56,901 51.80%
Black, Non-
Hispanic 1,142 1.18% 1,653 1.51% 1,879 1.71%
Hispanic 19,300 19.89% 34,569 31.61% 39,405 35.87%
Asian or Pacific
Islander, Non-
Hispanic 6,024 6.21% 9,204 8.42% 10,680 9.72%
Native American,
Non-Hispanic 331 0.34% 771 0.71% 673 0.61%
National Origin
Foreign-born 20,844 21.50% 31,702 28.98% 29,598 26.94%
LEP
Limited English
Proficiency 12,652 13.05% 21,813 19.94% 17,533 15.96%
Sex
Male 49,424 50.97% 55,859 51.07% 55,886 50.87%
Female 47,542 49.03% 53,518 48.93% 53,971 49.13%
Age
Under 18 18,841 19.43% 25,930 23.71% 23,729 21.60%
18-64 70,221 72.42% 74,185 67.83% 75,989 69.17%
65+ 7,905 8.15% 9,261 8.47% 10,139 9.23%
Family Type
Families with
children 9,631 43.63% 10,809 50.61% 11,152 48.03%
56
Table 6.1: Demographics, Fountain Valley
(Fountain Valley, CA CDBG)
Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 26,433 46.67% 4,056,820 31.62%
Black, Non-Hispanic 256 0.45% 859,086 6.70%
Hispanic 9418 16.63% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 18,565 32.78% 1,888,969 14.72%
Native American, Non-Hisp. 69 0.12% 25,102 0.20%
Two+ Races, Non-Hispanic 1,601 2.88% 267,038 2.08%
Other, Non-Hispanic 113 0.20% 30,960 0.24%
#1 country of origin Vietnam 7,556 13.34% Mexico 1,735,902 14.34%
#2 country of origin Mexico 1,490 2.63% Philippines 288,529 2.38%
#3 country of origin Taiwan 696 1.23% El Salvador 279,381 2.31%
#4 country of origin Korea 566 1.00% Vietnam 234,251 1.93%
#5 country of origin Philippines 521 0.92% Korea 224,370 1.85%
#6 country of origin Japan 485 0.86% Guatemala 188,854 1.56%
#7 country of origin Egypt 454 0.80%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin
China, excl.
Hong Kong
and Taiwan 408 0.72% Iran 133,596 1.10%
#9 country of origin India 402 0.71% Taiwan 87,643 0.72%
#10 country of origin Canada 341 0.60% India 79,608 0.66%
#1 LEP Language Vietnamese 4,989 9.32% Spanish 2,033,088 16.79%
#2 LEP Language Chinese 1,337 2.50% Chinese 239,576 1.98%
#3 LEP Language Spanish 1,251 2.34% Korean 156,343 1.29%
#4 LEP Language Korean 361 0.67% Vietnamese 147,472 1.22%
#5 LEP Language Japanese 225 0.42% Armenian 87,201 0.72%
#6 LEP Language Arabic 203 0.38% Tagalog 86,691 0.72%
#7 LEP Language Tagalog 182 0.34% Persian 41,051 0.34%
#8 LEP Language Persian 111 0.21% Japanese 32,457 0.27%
#9 LEP Language Armenian 78 0.15% Russian 28,358 0.23%
#10 LEP Language German 71 0.13% Arabic 23,275 0.19%
Hearing difficulty 1,842 3.26% 303,390 2.52%
Vision difficulty 685 1.21% 227,927 1.90%
Cognitive difficulty 2,394 4.24% 445,175 3.70%
Ambulatory difficulty 3,093 5.48% 641,347 5.34%
Self-care difficulty 1,266 2.24% 312,961 2.60%
Independent living difficulty 2,261 4.01% 496,105 4.13%
Male 27,076 48.76% 6,328,434 49.33%
Female 28,451 51.24% 6,500,403 50.67%
57
Under 18 11,794 21.24% 3,138,867 24.47%
18-64 34,068 61.35% 8,274,594 64.50%
65+ 9,664 17.40% 1,415,376 11.03%
Families with children 5,656 39.90% 1,388,564 47.84%
Race and Ethnicity
Fountain Valley has a near-majority White population (46.67%), with a large population of non-Hispanic
Asian residents (32.78%) and a sizable population of Hispanic residents (16.63%). This represents a large
increase in the percentage of non-Hispanic Asian residents as compared to Orange County overall (19.78%)
and a large decrease in the percentage of Hispanic residents as compared to the County (34.20%). Black
residents comprise 1.57% of the population, and non-Hispanic Native Americans comprise 0.21% of the
population. The percentage of multi-race non-Hispanic population is 2.71%, and the other non-Hispanic
population is 0.21%.
National Origin
The most common country of origin for Fountain Valley residents is Mexico, with 11.21% of the city
population comprised of residents from Mexico. The remaining most common countries of origin are, in
order, Vietnam, Korea, Philippines, China (excluding Hong Kong & Taiwan), India, Iran, Taiwan, El
Salvador, and Canada.
Limited English Proficiency
The most commonly spoken language for those in Fountain Valley with Limited English Proficiency (LEP)
is Vietnamese – different than the County’s most prominent LEP language (Spanish). The remaining most
common languages for those with LEP are, in order, Chinese, Spanish, Korean, Japanese, Arabic, Tagalog,
Persian, Armenian, and German.
Disability
The most common type of disability experienced by Fountain Valley residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, cognitive difficulty, independent living
difficulty, hearing difficulty, self-care difficulty, and vision difficulty.
Sex
Fountain Valley residents are 48.76% male and 51.24% female.
Age
The majority of Fountain Valley residents are between 18-64, with 61.35% of residents falling in this group.
21.24% of city residents are under 18, and 17.40% are 65 or older.
Familial Status
Families with children constitute 39.90% of Fountain Valley’s population.
58
Table 6.2: Demographic Trends, Fountain Valley
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 38,801 71.93% 31,386 57.39% 26,642 47.98%
Black, Non-
Hispanic 508 0.94% 731 1.34% 692 1.25%
Hispanic 4,884 9.05% 6,490 11.87% 8,071 14.54%
Asian or Pacific
Islander, Non-
Hispanic 9,405 17.43% 15,167 27.73% 19,632 35.36%
Native American,
Non-Hispanic 257 0.48% 434 0.79% 350 0.63%
National Origin
Foreign-born 10,915 20.20% 15,516 28.37% 16,514 29.74%
LEP
Limited English
Proficiency 5,757 10.65% 9,813 17.94% 9,881 17.80%
Sex
Male 26,814 49.63% 26,709 48.84% 27,076 48.76%
Female 27,215 50.37% 27,980 51.16% 28,451 51.24%
Age
Under 18 12,767 23.63% 13,344 24.40% 11,794 21.24%
aaaaa18-64 37,304 69.04% 34,958 63.92% 34,068 61.35%
65+ 3,958 7.33% 6,387 11.68% 9,664 17.40%
Family Type
Families with
children 6,674 47.04% 6,185 43.95% 5,656 39.90%
Table 7.1: Demographics, Fullerton
(Fullerton, CA CDBG, HOME)
Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 46145 32.97% 4,056,820 31.62%
Black, Non-Hispanic 3800 2.71% 859,086 6.70%
Hispanic 50957 36.40% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 34692 24.78% 1,888,969 14.72%
Native American, Non-Hisp. 203 0.15% 25,102 0.20%
Two+ Races, Non-Hispanic 2,959 2.18% 267,038 2.08%
Other, Non-Hispanic 232 0.17% 30,960 0.24%
59
#1 country of origin Mexico 14,379 10.27% Mexico 1,735,902 14.34%
#2 country of origin Korea 11,208 8.01% Philippines 288,529 2.38%
#3 country of origin Philippines 2,344 1.67% El Salvador 279,381 2.31%
#4 country of origin India 1,993 1.42% Vietnam 234,251 1.93%
#5 country of origin
China excl.
Hong Kong
& Taiwan 1,836 1.31% Korea 224,370 1.85%
#6 country of origin Vietnam 1,475 1.05% Guatemala 188,854 1.56%
#7 country of origin Taiwan 1,105 0.79%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin El Salvador 629 0.45% Iran 133,596 1.10%
#9 country of origin Canada 494 0.35% Taiwan 87,643 0.72%
#10 country of origin Japan 473 0.34% India 79,608 0.66%
#1 LEP Language Spanish 13,340 10.42% Spanish 2,033,088 16.79%
#2 LEP Language Korean 7,394 5.78% Chinese 239,576 1.98%
#3 LEP Language Chinese 2,134 1.67% Korean 156,343 1.29%
#4 LEP Language Vietnamese 828 0.65% Vietnamese 147,472 1.22%
#5 LEP Language Japanese 375 0.29% Armenian 87,201 0.72%
#6 LEP Language Tagalog 372 0.29% Tagalog 86,691 0.72%
#7 LEP Language Gujarati 351 0.27% Persian 41,051 0.34%
#8 LEP Language Arabic 228 0.18% Japanese 32,457 0.27%
#9 LEP Language
Other Asian
Language 227 0.18% Russian 28,358 0.23%
#10 LEP Language
Other Indo-
European
Language 204 0.16% Arabic 23,275 0.19%
Hearing difficulty 3,344 2.40% 303,390 2.52%
Vision difficulty 2,406 1.73% 227,927 1.90%
Cognitive difficulty 4,478 3.22% 445,175 3.70%
Ambulatory difficulty 6,425 4.62% 641,347 5.34%
Self-care difficulty 2,683 1.93% 312,961 2.60%
Independent living difficulty 4,992 3.59% 496,105 4.13%
Male 66,653 49.10% 66,653 49.10%
Female 69,094 50.90% 69,094 50.90%
Under 18 31,953 23.54% 3,138,867 24.47%
18-64 87,901 64.75% 8,274,594 64.50%
65+ 15,893 11.71% 1,415,376 11.03%
Families with children 14,582 46.37% 1,388,564 47.84%
Race and Ethnicity
Fullerton has a plurality Hispanic population (36.40%), with a large population of Whites (32.97%) and
non-Hispanic Asian residents (24.78%). Black residents comprise 2.71% of the population, and non-
60
Hispanic Native Americans comprise 0.15% of the population. The percentage of multi-race non-Hispanic
population is 2.18%, and the other non-Hispanic population is 0.17%.
National Origin
The most common country of origin for Fullerton residents is Mexico, with 10.27% of the city population
comprised of residents from Mexico. The remaining most common countries of origin are, in order, Korea,
Philippines, India, China (excluding Hong Kong & Taiwan), Vietnam, Taiwan, El Salvador, Canada, and
Japan.
Limited English Proficiency
The most commonly spoken language for those in Fullerton with Limited English Proficiency (LEP) is
Spanish. The remaining most common languages for those with LEP are, in order, Korean, Chinese,
Vietnamese, Japanese, Tagalog, Gujarati, Arabic, Other Asian Languages, and Other Indo -European
Languages.
Disability
The most common type of disability experienced by Fullerton residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, independent living difficulty, cognitive
difficulty, hearing difficulty, self-care difficulty, and vision difficulty.
Sex
Fullerton residents are 49.10% male and 50.90% female.
Age
The majority of Fullerton residents are between 18-64, with 64.75% of residents falling in this group.
23.54% of city residents are under 18, and 11.71% are 65 or older.
Familial Status
Families with children constitute 46.37% of Fullerton’s population.
Table 7.2: Demographic Trends, Fullerton
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 73,647 65.17% 62,021 49.24% 52,356 38.57%
Black, Non-
Hispanic 2,273 2.01% 3,060 2.43% 3,330 2.45%
Hispanic 23,894 21.14% 38,323 30.43% 47,235 34.80%
Asian or Pacific
Islander, Non-
Hispanic 12,608 11.16% 20,690 16.43% 31,810 23.43%
Native American,
Non-Hispanic 364 0.32% 927 0.74% 707 0.52%
61
National Origin
Foreign-born 25,948 22.98% 35,894 28.49% 39,906 29.40%
LEP
Limited English
Proficiency 16,188 14.33% 24,576 19.50% 25,536 18.81%
Sex
Male 56,379 49.92% 62,453 49.57% 66,653 49.10%
Female 56,554 50.08% 63,542 50.43% 69,094 50.90%
Age
Under 18 25,569 22.64% 32,955 26.16% 31,953 23.54%
18-64 75,660 67.00% 78,816 62.55% 87,901 64.75%
65+ 11,703 10.36% 14,224 11.29% 15,893 11.71%
Family Type
Families with
children 12,505 44.91% 11,097 48.22% 14,582 46.37%
Table 8.1: Demographics, Garden Grove
(Garden Grove, CA CDBG, HOME,
ESG) Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 36,168 20.69% 4,056,820 31.62%
Black, Non-Hispanic 1,607 0.92% 859,086 6.70%
Hispanic 63,059 36.07% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 69,872 39.97% 1,888,969 14.72%
Native American, Non-Hisp. 514 0.29% 25,102 0.20%
Two+ Races, Non-Hispanic 2,881 1.66% 267,038 2.08%
Other, Non-Hispanic 235 0.14% 30,960 0.24%
#1 country of origin Vietnam 39,624 22.67% Mexico 1,735,902 14.34%
#2 country of origin Mexico 21,168 12.11% Philippines 288,529 2.38%
#3 country of origin Korea 3,408 1.95% El Salvador 279,381 2.31%
#4 country of origin Philippines 2,743 1.57% Vietnam 234,251 1.93%
#5 country of origin El Salvador 1,169 0.67% Korea 224,370 1.85%
#6 country of origin Guatemala 780 0.45% Guatemala 188,854 1.56%
#7 country of origin Peru 650 0.37%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin
China excl.
Hong Kong
& Taiwan 594 0.34% Iran 133,596 1.10%
#9 country of origin Cambodia 466 0.27% Taiwan 87,643 0.72%
#10 country of origin Egypt 406 0.23% India 79,608 0.66%
62
#1 LEP Language Vietnamese 28,226 17.39% Spanish 2,033,088 16.79%
#2 LEP Language Spanish 19,752 12.17% Chinese 239,576 1.98%
#3 LEP Language Korean 2,897 1.78% Korean 156,343 1.29%
#4 LEP Language Chinese 1,795 1.11% Vietnamese 147,472 1.22%
#5 LEP Language Tagalog 380 0.23% Armenian 87,201 0.72%
#6 LEP Language Cambodian 294 0.18% Tagalog 86,691 0.72%
#7 LEP Language
Other Pacific
Island
Language 288 0.18% Persian 41,051 0.34%
#8 LEP Language Arabic 256 0.16% Japanese 32,457 0.27%
#9 LEP Language Japanese 237 0.15% Russian 28,358 0.23%
#10 LEP Language Hmong 162 0.10% Arabic 23,275 0.19%
Hearing difficulty 5,132 2.95% 303,390 2.52%
Vision difficulty 3,044 1.75% 227,927 1.90%
Cognitive difficulty 6,805 3.91% 445,175 3.70%
Ambulatory difficulty 8,226 4.73% 641,347 5.34%
Self-care difficulty 3,996 2.30% 312,961 2.60%
Independent living difficulty 7,328 4.21% 496,105 4.13%
Male 86,373 49.85% 6,328,434 49.33%
Female 86,888 50.15% 6,500,403 50.67%
Under 18 44,233 25.53% 3,138,867 24.47%
18-64 110,100 63.55% 8,274,594 64.50%
65+ 18,928 10.92% 1,415,376 11.03%
Families with children 18,046 47.97% 1,388,564 47.84%
Race and Ethnicity
Garden Grove has a plurality non-Hispanic Asian population (39.97%), with a large population of Hispanics
(36.07%) and Whites (20.69%). This represents a large increase in the percentage of non-Hispanic Asian
residents as compared to Orange County overall (19.78%). Black residents comprise 0.92% of the
population, and non-Hispanic Native Americans comprise 0.29% of the population. The percentage of
multi-race non-Hispanic population is 1.66%, and the other non-Hispanic population is 0.14%.
National Origin
The most common country of origin for Garden Grove residents is Vietnam, with 22.67% of the city
population comprised of residents from Vietnam. This is distinct from the most common country of origin
for Orange County overall (Mexico). The remaining most common countries of origin in Garden Grove
are, in order, Mexico, Korea, Philippines, El Salvador, Guatemala, Peru, China (excluding Hong Kong &
Taiwan), Cambodia, and Egypt.
Limited English Proficiency
The most commonly spoken language for those in Garden Grove with Limited English Proficiency (LEP)
is Vietnamese. This is distinct from the most common LEP language in the broader county (Spanish). The
63
remaining most common languages for those with LEP are, in order, Spanish, Korean, Chinese, Tagalog,
Cambodian, Other Pacific Island Languages, Arabic, Japanese, and Hmong.
Disability
The most common type of disability experienced by Garden Grove residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, independent living difficulty, cognitive
difficulty, hearing difficulty, self-care difficulty, and vision difficulty.
Sex
Garden Grove residents are 49.85% male and 50.15% female.
Age
The majority of Garden Grove residents are between 18-64, with 63.55% of residents falling in this group.
25.53% of city residents are under 18, and 10.92% are 65 or older.
Familial Status
Families with children constitute 47.97% of Garden Grove’s population.
Table 8.2: Demographic Trends, Garden Grove
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 79,750 54.42% 54,141 32.25% 38,900 22.45%
Black, Non-
Hispanic 2,145 1.46% 2,474 1.47% 2,376 1.37%
Hispanic 34,492 23.54% 55,487 33.06% 64,694 37.34%
Asian or Pacific
Islander, Non-
Hispanic 29,209 19.93% 53,793 32.05% 66,272 38.25%
Native American,
Non-Hispanic 631 0.43% 1,107 0.66% 725 0.42%
National Origin
Foreign-born 44,669 30.48% 72,339 43.10% 74,749 43.14%
LEP
Limited English
Proficiency 32,715 22.32% 57,735 34.40% 56,658 32.70%
Sex
Male 74,265 50.67% 84,033 50.06% 86,373 49.85%
Female 72,300 49.33% 83,818 49.94% 86,888 50.15%
64
Age
Under 18 38,170 26.04% 48,566 28.93% 44,233 25.53%
18-64 95,383 65.08% 103,249 61.51% 110,100 63.55%
65+ 13,013 8.88% 16,038 9.55% 18,928 10.92%
Family Type
Families with
children 17,177 48.90% 19,501 53.21% 18,046 47.97%
Table 9.1: Demographics, Huntington Beach
(Huntington Beach, CA CDBG,
HOME) Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 126,453 63.10% 4,056,820 31.62%
Black, Non-Hispanic 2,510 1.25% 859,086 6.70%
Hispanic 38,773 19.35% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 24,069 12.01% 1,888,969 14.72%
Native American, Non-Hisp. 721 0.36% 25,102 0.20%
Two+ Races, Non-Hispanic 6,008 3.15% 267,038 2.08%
Other, Non-Hispanic 392 0.21% 30,960 0.24%
#1 country of origin Mexico 7,734 3.86% Mexico 1,735,902 14.34%
#2 country of origin Vietnam 5,826 2.91% Philippines 288,529 2.38%
#3 country of origin Philippines 2,006 1.00% El Salvador 279,381 2.31%
#4 country of origin Canada 1,248 0.62% Vietnam 234,251 1.93%
#5 country of origin Egypt 1,159 0.58% Korea 224,370 1.85%
#6 country of origin
China excl.
Hong Kong
and Taiwan 1,140 0.57% Guatemala 188,854 1.56%
#7 country of origin Japan 1,135 0.57%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin Korea 1,061 0.53% Iran 133,596 1.10%
#9 country of origin India 664 0.33% Taiwan 87,643 0.72%
#10 country of origin Taiwan 638 0.32% India 79,608 0.66%
#1 LEP Language Spanish 7,526 4.10% Spanish 2,033,088 16.79%
#2 LEP Language Vietnamese 2,822 1.54% Chinese 239,576 1.98%
#3 LEP Language Chinese 1,518 0.83% Korean 156,343 1.29%
#4 LEP Language Korean 741 0.40% Vietnamese 147,472 1.22%
#5 LEP Language Arabic 730 0.40% Armenian 87,201 0.72%
#6 LEP Language Japanese 533 0.29% Tagalog 86,691 0.72%
#7 LEP Language Tagalog 270 0.15% Persian 41,051 0.34%
#8 LEP Language Portuguese 206 0.11% Japanese 32,457 0.27%
#9 LEP Language
Other Indo-
European
Language 200 0.11% Russian 28,358 0.23%
#10 LEP Language Thai 150 0.08% Arabic 23,275 0.19%
65
Hearing difficulty 5,818 2.91% 303,390 2.52%
Vision difficulty 3,392 1.70% 227,927 1.90%
Cognitive difficulty 7,239 3.62% 445,175 3.70%
Ambulatory difficulty 9,226 4.61% 641,347 5.34%
Self-care difficulty 3,952 1.98% 312,961 2.60%
Independent living difficulty 6,816 3.41% 496,105 4.13%
Male 94,733 49.60% 6,328,434 49.33%
Female 96,243 50.40% 6,500,403 50.67%
Under 18 39,353 20.61% 3,138,867 24.47%
18-64 124,400 65.14% 8,274,594 64.50%
65+ 27,224 14.26% 1,415,376 11.03%
Families with children 20,083 41.45% 1,388,564 47.84%
Race and Ethnicity
Huntington Beach has a majority White population (63.10%) and sizable populations of Hispanics (19.35%)
and non-Hispanic Asians (12.01%). This represents a large increase in the percentage of White residents as
compared to Orange County overall (41.40%). Black residents comprise 1.25% of the population, and non-
Hispanic Native Americans comprise 0.36% of the population. The percentage of multi-race non-Hispanic
population is 3.15%, and the other non-Hispanic population is 0.21%.
National Origin
The most common country of origin for Huntington Beach residents is Mexico, with 3.86% of the city
population comprised of residents from Mexico. The remaining most common countries of origin in
Huntington Beach are, in order, Vietnam, Philippines, Canada, Egypt, China (excluding Hong Kong &
Taiwan), Japan, Korea, India, and Taiwan.
Limited English Proficiency
The most commonly spoken language for those in Huntington Beach with Limited English Proficiency
(LEP) is Spanish. The remaining most common languages for those with LEP are, in order, Vietnamese,
Chinese, Korean, Arabic, Japanese, Tagalog, Portuguese, Other Indo-European Languages, and Thai.
Disability
The most common type of disability experienced by Huntington Beach residents is ambulatory difficulty.
The remaining most common disabilities are, in order of prevalence, cognitive difficulty, independent living
difficulty, hearing difficulty, self-care difficulty, and vision difficulty.
Sex
Huntington Beach residents are 49.60% male and 50.40% female.
66
Age
The majority of Huntington Beach residents are between 18-64, with 65.14% of residents falling in this
group. 20.61% of city residents are under 18, and 14.26% are 65 or older.
Familial Status
Families with children constitute 41.45% of Huntington Beach’s population.
Table 9.2: Demographic Trends, Huntington Beach
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 144,453 79.16% 137,054 71.80% 127,955 67.00%
Black, Non-
Hispanic 1,602 0.88% 1,905 1.00% 2,377 1.24%
Hispanic 20,522 11.25% 27,945 14.64% 32,552 17.05%
Asian or Pacific
Islander, Non-
Hispanic 14,732 8.07% 20,786 10.89% 25,886 13.55%
Native American,
Non-Hispanic 898 0.49% 1,925 1.01% 1,669 0.87%
National Origin
Foreign-born 27,066 14.84% 32,414 16.99% 30,902 16.18%
LEP
Limited English
Proficiency 13,562 7.43% 18,168 9.52% 15,869 8.31%
Sex
Male 91,952 50.40% 95,767 50.18% 94,733 49.60%
Female 90,486 49.60% 95,063 49.82% 96,243 50.40%
Age
Under 18 37,779 20.71% 43,525 22.81% 39,353 20.61%
18-64 129,499 70.98% 127,288 66.70% 124,400 65.14%
65+ 15,160 8.31% 20,017 10.49% 27,224 14.26%
Family Type
Families with
children 20,283 43.80% 19,930 44.46% 20,083 41.45%
67
Table 10.1: Demographics, Irvine
(Irvine, CA CDBG, HOME)
Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 107,202 41.73% 4,056,820 31.62%
Black, Non-Hispanic 4,714 1.84% 859,086 6.70%
Hispanic 25,025 9.74% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 107,337 41.79% 1,888,969 14.72%
Native American, Non-Hisp. 221 0.09% 25,102 0.20%
Two+ Races, Non-Hispanic 9,526 4.50% 267,038 2.08%
Other, Non-Hispanic 544 0.26% 30,960 0.24%
#1 country of origin Korea 14,066 5.48% Mexico 1,735,902 14.34%
#2 country of origin
China excl.
Hong Kong
& Taiwan 13,021 5.07% Philippines 288,529 2.38%
#3 country of origin India 9,749 3.80% El Salvador 279,381 2.31%
#4 country of origin Iran 9,518 3.71% Vietnam 234,251 1.93%
#5 country of origin Taiwan 8,648 3.37% Korea 224,370 1.85%
#6 country of origin Vietnam 4,945 1.93% Guatemala 188,854 1.56%
#7 country of origin Philippines 4,792 1.87%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin Japan 4,752 1.85% Iran 133,596 1.10%
#9 country of origin Mexico 2,956 1.15% Taiwan 87,643 0.72%
#10 country of origin Hong Kong 1,977 0.77% India 79,608 0.66%
#1 LEP Language Chinese 8,033 3.83% Spanish 2,033,088 16.79%
#2 LEP Language Korean 6,701 3.19% Chinese 239,576 1.98%
#3 LEP Language Persian 3,404 1.62% Korean 156,343 1.29%
#4 LEP Language Spanish 2,522 1.20% Vietnamese 147,472 1.22%
#5 LEP Language Vietnamese 2,033 0.97% Armenian 87,201 0.72%
#6 LEP Language Japanese 1,947 0.93% Tagalog 86,691 0.72%
#7 LEP Language Arabic 875 0.42% Persian 41,051 0.34%
#8 LEP Language
Other Indic
Language 715 0.34% Japanese 32,457 0.27%
#9 LEP Language
Other Asian
Language 578 0.28% Russian 28,358 0.23%
#10 LEP Language Russian 545 0.26% Arabic 23,275 0.19%
Hearing difficulty 4,154 1.62% 303,390 2.52%
Vision difficulty 2,032 0.79% 227,927 1.90%
Cognitive difficulty 5,481 2.14% 445,175 3.70%
Ambulatory difficulty 6,719 2.62% 641,347 5.34%
Self-care difficulty 3,527 1.37% 312,961 2.60%
Independent living difficulty 5,713 2.23% 496,105 4.13%
Male 103,034 48.71% 6,328,434 49.33%
Female 108,498 51.29% 6,500,403 50.67%
68
Under 18 45,857 21.68% 45,857 21.68%
18-64 146,753 69.38% 146,753 69.38%
65+ 18,922 8.95% 18,922 8.95%
Families with children 25,573 49.80% 1,388,564 47.84%
Race and Ethnicity
Irvine has a plurality non-Hispanic Asian population (41.79%) with a large population of White residents
(41.73%) and a relatively small population of Hispanic residents (9.74%) as compared to the county (over
34%). Black residents comprise 1.84% of the population, and non-Hispanic Native Americans comprise
0.09% of the population. The percentage of multi-race non-Hispanic population is 4.50%, and the other
non-Hispanic population is 0.26%.
National Origin
The most common country of origin for Irvine residents is Korea, with 5.48% of the city population
comprised of residents from Korea. This is distinct from the County, for which the most common country
of origin is Mexico. The remaining most common countries of origin in Irvine are, in order, China
(excluding Hong Kong & Tibet), India, Iran, Taiwan, Vietnam, Philippines, Japan, Mexico, and Hong
Kong.
Limited English Proficiency
The most commonly spoken language for those in Irvine with Limited English Proficiency (LEP) is Chinese
– distinct from the most common language spoken by those with LEP in the County (Spanish). The
remaining most common languages for those with LEP are, in order, Korean, Persian, Spanish, Vietnamese,
Japanese, Arabic, Other Indic Languages, Other Asian Languages, and Russian.
Disability
The most common type of disability experienced by Irvine residents is ambulatory difficulty. The remaining
most common disabilities are, in order of prevalence, independent living difficulty, cognitive difficulty,
hearing difficulty, self-care difficulty, and vision difficulty.
Sex
Irvine residents are 48.71% male and 51.29% female.
Age
The majority of Irvine residents are between 18-64, with 69.38% of residents falling in this group. 21.68%
of city residents are under 18, and 8.95% are 65 or older.
Familial Status
Families with children constitute 49.80% of Irvine’s population.
69
Table 10.2: Demographic Trends, Irvine
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 92,181 73.19% 85,972 57.41% 96,467 45.60%
Black, Non-
Hispanic 3,263 2.59% 2,573 1.72% 4,514 2.13%
Hispanic 9,685 7.69% 12,271 8.19% 20,401 9.64%
Asian or Pacific
Islander, Non-
Hispanic 20,256 16.08% 46,268 30.90% 88,674 41.92%
Native American,
Non-Hispanic 316 0.25% 618 0.41% 755 0.36%
National Origin
Foreign-born 26,301 20.88% 47,114 31.46% 67,886 32.09%
LEP
Limited English
Proficiency 11,047 8.77% 21,335 14.25% 28,611 13.53%
Sex
Male 62,975 50.00% 73,019 48.77% 103,034 48.71%
Female 62,976 50.00% 76,715 51.23% 108,498 51.29%
Age
Under 18 30,335 24.08% 36,552 24.41% 45,857 21.68%
18-64 88,663 70.40% 102,353 68.36% 146,753 69.38%
65+ 6,952 5.52% 10,830 7.23% 18,922 8.95%
Family Type
Families with
children 17,137 55.14% 16,168 52.72% 25,573 49.80%
Table 11.1: Demographics, La Habra
(La Habra, CA CDBG) Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 15,817 25.53% 4,056,820 31.62%
Black, Non-Hispanic 676 1.09% 859,086 6.70%
Hispanic 36,975 59.67% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 7,514 12.13% 1,888,969 14.72%
Native American, Non-Hisp. 96 0.15% 25,102 0.20%
Two+ Races, Non-Hispanic 969 1.61% 267,038 2.08%
Other, Non-Hispanic 90 0.15% 30,960 0.24%
70
#1 country of origin Mexico 10,133 16.35% Mexico 1,735,902 14.34%
#2 country of origin Korea 2,248 3.63% Philippines 288,529 2.38%
#3 country of origin Philippines 1,379 2.23% El Salvador 279,381 2.31%
#4 country of origin Guatemala 365 0.59% Vietnam 234,251 1.93%
#5 country of origin
China excl.
Hong Kong
and Taiwan 334 0.54% Korea 224,370 1.85%
#6 country of origin Indonesia 263 0.42% Guatemala 188,854 1.56%
#7 country of origin India 233 0.38%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin El Salvador 228 0.37% Iran 133,596 1.10%
#9 country of origin Taiwan 220 0.36% Taiwan 87,643 0.72%
#10 country of origin Nicaragua 199 0.32% India 79,608 0.66%
#1 LEP Language Spanish 11,038 19.59% Spanish 2,033,088 16.79%
#2 LEP Language Korean 1,241 2.20% Chinese 239,576 1.98%
#3 LEP Language Chinese 245 0.43% Korean 156,343 1.29%
#4 LEP Language Tagalog 156 0.28% Vietnamese 147,472 1.22%
#5 LEP Language Vietnamese 105 0.19% Armenian 87,201 0.72%
#6 LEP Language Persian 102 0.18% Tagalog 86,691 0.72%
#7 LEP Language Hindi 98 0.17% Persian 41,051 0.34%
#8 LEP Language
Other Pacific
Island
Language 41 0.07% Japanese 32,457 0.27%
#9 LEP Language Russian 41 0.07% Russian 28,358 0.23%
#10 LEP Language Arabic 38 0.07% Arabic 23,275 0.19%
Hearing difficulty 1,803 2.92% 303,390 2.52%
Vision difficulty 1,044 1.69% 227,927 1.90%
Cognitive difficulty 2,272 3.68% 445,175 3.70%
Ambulatory difficulty 3,659 5.93% 641,347 5.34%
Self-care difficulty 1,530 2.48% 312,961 2.60%
Independent living difficulty 2,354 3.81% 496,105 4.13%
Male 29,680 49.24% 6,328,434 49.33%
Female 30,594 50.76% 6,500,403 50.67%
Under 18 16,021 26.58% 3,138,867 24.47%
18-64 37,554 62.31% 8,274,594 64.50%
65+ 6,700 11.12% 1,415,376 11.03%
Families with children 6,885 47.85% 1,388,564 47.84%
Race and Ethnicity
La Habra is majority Hispanic (59.67%) with a large population of Whites (25.53%) and non-Hispanic
Asian residents (12.13%). This is a significantly larger Hispanic population percentage than the County as
71
a whole (34.20%). Black residents comprise 1.09% of the population, and non-Hispanic Native Americans
comprise 0.15% of the population. The percentage of multi-race non-Hispanic population is 1.61%, and the
other non-Hispanic population is 0.15%.
National Origin
The most common country of origin for La Habra residents is Mexico, with 16.35% of the city population
comprised of residents from Mexico. The remaining most common countries of origin in La Habra are, in
order, Korea, Philippines, Guatemala, China (excluding Hong Kong & Tibet), Indonesia, India, El Salvador,
Taiwan, and Nicaragua.
Limited English Proficiency
The most commonly spoken language for those in La Habra with Limited English Proficiency (LEP) is
Spanish. The remaining most common languages for those with LEP are, in order, Korean, Chinese,
Tagalog, Vietnamese, Persian, Hindi, Other Pacific Island Languages, Russian, and Arabic.
Disability
The most common type of disability experienced by La Habra residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, independent living difficulty, cognitive
difficulty, hearing difficulty, self-care difficulty, and vision difficulty.
Sex
La Habra residents are 49.24% male and 50.76% female.
Age
The majority of La Habra residents are between 18-64, with 62.31% of residents falling in this group.
26.58% of city residents are under 18, and 11.12% are 65 or older.
Familial Status
Families with children constitute 47.85% of La Habra’s population.
Table 11.2: Demographic Trends, La Habra
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 31,691 60.04% 24,513 41.17% 18,331 30.41%
Black, Non-
Hispanic 422 0.80% 941 1.58% 995 1.65%
Hispanic 17,408 32.98% 28,525 47.91% 33,528 55.63%
Asian or Pacific
Islander, Non-
Hispanic 2,959 5.61% 4,782 8.03% 6,943 11.52%
Native American,
Non-Hispanic 201 0.38% 374 0.63% 325 0.54%
72
National Origin
Foreign-born 10,852 20.55% 16,382 27.53% 17,238 28.60%
LEP
Limited English
Proficiency 7,693 14.57% 12,530 21.06% 13,172 21.85%
Sex
Male 26,272 49.75% 29,148 48.99% 29,680 49.24%
Female 26,539 50.25% 30,349 51.01% 30,594 50.76%
Age
Under 18 13,363 25.30% 17,662 29.69% 16,021 26.58%
18-64 33,885 64.16% 35,363 59.44% 37,554 62.31%
65+ 5,563 10.53% 6,472 10.88% 6,700 11.12%
Family Type
Families with
children 6,424 47.32% 6,353 54.73% 6,885 47.85%
Table 12.1: Demographics, La Palma
(La Palma, Orange County)
Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 4,179 26.43% 4,056,820 31.62%
Black, Non-Hispanic 833 5.27% 859,086 6.70%
Hispanic 2,781 17.59% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 7398 46.78% 1,888,969 14.72%
Native American, Non-Hisp. 83 0.52% 25,102 0.20%
Two+ Races, Non-Hispanic 529 3.35% 267,038 2.08%
Other, Non-Hispanic 11 0.07% 30,960 0.24%
#1 country of origin Korea 1,292 24.53% Mexico 1,735,902 14.34%
#2 country of origin India 803 15.25% Philippines 288,529 2.38%
#3 country of origin Philippines 592 11.24% El Salvador 279,381 2.31%
#4 country of origin Mexico 532 10.10% Vietnam 234,251 1.93%
#5 country of origin Vietnam 499 9.47% Korea 224,370 1.85%
#6 country of origin Taiwan 430 8.16% Guatemala 188,854 1.56%
#7 country of origin
China,
excluding
Hong Kong
and Taiwan
191
3.63%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin Pakistan 152 2.89% Iran 133,596 1.10%
#9 country of origin Cambodia 67 1.27% Taiwan 87,643 0.72%
#10 country of origin Romania 63 1.20% India 79,608 0.66%
73
#1 LEP Language Korean 1,115 7.42% Spanish 2,033,088 16.79%
#2 LEP Language
Spanish or
Spanish
Creole
675
4.49% Chinese 239,576 1.98%
#3 LEP Language Chinese 490 3.26% Korean 156,343 1.29%
#4 LEP Language
African
languages
191
1.27% Vietnamese 147,472 1.22%
#5 LEP Language Tagalog 161 1.07% Armenian 87,201 0.72%
#6 LEP Language Vietnamese 109 0.73% Tagalog 86,691 0.72%
#7 LEP Language Gujarati 90 0.60% Persian 41,051 0.34%
#8 LEP Language Japanese 78 0.52% Japanese 32,457 0.27%
#9 LEP Language Arabic 74 0.49% Russian 28,358 0.23%
#10 LEP Language
Other Indic
languages
69
0.46% Arabic 23,275 0.19%
Hearing difficulty 421 2.7% 303,390 2.52%
Vision difficulty 262 1.7% 227,927 1.90%
Cognitive difficulty 476 3.1% 445,175 3.70%
Ambulatory difficulty 825 5.4% 641,347 5.34%
Self-care difficulty 496 3.3% 312,961 2.60%
Independent living difficulty 547 4.2% 496,105 4.13%
Male 7,673 48.54% 6,328,434 49.33%
Female 8,135 51.46% 6,500,403 50.67%
Under 18 2,866 18.13% 3,138,867 24.47%
18-64 10,101 63.90% 8,274,594 64.50%
65+ 2,841 17.97% 1,415,376 11.03%
Families with children 3,999 81.5% 1,388,564 47.84%
Race and Ethnicity
La Palma has a high Asian or Pacific Islander population at 46.78% of the population. White residents make
up 26.43% of the population, Hispanic residents are 17.59%, Black residents are 5.27%, and Native
Americans are 0.52%.
National Origin
The most common countries of origin for foreign-born residents in the city are Korea, at 24.53%, and India,
at 15.25%. The remaining most common countries for foreign -born residents, in order, are the Philippines,
Mexico, Vietnam, Taiwan, China excluding Hong Kong and Taiwan, Pakistan, Cambodia, and Romania.
Limited English Proficiency
The most commonly spoken language for those in La Palma with Limited English Proficiency (LEP) is
Korean. The remaining most common languages for those with LEP are, in order, Spanish or Spanish
Creole, Chinese, African languages, Tagalog, Vietnamese, Guajarati, Japanese, Arabic, and Other Indic
Languages.
74
Disability
The most common type of disability experienced by La Palma residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, independent living difficulty, self-care
difficulty, cognitive difficulty, hearing difficulty, and vision difficulty.
Sex
La Palma residents are 48.54% male and 51.46% female.
Age
The majority of La Palma residents are between 18-64, with 63.90% of residents falling in this group.
18.13% of city residents are under 18, and 17.97% are 65 or older.
Familial Status
Families with children constitute 81.5% of La Palma’s population.
Table 13.1: Demographics, Laguna Niguel
(Laguna Niguel, CA CDBG)
Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 43,496 66.48% 4,056,820 31.62%
Black, Non-Hispanic 1,238 1.89% 859,086 6.70%
Hispanic 11,021 16.84% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 6,613 10.11% 1,888,969 14.72%
Native American, Non-Hisp. 74 0.11% 25,102 0.20%
Two+ Races, Non-Hispanic 2,176 3.42% 267,038 2.08%
Other, Non-Hispanic 119 0.19% 30,960 0.24%
#1 country of origin Iran 2,065 3.16% Mexico 1,735,902 14.34%
#2 country of origin Mexico 1,785 2.73% Philippines 288,529 2.38%
#3 country of origin
China excl.
Hong Kong
& Taiwan 865 1.32% El Salvador 279,381 2.31%
#4 country of origin Philippines 786 1.20% Vietnam 234,251 1.93%
#5 country of origin El Salvador 693 1.06% Korea 224,370 1.85%
#6 country of origin Taiwan 629 0.96% Guatemala 188,854 1.56%
#7 country of origin Canada 583 0.89%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin Korea 438 0.67% Iran 133,596 1.10%
#9 country of origin Egypt 407 0.62% Taiwan 87,643 0.72%
#10 country of origin Germany 320 0.49% India 79,608 0.66%
#1 LEP Language Spanish 2,022 3.36% Spanish 2,033,088 16.79%
#2 LEP Language Persian 994 1.65% Chinese 239,576 1.98%
#3 LEP Language Chinese 503 0.84% Korean 156,343 1.29%
#4 LEP Language Vietnamese 194 0.32% Vietnamese 147,472 1.22%
75
#5 LEP Language Korean 185 0.31% Armenian 87,201 0.72%
#6 LEP Language French 145 0.24% Tagalog 86,691 0.72%
#7 LEP Language Japanese 79 0.13% Persian 41,051 0.34%
#8 LEP Language
Other Slavic
Language 70 0.12% Japanese 32,457 0.27%
#9 LEP Language Tagalog 59 0.10% Russian 28,358 0.23%
#10 LEP Language Russian 57 0.09% Arabic 23,275 0.19%
Hearing difficulty 1,815 2.78% 303,390 2.52%
Vision difficulty 807 1.23% 227,927 1.90%
Cognitive difficulty 1,965 3.00% 445,175 3.70%
Ambulatory difficulty 1,943 2.97% 641,347 5.34%
Self-care difficulty 938 1.43% 312,961 2.60%
Independent living difficulty 1,910 2.92% 496,105 4.13%
Male 30,893 48.50% 6,328,434 49.33%
Female 32,803 51.50% 6,500,403 50.67%
Under 18 14,428 22.65% 3,138,867 24.47%
18-64 41,100 64.53% 8,274,594 64.50%
65+ 8,168 12.82% 1,415,376 11.03%
Families with children 7,796 44.73% 1,388,564 47.84%
Race and Ethnicity
Laguna Niguel is majority White (66.48%) with sizable minority populations of Hispanics (16.84%) and
non-Hispanic Asian residents (10.11%) This is a significantly larger White population than the county as a
whole (41.40%). Black residents comprise 1.89% of the population, and non-Hispanic Native Americans
comprise 0.11% of the population. The percentage of multi-race non-Hispanic population is 3.42%, and the
other non-Hispanic population is 0.19%.
National Origin
The most common country of origin for Laguna Niguel residents is Iran, with 3.16% of the city population
comprised of residents from Iran. This is distinct from the most common country of origin for county
residents overall (Mexico). The remaining most common countries of origin in Laguna Niguel are, in order,
Mexico, China (excluding Hong Kong & Taiwan), Philippines, El Salvador, Taiwan, Canada, Korea, Egypt,
and Germany.
Limited English Proficiency
The most commonly spoken language for those in Laguna Niguel with Limited English Proficiency (LEP)
is Spanish. The remaining most common languages for those with LEP are, in order, Persian, Chinese,
Vietnamese, Korean, French, Japanese, Other Slavic Languages, Tagalog, and Russian.
76
Disability
The most common type of disability experienced by Laguna Niguel residents is cognitive difficulty. The
remaining most common disabilities are, in order of prevalence, ambulatory difficulty, independent living
difficulty, hearing difficulty, self-care difficulty, and vision difficulty.
Sex
Laguna Niguel residents are 48.50% male and 51.50% female.
Age
The majority of Laguna Niguel residents are between 18-64, with 64.53% of residents falling in this group.
22.65% of city residents are under 18, and 12.82% are 65 or older.
Familial Status
Families with children constitute 44.73% of Laguna Niguel’s population.
Table 13.2: Demographic Trends, Laguna Niguel
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 37,998 83.58% 49,243 77.33% 46,192 72.52%
Black, Non-
Hispanic 517 1.14% 936 1.47% 966 1.52%
Hispanic 3,422 7.53% 6,591 10.35% 8,842 13.88%
Asian or Pacific
Islander, Non-
Hispanic 3,364 7.40% 5,875 9.23% 7,203 11.31%
Native American,
Non-Hispanic 93 0.20% 310 0.49% 331 0.52%
National Origin
Foreign-born 6,198 13.60% 11,286 17.67% 13,355 20.97%
LEP
Limited English
Proficiency 2,169 4.76% 4,238 6.64% 4,317 6.78%
Sex
Male 22,303 48.94% 31,200 48.85% 30,893 48.50%
Female 23,269 51.06% 32,665 51.15% 32,803 51.50%
Age
Under 18 10,922 23.97% 17,408 27.26% 14,428 22.65%
18-64 31,371 68.84% 41,029 64.24% 41,100 64.53%
77
65+ 3,280 7.20% 5,429 8.50% 8,168 12.82%
Family Type
Families with
children 6,218 48.60% 7,957 53.94% 7,796 44.73%
Table 14.1: Demographics, Lake Forest
(Lake Forest, CA CDBG)
Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 44,160 53.98% 44160 53.98%
Black, Non-Hispanic 1,476 1.80% 1476 1.80%
Hispanic 20,057 24.52% 20057 24.52%
Asian/Pacific Island, Non-
Hispanic 12,740 15.57% 12740 15.57%
Native American, Non-Hisp. 361 0.44% 361 0.44%
Two+ Races, Non-Hispanic 2,393 3.09% 2,393 3.09%
Other, Non-Hispanic 184 0.24% 184 0.24%
#1 country of origin Mexico 4,765 5.82% Mexico 1,735,902 14.34%
#2 country of origin Philippines 2,714 3.32% Philippines 288,529 2.38%
#3 country of origin Vietnam 1,117 1.37% El Salvador 279,381 2.31%
#4 country of origin India 1,055 1.29% Vietnam 234,251 1.93%
#5 country of origin Iran 753 0.92% Korea 224,370 1.85%
#6 country of origin Korea 739 0.90% Guatemala 188,854 1.56%
#7 country of origin El Salvador 704 0.86%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin
China excl.
Hong Kong
and Taiwan 576 0.70% Iran 133,596 1.10%
#9 country of origin Canada 509 0.62% Taiwan 87,643 0.72%
#10 country of origin Guatemala 485 0.59% India 79,608 0.66%
#1 LEP Language Spanish 5,074 6.89% Spanish 5,074 6.89%
#2 LEP Language Vietnamese 684 0.93% Vietnamese 684 0.93%
#3 LEP Language Chinese 483 0.66% Chinese 483 0.66%
#4 LEP Language Tagalog 428 0.58% Tagalog 428 0.58%
#5 LEP Language Korean 396 0.54% Korean 396 0.54%
#6 LEP Language Persian 385 0.52% Persian 385 0.52%
#7 LEP Language Japanese 236 0.32% Japanese 236 0.32%
#8 LEP Language
Other Pacific
Island
Language 205 0.28%
Other Pacific
Island
Language 205 0.28%
#9 LEP Language Arabic 145 0.20% Arabic 145 0.20%
#10 LEP Language
Scandinavian
Language 96 0.13%
Scandinavian
Language 96 0.13%
Hearing difficulty 2,141 2.62% 303,390 2.52%
Vision difficulty 715 0.88% 227,927 1.90%
78
Cognitive difficulty 2,001 2.45% 445,175 3.70%
Ambulatory difficulty 2,705 3.31% 641,347 5.34%
Self-care difficulty 1,371 1.68% 312,961 2.60%
Independent living difficulty 2,451 3.00% 496,105 4.13%
Male 38,359 49.58% 6,328,434 49.33%
Female 39,011 50.42% 6,500,403 50.67%
Under 18 19,017 24.58% 19,017 24.58%
18-64 51,306 66.31% 51,306 66.31%
65+ 7,047 9.11% 7,047 9.11%
Families with children 9,581 48.85% 1,388,564 47.84%
Race and Ethnicity
Lake Forest is majority White (53.98%) with sizable minority populations of Hispanics (24.52%) and non-
Hispanic Asian residents (15.57%) This is a moderately larger White population than the county as a whole
(41.40%). Black residents comprise 1.80% of the population, and non-Hispanic Native Americans comprise
0.44% of the population. The percentage of multi-race non-Hispanic population is 3.09%, and the other
non-Hispanic population is 0.24%.
National Origin
The most common country of origin for Lake Forest residents is Mexico, with 5.82% of the city population
comprised of residents from Mexico. The remaining most common countries of origin in Lake Forest are,
in order, Philippines, Vietnam, India, Iran, Korea, El Salvador, China (excluding Hong Kong & Taiwan),
Canada, and Guatemala.
Limited English Proficiency
The most commonly spoken language for those in Lake Forest with Limited English Proficiency (LEP) is
Spanish. The remaining most common languages for those with LEP are, in order, Vietnamese, Chinese,
Tagalog, Korean, Persian, Japanese, Other Pacific Island Languages, Arabic, and Scandinavian Languages.
Disability
The most common type of disability experienced by Lake Forest residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, independent living difficulty, hearing
difficulty, cognitive difficulty, self-care difficulty, and vision difficulty.
Sex
Lake Forest residents are 49.58% male and 50.42% female.
Age
The majority of Lake Forest residents are between 18-64, with 66.31% of residents falling in this group.
24.58% of city residents are under 18, and 9.11% are 65 or older.
79
Familial Status
Families with children constitute 48.85% of Lake Forest’s population.
Table 14.2: Demographic Trends, Lake Forest
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 42,174 78.97% 50,433 67.52% 43,702 56.48%
Black, Non-
Hispanic 908 1.70% 1,596 2.14% 1,566 2.02%
Hispanic 5,491 10.28% 12,968 17.36% 19,165 24.77%
Asian or Pacific
Islander, Non-
Hispanic 4,560 8.54% 8,665 11.60% 12,232 15.81%
Native American,
Non-Hispanic 178 0.33% 451 0.60% 481 0.62%
National Origin
Foreign-born 7,305 13.69% 14,986 20.06% 17,450 22.55%
LEP
Limited English
Proficiency 3,511 6.58% 7,915 10.59% 8,219 10.62%
Sex
Male 26,304 49.29% 36,511 48.87% 38,359 49.58%
Female 27,061 50.71% 38,202 51.13% 39,011 50.42%
Age
Under 18 13,865 25.98% 21,344 28.57% 19,017 24.58%
18-64 35,856 67.19% 47,998 64.24% 51,306 66.31%
65+ 3,643 6.83% 5,372 7.19% 7,047 9.11%
Family Type
Families with
children 7,705 53.68% 10,230 56.68% 9,581 48.85%
Table 15.1: Demographics, Mission Viejo
(Mission Viejo, CA CDBG)
Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 64,552 66.87% 4,056,820 31.62%
Black, Non-Hispanic 1,312 1.36% 859,086 6.70%
Hispanic 16,350 16.94% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 10,253 10.62% 1,888,969 14.72%
80
Native American, Non-Hisp. 201 0.21% 25,102 0.20%
Two+ Races, Non-Hispanic 3,108 3.36% 267,038 2.08%
Other, Non-Hispanic 185 0.20% 30,960 0.24%
#1 country of origin Mexico 3,664 3.80% Mexico 1,735,902 14.34%
#2 country of origin Iran 2,599 2.69% Philippines 288,529 2.38%
#3 country of origin Philippines 1,653 1.71% El Salvador 279,381 2.31%
#4 country of origin Vietnam 972 1.01% Vietnam 234,251 1.93%
#5 country of origin
China excl.
Hong Kong
& Taiwan 690 0.71% Korea 224,370 1.85%
#6 country of origin Korea 640 0.66% Guatemala 188,854 1.56%
#7 country of origin Taiwan 581 0.60%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin Canada 562 0.58% Iran 133,596 1.10%
#9 country of origin India 374 0.39% Taiwan 87,643 0.72%
#10 country of origin El Salvador 341 0.35% India 79,608 0.66%
#1 LEP Language Spanish 2,626 2.93% Spanish 2,033,088 16.79%
#2 LEP Language Persian 1,187 1.33% Chinese 239,576 1.98%
#3 LEP Language Chinese 635 0.71% Korean 156,343 1.29%
#4 LEP Language Vietnamese 408 0.46% Vietnamese 147,472 1.22%
#5 LEP Language Arabic 264 0.30% Armenian 87,201 0.72%
#6 LEP Language Korean 196 0.22% Tagalog 86,691 0.72%
#7 LEP Language Japanese 184 0.21% Persian 41,051 0.34%
#8 LEP Language Tagalog 112 0.13% Japanese 32,457 0.27%
#9 LEP Language
Other Pacific
Island
Language 95 0.11% Russian 28,358 0.23%
#10 LEP Language Russian 78 0.09% Arabic 23,275 0.19%
Hearing difficulty 3,325 3.46% 303,390 2.52%
Vision difficulty 1,719 1.79% 227,927 1.90%
Cognitive difficulty 3,474 3.61% 445,175 3.70%
Ambulatory difficulty 5,015 5.22% 641,347 5.34%
Self-care difficulty 2,574 2.68% 312,961 2.60%
Independent living difficulty 3,937 4.10% 496,105 4.13%
Male 45,368 49.01% 6,328,434 49.33%
Female 47,192 50.99% 6,500,403 50.67%
Under 18 21,375 23.09% 3,138,867 24.47%
18-64 58,357 63.05% 8,274,594 64.50%
65+ 12,828 13.86% 1,415,376 11.03%
Families with children 10,884 44.01% 1,388,564 47.84%
81
Race and Ethnicity
Mission Viejo is majority White (66.87%) with sizable minority populations of Hispanics (16.94%) and
non-Hispanic Asian residents (10.62%) This is a significantly larger White population than the county as a
whole (41.40%). Black residents comprise 1.36% of the population, and non-Hispanic Native Americans
comprise 0.21% of the population. The percentage of multi-race non-Hispanic population is 3.36%, and the
other non-Hispanic population is 0.20%.
National Origin
The most common country of origin for Mission Viejo residents is Mexico, with 3.80% of the city
population comprised of residents from Mexico. The remaining most common countries of origin in
Mission Viejo are, in order, Iran, Philippines, Vietnam, China (excluding Hong Kong & Taiwan), Korea,
Taiwan, Canada, India, and El Salvador.
Limited English Proficiency
The most commonly spoken language for those in Mission Viejo with Limited English Proficiency (LEP)
is Spanish. The remaining most common languages for those with LEP are, in order, Persian, Chinese,
Vietnamese, Arabic, Korean, Japanese, Tagalog, Other Pacific Island Languages, and Russian.
Disability
The most common type of disability experienced by Mission Viejo residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, independent living difficulty, cogniti ve
difficulty, hearing difficulty, self-care difficulty, and vision difficulty.
Sex
Mission Viejo residents are 49.01% male and 50.99% female.
Age
The majority of Mission Viejo residents are between 18-64, with 63.05% of residents falling in this group.
23.09% of city residents are under 18, and 13.86% are 65 or older.
Familial Status
Families with children constitute 44.01% of Mission Viejo’s population.
Table 15.2: Demographic Trends, Mission Viejo
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 67,490 83.86% 69,945 75.84% 63,297 68.38%
Black, Non-
Hispanic 759 0.94% 1,331 1.44% 1,638 1.77%
Hispanic 6,583 8.18% 11,246 12.19% 16,286 17.60%
82
Asian or Pacific
Islander, Non-
Hispanic 5,327 6.62% 8,512 9.23% 10,597 11.45%
Native American,
Non-Hispanic 198 0.25% 507 0.55% 475 0.51%
National Origin
Foreign-born 10,815 13.44% 15,120 16.39% 16,427 17.75%
LEP
Limited English
Proficiency 4,189 5.21% 6,072 6.58% 6,250 6.75%
Sex
Male 39,987 49.69% 44,952 48.73% 45,368 49.01%
Female 40,480 50.31% 47,294 51.27% 47,192 50.99%
Age
Under 18 22,602 28.09% 26,099 28.29% 21,375 23.09%
18-64 51,800 64.37% 56,701 61.47% 58,357 63.05%
65+ 6,065 7.54% 9,446 10.24% 12,828 13.86%
Family Type
Families with
children 11,971 53.71% 11,488 51.77% 10,884 44.01%
Table 17.1: Demographics, Orange (City)
(Orange, CA CDBG, HOME)
Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 63,146 45.01% 4,056,820 31.62%
Black, Non-Hispanic 2,025 1.44% 859,086 6.70%
Hispanic 55,293 39.41% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 16,243 11.58% 1,888,969 14.72%
Native American, Non-Hisp. 292 0.21% 25,102 0.20%
Two+ Races, Non-Hispanic 2,692 1.92% 267,038 2.08%
Other, Non-Hispanic 258 0.18% 30,960 0.24%
#1 country of origin Mexico 16,969 12.10% Mexico 1,735,902 14.34%
#2 country of origin Vietnam 2,596 1.85% Philippines 288,529 2.38%
#3 country of origin Philippines 2,298 1.64% El Salvador 279,381 2.31%
#4 country of origin Korea 1,039 0.74% Vietnam 234,251 1.93%
#5 country of origin India 986 0.70% Korea 224,370 1.85%
#6 country of origin Guatemala 758 0.54% Guatemala 188,854 1.56%
83
#7 country of origin Taiwan 682 0.49%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin Iran 640 0.46% Iran 133,596 1.10%
#9 country of origin
China excl.
Hong Kong
and Taiwan 558 0.40% Taiwan 87,643 0.72%
#10 country of origin El Salvador 526 0.37% India 79,608 0.66%
#1 LEP Language Spanish 18,642 14.45% Spanish 2,033,088 16.79%
#2 LEP Language Vietnamese 2,048 1.59% Chinese 239,576 1.98%
#3 LEP Language Korean 1,149 0.89% Korean 156,343 1.29%
#4 LEP Language Chinese 779 0.60% Vietnamese 147,472 1.22%
#5 LEP Language Tagalog 313 0.24% Armenian 87,201 0.72%
#6 LEP Language Arabic 264 0.20% Tagalog 86,691 0.72%
#7 LEP Language Japanese 205 0.16% Persian 41,051 0.34%
#8 LEP Language Gujarati 193 0.15% Japanese 32,457 0.27%
#9 LEP Language Cambodian 192 0.15% Russian 28,358 0.23%
#10 LEP Language Persian 185 0.14% Arabic 23,275 0.19%
Hearing difficulty 2,921 2.14% 303,390 2.52%
Vision difficulty 1,841 1.35% 227,927 1.90%
Cognitive difficulty 4,106 3.01% 445,175 3.70%
Ambulatory difficulty 5,357 3.93% 641,347 5.34%
Self-care difficulty 2,762 2.02% 312,961 2.60%
Independent living difficulty 4,334 3.18% 496,105 4.13%
Male 68,542 50.29% 6,328,434 49.33%
Female 67,753 49.71% 6,500,403 50.67%
Under 18 31,745 23.29% 3,138,867 24.47%
18-64 89,676 65.80% 8,274,594 64.50%
65+ 14,874 10.91% 1,415,376 11.03%
Families with children 14,250 45.66% 1,388,564 47.84%
Race and Ethnicity
Orange has a plurality of White residents (45.01%) with significant minority populations of Hispanics
(39.41%) and non-Hispanic Asian residents (11.58%). Black residents comprise 1.44% of the population,
and non-Hispanic Native Americans comprise 0.21% of the population. The percentage of multi-race non-
Hispanic population is 1.92%, and the other non-Hispanic population is 0.18%.
National Origin
The most common country of origin for Orange residents is Mexico, with 12.10% of the city population
comprised of residents from Mexico. The remaining most common countries of origin in Orange are, in
order, Vietnam, Philippines, Korea, India, Guatemala, Taiwan, Iran, China (excluding Hong Kong and
Taiwan), and El Salvador.
84
Limited English Proficiency
The most commonly spoken language for those in Orange with Limited English Proficiency (LEP) is
Spanish. The remaining most common languages for those with LEP are, in order, Vietnamese, Korean,
Chinese, Tagalog, Arabic, Japanese, Gujarati, Cambodian, and Persian.
Disability
The most common type of disability experienced by Orange residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, independent living difficulty, cognitive
difficulty, hearing difficulty, self-care difficulty, and vision difficulty.
Sex
Orange residents are 50.29% male and 49.71% female.
Age
The majority of Orange residents are between 18-64, with 65.80% of residents falling in this group. 23.29%
of city residents are under 18, and 10.91% are 65 or older.
Familial Status
Families with children constitute 45.66% of Orange’s population.
Table 17.2: Demographic Trends, Orange (City)
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 76,480 67.86% 71,105 54.48% 63,698 46.74%
Black, Non-
Hispanic 1,411 1.25% 2,258 1.73% 2,478 1.82%
Hispanic 26,031 23.10% 42,446 32.52% 52,480 38.50%
Asian or Pacific
Islander, Non-
Hispanic 8,193 7.27% 13,081 10.02% 16,512 12.11%
Native American,
Non-Hispanic 421 0.37% 840 0.64% 793 0.58%
National Origin
Foreign-born 22,772 20.22% 33,137 25.40% 35,300 25.90%
LEP
Limited English
Proficiency 15,638 13.88% 22,812 17.49% 24,965 18.32%
Sex
Male 56,489 50.15% 64,927 49.77% 68,542 50.29%
85
Female 56,148 49.85% 65,535 50.23% 67,753 49.71%
Age
Under 18 27,188 24.14% 35,677 27.35% 31,745 23.29%
18-64 75,361 66.91% 81,767 62.67% 89,676 65.80%
65+ 10,089 8.96% 13,018 9.98% 14,874 10.91%
Family Type 76,480 67.86% 71,105 54.48% 63,698 46.74%
Families with
children 1,411 1.25% 2,258 1.73% 2,478 1.82%
Table 18.1: Demographics, Rancho Santa Margarita
(Rancho Santa Margarita, CA
CDBG) Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 31,096 63.36% 4,056,820 31.62%
Black, Non-Hispanic 1,210 2.47% 859,086 6.70%
Hispanic 9,604 19.57% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 5,137 10.47% 1,888,969 14.72%
Native American, Non-Hisp. 0 0.00% 25,102 0.20%
Two+ Races, Non-Hispanic 1,604 3.31% 267,038 2.08%
Other, Non-Hispanic 97 0.20% 30,960 0.24%
#1 country of origin Mexico 1,379 2.81% Mexico 1,735,902 14.34%
#2 country of origin Philippines 901 1.84% Philippines 288,529 2.38%
#3 country of origin El Salvador 475 0.97% El Salvador 279,381 2.31%
#4 country of origin Iran 446 0.91% Vietnam 234,251 1.93%
#5 country of origin
China excl.
Hong Kong
and Taiwan 439 0.89% Korea 224,370 1.85%
#6 country of origin India 356 0.73% Guatemala 188,854 1.56%
#7 country of origin Vietnam 345 0.70%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin Germany 263 0.54% Iran 133,596 1.10%
#9 country of origin Korea 232 0.47% Taiwan 87,643 0.72%
#10 country of origin Argentina 208 0.42% India 79,608 0.66%
#1 LEP Language Spanish 2,183 4.80% Spanish 2,033,088 16.79%
#2 LEP Language Vietnamese 224 0.49% Chinese 239,576 1.98%
#3 LEP Language Korean 223 0.49% Korean 156,343 1.29%
#4 LEP Language Arabic 192 0.42% Vietnamese 147,472 1.22%
#5 LEP Language Tagalog 190 0.42% Armenian 87,201 0.72%
#6 LEP Language Persian 187 0.41% Tagalog 86,691 0.72%
#7 LEP Language Chinese 155 0.34% Persian 41,051 0.34%
#8 LEP Language Japanese 87 0.19% Japanese 32,457 0.27%
#9 LEP Language
Other Slavic
Language 54 0.12% Russian 28,358 0.23%
86
#10 LEP Language German 42 0.09% Arabic 23,275 0.19%
Hearing difficulty 677 1.38% 303,390 2.52%
Vision difficulty 442 0.90% 227,927 1.90%
Cognitive difficulty 838 1.71% 445,175 3.70%
Ambulatory difficulty 1,108 2.26% 641,347 5.34%
Self-care difficulty 477 0.97% 312,961 2.60%
Independent living difficulty 715 1.46% 496,105 4.13%
Male 23,681 48.81% 6,328,434 49.33%
Female 24,839 51.19% 6,500,403 50.67%
Under 18 13,719 28.27% 3,138,867 24.47%
18-64 31,402 64.72% 8,274,594 64.50%
65+ 3,399 7.01% 1,415,376 11.03%
Families with children 7,256 56.76% 1,388,564 47.84%
Race and Ethnicity
Rancho Santa Margarita is majority White (63.36%) with significant minority populations of Hispanics
(19.57%) and non-Hispanic Asian residents (10.47%). This is a significantly larger White population than
the county as a whole (41.40%). Black residents comprise 2.47% of the population, and non -Hispanic
Native Americans comprise 0% of the population. The percentage of multi-race non-Hispanic population
is 3.31%, and the other non-Hispanic population is 0.20%.
National Origin
The most common country of origin for Rancho Santa Margarita residents is Mexico, with 2.81% of the
city population comprised of residents from Mexico. The remaining most common countries of origin in
Rancho Santa Margarita are, in order, Philippines, El Salvador, Iran, China (excluding Hong Kong and
Taiwan), India, Vietnam, Germany, Korea, and Argentina.
Limited English Proficiency
The most commonly spoken language for those in Rancho Santa Margarita with Limited English
Proficiency (LEP) is Spanish. The remaining most common languages for those with LEP are, in order,
Vietnamese, Korean, Arabic, Tagalog, Persian, Chinese, Japanese, Other Slavic Languages, and German.
Disability
The most common type of disability experienced by Rancho Santa Margarita residents is ambulatory
difficulty. The remaining most common disabilities are, in order of prevalence, cognitive difficulty,
independent living difficulty, hearing difficulty, self-care difficulty, and vision difficulty.
Sex
Rancho Santa Margarita residents are 48.81% male and 51.19% female.
87
Age
The majority of Rancho Santa Margarita residents are between 18-64, with 64.72% of residents falling in
this group. 28.27% of city residents are under 18, and 7.01% are 65 or older.
Familial Status
Families with children constitute 56.76% of Rancho Santa Margarita’s population.
Table 18.2: Demographic Trends, Rancho Santa Margarita
1990 Trend2 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 9,721 80.59% 35,728 74.82% 32,644 67.28%
Black, Non-
Hispanic 147 1.22% 1,014 2.12% 1,111 2.29%
Hispanic 1,183 9.81% 6,019 12.60% 8,850 18.24%
Asian or Pacific
Islander, Non-
Hispanic 932 7.73% 4,350 9.11% 5,521 11.38%
Native American,
Non-Hispanic 43 0.36% 325 0.68% 270 0.56%
National Origin
Foreign-born 1,753 14.49% 6,404 13.40% 7,746 15.97%
LEP
Limited English
Proficiency 653 5.40% 2,595 5.43% 2,723 5.61%
Sex
Male 6,055 50.06% 23,527 49.21% 23,681 48.81%
Female 6,041 49.94% 24,281 50.79% 24,839 51.19%
Age
Under 18 3,118 25.78% 15,827 33.10% 13,719 28.27%
18-64 8,519 70.43% 29,814 62.36% 31,402 64.72%
65+ 459 3.79% 2,168 4.53% 3,399 7.01%
Family Type
Families with
children 1,819 54.54% 7,149 64.49% 7,256 56.76%
2 Rancho Santa Margarita was incorporated in 2000 so boundaries prior to incorporation may be different.
88
Table 19.1: Demographics, San Clemente
(San Clemente, CA CDBG)
Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 47,747 73.20% 4,056,820 31.62%
Black, Non-Hispanic 433 0.66% 859,086 6.70%
Hispanic 11,665 17.88% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 2,940 4.51% 1,888,969 14.72%
Native American, Non-Hisp. 75 0.11% 25,102 0.20%
Two+ Races, Non-Hispanic 1,551 2.49% 267,038 2.08%
Other, Non-Hispanic 89 0.14% 30,960 0.24%
#1 country of origin Mexico 2,877 4.41% Mexico 1,735,902 14.34%
#2 country of origin Canada 400 0.61% Philippines 288,529 2.38%
#3 country of origin Iran 363 0.56% El Salvador 279,381 2.31%
#4 country of origin Philippines 321 0.49% Vietnam 234,251 1.93%
#5 country of origin Germany 264 0.40% Korea 224,370 1.85%
#6 country of origin England 202 0.31% Guatemala 188,854 1.56%
#7 country of origin Colombia 198 0.30%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin Korea 179 0.27% Iran 133,596 1.10%
#9 country of origin India 175 0.27% Taiwan 87,643 0.72%
#10 country of origin Poland 162 0.25% India 79,608 0.66%
#1 LEP Language Spanish 2,672 4.47% Spanish 2,033,088 16.79%
#2 LEP Language Vietnamese 103 0.17% Chinese 239,576 1.98%
#3 LEP Language Tagalog 91 0.15% Korean 156,343 1.29%
#4 LEP Language Korean 83 0.14% Vietnamese 147,472 1.22%
#5 LEP Language Persian 74 0.12% Armenian 87,201 0.72%
#6 LEP Language Japanese 60 0.10% Tagalog 86,691 0.72%
#7 LEP Language Chinese 53 0.09% Persian 41,051 0.34%
#8 LEP Language Greek 34 0.06% Japanese 32,457 0.27%
#9 LEP Language Thai 34 0.06% Russian 28,358 0.23%
#10 LEP Language
Other Pacific
Island
Language 17 0.03% Arabic 23,275 0.19%
Hearing difficulty 1,950 3.01% 303,390 2.52%
Vision difficulty 783 1.21% 227,927 1.90%
Cognitive difficulty 1,581 2.44% 445,175 3.70%
Ambulatory difficulty 2,060 3.18% 641,347 5.34%
Self-care difficulty 929 1.43% 312,961 2.60%
Independent living difficulty 1,675 2.59% 496,105 4.13%
Male 31,315 50.27% 6,328,434 49.33%
Female 30,980 49.73% 6,500,403 50.67%
89
Under 18 14,972 24.03% 3,138,867 24.47%
18-64 39,094 62.76% 8,274,594 64.50%
65+ 8,228 13.21% 1,415,376 11.03%
Families with children 7,482 45.56% 1,388,564 47.84%
Race and Ethnicity
San Clemente is majority White (73.20%) with a significant minority population of Hispanics (17.88%).
This is a significantly larger White population than the county as a whole (41.40%). Black residents
comprise 0.66% of the population, and non-Hispanic Native Americans comprise 0.11% of the population.
The percentage of multi-race non-Hispanic population is 2.49%, and the other non-Hispanic population is
0.14%.
National Origin
The most common country of origin for San Clemente residents is Mexico, with 4.41% of the city
population comprised of residents from Mexico. The remaining most common countries of origin in San
Clemente are, in order, Canada, Iran, Philippines, Germany, England, Colombia, Korea, India, and Poland.
Limited English Proficiency
The most commonly spoken language for those in San Clemente with Limited English Proficiency (LEP)
is Spanish. The remaining most common languages for those with LEP are, in order, Vietnamese, Tagalog,
Korean, Persian, Japanese, Chinese, Greek, Thai, and Other Pacific Island Languages.
Disability
The most common type of disability experienced by San Clemente residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, hearing difficulty, independent living
difficulty, cognitive difficulty, self-care difficulty, and vision difficulty.
Sex
San Clemente residents are 50.27% male and 49.73% female.
Age
The majority of San Clemente residents are between 18-64, with 62.76% of residents falling in this group.
24.03% of city residents are under 18, and 13.21% are 65 or older.
Familial Status
Families with children constitute 45.56% of San Clemente’s population.
90
Table 19.2: Demographic Trends, San Clemente
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 35,093 83.45% 40,022 78.55% 47,349 76.01%
Black, Non-
Hispanic 250 0.59% 442 0.87% 577 0.93%
Hispanic 5,435 12.92% 8,028 15.76% 10,518 16.88%
Asian or Pacific
Islander, Non-
Hispanic 1,074 2.55% 1,802 3.54% 3,236 5.19%
Native American,
Non-Hispanic 140 0.33% 419 0.82% 488 0.78%
National Origin
Foreign-born 5,069 12.11% 6,797 13.34% 7,605 12.21%
LEP
Limited English
Proficiency 2,552 6.09% 3,666 7.20% 2,694 4.32%
Sex
Male 21,017 50.19% 26,076 51.18% 31,315 50.27%
Female 20,856 49.81% 24,871 48.82% 30,980 49.73%
Age
Under 18 9,037 21.58% 12,640 24.81% 14,972 24.03%
18-64 27,570 65.84% 31,879 62.57% 39,094 62.76%
65+ 5,267 12.58% 6,428 12.62% 8,228 13.21%
Family Type
Families with
children 4,973 43.73% 4,960 45.52% 7,482 45.56%
Table 20.1: Demographics, San Juan Capistrano
(San Juan Capistrano, Orange
County) Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 20,600 57.30% 4,056,820 31.62%
Black, Non-Hispanic 32 0.09% 859,086 6.70%
Hispanic 13,073 36.37% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 1186 3.30% 1,888,969 14.72%
Native American, Non-Hisp. 140 0.39% 25,102 0.20%
Two+ Races, Non-Hispanic 595 1.66% 267,038 2.08%
Other, Non-Hispanic 322 0.90% 30,960 0.24%
91
#1 country of origin Mexico 5,627 68.92% Mexico 1,735,902 14.34%
#2 country of origin Canada 272 3.33% Philippines 288,529 2.38%
#3 country of origin England 271 3.32% El Salvador 279,381 2.31%
#4 country of origin Peru 191 2.34% Vietnam 234,251 1.93%
#5 country of origin Iran 150 1.84% Korea 224,370 1.85%
#6 country of origin Cuba 149 1.82% Guatemala 188,854 1.56%
#7 country of origin
Philippines
147
1.80%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin
China,
excluding
Hong Kong
and Taiwan
142
1.74% Iran 133,596 1.10%
#9 country of origin India 126 1.54% Taiwan 87,643 0.72%
#10 country of origin Poland 119 1.46% India 79,608 0.66%
#1 LEP Language
Spanish or
Spanish
Creole:
5,935
17.65% Spanish 2,033,088 16.79%
#2 LEP Language Persian: 143 0.43% Chinese 239,576 1.98%
#3 LEP Language Chinese: 102 0.30% Korean 156,343 1.29%
#4 LEP Language
Other Indic
languages:
54
0.16% Vietnamese 147,472 1.22%
#5 LEP Language Vietnamese: 48 0.14% Armenian 87,201 0.72%
#6 LEP Language German: 33 0.10% Tagalog 86,691 0.72%
#7 LEP Language Japanese: 32 0.10% Persian 41,051 0.34%
#8 LEP Language Russian: 29 0.09% Japanese 32,457 0.27%
#9 LEP Language
Mon-
Khmer,
Cambodian:
29
0.09% Russian 28,358 0.23%
#10 LEP Language Tagalog: 28 0.08% Arabic 23,275 0.19%
Hearing difficulty 1,181 3.3% 303,390 2.52%
Vision difficulty 744 2.1% 227,927 1.90%
Cognitive difficulty 1,134 3.4% 445,175 3.70%
Ambulatory difficulty 2,144 6.4% 641,347 5.34%
Self-care difficulty 1,251 3.7% 312,961 2.60%
Independent living difficulty 1,653 6.0% 496,105 4.13%
Male 48.03% 11.0% 6,328,434 49.33%
Female 51.97% 9.4% 6,500,403 50.67%
Under 18 8,381 23.35% 3,138,867 24.47%
18-64 20,925 58.29% 8,274,594 64.50%
65+ 6,593 18.37% 1,415,376 11.03%
Families with children 8,839 72.3% 1,388,564 47.84%
92
Race and Ethnicity
San Juan Capistrano is a majority White city, with 57.30% of residents being White. 0.09% of residents are
Black, 36.37% Hispanic, 3.30% Asian or Pacific Islander, and 0.39% Native American.
National Origin
The most common countries of origin for foreign-born residents in the city is Mexico, at 68.92%. The
remaining most common countries for foreign-born residents, in order, are Canada, England, Peru, Iran,
Cuba, the Philippines, China, excluding Hong Kong and Taiwan, India, and Poland.
Limited English Proficiency
The most commonly spoken language for those in San Juan Capistrano with Limited English Proficiency
(LEP) is Spanish or Spanish Creole. The remaining most common languages for those with LEP are, in
order, Persian, Chinese, other Indic languages, Vietnamese, German, Japanese, Russian, Mon-Khmer
Cambodian, and Tagalog.
Disability
The most common types of disability experienced by San Juan Capistrano residents in order are ambulatory,
independent living, self-care, cognitive, hearing, and vision.
Sex
San Juan Capistrano residents are 48.03% male and 51.97% female.
Age
The majority of residents are between 18-64, with 58.29% of residents falling in this group. 23.35% of city
residents are under 18, and 18.37% are 65 or older.
Familial Status
Families with children constitute 72.3% of the population.
Table 21.1: Demographics, Santa Ana
(Santa Ana, CA CDBG, HOME,
ESG) Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 31,499 9.42% 4,056,820 31.62%
Black, Non-Hispanic 2,716 0.81% 859,086 6.70%
Hispanic 258,449 77.27% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 38,872 11.62% 1,888,969 14.72%
Native American, Non-Hisp. 430 0.13% 25,102 0.20%
Two+ Races, Non-Hispanic 2,184 0.68% 267,038 2.08%
Other, Non-Hispanic 377 0.12% 30,960 0.24%
#1 country of origin Mexico 108,270 32.37% Mexico 108,270 32.37%
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#2 country of origin Vietnam 20,391 6.10% Vietnam 20,391 6.10%
#3 country of origin El Salvador 6,021 1.80% El Salvador 6,021 1.80%
#4 country of origin Guatemala 3,153 0.94% Guatemala 3,153 0.94%
#5 country of origin Philippines 2,234 0.67% Philippines 2,234 0.67%
#6 country of origin
China excl.
Hong Kong
and Taiwan 1,215 0.36%
China excl.
Hong Kong
and Taiwan 1,215 0.36%
#7 country of origin Cambodia 1,211 0.36% Cambodia 1,211 0.36%
#8 country of origin Korea 740 0.22% Korea 740 0.22%
#9 country of origin Honduras 707 0.21% Honduras 707 0.21%
#10 country of origin Peru 494 0.15% Peru 494 0.15%
#1 LEP Language Spanish 123,215 41.06% Spanish 2,033,088 16.79%
#2 LEP Language Vietnamese 13,682 4.56% Chinese 239,576 1.98%
#3 LEP Language Chinese 984 0.33% Korean 156,343 1.29%
#4 LEP Language Tagalog 676 0.23% Vietnamese 147,472 1.22%
#5 LEP Language Cambodian 618 0.21% Armenian 87,201 0.72%
#6 LEP Language Laotian 327 0.11% Tagalog 86,691 0.72%
#7 LEP Language Korean 284 0.09% Persian 41,051 0.34%
#8 LEP Language Japanese 224 0.07% Japanese 32,457 0.27%
#9 LEP Language
Other Indic
Language 222 0.07% Russian 28,358 0.23%
#10 LEP Language
Other Pacific
Island
Language 171 0.06% Arabic 23,275 0.19%
Hearing difficulty 6,745 2.04% 303,390 2.52%
Vision difficulty 9,075 2.74% 227,927 1.90%
Cognitive difficulty 9,177 2.77% 445,175 3.70%
Ambulatory difficulty 11,321 3.42% 641,347 5.34%
Self-care difficulty 5,603 1.69% 312,961 2.60%
Independent living difficulty 9,146 2.76% 496,105 4.13%
Male 164,857 51.05% 6,328,434 49.33%
Female 158,082 48.95% 6,500,403 50.67%
Under 18 99,297 30.75% 3,138,867 24.47%
18-64 201,647 62.44% 8,274,594 64.50%
65+ 21,995 6.81% 1,415,376 11.03%
Families with children 34,031 57.04% 1,388,564 47.84%
Race and Ethnicity
Santa Ana is majority Hispanic (77.27%) with a significant minority population of non-Hispanic Asian
residents (11.62%). This is a significantly larger Hispanic population than the county as a whole (34.20%).
Black residents comprise 0.81% of the population, and non-Hispanic Native Americans comprise 0.13% of
the population. The percentage of multi-race non-Hispanic population is 0.68%, and the other non-Hispanic
population is 0.12%.
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National Origin
The most common country of origin for Santa Ana residents is Mexico, with 32.37% of the city population
comprised of residents from Mexico. The remaining most common countries of origin in Santa Ana are, in
order, Vietnam, El Salvador, Guatemala, Philippines, China (excluding Hong Kong and Taiwan),
Cambodia, Korea, Honduras, and Peru.
Limited English Proficiency
The most commonly spoken language for those in Santa Ana with Limited English Proficiency (LEP) is
Spanish. The remaining most common languages for those with LEP are, in order, Vietnamese, Chinese,
Tagalog, Cambodian, Laotian, Korean, Japanese, Other Indic Languages, and Other Pacific Island
Languages.
Disability
The most common type of disability experienced by Santa Ana residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, cognitive difficulty, independent living
difficulty, vision difficulty, hearing difficulty, and self-care difficulty.
Sex
Santa Ana residents are 51.05% male and 48.95% female.
Age
The majority of Santa Ana residents are between 18-64, with 62.44% of residents falling in this group.
30.75% of city residents are under 18, and 6.81% are 65 or older.
Familial Status
Families with children constitute 57.04% of Santa Ana’s population.
Table 21.2: Demographic Trends, Santa Ana
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 68,937 23.58% 42,837 12.74% 30,994 9.60%
Black, Non-
Hispanic 6,272 2.15% 4,817 1.43% 3,662 1.13%
Hispanic 189,758 64.92% 254,995 75.81% 251,792 77.97%
Asian or Pacific
Islander, Non-
Hispanic 26,112 8.93% 31,510 9.37% 35,171 10.89%
Native American,
Non-Hispanic 671 0.23% 1,333 0.40% 891 0.28%
National Origin
Foreign-born 148,116 50.69% 178,689 53.13% 159,506 49.39%
95
LEP
Limited English
Proficiency 125,596 42.98% 155,759 46.31% 147,471 45.67%
Sex
Male 155,301 53.15% 174,039 51.75% 164,857 51.05%
Female 136,895 46.85% 162,299 48.25% 158,082 48.95%
Age
Under 18 89,063 30.48% 118,041 35.10% 99,297 30.75%
18-64 186,981 63.99% 200,328 59.56% 201,647 62.44%
65+ 16,151 5.53% 17,969 5.34% 21,995 6.81%
Family Type
Families with
children 32,142 58.43% 35,540 64.63% 34,031 57.04%
Table 22: Demographics, Tustin
(Tustin, CA CDBG) Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 24,289 30.36% 4,056,820 31.62%
Black, Non-Hispanic 1,926 2.41% 859,086 6.70%
Hispanic 32,982 41.22% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 17,542 21.93% 1,888,969 14.72%
Native American, Non-Hisp. 418 0.52% 25,102 0.20%
Two+ Races, Non-Hispanic 1,949 2.62% 267,038 2.08%
Other, Non-Hispanic 169 0.23% 30,960 0.24%
#1 country of origin Mexico 11,270 14.09% Mexico 1,735,902 14.34%
#2 country of origin Vietnam 2,115 2.64% Philippines 288,529 2.38%
#3 country of origin India 2,048 2.56% El Salvador 279,381 2.31%
#4 country of origin Philippines 1,677 2.10% Vietnam 234,251 1.93%
#5 country of origin Korea 1,446 1.81% Korea 224,370 1.85%
#6 country of origin
China excl.
Hong Kong
& Taiwan 1,250 1.56% Guatemala 188,854 1.56%
#7 country of origin Taiwan 1,040 1.30%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin Iran 507 0.63% Iran 133,596 1.10%
#9 country of origin Guatemala 405 0.51% Taiwan 87,643 0.72%
#10 country of origin Canada 339 0.42% India 79,608 0.66%
#1 LEP Language Spanish 10,333 14.60% Spanish 2,033,088 16.79%
#2 LEP Language Vietnamese 1,665 2.35% Chinese 239,576 1.98%
#3 LEP Language Korean 844 1.19% Korean 156,343 1.29%
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#4 LEP Language Chinese 816 1.15% Vietnamese 147,472 1.22%
#5 LEP Language Tagalog 400 0.57% Armenian 87,201 0.72%
#6 LEP Language
Other Indic
Language 285 0.40% Tagalog 86,691 0.72%
#7 LEP Language Hindi 218 0.31% Persian 41,051 0.34%
#8 LEP Language Persian 216 0.31% Japanese 32,457 0.27%
#9 LEP Language
Other Asian
Language 183 0.26% Russian 28,358 0.23%
#10 LEP Language Arabic 165 0.23% Arabic 23,275 0.19%
Hearing difficulty 1,749 2.19% 303,390 2.52%
Vision difficulty 1,216 1.52% 227,927 1.90%
Cognitive difficulty 2,308 2.89% 445,175 3.70%
Ambulatory difficulty 2,894 3.63% 641,347 5.34%
Self-care difficulty 1,162 1.46% 312,961 2.60%
Independent living difficulty 2,353 2.95% 496,105 4.13%
Male 36,263 48.83% 6,328,434 49.33%
Female 37,995 51.17% 6,500,403 50.67%
Under 18 19,341 26.05% 3,138,867 24.47%
18-64 48,704 65.59% 8,274,594 64.50%
65+ 6,213 8.37% 1,415,376 11.03%
Families with children 9,226 52.64% 1,388,564 47.84%
Race and Ethnicity
Tustin is majority Hispanic (41.22%) with a significant minority population of White residents (30.36%)
and non-Hispanic Asian residents (21.93%). Black residents comprise 2.41% of the population, and non-
Hispanic Native Americans comprise 0.52% of the population. The percentage of multi-race non-Hispanic
population is 2.62%, and the other non-Hispanic population is 0.23%.
National Origin
The most common country of origin for Tustin residents is Mexico, with 14.09% of the city population
comprised of residents from Mexico. The remaining most common countries of origin in Tustin are, in
order, Vietnam, India, Philippines, Korea, China (excluding Hong Kong and Taiwan), Taiwan, Iran,
Guatemala, and Canada.
Limited English Proficiency
The most commonly spoken language for those in Tustin with Limited English Proficiency (LEP) is
Spanish. The remaining most common languages for those with LEP are, in order, Vietnamese, Korean,
Chinese, Tagalog, Other Indic Language, Hindi, Persian, Other Asian Language, and Arabic.
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Disability
The most common type of disability experienced by Tustin residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, independent living difficulty, cognitive
difficulty, hearing difficulty, vision difficulty, and self-care difficulty.
Sex
Tustin residents are 48.83% male and 51.17% female.
Age
The majority of Tustin residents are between 18-64, with 65.59% of residents falling in this group. 26.05%
of city residents are under 18, and 8.37% are 65 or older.
Familial Status
Families with children constitute 47.84% of Tustin’s population.
Table 22.2: Demographic Trends, Tustin
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 33,203 64.04% 29,936 45.70% 26,741 36.01%
Black, Non-
Hispanic 2,546 4.91% 2,001 3.05% 1,879 2.53%
Hispanic 10,687 20.61% 22,177 33.85% 28,873 38.88%
Asian or Pacific
Islander, Non-
Hispanic 5,105 9.85% 10,452 15.95% 16,240 21.87%
Native American,
Non-Hispanic 197 0.38% 401 0.61% 314 0.42%
National Origin
Foreign-born 11,250 21.67% 21,580 32.92% 24,470 32.95%
LEP
Limited English
Proficiency 6,814 13.13% 13,970 21.31% 14,937 20.12%
Sex
Male 26,403 50.87% 32,163 49.07% 36,263 48.83%
Female 25,502 49.13% 33,386 50.93% 37,995 51.17%
Age
Under 18 12,604 24.28% 17,885 27.28% 19,341 26.05%
18-64 35,509 68.41% 42,998 65.60% 48,704 65.59%
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65+ 3,792 7.31% 4,665 7.12% 6,213 8.37%
Family Type
Families with
children 6,634 51.65% 8,043 53.99% 9,226 52.64%
Table 23.1: Demographics, Westminster
(Westminster, CA CDBG, HOME)
Jurisdiction
(Los Angeles – Long Beach –
Anaheim, CA) Region
Race/Ethnicity # % # %
White, Non-Hispanic 22,450 24.46% 4,056,820 31.62%
Black, Non-Hispanic 797 0.87% 859,086 6.70%
Hispanic 21,783 23.73% 5,700,860 44.44%
Asian/Pacific Island, Non-
Hispanic 43,957 47.89% 1,888,969 14.72%
Native American, Non-Hisp. 384 0.42% 25,102 0.20%
Two+ Races, Non-Hispanic 1,858 2.07% 267,038 2.08%
Other, Non-Hispanic 121 0.13% 30,960 0.24%
#1 country of origin Vietnam 26,801 29.20% Mexico 1,735,902 14.34%
#2 country of origin Mexico 7,184 7.83% Philippines 288,529 2.38%
#3 country of origin Philippines 906 0.99% El Salvador 279,381 2.31%
#4 country of origin
China excl.
Hong Kong
& Taiwan 467 0.51% Vietnam 234,251 1.93%
#5 country of origin Egypt 428 0.47% Korea 224,370 1.85%
#6 country of origin Cambodia 379 0.41% Guatemala 188,854 1.56%
#7 country of origin Peru 294 0.32%
China excl.
Hong Kong &
Taiwan 174,424 1.44%
#8 country of origin Laos 277 0.30% Iran 133,596 1.10%
#9 country of origin Taiwan 273 0.30% Taiwan 87,643 0.72%
#10 country of origin Korea 254 0.28% India 79,608 0.66%
#1 LEP Language Vietnamese 22,514 26.32% Spanish 2,033,088 16.79%
#2 LEP Language Spanish 6,446 7.53% Chinese 239,576 1.98%
#3 LEP Language Chinese 1,026 1.20% Korean 156,343 1.29%
#4 LEP Language Korean 234 0.27% Vietnamese 147,472 1.22%
#5 LEP Language Cambodian 223 0.26% Armenian 87,201 0.72%
#6 LEP Language Tagalog 213 0.25% Tagalog 86,691 0.72%
#7 LEP Language Laotian 202 0.24% Persian 41,051 0.34%
#8 LEP Language Japanese 154 0.18% Japanese 32,457 0.27%
#9 LEP Language Arabic 147 0.17% Russian 28,358 0.23%
#10 LEP Language Armenian 77 0.09% Arabic 23,275 0.19%
Hearing difficulty 3,399 3.71% 303,390 2.52%
Vision difficulty 1,959 2.14% 227,927 1.90%
Cognitive difficulty 5,517 6.02% 445,175 3.70%
Ambulatory difficulty 6,308 6.89% 641,347 5.34%
Self-care difficulty 2,964 3.24% 312,961 2.60%
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Independent living difficulty 5,665 6.19% 496,105 4.13%
Male 44,523 49.57% 6,328,434 49.33%
Female 45,295 50.43% 6,500,403 50.67%
Under 18 21,014 23.40% 3,138,867 24.47%
18-64 56,236 62.61% 8,274,594 64.50%
65+ 12,568 13.99% 1,415,376 11.03%
Families with children 9,079 44.54% 1,388,564 47.84%
Race and Ethnicity
Westminster is majority non-Hispanic Asian residents (47.89%) with a significant minority population of
White residents (24.46%) and Hispanic residents (23.73%). This is a significantly higher percentage of non-
Hispanic Asian residents than Orange County overall (19.78%). Black residents comprise 0.87% of the
population, and non-Hispanic Native Americans comprise 0.42% of the population. The percentage of
multi-race non-Hispanic population is 2.07%, and the other non-Hispanic population is 0.13%.
National Origin
The most common country of origin for Westminster residents is Vietnam, with 29.20% of the city
population comprised of residents from Vietnam. This is distinct from the most common country of origin
for all Orange County residents (Mexico). The remaining most common countries of origin in Westminster
are, in order, Mexico, Philippines, China (excluding Hong Kong and Taiwan), Egypt, Cambodia, Peru,
Laos, Taiwan, and Korea.
Limited English Proficiency
The most commonly spoken language for those in Westminster with Limited English Proficiency (LEP) is
Vietnamese. This is distinct from the most common LEP language overall in Orange County (Spanish).
The remaining most common languages for those with LEP are, in order, Spanish, Chinese, Korean,
Cambodian, Tagalog, Laotian, Japanese, Arabic, and Armenian.
Disability
The most common type of disability experienced by Westminster residents is ambulatory difficulty. The
remaining most common disabilities are, in order of prevalence, independent living difficulty, cognitive
difficulty, hearing difficulty, self-care difficulty, and vision difficulty.
Sex
Westminster residents are 49.57% male and 50.43% female.
Age
The majority of Westminster residents are between 18-64, with 62.61% of residents falling in this group.
23.40% of city residents are under 18, and 13.99% are 65 or older.
100
Familial Status
Families with children constitute 44.54% of Westminster’s population.
Table 23.2: Demographic Trends, Westminster
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicity # % # % # %
White, Non-
Hispanic 45,552 57.77% 32,550 36.89% 23,627 26.31%
Black, Non-
Hispanic 775 0.98% 985 1.12% 1,047 1.17%
Hispanic 15,131 19.19% 19,678 22.30% 21,709 24.17%
Asian or Pacific
Islander, Non-
Hispanic 16,918 21.45% 33,809 38.32% 42,829 47.68%
Native American,
Non-Hispanic 357 0.45% 756 0.86% 454 0.51%
National Origin
Foreign-born 22,718 28.86% 37,094 42.04% 39,808 44.32%
LEP
Limited English
Proficiency 16,594 21.08% 28,427 32.22% 30,447 33.90%
Sex
Male 40,162 51.03% 44,216 50.11% 44,523 49.57%
Female 38,546 48.97% 44,019 49.89% 45,295 50.43%
Age
Under 18 19,745 25.09% 23,821 27.00% 21,014 23.40%
18-64 51,871 65.90% 54,970 62.30% 56,236 62.61%
65+ 7,093 9.01% 9,443 10.70% 12,568 13.99%
Family Type
Families with
children 9,049 46.90% 9,753 49.37% 9,079 44.54%
Los Angeles – Long Beach – Anaheim, CA Region
Religion
The most common religious group is Roman Catholic. Approximately 797,473 County residents identify
as Roman Catholic, which is 26.49% of the total population. The second most common is
nondenominational, which accounts for 122,205 residents, or 4.06% of the total population. Southern
Baptist Convention and Mormon account for 2.30% and 2.22% of the population respectively. The
101
remaining religions, which account for less than 1% of the total county population, are Assemblies of God,
Buddhism, Muslim, Presbyterian, Lutheran, and Church of Christ.
Table 24: Demographic Trends, Region
1990 Trend 2000 Trend 2010 Trend
Race/Ethnicit
y # % # % # %
White, Non-
Hispanic 5,166,768 45.86% 4,417,595 35.72% 4,056,820 31.62%
Black, Non-
Hispanic 971,105 8.62% 1,001,103 8.10% 932,431 7.27%
Hispanic 3,914,001 34.74% 5,117,049 41.38% 5,700,862 44.44%
Asian or
Pacific
Islander, Non-
Hispanic 1,146,691 10.18% 1,651,006 13.35% 2,046,118 15.95%
Native
American,
Non-Hispanic 36,210 0.32% 66,029 0.53% 54,362 0.42%
National
Origin
Foreign-born 3,469,567 30.80% 4,299,323 34.77% 4,380,850 34.15%
LEP
Limited
English
Proficiency 2,430,630 21.57% 3,132,663 25.33% 3,053,077 23.80%
Sex
Male 5,626,077 49.94% 6,107,286 49.39% 6,328,434 49.33%
Female 5,640,051 50.06% 6,258,058 50.61% 6,500,403 50.67%
Age
Under 18 2,911,031 25.84% 3,518,245 28.45% 3,138,867 24.47%
18-64 7,280,517 64.62% 7,641,369 61.80% 8,274,594 64.50%
65+ 1,074,580 9.54% 1,205,730 9.75% 1,415,376 11.03%
Family Type
Families with
children 1,318,473 50.20% 1,143,222 53.64% 1,388,564 47.84%
Over time, the non-Hispanic white population has dropped over time since 1990 both measured both by
percentage change and overall population decline. The white population has dropped by 21.48% since 1990,
and has decreased by 1,109,948 people over that span. The white population has gone from representing
45.86% of the region’s population to representing 31.62% of the region’s population. By contrast, the
Hispanic population in Orange County has grown significantly: 1,786,859 more people identify as Hispanic
currently as compared to 1990, and Hispanic residents now represent 44.44% of the region’s population,
up from 34.74% in 1990. The Asian, non-Hispanic population has also increased over this time period,
102
albeit at a slower pace than the Hispanic population: 237,963 more residents are non-Hispanic Asians, and
their proportion of the region’s population has increased from 10.18% to 14.72% today. The Black
population has decreased slightly (from 8.62% to 6.70%), while the Native American population has
remained relatively flat (0.32% to 0.20%).
The percentage of population with LEP has seen an increase of approximately 2%. The percentage of the
population that are families with children has decreased slightly, by approximately 2.5% since 1990. The
population of residents under 18 has remained essentially constant. The population of residents from 18-64
has also remained basically constant, while the percentage of those over 65 years of age has increased
slightly (by approximately 1.5%).
103
A. General Issues
i. Segregation/Integration
1. Analysis
a. Describe and compare segregation levels in the jurisdiction and region. Identify the
racial/ethnic groups that experience the highest levels of segregation.
Dissimilarity Index
Value Level of Segregation
Dissimilarity Index
Value (0-100)
0-40 Low Segregation
41-54 Moderate Segregation 55-100 High Segregation
The tables below reflect the Dissimilarity Indices for each jurisdiction. The Dissimilarity Index
measures the percentage of a certain group’s population that would have to move to a different
census tract in order to be evenly distributed within a city or metropolitan area in relation to another
group. The higher the Dissimilarity Index, the higher the extent of the segregation.
Overall, Orange County experiences moderate levels of segregation, with significant variances in
some individual jurisdictions. The Non-White/White value is 44.71, Black/White 46.98,
Hispanic/White 52.82, and Asian or Pacific Islander/White 43.19. These values have all increased
sharply since 2010, though values had remained consistent from 2000 and 2010. Jurisdictional
values tend to indicate low levels of segregation in comparison to the county as a whole, but this
is due to the spatial distribution of populations across different jurisdictions rather than within
different jurisdictions.
Areas in central Orange County have the highest Dissimilarity Index values for their populations.
The Cities of Orange, Santa Ana and Tustin are particularly affected. The Black/White index value
for the City of Orange is 42.35, as opposed to a 22.63 Non-White/White index value. Neighboring
Santa Ana has a 50.58 Non-White/White index value, and Tustin 48.19. Hispanic residents are
affected in Santa Ana, with Dissimilarity Index value of 52.62, and Black and Hispanic residents
are especially segregated with values of 66.02 and 57.43, respectively. These measures are relevant
because Hispanic residents are more concentrated in Anaheim and Santa Ana, compared to the rest
of the county.
Black residents face consistently high Dissimilarity Index values, especially compared to Non-
White/White or other populations’ index values. They experience higher levels of segregation in
La Habra, Laguna Niguel, Mission Viejo, Orange and Santa Ana, and especially high levels in
Newport Beach and Tustin, at 67.68 and 66.02, respectively. This is not represented in county-
wide Dissimilarity Index values likely due to Black residents being comparatively more evenly
distributed throughout the county than in individual jurisdictions.
104
Hispanic residents also face somewhat high Dissimilarity Index values, though values in individual
jurisdictions are typically below the 40.00 threshold. Noticeable differences are evident in Costa
Mesa, Fountain Valley, Santa Ana, and Tustin, which have relatively high levels of segregation.
In Santa Ana and Tustin, Dissimilarity Index values for Hispanic residents in relation to White
residents are 52.62 and 57.43 respectively.
Dissimilarity Index values for Asian or Pacific Islander residents vary. Some jurisdictions have
lower values, and others higher. In Garden Grove, values for Asian or Pacific Islanders are higher
than for other groups.
Table 1 Dissimilarity Index Values by Race and Ethnicity for Orange County
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 30.38 34.71 33.58 44.71
Black/White 32.60 33.63 32.27 46.98
Hispanic/White 36.13 41.08 38.18 52.82
Asian or Pacific Islander/White 32.58 34.31 34.82 43.19
Table 2: Dissimilarity Index Values by Race and Ethnicity for Aliso Viejo
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White N/A N/A N/A 13.3
Black/White N/A 12.6 12.3 50.89
Hispanic/White N/A 11.6 20.4 22.57
Asian or Pacific Islander/White N/A 6.1 8.1 14.98
Table 3: Dissimilarity Index Values by Race and Ethnicity for Anaheim
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend
2010
Trend Current
Non-White/White 29.37 31.67 31.72 31.70
Black/White 22.24 26.01 27.90 39.71
Hispanic/White 38.81 40.34 38.84 38.40
Asian or Pacific Islander/White 13.26 17.36 21.59 25.16
Table 4: Dissimilarity Index Values by Race and Ethnicity for Buena Park
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 18.17 22.07 21.40 23.51
Black/White 21.76 23.51 25.25 42.66
Hispanic/White 26.64 33.21 30.85 36.71
105
Asian or Pacific Islander/White 11.56 13.87 16.44 15.49
Table 5: Dissimilarity Index Values by Race and Ethnicity for Costa Mesa
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 29.76 36.82 34.36 35.80
Black/White 30.21 27.11 27.72 44.23
Hispanic/White 34.42 45.28 41.93 42.06
Asian or Pacific Islander/White 30.34 31.93 30.60 42.65
Table 6: Dissimilarity Index Values by Race and Ethnicity for Fountain Valley
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 14.25 22.27 23.54 34.00
Black/White 27.24 27.57 26.28 39.71
Hispanic/White 21.64 28.33 29.59 42.15
Asian or Pacific Islander/White 13.85 22.12 23.58 33.68
Table 7: Dissimilarity Index Values by Race and Ethnicity for Fullerton
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 25.53 31.15 30.52 29.76
Black/White 30.59 31.83 26.53 28.59
Hispanic/White 33.72 39.98 38.28 35.96
Asian or Pacific Islander/White 30.41 33.48 35.24 33.56
Table 8: Dissimilarity Index Values by Race and Ethnicity for Garden Grove
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 25.06 31.79 32.16 34.93
Black/White 22.18 23.11 23.45 35.03
Hispanic/White 27.67 32.64 33.20 36.26
Asian or Pacific Islander/White 27.45 34.98 33.98 38.21
Table 9: Dissimilarity Index Values by Race and Ethnicity for Huntington Beach
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 21.11 23.44 21.58 25.52
Black/White 21.45 19.99 24.21 37.58
Hispanic/White 28.10 33.37 30.09 28.86
Asian or Pacific Islander/White 22.86 20.11 18.25 26.26
Table 10: Dissimilarity Index Values by Race and Ethnicity for Irvine
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 16.50 21.56 18.01 19.24
Black/White 43.00 27.84 19.37 39.54
Hispanic/White 21.99 22.81 17.89 26.58
Asian or Pacific Islander/White 18.18 22.57 18.73 73.67
106
Table 11: Dissimilarity Index Values by Race and Ethnicity for La Habra
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 28.16 26.70 24.12 25.08
Black/White 12.56 13.23 19.35 40.12
Hispanic/White 33.91 30.92 28.56 30.22
Asian or Pacific Islander/White 40.47 38.68 36.53 27.99
Table 12: Dissimilarity Index Values by Race and Ethnicity for La Palma
Racial/Ethnic Dissimilarity Index Current
Non-White/White 9.67
Black/White 17.98
Hispanic/White 1.93
Asian or Pacific Islander/White 13.62
Table 13: Dissimilarity Index Values by Race and Ethnicity for Laguna Niguel
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 9.17 12.98 16.34 20.29
Black/White 13.82 22.75 16.24 45.64
Hispanic/White 13.34 20.76 22.79 27.18
Asian or Pacific Islander/White 13.37 12.68 13.82 18.94
Table 14: Dissimilarity Index Values by Race and Ethnicity for Lake Forest
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 9.39 15.38 17.28 19.97
Black/White 12.43 12.16 9.52 26.59
Hispanic/White 15.72 26.10 27.63 30.04
Asian or Pacific Islander/White 8.84 11.06 13.46 17.18
Table 15: Dissimilarity Index Values by Race and Ethnicity for Mission Viejo
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 13.67 15.18 15.75 29.15
Black/White 18.03 20.63 16.83 43.54
Hispanic/White 12.26 18.75 20.96 20.00
Asian or Pacific Islander/White 20.00 16.83 13.98 16.84
able 16: Dissimilarity Index Values by Race and Ethnicity for Orange (City)
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 23.79 24.21 22.68 22.63
Black/White 24.12 24.45 24.72 42.35
Hispanic/White 30.24 29.79 26.90 27.94
Asian or Pacific Islander/White 19.54 22.34 22.70 27.55
107
Table 17: Dissimilarity Index Values by Race and Ethnicity for Rancho Santa Margarita
Racial/Ethnic Dissimilarity Index 1990 Trend3 2000 Trend 2010 Trend Current
Non-White/White 5.43 12.26 14.07 18.27
Black/White 7.18 12.64 13.35 23.56
Hispanic/White 5.73 19.52 23.13 24.53
Asian or Pacific Islander/White 6.70 8.56 9.55 17.95
Table 18: Dissimilarity Index Values by Race and Ethnicity for San Clemente
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 21.89 25.93 16.76 17.23
Black/White 13.86 19.08 14.93 37.45
Hispanic/White 27.16 32.90 23.71 21.95
Asian or Pacific Islander/White 14.66 14.76 16.56 27.33
Table 20: Dissimilarity Index Values by Race and Ethnicity for Santa Ana
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 47.73 49.25 46.51 50.58
Black/White 36.60 28.03 25.25 42.30
Hispanic/White 53.07 53.60 50.02 52.62
Asian or Pacific Islander/White 43.05 46.79 46.94 43.95
Table 21: Dissimilarity Index Values by Race and Ethnicity for Tustin
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 26.33 36.73 32.93 48.19
Black/White 42.49 35.11 29.03 66.02
Hispanic/White 31.14 48.19 42.55 57.43
Asian or Pacific Islander/White 19.20 17.74 19.76 28.73
Table 22: Dissimilarity Index Values by Race and Ethnicity for Westminster
Racial/Ethnic Dissimilarity Index 1990 Trend 2000 Trend 2010 Trend Current
Non-White/White 24.58 28.05 31.59 11.95
Black/White 11.56 14.18 17.62 35.61
Hispanic/White 30.31 29.74 31.83 9.64
Asian or Pacific Islander/White 23.15 29.73 34.65 16.31
b. Explain how these segregation levels have changed over time (since 1990).
In addition to the Dissimilarity Index, social scientists also use the Isolation and Exposure Indices
to measure segregation. These indices, when taken together, capture the neighborhood
demographics experienced, on average, by members of a particular racial or ethnic group within a
city or metropolitan area. The Isolation Index measures what percentage of the census tract in
which a person of a certain racial identity lives is comprised of other persons of that same
racial/ethnic group. Values for the Isolation Index range from 0 to 100. The Exposure Index is a
group's exposure to all racial groups. Values for the Exposure Index also range from 0 to 100. A
3 Rancho Santa Margarita was incorporated in 2000 so boundaries prior to incorporation may be different.
108
larger value means that the average group member lives in a census tract with a higher percentage
of people from another group.
Table 23 Isolation Index Values by Race and Ethnicity, Orange County
Isolation Index Current
White/White 55.16
Black/Black 3.32
Hispanic/Hispanic 52.81
Asian/Asian 31.84
Table 24: Aliso Viejo
Isolation Index 1980 1990 2000 2010 Current
White/White N/A N/A 71.3 62.6 62.94
Black/Black N/A N/A 2.7 2.7 3.97
Hispanic/Hispanic N/A N/A 12.5 21.7 19.52
Asian/Asian N/A N/A 13.5 18.5 16.32
Table 25: Anaheim
Isolation Index 1980 1990 2000 2010 Current
White/White 78.8 62.1 44.9 37.1 35.8
Black/Black 1.8 3.1 3.6 3.6 3.61
Hispanic/Hispanic 28.6 44.8 58.2 61.7 59.25
Asian/Asian 4.4 10.8 16.5 20 22.66
Table 26: Buena Park
Isolation Index 1980 1990 2000 2010 Current
White/White 76.3 60.3 42.2 31.8 27.37
Black/Black 1.6 3.1 4.7 4.6 5.08
Hispanic/Hispanic 20 29 40.1 45.2 49.04
Asian/Asian 5.2 15.1 24.5 31.6 34.19
Table 27: Costa Mesa
Isolation Index 1980 1990 2000 2010 Current
White/White 84.1 74.8 64.6 59.7 57.38
Black/Black 1.6 1.8 2 2.1 3.18
Hispanic/Hispanic 14.9 29.3 47.7 49.2 45.35
Asian/Asian 6.4 9.7 12.7 14.3 22.27
Table 28: Fountain Valley
Isolation Index 1980 1990 2000 2010 Current
White/White 83.9 73.4 60.6 52.4 45.93
Black/Black 0.8 1.2 1.7 1.5 0.75
Hispanic/Hispanic 7.1 9.2 12.4 15.1 29.93
109
Asian/Asian 7.6 18.6 30.7 38.8 42.97
Table 29: Fullerton
Isolation Index 1980 1990 2000 2010 Current
White/White 81 68.4 55.9 45.6 40.27
Black/Black 2.8 3 3.1 3 3.19
Hispanic/Hispanic 24.8 33.3 43.7 47.8 47.56
Asian/Asian 7 21 31.4 41 38.19
Table 30: Garden Grove
Isolation Index 1980 1990 2000 2010 Current
White/White 80.4 59 42 34.3 32.11
Black/Black 1.1 1.7 1.8 1.5 2.54
Hispanic/Hispanic 25.4 30.4 39.4 43.4 44.37
Asian/Asian 7.5 24.6 39.8 45.4 45.88
Table 31: Huntington Beach
Isolation Index 1980 1990 2000 2010 Current
White/White 85.4 80.5 74.4 69.8 63.99
Black/Black 1 1.1 1.2 1.7 2.68
Hispanic/Hispanic 9.5 18.3 26.7 26.9 27.39
Asian/Asian 5.9 9.7 12.6 14.8 21.32
Table 32: Irvine
Isolation Index 1980 1990 2000 2010 Current
White/White 84.3 74.5 59.2 47 46.09
Black/Black 3.6 4.4 2.2 2.5 3.19
Hispanic/Hispanic 7.1 7 8 10.4 15.57
Asian/Asian 8.4 19.4 35.1 44.6 41.54
Table 33: La Habra
Isolation Index 1980 1990 2000 2010 Current
White/White 76.6 64.7 46.5 34.7 35.40
Black/Black 0.4 1 1.8 2 1.79
Hispanic/Hispanic 31.2 41.9 55.4 62.7 62.64
Asian/Asian 2.8 5.8 15.4 22.5 18.18
Table 34: Laguna Niguel
Isolation Index 1980 1990 2000 2010 Current
White/White 92.7 83.2 77.9 73.4 68.74
Black/Black 0.4 1.4 1.8 1.7 3.98
Hispanic/Hispanic 4.4 8.4 12.2 16.7 20.88
110
Asian/Asian 2.2 8.2 9.8 12.3 11.02
Table 35: Lake Forest
Isolation Index 1980 1990 2000 2010 Current
White/White n/a n/a 67.9 59.3 54.69
Black/Black n/a n/a 2.4 2.2 2.95
Hispanic/Hispanic n/a n/a 23.1 30.7 32.32
Asian/Asian n/a n/a 11.6 16.2 17.49
Table 36: Mission Viejo
Isolation Index 1980 1990 2000 2010 Current
White/White 89.8 85.2 76.8 70.1 67.55
Black/Black 0.8 1 1.8 2 3.11
Hispanic/Hispanic 5.9 8.2 15.6 20.8 21.55
Asian/Asian 3.4 7 10.2 12.5 12.48
Table 37: Orange (City)
Isolation Index 1980 1990 2000 2010 Current
White/White 82.9 70.3 58.5 50.4 52.18
Black/Black 1.4 1.8 2.3 2.2 2.71
Hispanic/Hispanic 17 30.6 39.7 43.9 44.99
Asian/Asian 3.7 10.2 13.6 15.9 14.10
Table 38: Rancho Santa Margarita
White/White n/a 78.3 74.9 68 67.91
Black/Black n/a 1.4 2.3 2.4 2.28
Hispanic/Hispanic n/a 11.6 15.1 21.9 21.90
Asian/Asian n/a 8.2 9.6 11.9 10.65
Table 39: San Clemente
Isolation Index 1980 1990 2000 2010 Current
White/White 88.4 84.5 80.4 77.1 75.50
Black/Black 1.2 0.7 1 1 1.62
Hispanic/Hispanic 10 19.3 25.8 22.4 23.44
Asian/Asian 1.7 2.9 4.1 6.1 6.16
Table 40: Santa Ana
Isolation Index 1980 1990 2000 2010 Current
White/White 58.9 41.7 28.4 20.6 25.46
Black/Black 7.7 3.5 2.4 1.8 2.16
Hispanic/Hispanic 58.5 74.6 81.4 82.4 82.04
Asian/Asian 7 17.7 22.1 25.9 16.90
111
Table 41: Tustin
Isolation Index 1980 1990 2000 2010 Current
White/White 83.7 66.3 54.3 43.2 52.44
Black/Black 6.1 9.9 3.6 2.7 4.84
Hispanic/Hispanic 10.2 27 51.3 51.9 56.10
Asian/Asian 4.4 12.1 19.6 26.7 19.86
Table 42: Westminster
Isolation Index 1980 1990 2000 2010 Current
White/White 78.2 60.7 43.2 34.3 16.61
Black/Black 0.8 1.1 1.2 1.3 0.78
Hispanic/Hispanic 14.5 24.8 26 28.6 28.35
Asian/Asian 9.5 25.9 45.8 55.4 57.40
Isolation values for different populations vary widely across the county and individual
jurisdictions. Values for White residents are generally higher than for other residents, likely due
to the larger number of White residents overall. In Orange County, W hite residents have an
Isolation Index value of 55.16, Black residents 3.32, Hispanic residents 52.81, and Asian residents
31.84. Values for the county are sometimes higher than values in individual jurisdictions for White,
Hispanic, and Asian residents, again likely due to higher segregation across jurisdictions rather
than within them. Isolation values have generally decreased for White residents over time,
increased for Hispanic and Asian residents, and remained low for Black residents.
There are notable exceptions, however. White residents have especially high Isolation values in
Aliso Viejo, Costa Mesa, Huntington Beach, Laguna Niguel, Lake Forest, Mission Viejo, Rancho
Santa Margarita, and San Clemente. While some of those cities have lower non-White populations,
Lake Forest’s significant Hispanic population suggests that White residents are disproportionately
isolated. San Clemente has the highest White Isolation index value at 75.5. Buena Park has the
lowest at 27.37.
Isolation index values for Black residents are uniformly low. Values are in the single digits, due
to the low Black population across the county. These values have remained low and fairly
consistent since the 1980s, with no noticeable exceptions.
Hispanic residents have experienced the highest Isolation Index value change over the last few
decades. This is partly due to the increasing size of the population in the county. Certain areas have
exceptionally high Hispanic Isolation Index values, however including La Habra at 62.64 and
Santa Ana with 82.04.
Table 43 Exposure Index Values for Orange County
Exposure Index Current
Black/White 38.76
Hispanic/White 27.47
Asian/White 35.78
White/Black 1.47
112
Hispanic/Black 1.56
Asian/Black 1.64
White/Hispanic 22.69
Black/Hispanic 34.09
Asian/Hispanic 27.54
White/Asian 17.10
Black/Asian 20.66
Hispanic/Asian 15.93
Table 44: Aliso Viejo
Exposure Index 1980 1990 2000 2010 Current
Black/White 70.7 55.1 35.3 25.5 20.09
Hispanic/White 72.8 54.7 33 24.4 20.39
Asian/White 73.7 58.7 39.4 28.6 25.83
White/Black 1 2.2 3.8 3.7 3.01
Hispanic/Black 1.2 2.6 4.4 4.3 4.15
Asian/Black 1.2 2.4 4 3.8 3.12
White/Hispanic 17.1 22.9 29 34.6 34.98
Black/Hispanic 20.5 27.1 36.4 42.2 47.49
Asian/Hispanic 17.7 23.1 30.5 35.3 34.03
White/Asian 4.1 13.8 23.4 29.2 31.53
Black/Asian 5 14 22 27 25.39
Hispanic/Asian 4.2 13 20.6 25.4 24.21
Table 45: Anaheim
Exposure Index 1980 1990 2000 2010 Current
Black/White 76.7 57.2 36.7 27.8 25.38
Hispanic/White 65.9 45.4 27.3 21.2 20.8
Asian/White 78.7 61.6 41 31.4 28.44
White/Black 1.1 2.4 2.8 2.9 2.03
Hispanic/Black 1 2.2 2.6 2.7 2.09
Asian/Black 1.2 2.5 3.2 3.2 2.12
White/Hispanic 14.8 25.2 35.6 40.7 40.09
Black/Hispanic 15.8 29.7 43.1 49.9 50.48
Asian/Hispanic 14.2 24.6 37.8 44.8 44.5
White/Asian 3.9 9.8 15.2 18.6 19.66
Black/Asian 4.1 9.4 15.1 18.1 18.31
Hispanic/Asian 3.1 7.1 10.7 13.8 15.96
113
Table 46: Buena Park
Exposure Index 1980 1990 2000 2010 Current
Black/White 70.7 55.1 35.3 25.5 20.09
Hispanic/White 72.8 54.7 33 24.4 20.39
Asian/White 73.7 58.7 39.4 28.6 25.83
White/Black 1 2.2 3.8 3.7 3.01
Hispanic/Black 1.2 2.6 4.4 4.3 4.15
Asian/Black 1.2 2.4 4 3.8 3.12
White/Hispanic 17.1 22.9 29 34.6 34.98
Black/Hispanic 20.5 27.1 36.4 42.2 47.49
Asian/Hispanic 17.7 23.1 30.5 35.3 34.03
White/Asian 4.1 13.8 23.4 29.2 31.53
Black/Asian 5 14 22 27 25.39
Hispanic/Asian 4.2 13 20.6 25.4 24.21
Table 47: Costa Mesa
Exposure Index 1980 1990 2000 2010 Current
Black/White 83.3 71.4 57.2 51.6 48.14
Hispanic/White 78.6 63.2 42.6 40.2 39.24
Asian/White 81.4 69.5 57.2 52.7 43.84
White/Black 0.6 1.2 1.5 1.7 1.49
Hispanic/Black 0.6 1.2 1.4 1.6 1.23
Asian/Black 0.6 1.3 1.9 2.1 2.21
White/Hispanic 9.7 17.6 23.8 27.8 25.99
Black/Hispanic 9.8 19.4 28.9 33.3 26.41
Asian/Hispanic 10.2 19.1 26.7 30 28.27
White/Asian 4.2 6 8.5 9.9 11.69
Black/Asian 4 7 10.5 12.1 19.1
Hispanic/Asian 4.3 5.9 7.1 8.2 11.38
Table 48: Fountain Valley
Exposure Index 1980 1990 2000 2010 Current
Black/White 83.5 70.8 54.9 47 40.9
Hispanic/White 83.4 71.6 55.4 46.4 29.3
Asian/White 83.3 71.8 55.2 45.9 32.95
White/Black 0.7 0.9 1.3 1.2 0.47
Hispanic/Black 0.7 1.1 1.6 1.4 0.47
Asian/Black 0.7 0.9 1.4 1.2 0.35
White/Hispanic 6.8 8 10.1 12.4 16.67
Black/Hispanic 7 9.6 12.7 15.1 23.22
Asian/Hispanic 6.8 8.1 11 13.3 21.16
White/Asian 7 17.2 26.3 33.2 33.5
114
Black/Asian 7 17.8 29.1 35.5 31.29
Hispanic/Asian 7 17.4 28.8 36.2 37.8
Table 49: Fullerton
Exposure Index 1980 1990 2000 2010 Current
Black/White 73.3 59.5 44.7 37.3 32.48
Hispanic/White 67.9 54.6 40 33 29.88
Asian/White 78.6 60.7 44.3 33.9 30.48
White/Black 1.5 1.9 2.2 2.4 2.39
Hispanic/Black 2.1 2.6 2.8 2.7 2.76
Asian/Black 1.5 1.8 2.1 2.1 2.17
White/Hispanic 11.6 18.1 24.8 29.7 31.92
Black/Hispanic 18.1 26.4 35.6 37.8 40.13
Asian/Hispanic 11.3 16.1 21 22.4 25.69
White/Asian 4.4 11.2 15.7 21.5 21.94
Black/Asian 4.1 11.2 15.2 21.1 21.26
Hispanic/Asian 3.7 9 12 15.8 17.3
Table 50: Garden Grove
Exposure Index 1980 1990 2000 2010 Current
Black/White 77 53 32.7 23.4 28.9
Hispanic/White 66.7 48.2 27.9 19.2 17.18
Asian/White 77 50.5 27.6 18.9 17.02
White/Black 0.8 1.3 1.4 1.4 1.48
Hispanic/Black 0.8 1.4 1.5 1.3 0.92
Asian/Black 0.9 1.4 1.4 1.3 0.89
White/Hispanic 11.5 20.7 27.8 31.3 31.25
Black/Hispanic 13.8 23.7 33 36.9 32.61
Asian/Hispanic 12.7 22.9 30.2 33.9 34.42
White/Asian 5.6 18.4 27.6 32.4 32.34
Black/Asian 6.2 21 31.4 37.7 32.74
Hispanic/Asian 5.4 19.4 30.2 35.6 35.94
Table 51: Huntington Beach
Exposure Index 1980 1990 2000 2010 Current
Black/White 83.9 77.5 69.4 64.5 59.11
Hispanic/White 82.9 71.8 60.4 57.7 52.89
Asian/White 83.4 77.2 70.9 66.3 54.76
White/Black 0.7 0.9 1 1.2 1.26
Hispanic/Black 0.8 1 1.1 1.4 1.3
Asian/Black 0.7 0.9 1.1 1.3 1.21
White/Hispanic 7.7 10.2 12.3 14.6 17.18
115
Black/Hispanic 8.6 12.8 16.1 18.8 19.87
Asian/Hispanic 8.2 11.7 13.8 16.5 18.84
White/Asian 4.7 7.8 10.7 13.2 13.44
Black/Asian 4.8 7.9 11.7 13.9 13.99
Hispanic/Asian 5 8.3 10.3 13 14.24
Table 52: Irvine
Exposure Index 1980 1990 2000 2010 Current
Black/White 76.8 70 54.1 43.9 39.74
Hispanic/White 81.2 71.9 55.2 44 42.26
Asian/White 81.7 72.1 53.8 43.4 41.17
White/Black 1.3 1.6 1.6 2.1 1.57
Hispanic/Black 2 2.2 1.9 2.3 1.72
Asian/Black 1.8 1.7 1.8 2.2 1.83
White/Hispanic 5.8 6.1 7.1 8.6 10.98
Black/Hispanic 8.3 7.9 8.2 9.9 11.29
Asian/Hispanic 6.7 6.5 7.6 9.2 10.48
White/Asian 7.3 17.4 30.3 41.3 36.5
Black/Asian 9.6 17.2 33.6 43 41.09
Hispanic/Asian 8.4 18.7 33 42.6 35.75
Table 53: La Habra
Exposure Index 1980 1990 2000 2010 Current
Black/White 75.6 63.3 42.5 30.8 30.02
Hispanic/White 65.7 53.6 36.6 27.4 25.8
Asian/White 77.6 63.8 43.5 32.1 34.55
White/Black 0.3 0.9 1.7 1.7 1.09
Hispanic/Black 0.3 0.8 1.6 1.6 1.09
Asian/Black 0.4 0.9 1.8 2.1 0.96
White/Hispanic 19.7 29.8 43.4 51.9 48.56
Black/Hispanic 20.2 30.9 47.1 53.6 56.34
Asian/Hispanic 17.9 29 38.1 42.5 44.47
White/Asian 2.2 4 7 10.8 12.95
Black/Asian 2.6 4.3 7.4 12.8 9.89
Hispanic/Asian 1.7 3.3 5.2 7.6 8.86
Table 54: Laguna Niguel
Exposure Index 1980 1990 2000 2010 Current
Black/White 92.4 82.4 75.5 70.9 59.48
Hispanic/White 92.4 82.6 75.1 69.4 62.18
Asian/White 92.1 82.7 76.6 71.2 65.29
White/Black 0.4 1.3 1.4 1.5 1.64
116
Hispanic/Black 0.4 1.4 1.7 1.6 2.3
Asian/Black 0.4 1.3 1.4 1.6 2.11
White/Hispanic 4.2 7.7 10.1 13.3 15.5
Black/Hispanic 4.3 8.4 11.9 15.1 20.84
Asian/Hispanic 4.4 7.6 10.6 14.2 16.95
White/Asian 2 7.5 9.1 11.1 9.62
Black/Asian 2.1 7.5 9.1 11.6 11.33
Hispanic/Asian 2.1 7.4 9.3 11.5 10.03
Table 55: Lake Forest
Exposure Index 1980 1990 2000 2010 Current
Black/White n/a n/a 67.3 58.3 52.72
Hispanic/White n/a n/a 62.4 52 47.67
Asian/White n/a n/a 66.5 57.4 52.56
White/Black n/a n/a 2.1 2 2.01
Hispanic/Black n/a n/a 2 1.9 2.01
Asian/Black n/a n/a 2.2 2 1.87
White/Hispanic n/a n/a 17.4 22.4 23.84
Black/Hispanic n/a n/a 17.4 23 26.34
Asian/Hispanic n/a n/a 18.4 23.5 24
White/Asian n/a n/a 11.2 15.5 15.36
Black/Asian n/a n/a 11.5 15.6 14.3
Hispanic/Asian n/a n/a 11.2 14.7 14.02
Table 56: Mission Viejo
Exposure Index 1980 1990 2000 2010 Current
Black/White 88.9 83.9 73.6 67.4 67.06
Hispanic/White 89.1 84.3 72 65 61.99
Asian/White 88.6 83.8 74.5 68 65.26
White/Black 0.7 0.9 1.4 1.7 1.62
Hispanic/Black 0.7 1 1.6 1.9 1.46
Asian/Black 0.7 1 1.6 1.8 1.47
White/Hispanic 5.6 7.6 11.5 16 15.89
Black/Hispanic 5.9 8.2 13.5 18.3 15.45
Asian/Hispanic 6 7.9 12.4 17 16.76
White/Asian 2.8 6 9 11.4 10.9
Black/Asian 3.2 6.5 9.8 11.4 10.12
Hispanic/Asian 3.1 6.2 9.4 11.5 10.92
Table 57: Orange (City)
Exposure Index 1980 1990 2000 2010 Current
Black/White 79 35.2 51.7 43.3 43.93
117
Hispanic/White 76.8 60.6 48 42.2 42.34
Asian/White 81.1 67.4 54.7 47.5 48.65
White/Black 0.9 1.2 1.6 1.6 1.09
Hispanic/Black 1.1 1.4 1.8 1.9 1.28
Asian/Black 0.9 1.2 1.8 1.9 1.16
White/Hispanic 11.6 20.4 28.3 34.4 33.22
Black/Hispanic 14.8 25.2 34 40.5 40.53
Asian/Hispanic 12.9 20.8 28.8 34 33.15
White/Asian 3.2 7.6 10.4 12.8 10.58
Black/Asian 3.2 7.5 10.8 13.2 10.22
Hispanic/Asian 3.4 7 9.3 11.2 9.19
Table 58: Rancho Santa Margarita
Exposure Index 1980 1990 2000 2010 Current
Black/White n/a 78.3 73.2 66 66.49
Hispanic/White n/a 78.3 72.1 63.6 62.68
Asian/White n/a 78.3 74 66.6 65.32
White/Black n/a 1.4 2.1 2.3 1.73
Hispanic/Black n/a 1.4 2.3 2.4 1.63
Asian/Black n/a 1.4 2.2 2.4 1.9
White/Hispanic n/a 11.6 12.6 17.7 16.66
Black/Hispanic n/a 11.6 14 19.3 16.6
Asian/Hispanic n/a 11.6 13 18.4 17.99
White/Asian n/a 8.2 9.2 11.3 9.43
Black/Asian n/a 8.1 9.3 11.5 10.51
Hispanic/Asian n/a 8.2 9.2 11.2 9.77
Table 59: San Clemente
Exposure Index 1980 1990 2000 2010 Current
Black/White 85.5 82.3 75.9 75.3 76.35
Hispanic/White 86 77.1 68.6 70.8 68.96
Asian/White 87.1 83.6 79.3 76.4 74.08
White/Black 0.8 0.6 0.8 0.9 0.75
Hispanic/Black 1.1 0.6 1 0.9 0.63
Asian/Black 1 0.6 0.9 1 0.76
White/Hispanic 8.2 11.9 13.9 15.7 15.89
Black/Hispanic 10.4 13.8 18.2 17 14.78
Asian/Hispanic 9 12.4 14.5 15.5 14.98
White/Asian 1.5 2.6 3.7 5.4 4.29
Black/Asian 1.6 2.8 3.8 5.7 4.45
Hispanic/Asian 1.6 2.5 3.3 4.9 3.77
118
Table 60: Santa Ana
Exposure Index 1980 1990 2000 2010 Current
Black/White 38.2 27.1 19.5 14.5 15.73
Hispanic/White 30.8 15.8 9.3 7.5 8.57
Asian/White 46.2 27.4 15.4 11.1 13.25
White/Black 3.3 2.6 2.3 1.8 1.29
Hispanic/Black 4 2 1.3 1 0.83
Asian/Black 4.8 2.4 1.6 1.2 0.96
White/Hispanic 30.8 44.4 56.7 63.9 60.58
Black/Hispanic 45.6 59.1 66.7 71.8 71.44
Asian/Hispanic 39.2 52.2 60.1 61.5 67.45
White/Asian 4.9 10.8 11.8 13.2 10.72
Black/Asian 5.9 9.9 10.6 11.4 9.44
Hispanic/Asian 4.2 7.3 7.5 8.7 7.72
Table 61: Tustin
Exposure Index 1980 1990 2000 2010 Current
Black/White 78 57 40.3 32.5 20.01
Hispanic/White 81.4 56.6 30.8 26.3 23.47
Asian/White 83 62.7 48.9 37.2 39.02
White/Black 2.4 4.9 2.8 2.3 1.36
Hispanic/Black 3 6.3 3.5 2.7 3.49
Asian/Black 2.6 4.6 2.9 2.4 2.56
White/Hispanic 8.5 18.5 23.5 30 25.32
Black/Hispanic 10.2 24 39 42.8 55.54
Asian/Hispanic 8.6 20.1 27.2 33.1 34.8
White/Asian 4 9.8 17.9 23.8 17.08
Black/Asian 4 8.4 15.6 21.4 16.51
Hispanic/Asian 3.9 9.6 13.1 18.5 14.12
Table 62: Westminster
Exposure Index 1980 1990 2000 2010 Current
Black/White 78.8 57.8 38.6 29.6 17.19
Hispanic/White 74.1 52 33.4 24.5 16.4
Asian/White 75 53.8 31.1 21.4 15.21
White/Black 0.7 1 1.2 1.3 0.45
Hispanic/Black 0.6 1 1.1 1.2 0.51
Asian/Black 0.6 1 1 1 0.36
White/Hispanic 11.5 17.3 20 22.6 27.06
Black/Hispanic 11.4 18.7 21.8 25.7 31.71
Asian/Hispanic 12.9 18.8 20.9 21.7 24.54
White/Asian 7.7 20.5 34.1 41.1 53.04
119
Black/Asian 7.1 21.9 37 42.6 47.49
Hispanic/Asian 8.5 21.6 38.2 45.1 51.88
Exposure Index values are for the most part consistent with proportions of populations in
individual jurisdictions. While Non-White/White exposure values are decreasing, exposure to
Hispanic and Asian populations is increasing, and to the Black population is remaining the same.
Exposure to White residents is exceptionally high in Mission Viejo and San Clemente. Areas with
high Hispanic populations have high exposure to Hispanic residents as well, as seen in Santa Ana,
but less so in Lake Forest, indicating higher levels of segregation.
c. Identify areas in the jurisdiction and region with relatively high segregation and
integration by race/ethnicity, national origin, or LEP group, and indicate the
predominant groups living in each area.
120
Race/Ethnicity
Map 1: Race/Ethnicity, North Orange County, CA
121
Map 2: Race/Ethnicity, Central Orange County, CA
Map 2.1: Hispanic Origin, Central Orange County
122
Map 3: Race/Ethnicity, South Orange County, CA
Clear patterns of segregation both across and within jurisdictions are visible in the above maps. In
general, White residents tend to reside towards the outer edges of the county, while Hispanic and
sometimes Asian residents are found more in the center of the county. La Habra, Anaheim, Buena
Park, Santa Ana, Tustin, and parts of Costa Mesa have higher concentrations of Hispanic residents,
while Fullerton, Westminster, Garden Grove, and Anaheim have higher populations of Asian
residents. In areas with high Hispanic or Asian populations are present, segregation within a
jurisdiction is more visible. For example, Hispanic residents are found more in northern Anaheim,
western Costa Mesa, eastern Tustin, northern Huntington Beach, southeastern Lake Forest, and
northwestern San Juan Capistrano. Asian residents are more heavily concentrated in Garden
Grove, northern Fullerton, eastern Westminster, and northwestern Irvine.
Integration
More integrated areas of the County include the city of Orange, Fountain Valley, and Mission
Viejo.
123
National Origin
Map 4: National Origin, North Orange County, CA
Map 5: National Origin, North Orange County, CA
124
Map 6: National Origin, Central Orange County, CA
Map 7: National Origin, Central Orange County, CA
125
Map 8: National Origin, South Orange County, CA
Map 9: National Origin, South Orange County, CA
126
There are some clear patterns of settlement based on national origin in Orange County. The maps
above show the largest populations of foreign national origins in both the county overall and in
individual jurisdictions. These maps were formed using the top five largest foreign born
populations in each jurisdiction, but due to the high levels of overlap across jurisdictions, 12
populations total are represented.
In northern Orange County, there is a high Korean population in La Habra and Fullerton. A very
large Vietnamese population exists in the area stretching from Garden Grove into Westminster,
and a Filipino population is most populous in Buena Park and Anaheim. Anaheim, along with
Santa Ana, also contains a large Mexican population, stretching into south Costa Mesa. Mexican
residents are similarly scattered throughout central Orange County, though less are present in
Irvine. Irvine has significant populations of all represented populations, and higher numbers of
residents from the United Kingdom in particular. Mexican residents are especially present in the
areas of Lake Forest, Mission Viejo and Laguna Hills, and central San Juan Capistrano.
d. Consider and describe the location of owner and renter occupied housing in the
jurisdiction and region in determining whether such housing is located in segregated or
integrated areas, and describe trends over time.
Map 10: North Orange County, Housing Tenure
127
Map 11: Central Orange County, Housing Tenure
Map 12: South Orange County, Housing Tenure
128
Housing tenure varies widely across the county. Northern and more rural areas of the county tend
to have less renters, as compared to more populous areas towards the center of the county.
Anaheim, Santa Ana, Costa Mesa, Seal Beach, and Irvine tend to have much more renters than
average. Some of these areas have high populations of Hispanic residents specifically, including
Anaheim and Santa Ana. Irvine has a high population of students, which may explain the higher
percentages of renters in that city too.
e. Discuss how patterns of segregation have changed over time (since 1990).
129
Maps 13 & 14: Race/Ethnicity in 1990
130
Maps 15 & 16: Race/Ethnicity in 2000
131
Maps 17 & 18: Race/Ethnicity in 2010
132
The main trends present in residential patterns in the County are in Asian and Hispanic populations.
Asian and Hispanic populations were small but significant in 1990, and for the most part
constrained to certain sections of the Central part of the County. This was mostly in the vicinity of
Garden Grove and Westminster. By the 2000s, the Hispanic population began growing more
rapidly in Anaheim, and Hispanic and Asian populations grew more rapidly into other northern
parts of the county, including in Buena Park and Fullerton. There are fewer visible changes in
residential patterns from 2000 to 2010.
Additional Information
Beyond the HUD-provided data, provide additional relevant information, if any, about
segregation in the jurisdiction and region affecting groups with other protected
characteristics.
HUD does not provide and the Census Bureau does not collect data concerning religious affiliation,
but religion remains a prohibited basis for discrimination under the Fair Housing Act. Although
the data discussed above with respect to national origin and LEP status can provide some insight
into residential patterns with respect to religion given correlations between language, national
origin, and religion, the resulting picture is merely a rough prox y. It is also a proxy that does not
genuinely capture minority religious communities whose members are less likely to be recent
immigrants.
The tables below, from USC’s Center for Religion and Civic Culture, indicates the number of each
type of religious center located in the county’s jurisdictions. These numbers roughly correlate to
residential patterns based on race/ethnicity and national origin. Areas with higher numbers of
Buddhist or Hindu centers, including Anaheim, Fullerton, Garden Grove, Huntington Beach, and
Irvine, indicate more Asian or Pacific Islander residents or residents of Asian descent in those
jurisdictions.
Table 63.1: Religious Centers, Orange County
Religious Center ALISO
VIEJO
ANAHEIM BUENA
PARK
COSTA
MESA
FOUNTAIN
VALLEY
FULLERTON
BUDDHIST 25 1 8 5 1
CATHOLIC 22 3 2 4 11
CHRISTIAN-
OTHER
1 42 10 26 10 28
HINDU 6 3 2 5
JEWISH 2 12 2 3 3 4
MUSLIM 8 1 1 7
ORTHODOX 9 2 5
OTHER 37 4 23 4 13
OTHER-INDIA 9 7 2
OTHER-
INTERRELIGIOUS
1 1
OTHER-JAPANESE 5 3
PENTECOSTAL 1
133
PROTESTANT 12 452 143 177 70 266
Grand Total 15 628 173 245 100 343
Table 63.2: Religious Centers, Orange County
Religious Center GARDEN
GROVE
HUNTINGTON
BEACH
IRVINE LA
HABRA
LA
PALMA
LAGUNA
NIGUEL
BUDDHIST 46 1 4
CATHOLIC 4 18 8 3 2
CHRISTIAN-
OTHER
33 20 19 6 8
HINDU 2 3
JEWISH 2 5 16 1 2
MUSLIM 3 1 1
ORTHODOX 5 9 2
OTHER 17 4 18 9 3
OTHER-INDIA 3
OTHER-
INTERRELIGIOUS
OTHER-JAPANESE
PENTECOSTAL
PROTESTANT 301 180 150 124 16 39
Grand Total 413 232 228 144 17 54
Table 63.3: Religious Centers, Orange County
Religious Center LAKE
FOREST
MISSION
VIEJO
NEWPORT
BEACH
ORANGE RANCHO
SANTA
MARGARITA
BUDDHIST 2 1
CATHOLIC 7 27 1
CHRISTIAN-
OTHER
5 13 20 19 5
HINDU 1 1 2
JEWISH 6 9 2 1
MUSLIM 1 2
ORTHODOX 1
OTHER 2 15 13 14
OTHER-INDIA 2
OTHER-
INTERRELIGIOUS
1 1
OTHER-JAPANESE 5
PENTCOSTAL
PROTESTANT 16 64 51 263 13
Grand Total 25 102 104 335 20
134
Table 63.4: Religious Centers, Orange County
Religious Center SAN
CLEMENTE
SAN JUAN
CAPISTRANO
TUSTIN WESTMINSTER
BUDDHIST 23
CATHOLIC 4 5 6 6
CHRISTIAN-OTHER 8 8 13 16
HINDU 2
JEWISH 6 5
MUSLIM 1 1
ORTHODOX 2
OTHER 1 11 6 8
OTHER-INDIA 2 2
OTHER-
INTERRELIGIOUS
OTHER-JAPANESE
PENTECOSTAL
PROTESTANT 57 52 98 150
Grand Total 70 78 136 209
Contributing Factors of Segregation
Consider the listed factors and any other factors affecting the jurisdiction and Region.
Identify factors that significantly create, contribute to, perpetuate, or increase the severity of
segregation.
Please see the Appendix for the following Contributing Factors to Segregation:
Community opposition
Displacement of residents due to economic pressures
Lack of community revitalization strategies
Lack of private investment in specific neighborhoods
Lack of public investment in specific, neighborhoods, including services and amenities
Lack of local or regional cooperation
Land use and zoning laws
Lending discrimination
Location and type of affordable housing
Loss of affordable housing
Occupancy codes and restrictions
Private discrimination
Source of income discrimination
Lack of public investment in specific, neighborhoods, including services and amenities
135
ii. Racially or Ethnically Concentrated Areas of Poverty (R/ECAPs)
R/ECAPs are geographic areas with significant concentrations of poverty and minority
populations. HUD has developed a census-tract based definition of R/ECAPs. In terms of racial or
ethnic concentration, R/ECAPs are areas with a non-White population of 50 percent or more. With
regards to poverty, R/ECAPs are census tracts in which 40 percent or more of individuals are living
at or below the poverty limit or that have a poverty rate three times the average poverty rate for
the metropolitan area, whichever threshold is lower.
Where one lives has a substantial effect on mental and physical health, education, crime levels,
and economic opportunity. Urban areas that are more residentially segregated by race and income
tend to have lower levels of upward economic mobility than other areas. Research has found that
racial inequality is thus amplified by residential segregation. Concentrated poverty is also
associated with higher crime rates and worse health outcomes. However, these areas may also offer
some opportunities as well. Individuals may actively choose to settle in neighborhoods containing
R/ECAPs due to proximity to job centers and access to public services. Ethnic enclaves in
particular may help immigrants build a sense of community and adapt to life in the U.S. The
businesses, social networks, and institutions in ethnic enclaves may help immigrants preserve their
cultural identities while providing a variety of services that allow them to establish themselves in
their new homes. Overall, identifying R/ECAPs is important in order to better understand
entrenched patterns of segregation and poverty.
a) Identify any R/ECAPs or groupings of R/ECAP tracts within the jurisdiction and Region.
136
Map 1: R/ECAPs in Orange County
137
There are four R/ECAPs in Orange County, two of which are found in Santa Ana, two of which
are found in Irvine. The two R/ECAPs found in Santa Ana are predominantly Hispanic and found
close to the Santa Ana Freeway. The northernmost R/ECAP is located along North Spurgeon
Street, while the more southern R/ECAP is found along South Standard Avenue. The R/ECAPs
found in Irvine are adjacent to each other and located on the campus of University of California,
Irvine, making it likely that they qualify as R/ECAPs due to the high proportions of students. These
R/ECAPs have a much more diverse group of residents, with some White, Asian or Pacific
Islander, Hispanic and Black residents.
b) Describe and identify the predominant protected classes residing in R/ECAPs in the
jurisdiction and Region. How do these demographics of the R/ECAPs compare with the
demographics of the jurisdiction and Region?
Table 1 - R/ECAP Demographics
Jurisdiction
R/ECAP
Race/Ethnicity
# %
Total Population in
R/ECAPs
33458
White, Non-Hispanic 7858 23.49%
Black, Non-Hispanic 7858 1.63%
Hispanic 48.50%
Asian or Pacific
Islander, Non-
Hispanic
79300 23.70%
Native American,
Non-Hispanic
48 0.14%
R/ECAP Family Type
Total Families in
R/ECAPs
7848
Families with children 2529 32.22%
R/ECAP National Origin
Total Population in
R/ECAPs
#1 country of origin Mexico 5782 17.28%
#2 country of origin China, excluding Hong
Kong and Taiwan 1387 4.15%
#3 country of origin Korea 520 1.55%
#4 country of origin El Salvador 464 1.39%
#5 country of origin India 459 1.37%
#6 country of origin Iran 395 1.18%
#7 country of origin Saudi Arabia 219 0.65%
138
#8 country of origin Russia 195 0.58%
#9 country of origin Cambodia 192 0.57%
#10 country of origin Taiwan 187 0.56%
Note 1: 10 most populous groups at the jurisdiction level may not be the same as the 10
most populous at the Region level, and are thus labeled separately.
Note 2: Data Sources: Decennial Census; ACS
Note 3: Refer to the Data Documentation for details
(www.hudexchange.info/resource/4848/affh-data-documentation).
These R/ECAPs primarily contain Asian or Pacific Islander or Hispanic residents. 23.49% of
residents are White, 1.63% are Black, 48.50% are Hispanic, 23.70% are Asian or Pacific Islander,
and 0.14% are Native American. 32.22% of households are families with children (they are likely
located primarily in the Santa Ana R/ECAPs). The most populous countries of origin, in order, are
Mexico at 17.28% of the total population, China, excluding Hong Kong and Taiwan at 4.15%,
Korea at 1.55%, El Salvador at 1.39%, India at 1.37%, Iran at 1.18%, Saudi Arabia at 0.65%,
Russia at 0.58%, Cambodia at 0.57%, and Taiwan at 0.56%.
c) Describe how R/ECAPs have changed over time in the jurisdiction and the Region (since
1990).
139
Map 2: R/ECAPs 1990, Orange County
In 1990, one R/ECAP was present in Orange County, along E La Palma Ave in Yorba Linda. This
R/ECAP had a low population, with 82 total residents. 47.56% of the population was Hispanic,
8.54% was Asian, and the remainder were White.
140
Map 3: R/ECAPs 2000, Orange County
By 2000, the R/ECAP present in Orange County had shifted slightly to the West, in the area
between E Orangethorpe Ave and E Frontera St. This R/ECAP remained sparsely populated, with
302 residents, 19.21% of which were White, 0.99% were Native American, 4.64% Asian or Pacific
Islander, and 75.17% Hispanic. The original R/ECAP had a larger Hispanic population than before,
and a shrinking White population. Another R/ECAP appeared in the northernmost portion of the
University of California, Irvine campus, likely due to the presence of students. The R/ECAP had
2672 residents, which were 34.73% White, 1.57% Black, 0.41% Native American, 53.41% Asian
or Pacific Islander, and 7.49% Hispanic.
141
Map 4: R/ECAPs 2010, Orange County
By 2010, the R/ECAP in Santa Ana was no longer present. The high level of fluctuation in this
R/ECAP indicates that the area hovers around the 40% poverty threshold to qualify as a R/ECAP.
The second R/ECAP, which appeared on the University of California, Irvine campus is again likely
caused by the presence of diverse students, though increasing poverty is also likely a factor. All
the areas with R/ECAPs in the maps above once again were present in the most current map of
R/ECAPs, suggesting that these will be continued areas for concern in the future.
Contributing Factors of R/ECAPs
Consider the listed factors and any other factors affecting the jurisdiction and Region.
Identify factors that significantly create, contribute to, perpetuate, or increase the severity of
R/ECAPs.
Please see the Appendix for the following Contributing Factors to R/ECAPs:
● Community opposition
● Deteriorated and abandoned properties
● Displacement of residents due to economic pressures
● Lack of community revitalization strategies
● Lack of local or regional cooperation
● Lack of private investments in specific neighborhoods
142
● Lack of public investments in specific neighborhoods, including services or amenities
● Land use and zoning laws
● Location and type of affordable housing
● Loss of affordable housing
● Occupancy codes and restrictions
● Private discrimination
● Source of income discrimination
143
iii. Disparities in Access to Opportunity
The following section describes locational differences and disparities experienced by different
groups in accessing key features of opportunity: educational quality, economic factors,
transportation, and environmental health. Access to neighborhoods with higher levels of
opportunity can be more difficult due to discrimination and when there may not be a sufficient
range and supply of housing in such neighborhoods. In addition, the continuing legacy of
discrimination and segregation can impact the availability of quality infrastructure, educational
resources, environmental protections, and economic drivers, all of which can create disparities in
access to opportunity.
Three opportunity indices (economic, educational, and environmental) use data assembled by the
California Fair Housing Task Force on behalf of the Department of Housing and Community
Development (HCD) and California Tax Credit Allocation Committee (TCAC) for the 2020
TCAC/HCD Opportunity Map4. The Economic Opportunity Index is a composite of four
indicators5 depicting elements of neighborhood socio-economic character. The Environmental
Opportunity Index reflects indicators6 from the exposures and environmental effects
subcomponents of the “pollution burden” domain of CalEnviroScreen 3.0. The Educational
Opportunity Index is a composite of four educational indicators7 capturing information on student
proficiency, graduation rates, and student poverty. All indices range from 0 to 100, reflecting
percentiles scaled to census tracts in Orange Count y8, and with higher values indicating higher
levels of opportunity.
The two transportation indicators (transit trips and low transportation cost) analyzed below employ
data from version 3.0 of the Location Affordability Index (LAI)9. The transit trips index measures
how often low-income families in a neighborhood use public transportation. The index ranges
from 0 to 100, with higher values indicating a higher likelihood that residents in a neighborhood
utilize public transit. The low transportation cost index measures cost of transportation and
proximity to public transportation by neighborhood. It too varies from 0 to 100, and higher scores
point to lower transportation costs in that neighborhood.
4 Data files and methodology details available for download here:
https://www.treasurer.ca.gov/ctcac/opportunity.asp
5 The Economic Opportunity Index summarizes the following four indicators: (1) Poverty: % of population with
income above 200% of federal poverty line (2013 -17 ACS); (2) Adult Education: % of adults with a bachelor’s
degree or above (2013-17 ACS); (3) Employment: % of adults aged 20-64 who are employed in civilian labor force
or in armed forces (2013-17 ACS); (4) Jobs proximity: number of jobs filled by workers with less than a BA that
fall within a given radius of each census tract population-weighted centroid (2017 LEHD LODES). See
methodology document for further details.
6 See methodology document for additional details. Also note that because higher pollution exposure and effects
reflects a negative outcome, the final composite environmental index is inverted to ensure that higher index values
denote higher opportunity.
7 (1) Math and Reading Proficiency: % of 4th graders who meet/exceed literacy or math standards; (2)
Graduation: % of students who graduate high school in 4 years; (3) Student Poverty: % of students not receiving
free or reduced-price lunch. All indicators use data from 2017 -18 CA DOE.
8 Similarly, data computed for LA County (for regional comparisons) are scaled to census tracts in LA County.
9 Data available for download here: https://www.hudexchange.info/programs/location-affordability-index/
144
a. Educational Opportunities
1. For the protected class group(s) HUD has provided data, describe any disparities
in access to education in the jurisdiction and region.
Countywide, there are disparities across racial/ethnic groups in access to educational opportunities
as measured by the index. Across all tracts in Orange County, non-Hispanic Whites exhibit the
highest exposure to educational opportunity (index score of about 59) and non-Hispanic Asians
second-highest (53). Hispanics have the lowest access to these opportunities (31), with non-
Hispanic Blacks in between (46).
Several jurisdictions score highly (index values at or above 60) on educational opportunity across
all racial categories. These cities include Aliso Viejo, Huntington Beach, Irvine, Laguna Niguel,
La Palma, Mission Viejo, and Rancho Santa Margarita.
Other jurisdictions obtain low scores on the index. San Juan Capistrano has low educational
opportunity, scoring below 10 on the index for all races/ethnicities. San Clemente, Anaheim, and
Santa Ana fare similarly poorly, although non-Hispanic Whites score higher (39) than other
race/ethnic groups in that city. Buena Park, Costa Mesa, Garden Grove, Orange City, La Habra
and Westminster are other cities that struggle with educational opportunity, all with scores in the
30s to 40s on the composite education index.
Finally, a few cities have educational opportunity patterns that mirror those of Orange County
overall. Non-Hispanic Whites in Fountain Valley have high exposure to educational opportunity
(scores of about 60), whereas Hispanics in the city do not (30). In both Fullerton and Tustin, Non-
Hispanic Whites and Asians have much higher access than do Blacks and Hispanics.
2. For the protected class group(s) HUD has provided data, describe how the
disparities in access to education relate to residential living patterns in the
jurisdiction and region.
Jurisdictions that score low on the education opportunity index exhibit different residential
patterns. For instance, Santa Ana has high concentrations of Hispanics and a ve ry light presence
of any other racial or ethnic group. Anaheim also has high concentrations of Hispanics in the low-
opportunity western neighborhoods of the city, but Whites and Asian/Pacific Islanders also appear
to reside in those tracts (although at lower densities). The high opportunity eastern Anaheim
neighborhoods are almost exclusively White. Garden Grove, Westminster, Buena Park and La
Habra are examples of cities with low educational opportunity and that have a noticeable mix of
Hispanics, Asians and Whites. Costa Mesa, San Juan Capistrano and San Clemente are low
opportunity jurisdictions with high densities of Whites (although San Juan Capistrano and Costa
Mesa have important Hispanic populations as well).
Jurisdictions with the highest educational opportunity also appear to have primarily large
concentrations of non-Hispanic Whites and Asian/Pacific Islanders. Irvine, Aliso Viejo and
Huntington Beach are good examples of cities with large populations of those two groups. Other
high opportunity cities, by contrast appear more segregated and more heavily populated by non-
Hispanic Whites. Rancho Santa Margarita and Mission Viejo are two examples of such places.
145
b. Environmental Opportunities
1. For the protected class group(s) HUD has provided data, describe any disparities
in access to environmental opportunity in the jurisdiction and region.
Countywide, there are disparities across racial/ethnic groups in access to environmental
opportunities, measured as lower exposure to and effects from pollution. Across all tracts in
Orange County, non-Hispanic Whites exhibit the highest access to environmentally healthy
neighborhoods (index score of about 54). All other racial/ethnic groups obtain lower index scores
in the 40s: Hispanics score lowest at 41, followed by non-Hispanic Blacks (45), non-Hispanic
Asian/Pacific Islander (47), and non-Hispanic Native American (48).
Several jurisdictions score especially highly on environmental opportunity across all racial
categories. Laguna Niguel, Aliso Viejo, Mission Viejo, and Rancho Santa Margarita all have
index scores in the 70s to 90s for all racial and ethnic groups. Fountain Valley and Huntington
Beach also have higher access to environmental health, scoring in the 50s to low-70s on the index.
Other cities are low-scoring across the board. Orange City, La Habra, and Fullerton are the least
environmentally healthy, with index scores in the 20s. Anaheim, Buena Park, Irvine, Santa Ana,
and Westminster also have low access to environmental opportunity, scoring in the 30s to 40s on
the index.
Other cities have disparate environmental scores between races. One such jurisdiction is Costa
Mesa, in which Hispanics, non-Hispanic Whites, and non-Hispanic Native Americans score the
highest (50s), while non-Hispanic Blacks (44) and non-Hispanic Asian/Pacific Islanders (35) score
lower. Another such city is Tustin, with non-Hispanic Blacks and Hispanics scoring the lowest
(20s/30s) and non-Hispanic Whites the highest (55).
2. For the protected class group(s) HUD has provided data, describe how the
disparities in access to environmental opportunity relate to residential living
patterns in the jurisdiction and region.
Jurisdictions with the highest environmental opportunity appear to have primarily large
concentrations of non-Hispanic Whites and Asian/Pacific Islanders. Laguna Niguel, Aliso Viejo,
Fountain Valley and Huntington Beach are good examples of cities with large populations of those
two groups. Other high opportunity cities, by contrast appear more segregated and more heavily
populated by non-Hispanic Whites. Rancho Santa Margarita and Mission Viejo are two examples
of such places.
Lower-scoring cities exhibit a diversity of residential patterns. For example, Orange (city) has
concentrations of both Hispanics and non-Hispanic Whites. Similarly, Fullerton has
concentrations of Hispanic neighborhoods as well as non-Hispanic Whites and Asian/Pacific
Islanders. Anaheim and La Habra follow a similar pattern. By contrast, Santa Ana is a city with
low environmental quality that is characterized almost exclusively by dense concentrations of
Hispanics.
146
c. Economic Opportunities
1. For the protected class groups HUD has provided data, describe any disparities in
access to economic opportunity by protected class groups in the jurisdiction and
region.
In Orange County, there are significant disparities in access to economic opportunity. Non -
Hispanic White residents have the greatest access to economic opportunity. Asian and Pacific
Islander residents (49), Native Americans (46), and Black residents (46) have lower index scores
in the high to mid-40s. Hispanic residents (32) have the lowest access to economic opportunity of
all racial and ethnic groups in Orange County. Among residents living below the poverty line,
there are significant disparities between groups. White residents have the highest economic
opportunity score (30) followed by Black residents (27) and Asian Americans and Pacific Islanders
(23). Poor Native Americans and Hispanic residents have the lowest economic opportunity scores
(19).
There are major disparities in economic opportunity scores across racial/ethnic groups in other
cities in the County. Generally, Asian and White residents tend to have the highest index scores in
these cities. For instance, Tustin has very high scores for non-Hispanic White residents (77) as
well as Asian residents (67) but Black and Hispanic residents have significantly lower scores (in
the 40s). In Fullerton, Asian residents have the highest score (64) while Black residents have a
score of 44 and Hispanic residents have a score of 37. In Santa Ana, White residents have the
highest score (41) while Hispanics have the lowest (18). Costa Mesa has relatively high access to
economic opportunity for all groups (high 50s to high 60s) but Hispanic residents have a
significantly lower score (42). In La Habra, economic opportunity scores are relatively low for all
groups (30s and 40s) but White residents have significantly higher scores than other racial/ethnic
groups. Other jurisdictions with relatively large disparities by protected class groups include
Anaheim, Buena Park, Fountain Valley, Lake Forest, and Orange City. In these cities, Hispanic
residents have significantly lower access to economic opportunity than other racial/ethnic groups.
A number of jurisdictions have relatively little disparity between groups. There are high economic
opportunity scores for all racial and ethnic groups in Aliso Viejo and Irvine (high 60s to low 70s),
although there are large disparities across racial/ethnic groups for the population living below the
poverty line in Irvine. La Palma also has relatively high opportunity and little variation in scores
between groups (index values ranging from 60 to 66). Huntington Beach, Laguna Niguel, Mission
Viejo, and Rancho Santa Margarita have moderate economic opportunity scores for all
racial/ethnic groups (scores from the mid-40s to mid-50s). San Clemente has moderately low
economic opportunity scores with little difference between groups (scores ranging from 40-46).
There is low access to economic opportunity for all racial and ethnic groups in Garden Grove
(index scores range from 9-25) and Westminster (scores in the 10s).
a. For the protected class groups HUD has provided data, describe how disparities
in access to employment relate to residential living patterns in the jurisdiction and
region
147
Economic Opportunity Index scores are generally lower in North Orange County than in South
Orange County. Scores are especially low in Westminster, Garden Grove, and much of Santa Ana
and Anaheim. Scores are generally high in much of Irvine, La Palma, and Tustin and along the
coast from Newport Beach to Laguna Niguel as well as in unincorporated areas near the eastern
border with Riverside County.
Areas in Orange County with the highest index scores tend to have large concentrations of non -
Hispanic and Asian residents. By contrast, areas with the highest concentration of Hispanic
residents tend to have lower economic index scores. Cities such as Fullerton and Costa Mesa are
examples of localities with segregated living patterns and significant disparities between racial and
ethnic groups. Neighborhoods in these cities with higher Hispanic populations score lower than
neighborhoods that are heavily populated by non-Hispanic and Asian residents.
d. Transportation
1. For the protected class groups HUD has provided data, describe any disparities in
access to transportation related to costs and access to public transit in the
jurisdiction and region.
As previously mentioned, higher scores on the low transportation cost index indicate greater access
to low cost transportation. When analyzing Orange County as a whole, non-Hispanic Whites have
the lowest scores (34). Asians and Pacific Islanders as well as Native Americans have a score of
38. Black residents have a score of 39 while Hispanic residents have the highest score (42).
Regionally, low transportation cost index scores are similar for all racial and ethnic groups. Non-
Hispanic Whites and Native Americans both have a score of 19, Asians/Pacific Islanders as well
as Hispanics have a score of 20, and Black residents have a score of 21.
There are no significant disparities between racial/ethnic groups in the low transportat ion cost
index in most jurisdictions in Orange County. Index scores are in the 20s for all groups in Laguna
Niguel, Mission Viejo, and San Clemente. Scores are in the low to mid 30s for all racial/ethnic
groups in Buena Park, Lake Forest, La Palma, Orange City. Scores are in the high 30s to low 40s
for all groups in Aliso Viejo, Anaheim, Fountain Valley, Fullerton, Garden Grove, Irvine,
Huntington Beach, La Habra. Scores are moderate (in the high 40s to low 50s) across groups in
Costa Mesa, Santa Ana, and Westminster.
In both Tustin and Rancho Santa Margarita, White and Asian residents have significantly lower
scores on the low transportation cost index compared to Black and Hispanic residents. These
patterns are similar to those of Orange County overall.
Transit index scores do not vary significantly by racial or ethnic group in most jurisdictions in
Orange County. Scores are moderate for all groups in Santa Ana with every group having a score
in the low 50s. Scores are moderately low (30s to 40s) across the board in Anaheim, Buena Park,
Costa Mesa, Fountain Valley, Fullerton, Garden Grove, Huntington Beach, Irvine, La Habra, La
Palma, Orange City, and Westminster. Transit use is extremely low (scores of 3 and lower) for all
groups in Aliso Viejo, Laguna Niguel, Lake Forest, Mission Viejo, Rancho Santa Margarita, San
148
Clemente, and San Juan Capistrano. There is also little difference in transit index scores by racial
or ethnic group in Orange County with all groups scoring in the low 20s.
There is a significant disparity between groups in Tustin and Countywide. Hispanics in Tustin
have the highest transit index scores (64) followed closely by African Americans (60). Asian and
White residents have significantly lower scores (49 and 42 respectively). Count ywide, Hispanics
have the highest transit index score (41) while non-Hispanic Whites have a significantly lower
score (27) than other racial and ethnic groups.
2. For the protected class groups HUD has provided data, describe how disparities
in access to transportation related to residential living patterns in the jurisdiction
and region
Low transportation cost index scores as well as transit index scores are generally higher in North
Orange County than in South Orange County. Scores are generally higher i n jurisdictions with
greater levels of density. Generally, North Orange County cities have a variety of residential living
patterns with varying levels of density. Additionally, some jurisdictions have highly segregated
living patterns while others have a mix of multiple racial and ethnic groups across neighborhoods.
Jurisdictions and neighborhoods with greater concentrations of non-Hispanic White residents tend
to have lower transit index scores and transportation cost index scores.
South Orange County has a greater concentration of non-White Hispanic residents and has lower
levels of transit service than North Orange County. This pattern likely contributes to disparities in
transportation cost index and transit index scores between non-Hispanic Whites and other racial
and ethnic groups in South Orange County jurisdictions and countywide.
e. Patterns in Disparities in Access to Opportunity
1. For the protected class groups HUD has provided data, identify and discuss any
overarching patterns of access to opportunity and exposure to adverse community
factors. Include how these patterns compare to patterns of segregation, integration,
and R/ECAPs. Describe these patterns for the jurisdiction and region
Generally, access to opportunity is highest for non-Hispanic Whites and Asians/Pacific Islanders
in Orange County. By contrast, access to opportunity is generally lower for Black residents than
for non-Hispanic Whites and Asians and access is lowest for Hispanics. Metrics are lower on
average in census tracts with more of each of these groups. Geographically, access to economic,
environmental, and educational opportunity is generally lowest in portions of North Orange
County. Anaheim, Garden Grove, Santa Ana, and Westminster all have relatively low scores
across various dimensions of opportunity. Access to opportunity is also low in San Juan
Capistrano. However, access to transportation is generally better in North Orange County than in
South Orange County.
149
Maps and Tables Appendix:
Table 1: Index Values, Aliso Viejo
Aliso Viejo
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 72.30550385 83.83909607 72.71175385 37.90481567 2.982049465
Black, Non-
Hispanic 66.52386475 85.23960114 71.72485352 43.27718735 3.305222511
Hispanic 65.70877838 85.67479706 69.67499542 43.99542999 3.4930861
Asian or
Pacific
Islander, Non-
Hispanic
71.44657135 87.03471375 72.0605011 38.21439362 3.052240849
Native
American,
Non-Hispanic
66.95543671 85.84021759 72.0728302 44.31396484 3.418583393
Population below federal poverty line
White, Non-
Hispanic 72.1219101 76.88407898 76.13404083 40.00963593 3.032668829
Black, Non-
Hispanic 73.1000061 82.69999695 66.6000061 30.55382347 2.297693729
Hispanic 67.39414215 84.66527557 75.61569214 42.99341965 3.097574472
Asian or
Pacific
Islander, Non-
Hispanic
67.48900604 85.0457077 69.90343475 44.67321396 3.799084425
Native
American,
Non-Hispanic
73.30000305 88 66.19999695 30.19909286 2.297693729
Table 2: Index Values, Anaheim
Anaheim
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index" Transit Index
Total Population
White, Non-
Hispanic 43.93139267 38.43595505 39.49500275 35.00980759 38.28310013
Black, Non-
Hispanic 30.85617065 43.77084732 24.11480904 41.09883118 42.81028366
Hispanic 24.94393539 35.08900452 16.60894966 42.32661819 45.37927628
Asian or
Pacific
Islander, Non-
Hispanic 35.78163528 45.57190704 28.93398666 38.00388718 40.76144028
150
Native
American,
Non-Hispanic 31.95301437 39.92325211 25.63920212 40.02379227 43.23343277
Population below federal poverty line
White, Non-
Hispanic 31.62712288 41.38234711 26.39390373 40.36358643 42.55496979
Black, Non-
Hispanic 21.08607101 37.48281479 15.80590439 42.93815613 42.37175751
Hispanic 18.12784386 35.43183517 11.7365303 44.72396088 48.39587402
Asian or
Pacific
Islander, Non-
Hispanic 31.28238106 50.9586525 23.88062859 39.64730453 41.40625763
Native
American,
Non-Hispanic 19.2225132 23.75654411 28.95340347 40.15534973 44.56227112
Table 3: Index Values, Buena Park
Buena Park
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index" Transit Index
Total Population
White, Non-
Hispanic 46.83927917 44.0955658 42.70969772 33.90605164 37.46681976
Black, Non-
Hispanic 32.80804825 33.55254364 34.25307465 36.66135025 37.74475479
Hispanic 28.33981895 29.21013069 30.79724121 37.55573654 37.4323349
Asian or
Pacific
Islander, Non-
Hispanic 47.61252594 39.32788467 42.41317368 34.37330246 37.90651321
Native
American,
Non-Hispanic 40.82292938 40.50382233 38.02802658 34.82195663 37.10214996
Population below federal poverty line
White, Non-
Hispanic 40.31472397 40.72068405 37.29474258 36.05626297 37.11514664
Black, Non-
Hispanic 25.9830513 38.49584198 35.70261765 40.10052872 38.47552109
Hispanic 17.92495918 21.97593117 24.49638939 39.0867157 37.56377792
Asian or
Pacific
Islander, Non-
Hispanic 41.90719986 39.55010986 39.26160431 35.59976578 37.79622269
Native
American,
Non-Hispanic 81.6641922 33.69506073 49.20370483 31.88211632 37.17000198
151
Table 4: Index Values, Costa Mesa
Costa Mesa
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index" Transit Index
Total Population
White, Non-
Hispanic 67.58622742 55.52037811 38.89334488 47.27882385 43.22631836
Black, Non-
Hispanic 60.21097183 43.73588943 35.36569214 51.47803497 47.67166901
Hispanic 41.75721741 52.17251968 29.46787262 49.68540573 45.92378235
Asian or
Pacific
Islander, Non-
Hispanic 62.83917236 34.57888412 37.24597931 51.76671982 49.81667328
Native
American,
Non-Hispanic 57.93167114 57.8879776 36.08298874 49.50308228 45.41753769
Population below federal poverty line
White, Non-
Hispanic 59.96794891 54.49015427 36.67170334 49.62751389 44.84539795
Black, Non-
Hispanic 69.71747589 15.24660206 44.42038727 60.94523239 57.05648804
Hispanic 30.79871941 51.77633667 27.76061058 50.66155243 45.77159119
Asian or
Pacific
Islander, Non-
Hispanic 65.26630402 45.6599617 37.13913345 51.9749794 47.06335831
Native
American,
Non-Hispanic 47.94121552 40.6466217 39.73918915 44.072155 50.18476486
Table 5: Index Values, Fountain Valley
Fountain
Valley
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index" Transit Index
Total Population
White, Non-
Hispanic 60.60261536 64.15343475 58.0732193 34.88885498 39.57632446
Black, Non-
Hispanic 53.71952438 56.91206741 44.76111221 39.96112061 40.72764587
Hispanic 41.24127579 59.6288147 33.37312698 39.45233154 41.81933975
Asian or
Pacific
Islander, Non-
Hispanic 44.98392868 58.26979065 41.64525986 37.5691185 40.36568451
Native
American,
Non-Hispanic 52.49386597 69.90551758 47.91042709 36.09816742 39.42101669
152
Population below federal poverty line
White, Non-
Hispanic 64.17408752 71.23667908 61.07992172 32.63380432 39.16001511
Black, Non-
Hispanic 64.10958862 65.91918182 73.40000153 42.57266617 40.4589119
Hispanic 31.28120613 67.20317078 28.9899292 39.14260483 41.5614624
Asian or
Pacific
Islander, Non-
Hispanic 44.84921646 49.497612 36.71788025 40.1937294 40.57577133
Native
American,
Non-Hispanic 18 72.09999847 6.900000095 39.88677597 43.88391495
Table 6: Index Values, Fullerton
Fullerton
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 55.78549576 26.03284073 58.12939072 38.56270599 36.36819077
Black, Non-
Hispanic 43.93449402 23.39889526 50.62736893 43.17352676 39.78337097
Hispanic 37.14920425 20.28424263 43.05700684 41.48886108 39.47481537
Asian or
Pacific
Islander, Non-
Hispanic
64.09486389 25.70118332 65.7769165 35.43569183 35.37657928
Native
American,
Non-Hispanic
42.6170578 22.90802765 48.14080048 41.21847534 38.35867691
Population below federal poverty line
White, Non-
Hispanic 42.62480927 23.49648094 50.72012711 45.41986847 40.98034668
Black, Non-
Hispanic 26.27262497 20.02443314 37.49615479 50.76286316 44.32195663
Hispanic 29.84314728 19.52399254 38.35726547 43.06222916 41.15517044
Asian or
Pacific
Islander, Non-
Hispanic
57.70301437 27.73388481 64.75909424 42.01194 39.39395523
Native
American,
Non-Hispanic
43.26682663 22.70192337 51.35336685 38.76887131 34.99217987
Table 7: Index Values, Garden Grove
Garden Grove
"Economic
Opportunity
Index"
"Environment
al
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
153
Opportunity
Index"
Total Population
White, Non-
Hispanic 36.39666367 47.3960228 40.38077927 36.63133621 39.78887558
Black, Non-
Hispanic 27.92678833 47.87880325 33.18390274 41.15602112 41.82769394
Hispanic 22.90080643 47.05417633 29.86315918 41.03567505 42.94892883
Asian or
Pacific
Islander, Non-
Hispanic
23.95595741 49.54003143 35.30280304 40.51235199 40.41277313
Native
American,
Non-Hispanic
27.66724777 46.53165817 34.10087204 41.22572708 41.86322403
Population below federal poverty line
White, Non-
Hispanic 30.0959301 47.71313477 35.78342056 39.06194305 41.55861664
Black, Non-
Hispanic 27.44144821 54.79440689 33.70690918 39.97136688 38.74142075
Hispanic 18.94665909 46.0896759 26.74869919 43.83759689 44.6900177
Asian or
Pacific
Islander, Non-
Hispanic
22.66533279 47.17929077 37.85955429 40.4188385 39.69983673
Native
American,
Non-Hispanic
18.80149269 38.3007431 27.1022377 48.05475616 43.73262405
Table 8: Index Values, Huntington Beach
Huntington
Beach
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 64.58568573 71.44684601 69.54529572 37.66327667 35.70833206
Black, Non-
Hispanic 55.74852371 61.43478394 59.94100952 40.57863235 36.41617966
Hispanic 48.91268921 56.34483719 59.14129257 42.3997879 36.54937363
Asian or
Pacific
Islander, Non-
Hispanic
55.79597092 58.89957809 60.11377335 38.13786316 35.30189133
Native
American,
Non-Hispanic
59.45223999 69.95332336 66.42298126 39.55618668 36.38960266
Population below federal poverty line
White, Non-
Hispanic 63.94906235 71.72304535 68.93916321 40.83568192 37.38664627
154
Black, Non-
Hispanic 46.80564499 57.03628922 63.21209335 44.36582947 38.40356827
Hispanic 37.6064682 48.60849762 55.68051147 45.98036194 37.06981277
Asian or
Pacific
Islander, Non-
Hispanic
55.28670883 58.22230911 58.15016174 42.73658752 36.3033371
Native
American,
Non-Hispanic
63.99184036 89.20612335 79.1040802 25.95944023 33.74476242
Table 9: Index Values, Irvine
Irvine
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 73.63127136 39.08622742 81.49776459 36.18370819 35.191082
Black, Non-
Hispanic 70.55041504 36.09516525 81.03330994 39.19680023 37.68433762
Hispanic 68.2244339 34.8563385 75.89785004 37.90677261 35.78848267
Asian or
Pacific
Islander, Non-
Hispanic
73.3141861 38.35515213 85.66765594 37.19092941 37.06846237
Native
American,
Non-Hispanic
68.81182861 37.30687332 78.0866394 37.68278122 34.32770157
Population below federal poverty line
White, Non-
Hispanic 62.00982285 41.2605896 81.79143524 41.65803909 40.29730606
Black, Non-
Hispanic 78.47797394 30.86845207 85.13333893 36.81203842 36.52822113
Hispanic 45.06617737 43.96442032 84.95259094 44.5932579 42.19712067
Asian or
Pacific
Islander, Non-
Hispanic
50.49572372 45.72290802 87.87575531 44.2512207 42.13927078
Native
American,
Non-Hispanic
34.17985535 56.2374115 91.07769775 53.02960205 50.96051407
155
Table 10: Index Values, Los Angeles County
Los Angeles
County
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 65.67538452 55.94469833 67.478302 18.965065 21.0825634
Black, Non-
Hispanic 40.16342545 53.13132858 33.42098999 21.05691338 24.56006813
Hispanic 36.33623123 45.2298851 38.80290604 19.82450485 23.3633194
Asian or
Pacific
Islander, Non-
Hispanic
57.39865494 49.95420074 61.21666336 20.27166367 23.09456062
Native
American,
Non-Hispanic
45.30443192 51.25786972 49.35198593 19.37051392 21.6207428
Population below federal poverty line
White, Non-
Hispanic 57.50989532 51.78505325 59.31045151 23.57732391 25.74990845
Black, Non-
Hispanic 31.36289787 50.94706726 26.02533722 23.28333092 27.20900345
Hispanic 31.3007412 42.91162491 31.26461411 22.65198517 26.92627716
Asian or
Pacific
Islander, Non-
Hispanic
50.03251266 47.77090454 55.55622864 24.86695862 28.33756065
Native
American,
Non-Hispanic
34.06453323 48.27433014 35.94702911 22.76408005 26.06622124
Table 11: Index Values, Laguna Niguel
Laguna
Niguel
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 51.88405609 94.96172333 69.4879303 26.46920204 2.232567787
Black, Non-
Hispanic 49.20069885 94.27303314 70.40055847 27.88728714 2.385162592
Hispanic 46.48111725 94.03167725 69.29504395 29.60008812 2.543926477
Asian or
Pacific
Islander, Non-
Hispanic
51.05093765 94.28031921 70.32914734 28.43764305 2.466272593
Native
American,
Non-Hispanic
52.94462585 95.30413055 70.03966522 27.89173698 2.296560049
156
Population below federal poverty line
White, Non-
Hispanic 48.66943741 93.59718323 70.38157654 27.90661812 2.297754049
Black, Non-
Hispanic 61.86949158 94.28262329 58.08516693 32.82440567 2.653566122
Hispanic 47.95252228 94.91544342 73.69073486 29.40856171 2.452992439
Asian or
Pacific
Islander, Non-
Hispanic
42.89958572 90.35707855 72.27500153 34.07725906 2.88683486
Native
American,
Non-Hispanic
N/A N/A N/A N/A N/A
Table 12: Index Values, La Habra
La Habra
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 40.55103683 27.87729454 48.14756012 35.66272736 35.27762604
Black, Non-
Hispanic 35.30363846 29.53260612 45.65385437 39.55151749 35.42910004
Hispanic 32.31658936 27.45372391 44.28807068 38.3514595 34.83366394
Asian or
Pacific
Islander, Non-
Hispanic
39.38534927 24.85019112 49.1582222 37.03078079 37.28299713
Native
American,
Non-Hispanic
38.17602921 30.35684967 47.53630066 35.54092407 33.94094467
Population below federal poverty line
White, Non-
Hispanic 40.29798126 29.05448341 48.00325012 35.98387527 34.38015747
Black, Non-
Hispanic 31.18307686 28.36153793 45.95999908 39.51876068 36.60215759
Hispanic 27.1908226 25.55690002 41.80315781 39.25904846 35.26225281
Asian or
Pacific
Islander, Non-
Hispanic
32.04285431 28.29251671 42.60680389 37.83418655 36.04021072
Native
American,
Non-Hispanic
24.10000038 11.80000019 38 44.92282867 41.23970032
157
Table 13: Index Values, La Palma
La Palma
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 60.54538345 52.2887764 74.90605927 31.26264191 33.98268509
Black, Non-
Hispanic 62.44117737 50.76352692 79.34926605 30.94960976 32.45330429
Hispanic 60.14683151 53.11293411 76.4289093 31.19957161 33.79656219
Asian or
Pacific
Islander, Non-
Hispanic
59.61754608 54.71827316 80.94405365 30.98505211 33.03434372
Native
American,
Non-Hispanic
66.49090576 44.5484848 74.41212463 31.03777504 32.16746521
Population below federal poverty line
White, Non-
Hispanic 56.16556168 58.63651657 78.42116547 31.26299286 34.6687851
Black, Non-
Hispanic 62 52.13999939 83.30000305 30.76098061 31.77929115
Hispanic 62.43789673 49.73848724 74.32682037 31.21320152 33.49207687
Asian or
Pacific
Islander, Non-
Hispanic
57.32141113 57.53029633 80.26992798 31.11726379 33.91407013
Native
American,
Non-Hispanic
59.40000153 51.29999924 62.90000153 31.94073486 36.83267593
Table 14: Index Values, Lake Forest
Lake Forest
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 52.10555649 54.81097412 60.88927078 31.83229065 3.096983671
Black, Non-
Hispanic 49.18192673 55.03483963 61.46455765 34.36283493 3.168195009
Hispanic 39.65441513 43.67831039 53.05497742 35.60156631 3.339822292
Asian or
Pacific
Islander, Non-
Hispanic
51.61265182 53.55771637 59.62294769 32.0095787 2.971857309
Native
American,
Non-Hispanic
45.60740662 53.91375732 59.4603157 34.44470978 3.268085241
158
Population below federal poverty line
White, Non-
Hispanic 42.87811661 48.27126312 56.19835281 35.24717331 3.274830103
Black, Non-
Hispanic 58.93999863 62.13200378 49.3239975 28.69176102 3.198252678
Hispanic 23.69203186 17.86175346 43.00056839 33.14248276 3.199719906
Asian or
Pacific
Islander, Non-
Hispanic
34.96779251 36.78378296 52.04999924 39.137043 3.588968277
Native
American,
Non-Hispanic
6.400000095 10.10000038 39.90000153 50.44693375 4.321035862
Table 15: Index Values, Mission Viejo
Mission Viejo
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 54.71001434 80.4629364 68.59661865 20.06777954 2.14685297
Black, Non-
Hispanic 53.97848892 77.18696594 69.5125351 22.50149727 2.178300142
Hispanic 49.20601654 77.96643066 69.57389832 24.251894 2.186423779
Asian or
Pacific
Islander, Non-
Hispanic
56.29401779 79.96483612 69.64553833 20.08021736 2.172489405
Native
American,
Non-Hispanic
52.15392685 77.70209503 68.03507996 20.00351524 2.125685453
Population below federal poverty line
White, Non-
Hispanic 52.77148438 79.52762604 68.10930634 20.6295166 2.147603989
Black, Non-
Hispanic 47.77692413 72.13846588 60.4153862 30.359375 2.514009476
Hispanic 41.74552917 75.55897522 73.74349976 27.94129181 2.138385296
Asian or
Pacific
Islander, Non-
Hispanic
50.18946457 76.0255127 75.70388031 27.29961014 2.231768131
Native
American,
Non-Hispanic
N/A N/A N/A N/A N/A
159
Table 16: Index Values, Orange City
Orange City
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 59.93873978 24.79452133 42.08477402 31.92243958 36.35044479
Black, Non-
Hispanic 54.84865952 18.7726078 35.12828445 37.30315018 39.30299377
Hispanic 47.76997757 19.34976578 33.2277832 36.87007141 38.43082809
Asian or
Pacific
Islander, Non-
Hispanic
61.62908554 28.02267647 45.12159348 31.81376266 35.78025818
Native
American,
Non-Hispanic
52.82477188 20.58942604 36.06827545 34.44309235 37.73715973
Population below federal poverty line
White, Non-
Hispanic 53.57085419 17.67649841 33.95972061 36.44538879 39.62675095
Black, Non-
Hispanic 35.50442505 12.76637173 29.51858521 37.15558624 28.86623383
Hispanic 41.78118134 23.23805237 32.39267731 36.83862305 39.01893616
Asian or
Pacific
Islander, Non-
Hispanic
61.44256592 21.8933773 41.95364761 37.79168701 37.63070297
Native
American,
Non-Hispanic
31.33373451 10.93734932 20.50963974 41.80668259 43.29630661
Table 17: Index Values, Orange County
Orange
County
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 59.36914825 53.88697052 58.6191597 33.84046555 27.43986702
Black, Non-
Hispanic 45.8503685 45.21717072 45.6352005 39.68424606 36.21459579
Hispanic 31.86008644 41.02077866 30.86243248 41.80742645 41.28927612
Asian or
Pacific
Islander, Non-
Hispanic
49.36313629 46.78428268 52.50125504 37.48302841 36.11438751
Native
American,
Non-Hispanic
46.39406204 48.79929352 45.07330704 37.47456741 33.02807617
160
Population below federal poverty line
White, Non-
Hispanic 51.70472336 51.01126099 52.13442612 39.18977356 32.26565933
Black, Non-
Hispanic 36.25161743 40.4234581 37.29018784 40.77672958 35.60103607
Hispanic 22.65623665 39.02124786 23.81145287 45.65877533 46.35126877
Asian or
Pacific
Islander, Non-
Hispanic
38.94393158 46.38044739 48.32249832 41.97251129 39.51419449
Native
American,
Non-Hispanic
35.89070892 38.62186813 40.92134476 40.15331268 40.17951965
Table 18: Index Values, Rancho Santa Margarita
Rancho Santa
Margarita
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 55.31455231 77.42084503 74.73116302 22.26515198 1.739218593
Black, Non-
Hispanic 48.5736618 78.66453552 72.82685852 29.90576553 2.138027906
Hispanic 46.87901688 79.68223572 71.21639252 31.94477654 2.276622057
Asian or
Pacific
Islander, Non-
Hispanic
52.71126556 76.4618454 74.23796082 25.72115326 1.882683992
Native
American,
Non-Hispanic
52.11122513 76.42857361 73.22245026 27.17526817 1.988348365
Population below federal poverty line
White, Non-
Hispanic 46.90814972 80.66777802 70.89245605 30.65854645 2.180054665
Black, Non-
Hispanic N/A N/A N/A N/A N/A
Hispanic 37.29422379 84.92796326 66.2130661 40.81872559 2.736426592
Asian or
Pacific
Islander, Non-
Hispanic
60.54124069 82.12485504 78.08983612 16.653265 1.491689444
Native
American,
Non-Hispanic
N/A N/A N/A N/A N/A
161
Table 19: Index Values, San Clemente
San Clemente
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 43.86069107 53.53229904 26.15826035 20.86557388 1.323781729
Black, Non-
Hispanic 44.58891678 53.67986298 26.91267014 20.62924576 1.308523178
Hispanic 40.03211212 58.22519684 23.51825714 25.35934067 1.459569693
Asian or
Pacific
Islander, Non-
Hispanic
46.24467087 51.4276619 27.82583618 19.14149284 1.219676495
Native
American,
Non-Hispanic
41.8181076 55.99135971 26.10987663 23.12410355 1.460949898
Population below federal poverty line
White, Non-
Hispanic 40.29958344 52.50610733 22.75804329 23.32270622 1.429345369
Black, Non-
Hispanic 21.60899544 46.30582047 12.44285679 22.93115044 1.561009169
Hispanic 38.13341522 59.1672554 19.66854095 25.5105629 1.351897478
Asian or
Pacific
Islander, Non-
Hispanic
36.40293121 78.38371277 26.14299583 19.77955627 0.901919305
Native
American,
Non-Hispanic
40.5885849 56.44565201 26.93206596 15.30980492 0.906552672
Table 20: Index Values, San Juan Capistrano
San Juan
Capistrano
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 24.8559227 40.60459518 3.96122098 28.67803192 2.159676313
Black, Non-
Hispanic 17.48586845 44.83804321 4.980434895 30.27136993 2.118023157
Hispanic 9.223362923 51.43849182 6.480751991 31.45836258 1.975713015
Asian or
Pacific
Islander, Non-
Hispanic
24.93882942 43.21843719 4.463120461 27.79998398 2.022916555
Native
American,
Non-Hispanic
12.91760635 49.70633698 6.045070648 30.53370857 1.976489902
162
Population below federal poverty line
White, Non-
Hispanic 24.2220974 38.93087769 3.655807257 29.47362709 2.26116538
Black, Non-
Hispanic 53.59999847 39.20000076 2.900000095 17.58180046 1.543227077
Hispanic 8.015656471 53.10263824 6.83494997 31.40584183 1.918851495
Asian or
Pacific
Islander, Non-
Hispanic
8.699999809 32.79999924 2.900000095 37.69218826 2.949278355
Native
American,
Non-Hispanic
N/A N/A N/A N/A N/A
Table 21: Index Values, Santa Ana
Santa Ana
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 40.84465027 33.96951294 24.41191101 47.15653229 52.06034851
Black, Non-
Hispanic 29.20541 38.66877747 19.36479187 48.0304451 54.12454987
Hispanic 18.03375626 41.18429947 15.26601601 46.74744034 54.8878212
Asian or
Pacific
Islander, Non-
Hispanic
25.11046028 46.18630219 18.69794273 47.20291138 54.18437576
Native
American,
Non-Hispanic
25.56700134 38.30905533 17.4342041 45.30844498 52.30129623
Population below federal poverty line
White, Non-
Hispanic 31.77580452 34.26587677 19.81741333 48.76362228 52.66421127
Black, Non-
Hispanic 25.08537483 23.57221222 20.0210247 50.08654785 50.39803314
Hispanic 14.87970352 41.16586304 15.27909184 50.43182755 57.66402054
Asian or
Pacific
Islander, Non-
Hispanic
25.55044937 45.79997253 17.13907242 48.1301918 52.26394272
Native
American,
Non-Hispanic
16.78843117 43.75597 12.58059692 42.92389297 57.04358673
163
Table 22: Index Values, Tustin
Tustin
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 77.3833313 55.53118134 57.9779892 37.03637695 41.61579132
Black, Non-
Hispanic 49.5615654 33.86757278 33.26813889 54.51399994 60.01934433
Hispanic 42.9604187 28.64287949 27.41756248 56.88419342 63.88144684
Asian or
Pacific
Islander, Non-
Hispanic
67.04686737 46.94258499 49.78988266 44.89656067 48.62200546
Native
American,
Non-Hispanic
63.12244797 43.92755127 47.4581604 43.06391144 49.6460228
Population below federal poverty line
White, Non-
Hispanic 57.39323807 42.8909874 38.77998352 47.96840286 52.79444885
Black, Non-
Hispanic 36.90000153 22.5 25.10000038 55.18679047 64.45001984
Hispanic 32.15452576 17.71869659 18.61776543 65.68024445 74.0960083
Asian or
Pacific
Islander, Non-
Hispanic
42.37282944 30.59916115 25.81988907 55.87603378 61.07912064
Native
American,
Non-Hispanic
26.20000076 13.69999981 14.19999981 65.00455475 66.8004303
Table 23: Index Values, Westminster
Westminster
"Economic
Opportunity
Index"
"Environment
al
Opportunity
Index"
"Educational
Opportunity
Index"
"Low
Transportatio
n Cost Index"
Transit Index
Total Population
White, Non-
Hispanic 13.81653023 42.93841171 35.6662941 44.7712059 37.7172699
Black, Non-
Hispanic 10.56679821 38.13873291 32.76600647 45.53092575 37.15086365
Hispanic 11.77696323 40.45322037 32.86334991 44.28075409 36.86459732
Asian or
Pacific
Islander, Non-
Hispanic
14.33915138 46.11770248 35.44109344 44.00982666 37.56019592
Native
American,
Non-Hispanic
15.28125 44.0395813 36.25625229 43.3792572 37.29174042
164
Population below federal poverty line
White, Non-
Hispanic 15.20829582 44.93229675 37.83362961 45.77521515 38.73999023
Black, Non-
Hispanic 8.191836357 21.56734848 37.28163528 40.71427536 33.28907013
Hispanic 10.51876068 37.48429489 28.36954689 43.8158226 36.38402557
Asian or
Pacific
Islander, Non-
Hispanic
12.96408653 44.58031464 32.6651535 44.92889404 37.62247467
Native
American,
Non-Hispanic
25.30000114 48.70000076 52.20000076 45.22904587 41.23970032
Map 1: Economic Opportunity Index, North Orange County
165
Map 2: Economic Opportunity Index, South Orange County
166
Map 3: Educational Opportunity Index, North Orange County
167
Map 4: Educational Opportunity Index, South Orange County
168
Map 5: Environmental Opportunity Index, North Orange County
169
Map 6: Environmental Opportunity Index, South Orange County
170
Map 7: Transportation Cost Index, North Orange County
171
Map 8: Transportation Cost Index, South Orange County
172
Map 9: Transit Trips Index, North Orange County
173
Map 10: Transit Trips Index, South Orange County
174
iv. Disproportionate Housing Needs 10
Which groups (by race/ethnicity and family status) experience higher rates of housing cost burden,
overcrowding, or substandard housing when compared to other groups? Which groups also
experience higher rates of severe housing burdens when compared to other groups?
Across Orange County, many residents face high rates of housing problems, severe housing
problems, and severe housing cost burden. The four HUD-designated housing problems include
when a “1) housing unit lacks complete kitchen facilities; 2) housing unit lacks complete plumbing
facilities; 3) household is overcrowded;11 and 4) household is cost burdened”12. Households are
considered to have a housing problem if they experience at least one of the above. This analysis
also considers what HUD designates as severe housing problems, which are a lack of kitchen or
plumbing, more than one person per room, or cost burden greater than 50%.
10 The AFFH rule defines “disproportionate housing needs” as “a condition in which there are significant disparities
in the proportion of members of a protected class experiencing a category of housing needs when compared to the
proportion of members of any other relevant groups or the total population experiencing tha t category of housing
need in the applicable geographic area.” 24 C.F.R. § 5.152
11 Households having more than 1.01 to 1.5 persons per room are considered overcrowded and those having more
than 1.51 persons per room are considered severely overcrowded. T he person per room analysis excludes
bathrooms, porches, foyers, halls, or half-rooms.
12 https://www.huduser.gov/portal/datasets/cp/CHAS/bg_chas.html
175
Housing Problems
Table 1: Housing Problems, Orange County13
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 206,658 540,773 38.22%
Black, Non-Hispanic 8,074 16,719 48.29%
Hispanic 152,740 241,841 63.16%
Asian or Pacific Islander, Non-
Hispanic 84,193 186,038 45.26%
Native American, Non-Hispanic 1063 2,179 48.78%
Total 452,728 987,550 45.84%
Household Type and Size
Family households, <5 people 228740 576690 39.66%
Family households, 5+ people 95050 145028 65.54%
Non-family households 138270 273662 50.53%
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 104324 540,773 19.29%
Black, Non-Hispanic 4816 16,719 28.81%
Hispanic 107752 241,841 44.55%
Asian or Pacific Islander, Non-
Hispanic 50205 186,038 26.99%
Native American, Non-Hispanic 544 2,179 24.97%
Total 267,641 987,550 27.10%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 93564 540,773 17.30%
13 Please note that the extrapolation of HUD data may result in variances and rounding errors.
176
Black, Non-Hispanic 3774 16,719 22.57%
Hispanic 59920 241,841 24.78%
Asian or Pacific Islander, Non-
Hispanic 36879 186,038 19.82%
Native American, Non-Hispanic 432 2,179 19.83%
Total 194,569 987,550 19.70%
Household Type and Size
Family households, <5 people 79610 576690 13.80%
Family households, 5+ people 24586 145028 16.95%
Non-family households 39386 273662 14.39%
Table 2: Housing Problems, Aliso Viejo
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 4,840 12,570 38.50%
Black, Non-Hispanic 235 380 61.84%
Hispanic 930 2,120 43.87%
Asian or Pacific Islander, Non-
Hispanic 995 2,830 35.16%
Native American, Non-Hispanic 20 70 28.57%
Total 7,020 17,970 39.07%
Household Type and Size
Family households, <5 people 3955 11390 34.72%
Family households, 5+ people 705 1420 49.65%
Non-family households 2635 5605 47.01%
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 2075 12,570 16.51%
Black, Non-Hispanic 140 380 36.84%
Hispanic 400 2,120 18.87%
Asian or Pacific Islander, Non-
Hispanic 425 2,830 15.02%
Native American, Non-Hispanic 0 70 0.00%
177
Total 3,040 17,970 16.92%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 1840 12,570 14.64%
Black, Non-Hispanic 140 380 36.84%
Hispanic 225 2,120 10.61%
Asian or Pacific Islander, Non-
Hispanic 350 2,830 12.37%
Native American, Non-Hispanic 0 70 0.00%
Total 2,555 17,970 14.22%
Household Type and Size
Family households, <5 people 1010 11390 8.87%
Family households, 5+ people 150 1420 10.56%
Non-family households 730 5605 13.02%
Table 3: Housing Problems, Anaheim
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 15,085 36,390 41.45%
Black, Non-Hispanic 1,409 2,688 52.42%
Hispanic 28,175 41,509 67.88%
Asian or Pacific Islander, Non-
Hispanic 8,305 17,464 47.55%
Native American, Non-Hispanic 105 170 61.76%
Total 53,079 98,221 54.04%
Household Type and Size
Family households, <5 people 24720 53980 45.79%
Family households, 5+ people 15450 20740 74.49%
Non-family households 13885 24384 56.94%
178
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 8425 36,390 23.15%
Black, Non-Hispanic 993 2,688 36.94%
Hispanic 20590 41,509 49.60%
Asian or Pacific Islander, Non-
Hispanic 5065 17,464 29.00%
Native American, Non-Hispanic 85 170 50.00%
Total 35,158 98,221 35.79%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 7210 36,390 19.81%
Black, Non-Hispanic 810 2,688 30.13%
Hispanic 11330 41,509 27.30%
Asian or Pacific Islander, Non-
Hispanic 3290 17,464 18.84%
Native American, Non-Hispanic 50 170 29.41%
Total 22,690 98,221 23.10%
Household Type and Size
Family households, <5 people 9845 53980 18.24%
Family households, 5+ people 4225 20740 20.37%
Non-family households 4050 24384 16.61%
Table 4: Housing Problems, Buena Park
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 2,500 7,540 33.16%
Black, Non-Hispanic 455 835 54.49%
Hispanic 4,725 7,705 61.32%
179
Asian or Pacific Islander, Non-
Hispanic 3,505 6,830 51.32%
Native American, Non-Hispanic 80 99 80.81%
Total 11,265 23,009 48.96%
Household Type and Size
Family households, <5 people 6340 14230 44.55%
Family households, 5+ people 3060 4930 62.07%
Non-family households 2045 3910 52.30%
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 1125 7,540 14.92%
Black, Non-Hispanic 300 835 35.93%
Hispanic 3050 7,705 39.58%
Asian or Pacific Islander, Non-
Hispanic 2070 6,830 30.31%
Native American, Non-Hispanic 50 99 50.51%
Total 6,595 23,009 28.66%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 955 7,540 12.67%
Black, Non-Hispanic 255 835 30.54%
Hispanic 1780 7,705 23.10%
Asian or Pacific Islander, Non-
Hispanic 1515 6,830 22.18%
Native American, Non-Hispanic 50 99 50.51%
Total 4,555 23,009 19.80%
Household Type and Size
Family households, <5 people 2445 14230 17.18%
Family households, 5+ people 770 4930 15.62%
Non-family households 569 3910 14.55%
180
Table 5: Housing Problems, Costa Mesa
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 10,055 25,230 39.85%
Black, Non-Hispanic 320 695 46.04%
Hispanic 6,820 10,105 67.49%
Asian or Pacific Islander, Non-
Hispanic 1,670 3,870 43.15%
Native American, Non-Hispanic 25 70 35.71%
Total 18,890 39,970 47.26%
Household Type and Size
Family households, <5 people 8775 20195 43.45%
Family households, 5+ people 3175 4175 76.05%
Non-family households 7325 15975 45.85%
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 5335 25,230 21.15%
Black, Non-Hispanic 200 695 28.78%
Hispanic 4650 10,105 46.02%
Asian or Pacific Islander, Non-
Hispanic 804 3,870 20.78%
Native American, Non-Hispanic 15 70 21.43%
Total 11,004 39,970 27.53%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 4905 25,230 19.44%
Black, Non-Hispanic 125 695 17.99%
Hispanic 2960 10,105 29.29%
Asian or Pacific Islander, Non-
Hispanic 610 3,870 15.76%
Native American, Non-Hispanic 15 70 21.43%
181
Total 8,615 39,970 21.55%
Household Type and Size
Family households, <5 people 3460 20195 17.13%
Family households, 5+ people 904 4175 21.65%
Non-family households 2650 15975 16.59%
Table 6: Housing Problems, Fountain Valley
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 3,910 10,405 37.58%
Black, Non-Hispanic 75 175 42.86%
Hispanic 1,290 2,174 59.34%
Asian or Pacific Islander, Non-
Hispanic 2,425 5,785 41.92%
Native American, Non-Hispanic 0 55 0.00%
Total 7,700 18,594 41.41%
Household Type and Size
Family households, <5 people 4625 12275 37.68%
Family households, 5+ people 1110 2200 50.45%
Non-family households 2150 4325 49.71%
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 1860 10,405 17.88%
Black, Non-Hispanic 25 175 14.29%
Hispanic 585 2,174 26.91%
Asian or Pacific Islander, Non-
Hispanic 1419 5,785 24.53%
Native American, Non-Hispanic 0 55 0.00%
Total 3,889 18,594 20.92%
182
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 1630 10,405 15.67%
Black, Non-Hispanic 25 175 14.29%
Hispanic 350 2,174 16.10%
Asian or Pacific Islander, Non-
Hispanic 1105 5,785 19.10%
Native American, Non-Hispanic 0 55 0.00%
Total 3,110 18,594 16.73%
Household Type and Size
Family households, <5 people 1245 12275 10.14%
Family households, 5+ people 250 2200 11.36%
Non-family households 629 4325 14.54%
Table 7: Housing Problems, Fullerton
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 7,960 20,005 39.79%
Black, Non-Hispanic 655 1,448 45.23%
Hispanic 7,620 11,890 64.09%
Asian or Pacific Islander, Non-
Hispanic 5,085 10,615 47.90%
Native American, Non-Hispanic 20 90 22.22%
Total 21,340 44,048 48.45%
Household Type and Size
Family households, <5 people 10595 25185 42.07%
Family households, 5+ people 4450 6275 70.92%
Non-family households 6925 12920 53.60%
183
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 4320 20,005 21.59%
Black, Non-Hispanic 433 1,448 29.90%
Hispanic 5250 11,890 44.15%
Asian or Pacific Islander, Non-
Hispanic 3125 10,615 29.44%
Native American, Non-Hispanic 20 90 22.22%
Total 13,148 44,048 29.85%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 3665 20,005 18.32%
Black, Non-Hispanic 375 1,448 25.90%
Hispanic 2950 11,890 24.81%
Asian or Pacific Islander, Non-
Hispanic 2495 10,615 23.50%
Native American, Non-Hispanic 0 90 0.00%
Total 9,485 44,048 21.53%
Household Type and Size
Family households, <5 people 3695 25185 14.67%
Family households, 5+ people 1029 6275 16.40%
Non-family households 2664 12920 20.62%
Table 8: Housing Problems, Garden Grove
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 5,055 14,255 35.46%
Black, Non-Hispanic 287 592 48.48%
Hispanic 8,945 13,550 66.01%
184
Asian or Pacific Islander, Non-
Hispanic 10,303 18,418 55.94%
Native American, Non-Hispanic 130 148 87.84%
Total 24,720 46,963 52.64%
Household Type and Size
Family households, <5 people 12495 26390 47.35%
Family households, 5+ people 7515 10735 70.00%
Non-family households 5059 9854 51.34%
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 2645 14,255 18.55%
Black, Non-Hispanic 173 592 29.22%
Hispanic 6540 13,550 48.27%
Asian or Pacific Islander, Non-
Hispanic 6775 18,418 36.78%
Native American, Non-Hispanic 85 148 57.43%
Total 16,218 46,963 34.53%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 2135 14,255 14.98%
Black, Non-Hispanic 145 592 24.49%
Hispanic 3435 13,550 25.35%
Asian or Pacific Islander, Non-
Hispanic 4685 18,418 25.44%
Native American, Non-Hispanic 85 148 57.43%
Total 10,485 46,963 22.33%
Household Type and Size
Family households, <5 people 4950 26390 18.76%
Family households, 5+ people 1945 10735 18.12%
Non-family households 1450 9854 14.71%
185
Table 9: Housing Problems, Huntington Beach
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 19,865 53,650 37.03%
Black, Non-Hispanic 344 753 45.68%
Hispanic 5,500 10,855 50.67%
Asian or Pacific Islander, Non-
Hispanic 3,089 8,114 38.07%
Native American, Non-Hispanic 74 274 27.01%
Total 28,872 73,646 39.20%
Household Type and Size
Family households, <5 people 15230 43760 34.80%
Family households, 5+ people 3035 5995 50.63%
Non-family households 11235 24905 45.11%
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 9745 53,650 18.16%
Black, Non-Hispanic 179 753 23.77%
Hispanic 3570 10,855 32.89%
Asian or Pacific Islander, Non-
Hispanic 1669 8,114 20.57%
Native American, Non-Hispanic 55 274 20.07%
Total 15,218 73,646 20.66%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 9030 53,650 16.83%
Black, Non-Hispanic 139 753 18.46%
Hispanic 2580 10,855 23.77%
Asian or Pacific Islander, Non-
Hispanic 1475 8,114 18.18%
Native American, Non-Hispanic 45 274 16.42%
186
Total 13,269 73,646 18.02%
Household Type and Size
Family households, <5 people 5195 43760 11.87%
Family households, 5+ people 899 5995 15.00%
Non-family households 3245 24905 13.03%
Table 10: Housing Problems, Irvine
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 18,555 45,505 40.78%
Black, Non-Hispanic 865 1,795 48.19%
Hispanic 3,310 6,790 48.75%
Asian or Pacific Islander, Non-
Hispanic 13,955 33,220 42.01%
Native American, Non-Hispanic 65 130 50.00%
Total 36,750 87,440 42.03%
Household Type and Size
Family households, <5 people 20175 52685 38.29%
Family households, 5+ people 3630 6270 57.89%
Non-family households 14279 28074 50.86%
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 9085 45,505 19.96%
Black, Non-Hispanic 570 1,795 31.75%
Hispanic 1805 6,790 26.58%
Asian or Pacific Islander, Non-
Hispanic 7850 33,220 23.63%
Native American, Non-Hispanic 10 130 7.69%
Total 19,320 87,440 22.10%
187
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 7700 45,505 16.92%
Black, Non-Hispanic 315 1,795 17.55%
Hispanic 1510 6,790 22.24%
Asian or Pacific Islander, Non-
Hispanic 6110 33,220 18.39%
Native American, Non-Hispanic 10 130 7.69%
Total 15,645 87,440 17.89%
Household Type and Size
Family households, <5 people 6605 52685 12.54%
Family households, 5+ people 1055 6270 16.83%
Non-family households 5460 28074 19.45%
Table 11: Housing Problems, La Habra
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 2,910 7,363 39.52%
Black, Non-Hispanic 144 304 47.37%
Hispanic 4,800 8,870 54.11%
Asian or Pacific Islander, Non-
Hispanic 965 2,260 42.70%
Native American, Non-Hispanic 10 10 100.00%
Total 8,829 18,807 46.95%
Household Type and Size
Family households, <5 people 4335 10875 39.86%
Family households, 5+ people 2325 3285 70.78%
Non-family households 2240 4600 48.70%
188
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 1630 7,363 22.14%
Black, Non-Hispanic 59 304 19.41%
Hispanic 3285 8,870 37.03%
Asian or Pacific Islander, Non-
Hispanic 700 2,260 30.97%
Native American, Non-Hispanic 10 10 100.00%
Total 5,684 18,807 30.22%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 1240 7,363 16.84%
Black, Non-Hispanic 55 304 18.09%
Hispanic 1765 8,870 19.90%
Asian or Pacific Islander, Non-
Hispanic 485 2,260 21.46%
Native American, Non-Hispanic 10 10 100.00%
Total 3,555 18,807 18.90%
Household Type and Size
Family households, <5 people 1640 10875 15.08%
Family households, 5+ people 465 3285 14.16%
Non-family households 555 4600 12.07%
Table 12: Housing Problems, La Palma
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 430 1,619 26.56%
Black, Non-Hispanic 150 370 40.54%
Hispanic 320 709 45.13%
189
Asian or Pacific Islander, Non-
Hispanic 810 2,148 37.71%
Native American, Non-Hispanic 30 30 100.00%
Total 1,740 4,876 35.68%
Household Type and Size
Family households, <5 people 1015 3220 31.52%
Family households, 5+ people 340 765 44.44%
Non-family households 435 930 46.77%
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 210 1,619 12.97%
Black, Non-Hispanic 75 370 20.27%
Hispanic 239 709 33.71%
Asian or Pacific Islander, Non-
Hispanic 434 2,148 20.20%
Native American, Non-Hispanic 0 30 0.00%
Total 958 4,876 19.65%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 140 1,619 8.65%
Black, Non-Hispanic 70 370 18.92%
Hispanic 175 709 24.68%
Asian or Pacific Islander, Non-
Hispanic 340 2,148 15.83%
Native American, Non-Hispanic 0 30 0.00%
Total 725 4,876 14.87%
Household Type and Size
Family households, <5 people 325 3220 10.09%
Family households, 5+ people 160 765 20.92%
Non-family households 75 930 8.06%
190
Table 13: Housing Problems, Laguna Niguel
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 7,480 18,280 40.92%
Black, Non-Hispanic 145 395 36.71%
Hispanic 2,010 3,210 62.62%
Asian or Pacific Islander, Non-
Hispanic 835 2,350 35.53%
Native American, Non-Hispanic 65 85 76.47%
Total 10,535 24,320 43.32%
Household Type and Size
Family households, <5 people 6000 15965 37.58%
Family households, 5+ people 815 1680 48.51%
Non-family households 3975 6930 57.36%
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 3445 18,280 18.85%
Black, Non-Hispanic 65 395 16.46%
Hispanic 1210 3,210 37.69%
Asian or Pacific Islander, Non-
Hispanic 390 2,350 16.60%
Native American, Non-Hispanic 15 85 17.65%
Total 5,125 24,320 21.07%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 3310 18,280 18.11%
Black, Non-Hispanic 35 395 8.86%
Hispanic 905 3,210 28.19%
Asian or Pacific Islander, Non-
Hispanic 325 2,350 13.83%
Native American, Non-Hispanic 15 85 17.65%
191
Total 4,590 24,320 18.87%
Household Type and Size
Family households, <5 people 1745 15965 10.93%
Family households, 5+ people 265 1680 15.77%
Non-family households 900 6930 12.99%
Table 14: Housing Problems, Lake Forest
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 6,230 18,240 34.16%
Black, Non-Hispanic 235 535 43.93%
Hispanic 2,700 4,370 61.78%
Asian or Pacific Islander, Non-
Hispanic 1,310 3,870 33.85%
Native American, Non-Hispanic 15 19 78.95%
Total 10,490 27,034 38.80%
Household Type and Size
Family households, <5 people 5800 17525 33.10%
Family households, 5+ people 1640 3165 51.82%
Non-family households 3340 6660 50.15%
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 2740 18,240 15.02%
Black, Non-Hispanic 135 535 25.23%
Hispanic 1855 4,370 42.45%
Asian or Pacific Islander, Non-
Hispanic 660 3,870 17.05%
Native American, Non-Hispanic 15 19 78.95%
Total 5,405 27,034 19.99%
192
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 2395 18,240 13.13%
Black, Non-Hispanic 100 535 18.69%
Hispanic 1340 4,370 30.66%
Asian or Pacific Islander, Non-
Hispanic 435 3,870 11.24%
Native American, Non-Hispanic 15 19 78.95%
Total 4,285 27,034 15.85%
Household Type and Size
Family households, <5 people 1825 17525 10.41%
Family households, 5+ people 445 3165 14.06%
Non-family households 804 6660 12.07%
Table 15: Housing Problems, Mission Viejo
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 8,690 25,265 34.40%
Black, Non-Hispanic 199 389 51.16%
Hispanic 2,105 4,099 51.35%
Asian or Pacific Islander, Non-
Hispanic 955 3,050 31.31%
Native American, Non-Hispanic 20 30 66.67%
Total 11,969 32,833 36.45%
Household Type and Size
Family households, <5 people 7265 22375 32.47%
Family households, 5+ people 950 3305 28.74%
Non-family households 4055 7870 51.52%
193
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 3779 25,265 14.96%
Black, Non-Hispanic 79 389 20.31%
Hispanic 995 4,099 24.27%
Asian or Pacific Islander, Non-
Hispanic 465 3,050 15.25%
Native American, Non-Hispanic 20 30 66.67%
Total 5,338 32,833 16.26%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 3505 25,265 13.87%
Black, Non-Hispanic 60 389 15.42%
Hispanic 865 4,099 21.10%
Asian or Pacific Islander, Non-
Hispanic 335 3,050 10.98%
Native American, Non-Hispanic 20 30 66.67%
Total 4,785 32,833 14.57%
Household Type and Size
Family households, <5 people 1770 22375 7.91%
Family households, 5+ people 245 3305 7.41%
Non-family households 725 7870 9.21%
Table 16: Housing Problems, Orange (City)
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 8,845 24,095 36.71%
Black, Non-Hispanic 365 530 68.87%
Hispanic 7,255 12,030 60.31%
194
Asian or Pacific Islander, Non-
Hispanic 1,810 4,979 36.35%
Native American, Non-Hispanic 45 75 60.00%
Total 18,320 41,709 43.92%
Household Type and Size
Family households, <5 people 8815 23870 36.93%
Family households, 5+ people 4080 6705 60.85%
Non-family households 5800 11369 51.02%
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 4580 24,095 19.01%
Black, Non-Hispanic 235 530 44.34%
Hispanic 5105 12,030 42.44%
Asian or Pacific Islander, Non-
Hispanic 1130 4,979 22.70%
Native American, Non-Hispanic 4 75 5.33%
Total 11,054 41,709 26.50%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 4155 24,095 17.24%
Black, Non-Hispanic 195 530 36.79%
Hispanic 2935 12,030 24.40%
Asian or Pacific Islander, Non-
Hispanic 795 4,979 15.97%
Native American, Non-Hispanic 4 75 5.33%
Total 8,084 41,709 19.38%
Household Type and Size
Family households, <5 people 3145 23870 13.18%
Family households, 5+ people 1105 6705 16.48%
Non-family households 2185 11369 19.22%
195
Table 17: Housing Problems, Rancho Santa Margarita
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 4,505 11,890 37.89%
Black, Non-Hispanic 140 285 49.12%
Hispanic 1,629 2,674 60.92%
Asian or Pacific Islander, Non-
Hispanic 565 1,855 30.46%
Native American, Non-Hispanic 0 0 0%
Total 6,839 16,704 40.94%
Household Type and Size
Family households, <5 people 4000 11285 35.45%
Family households, 5+ people 745 1720 43.31%
Non-family households 2250 3975 56.60%
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 2000 11,890 16.82%
Black, Non-Hispanic 84 285 29.47%
Hispanic 720 2,674 26.93%
Asian or Pacific Islander, Non-
Hispanic 175 1,855 9.43%
Native American, Non-Hispanic 0 0 #DIV/0!
Total 2,979 16,704 17.83%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 1860 11,890 15.64%
Black, Non-Hispanic 85 285 29.82%
Hispanic 500 2,674 18.70%
Asian or Pacific Islander, Non-
Hispanic 130 1,855 7.01%
Native American, Non-Hispanic 0 0 #DIV/0!
196
Total 2,575 16,704 15.42%
Household Type and Size
Family households, <5 people 1220 11285 10.81%
Family households, 5+ people 140 1720 8.14%
Non-family households 570 3975 14.34%
Table 18: Housing Problems, San Clemente
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 7,940 19,490 40.74%
Black, Non-Hispanic 30 125 24.00%
Hispanic 2,005 3,264 61.43%
Asian or Pacific Islander, Non-
Hispanic 310 970 31.96%
Native American, Non-Hispanic 10 20 50.00%
Total 10,295 23,869 43.13%
Household Type and Size
Family households, <5 people 5670 14590 38.86%
Family households, 5+ people 1240 2445 50.72%
Non-family households 3689 7229 51.03%
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 4055 19,490 20.81%
Black, Non-Hispanic 20 125 16.00%
Hispanic 1375 3,264 42.13%
Asian or Pacific Islander, Non-
Hispanic 145 970 14.95%
Native American, Non-Hispanic 10 20 50.00%
Total 5,605 23,869 23.48%
197
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 3685 19,490 18.91%
Black, Non-Hispanic 20 125 16.00%
Hispanic 960 3,264 29.41%
Asian or Pacific Islander, Non-
Hispanic 95 970 9.79%
Native American, Non-Hispanic 10 20 50.00%
Total 4,770 23,869 19.98%
Household Type and Size
Family households, <5 people 1855 14590 12.71%
Family households, 5+ people 405 2445 16.56%
Non-family households 1149 7229 15.89%
Table 19: Housing Problems, San Juan Capistrano
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 3,805 8,630 44.09%
Black, Non-Hispanic 0 0 #DIV/0!
Hispanic 1,915 2,725 70.28%
Asian or Pacific Islander, Non-
Hispanic 115 340 33.82%
Native American, Non-Hispanic 30 80 37.50%
Total 5,865 11,775 49.81%
Household Type and Size
Family households, <5 people 2945 6970 42.25%
Family households, 5+ people 1425 1925 74.03%
Non-family households 1590 2915 54.55%
198
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 2070 8,630 23.99%
Black, Non-Hispanic 0 0 #DIV/0!
Hispanic 1650 2,725 60.55%
Asian or Pacific Islander, Non-
Hispanic 70 340 20.59%
Native American, Non-Hispanic 30 80 37.50%
Total 3,820 11,775 32.44%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 2015 8,630 23.35%
Black, Non-Hispanic 0 0 #DIV/0!
Hispanic 1070 2,725 39.27%
Asian or Pacific Islander, Non-
Hispanic 65 340 19.12%
Native American, Non-Hispanic 30 80 37.50%
Total 3,180 11,775 27.01%
Household Type and Size
Family households, <5 people 1100 6970 15.78%
Family households, 5+ people 555 1925 28.83%
Non-family households 275 2915 9.43%
Table 20: Housing Problems, Santa Ana
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 4,650 12,430 37.41%
Black, Non-Hispanic 435 899 48.39%
Hispanic 36,965 50,935 72.57%
199
Asian or Pacific Islander, Non-
Hispanic 5,440 9,959 54.62%
Native American, Non-Hispanic 63 128 49.22%
Total 47,553 74,351 63.96%
Household Type and Size
Family households, <5 people 18765 34015 55.17%
Family households, 5+ people 22140 27010 81.97%
Non-family households 7055 13590 51.91%
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 2495 12,430 20.07%
Black, Non-Hispanic 234 899 26.03%
Hispanic 29395 50,935 57.71%
Asian or Pacific Islander, Non-
Hispanic 3450 9,959 34.64%
Native American, Non-Hispanic 8 128 6.25%
Total 35,582 74,351 47.86%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 2130 12,430 17.14%
Black, Non-Hispanic 195 899 21.69%
Hispanic 12800 50,935 25.13%
Asian or Pacific Islander, Non-
Hispanic 2155 9,959 21.64%
Native American, Non-Hispanic 10 128 7.81%
Total 17,290 74,351 23.25%
Household Type and Size
Family households, <5 people 8010 34015 23.55%
Family households, 5+ people 4990 27010 18.47%
Non-family households 1809 13590 13.31%
200
Table 21: Housing Problems, Tustin
Demographics of Households with Disproportionate Housing Needs
Disproportionate Housing
Needs Jurisdiction
Households experiencing any of
4 housing problems # with problems # households % with
problems
Race/Ethnicity
White, Non-Hispanic 4,465 10,495 42.54%
Black, Non-Hispanic 380 609 62.40%
Hispanic 5,485 7,705 71.19%
Asian or Pacific Islander, Non-
Hispanic 2,644 6,089 43.42%
Native American, Non-Hispanic 60 120 50.00%
Total 13,034 25,018 52.10%
Household Type and Size
Family households, <5 people 6690 14315 46.73%
Family households, 5+ people 2840 3775 75.23%
Non-family households 3825 7465 51.24%
Households experiencing any of
4 Severe Housing Problems
# with severe
problems # households % with severe
problems
Race/Ethnicity
White, Non-Hispanic 2085 10,495 19.87%
Black, Non-Hispanic 205 609 33.66%
Hispanic 3915 7,705 50.81%
Asian or Pacific Islander, Non-
Hispanic 1519 6,089 24.95%
Native American, Non-Hispanic 10 120 8.33%
Total 7,734 25,018 30.91%
Demographics of Households with Severe Housing Cost Burden
Households with Severe
Housing Cost Burden Jurisdiction
Race/Ethnicity # with severe
cost burden # households % with severe
cost burden
White, Non-Hispanic 1840 10,495 17.53%
Black, Non-Hispanic 170 609 27.91%
Hispanic 1975 7,705 25.63%
Asian or Pacific Islander, Non-
Hispanic 969 6,089 15.91%
Native American, Non-Hispanic 0 120 0.00%
201
Total 4,954 25,018 19.80%
Household Type and Size
Family households, <5 people 2300 14315 16.07%
Family households, 5+ people 589 3775 15.60%
Non-family households 1025 7465 13.73%
A few trends are immediately clear in housing needs in Orange County. The housing problems
data displayed in the charts above include houses that have 1 of 4 housing problems by
race/ethnicity and family type, 1 of 4 severe housing problems by race/ethnicity, and severe
housing cost burden by race/ethnicity and family type. Overall, across the County, Black and
Hispanic residents are more likely to face all of these housing problems, with varying rates across
different jurisdictions.
Some figures in the data above may be inaccurate depending on the number of households of a
particular group in a jurisdiction. For example, 0 Black households are listed in San Juan
Capistrano. It may be that this figure was lower than the margin of error, so figures with low or no
households should carry less weight in indicating frequency of problems. However, the County
data overall gives an idea of housing needs for smaller populations.
In the County, 45.84% of residents overall face at least 1 of 4 housing problems. White and Asian
or Pacific Islander residents have slightly lower rates of housing problems, at 38.22% and 45.26%
respectively, while Black residents have a slightly higher rate of 48.29%. Hispanic residents have
the highest rates at 63.16% countywide. Native American residents have a rate similar to the
average at 48.74%, but the low populations of Native American residents across jurisdictions may
lead to misleading data (which is why they are not as frequently discussed here). Housing problems
are found in differing rates across family types, with 39.66% for families of 5 or less, 65.59% for
families of 5 or more, and 50.53% for non-family households.
Housing problems occur more frequently in more populated areas of the County, including in
Anaheim and Santa Ana in particular. There are some more obvious discrepancies in rates of
housing problems across different demographic groups. Black residents in Aliso Viejo experience
housing problems at a rate of 61.84%, in Orange (city) at 68.87%, in Tustin at 62.40%, and in
Buena Park at 54.49%. Hispanic residents experience rates of housing problems that are high
overall, but significantly higher in central and southern Orange County, at 72.57% in Santa Ana,
71.19% in Tustin, and 70.28% in San Juan Capistrano. Asian residents generally experience
average or lower rates of housing problems, with exceptions in Garden Grove and Santa Ana,
where they experience housing problems at rates of 55.94% and 54.62% respectively.
Rates of severe housing problems are overall low er than housing problems at 27.10%, but more
drastic discrepancies exist compared to the white population. White residents face severe housing
problems at a rate of 19.29%. Black residents experience them at a rate of 28.81%, Hispanic
residents at 44.55%, Asian or Pacific Islander residents at 26.99%, and Native American residents
at 24.97%. Rates of severe housing problems are especially high in parts of Orange County,
including Anaheim, Buena Park, Garden Grove, Orange, San Juan Capistrano, and Santa Ana.
202
Black residents experience severe housing problems at rates of 36.84% in Aliso Viejo and 44.34%
in Orange (city). Hispanic residents face severe housing problems at significantly high rates of
49.60% in Anaheim, 60.55% in San Juan Capistrano, and 50.81% in Tustin, but also higher than
average in Buena Park, Costa Mesa, Garden Grove, La Habra, Laguna Niguel, Lake Forest, Orange
and San Clemente. Asian residents face noticeably high rates of severe housing problems in
Garden Grove, at 36.78%.
Severe housing cost burden is a large but not as frequent problem for residents in Orange County.
The average rate of residents experiencing severe housing cost burden is 19.70% across the county.
Overall, White residents have a rate of 17.30%, Black residents 22.57%, Hispanic residents
24.78%, Asian American or Pacific Islander residents 19.82%, and Native American residents
19.83%. Families of 5 or less have a rate of 13.8%, families of 5 or more 16.95%, and non-family
households 14.39%. Discrepancies across race/ethnicity or family type are much lower than for
housing problems or severe housing problems in the County. Black and Hispanic residents still
face higher than average rates of severe housing cost burdens in some individual jurisdictions,
however. In Orange (city), Black residents experience severe housing cost burden at a rate of
36.79%. Hispanic residents experience rates of housing cost burden at 39.58% in Buena Park , and
39.27% in San Juan Capistrano.
Table 17: Percentage of Overcrowded Households by Race or Ethnicity, 2013-2017
American Community Survey
Geography White,
Non-
Hispanic
Black Native
American
Asian
American
or Pacific
Islander
Hispanic
Orange County, California 1.95% 6.52% 11.38% 7.76% 25.72%
Aliso Viejo city, California 1.47% 0.00% 0.00% 2.79% 7.47%
Anaheim city, California 3.20% 5.94% 27.51% 9.81% 29.07%
Buena Park city, California 4.33% 8.11% 17.03% 7.17% 23.11%
Costa Mesa city, California 2.70% 9.01% 16.30% 7.20% 25.16%
Fountain Valley city,
California
1.93% 0.00% 0.00% 6.46% 15.37%
Fullerton city, California 2.63% 4.20% 23.42% 6.42% 23.52%
Garden Grove city,
California
3.46% 9.69% 15.77% 12.23% 30.05%
Huntington Beach city,
California
1.50% 6.45% 0.00% 3.16% 14.59%
Irvine city, California 4.21% 11.78% 0.00% 6.79% 6.30%
Laguna Niguel city,
California
0.67% 2.91% 0.00% 1.52% 13.74%
La Habra city, California 3.86% 0.00% 5.30% 11.84% 22.09%
Lake Forest city, California 1.95% 8.93% 17.17% 4.68% 16.52%
La Palma city, California 1.70% 0.00% 0.00% 6.63% 14.91%
Mission Viejo city, California 0.72% 5.35% 0.00% 3.76% 6.30%
203
Orange city, California 1.67% 11.81% 5.02% 8.05% 21.46%
Rancho Santa Margarita
city, California
1.40% 0.00% 0.00% 1.50% 8.33%
San Clemente city,
California
1.36% 0.00% 0.00% 3.52% 18.12%
San Juan Capistrano city,
California
0.11% 100.00% 0.00% 0.00% 26.44%
Santa Ana city, California 3.88% 7.82% 26.59% 14.75% 42.93%
Tustin city, California 1.35% 10.52% 4.35% 7.35% 28.28%
The tables above indicate overcrowdedness in the County and its jurisdictions. Some of these
numbers are inaccurate, due to low populations in a given jurisdiction (especially for Black or
Native American residents). In the County, White residents experience an overcrowdedness rate
of 1.95%, Black residents 6.52%, Native American residents 11.38%, Asian American or Pacific
Islander residents 7.76%, and Hispanic residents 25.72%. Hispanic residents face especially high
rates of overcrowdedness. This is especially true in Anaheim and Santa Ana, where their
overcrowdedness rates are 29.07% and 42.93%, respectively.
Which areas in the jurisdiction and Region experience the greatest housing burdens? Which of
these areas align with segregated areas, integrated areas, or R/ECAPs and what are the
predominant race/ethnicity or national origin groups in such areas?
204
Map 1: Housing Problems in North Orange County, Race
205
Map 2: Housing Problems in Central Orange County, Race
206
Map 3: Housing Problems in South Orange County, Race
207
Map 4: Housing Problems in North Orange County, National Origin
208
Map 5: Housing Problems in Central Orange County, National Origin
209
Map 6: Housing Problems in South Orange County, National Origin
210
Map 7: Housing Problems in North Orange County, National Origin
211
Map 8: Housing Problems in Central Orange County, National Origin
212
Map 9: Housing Problems in South Orange County, National Origin
213
Patterns in housing problems described earlier are present in the maps above. While housing
problems are generally evenly dispersed throughout the County, there are some exceptions, which
tend to have higher numbers of Hispanic residents. This is seen in the high number of Hispanic
residents in Anaheim and Santa Ana, both of which have slightly higher percentages of housing
problems. In Central Orange County, east Fountain Valley also has higher percentages of
households with housing problems in areas with higher numbers of Hispanic residents. The same
is the case for Hispanic residents in San Juan Capistrano, Lake Forest and Laguna Woods. While
the charts above suggested that Black residents similarly had higher rates of housing problems
than White and Asian residents, those patterns are more difficult to view in maps due to the lower
population of Black residents overall.
Asian or Pacific Islander residents generally live in areas with fewer housing problems, with one
notable exception. Garden Grove, which has slightly higher rates of housing problems than its
surroundings, also has a noticeably high population of Asian or Pacific Islander residents.
These patterns are further explained by national origin maps. Map 4 shows that high numbers of
Vietnamese residents are found in Garden Grove, which does have slightly higher rates of housing
problems. Filipino residents in the areas between Buena Park and Anaheim, similarly reside in
areas with higher rates of housing problems. The same holds for Filipino residents in Lake Forest
and Laguna Hills, as seen in Map 6. Mexican residents have the most noticeable pattern of living
in areas with higher rates of housing problems. Mexican residents in Santa Ana, Anaheim, Costa
Mesa, and San Juan Capistrano live in areas with higher rates of housing problems, as seen in
Maps 7, 8 and 9.
Additional Information
Beyond the HUD-provided data, provide additional relevant information, if any, about
disproportionate housing needs in the jurisdiction and Region affecting groups with other
protected characteristics.
The program participant may also describe other information relevant to its assessment of
disproportionate housing needs. For PHAs, such information may include a PHA’s overriding
housing needs analysis.
Contributing Factors of Disproportionate Housing Needs
Please see the Appendix for the following Contributing Factors to Disproportionate Housing
Needs:
● Availability of affordable units in a range of sizes
● Displacement of residents due to economic pressures
● Displacement of and/or lack of housing support for victims of domestic violence, dating
violence, sexual assault, and stalking
● Lack of access to opportunity due to high housing costs
● Lack of private investments in specific neighborhoods
● Lack of public investments in specific neighborhoods, including services or amenities
214
● Land use and zoning laws
● Lending discrimination
● Loss of affordable housing
● Source of income discrimination
215
C. PUBLICLY SUPPORTED HOUSING ANALYSIS
Overview of Housing Authorities in Orange County
Orange County Housing Authority
The Orange County Housing Authority (OCHA) operates numerous special housing programs.
The Housing Choice Voucher (HCV) program provides subsidies to help qualifying participants
pay for homeownership expenses. The Family Self-Sufficiency (FSS) program helps HCV
program participants gain employment to support themselves and their families by working with
other agencies for employment assistance. The Family Unification Program (FUP) promotes
family unification by providing HCV assistance specifically to families for whom housing
represents a barrier to children and parents living together. The Non-Elderly Disabled (NED)
program provides HCV for non-elderly disabled families with demonstrated need for supportive
services. Finally, the Veterans Affairs Supportive Housing (VASH) program, run jointly through
the Department of Housing and the Department of Veteran Affairs, provides housing subsidies
and other services to homeless veterans with mental and addictive disorders.
Most HCV programs are offered with a focus on guaranteeing freedom of choice as to where
families can live or use HCV program assistance. Some additional HCV “Project-Based” vouchers
are also available with HCV vouchers tied to specific housing units.
Anaheim Housing Authority
The Anaheim Housing Authority (AHA) operates multiple housing programs. The Anaheim
Housing Choice Voucher (HCV) program allows participating families to move into units of their
choice so long as property owners agree to participate in the HCV program. They also operate a
Project-Based Voucher (PBV) program that provides rental assistance at specific complexes within
the city. The AHA also maintains an affordable housing list for individuals and families looking
to rent units at an affordable rate.
Additionally, the AHA operates several programs run through the Department of Housing and
Urban Development (HUD). The Community Development Block Grant (CDBG) program
delivers funding to agencies and businesses that provide benefits to low-and-moderate income
persons. The Emergency Solutions Grant (ESG) program funds non -profit organizations
sponsoring projects for low-and-moderate income persons. The HOME Investments Partnerships
program provides funding for local government for plans designed to increase the supply of
affordable housing. Finally the Housing Opportunity for Persons with AIDS (HOPWA) program
provides funding for low-to-moderate income persons living with HIV or AIDS.
Garden Grove Housing Authority
The Garden Grove Housing Authority (GGHA) operates several housing programs. GGHA
maintains information for landlords and tenants on their website. Additionally, GGHA operates a
rental subsidy program (HCV) for eligible participants based on income. Finally, applicants who
216
have qualified for housing assistance in Garden Grove are permitted to maintain assistance through
mobility and portability programs when such an applicant leaves the city of Garden Grove.
Santa Ana Housing Authority
The Santa Ana Housing Authority (SAHA) operates several housing programs. SAHA operates
an HCV program for Housing Choice Vouchers within the City. Additionally, SAHA operates a
project-based voucher program with HCV vouchers tied to specific complexes within the City.
SAHA also has numerous resources for landlords and tenants, including a database of affordable
housing and pocket resources for homeless services.
SAHA was also recently recognized by HUD for the work done by the “Foster Youth to
Independence Initiative” which targets housing assistance to young people aging out of foster care
who are at extreme risk of experiencing homelessness. This project was done in tandem with the
United Way.
1. Analysis
a. Publicly Supported Housing Demographics
The Publicly Supported Housing section analyzes federally funded affordable housing and other
types of affordable housing, to determine whether the level of need is being met and whether
patterns of affordable housing siting concentrate minorities in low opportunity areas, among other
things. In Orange County, each category of publicly supported housing (public housing, Project -
Based Section 8, Other Multifamily Housing, Housing Choice Vouchers, and Low-Income
Housing Tax Credit [LIHTC] units) is represented, although that representation varies greatly
depending on the individual municipality. Affordable housing (including LIHTC) makes up 5%
or less of the total housing stock in all but six of the entitlement jurisdictions in this analys is
(Anaheim, Garden Grove, Irvine, La Palma, Santa Ana, and Westminster; incomplete data is
available for Buena Park, which likely counts among these as well). In each of these jurisdictions,
LIHTC and Housing Choice Voucher units tend to predominate, and there is no Public Housing at
all, indicating an overall preference for private housing development. Overall, the amount of
publicly supported housing available in Orange County does not rise to meet the level of need,
although progress is being made.
Table 1: Publicly Supported Housing Units by Program Category, Orange County14
Housing Units # %
Total housing units 219,058 -
Public Housing N/a N/a
Project-based Section 8 429 0.20%
Other Multifamily 33 0.02%
14 Data from Inventory Management System (IMS)/PIH Information Center (PIC ),
https://files.hudexchange.info/resources/documents/AFFH-T-Data-Documentation-(AFFHT0004a)-March-2018.pdf
217
HCV Program 2,286 1.04%
LIHTC 2,110 0.96%
Table 2: Publicly Supported Housing Units by Program Category, Aliso Viejo
Housing Units # %
Total housing units 19,786 -
LIHTC 128 0.65%
Table 3: Publicly Supported Housing Units by Program Category, Anaheim
Housing Units # %
Total housing units 103,787 -
Public Housing N/a N/a
Project-based Section 8 279 0.27%
Other Multifamily N/a N/a
HCV Program 5,089 4.90%
LIHTC 3,017 2.91%
Table 4: Publicly Supported Housing Units by Program Category, Buena Park
Housing Units # %
Total housing units 24,741 -
Public Housing N/a N/a
Project-based Section 8 110 0.44%
Other Multifamily N/a N/a
HCV Program 762 3.08%
LIHTC 185 0.75%
Table 5: Publicly Supported Housing Units by Program Category, Costa Mesa
Housing Units # %
Total housing units 41,933 -
Public Housing N/a N/a
Project-based Section 8 110 0.26%
Other Multifamily N/a N/a
218
HCV Program 604 1.44%
LIHTC 266 0.63%
Table 6: Publicly Supported Housing Units by Program Category, Fountain Valley
Housing Units # %
Total housing units 19,050 -
Public Housing N/a N/a
Project-based Section 8 71 0.37%
Other Multifamily N/a N/a
HCV Program 502 2.64%
LIHTC 154 0.81%
Table 7: Publicly Supported Housing Units by Program Category, Fullerton
Housing Units # %
Total housing units 47,991 -
Public Housing N/a N/a
Project-based Section 8 101 0.21%
Other Multifamily 48 0.10%
HCV Program 715 1.49%
LIHTC 858 1.79%
Table 8: Publicly Supported Housing Units by Program Category, Garden Grove
Housing Units # %
Total housing units 48,499 -
Public Housing N/a N/a
Project-based Section 8 225 0.46%
Other Multifamily N/a N/a
HCV Program 2,681 5.53%
LIHTC 671 1.38%
219
Table 9: Publicly Supported Housing Units by Program Category, Huntington Beach
Housing Units # %
Total housing units 78,583 -
Public Housing N/a N/a
Project-based Section 8 377 0.48%
Other Multifamily N/a N/a
HCV Program 976 1.24%
LIHTC 607 0.77%
Table 10: Publicly Supported Housing Units by Program Category, Irvine
Housing Units # %
Total housing units 83,616 -
Public Housing N/a N/a
Project-based Section 8 717 0.86%
Other Multifamily 23 0.03%
HCV Program 1,146 1.37%
LIHTC 2,329 2.79
Table 11: Publicly Supported Housing Units by Program Category, La Habra
Housing Units # %
Total housing units 19,932 -
Public Housing N/a N/a
Project-based Section 8 148 0.74%
Other Multifamily N/a N/a
HCV Program 178 0.89%
Table 12: Publicly Supported Housing Units by Program Category, La Palma
Housing Units # %
Total housing units 5,039 -
LIHTC 304 6.03%
220
Table 13: Publicly Supported Housing Units by Program Category, Laguna Niguel
Housing Units # %
Total housing units 25,565 -
Public Housing N/a N/a
Project-based Section 8 156 0.61%
Other Multifamily N/a N/a
HCV Program 102 0.40%
Table 14: Publicly Supported Housing Units by Program Category, Lake Forest
Housing Units # %
Total housing units 27,044 -
Public Housing N/a N/a
Project-based Section 8 N/a N/a
Other Multifamily N/a N/a
HCV Program 275 1.02%
LIHTC 187 0.69%
Table 15: Publicly Supported Housing Units by Program Category, Mission Viejo
Housing Units # %
Total housing units 34,177 -
Public Housing N/a N/a
Project-based Section 8 N/a N/a
Other Multifamily N/a N/a
HCV Program 226 0.66%
LIHTC 296 0.87%
Table 16: Publicly Supported Housing Units by Program Category, Newport Beach
Housing Units # %
Total housing units 44,242 -
Public Housing N/a N/a
Project-based Section 8 100 0.23%
Other Multifamily N/a N/a
221
HCV Program 139 0.31%
LIHTC 205 0.46%
Table 17: Publicly Supported Housing Units by Program Category, Orange (City)
Housing Units # %
Total housing units 45,363 -
Public Housing N/a N/a
Project-based Section 8 197 0.43%
Other Multifamily N/a N/a
HCV Program 642 1.42%
LIHTC 964 2.13%
Table 18: Publicly Supported Housing Units by Program Category, Rancho Santa
Margarita
Housing Units # %
Total housing units 17,408 -
Public Housing N/a N/a
Project-based Section 8 N/a N/a
Other Multifamily N/a N/a
HCV Program 138 0.79%
Table 19: Publicly Supported Housing Units by Program Category, San Clemente
Housing Units # %
Total housing units 25,556 -
Public Housing N/a N/a
Project-based Section 8 72 0.28%
Other Multifamily N/a N/a
HCV Program 123 0.48%
LIHTC 393 1.54%
Table 20: Publicly Supported Housing Units by Program Category, San Juan Capistrano
Housing Units # %
Total housing units 12,905 -
222
LIHTC 215 1.67%
Table 21: Publicly Supported Housing Units by Program Category, Santa Ana
Housing Units # %
Total housing units 76,075 -
Public Housing N/a N/a
Project-based Section 8 801 1.05%
Other Multifamily N/a N/a
HCV Program 2,773 3.65%
LIHTC 1,092 1.44%
Table 22: Publicly Supported Housing Units by Program Category, Tustin
Housing Units # %
Total housing units 26,633 -
Public Housing N/a N/a
Project-based Section 8 100 0.38%
Other Multifamily N/a N/a
HCV Program 524 1.97%
LIHTC 672 2.52%
Table 23: Publicly Supported Housing Units by Program Category, Westminster
Housing Units # %
Total housing units 27,695 -
Public Housing N/a N/a
Project-based Section 8 97 0.35%
Other Multifamily N/a N/a
HCV Program 2,169 7.83%
LIHTC 439 1.59%
LIHTC
According to the California Tax Credit Allocation Committee, there are 175 LIHTC developments
in Orange County, some of which are designated for specific populations. These developments
include 15,092 low-income units, with 2 reserved for At-Risk populations, 79 for large families,
30 Non-Targeted, 46 for Seniors, 8 for Special Needs populations, 4 Single Room Occupancy
223
(SRO), and 6 which are not categorized. There are no active LIHTC developments in La Habra,
Laguna Niguel, or Rancho Santa Margarita.
i. Are certain racial/ethnic groups more likely to be residing in one program category of
publicly supported housing than other program categories (public housing, project-
based Section 8, Other Multifamily Assisted developments, and Housing Choice
Voucher (HCV) in the jurisdiction?
Please note: rows for which all values are zero or n/a have been deleted for space
Table 24: Publicly Supported Housing Demographics, Orange County
Orange
County White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
Project-Based
Section 8 164 40.80% 9 2.24% 88 21.89% 138 34.33%
Other
Multifamily 22 95.65% 0 0.00% 1 4.35% 0 0.00%
HCV Program 808 35.96% 156 6.94% 412 18.34% 866 38.54%
LIHTC 1352 25.12% 254 4.72% 1621 30.11% 991 18.41%
Total
Households 140,530 67.71% 2,907 1.40% 30,185 14.54% 29,767 14.34%
0-30% of AMI 14,094 61.62% 259 1.13% 4,388 19.18% 3,541 15.48%
0-50% of AMI 23,293 50.78% 503 1.10% 9,148 19.94% 6,728 14.67%
0-80% of AMI 43,952 56.98% 926 1.20% 14,322 18.57% 11,131 14.43%
Region White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
Public Housing 683 6.99% 2,627 26.90% 6,110 62.56% 344 3.52%
Project-Based
Section 8 9,154 23.86% 6,942 18.10% 10,365 27.02% 11,753 30.64%
Other
Multifamily 1,707 33.38% 465 9.09% 1,094 21.39% 1,839 35.96%
HCV Program N/a N/a N/a N/a N/a N/a N/a N/a
Total
Households 1,766,510 41.80% 333,080 7.88% 1,405,070 33.25% 629,349 14.89%
0-30% of AMI 215,775 29.59% 86,225 11.83% 305,885 41.95% 105,314 14.44%
224
0-50% of AMI 343,565 26.07% 135,740 10.30% 587,685 44.60% 175,814 13.34%
0-80% of AMI 590,895 28.77% 195,155 9.50% 905,370 44.09% 272,549 13.27%
Table 25: Publicly Supported Housing Demographics, Aliso Viejo 15
Aliso Viejo White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
LIHTC 239 75.39% 22 6.94% 91 28.71% 15 4.73%
Table 26: Publicly Supported Housing Demographics, Anaheim
Anaheim White Black Hispanic
Asian or
Pacific Islander
Housing Type # % # % # % # %
Project-Based Section 8 60 22.22% 19 7.04% 50 18.52% 141 52.22%
HCV Program 1,328 27.62% 412 8.57% 1,849 38.46% 1,210 25.17%
LIHTC 2029 23.08% 506 5.76% 4720 53.70% 792 9.01%
Total Households 38,125 38.49% 3,014 3.04% 39,630 40.01% 16,470 16.63%
0-30% of AMI 5,245 28.95% 755 4.17% 8,675 47.88% 3,070 16.94%
0-50% of AMI 8,870 25.76% 1,305 3.79% 17,310 50.28% 5,005 14.54%
0-80% of AMI 15,335 28.28% 1,845 3.40% 26,855 49.52% 7,835 14.45%
Table 27: Publicly Supported Housing Demographics, Buena Park
Buena Park White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
Project-Based Section 8 16 13.91% 1 0.87% 4 3.48% 94 81.74%
HCV Program 194 25.80% 167 22.21% 229 30.45% 161 21.41%
LIHTC 287 21.91% 135 10.31% 374 28.55% 306 23.36%
Total Households 7,755 33.70% 1,120 4.87% 7,060 30.68% 6,669 28.98%
15 HUD-provided demographic data for residents of publicly supported housing in Aliso V iejo was not available, but
data from CTAC reflecting the demographics of LIHTC residents is reflected above.
225
0-30% of AMI 740 21.76% 200 5.88% 1,270 37.35% 1,160 34.12%
0-50% of AMI 1,645 23.40% 285 4.05% 2,885 41.04% 1,864 26.51%
0-80% of AMI 3,015 26.03% 570 4.92% 4,435 38.28% 3,084 26.62%
Table 28: Publicly Supported Housing Demographics, Costa Mesa
Costa Mesa White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
Project-Based Section 8 78 72.22% 0 0.00% 16 14.81% 14 12.96%
HCV Program 377 60.32% 18 2.88% 107 17.12% 122 19.52%
LIHTC 174 52.73% 7 2.12% 34 10.30% 58 17.58%
Total Households 25,410 62.60% 509 1.25% 9,730 23.97% 4,021 9.91%
0-30% of AMI 3,010 50.00% 140 2.33% 2,140 35.55% 600 9.97%
0-50% of AMI 4,980 44.19% 165 1.46% 4,225 37.49% 1,102 9.78%
0-80% of AMI 8,995 48.10% 290 1.55% 6,530 34.92% 1,897 10.14%
Table 29: Publicly Supported Housing Demographics, Fountain Valley
Fountain Valley White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
Project-Based Section 8 10 14.93% 0 0.00% 0 0.00% 57 85.07%
HCV Program 107 20.66% 3 0.58% 37 7.14% 369 71.24%
LIHTC 98 49.00% 1 0.50% 24 12.00% 92 46.00%
Total Households 10,548 56.47% 255 1.37% 2,194 11.75% 5,339 28.58%
0-30% of AMI 1,044 48.45% 0 0.00% 215 9.98% 849 39.40%
0-50% of AMI 1,649 41.29% 25 0.63% 519 12.99% 1,354 33.90%
0-80% of AMI 3,388 47.27% 125 1.74% 1,059 14.77% 2,084 29.07%
226
Table 30: Publicly Supported Housing Demographics, Fullerton
Fullerton White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
Project-Based Section 8 9 8.91% 0 0.00% 1 0.99% 91 90.10%
Other Multifamily 35 76.09% 3 6.52% 6 13.04% 2 4.35%
HCV Program 308 43.08% 88 12.31% 235 32.87% 81 11.33%
LIHTC 919 35.02% 77 2.93% 1212 46.19% 197 7.51%
Total Households 20,560 46.53% 1,338 3.03% 11,365 25.72% 9,904 22.41%
0-30% of AMI 2,625 35.02% 254 3.39% 2,490 33.22% 1,835 24.48%
0-50% of AMI 4,560 34.43% 364 2.75% 4,465 33.71% 2,985 22.54%
0-80% of AMI 7,445 36.45% 544 2.66% 6,935 33.95% 4,420 21.64%
Table 31: Publicly Supported Housing Demographics, Garden Grove
Garden Grove White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
Project-Based Section 8 11 4.91% 2 0.89% 2 0.89% 209 93.30%
HCV Program 140 5.14% 33 1.21% 243 8.92% 2,303 84.51%
LIHTC 192 11.15% 29 1.68% 431 25.03% 552 32.06%
Total Households 14,423 31.41% 549 1.20% 13,059 28.44% 17,061 37.16%
0-30% of AMI 1,685 18.36% 195 2.12% 2,744 29.89% 4,409 48.03%
0-50% of AMI 2,920 18.20% 230 1.43% 5,164 32.19% 6,964 43.41%
0-80% of AMI 5,765 22.38% 335 1.30% 8,594 33.36% 10,128 39.32%
227
Table 32: Publicly Supported Housing Demographics, Huntington Beach
Huntington Beach White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
Project-Based Section 8 150 39.68% 4 1.06% 41 10.85% 182 48.15%
HCV Program 448 43.92% 35 3.43% 163 15.98% 370 36.27%
LIHTC 580 53.51% 50 4.61% 356 32.84% 45 4.15%
Total Households 54,285 73.20% 558 0.75% 10,165 13.71% 7,589 10.23%
0-30% of AMI 5,115 65.03% 4 0.05% 1,565 19.90% 1,075 13.67%
0-50% of AMI 8,815 57.45% 43 0.28% 3,075 20.04% 1,725 11.24%
0-80% of AMI 17,035 61.80% 108 0.39% 5,505 19.97% 2,960 10.74%
Table 33: Publicly Supported Housing Demographics, Irvine
Irvine White Black Hispanic
Asian or
Pacific Islander
Housing Type # % # % # % # %
Project-Based Section 8 433 60.99% 20 2.82% 39 5.49% 217 30.56%
Other Multifamily 12 52.17% 6 26.09% 0 0.00% 5 21.74%
HCV Program 588 49.45% 212 17.83% 195 16.40% 191 16.06%
LIHTC 1176 25.79% 175 3.84% 568 12.46% 614 13.46%
Total Households 42,999 53.05% 1,485 1.83% 6,714 8.28% 27,793 34.29%
0-30% of AMI 5,079 46.30% 245 2.23% 895 8.16% 4,155 37.88%
0-50% of AMI 7,409 44.73% 465 2.81% 1,665 10.05% 5,460 32.96%
0-80% of AMI 12,664 48.96% 575 2.22% 2,524 9.76% 8,339 32.24%
228
Table 34: Publicly Supported Housing Demographics, La Habra
La Habra White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
Project-Based Section 8 46 31.72% 0 0.00% 51 35.17% 48 33.10%
HCV Program 41 24.85% 4 2.42% 113 68.48% 7 4.24%
Total Households 7,415 39.82% 430 2.31% 8,895 47.77% 1,565 8.40%
0-30% of AMI 1,015 34.00% 75 2.51% 1,590 53.27% 255 8.54%
0-50% of AMI 1,645 27.51% 160 2.68% 3,415 57.11% 410 6.86%
0-80% of AMI 3,315 33.60% 205 2.08% 5,305 53.78% 650 6.59%
Table 35: Publicly Supported Housing Demographics, La Palma 16
La Palma White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
LIHTC 144 15.62% 35 3.80% 156 16.92% 454 49.24%
Table 36: Publicly Supported Housing Demographics, Laguna Niguel
Laguna Niguel White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
Project-Based Section 8 122 82.99% 3 2.04% 12 8.16% 10 6.80%
HCV Program 81 79.41% 5 4.90% 11 10.78% 4 3.92%
Total Households 18,550 76.09% 410 1.68% 2,575 10.56% 2,085 8.55%
0-30% of AMI 1,435 68.99% 55 2.64% 235 11.30% 210 10.10%
0-50% of AMI 2,150 52.83% 100 2.46% 485 11.92% 320 7.86%
0-80% of AMI 4,325 59.00% 155 2.11% 1,015 13.85% 600 8.19%
16 As with Aliso Viejo, HUD-provided demographic data for residents of publicly supported housing was not
available for La Palma.
229
Table 37: Publicly Supported Housing Demographics, Lake Forest
Lake Forest White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
HCV Program 170 62.04% 36 13.14% 48 17.52% 20 7.30%
LIHTC 38 7.45% 38 7.45% 188 36.86% 28 5.49%
Total Households 17,714 65.95% 560 2.08% 4,310 16.05% 3,539 13.18%
0-30% of AMI 1,129 56.17% 25 1.24% 510 25.37% 319 15.87%
0-50% of AMI 1,954 44.16% 105 2.37% 1,125 25.42% 599 13.54%
0-80% of AMI 4,144 49.57% 235 2.81% 2,135 25.54% 1,134 13.56%
Table 38: Publicly Supported Housing Demographics, Mission Viejo
Mission Viejo White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
HCV Program 166 73.45% 20 8.85% 28 12.39% 12 5.31%
LIHTC 201 44.47% 4 0.88% 112 24.78% 47 10.40%
Total Households 25,645 77.02% 585 1.76% 3,739 11.23% 2,504 7.52%
0-30% of AMI 1,935 75.73% 45 1.76% 365 14.29% 124 4.85%
0-50% of AMI 3,295 58.84% 70 1.25% 920 16.43% 314 5.61%
0-80% of AMI 6,680 64.11% 270 2.59% 1,635 15.69% 719 6.90%
Table 39: Publicly Supported Housing Demographics, Newport Beach
Newport Beach White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
Project-Based Section
8 85 87.63% 0 0.00% 3 3.09% 9 9.28%
HCV Program 99 70.21% 14 9.93% 15 10.64% 13 9.22%
LIHTC 238 59.20% 8 1.99% 147 36.57% 12 2.99%
Total Households 32,490 84.94% 135 0.35% 2,485 6.50%
2,47
7 6.48%
230
0-30% of AMI 3,130 78.54% 0 0.00% 400 10.04% 404 10.14%
0-50% of AMI 4,940 70.07% 0 0.00% 730 10.35% 653 9.26%
0-80% of AMI 8,355 74.90% 40 0.36% 1,030 9.23% 893 8.01%
Table 40: Publicly Supported Housing Demographics, Orange (City)
Orange (City) White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
Project-Based Section 8 89 49.17% 2 1.10% 76 41.99% 13 7.18%
HCV Program 221 35.25% 44 7.02% 218 34.77% 144 22.97%
LIHTC 943 39.03% 47 1.95% 1347 55.75% 104 4.30%
Total Households 24,840 57.94% 430 1.00% 11,370 26.52% 5,535 12.91%
0-30% of AMI 2,880 50.79% 50 0.88% 1,880 33.16% 740 13.05%
0-50% of AMI 4,290 41.67% 65 0.63% 3,785 36.77% 1,270 12.34%
0-80% of AMI 8,130 45.70% 200 1.12% 6,635 37.30% 1,800 10.12%
Table 41: Publicly Supported Housing Demographics, Rancho Santa Margarita
Rancho Santa
Margarita White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
HCV Program 90 64.29% 20 14.29% 22 15.71% 8 5.71%
Total Households 11,575 70.36% 228 1.39% 2,580 15.68% 1,800 10.94%
0-30% of AMI 735 68.37% 24 2.23% 265 24.65% 30 2.79%
0-50% of AMI 1,060 48.07% 64 2.90% 570 25.85% 130 5.90%
0-80% of AMI 2,595 57.10% 114 2.51% 1,110 24.42% 290 6.38%
231
Table 42: Publicly Supported Housing Demographics, San Clemente
San Clemente White Black Hispanic
Asian or
Pacific Islander
Housing Type # % # % # % # %
Project-Based Section 8 56 78.87% 0 0.00% 10 14.08% 5 7.04%
HCV Program 98 78.40% 4 3.20% 20 16.00% 3 2.40%
LIHTC 592 59.80% 13 1.31% 432 43.64% 34 3.43%
Total Households 19,935 82.43% 130 0.54% 2,658 10.99% 880 3.64%
0-30% of AMI 1,795 72.38% 35 1.41% 364 14.68% 125 5.04%
0-50% of AMI 3,080 62.41% 35 0.71% 843 17.08% 190 3.85%
0-80% of AMI 5,730 69.29% 55 0.67% 1,358 16.42% 270 3.26%
Table 43: Publicly Supported Housing Demographics, San Juan Capistrano17
San Clemente White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
LIHTC 207 81.50% 3 1.18% 30 11.81% 5 1.97%
Table 44: Publicly Supported Housing Demographics, Santa Ana
Santa Ana White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
Project-Based Section 8 45 5.70% 7 0.89% 195 24.68% 496 62.78%
HCV Program 181 10.20% 49 2.76% 557 31.38% 986 55.55%
LIHTC 1659 48.24% 44 1.28% 2990 86.94% 88 2.56%
Total Households 12,725 17.47% 1,299 1.78% 48,985 67.26% 9,002 12.36%
0-30% of AMI 1,370 9.10% 140 0.93% 11,260 74.77% 2,155 14.31%
0-50% of AMI 2,635 8.81% 310 1.04% 22,620 75.66% 3,594 12.02%
0-80% of AMI 5,370 11.10% 685 1.42% 35,940 74.29% 5,523 11.42%
17 As with Aliso Viejo and La Palma, HUD-provided demographic data for residents of publicly supported housing
in San Juan Capistrano was not available.
232
Table 45: Publicly Supported Housing Demographics, Tustin
Tustin White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
Project-Based Section 8 29 28.71% 0 0.00% 12 11.88% 60 59.41%
HCV Program 181 34.74% 82 15.74% 194 37.24% 62 11.90%
LIHTC
480
24.33%
85
4.31%
1052
53.32%
223
11.30%
Total Households 10,755 43.06% 693 2.77% 7,365 29.49% 5,633 22.55%
0-30% of AMI 1,115 35.07% 104 3.27% 1,385 43.57% 494 15.54%
0-50% of AMI 2,075 31.64% 189 2.88% 2,995 45.66% 974 14.85%
0-80% of AMI 3,635 32.59% 318 2.85% 5,125 45.95% 1,684 15.10%
Table 46: Publicly Supported Housing Demographics, Westminster
Westminster White Black Hispanic
Asian or Pacific
Islander
Housing Type # % # % # % # %
Project-Based Section 8 2 2.08% 0 0.00% 0 0.00% 94 97.92%
HCV Program 146 6.33% 17 0.74% 93 4.03% 2,044 88.56%
LIHTC 104 15.16% 18 2.62% 118 17.20% 400 58.31%
Total Households 9,604 35.42% 190 0.70% 5,115 18.86% 11,769 43.40%
0-30% of AMI 1,429 23.80% 25 0.42% 1,080 17.99% 3,445 57.37%
0-50% of AMI 2,359 21.85% 35 0.32% 2,115 19.59% 5,820 53.91%
0-80% of AMI 3,859 24.49% 90 0.57% 3,460 21.96% 7,684 48.77%
In Project-Based Section 8 developments, the majority racial/ethnic group in every entitlement
jurisdiction is either White or Asian American and Pacific Islander. In San Clemente, Newport
Beach, Laguna Niguel, and Costa Mesa, White residents make up a substantial majority, while in
Irvine they make up a majority and in Orange (City) and Orange County they make up a plurality.
In La Habra, Hispanics make up a plurality, but Asian American or Pacific Islanders and White
residents trail them by 2 and 4 percentage points, respectively. Asian American or Pacific Islanders
make up a supermajority in Buena Park, Fountain Valley, Garden Grove, and Westminster, a
majority in Anaheim, Santa Ana, and Tustin, and a plurality in Huntington Beach. In Other
233
Multifamily Housing, White residents make up a majority in Irvine and a supermajority in
Fullerton and Orange County. By far, Housing Choice Voucher households are the most evenly
distributed across racial/ethnic groups. Asian American or Pacific Islanders make up a
supermajority of HCV units in Westminster, Fountain Valley, and Garden Grove, and a majority
in Santa Ana. They also make up a plurality in Orange County, followed closely by White
residents. White residents make up a supermajority in Laguna Niguel, Mission Viejo, San
Clemente, and Newport Beach, a majority in Lake Forest, Rancho Santa Margarita, and Costa
Mesa, and a plurality in Fullerton, Huntington Beach, Irvine, and Orange (City, followed closely
by Hispanics). Hispanics make up a plurality of HCV residents in Anaheim, Buena Park, and
Tustin, and a majority of residents in La Habra. LIHTC developments are also quite diverse, with
Hispanics predominating in Anaheim, Buena Park, Fullerton, Lake Forest, Orange (City), Santa
Ana, and Tustin, and Asian American or Pacific Islanders predominating in Garden Grove, La
Palma, and Westminster, and bringing up a close second in Fountain Valley; the other cities have
predominantly-White LIHTC demographics.
ii. Compare the racial/ethnic demographics of each program category of publicly
supported housing for the jurisdiction to the demographics of the same program
category in the region.
In the region, there are several important differences in occupancy between various types of
publicly supported housing. Firstly, there is Public Housing in the broader Los Angeles-Long Beach-
Anaheim region, which is predominantly Hispanic, with Black residents making up the next highest
share (at a rate that far outstrips the general population). Project-Based Section 8 Housing in the
region is fairly evenly spread out across racial/ethnic group, with the largest group (Asian
American or Pacific Islanders) making up only 31%. Other Multifamily units are less diverse, and
split fairly evenly between White (33%) and Asian American or Pacific Islander (36%) residents,
with Hispanic (21%) and Black (9%) residents trailing farther behind. Housing Choice Voucher
and LIHTC data are not available at the regional level.
iii. Compare the demographics, in terms of protected class, of residents of each program
category of publicly supported housing (public housing, project-based Section 8, Other
Multifamily Assisted developments, and HCV) to the population in general, and persons
who meet the income eligibility requirements for the relevant program category of
publicly supported housing in the jurisdiction and region. Include in the comparison, a
description of whether there is a higher or lower proportion of groups based on
protected class.
In comparison to the demographics of the Urban County and each of the entitlement cities, White
residents tend to be either proportionally represented in Project-Based Section 8 and Other
Multifamily housing and to be either proportionally represented or underrepresented among
Housing Choice Voucher holders, including when controlling for household income. Data for
LIHTC does not offer an apples-to-apples comparison because the state does not disaggregate
White, Hispanic residents from White, Non-Hispanic residents. Meanwhile, Hispanics tend to be
underrepresented in Project-Based Section 8 developments and among Housing Choice Voucher
holders and to be participate in the LIHTC program proportion to their share of the income-eligible
population. This may result from eligibility rules for Project-Based Section 8 and the Housing
234
Choice Voucher program that exclude undocumented immigrants. By contrast, the LIHTC
program does not bar undocumented immigrants. Asian American or Pacific Islanders tend to be
either proportionally represented or overrepresented across types of publicly supported housing,
with the greatest overrepresentation in Project-Based Section 8 developments. Black residents
make up a disproportionate share of Housing Choice Voucher holders but participate in other
programs in proportion to their share of the income-eligible population.
There are a few cities with somewhat more stark contrasts between the income-eligible population
and the occupancy of particular types of publicly supported housing. In Anaheim, Black residents
make up a disproportionate share of occupants of all types of publicly supported housing, not just
of Housing Choice Voucher holders. In Buena Park, Fountain Valley, Fullerton, Garden Grove,
and Westminster, the proportion of Project-Based Section 8 residents that is Asian or Pacific
Islander is particularly extreme. In Costa Mesa, White residents are highly overrepresented in
Project-Based Section 8 housing, which includes a 204-unit predominantly-white senior housing
development. In Fullerton, White residents are highly overrepresented in Other Multifamily
housing. In La Habra, Hispanic residents are slightly overrepresented among Housing Choice
Voucher holders despite being underrepresented in most places. In Laguna Niguel, White residents
are strongly overrepresented in both types of publicly supported housing that are present. In the
city of Orange, unlike in most cities, Asian or Pacific Islander residents are underrepresented
among residents of Project-Based Section 8 housing.
b. Publicly Supported Housing Location and Occupancy
i. Describe patterns in the geographic location of publicly supported housing by program
category (public housing, project-based Section 8, Other Multifamily Assisted
developments, HCV, and LIHTC) in relation to previously discussed segregated areas
and R/ECAPs in the jurisdiction and region.
Map 1: Publicly Supported Housing and Race/Ethnicity
There are four R/ECAPs in Orange County, and only one LIHTC development located within one
of them. Overall, publicly supported housing in the County is far more likely to be concentrated
in the northernmost part, nearer to Los Angeles, than in the southern part. Developments are
concentrated along the main thoroughfare of Highway 5, and are particularly prevalent in
Anaheim, Santa Ana, and Irvine. It should be noted that there is a particularly high concentration
of Housing Choice Voucher use in the Garden Grove-Westminster area, which does not seem to
have a particularly high concentration of hard units of publicly supported housing. These areas
correspond with areas of high Hispanic and Asian American or Pacific Islander segregation and
concentration.
In the broader region, Public Housing is concentrated in the cities of Long Beach and Los Angeles
and particularly in South LA and East LA. There is also some public housing in West Hollywood
as well as in the eastern Los Angeles County cities of Baldwin P ark and La Puente. With the
exception of West Hollywood, these tend to be areas of concentrated Black and/or Hispanic
population. In South LA, East LA, and Long Beach, there is a significant overlap between the
location of Public Housing developments and R/ECAPs. Other Multifamily developments are
235
proportionally concentrated in Los Angeles County as opposed to Orange County but are well
integrated throughout Los Angeles County. There is a significant number of Other Multifamily
developments in communities with West LA and the San Fernando Valley that tend to have
relatively little publicly supported housing overall. The part of the region (outside of Orange
County) with the least Other Multifamily housing is actually the predominantly Hispanic far
eastern portion of Los Angeles County. Project-Based Section 8 developments are also relatively
integrated throughout the region, albeit with a slightly higher concentration in Los Angeles County
than in Orange County. LIHTC developments are relatively integrated throughout the region but
with some concentration near Downtown LA. Downtown LA is fairly segregated and has a
concentration of R/ECAPs but is also subject to the most intense gentrification pressures in the
region. Housing Choice Voucher utilization is concentrated in South LA and adjacent communities
like Westmont, in Norwalk in southeastern Los Angeles County, in Lancaster and Palmdale in
northeastern Los Angeles County, and in Anaheim and Westminster within Orange County. There
is some overlap with the location of R/ECAPs although the pattern is not as pronounced as for
Public Housing. Areas with concentrations of voucher holders in Los Angeles County are
especially likely to be areas of Black population concentration.
i. Describe patterns in the geographic location for publicly supported housing that
primarily serves families with children, elderly persons, or persons with disabilities in
relation to previously discussed segregated areas or R/ECAPs in the jurisdiction and
region.
Families with children
Non-Targeted and Large Family developments are the most plentiful in the County, and are most
often concentrated in diverse, metropolitan pockets of the County. However, families with children
are more likely to occupy LIHTC units or use a Housing Choice Voucher than to reside in Other
Multifamily or Project-Based Section 8 units. In the broader region, publicly supported housing
for families with children across categories is comparatively likely to be located in R/ECAP areas
than in more integrated areas or predominantly White areas.
Elderly
In terms of elderly populations, a significant proportion of Project-Based Section 8 units house
elderly residents. Additionally, in Costa Mesa, Fountain Valley, and San Juan Capistrano, all
publicly supported housing is either specifically reserved for seniors or records 90-100% elderly
residents in their statistics. Each of these communities are near the coast, driving up the cost of
real estate. San Juan Capistrano and Costa Mesa are more heavily White and Hispanic, while
Fountain Valley is more diverse and have a more significant Asian American or Pacific Islander
population. In the broader region, publicly supported housing for elderly residents across
categories is comparatively likely to be located in non-R/ECAP areas.
Persons with disabilities
In terms of residents with disabilities, there are LIHTC developments specifically reserved for
people with special needs in the Urban County (Jackson Aisle Apartments),18 Anaheim (Avenida
18 The Orange County Urban County Program is comprised of the County unincorporated area and thirteen cities.
The participating cities include Placentia, Yorba Linda, Brea, Cypress, Dana Point, Laguna Beach, Laguna Hills,
Laguna Woods, La Palma, Los Alamitos, Seal Beach, Stanton, and Villa Park .
236
Villas, Casa Alegre, Diamond Aisle Apartments), Fullerton (Fullerton Heights), Huntington Beach
(Pacific Sun Apartments), and Santa Ana (Guest House, Vista Del Rio). Additionally, the
percentage of people with disabilities occupying Other Multifamily units in the Urban County,
Fullerton, and Irvine is very high compared to the rest of the County. In the broader region, publicly
supported housing for persons with disabilities across categories is comparatively likely to be
located in non-R/ECAP areas.
ii. How does the demographic composition of occupants of publicly supported housing in
R/ECAPS compare to the demographic composition of occupants of publicly supported
housing outside of R/ECAPs in the jurisdiction and region?
Only jurisdictions which contain R/ECAPs have been included below. Rows with only 0
and/or N/A values have been deleted for space
Table 48: Irvine
Irvine
Total
# units
(occup
ied)
%
White
%
Black
%
Hispanic
% Asian
or
Pacific
Islander
%
Families
with
children
%
Elderly
% with a
disability
Project-based
Section 8
R/ECAP tracts 98 60.00% 2.00% 9.00% 29.00% 16.83% 68.32% 6.93%
Non R/ECAP
tracts 619 61.15% 2.95% 4.92% 30.82% 14.04% 60.45% 14.04%
Other
Multifamily
R/ECAP tracts N/a N/a N/a N/a N/a N/a N/a N/a
Non R/ECAP
tracts 22 52.17% 26.09% 0.00% 21.74% 0.00% 50.00% 70.83%
HCV
Program
R/ECAP tracts 18 85.00% 0.00% 5.00% 10.00% 0.00% 56.52% 43.48%
Non R/ECAP
tracts 955 48.79% 18.08% 16.65% 16.20% 34.88% 36.00% 22.48%
There are only four R/ECAPs in Orange County, and they are all located in Irvine or Santa Ana.
However, there is only one publicly supported housing development located within one of those
R/ECAPs – Wakeham Grant Apartments (LIHTC), in Santa Ana. The data presented by HUD is
outdated, as it does not identify the same exact R/ECAPs as this analysis, but it is nevertheless
presented as it may give insight into former R/ECAPs which exhibit similar characteristics. Using
the former Irvine R/ECAPs, the occupancy of Project-Based Section 8 units was remarkably
similar both within and outside those tracts, with the exception of residents with a disability, who
were more plentiful outside of R/ECAPs. With regard to the Housing Choice Voucher Program,
the results were markedly different. Surprisingly, the proportion of all voucher holders that were
White within R/ECAPS was nearly double that outside of R/ECAPs. This is likely an aberration
237
resulting from the extremely small number of voucher holders in R/ECAPs in Irvine. The
percentages of elderly and disabled residents, which often coincide, were similarly high.
Table 49: Santa Ana
Santa Ana
Total
# units
(occup
ied)
%
White
%
Black
%
Hispanic
% Asian
or Pacific
Islander
%
Families
with
children
%
Elderly
% with a
disability
Project-based
Section 8
R/ECAP tracts N/a N/a 0.00% N/a N/a N/a N/a N/a
Non R/ECAP
tracts 790 5.70% 0.89% 24.68% 62.78% 3.60% 92.31% 14.64%
HCV Program
R/ECAP tracts 130 6.02% 3.61% 26.51% 63.86% 22.35% 47.06% 25.88%
Non R/ECAP
tracts 2,512 10.40% 2.72% 31.62% 55.14% 25.97% 50.88% 21.17%
LIHTC
R/ECAP tracts 126 8.83% 1.42% 84.33% 5.98% N/A N/A N/A
Non R/ECAP
tracts 966 52.72% 1.26% 87.24% 2.17% N/A N/A N/A
Like the analysis of Irvine above, the HUD tables provided here are outdated and utilize old
R/ECAPs, but they are nevertheless useful in comparing tracts with similar characteristics. The
LIHTC data is accurate, however, and reflects the only publicly supported housing development
within a R/ECAP – Wakeham Grant Apartments. The outdated data on Housing Choice Vouchers
shows a general tendency for the demographic composition of voucher holders to be quite similar
inside and outside R/ECAPs, with a slight tendency toward higher Asian American or Pacific
Islander representation in R/ECAPs. The LIHTC demographics tell a similar story. It should be
noted that LIHTC demographic information has been self-reported to the California state treasurer,
and does not always match the way HUD reports demographics, especially when it comes to race
versus ethnicity. This might account for the extremely high co-incidence of White and Hispanic
residents. Overall, it seems there is not much difference within and outside R/ECAPs for LIHTC
units in Santa Ana.
i. Do any developments of public housing, properties converted under the RAD, and
LIHTC developments have a significantly different demographic composition, in terms
of protected class, than other developments of the same category for the jurisdiction?
Describe how these developments differ.
See Tables in Appendix
In Westminster, the Royale Apartments stand out for having a plurality-Hispanic population, while
every other LIHTC development has a strong majority of Asian American or Pacific Islander
238
residents. In Orange (City), Casa Ramon stands out as the only Project-Based Section 8
development with a supermajority-Hispanic population, while the others are majority-White. In
Newport Beach, Lange Drive Family and Newport Veterans Housing stand out for their majority-
Hispanic and large Black populations, respectively, compared to the other far larger developments
in the city which are supermajority-White. In Irvine, The Parklands stands out among Project-
Based Section 8 developments for its large Asian American or Pacific Islander population,
compared to all the other developments which are predominantly White. Similarly, four LIHTC
developments have large Asian populations (The Arbor at Woodbury, Montecito Vista Apartment
Homes, Doria Apartment Homes Phase I, Anesi Apartments) compared to the other
predominantly-White developments. In Huntington Beach, the two Project-Based Section 8
developments are polar opposites, with one 60% White while the other is 63% Asian. Meanwhile,
most of the LIHTC developments in Huntington Beach are predominantly White, while Hermosa
Vista Apartments is predominantly Hispanic. In Garden Grove, Briar Crest+Rosecrest Apartments
and Malabar Apartments stand out at LIHTC developments with large Hispanic populations, while
the other developments are predominantly Asian American or Pacific Islander. In Fullerton,
Ventana Senior Apartments stands out for its large Asian American or Pacific Islander population,
while every other LIHTC development is predominantly White or Hispanic. In Buena Park, Park
Landing Apartments and Emerald Gardens Apartments stand out for their large White and
Hispanic populations, respectively, compared to the other LIHTC developments which are
predominantly Asian American or Pacific Islander. The Project-Based Section 8 developments are
markedly different as well, with 73% White residents at Newport House and 91% Asian American
or Pacific Islander residents at Casa Santa Maria. In Orange County, Continental Gardens
Apartments and Tara Village Apartments stand out for their large Asian American or Pacific
Islander populations, while the rest of the LIHTC developments are predominantly White or
Hispanic.
i. Provide additional relevant information, if any, about occupancy, by protected class,
in other types of publicly supported housing for the jurisdiction and region.
Effective January 2020, the Tenant Protection Act of 2019, a statewide rent gouging law, restricts
rent increases to 5% plus the local rate of inflation per year. As of January 2020, the rate of inflation
in the region was 3.1%. Additionally, San Juan Capistrano has a Mobile Home Rent Control
Ordinance, working to preserve access to a source of unsubsidized affordable housing. However,
cutting in the opposite direction, Ellis Act evictions of rent-controlled units have the potential to
counteract rent control laws. Data about Ellis Act evictions in the area is not widely available, so
it is difficult to estimate the effect they may have.
In October 2019, Governor Newsom signed into law SB 329, prohibiting discrimination in housing
based on source of income statewide.
San Clemente, Irvine, Huntington Beach, and Newport Beach all have inclusionary zoning
programs. The Anaheim Housing Authority implements the Affordable Housing Program, which
consists of multifamily apartment complexes that include affordable units.19 These units maintain
rents at levels below regular market rent rates through agreements with the City, but is not a
mandatory program. People on the Interest List are notified as affordable units become available.
19 https://www.anaheim.net/770/Affordable-Housing
239
The Orange County Housing Authority maintains a similar list of deed -restricted units for the
entire county.20 In addition to these housing authorities, several cities maintain similar lists of
deed-restricted units and many provide development incentives to develop affordable housing
units.
i. Compare the demographics of occupants of developments in the jurisdiction, for each
category of publicly supported housing (public housing, project-based Section 8, Other
Multifamily Assisted developments, properties converted under RAD, and LIHTC) to
the demographic composition of the areas in which they are located. For the
jurisdiction, describe whether developments that are primarily occupied by one
race/ethnicity are located in areas occupied largely by the same race/ethnicity.
Describe any differences for housing that primarily serves families with children,
elderly persons, or persons with disabilities.
See table in Appendix
There is quite a bit of inconsistency when comparing the individual demographics of publicly
supported housing developments to the census tracts where they are located. In the Urban County,
for example, the tracts tend to be predominantly White, but the developments themselves are far
more likely to be majority-Hispanic or majority-Asian American or Pacific Islander. In Anaheim,
the developments are consistently located in majority-Hispanic tracts, but the developments
themselves do not always mirror those demographics. In Buena Park, on the other hand, the
developments tend to be mostly Asian American or Pacific Islander, while located in mostly
Hispanic tracts. Similarly, Costa Mesa’s developments are located in Hispanic tracts, but the
developments are predominantly Asian American or Pacific Islander. Fountain Valley and
Fullerton both stand out, with their singular Project-Based Section 8 developments being
supermajority Asian American or Pacific Islander, but located in majority-White tracts. In Garden
Grove, nearly every LIHTC has an inverse relationship between its tract and development
population, with majority-Hispanic developments located in Asian American or Pacific Islander
tracts, and vice versa.
Huntington Beach has two specific standouts in Huntington Villa Yorba, which is majority-Asian
American or Pacific Islander in a White tract, and Hermosa Vista Apartments, majority-Hispanic
in a White tract. In Irvine, several Project-Based Section 8 developments are predominantly White
while located in Asian American or Pacific Islander tracts; for LIHTC developments this trend
holds. In La Habra, Casa El Centro Apartments is predominantly Asian American or Pacific
Islander, while located in a Hispanic tract. Newport Beach is home to Newport Veterans Housing,
which is 15% Black (far greater than the general Black population) in a White tract.
In Orange (City), the Project-Based Section 8 development Casa Ramon is predominantly
Hispanic, while located in a White tract. Meanwhile, Casa Del Rio is predominantly-White but
located in a Hispanic tract. Nearly every tract containing a LIHTC development is predominantly-
Hispanic, while several of the developments’ populations are mostly White. In San Clemente, there
are three LIHTC developments that are predominantly-Hispanic but are located in White tracts. In
San Juan Capistrano, all three LIHTC developments (each restricted to seniors), have
predominantly-White populations in Hispanic tracts. In Santa Ana, every development is located
20 http://www.ochousing.org/civicax/filebank/blobdload.aspx?BlobID=39906
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in a Hispanic tract, but there are four predominantly-Asian American or Pacific Islander
developments and one predominantly-White development. In Tustin, the only Project-Based
Section 8 development is predominantly-Asian American or Pacific Islander in a White tract, and
every LIHTC development is predominantly-Asian American or Pacific Islander, but located in a
White or Hispanic tract. In Westminster, every tract is predominantly-Asian American or Pacific
Islander, but the Royales Apartments are predominantly Hispanic.
c. Disparities in Access to Opportunity
i. Describe any disparities in access to opportunity for residents of publicly supported
housing in the jurisdiction and region, including within different program categories
(public housing, project-based Section 8, Other Multifamily Assisted Developments,
HCV, and LIHTC) and between types (housing primarily serving families with
children, elderly persons, and persons with disabilities) of publicly supported housing.
Disparities in access to opportunity, when compared to publicly supported housing, cut in
conflicting directions. School proficiency, for instance, is very good in the Urban County, along
the coast, in the southern part of the County, and on the northeast edge; this cuts out most of the
more urban areas, where publicly supported housing is concentrated. Job proximity is far more
variable, although with a general tendency to be located along the main thoroughfares – the same
as publicly supported housing. The entire County has good low transportation cost index scores,
with slightly better scores in the northern part of the County where most of the publicly supported
housing is clustered. Environmental health is very poor overall, but better to the south, where there
is far less publicly supported housing.
Contributing Factors of Publicly Supported Housing Location and Occupancy
Consider the listed factors and any other factors affecting the jurisdiction and region. Identify
factors that significantly create, contribute to, perpetuate, or increase the severity of fair housing
issues related to publicly supported housing, including Segregation, R/ECAPs, Disparities in
Access to Opportunity, and Disproportionate Housing Needs. For each contributing factor that is
significant, note which fair housing issue(s) the selected contributing factor relates to.
Please see the Appendix for the following Contributing Factors to Publicly Supported
Housing Location and Occupancy:
Admissions and occupancy policies and procedures, including preferences in publicly
supported housing
Community opposition
Displacement of residents due to economic pressures
Displacement of and/or lack of housing support for victims of domestic violence,
dating violence, sexual assault, and stalking
Impediments to mobility
Lack of access to opportunity due to high housing costs
Lack of meaningful language access for individuals with limited English proficiency
Lack of local or regional cooperation
241
Lack of private investment in specific neighborhoods
Lack of public investment in specific neighborhoods, including services and
amenities
Land use and zoning laws
Loss of affordable housing
Occupancy codes and restrictions
Quality of affordable housing information programs
Siting selection policies, practices, and decisions for publicly supported housing,
including discretionary aspects of Qualified Allocation Plans and other programs
Source of income discrimination
242
D. Disability and Access
Population Profile
Map 1: Disability by Type, North Orange County
243
Map 1: Disability by Type, Central Orange County
244
Map 1: Disability by Type, South Orange County
245
Table 4: Disability by Type, Orange County, Region
Orange County Region
Disability Type # % # %
Hearing Difficulty 81,297 2.59% 333,537 2.53%
Vision Difficulty 51,196 1.63% 247,670 1.88%
Cognitive Difficulty 99,317 3.16% 480,601 3.65%
Ambulatory Difficulty 133,232 4.24% 677,592 5.14%
Self-Care Difficulty 61,615 1.96% 327,895 2.49%
Independent Living Difficulty 104,705 3.34% 526,534 4.00%
Table 5: Aliso Viejo
Disability Type # %
Hearing Difficulty 914 1.80%
Vision Difficulty 503 0.99%
Cognitive Difficulty 1,140 2.25%
Ambulatory Difficulty 1,148 2.27%
Self-Care Difficulty 669 1.32%
Independent Living Difficulty 913 1.80%
Table 6: Anaheim
Disability Type # %
Hearing Difficulty 7,308 2.11%
Vision Difficulty 4,967 1.43%
Cognitive Difficulty 11,360 3.27%
Ambulatory Difficulty 15,684 4.52%
Self-Care Difficulty 7,324 2.11%
Independent Living Difficulty 12,332 3.55%
Table 7: Buena Park
Disability Type # %
Hearing Difficulty 2,403 2.90%
Vision Difficulty 1,387 1.68%
Cognitive Difficulty 2,290 2.77%
Ambulatory Difficulty 4,242 5.13%
Self-Care Difficulty 1,843 2.23%
Independent Living Difficulty 2,793 3.38%
Table 8: Costa Mesa
Disability Type # %
Hearing Difficulty 2,462 2.19%
Vision Difficulty 1,967 1.75%
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Cognitive Difficulty 3,899 3.47%
Ambulatory Difficulty 4,401 3.91%
Self-Care Difficulty 1,737 1.54%
Independent Living Difficulty 3,278 2.91%
Table 9: Fountain Valley
Disability Type # %
Hearing Difficulty 1,842 3.26%
Vision Difficulty 685 1.21%
Cognitive Difficulty 2,394 4.24%
Ambulatory Difficulty 3,093 5.48%
Self-Care Difficulty 1,266 2.24%
Independent Living Difficulty 2,261 4.01%
Table 10: Fullerton
Disability Type # %
Hearing Difficulty 3,344 2.40%
Vision Difficulty 2,406 1.73%
Cognitive Difficulty 4,478 3.22%
Ambulatory Difficulty 6,425 4.62%
Self-Care Difficulty 2,683 1.93%
Independent Living Difficulty 4,992 3.59%
Table 11: Garden Grove
Disability Type # %
Hearing Difficulty 5,132 2.95%
Vision Difficulty 3,044 1.75%
Cognitive Difficulty 6,805 3.91%
Ambulatory Difficulty 8,226 4.73%
Self-Care Difficulty 3,996 2.30%
Independent Living Difficulty 7,328 4.21%
Table 12: Huntington Beach
Disability Type # %
Hearing Difficulty 5,818 2.91%
Vision Difficulty 3,392 1.70%
Cognitive Difficulty 7,239 3.62%
Ambulatory Difficulty 9,226 4.61%
Self-Care Difficulty 3,952 1.98%
Independent Living Difficulty 6,816 3.41%
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Table 13: Irvine
Disability Type # %
Hearing Difficulty 4,154 1.62%
Vision Difficulty 2,032 0.79%
Cognitive Difficulty 5,481 2.14%
Ambulatory Difficulty 6,719 2.62%
Self-Care Difficulty 3,527 1.37%
Independent Living Difficulty 5,713 2.23%
Table 14: La Habra
Disability Type # %
Hearing Difficulty 1,803 2.92%
Vision Difficulty 1,044 1.69%
Cognitive Difficulty 2,272 3.68%
Ambulatory Difficulty 3,659 5.93%
Self-Care Difficulty 1,530 2.48%
Independent Living Difficulty 2,354 3.81%
Table 15: La Palma
Disability Type # %
Hearing Difficulty 421 2.66%
Vision Difficulty 262 1.66%
Cognitive Difficulty 476 3.01%
Ambulatory Difficulty 825 5.22%
Self-Care Difficulty 496 3.14%
Independent Living Difficulty 547 3.46%
Table 16: Laguna Niguel
Disability Type # %
Hearing Difficulty 1,815 2.78%
Vision Difficulty 807 1.23%
Cognitive Difficulty 1,965 3.00%
Ambulatory Difficulty 1,943 2.97%
Self-Care Difficulty 938 1.43%
Independent Living Difficulty 1,910 2.92%
Table 17: Lake Forest
Disability Type # %
Hearing Difficulty 2,141 2.62%
Vision Difficulty 715 0.88%
Cognitive Difficulty 2,001 2.45%
Ambulatory Difficulty 2,705 3.31%
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Self-Care Difficulty 1,371 1.68%
Independent Living Difficulty 2,451 3.00%
Table 18: Mission Viejo
Disability Type # %
Hearing Difficulty 3,325 3.46%
Vision Difficulty 1,719 1.79%
Cognitive Difficulty 3,474 3.61%
Ambulatory Difficulty 5,015 5.22%
Self-Care Difficulty 2,574 2.68%
Independent Living Difficulty 3,937 4.10%
Table 19: Newport Beach
Disability Type # %
Hearing Difficulty 2,487 2.87%
Vision Difficulty 1,341 1.55%
Cognitive Difficulty 2,265 2.62%
Ambulatory Difficulty 3,243 3.75%
Self-Care Difficulty 1,330 1.54%
Independent Living Difficulty 2,619 3.03%
Table 20: Orange (City)
Disability Type # %
Hearing Difficulty 2,921 2.14%
Vision Difficulty 1,841 1.35%
Cognitive Difficulty 4,106 3.01%
Ambulatory Difficulty 5,357 3.93%
Self-Care Difficulty 2,762 2.02%
Independent Living Difficulty 4,334 3.18%
Table 21: Rancho Santa Margarita
Disability Type # %
Hearing Difficulty 677 1.38%
Vision Difficulty 442 0.90%
Cognitive Difficulty 838 1.71%
Ambulatory Difficulty 1,108 2.26%
Self-Care Difficulty 477 0.97%
Independent Living Difficulty 715 1.46%
Table 22: San Clemente
Disability Type # %
Hearing Difficulty 1,950 3.01%
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Vision Difficulty 783 1.21%
Cognitive Difficulty 1,581 2.44%
Ambulatory Difficulty 2,060 3.18%
Self-Care Difficulty 929 1.43%
Independent Living Difficulty 1,675 2.59%
Table 23: San Juan Capistrano
Disability Type # %
Hearing Difficulty 1,181 3.29%
Vision Difficulty 744 2.07%
Cognitive Difficulty 1,134 3.16%
Ambulatory Difficulty 2,144 5.97%
Self-Care Difficulty 1,251 3.48%
Independent Living Difficulty 1,653 4.60%
Table 24: Santa Ana
Disability Type # %
Hearing Difficulty 6,745 2.04%
Vision Difficulty 9,075 2.74%
Cognitive Difficulty 9,177 2.77%
Ambulatory Difficulty 11,321 3.42%
Self-Care Difficulty 5,603 1.69%
Independent Living Difficulty 9,146 2.76%
Table 25: Tustin
Disability Type # %
Hearing Difficulty 1,749 2.19%
Vision Difficulty 1,216 1.52%
Cognitive Difficulty 2,308 2.89%
Ambulatory Difficulty 2,894 3.63%
Self-Care Difficulty 1,162 1.46%
Independent Living Difficulty 2,353 2.95%
Table 26: Westminster
Disability Type # %
Hearing Difficulty 3,399 3.71%
Vision Difficulty 1,959 2.14%
Cognitive Difficulty 5,517 6.02%
Ambulatory Difficulty 6,308 6.89%
Self-Care Difficulty 2,964 3.24%
Independent Living Difficulty 5,665 6.19%
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How are people with disabilities geographically dispersed or concentrated in the jurisdiction and
region, including R/ECAPs and other segregated areas identified in previous sections?
ACS Disability Information
According to the 2013-2017 American Community Survey (ACS) 5-Year Estimates, 81,297
residents of Orange County have hearing disabilities, which represents 2.59% of the county’s
population; 51,196 residents (1.63%) have vision disabilities; 99,317 residents (3.16%) have
cognitive disabilities; 133,232 residents (4.24%) have ambulatory disabilities; 61,615 residents
(1.96%) have self-care disabilities; and 104,705 residents (3.34) have independent living
disabilities. Across the cities collaborating on this Analysis, concentrations of persons with
particular types of disabilities vary widely. In Aliso Viejo, Irvine, Laguna Niguel, Lake Forest,
Rancho Santa Margarita, San Clemente, Santa Ana, and Tustin, concentrations of persons with
various types of disabilities are generally lower than they are countywide. In Anaheim, Buena
Park, Fountain Valley, Garden Grove, La Habra, Mission Viejo, San Juan Capistrano, and
Westminster, concentrations of persons with various types of disabilities are generally higher than
they are countywide. In Costa Mesa, Fullerton, Huntington Beach, La Palma, Newport Beach, and
Orange, concentrations of persons with various types of disabilities are generally similar to
countywide levels. There are partial exceptions to these overall trends. For example, in Santa Ana,
a higher proportion of residents have vision disabilities than is the case countywide despite
concentrations of persons with other types of disabilities being lower. Additionally, although some
cities have much lower or much higher concentrations of residents with particular types of
disabilities, differences in others are more modest. For example, concentrations of persons with
various types of disabilities in Westminster are much higher than in Mission Viejo, another city
that has higher concentrations of persons with various types of disabilities than Orange County as
a whole.
Communities with higher concentrations of persons with disabilities are somewhat more likely to
be located in the more racially and ethnically diverse northern portion of the county than the y are
in the southern portion of the county. Six out of the eight cities that have higher concentrations of
persons with disabilities across most types of disabilities are located in the northern part of the
county. At the same time, the two exceptions to this trend – Mission Viejo and San Juan Capistrano
– are notable in that they are both majority-White cities. Additionally, diverse cities in northern
Orange County, like Santa Ana and Tustin, have relatively low concentrations of persons with
disabilities. This may stem in part from the fact that these communities have relatively youthful
populations and disability status is highly correlated with age. There is no overlap between areas
of concentration of persons with disabilities and R/ECAPs.
17.1% of people with disabilities have incomes below the poverty line, as opposed to 11.7% of
individuals without disabilities. Although a breakdown of poverty status by type of disability is
not available through the American Community Survey (ACS), it is clear that the need for
affordable housing is greater among people with disabilities than it is among people without
disabilities. Another indicator of disability and limited income are the number of people receiving
Supplemental Social Security (SSI) which is limited to people with disabilities. According to the
2013-2017 ACS, 44,540 of households receive SSI (4.3% of total households), which is such a
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small subsidy that all of the recipients are extremely low-income. Not all SSI recipients have the
types of disabilities that necessitate accessible units.
The broader region, which includes Los Angeles County in addition to Orange County, has higher
concentrations of persons with all types of disabilities than Orange County with one exception.
The percentage of persons with hearing disabilities is marginally higher in Orange County than in
the broader region.
Describe whether these geographic patterns vary for people with each type of disability or for
people with disabilities in different age ranges for the jurisdiction and region.
In addition to the broader patterns described above, there are some other patterns of concentration
based on both type of disability and disability status by age. Garden Grove has higher
concentrations of persons with self-care and independent living disabilities, as well as higher
concentrations of elderly persons with disabilities. La Habra has elevated concentrations of persons
with ambulatory disabilities while Laguna Niguel has lower concentrations of persons with
ambulatory disabilities. All categories of disabilities become more prevalent as individuals age,
with the number of people in Orange County 65 and over (131,765) with a disability nearly
matches the amount of people under 65 (139,497) with a disability.
Housing Accessibility
Describe whether the jurisdiction and region have sufficient affordable, accessible housing in a
range of unit sizes.
Accessibility Requirement for Federally-Funded Housing
HUD’s implementation of Section 504 of the Rehabilitation Act of 1973 (24 CFR Part 8) requires
that federally financed housing developments have five percent (5%) of total units be accessible
to individuals with mobility disabilities and an additional two percent (2%) of total units be
accessible to individuals with sensory disabilities. It requires that each property, including site and
common areas, meet the Federal Uniform Accessibility Standards (UFAS) or HUD’s Alternative
Accessibility Standard.
In Orange County, there are 104 Other Multifamily Housing and 4,090 Project -Based Section 8
units that are subject to Section 504 of the Rehabilitation Act. 81 people with disabilities reside
in Multifamily Housing, and 549 reside in Project-Based Section 8 units. At this time, we do not
know how many accessible units are in Project Based Section 8 units. The HOME Partnership
Program is a grant of federal funds for housing, therefore, these units are subject to Section 504.
HUD regularly publishes Performance Snapshots of HOME program participants’ activities over
time. Of HOME program participants in Orange County, Anaheim has produced 16 Section 504
compliant units, Costa Mesa has produced four Section 504 compliant units, Fullerton has
produced three Section 504 compliant units, Garden Grove has not produced any Section 504
compliant units, Huntington Beach has produced seven Section 504 compliant units, Irvine has
produced 123 Section 504 compliant units, Orange County has produced 27 Section 504 compliant
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units, Orange has produced three Section 504 compliant units, Santa Ana has produced 16 Section
504 compliant units, and Westminster has produced one Section 504 compliant unit.
Low Income Housing Tax Credit (LIHTC) Units
According to the California Tax Credit Allocation Committee (CTCAC)’s LIHTC database, there
are 158 LIHTC developments currently in service. In these 158 developments, there are 16,201
affordable units. All of these developments were put into service after 1991, meaning that they
have all been built according to 1991 Fair Housing Act accessibility requirements. LIHTC
developments are categorized as non-targeted, large family, senior, SRO, special needs, and at
risk. Non-targeted: 32; Large family: 70; Senior: 44; SRO: 4; special needs: 6; at risk: 2; 158 total.
Within Orange County, LIHTC developments are not evenly distributed as there are far fewer in
the southern portion of Orange County with entire cities such as Rancho Santa Margarita, Mission
Viejo, and Lake Forest not having any LIHTC developments. Communities in central and northern
Orange County have higher concentrations of LIHTC developments, including in Anaheim, Irvine,
and Santa Ana.
In 2015, CTCAC has issued guidance stating that the accessibility requirements of the California
Building Code (CBC) for public housing (Chapter 11B) apply to LIHTC developments. Chapter
11B is the California equivalent of the 2010 ADA Standards. Section 1.9.1.2.1. of the CBC states
that the accessibility requirements apply to “any building, structure, facility, complex …used by
the general public.” Facilities made available to the public, included privately owned buildings.
CTAC has expanded the requirement so that 10% of total units in a LIHTC development must be
accessible to people with mobility disabilities and that 4% be accessible to people with sensory
(hearing/vison) disabilities.
Also, effective 2015, CTCAC required that 50% of total units in a new construction project and
25% of all units in a rehabilitation project located on an accessible path will be mobility accessible
units in accordance with CBC Chapter 11B. CTAC also provides incentives for developers to
include additional accessible units through its Qualified Allocation Plan. LIHTC units comprise
an important segment of the supply of affordable, accessible units in Orange County.
Housing Choice Vouchers
5,045 people with disabilities reside in units assisted with Housing Choice Vouchers in Orange
County, but this does not represent a proxy for actual affordable, accessible units. Rather, Housing
Choice Vouchers are a mechanism for bringing otherwise unaffordable housing, which may or
may not be accessible, within reach of low-income people with disabilities. Unless another source
of federal financial assistance is present, units assisted with Housing Choice Vouchers are not
subject to Section 504 although participating landlords remain subject to the Fair Housing Act’s
duty to provide reasonable accommodations and to allow tenants to make reasonable modifications
at their own expense.
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Fair Housing Amendments Act Units
The Fair Housing Amendments Act of 1988 (FHAA) covers all multifamily buildings of four or
more units that were first occupied on or after March 13, 1991 – not just affordable housing
developments. The FHAA added protections for people with disabilities and prescribed certain
basic accessibility standards, such as one building entrance must be accessible; there must be an
accessible route throughout the development, and public rooms and common rooms must be
accessible to people with disabilities. Although these accessibility requirements are not as
intensive as those of Section 504, they were a first step in opening many apartment developments
to people with disabilities regardless of income level. The FHAA was also very helpful for middle-
income and upper-income people with disabilities also need accessible housing. It is important to
note that FHAA units are not the same as accessible units under Section 504 or ADA Title II.
Therefore, utilizing FHAA units as a proxy for the number of accessible housing units available
or required under Section 504 or ADA Title II does not produce an accurate count. Although they
are not fully accessible, these units are an important source of housing for people with disabilities
who do not need a mobility or hearing/vision unit.
In Orange County, 39,047 units in structures with 5 or more units have been built from 2000 to the
present. Additionally, 81,362 units in structures with 5 or more units were built from 1980 through
1999. If it is assumed that 45% of such units were constructed from 1991 through 1999, then there
would be an additional 36,613 units in multifamily housing that was subject to the design and
construction requirements of the Fair Housing Act at the time of its construction. Combined with
the total built from 2000 to the present, that totals a potential 75,660 units in structures covered by
the Fair Housing Act’s design and construction standards.
Affordable, Accessible Units in a Range of Sizes
Data breaking down affordable, accessible units by number of bedrooms is not available for private
housing. For Publicly Supported Housing, a supermajority (74.67%) of Project -Based Section 8
units are 0-1 bedroom units, as are Other Multifamily units (84.54%, the other 15% having 2
bedrooms). A plurality of Housing Choice Vouchers are also limited to 0-1 bedroom units
(43.97%). 5,561 households or 26.20% of Housing Choice Voucher occupants are also households
with children, the highest of any category of publicly supported housing (followed by Project -
Based Section 8, with 9.62%). It appears that affordable, accessible units that can accommodate
families with children or individuals with live-in aides are extremely limited in Orange County.
Although data reflecting the percentage of families with children that include children with
disabilities is not available, about 2.9% of all children in the County have a disability. If children
with disabilities are evenly distributed across families with children, about 9,500 families in the
County include a child with a disability.
Summary
Based on available data, the supply of affordable, accessible units in Orange County is insufficient
to meet the need. In the County, some 81,297 residents have hearing difficulty, 51,196 residents
have vision difficulty, and 133,232 residents have ambulatory difficulty, potentially requiring the
use of accessible units. Meanwhile, the data indicates there may be roughly 75,660 units that have
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been produced subject to the Fair Housing Act’s design and construction standards and
approximately 4,000 units within developments that must include accessible units subject to
Section 504. There is, without question, some overlap between these two categories, some of these
units are likely non-compliant, and some accessible units are occupied by individuals who do not
have disabilities.
Describe the areas where affordable, accessible housing units are located in the jurisdiction and
region. Do they align with R/ECAPs or other areas that are segregated?
Relying on the discussion of Publicly Supported Housing to guide the assessment of which types
of housing are most likely to be affordable and accessible, such housing is highly concentrated in
the central and northern portions of the county. In particular, units are concentrated in Anaheim,
Garden Grove, Irvine, and Santa Ana. Additionally, accessible housing is most likely to be located
in places with newer construction and many units, thus conforming to the Fair Housing Act’s
accessibility standards. Areas with newer construction include the central and southern portions of
the county.
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Map 4: Median Year Structure Built by Census Tract, Orange County
To what extent are people with different disabilities able to access and live in the different
categories of publicly supported housing in the jurisdiction and region?
Table 27: Disability by Publicly Supported Housing Program Category, Orange County
Orange County
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 31 7.47%
Other Multifamily 24 72.73%
HCV Program 610 25.33%
Region
Public Housing 1,407 14.32%
Project-Based Section 8 5,013 12.71%
Other Multifamily 869 15.62%
HCV Program N/a N/a
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Table 28: Anaheim
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 60 21.82%
Other Multifamily N/a N/a
HCV Program 1,100 22.32%
Table 29: Buena Park
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 15 12.71%
Other Multifamily N/a N/a
HCV Program 165 21.07%
Table 30: Costa Mesa
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 6 5.36%
Other Multifamily N/a N/a
HCV Program 192 29.40%
Table 31: Fountain Valley
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 14 20.59%
Other Multifamily N/a N/a
HCV Program 157 29.40%
Table 32: Fullerton
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 4 3.92%
Other Multifamily 40 80.00%
HCV Program 203 26.68%
257
Table 33: Garden Grove
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 4 1.76%
Other Multifamily N/a N/a
HCV Program 516 18.46%
Table 34: Huntington Beach
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 50 13.19%
Other Multifamily N/a N/a
HCV Program 270 25.64%
Table 35: Irvine
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 95 13.05%
Other Multifamily 17 70.83%
HCV Program 286 23.08%
Table 36: La Habra
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 6 4.08%
Other Multifamily N/a N/a
HCV Program 34 17.62%
Table 37: Laguna Niguel
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 45 29.61%
Other Multifamily N/a N/a
HCV Program 44 40.00%
258
Table 38: Lake Forest
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 N/a N/a
Other Multifamily N/a N/a
HCV Program 95 32.20%
Table 39: Mission Viejo
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 N/a N/a
Other Multifamily N/a N/a
HCV Program 92 37.86%
Table 40: Newport Beach
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 3 3.03%
Other Multifamily N/a N/a
HCV Program 42 27.81%
Table 41: Orange (City)
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 71 36.98%
Other Multifamily N/a N/a
HCV Program 167 24.52%
Table 42: Rancho Santa Margarita
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 N/a N/a
Other Multifamily N/a N/a
HCV Program 56 37.84%
259
Table 43: San Clemente
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 11 15.07%
Other Multifamily N/a N/a
HCV Program 52 39.10%
Table 44: Santa Ana
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 118 14.64%
Other Multifamily N/a N/a
HCV Program 397 21.39%
Table 45: Tustin
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 11 10.68%
Other Multifamily N/a N/a
HCV Program 108 19.82%
Table 46: Westminster
People with a Disability
# %
Public Housing N/a N/a
Project-Based Section 8 5 5.10%
Other Multifamily N/a N/a
HCV Program 459 19.60%
In Orange County, according to the 2013-2017 American Community Survey 5-Year Estimates,
11.1% of the civilian noninstitutionalized population has a disability. As the tables above reflect,
the proportion of people with disabilities with Housing Choice Vouchers exceeds the overall
population concentration of people with disabilities. For other programs, the data is more
idiosyncratic with disproportionately low concentrations of persons with disabilities in Project-
Based Section 8 and Other Multifamily housing in some cities and disproportionately high
concentrations in others. This inconsistency likely results from the differing natures of individual
developments that fall under those umbrellas, with some supportive housing – including Section
202 and Section 811 housing – encompassed in Other Multifamily housing and many age-
restricted Project-Based Section 8 developments.21 The table below shows that the extremely low-
21 Elderly individuals are significantly more likely to ha ve disabilities than non-elderly individuals.
260
income population, which is eligible for publicly supported housing across a range of programs,
contains a much higher proportion of persons with disabilities than does the population as a whole.
Table 47: Percentage of the population that is income eligible (0-30% AMI) and has a
disability, Orange County
Type of
Disability
Percentage
of Cost-
Eligible
Population
Number of
People in
Cost-
Eligible
Population
with a
Disability
Hearing or
Vision
9.97% 20,220
Ambulatory 13.80% 27,990
Cognitive 8.97% 18,195
Self-Care or
Independent
Living
12.02% 24,375
No
Disability
55.23% 111,985
Total 202,765
Integration of People with Disabilities Living in Institutions and Other Segregated Settings
To what extent do people with disabilities in or from the jurisdiction or region reside in
segregated or integrated settings?
Up until a wave of policy reforms and court decisions in the 1960s and 1970s, states, including
California, primarily housed people with intellectual and developmental disabilities and
individuals with psychiatric disabilities in large state-run institutions. In California, institutions for
people with intellectual and developmental disabilities are called developmental centers, an d
institutions for people with psychiatric disabilities are called state hospitals. Within these
institutions, people with disabilities have had few opportunities for meaningful interaction with
individuals without disabilities, limited access to education and employment, and a lack of
individual autonomy. The transition away from housing people with disabilities in institutional
settings and toward providing housing and services in home and community-based settings
accelerated with the passage of the Americans with Disabilities Act in 1991 and the U.S. Supreme
Court’s landmark decision in Olmstead v. L.C. in 1999. In Olmstead, the Supreme Court held that,
under the regulations of the U.S. Department of Justice (DOJ) implementing Title II of the
Americans with Disabilities Act (ADA), if a state or local government provides supportive services
to people with disabilities, it must do so in the most integrated setting appropriate to the needs of
a person with a disability and consistent with their informed choice. This obligation is not absolute
and is subject to the ADA defense that providing services in a more integrated setting would
constitute a fundamental alteration of the state or local government’s programs.
261
The transition from widespread institutionalization to community integration has not always been
linear, and concepts of what comprises a home and community-based setting have evolved over
time. Although it is clear that developmental centers and state hospitals are segregated settings and
that an individual’s own house or apartment in a development where the vast majority of residents
are individuals without disabilities is an integrated setting, significant ambiguities remain. Nursing
homes and intermediate care facilities are segregated though not to the same degree as state
institutions. Group homes fall somewhere between truly integrated supported housing and such
segregated settings, and the degree of integration present in group homes often corresponds to their
size.
Below, this assessment includes detailed information about the degree to which people with
intellectual and developmental disabilities and individuals with psychiatric disabilities reside in
integrated or segregated settings. The selection of these two areas of focus does not mean that
people with other types of disabilities are never subject to segregation. Although the State of
California did not operate analogous institutions on the same scale for people with ambulatory or
sensory disabilities, for example, many people with disabilities of varying types face segregation
in nursing homes. Data concerning people with various disabilities residing in nursing homes is
not as available as data relating specifically to people with intellectual and developmental
disabilities and people with psychiatric disabilities.
Table 48: Performance of Regional Center of Orange County, December 2018
Dec. 2018 Performance
Reports
Fewer
consumers live
in
developmental
centers
More
children
live with
families
More
adults
live in
home
settings
Fewer
children
live in
large
facilities
(more
than 6
people)
Fewer
adults
live in
large
facilities
(more
than 6
people)
State Average 0.12% 99.38% 80.20% 0.04% 2.31%
Regional Center of Orange
County
0.26% 99.32% 77.45% 0.03% 2.93%
In California, a system of regional centers is responsible for coordinating the delivery of supportive
services primarily to individuals with intellectual and developmental disabilities. The regional
centers serve individuals with intellectual disabilities, individuals with autism spectrum disorder,
individuals with epilepsy, and cerebral palsy. These disabilities may be co-occurring. Individuals
with intellectual disabilities and individuals with mild/moderate intellectual disability and
individuals with autism spectrum disorder make up the lion’s share of consumers. All data
regarding the regional centers is drawn from their annual performance reports.
On an annual basis, regional centers report to the California Department of Developmental
Services on their performance in relation to benchmarks for achieving community integration of
people with intellectual and developmental disabilities. As reflected in the table above, the
262
Regional Center of Orange County closely tracks the statewide average data though individuals
with developmental disabilities in Orange County are slightly more segregated than statewide.
The Fairview Developmental Center was the primary institution serving the region but is now in
the process of closing.
Psychiatric Disabilities
In Orange County, Behavioral Health Services (part of the County Health Agency) is responsible
for coordinating the provision of supportive services for people with psychiatric disabilities. The
Department provides Full Service Partnership programs to allow for the provision of supportive
services that facilitate community integration for Children, Transitional Age Youth, Adults, and
Older Adults. Data regarding participation in the Full Service Partnership by individuals is not
available.
As a result of Proposition 63, a successful 2004 statewide ballot initiative, funding is available for
permanent supportive housing for people with psychiatric disabilities through the Mental Health
Services Act (MHSA). The Department operates its No Place Like Home, Special Needs Housing,
and Mortgage Assistance Programs to increase access to community-based housing for persons
with psychiatric disabilities.
Describe the range of options for people with disabilities to access affordable housing and
supportive services in the jurisdiction and region.
There are four housing authorities operating within Orange County: Orange County Housing
Authority, Anaheim Housing Authority, Garden Grove Housing Authority, and the Housing
Authority of the City of Santa Ana. One of the easiest ways for people with disabilities to access
affordable housing is for the local housing authorities to implement disability preferences in their
HCV programs. The housing authorities for Anaheim and Garden Grove administer preferences
that provide a significant advantage in admissions to persons with disabilities. The housing
authority for the county has a preference that is weighted relatively lightly in comparison to other
factors while Santa Ana’s housing authority does not have a preference. Preferences for homeless
individuals and for veterans may significantly overlap with persons with disabilities and thereby
reduce concerns about the weakness of existing disability preferences.
Supportive services are primarily provided through programs administered by the Regional Center
of Orange County and the Orange County Behavioral Health Department. Additionally,
particularly for individuals with types of disabilities other than intellectual and developmental
disabilities and psychiatric disabilities, services may be available through a range of health care
providers, paid by Medi-Cal, Medicare, or private insurance, or through nursing homes. Payment
for supportive services for people with intellectual and developmental disabilities is typically
structured as Home and Community-Based Services Medicaid Waivers. These Waivers pay for a
wide variety of services necessary to empower individuals to maintain stable residence in home
and community-based services. There are, however, only as many Waivers available as there is
funding from the federal government and the State of California.
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Disparities in Access to Opportunity
To what extent are people with disabilities able to access the following in the jurisdiction and
region? Identify major barriers faced concerning:
i. Government services and facilities
This Analysis did not reveal any specific barriers that persons with disabilities face i n accessing
government services and facilities.
ii. Public infrastructure (e.g., sidewalks, pedestrian crossings, pedestrian signals)
This Analysis did not reveal any specific barriers persons with disabilities face in accessing public
infrastructure.
iii. Transportation
The relative lack of public transportation, particularly in the southern and coastal portions of the
county, disproportionately burdens persons with disabilities who are more likely to rely on public
transportation than are individuals who do not have disabilities.
iv. Proficient schools and educational programs
This Analysis did not reveal current systemic policies and practices that contribute to educational
disparities for students with disabilities in Orange County; however, dat a shows that, although
suspension rates are lower in Orange County than statewide, students with disabilities still face
suspension at twice the rate of other students.
v. Jobs
Data in the table below from the Regional Center of Orange County shows that persons with
developmental disabilities obtain earned income at higher rates than individuals with
developmental disabilities statewide but that rate is still very low in comparison to the proportion
of all adults with earned income.
264
Table 49: Employment Metrics for Adults with Intellectual and Developmental Disabilities
by Regional Center
Regional Center Percentage of
Consumers with
Earned Income
Percentage of Adults with
Integrated Employment as a Goal
in their Individual Program Plan
State Average 17% 27%
Regional Center of
Orange County
21% 30%
Describe the processes that exist in the jurisdiction and region for people with disabilities to
request and obtain reasonable accommodations and accessibility modifications to address the
barriers discussed above.
i. Government services and facilities
Government websites generally have accessibility information on them regarding the accessibility
of the websites themselves, but there is not clear, public information regarding how individuals
can request accommodations.
ii. Public infrastructure (e.g., sidewalks, pedestrian crossings, pedestrian signals)
There is no clear, public information regarding how individuals with disabilities can request
accommodations relating to public infrastructure.
iii. Transportation
By contrast, the Orange County Transportation Authority and Metrolink have clear, easily findable
information about their accommodation and modification policies.
iv. Proficient schools and educational programs
School districts are more disparate in how they display information relating to their
accommodation policies, with some making that information easy to find but others not.
v. Jobs
This Analysis did not reveal information suggesting patterns in how major employers do or do not
provide required accommodations in Orange County.
Describe any difficulties in achieving homeownership experienced by people with disabilities
and by people with different types of disabilities in the jurisdiction and region.
Persons with disabilities in Orange County are less able to access homeownership than individuals
who do not have disabilities, primarily because of the high cost of homeownership and relative
differences in income between persons with disabilities and individuals who do not have
disabilities. This pattern is slightly undercut by the prevalence of elderly homeowners with
265
disabilities that began in old age. Many of these individuals earned relatively high incomes prior
to the onset of their disabilities.
Disproportionate Housing Needs
Describe any disproportionate housing needs experienced by people with disabilities and by
people with certain types of disabilities in the jurisdiction and region.
Table 50: Residents experiencing 1 or more housing problems by Disability Type, Orange
County
Disability Type Has 1 or more housing
problems
Total Percent
Hearing or Vision 43,325 93,875 46.15%
Ambulatory 52,675 106,370 49.52%
Cognitive 39,405 72,515 54.34%
Self-Care or
Independent Living
46,695 90370 51.67%
CHAS data does not disaggregate data relating to persons with disabilities experiencing
overcrowding, incomplete plumbing and kitchen facilities, and cost burden. However, it does
disaggregate persons experiencing one or more of those housing problems by t ype of disability
(although it groups together hearing and vision, and self-care and independent living disabilities).
The data above indicate that people with disabilities experience very high rates of housing
problems, clustering around 50%, and there are no serious differences across the different
disability types. Although it is not possible to disaggregate the individual housing problems by
disability, given the age distribution of people with disabilities, it would seem to be unlikely that
people with disabilities are disproportionately subject to overcrowding. Just 2.1% of households
with elderly heads of household are overcrowded while 5.3% of households with nonelderly heads
of household are overcrowded. By contrast, in light of the relatively low earnings of people with
disabilities, it is likely that people with disabilities are disproportionately subject to cost burden
and severe cost burden.
Additional Information
Beyond the HUD-provided data, provide additional relevant information, if any, about disability
and access issues in the jurisdiction and region including those affecting people with disabilities
with other protected characteristics.
This Assessment has made extensive use of local data throughout the Disability and Access
section. The sources of data other than HUD-provided data are noted where appropriate.
266
The program participant may also describe other information relevant to its assessment of
disability and access issues.
The discussion above provides a comprehensive overview of information relevant to this Analysis.
Disability and Access Issues Contributing Factors
Consider the listed factors and any other factors affecting the jurisdiction and region. Identify
factors that significantly create, contribute to, perpetuate, or increase the severity of disability and
access issues and the fair housing issues, which are Segregation, R/ECAPs, Disparities in Access
to Opportunity, and Disproportionate Housing Needs. For each contributing factor, note which
fair housing issue(s) the selected contributing factor relates to.
Access for persons with disabilities to proficient schools
Access to publicly supported housing for persons with disabilities
Access to transportation for persons with disabilities
Inaccessible government facilities or services
Inaccessible public or private infrastructure
Lack of access to opportunity due to high housing costs
Lack of affordable in-home or community-based supportive services
Lack of affordable, accessible housing in range of unit sizes
Lack of affordable, integrated housing for individuals who need supportive services
Lack of assistance for housing accessibility modifications
Lack of assistance for transitioning from institutional settings to integrated housing
Lack of local or regional cooperation
Land use and zoning laws
Lending discrimination
Location of accessible housing
Loss of affordable housing
Occupancy codes and restrictions
Regulatory barriers to providing housing and supportive services for persons with
disabilities
Source of income discrimination
State or local laws, policies, or practices that discourage individuals with disabilities from
living in apartments, family homes, supportive housing and other integrated settings
267
E. Fair Housing Enforcement, Outreach Capacity and Resources
List and summarize any of the following that have not been resolved:
● A charge or letter of finding from HUD concerning a violation of a civil rights-related law;
● A cause determination from a substantially equivalent state or local fair housing agency
concerning a violation of a state or local fair housing law;
● Any voluntary compliance agreements, conciliation agreements, or settlement agreements
entered into with HUD or the Department of Justice;
● A letter of findings issued by or lawsuit filed or joined by the Department of Justice alleging
a pattern or practice or systemic violation of a fair housing or civil rights law;
● A claim under the False Claims Act related to fair housing, nondiscrimination, or civil
rights generally, including an alleged failure to affirmatively further fair housing;
● Pending administrative complaints or lawsuits against the locality alleging fair housing
violations or discrimination.
o Watts v. City of Newport Beach, 790 Fed.Appx. 853 (9th Cir. 2019): The City of
Newport Beach was recently sued by a young woman who alleged excessive force,
unlawful entry, and unlawful arrest. Upon the decline of her card for a taxi fare, the
driver called the police, who threatened to take Watts to jail if she could not produce
additional funds to pay. She asked to go to her apartment to get another form of
payment, and officers escorted her. When she objected to their entry into her apartment
to retrieve the funds, they handcuffed her to the point of injury to her wrists, kicked her
legs out from under her, pushed her head into a wall, and took her to jail overnight. The
9th Circuit ruled affirmed that officers were not covered by qualified immunity for
unlawful arrest and unlawful entry, but that they were covered for the excessive force
claim.
o A. K. H by and through Landeros v. City of Tustin, 837 F.3d 1005 (9th Cir. 2016): In
2014, the city of Tustin was sued by the family of a minor who was shot and killed by
a Tustin police officer. The city moved for summary judgement based on qualified
immunity. The district court denied that motion. On appeal, the 9th Circuit affirmed
the lower court decision, holding that the shooting violated the 4th Amendment, and
that the officer was not covered by qualified immunity.
Describe any state or local fair housing laws. What characteristics are protected under each law?
California Laws
The State Department of Fair Employment and Housing (DFEH) enforces California laws that
provide protection and monetary relief to victims of unlawful housing practices. The Fair
Employment and Housing Act (FEHA) (Government Code Section 12955 et seq.) prohibits
discrimination and harassment in housing practices, including:
● Advertising
● Application and selection process
● Unlawful evictions
● Terms and conditions of tenancy
268
● Privileges of occupancy
● Mortgage loans and insurance
● Public and private land use practices (zoning)
● Unlawful restrictive covenants
The following categories are protected by FEHA:
● Race or color
● Ancestry or national origin
● Sex, including Gender, Gender Identity, and Gender Expression
● Marital status
● Source of income
● Sexual orientation
● Familial status (households with children under 18 years of age)
● Religion
● Mental/physical disability
● Medical condition
● Age
● Genetic information
In addition, FEHA contains similar reasonable accommodations, reasonable modifications, and
accessibility provisions as the Federal Fair Housing Amendments Act. FEHA explicitly provides
that violations can be proven through evidence of the unjustified disparate impact of challenged
actions and inactions and establishes the burden-shifting framework that courts and the
Department of Fair Employment and Housing must use in evaluating disparate impact claims.
The Unruh Civil Rights Act provides protection from discrimination by all business establishments
in California, including housing and accommodations, because of age, ancestry, color, disability,
national origin, race, religion, sex, and sexual orientation. While the Unruh Civil Rights Act
specifically lists “sex, race, color, religion, ancestry, national origin, disability, and medical
condition” as protected classes, the California Supreme Court has held that protections under the
Unruh Act are not necessarily restricted to these characteristics. In practice, this has meant that the
law protects against arbitrary discrimination, including discrimination on the basis of personal
appearance.
Furthermore, the Ralph Civil Rights Act (California Civil Code Section 51.7) forb ids acts of
violence or threats of violence because of a person’s race, color, religion, ancestry, national origin,
age, disability, sex, sexual orientation, political affiliation, or position in a labor dispute. Hate
violence can include: verbal or written threats; physical assault or attempted assault; and graffiti,
vandalism, or property damage.
The Bane Civil Rights Act (California Civil Code Section 52.1) provides another layer of
protection for fair housing choice by protecting all people in California from interference by force
or threat of force with an individual’s constitutional or statutory rights, including a right to equal
access to housing. The Bane Act also includes criminal penalties for hate crimes; however,
convictions under the Act may not be imposed for speech alone unless that speech itself threatened
violence.
269
Finally, California Civil Code Section 1940.3 prohibits landlords from questioning potential
residents about their immigration or citizenship status. In addition, this law forbids local
jurisdictions from passing laws that direct landlords to make inquiries about a person’s citizenship
or immigration status.
In addition to these acts, Government Code Sections 11135, 65008, and 65580-65589.8 prohibit
discrimination in programs funded by the State and in any land use decisions. Specifically, recent
changes to Sections 65580-65589.8 require local jurisdictions to address the provision of housing
options for special needs groups, including:
● Housing for persons with disabilities (SB 520)
● Housing for homeless persons, including emergency shelters, transitional housing, and
supportive housing (SB 2)
● Housing for extremely low-income households, including single-room occupancy units
(AB 2634)
● Housing for persons with developmental disabilities (SB 812)
Jurisdiction-Specific Laws
Aliso Viejo
In 2013, the city of Aliso Viejo adopted housing and reasonable accommodation regulations and
procedures.
Buena Park
As part of the zoning code, the city of Buena Park describes specific procedures for reasonable
accommodations in land use, zoning regulations, rules, policies, practices and procedures through
the completion of a Fair Housing Accommodation Request form.
Costa Mesa
As part of the zoning code, the city of Costa Mesa allows for reasonable accommodations in land
use and zoning regulations.
Fountain Valley
The City of Fountain Valley provides reasonable accommodation in the application of its zoning
and building laws, policies and procedures for persons with disabilities.
Huntington Beach
In 2013, the city of Huntington Beach adopted reasonable accommodations procedures.
Irvine
The Irvine Municipal Code prohibits discrimination on the basis of race, color, religion, national
origin, sex, age, marital status or physical handicap of any individual in the realms of employment,
real estate transactions, and educational institutions. Regarding housing, it is prohibits
discrimination in financial transactions, advertising, or give differential treatment and terms.
270
La Palma
La Palma specifically provides for reasonable accommodations for person with disabilities in “land
use, zoning and building regulations, policies, practices and procedures of the City.”22
Laguna Niguel
Laguna Niguel provides for reasonable accommodations in the application of zoning laws for
persons with disabilities.
Newport Beach
Newport Beach requires provision of reasonable accommodation during the permit review process
for new development.
Orange
The city of Orange provides for reasonable accommodations in the application of land use and
zoning laws for those with disabilities.
Rancho Santa Margarita
Rancho Santa Margarita allows for reasonable accommodations in the application of land use and
zoning laws for those with disabilities.
Santa Ana
The Santa Ana municipal code allows for modification of land use or zoning regulations if
necessary to provide a reasonable accommodation to persons with disabilities.
Tustin
Tustin allows for reasonable accommodations in the land use and zoning process for developers
of housing for persons with disabilities.
Westminster
Westminster allows for reasonable accommodations in land use and zoning when necessary to
accommodate the needs of persons with disabilities.
Additional Information
Provide additional relevant information, if any, about fair housing enforcement, outreach
capacity, and resources in the jurisdiction and region.
California Department of Fair Employment and Housing (DFEH)
DFEH accepts, investigates, conciliates, mediates, and prosecutes complaints under FEHA, the
Disabled Persons Act, the Unruh Civil Rights Act, and the Ralph Civil Rights Act. DFEH
investigates complaints of employment and housing discrimination based on race, sex, including
gender, gender identity, and gender expression, religious creed, color, national origin, familiar
status, medical condition (cured cancer only), ancestry, physical or mental disability, marital
22https://library.municode.com/ca/la_palma/codes/code_of_ordinances?nodeId=COOR_CH44ZO_ARTVPEPLCE_
DIV15REACRE
271
status, or age (over 40 only), and sexual orientation, DFEH established a program in May 2003 for
mediating housing discrimination complaints, which is among the largest fair housing mediation
program in the nation to be developed under HUD’s Partnership Initiative with state fair housing
enforcement agencies. The program provides California’s tenants, landlords, and property owners
and managers with a means of resolving housing discrimination cases in a fair, confidential, and
cost-effective manner. Key features of the program are: 1) it is free of charge to the parties; and 2)
mediation takes place within the first 30 days of the filing of the complaint, often avoiding the
financial and emotional costs associated with a full DFEH investigation and potential litigation.
Fair Housing Council of Orange County
Founded in 1965, the Fair Housing Council of Orange County is a non-profit operating throughout
the county with a mission of ensuring access to housing and preserving human rights. The council
provides a variety of services including community outreach and education, homebuyer education,
mortgage default counseling, landlord-tenant mediation, and limited low-cost advocacy. Their
services are provided in English, Spanish, and Vietnamese. In addition to these client services, the
Fair Housing Council investigates claims of housing discrimination and assists with referrals to
DFEH. The Council may also occasionally assist with or be part of litigation challenging housing
practices.
Fair Housing Foundation
The Fair Housing Foundation serves parts of Los Angeles County and several cities in Orange
County. Of the jurisdictions included in this analysis, the following are covered by the Fair
Housing Foundation’s service area: Anaheim, Buena Park, Costa Mesa, Fullerton, Garden Grove,
Huntington Beach, Irvine, La Habra, Mission Viejo, Newport Beach, Orange (city), San Clemente,
Tustin, and Westminster. The Foundation provides landlord-tenant counseling and mediation,
rental housing counseling, and community outreach and education. In addition, the Foundati on
screens fair housing complaints, investigates through testing, and will engage in conciliation or
mediation efforts or refer the complaints to the appropriate administrative agencies where
appropriate.
Community Legal Aid SoCal
Community Legal Aid SoCal is a holistic legal services provider serving low-income people
Orange County and Southeast Los Angeles County. Overall, community legal aid provides direct
representation, as well as engaging in policy advocacy and impact litigation. The advocates in the
housing program provide legal assistance across a broad range of fair housing issues, including
“eviction, federally or otherwise publicly subsidized housing, substandard housing,
landlord/tenant issues, homeownership issues, homeowners association issues mobile homes,
housing discrimination, an predatory lending practices.”23 The main office is located in Santa Ana,
with additional offices in Norwalk, Anaheim, and Compton. Across four offices, the organization
has 100 staff members and 30 attorneys. Like other Legal Aid offices, Community Legal Aid
SoCal is funded by the Legal Services Corporation, which carries restrictions against representing
undocumented clients.
23 https://www.communitylegalsocal.org/programs-services/area-of-law/housing/
272
Fair Housing Enforcement, Outreach Capacity, and Resources Contributing Factors
Consider the listed factors and any other factors affecting the jurisdiction and region. Identify
factors that significantly create, contribute to, perpetuate, or increase the lack of fair housing
enforcement, outreach capacity, and resources and the severity of fair housing issues, which are
Segregation, R/ECAPs, Disparities in Access to Opportunity, and Disproportionate Housing
Needs. For each significant contributing factor, note which fair housing issue(s) the selected
contributing factor impacts.
Lack of local private fair housing outreach and enforcement
Lack of resources for fair housing agencies and organizations
Lack of state or local fair housing laws
273
VI. FAIR HOUSING GOALS AND PRIORITIES
If implemented, the goals and strategies below will serve as an effective basis for affirmatively
furthering fair housing by reducing patterns of segregation, mitigating displacement, addressing
disproportionate housing needs, and increasing access to opportunity for members of protected
classes. The first six overarching goals below, multiple of which have several strategies listed for
implementation, are cross-jurisdictional goals. Orange County and the participating jurisdictions
all have a role to play in implementing those goals. Following those go als, this section includes
individual goals for Orange County, the participating jurisdictions, and the housing authorities that
may not be applicable to other jurisdictions because they respond to local circumstances.
Cross-Jurisdictional Goals
Goal 1: Increase the supply of affordable housing in high opportunity areas.
Orange County’s high and rapidly rising housing costs, along with the unequal distribution of
affordable housing across its communities, may be some of the leading drivers of fair housing
issues for members of protected classes in the area. Data indicates that Hispanic residents,
Vietnamese residents, and persons with disabilities experience these problems most acutely.
Many households are rent burdened, and some households pay more than 50% of their incomes
towards rent. In many high opportunity areas, current payment standards are far too low for
families with housing choice vouchers to move to these areas. Additionally, there has been vocal
community opposition to affordable housing throughout the county. These data reflect a need to
expand the both the supply and geographical diversity of affordable housing.
a. Explore the creation of a new countywide sources of affordable housing.
The State of California has approved several measures to issue bonds for affordable housing.
Orange County should consider the issuance of affordable housing bonds to meet the widening
gap for affordable rental housing through a ballot initiative or other county-wide or local means.
b. Using best practices from other jurisdictions, explore policies and programs that increase
the supply affordable housing, such as linkage fees, housing bonds, inclusionary housing,
public land set-aside, community land trusts, transit-oriented development, and expedited
permitting and review.
The above policies and practices have resulted in an increase in affordable housing in jurisdictions
throughout the country and in California in particular. In Orange County, there has be en an
increase in the supply of affordable housing in cities that have adopted these best practices.
c. Explore providing low-interest loans to single-family homeowners and grants to
homeowners with household incomes of up to 80% of the Area Median Income to develop
accessory dwelling units with affordability restriction on their property.
In 2019, the California Legislature passed AB 68 and AB 881 which permit the placement of two
accessory dwelling units (ADUs), including one “junior ADU,” on a lot with an existing or
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proposed single-family home statewide. Due to high construction costs and high demand, the small
size of ADUs may not be sufficient to ensure that they will be affordable by design. Local
governments may choose to provide financial assistance in order to incentivize homeowners to
make their ADUs affordable to lower income tenants at or below 80% of the area median income.
Because it can be difficult for homeowners to access bank financing to build ADUs, there may be
a need for such incentives among homeowners. As a condition of receiving assistance, jurisdictions
should also require homeowners to attend fair housing training and to maintain records that
facilitate audits of their compliance with non-discrimination laws. The need to educate individual
homeowners, who do not have experience as landlords and knowledge of the law, may prevent
unintentional and intentional violations of fair housing laws.
d. Review existing zoning policies and explore zoning changes to facilitate the develop ment
of affordable housing.
In several jurisdictions in Orange County, the prevalence of single-family residential zoning makes
it challenging to develop housing that could offer housing opportunities to members of protected
classes. Many cities across the country are increasing higher density zoning near transit. Increased
higher density zoning near transit in high opportunity areas, coupled with an affordable housing
set-aside, would provide additional mixed-income rental housing.
e. Align zoning codes to conform to recent California affordable housing legislation.
California passed several affordable housing bills that became effective on January 1, 2020.
Examples include as AB 1763, which expands existing density bonus law for 100% affordable
housing projects to include unlimited density around transit hubs with an additional three stories
or 33 feet of height, and AB 68, which allows two ADUs on a single lot, as well as multiple ADUs
on multifamily lots with limited design requirement that cities can impose and an approval process
of 60 days. This and other legislation necessitate changes to each jurisdiction’s zoning code.
Goal 2: Prevent displacement of low- and moderate-income residents with protected
characteristics, including Hispanic residents, Vietnamese residents, seniors, and people with
disabilities.
a. Explore piloting a Right to Counsel Program to ensure legal repr esentation for tenants in
landlord-tenant proceedings, including those involving the application of new laws like
A.B. 1482.
Thousands of residents in the county are displaced annually due to evictions. According to legal
services and fair housing organizations, many evictions occur because tenants do not understand
their rights and/or their obligations. It is estimated that only a small percentage of tenants facing
eviction have legal representation, and those without representation almost always are evicted,
regardless of a viable defense. Recently, other high cost cities such as New York, San Francisco,
Philadelphia, and soon Los Angeles have guaranteed a right to counsel at eviction hearings. There
are several legal providers in the county such as Community Legal Aid SoCal and Public Law
Center that are well-positioned to serve low-income tenants with financial support. Although there
would be an up-front investment, legal representation is less costly than serving homeless families.
275
Goal 3: Increase community integration for persons with disabilities
a. Conduct targeted outreach and provide tenant application assistance and support to persons
with disabilities, including individuals transitioning from institutional settings and
individuals who are at risk of institutionalization. As part of that assistance, maintain a
database of housing that is accessible to persons with disabilities.
Lack of access to housing is a significant impediment to full community integration for persons
with disabilities in the county. Stakeholders expressed frustration with the lack of information on
accessible affordable housing units and are required to call individual landlords to obtain this
information.
b. Consider adopting the accessibility standards adopted by the City of Los Angeles, which
require 15 percent of all new units in city-supported LIHTC projects to be ADA-accessible
with at 4 percent of total units to be accessible for persons with hearing and/or vision
disabilities.
In order to align with the Voluntary Compliance Agreement (VCA) between the City of Los
Angeles and HUD,24 Orange County should consider adopting the same standards. The City of
Los Angeles’ adopted accessibility standards resulting from this VCA will address deficiencies
related to the physical accessibility of designated accessible units and public/common areas in
connection with the certain housing developments and program policies and procedures.
Goal 4: Ensure equal access to housing for persons with protected characteristics, who are
disproportionately likely to be lower-income and to experience homelessness.
a. Reduce barriers to accessing rental housing by exploring eliminating application fees for
voucher holders and encouraging landlords to follow HUD’s guidance on the use of
criminal backgrounds in screening tenants.
Stakeholders reported that high application fees for rental housing are a significant barrier for
voucher holders. Additionally, some landlords continue to refuse rental housing to prospective
tenants based on decades-old criminal background checks or minor misdemeanors.
b. Consider incorporating a fair housing equity analysis into the review of significant
rezoning proposals and specific plans.
At times, large scale development and redevelopment efforts have not sufficiently addressed the
needs of large families with children, persons with disabilities, and Hispanic and Vietnamese
residents, in particular. By incorporating a fair housing analysis in the review process for
redevelopment plans at an early stage, planning staff from participating jurisdictions could catch
issues such as the distribution of unit sizes in proposed developments while it is still feasible to
amend plans.
24 https://www.hud.gov/sites/dfiles/Main/documents/HUD-City-of-Los-Angeles-VCA.pdf
276
Goal 5: Expand access to opportunity for protected classes.
a. Explore the voluntary adoption of Small Area Fair Market Rents or exception payment
standards in order to increase access to higher opportunity areas for Housing Choice
Voucher holders.
A significant barrier in the county is the lack of affordable housing and the sufficiency of payment
standards to provide geographic options to voucher holders. Orange County Housing Authority
has three payment standards; basic, central, and restricted. HUD’s Small Area FMRs for Orange
County permit certain zip codes to have higher payment standards than those currently used.
b. Continue implementing a mobility counseling program that informs Housing Choice
Voucher holders about their residential options in higher opportunity areas and provides
holistic supports to voucher holders seeking to move to higher opportunity areas.
The housing authorities located in Orange County currently lack funding to implement full -scale
housing mobility programs. A formal counseling program, as found in Chicago, Dallas, Baltimore,
and elsewhere, can make a significant difference in the settlement patterns of HCV households.
These programs generally identify opportunity areas, while assisting voucher holders to find new
residences within them. Workshops and information sessions allow for participants to ask
questions, find higher-performing schools and locate areas of lower crime. Individual counselors
may provide assistance to families to find units in opportunity areas, while also following up post-
move to ensure the family is adjusting well to their new neighborhood.
c. Study and make recommendations to improve and expand Orange County’s public
transportation to ensure that members of protected classes can access jobs in employment
centers in Anaheim, Santa Ana, and Irvine.
There are few viable and reliable public transportation options in Orange County. It is important
that there is a match between where low- and moderate-income members of protected classes, who
are more likely to use public transportation, are able to commute to county job centers. Part of this
study should include ensuring that people with disabilities are able to access transportation to jobs
and services.
d. Increase support for fair housing enforcement, education, and outreach.
Nonprofit fair housing organizations and legal services providers play a critical role in fair housing
enforcement, education, and outreach but struggle to meet the full needs of victims of
discrimination due to limited financial and staff capacity. By supporting these organizations,
jurisdictions can help ensure that these organizations can address existing and critical emerging
issues, like those that have stemmed from the passage of S.B. 329, which extends source of income
protections to Housing Choice Voucher holders, and A.B. 1482, which caps annual rent increases
in at five percent plus the regionally-adjusted Consumer Price Index and requires landlords to have
“just cause” in order to evict tenants. It would also make proactive audit testing of housing
providers rather than reactive complaint-based testing more feasible.
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Jurisdictional-Specific Goals
City of Aliso Viejo
1. In collaboration with the Orange County Housing Authority (OCHA):
a. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange of
information regarding the availability, procedures, and policies related to the Housing
Assistance Voucher program and regional housing issues.
b. Support OCHA's affirmative fair marketing plan and de-concentration policies by
providing five-year and annual PHA plan certifications.
c. In coordination with OCHA and fair housing services provider, conduct landlord
education campaign to educate property owners about State law prohibiting
discrimination based on household income.
2. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and homeowner
associations on why denial of reasonable modifications/accommodations is unlawful.
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property owners,
realtors, and property management companies. Methods of outreach may include
workshops, informational booths, presentations to community groups, and distribution of
multi-lingual fair housing literature.
City of Anaheim
Goal 1
Increase the supply of
affordable housing through
the following strategies:
Contributing
Factors
Metrics, Milestones,
and Timeframe for
Achievement
Responsible
Program
Participant(s)
1. Explore creative land use
and zoning policies that
facilitate the development of
affordable housing, examples
include a housing overlay
zone or religious institutions
amendment.
2. Review Anaheim’s current
Density Bonus and Accessory
Dwelling Unit (ADU)
Ordinances to ensure
compliance with state
requirements.
Lack of access to
opportunity due to
high housing costs;
Location and type of
affordable housing;
Availability of
affordable, accessible
units in a range of
unit sizes; Land use
and zoning laws
Introduce land use
policies that facilitate
affordable housing; 1-5
years; analyze the city’s
current ADU and
Density Bonus
ordinances to ensure
compliance; 1-2 years;
Recommend the
supporting of legislation
that removes CEQA
requirements; 2 years;
Study the feasibility of
allocating city owned
land for housing
development; 2-3 years.
Continue to support and
City staff,
Housing
Commission,
Planning
Commission,
City Council
278
3. Support legislation that
removes CEQA requirements
for affordable housing.
4. Identify and explore
allocating city-owned sites
that may be well suited for
housing for which there are
no other development plans.
5. Continue to support tenant
based rental assistance
programs that facilitates
additional affordable housing
for homeless and low-income
individuals.
explore expanding city
supported tenant based
rental assistance
programs; 1-5 years.
Goal 2
Preserve the existing stock
of affordable rental housing
and rent stabilized housing
through the following
strategies:
Contributing
Factors
Metrics, Milestones,
and Timeframe for
Achievement
Responsible
Program
Participant(s)
1. Strengthen and expand
education and outreach of
tenants and owners of
affordable rental housing at
risk of conversion to market
rents.
2. Extend affordability
restrictions through loan
extensions, workouts and buy-
downs of affordability
3. Preserve at-risk housing
through the issuance of Tax
Exempt Bond financing.
4. Explore the development of
a rental rehabilitation loan
program.
Displacement of
residents due to
economic pressures;
Lack of access to
opportunity due to
high housing costs;
Location and type of
affordable housing;
Availability of
affordable, accessible
units in a range of
unit sizes
Documentation of
outreach services,
education efforts,
termination notices
received and enforced,
1-5 years; offer
incentives to city
restricted properties
expiring in the next 5
years; Assist in the
preservation of at-risk
units through the
issuance of Tax-Exempt
Bond Financing, 1-5
years; Introduce the
creation of a rental
rehabilitation program
and target at-risk
housing projects; 1-3
years.
City staff,
Housing
Commission,
Planning
Commission,
City Council
279
Goal 3
Expand the access to fair
housing services and other
housing services through the
following strategies:
Contributing
Factors
Metrics, Milestones,
and Timeframe for
Achievement
Responsible
Program
Participant(s)
1. Dedicate eligible
entitlement dollars (CDBG,
HOME, etc.) and explore
local, state and federal
resources to expand fair
housing services.
2. Continue to support fair
housing testing and
investigation to look for
evidence of differential
treatment and disparate
impact, including providing
services to low income
tenants reporting fair housing
violations.
3. Continue to support fair
housing presentations, mass
media communications, and
multi-lingual literature
distribution; conduct fair
housing presentations at
accessible locations and
conduct fair housing
presentations for housing
providers
4. Explore alternative formats
for fair housing education
workshops such as pre-taped
videos and/ or recordings.
Such formats could serve
persons with one or more than
one job, families with you
children and other who find it
difficult to attend meetings in
person.
Displacement of
Residents Due to
Economic Pressures,
Private
discrimination,
accessible housing in
a range of unit sizes;
Admissions and
occupancy policies
and procedures,
including preferences
in publicly supported
housing
Continue to utilize
entitlement dollars to
support fair housing
services; Continue to
include testing services
as part of the required
scope of work for city
support fair housing
providers; Years 1-5;
Require city supported
fair housing providers to
provide its services on
multiple platforms and
in diverse locations.
City staff, Fair
Housing
Agencies,
Housing
Commission,
City Council
280
Goal 4
Continue efforts to build
complete communities
through the following
strategies;
Contributing
Factors
Metrics, Milestones,
and Timeframe for
Achievement
Responsible
Program
Participant(s)
1. Maximize and secure
funding from various state
and federal sources, including
the State of California’s Cap
and Trade Program
(Greenhouse Gas Reduction
Fund), to improve housing
opportunities, increase
economic investments and
address environmental factors
in disadvantaged
communities.
2. The City will continue to
work with local transit
agencies and other
appropriate agencies to
facilitate safe and efficient
routes of transportation,
including public transit,
walking and biking.
3. Explore development of a
policy to encourage
developers to provide
residents with incentives to
use non-auto means of
transportation, including
locating new developments
near public transportation and
providing benefits such as bus
passes.
4. Prioritize workforce
development resources in
racially or ethnically
concentrated areas of poverty
to improve economic
mobility.
Access to publicly
supported housing for
persons with
disabilities;
Availability of
affordable, accessible
units in a range of
unit sizes; Lack of
affordable, integrated
housing for
individuals who need
supportive services;
Location of
accessible housing
Actively submit and
compete for Affordable
Housing and Sustainable
Communities (AHSC)
program; Years 1-5;
Convene appropriate
parties from the city and
transportation agencies
to coordinate and
expand transportation
efforts; Years 1-5;
Introduce a policy that
provides developers
incentives that support
non-auto means of
transportation; Years 1-
3; Coordinate with the
City’s Workforce Center
to target workforce
development resources;
Years 1-5.
City staff,
Transportation
Agencies, City
Council
281
City of Buena Park
1. In collaboration with the Orange County Housing Authority (OCHA):
a. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange of
information regarding the availability, procedures, and policies related to the Housing
Assistance Voucher program and regional housing issues.
b. Support OCHA's affirmative fair marketing plan and de-concentration policies by
providing five-year and annual PHA plan certifications.
c. In coordination with OCHA and fair housing services provider, conduct landlord
education campaign to educate property owners about State law prohibiting
discrimination based on household income.
2. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and homeowner
associations on why denial of reasonable modifications/accommodations is unlawful.
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property owners,
realtors, and property management companies. Methods of outreach may include
workshops, informational booths, presentations to community groups, and distribution of
multi-lingual fair housing literature.
City of Orange
1. Continue to follow current State Density Bonus law and further its implementation through a
Density Bonus ordinance update.
2. Prepare a Transfer of Development Rights Ordinance to provide opportunities for
development rights transfers to accommodate higher density housing in transit and
employment-rich areas of the city.
3. Prepare and adopt a North Tustin Street Specific Plan with an objective of providing
opportunities for affordable housing.
4. Amend the City’s Accessory Dwelling Unit Ordinance to be consistent with State Junior
Accessory Dwelling Unit (JADU) and Accessory Dwelling Unit (ADU) laws.
5. Prepare and adopt a small lot subdivision ordinance to streamline entitlement processing of
housing development projects.
6. Continue providing CDBG funds to the Fair Housing Foundation to provide fair housing
activities to the community.
City of Costa Mesa
1. In collaboration with the Orange County Housing Authority (OCHA):
282
a. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange of
information regarding the availability, procedures, and policies related to the Housing
Assistance Voucher program and regional housing issues.
b. Support OCHA's affirmative fair marketing plan and de-concentration policies by
providing five-year and annual PHA plan certifications.
c. In coordination with OCHA and fair housing services provider, conduct landlord
education campaign to educate property owners about State law prohibiting
discrimination based on household income.
2. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and homeowner
associations on why denial of reasonable modifications/accommodations is unlawful.
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property owners,
realtors, and property management companies. Methods of outreach may include
workshops, informational booths, presentations to community groups, and distribution of
multi-lingual fair housing literature.
City of Fountain Valley
1. Explore an inclusionary zoning requirement for all new housing developments that requires at
least 10-15 percent of for-sale units be affordable to households with incomes 80 percent or
below and rental units be affordable to households with incomes 60 percent or below.
2. Consider adopting an expedited permitting and review process for new developments with an
affordable housing set-aside.
City of Fullerton
1. Create a Housing Incentive Overlay Zone (HOIZ).
2. Draft and Approve an Affordable Housing and Religious Institutions Amendment to the
Municipal Code.
3. Work with the State to streamline or remove CEQA Requirements for Affordable Housing.
4. Require Affordable Housing in Surplus Property Sales.
City of Garden Grove
1. Update Density Bonus Ordinance – Garden Grove will update the 2011 Density Bonus
Ordinance to comply with current State law. The update will streamline the approval process,
increase feasibility, and facilitate future housing development at all affordability levels.
2. Create Objective Residential Development Standards to allow for streamlined housing
development in all residential zones.
283
3. Create Objective Development Standards for Supportive Housing. These standards would be
for new construction of Supportive Housing.
4. Evaluate the creation of Objective Development Standards for Hotel/Motel/Office Conversion
to Supportive Housing.
5. Review and amend Garden Grove’s current Accessory Dwelling Unit (ADU) Ordinance to
comply with State requirements and further increase housing supply.
6. Continue to invest in landlord and tenant counseling and mediation services, unlawful detainer
assistance, housing discrimination services, homebuyer education and outreach, and local
eviction prevention strategies.
City of Huntington Beach
1. Modify the existing Inclusionary Housing Ordinance to increase the supply of affordable
housing opportunities available to lower income persons and households.
a. Study the current methodology of setting the maximum sales price and down payment
requirements of an affordable home for ownership.
b. Study requirements for the provision of inclusionary units through on-site units, dedication
of land, in-lieu fees, and off-site development.
c. Study the in-lieu fee structure.
d. Explore the provision of incentives for developments that exceed inclusionary requirements
and/or provide extremely low-income units on site. Incentives can be through the provision
of fee waivers and deferrals, financial assistance, regulatory relief, and flexible
development standards.
2. Update the density bonus ordinance to be consistent with state law,
3. Expand the TBRA program to help tenants impacted by Covid-19. Currently, an eviction
moratorium is in place to prevent evictions due to lack of non-payment of rent due to Covid-
19. This moratorium ends on May 31, 2020. The moratorium does not end the obligation to
pay the rent eventually. On June 1, 2020, there most likely will be an increased need from
persons to receive rental assistance for the rents due prior to May 31 and going forward. The
City would work with its current service providers to help tenants impacted by Covid-19.
City of Irvine
1. Ensure compliance with their HCD-certified Housing Element.
2. Update Density Bonus Ordinance – Irvine will update the Density Bonus Ordinance to comply
with current State law.
3. Review and amend Irvine’s Inclusionary Housing Ordinance, as necessary, to increase its
effectiveness.
284
4. Review and amend Irvine’s current Accessory Dwelling Unit (ADU) Ordinance to comply with
State requirements and further increase housing supply.
5. Create Objective Development Standards for Supportive Housing. These standards would be
for new construction of Supportive Housing.
6. Working with the City’s fair housing services provider, continue to invest in local eviction
prevention strategies to reduce the number of homeless individuals and families in Irvine.
7. Working with the City’s fair housing services provider, continue to invest in landlord and
tenant counseling and mediation services, unlawful detainer assistance, housing
discrimination services, and homebuyer education and outreach.
City of La Habra
1. Explore the creation of an inclusionary housing ordinance to increase the number of
affordable housing units.
2. Advocate for increasing the minimum percentage of affordable units at Park La Habra Mobile
Home and View Park Mobile Home Estates from 20 percent to 50 percent.
City of Laguna Niguel
1. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange of information
regarding the availability, procedures, and policies related to the Housing Assistance Voucher
program and regional housing issues.
2. In collaboration with the Orange County Housing Authority (OCHA):
a. Support OCHA's affirmative fair marketing plan and de-concentration policies by
providing five-year and annual PHA plan certifications.
b. In coordination with OCHA and fair housing services provider, conduct landlord
education campaign to educate property owners about State law prohibiting
discrimination based on household income.
3. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and homeowner
associations on why denial of reasonable modifications/accommodations is unlawful.
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property owners,
realtors, and property management companies. Methods of outreach may include
workshops, informational booths, presentations to community groups, and distribution of
multi-lingual fair housing literature.
c. Provide general fair housing counseling and referrals services to address tenant-landlord
issues, and investigate allegations of fair housing discrimination and take appropriate
actions to conciliate cases or refer to appropriate authorities.
d. Periodically monitor local newspapers and online media outlets to identify potentially
discriminatory housing advertisements.
285
e. Include testing/audits within the scope of work with fair housing provider.
4. Prepare a new Housing Element that is compliant with all current State laws and is certified
by the California Department of Housing and Community Development.
5. Update zoning ordinance to comply with current State law.
6. In cooperation with the Orange County Transportation Authority, provide community
education regarding transport services for persons with disabilities.
7. Support local eviction prevention strategies to reduce the number of homeless individuals and
families (homelessness prevention services).
City of Lake Forest
1. In collaboration with the Orange County Housing Authority (OCHA):
a. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange of
information regarding the availability, procedures, and policies related to the Housing
Assistance Voucher program and regional housing issues.
b. Support OCHA's affirmative fair marketing plan and de-concentration policies by
providing five-year and annual PHA plan certifications.
c. In coordination with OCHA and fair housing services provider, conduct landlord
education campaign to educate property owners about State law prohibiting
discrimination based on household income.
2. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and homeowner
associations on why denial of reasonable modifications/accommodations is unlawful.
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property owners,
realtors, and property management companies. Methods of outreach may include
workshops, informational booths, presentations to community groups, and distribution of
multi-lingual fair housing literature.
c. Provide general fair housing counseling and referrals services to address tenant-landlord
issues, and investigate allegations of fair housing discrimination and take appropriate
actions to conciliate cases or refer to appropriate authorities.
d. Periodically monitor local newspapers and online media outlets to identify potentially
discriminatory housing advertisements.
e. Include testing/audits within the scope of work with fair housing provider.
f. Regularly consult with the City's fair housing contractor on potential strategies f or
affirmatively furthering fair housing on an on-going basis.
3. In cooperation with the Orange County Transportation Authority:
a. Provide community education regarding transport services for persons with disabilities.
b. Explore bus route options to ensure neighborhoods with concentration of low-income or
protected class populations have access to transportation services.
286
4. Support local eviction prevention strategies to reduce the number of homeless individuals and
families (homelessness prevention services).
5. Prepare a new Housing Element that is compliant with all current State laws and is certified
by the California Department of Housing and Community Development.
6. Update zoning ordinance to comply with current State law.
City of Mission Viejo
1. In collaboration with the Orange County Housing Authority (OCHA):
a. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange of
information regarding the availability, procedures, and policies related to the Housing
Assistance Voucher program and regional housing issues.
b. Support OCHA's affirmative fair marketing plan and de-concentration policies by
providing five-year and annual PHA plan certifications.
c. In coordination with OCHA and fair housing services provider, conduct landlord
education campaign to educate property owners about State law prohibiting
discrimination based on household income.
2. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and homeowner
associations on why denial of reasonable modifications/accommodations is unlawful.
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property owners,
realtors, and property management companies. Methods of outreach may include
workshops, informational booths, presentations to community groups, and distribution of
multi-lingual fair housing literature.
c. Provide general fair housing counseling and referrals services to address tenant-landlord
issues, and investigate allegations of fair housing discrimination and take appropriate
actions to conciliate cases or refer to appropriate authorities.
d. Periodically monitor local newspapers and online media outlets to identify potentially
discriminatory housing advertisements.
e. Include testing/audits within the scope of work with fair housing provider.
3. In cooperation with the Orange County Transportation Authority:
a. Provide community education regarding transport services for persons with disabilities.
b. Explore bus route options to ensure neighborhoods with concentration of low-income or
protected class populations have access to transportation services.
4. Monitor FBI data to determine if any hate crimes are housing related and if there are actions
that may be taken by the City’s fair housing service provider to address potential
discrimination linked to the bias motivations of hate crimes.
5. Support local eviction prevention strategies to reduce the number of homeless individuals and
families (homelessness prevention services).
287
6. Seek funding through State programs (SB2/PLHA) to expand affordable housing and or
homelessness prevention services.
7. Prepare a new Housing Element that is compliant with all current State laws and is certified
by the California Department of Housing and Community Development.
8. Update zoning ordinance to comply with current State law.
City of Orange
1. Continue to follow current State Density Bonus law and further its implementation through a
Density Bonus ordinance update.
2. Prepare a Transfer of Development Rights Ordinance to provide opportunities for
development rights transfers to accommodate higher density housing in transit and
employment-rich areas of the city.
3. Facilitate the development of housing along the North Tustin corridor by the way of a specific
plan or rezoning measures.
4. Amend the City’s Accessory Dwelling Unit Ordinance to be consistent with State Junior
Accessory Dwelling Unit (JADU) and Accessory Dwelling Unit (ADU) laws.
5. Prepare and adopt a small lot subdivision ordinance to streamline entitlement processing of
housing development projects.
6. Continue providing CDBG funds to the Fair Housing Foundation to provide fair housing
activities to the community.
City of Rancho Santa Margarita
1. In collaboration with the Orange County Housing Authority (OCHA):
a. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange of
information regarding the availability, procedures, and policies related to the Housing
Assistance Voucher program and regional housing issues.
b. Support OCHA's affirmative fair marketing plan and de-concentration policies by
providing five-year and annual PHA plan certifications.
c. In coordination with OCHA and fair housing services provider, conduct landlord
education campaign to educate property owners about State law prohibiting
discrimination based on household income.
2. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and homeowner
associations on why denial of reasonable modifications/accommodations is unlawful.
288
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property owners,
realtors, and property management companies. Methods of outreach may include
workshops, informational booths, presentations to community groups, and distribution of
multi-lingual fair housing literature.
c. Provide general fair housing counseling and referrals services to address tenant-landlord
issues, and investigate allegations of fair housing discrimination and take appropriate
actions to conciliate cases or refer to appropriate authorities.
d. Periodically monitor local newspapers and online media outlets to identify potentially
discriminatory housing advertisements.
e. Include testing/audits within the scope of work with fair housing provider.
3. In cooperation with the Orange County Transportation Authority:
a. Provide community education regarding transport services for persons with disabilities.
b. Explore bus route options to ensure neighborhoods with concentration of low-income or
protected class populations have access to transportation services.
4. Monitor FBI data to determine if any hate crimes are housing related and if there are actions
that may be taken by the City’s fair housing service provider to address potential
discrimination linked to the bias motivations of hate crimes.
5. Support local eviction prevention strategies to reduce the number of homeless individuals and
families (homelessness prevention services).
6. Seek funding through State programs (SB2/PLHA) to expand affordable housing and or
homelessness prevention services.
7. Prepare a new Housing Element that is compliant with all current State laws and is certified
by the California Department of Housing and Community Development.
8. Update zoning ordinance to comply with current State law.
City of San Clemente
1. In collaboration with the Orange County Housing Authority (OCHA):
a. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange of
information regarding the availability, procedures, and policies related to the Housing
Assistance Voucher program and regional housing issues.
b. Support OCHA's affirmative fair marketing plan and de-concentration policies by
providing five-year and annual PHA plan certifications.
c. In coordination with OCHA and fair housing services provider, conduct landlord
education campaign to educate property owners about State law prohibiting
discrimination based on household income.
2. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and homeowner
associations on why denial of reasonable modifications/accommodations is unlawful.
289
b. Conduct multi-faceted fair housing outreach to tenants, landlords, property owners,
realtors, and property management companies. Methods of outreach may include
workshops, informational booths, presentations to community groups, and distribution
of multi-lingual fair housing literature.
c. Provide general fair housing counseling and referrals services to address tenant-
landlord issues, and investigate allegations of fair housing discrimination and take
appropriate actions to conciliate cases or refer to appropriate authorities.
d. Periodically monitor local newspapers and online media outlets to identify potentially
discriminatory housing advertisements.
e. Include testing/audits within the scope of work with fair housing provider.
3. Support local eviction prevention strategies to reduce the number of homeless individuals and
families (homelessness prevention services).
4. Prepare a new Housing Element that is compliant with all current State laws and is certified
by the California Department of Housing and Community Development.
5. Update zoning ordinance to comply with current State law.
6. Offer a variety of housing opportunities to enhance mobility among residents of all races and
ethnicities by facilitating affordable housing throughout the community through 1) flexible
development standards; 2) density bonuses; and 3) other zoning tools.
7. Review the type and effectiveness of current affordable housing development incentives, and
amend/augment as may be necessary to increase the production of affordable housing units.
City of San Juan Capistrano
1. Develop Strategies to Address Lack of Affordability and Insufficient Income
a. Work with developers, and non-profit organizations to expand the affordable housing stock
within San Juan Capistrano.
b. Increase production of new affordable units and assistance towards the purchase and
renovation of housing in existing neighborhoods.
c. Seek housing program resources through the County of Orange Urban County CDBG
Program, and others which may become available.
5. Increase Public Awareness of Fair Housing
a. Increase fair housing education and outreach efforts.
b. Investigate options for enforcement including local enforcement conducted by neighboring
jurisdictions.
6. Develop Strategies to Address Poverty and Low-Incomes Among Minority Populations
a. Expand job opportunities through encouragement of corporations relocating to the city,
local corporations seeking to expand, assistance with small business loans, and other
activities.
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b. Support agencies that provide workforce development programs and continuing education
courses to increase educational levels and job skills of residents.
7. Develop Strategies to Address Limited Resources to Assist Lower-Income, Elderly, and
Indigent Homeowners Maintain their Homes and Stability in Neighborhoods
a. Consider implementing a volunteer program for providing housing assistance to elderly
and indigent property owners, including assistance in complying with municipal housing
codes.
b. Encourage involvement from volunteers, community organizations, religious
organizations, and businesses as a means of supplementing available financial resources
for housing repair and neighborhood cleanup.
City of Santa Ana
1. Review and amend Santa Ana’s inclusionary housing ordinance to increase its effectiveness.
2. Evaluate the creation of a motel conversion ordinance to increase the supply of permanent
supportive housing similar to the City of Anaheim and Los Angeles.
3. Review Santa Ana’s density bonus ordinance and explore adding a density bonus for transit-
oriented development (TOD) similar to the City of Los Angeles.
4. Explore establishing a dedicated source of local funding for a Right to Counsel program for
residents of Santa Ana to ensure that they have access to legal representation during eviction
proceedings similar to the City of New York.
5. Continue to invest in local eviction prevention strategies to reduce the number of homeless
individuals and families in Santa Ana.
City of Tustin
1. In collaboration with the Orange County Housing Authority (OCHA):
a. Attend quarterly OCHA Housing Advisory Committee to enhance the exchange
of information regarding the availability, procedures, and policies related to the
Housing Assistance Voucher program and regional housing issues.
b. Support OCHA's affirmative fair marketing plan and de-concentration policies
by providing five-year and annual PHA plan certifications.
c. In coordination with OCHA and fair housing services provider, conduct
landlord education campaign to educate property owners about State law
prohibiting discrimination based on household income.
2. Through the City's fair housing contractor:
a. Provide fair housing education and information to apartment managers and
homeowner associations on why denial of reasonable modifications/accommodations is
unlawful.
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b. Conduct multi-faceted fair housing outreach to tenants, landlords, property
owners, realtors, and property management companies. Methods of outreach may
include workshops, informational booths, presentations to community groups, and
distribution of multi-lingual fair housing literature.
c. Provide general fair housing counseling and referrals services to address tenant-
landlord issues, and investigate allegations of fair housing discrimination and
take appropriate actions to conciliate cases or refer to appropriate authorities.
d. Periodically monitor local newspapers and online media outlets to identify
potentially discriminatory housing advertisements.
e. Include testing/audits within the scope of work with fair housing provider.
3. Prepare a new Housing Element that is compliant with all current State laws and is certified
by the California Department of Housing and Community Development.
4. Utilize funding through State programs (SB2) to support affordable housing and/or
homeless prevention services.
5. Update zoning ordinance to comply with current State law.
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VII. CONTRIBUTING FACTORS APPENDIX
Access for Students with Disabilities to Proficient Schools
Access for students with disabilities to proficient schools may be a significant contributing factor
to fair housing issues. There are more than 600 public schools in Orange County, part of 27 school
districts. There is a history of barriers to education for persons with disabilities in Orange County.25
These included issues with school districts in Garden Grove, Los Alamitos, and Orange, as well
as the Capistrano Unified School District which crosses city boundaries. However, this Analysis
did not reveal more recent systemic policies or practices driving disparities for stud ents with
disabilities. At the same time, school discipline data for Orange County reveals a 4.5% suspension
rate for students with disabilities as compared to a 1.9% suspension rate for students who do not
have disabilities. Both rates are lower than statewide but still show that students with disabilities
face barriers in accessing education that others do not encounter. This data calls for affirmative
strategies to reduce school discipline disparities and avoid unnecessary suspensions of students
with disabilities.
Access to Transportation for Persons with Disabilities
Access to transportation for persons with disabilities may be a significant contributing factor to
fair housing issues in Orange County. The main barrier to transportation for persons with
disabilities in Orange County is the lack of public transportation infrastructure generally, including
the lack of east-west rail service and rail service in coastal communities and long wait times for
buses in the southern portion of the county. Because many persons with disabilities are dependent
on public transportation, these problems hit persons with disabilities especially hard. This Analysis
did not reveal any systemic problems with the accessibility of major providers’ services, such as
Metrolink or the Orange County Transportation Authority. Each agency’s vehicles generally
appear to meet accessibility requirements, and the Orange County Transportation Authority
provides required paratransit service through OC Flex.
Access to Financial Services
Access to financial services may be a contributing factor to fair housing issues for Hispanic
residents of Orange County. Although this Analysis did not undertake a comprehensive analysis
of bank branch locations in Orange County, a limited review of the banks ranked as the three best
in Orange County by the Orange County Register revealed disparities in locations served.26 The
highest ranked bank, California Bank & Trust, has nine locations in Orange County, none of which
are located in the cities of Anaheim and Santa Ana,27 the two largest cities in the county and areas
with concentrations of Hispanic population. Although larger banks like Chase and Bank of
America have branches in Anaheim and Santa Ana, there are still disproportionately few branches
in those locations than in smaller, less heavily Hispanic cities like Irvine and Huntington Beach.
For example, there are 16 Chase branches in Irvine and seven in Huntington Beach as opposed to
five in Anaheim and one in Santa Ana. Bank of America’s distribution of service is somewhat
more balanced (though not when accounting for population) with six branches in Santa Ana, eight
25 Rex Dalton, OC Families Face Fierce Fight for Special Ed Services, VOICE OF OC (Sep. 25, 2012),
https://voiceofoc.org/2012/09/oc-families-face-fierce-fight-for-special-ed-services/.
26 Kenya Barrett, Best of Orange County 2019: Best Bank, THE ORANGE COUNTY REGISTER (Sep. 19, 2019),
https://www.ocregister.com/2019/09/19/best-of-orange-county-2019-best-bank/.
27 https://www.calbanktrust.com/locations/
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in Anaheim, eight in Irvine, and six in Huntington Beach. Lack of access to conventional financial
services like those offered by banks can prevent residents of underserved neighborhoods from
building credit that will help them attain homeownership and can leave residents with few options
but to patronize predatory financial services providers like payday lenders. A 2016 report from the
California Department of Business Oversight noted that, while 38.7% of California’s population
was Hispanic, the average percentage of Hispanic residents in zip codes with six or more storefront
payday lenders was 53%.28 Payday loans often lead to a cycle of debt that impedes individuals’
access to opportunity and economic mobility more generally. In Orange County, that phenomenon
appears to be especially likely to harm Hispanic residents, particularly in Santa Ana.
Access to Publicly Supported Housing for Persons with Disabilities
Access to publicly supported housing for persons with disabilities may be a significant contributing
factor to fair housing issues in Orange County. Although persons with disabilities are generally
able to access Housing Choice Vouchers at rates that are commensurate with their share of the
income-eligible population, access to Project-Based Section 8 is more limited in many cities. For
Project-Based Section 8, cities with disproportionately low concentrations of residents with
disabilities include Costa Mesa, Garden Grove, La Habra, and Westminster.
Admissions and Occupancy Policies and Procedures, Including Preferences in Publicly
Supported Housing
Admissions and occupancy policies and procedures, including preferences in publicly supported
housing may be a significant contributing factor to fair housing issues in Orange County. In
particular, housing authorities, including the Orange County Housing Authority, provide live-work
preferences to applicants for Housing Choice Vouchers. Given that Los Angeles County is
significantly more heavily Black than Orange County, live-work preferences in Orange County
may have the effect of disproportionately excluding Black families that might want to move to
Orange County. Housing authorities also have some criminal background screening policies that
might be overly restrictive. For example, the Orange County Housing Authority and the Anaheim
Housing Authority consider violent criminal activity that occurred as long as five years ago, even
if that activity consisted of minor misdemeanor conduct. The Garden Grove Housing Authority
also denies assistance based on arrest records alone in certain cases, a policy that contradicts
applicable HUD guidance.
Availability of Affordable Units in a Range of Sizes
The availability of affordable units in a range of sizes may be a significant contributing factor to
fair housing issues in Orange County. Overcrowding, as defined by HUD, in Orange County is
very high, at 9.51% overall, expanding to 15.97% for renters. Broken down by race, White, Black,
and Asian American residents live in overcrowded conditions at a rate of 6 or 7%, while Hispanic
residents are overcrowded at a rate of 26% countywide. For Publicly Supported Housing, a
supermajority (74.67%) of Project-Based Section 8 units are 0-1-bedroom units, as are Other
Multifamily units (84.54%, the other 15% having 2 bedrooms). A plurality of Housing Choice
Vouchers are also limited to 0-1 bedroom units (43.97%). 5,561 households or 26.20% of Housing
Choice Voucher occupants are also households with children, the highest of any category of
28 The Demographics of California Payday Lending: A Zip Code Analysis of Storefront Locations , CALIFORNIA
DEPARTMENT OF BUSINESS OVERSIGHT (2016), https://dbo.ca.gov/wp-content/uploads/sites/296/2019/02/The-
Demographics-of-CA-Payday-Lending-A-Zip-Code-Analysis-of-Storefront-Locations.pdf.
294
publicly supported housing (followed by Project-Based Section 8, with 9.62%). Overall, most
housing units in the county contain 2 (28%), 3 (30%), or 4 (21%) bedrooms, indicating that on
paper, accessing housing units with enough bedrooms to house families or live-in aides using a
voucher is likely. However, these numbers do not speak to affordability and/or whether these units
are within the payment standards for vouchers. Source of income discrimination was recently
outlawed statewide, so even more units within the payment standards should be available to
voucher users in the future.
Availability, Type, Frequency, and Reliability of Public Transportation
The availability, type, frequency, and reliability of public transportation may be contributing
factors to fair housing issues in Orange County. Public transportation in Orange County primarily
consists of bus service operated by the Orange County Transportation Authority (OCTA) and
Metrolink light rail service. Additionally, more geographically limited service is available through
Anaheim Resort Transportation’s bus system and the OC Streetcar, connecting Garden Grove and
Santa Ana. Paratransit service is available through OC Flex. This public transportation has two
important shortcomings that have ramifications for fair housing issues. First, Metrolink does not
provide service to coastal communities in the central and northern portions of Orange County.
These communities, such as Huntington Beach, Newport Beach, and Laguna Beach are
disproportionately White in comparison to the county as a whole. The relative lack of public
transportation in these areas may deter members of protected classes who do not have cars and are
reliant on public transportation from choosing to live there, thus reinforcing patterns of
segregation. Second, although the OCTA offers bus service throughout the county, none of its
high-frequency lines, which run every 15 minutes during weekday rush hour, serve the southern
half of the county. As with the lack of light rail service in coastal communities, poorer quality bus
service in the disproportionately White southern half of the county may deter households from
making residential choices that would further integration. The low frequency and sparse bus lines
in southern Orange County also burden low-income households that disproportionately consist of
protected class members and make their lives more difficult.
Community Opposition
Community Opposition may be a significant contributing factor to fair housing issues in Orange
County. The County is now only plurality White,29 but recent political and demographic change
have not slowed opposition to affordable housing in Orange County, as residents have mobilized
to delay and prevent affordable housing efforts. Some Orange County cities have voted to oppose
or are preparing to oppose statewide plans to add 22,000 affordable housing units in the County.30
For the most part, residents, community planners, and elected officers opposed to the plan have
cited procedural concerns such as insufficient concern for local participation.31 Opposition to
multifamily housing and housing for the homeless and affordable housing generally betrays a
wider opposition to such initiatives based on “NIMBY” (“Not In My Backyard”) sentiments.
In Fullerton, for example, residents recently mobilized to stop the creation of an affordable housing
complex, citing concerns that the complex would reduce property values, create danger to children,
29 QuickFacts: Orange County, California, UNITED STATES CENSUS BUREAU,
https://www.census.gov/quickfacts/orangecountycalifornia (last visited Jan. 16, 2020).
30 See, e.g.,Hosam Elattar and Noah Biesiada, OC Cities Pushing Back Against Housing Target Increases, VOICE OF
OC (Jan. 14, 2020), https://voiceofoc.org/2020/01/oc-cities-pushing-back-against-housing-target-increases/.
31 Id. Complaints included that the state plan’s “methodology was unfair” and not done in “good faith.”
295
and “attract people from other cities” that would become the responsibility of Fullerton residents.32
Additionally, in early 2019, opposition to state plans to increase affordable housing forced
California to sue the City of Huntington Beach to force compliance.33 Finally, State and regional
landlord associations have organized to oppose rent control and anti-eviction legislation.34
Overall, despite demographic and political changes, community opposition to fair housing in
Orange County remains robust.
Deteriorated and Abandoned Properties
Deteriorated and abandoned properties are not a significant contributing factor to fair housing
issues in Orange County. Although there was a surge in deteriorated and abandoned properties in
the wake of the foreclosure crisis, particularly in heavily Hispanic areas and with significant
harmful consequences for communities,35 that issue has gradually abated over the ensuring years.
The table below reflects the proportion of vacant housing units in each city in Orange County that
is categorized as “Other Vacant” in the American Community Survey. These are the vacant units
that are most likely to be abandoned rather than capturing vacation rentals and units that are
currently on the rental or sales market.
Table: Other Vacant Housing Units by City, 2013-2017 American Community Survey
City Number of Other Vacant
Units
% of Vacant Units That Are
Other Vacant Units
Aliso Viejo 150 13.3%
Anaheim 599 14.1%
Brea 74 14.3%
Buena Park 447 47.5%
Costa Mesa 300 15.6%
Cypress 144 33.8%
Dana Point 196 7.5%
Fountain Valley 180 36.3%
Fullerton 485 20.1%
Garden Grove 373 30.5%
32 Jill Replogle, ‘Not In My Backyard’: What the Shouting Down of One Homeless Housing Complex Means For Us
All, LAIST (Oct. 15, 2018), https://projects.scpr.org/interactives/fullerton-nimby/.
33 Don Thompson, California Sues Wealthy Coastal City Over Low-Income Housing, ASSOCIATED PRESS (Jan. 25,
2019), https://apnews.com/f5c6edc6bd31442082f5b4964a0bc51d .
34 Marisa Kendall, California-Wide Rent Cap Advances Despite Landlord Opposition, O.C. REGISTER (July 10,
2019), https://www.ocregister.com/2019/07/10/ab-1482-set-for-senate-hearing/.
35 Alejandra Molina, No More Eyesores: Santa Ana Asks Courts to Intervene and Fix Abandoned Properties , O.C.
REGISTER (Mar. 11, 2015), https://www.ocregister.com/2015/03/11/no-more-eyesores-santa-ana-asks-courts-to-
intervene-and-fix-abandoned-properties/.
296
Huntington Beach 835 18.9%
Irvine 628 11.4%
Laguna Beach 640 23.7%
Laguna Hills 26 4.6%
Laguna Niguel 453 27.8%
Laguna Woods 327 22.4%
La Habra 144 19.0%
Lake Forest 120 11.8%
La Palma 38 28.8%
Los Alamitos 12 9.2%
Mission Viejo 239 20.6%
Newport Beach 982 14.6%
Orange 548 33.7%
Placentia 155 38.3%
Rancho Santa Margarita 0 0.0%
San Clemente 397 12.0%
San Juan Capistrano 312 46.2%
Santa Ana 599 30.3%
Seal Beach 315 27.3%
Stanton 109 25.7%
Tustin 162 13.8%
Villa Park 45 43.3%
Westminster 213 24.9%
Yorba Linda 173 21.0%
These Other Vacant units do not appear to be disproportionately concentrated in communities with
high concentrations of Hispanic households and low White Populations. Villa Park and Fountain
Valley have relatively low Hispanic population concentrations while San Juan Capistrano and
Buena Park have similar concentrations to the county as a whole. Additionally, although Santa
Ana has a fairly high concentration of Other Vacant units among its vacant units, overall vacancy
297
is very low there in relation to the county as a whole. This is consistent with a picture of housing
market that is very tight for low-income residents even in the lowest income parts of the area.
Displacement and Lack of Housing Support for Victims of Domestic Violence, Dating Violence,
Sexual Assault, and Stalking
Displacement and lack of housing support for victims of domestic violence, dating violence, sexual
assault, and stalking are not significant contributing factors to fair housing issues in Orange
County. California state law protects victims of domestic violence, sexual assault, stalking, human
trafficking, or abused elder or dependent adult who terminates their lease early.36 The tenant must
provide written notice to the landlord, along with a copy of a temporary restraining order,
emergency protective order, or protective order that protects the household member from further
domestic violence, sexual assault, stalking, human trafficking, or abuse of an elder or dependent
adult. Alternatively, proof may be shown by submitting a copy of a written report by a peace
officer stating that the victim has filed an official report, or documentation from a qualified third
party acting in their professional capacity to indicate the resident is seeking assistance for physical
or mental injuries or abuse stemming from the abuse at issue. Notice to terminate the tenancy must
be given within 180 days of the issuance date of the qualifying order or within 180 days of the date
that any qualifying written report is made. This Analysis did not reveal specific evidence of
noncompliance with these requirements in Orange County or of other barriers faced by domestic
violence survivors.
Displacement of Residents Due to Economic Pressures
Displacement of residents due to economic pressures may be a significant contributing factor to
fair housing issues in Orange County and, in particular, in parts of Orange County that have
historically had concentrations of low-income Hispanic and Vietnamese residents. The map below
from the Urban Displacement Project at the University of California Berkeley shows census tracts
that experienced gentrification both between 1990 and 2000 and between 2000 and 2015 (in red),
census tracts that experienced gentrification between 2000 and 2015 (in light blue), census tracts
that experienced gentrification between 1990 and 2000 (in dark blue), and disadvantaged
communities that have not gentrified (in tan). Although there are no census tracts in Orange County
coded as having experienced gentrification in both time periods, there are several census tracts that
have undergone gentrification at some point since 1990 including in Anaheim, Costa Mesa, Dana
Point, Fountain Valley, Fullerton, Garden Grove, Huntington Beach, Irvine, Orange, San
Clemente, and Villa Park. Though the Urban Displacement Project does not map the risk of future
gentrification in displacement in Southern California as it does in the Bay Area, the areas most
vulnerable to gentrification and displacement in Orange County – going forward – are
disadvantaged areas located near areas that have already gentrified and disadvantaged areas
located near major transit assets as well as anchor institutions like universities and hospitals.
Because the southern and coastal portions of Orange County have relatively few disadvantaged
areas, displacement risk is therefore concentrated in inland portions of central and northern Orange
County such as Anaheim, Fullerton, Garden Grove, Irvine, Orange, Santa Ana, and Westminster.
These areas also tend to have higher Hispanic and Asian population concentrations than the county
as a whole, illustrating the fair housing implications of displacement.
36 ttps://leginfo.legislature.ca.gov/faces/codes_displaySection.xhtml?lawCode=CIV§ionNum=1946.7
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Impediments to Mobility
Impediments to mobility may be a significant contributing factor to fair housing issues in Orange
County. Specifically, Housing Choice Voucher payment standards that make it difficult to secure
housing in many, disproportionately White parts of the county contribute to segregation and
disparities in access to opportunity. Some housing authorities within the county have gone to tiered
rent systems that provide greater nuance than region-wide payment standards, but their payment
standards still are not as generous as Small Area Fair Market Rents would be. For example, the
Anaheim Housing Authority has two tiers, one for zip code 92808 and one for all other zip codes.
In zip code 92808, the payment standard for a two-bedroom unit is $2,438 while, in all other zip
codes, it is $2,106. Yet the hypothetical Small Area Fair Market Rent for a two-bedroom unit in
zip code 92808, which is located in the Anaheim Hills, would be $2,790. Additionally, zip codes
92806 and 92807, which also cover the eastern half of the city but do not benefit from the higher
payment standard, would have Small Area Fair Market Rents of $2,380 and $2,660 respectively,
far higher than $2,106. A similar phenomenon pervades the Orange County Housing Authority’s
administration of the voucher program. That agency has three tiers based on city rather than zip
code, but the highest tier - $2,280 for two-bedroom units in selected cities – falls far short of Small
Area Fair Market Rents and leaves some cities targeted for that payment standard out of reach. For
example, in zip code 92660, located in Newport Beach, the Small Area Fair Market Rent for two-
bedroom units would be $3,120. A Zillow search for that zip code revealed advertised two-
bedroom units in only two complexes available for under $2,280 but many more available between
$2,280 and $3,120.
Inaccessible Government Facilities or Services
Inaccessible government facilities or services are not a significant contributing factor to fair
housing issues in Orange County. This Analysis did not reveal examples of government facilities
or services in Orange County that are inaccessible.
Inaccessible Public or Private Infrastructure
Inaccessible public or private infrastructure is not a significant contributing factor to fair housing
issues in Orange County. This Analysis did not reveal examples of public or private infrastructure
in Orange County that is infrastructure.
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Lack of Access to Opportunity Due to High Housing Costs
Lack of access to opportunity due to high housing costs may be a significant contributing factor to
fair housing issues in Orange County. In particular, as the Disparities in Access to Opportunity
section of this Analysis reveals, coastal areas of Orange County as far eastern portions of the
county have greater access to educational, economic, and environmental opportunity than do most
areas in between, with the partial exception of Irvine. Additionally, environmental quality is higher
in predominantly White southern Orange County than in the more diverse areas to the north. In
general, the disproportionately White coastal and hillside communities with better educational,
economic, and environmental outcomes are also areas with high housing costs. Increasing housing
affordability in these areas would make it easier for low-income households, disproportionately
including Hispanic and Vietnamese households, to access the types of services and amenities that
further social mobility.
Lack of Affordable, Accessible Housing in a Range of Unit Sizes
Lack of affordable, accessible housing in a range of unit sizes may be a significant contributing
factor to fair housing issues in Orange County. As discussed in connection with several other
contributing factors, there is a general shortage of affordable housing in the county. This is
exacerbated by the fact that, as discussed in relation to the availability of affordable units in a range
of sizes, the vast majority of publicly supported housing units are one-bedroom units. Low-income
households that need larger units are dependent upon the Housing Choice Voucher program to
access housing. However, unlike with Project-Based Section 8 units, for example, there is no
requirement that privately owned and managed units that tenants use vouchers to rent meet the
heightened accessibility requirements of Section 504 of the Rehabilitation Act. This shortage has
a particular effect on low-income families in which at least one member has a disability that
requires accessibility features, and persons with disabilities who require the services of live -in
aides.
Lack of Affordable In-Home or Community-Based Supportive Services
Lack of affordable in-home or community-based supportive services may be a significant
contributing factor to fair housing issues in Orange County. Due to the absence of any waiting list
for Home and Community-Based Services for persons with developmental disabilities, this issue
primarily affects people with psychiatric disabilities. A robust array of services, including the most
intensive models of community-based services like Assertive Community Treatment,37 are
available. Nonetheless, many people have trouble accessing needed services, and service providers
are not always able to reach vulnerable populations through street outreach. Additionally, across
types of disabilities, undocumented adults face barriers due to federal restrictions of Medicaid
assistance for undocumented people. The California Legislature has approved state funding for
Medi-Cal services for undocumented people until they reach the age of 26, a critical investment
that exceeds that of any other state, but there remains a funding gap for services for most
undocumented adults.
Lack of Affordable, Integrated Housing for Individuals Who Need Supportive Services
37 Assertive community treatment (ACT) is a form of community-based mental health care that provides
community-based, multi-disciplinary mental health treatment for individuals with severe and persistent mental
illness.
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Lack of affordable, integrated housing for individuals who need supportive services may be a
significant contributing factor to fair housing issues in Orange County. This is a significant
contributing factor for two reasons. First, the shortage of permanent supportive housing throughout
Orange County in comparison to the total need is characteristic of the broader shortage of
affordable housing generally. Second, although there are some programs that specifically focus on
providing permanent supportive housing to individuals with disabilities including developments
built with Mental Health Services Act funds and Mainstream Housing Choice Vouchers, there has
not been a concerted effort to raise local bond funds for affordable housing and then to prioritize
permanent supportive housing with a portion of bond proceeds like there has been in some other
California jurisdictions, including Los Angeles County and Santa Clara County.
Lack of Assistance for Transitioning from Institutional Settings to Integrated Housing
Lack of assistance for transitioning from institutional settings to integrated housing is not a
significant contributing factor to fair housing issues in Orange County. The Dayle McIntosh Center
provides robust services to individuals transitioning from institutional settings to integrated
housing, and there is no indication that they are unable to meet the total need for such services.
Lack of Community Revitalization Strategies
Lack of community revitalization strategies is not a significant contributing factor to fair housing
issues in Orange County. In communities with significant revitalization needs, such as in
disproportionately low-income and heavily Hispanic and Vietnamese neighborhoods in Anaheim,
Fullerton, Garden Grove, Santa Ana, and Westminster, there is no shortage of private investment
interest that would enhance or has enhanced community amenities. The more pressing problem is
the risk of displacement that would prevent long-time residents enjoying new amenities in recently
revitalized communities.
Lack of Local or Regional Cooperation
Lack of local or regional cooperation may be a significant contributing factor to fair housing issues
in Orange County. Although the infrastructure for collaboration across jurisdictions exists, as
demonstrated by this county-wide Analysis of Impediments to Fair Housing Choice, there remains
a problem with local governments not taking the steps to achieve regionally determined goals like
progress toward meeting each jurisdictions Regional Housing Needs Allocation for very low -
income and low-income households. This gap has resulted in litigation between the City of
Huntington Beach and the State of California.38
Lack of Local Private Fair Housing Outreach and Enforcement
Lack of local private fair housing outreach and enforcement may be a significant contributing
factor to fair housing issues in Orange County. Although Orange County is served by two, high-
quality private, non-profit fair housing organizations, they are underfunded and understaffed in
comparison to the total need for their services. Victims of discrimination would be more able to
exercise their rights, thus deterring future discrimination, if the capacity of existing organizations
grew to meet the scale of the problem.
Lack of Local Public Fair Housing Outreach and Enforcement
38 Priscella Vega et al., State Sues Huntington Beach over Blocked Homebuilding, L.A. TIMES (Jan. 25, 2019),
https://www.latimes.com/socal/daily-pilot/news/tn-dpt-me-hb-housing-lawsuit-20190125-story.html.
301
Lack of local public fair housing outreach and enforcement may be a significant contributing factor
to fair housing issues in Orange County. There are no local public entities that conduct fair housing
outreach and enforcement, with the California Department of Fair Employment and Housing and
HUD constituting the only public enforcement bodies that operate in Orange County. Advocates
across Orange County and the state of California have reported issues with the timeline of the
California Department of Fair Employment and Housing’s investigations and the standards that it
applies in making probable cause determinations. A local public enforcement agency, if created,
would have the potential to be more responsive to victims of discrimination in Orange County than
either the state or HUD.
Lack of Meaningful Language Access for Individuals with Limited English Proficiency
Lack of meaningful language access for individuals with limited English proficiency may be a
significant contributing factor to fair housing issues in Orange County. Private landlords generally
are not required to provide leases or other key documents or communications in the primary
languages of individuals with limited English proficiency (LEP). This can create confusion about
individuals’ rights. Housing authorities frequently have staff who are fluent in Spanish and/or
Vietnamese, but LEP speakers of other languages may have limited options, with housing
authorities relying on paid translation or interpretation services to communicate.
Lack of Private Investment in Specific Neighborhoods
Lack of private investment in specific neighborhoods is not a significant contributing factor to fair
housing issues in Orange County. There are neighborhoods, particularly disproportionately low -
income, predominantly Hispanic neighborhoods, that have historically been subject to
disinvestment by the private sector. Santa Ana had long been emblematic of that pattern, but it has
begun to see a return of private capital, and accompanying gentrification risk, in recent years.39
Lack of Public Investment in Specific Neighborhoods
Lack of public investment in specific neighborhoods is not a significant contributing factor to fair
housing issues in Orange County. Although there is a history of disparities in public infrastructure
in Orange County between areas that are predominantly White and more heavily Hispanic
communities, this Analysis did not reveal evidence of the current extent of this potential problem
nor if the interrelationship of that issue to patterns of segregation and displacement. This Analysis
addresses the public resources available to schools in the contributing factor relating to the location
of proficient schools and school assignment policies.
Lack of Resources for Fair Housing Agencies and Organizations
Lack of resources for fair housing agencies and organizations may be a significant contributing
factor to fair housing issues in Orange County. Two robust fair housing organizations operate in
Orange County, provide services to residents, and engage in enforcement, outreach, and education.
However, the size of the federal Fair Housing Initiatives Program, the primary funding program
for fair housing organizations, has failed to keep up with inflation, making Congress’s
appropriations worth less over time. In order to meet the needs of residents of a large and diverse
county, local fair housing agencies and organizations require greater levels of resourcing.
39 Erualdo R. González et al., The Gentrification of Santa Ana: From Origin to Resistance, KCET (Sep. 13, 2017),
https://www.kcet.org/shows/city-rising/the-gentrification-of-santa-ana-from-origin-to-resistance.
302
Lack of State or Local Fair Housing Laws
Lack of state or local fair housing laws is not a significant contributing factor to fair housing issues
in Orange County. Although no jurisdictions in Orange County had prohibited source of income
discrimination against Housing Choice Voucher holders prior to the California Legislature passing
SB 222 and SB 329 banning the practice statewide, that step by the State means that there are not
significant gaps in non-discrimination protections for residents of Orange County.
Land Use and Zoning Laws
Land use and zoning laws may be a significant contributing factor to fair housing issues in Orange
County. With some exceptions, communities in Orange County that have relatively high
concentrations of White residents and relatively low concentrations of Hispanic residents tend to
have zoning that allows for limited opportunities to develop multifamily housing. In the absence
of multifamily zoning, it is generally infeasible to develop affordable housing for which occupancy
is likely to disproportionately consist of protected class members. The zoning map of Laguna
Beach, shown below, illustrates the high proportion of land that is reserved for low-density
residential development.
303
304
Villa Park appears to be a particularly extreme case. As the map below shows, multifamily housing
is not permitted in any location in the city.
305
306
Lending Discrimination
Lending discrimination may be a contributing factor to fair housing issues in Orange County.
Given the scarcity of affordable rental housing and high cost of living within Orange County, loan
opportunities for home improvement, purchase, and refinancing are important tools for moderate
and low-income households. Using Home Mortgage Disclosure Act (HMDA) data, the tables
below show the racial discrepancies in the likelihood that a person’s loan application, based on
their race, will result in an originated loan or a denial.
Percentage of Loan Applications Resulting in Originated Loans by Race or Ethnicity and
Loan Purpose in Orange County, 2014-2017 Home Mortgage Disclosure Act Data
Race or Ethnicity Home Purchase Refinancing Home Improvement
White, Not Hispanic 66.56% 59.12% 61.96%
Black, Not Hispanic 61.93% 49.62% 49.49%
Asian, Not Hispanic 63.95% 55.35% 51.26%
Hispanic/Latino 59.54% 50.57% 51.60%
Percentage of Loan Applications Denied by Race or Ethnicity and Loan Purpose in Orange
County, 2014-2017 Home Mortgage Disclosure Act Data
Race or Ethnicity Home Purchase Refinancing Home Improvement
White, Not Hispanic 9.09% 16.30% 17.60%
Black, Not Hispanic 12.03% 22.04% 31.74%
Asian, Not Hispanic 9.75% 16.65% 23.21%
Hispanic/Latino 12.38% 20.75% 28.12%
Across all ethnic groups and loan types, White residents are the most likely to have their loan
applications result in originated loans. Disparities across racial or ethnic groups are not very
significant, however. For Home Purchase, approval rates range between 59.54% and 66.56%.
Home Purchase loans also have the highest rate of approval, which is important in ensuring equal
access to the homeownership market. Refinancing and Home Improvement loans have similar
approval rates, with Black borrowers approved at about 49%, while White borrowers are approved
at 59% and 62%, respectively. In a county where 57% of housing units are owner occupied and
the median price for a sold home is $721,400,40 the lack of a significant disparity in loan origination
for home purchase loans is noteworthy.
More disparities emerge when looking at the other types of loans. Across refinancing and home
improvement loan applications, Hispanics are less likely to have a loan originate, and roughly 10%
more likely to have a home improvement loan application denied and 4% more likely to have a
refinancing loan denied. All ethnic groups are more likely than White residents to have their loan
40 https://www.zillow.com/orange-county-ca/home-values/
307
applications denied. Black residents are roughly 6% more likely to have refinancing loan
application denied. More drastic disparities appear for home improvement loans. Black residents
are nearly twice as likely to have a home improvement loan denied than White residents, Asian
residents are 5% more likely
In addition, the HMDA data indicates the rates at which certain races receive high-priced loans. In
Orange County, White and Asian borrowers are least likely to be given a high cost loan.
Meanwhile, Black residents are nearly twice as likely to receive subprime loans, and Hispanics are
nearly 2.5 times more likely. Lack of access to loans, or loans that are not high-priced, for Black
and Hispanic borrowers can often price these households out of owner-occupied single-family
homes, and increases the cost burden over time as rent continues to increase across the county.
Percentage of Originated Loans That Were High-Cost by Race or Ethnicity in Orange
County, 2014-2017 Home Mortgage Disclosure Act Data
Race or Ethnicity Number of Loans Originated Percentage High-Cost
White, Not Hispanic 3,408 2.06%
Black, Not Hispanic 102 3.79%
Asian, Not Hispanic 1,277 2.07%
Hispanic/Latino 1,757 4.90%
Location and Type of Affordable Housing
The location and type of affordable housing may be significant contributing factors to fair housing
issues in Orange County. With respect to the location of affordable housing, at a high level, there
is relatively little such housing in coastal areas, hillside communities, or in the southern portion of
the county, all areas that are disproportionately White and have relatively low Hispanic population
concentrations. Within some cities that have patterns of intra-jurisdictional segregation, affordable
housing is concentrated in particular areas that tend to be more heavily Hispanic. This is especially
true in Anaheim, where affordable housing is concentrated in the heavily Hispanic western portion
of the city rather than in the mostly White Anaheim Hills. Similarly, in Fullerton, affordable
housing is more concentrated in the disproportionately Hispanic southern portion of the city, and,
in Garden Grove, affordable housing is concentrated in the disproportionately Hispanic eastern
portion of the city. With respect to the role of the type of affordable housing in causing fair housing
issues, the total lack of public housing in Orange County, which tends to be more accessible to
members of protected classes than do Low Income Housing Tax Credit developments, may play a
role in perpetuating segregation.
Location of Accessible Housing
The location of accessible housing may be a significant contributing factor to fair housing issues
in Orange County. With a few exceptions the location of accessible housing tends to track areas
where there are concentrations of publicly supported housing. In Orange County, publicly
supported housing tends to be concentrated in areas that are disproportionately Hispanic and/or
Vietnamese and that have relatively limited access to educational opportunity and environmental
health. Irvine, which has a substantial supply of publicly supported housing, is a limited exception
308
to this trend. Market-rate multifamily housing is also more likely to be accessible, though to a
lesser standard than publicly supported housing, due to the design and construction standards of
the Fair Housing Act. Multifamily housing tends to be concentrated in communities of color, but
there are some predominantly White communities that have significant amounts of market-rate
multifamily housing that may be accessible and affordable to middle-income and high-income
persons with disabilities. These areas include Aliso Viejo, Laguna Woods (which primarily
consists of a large retirement community), Newport Beach, and Seal Beach. Overall, permitting
more multifamily housing and assisting more publicly supported housing in predominantly White
communities with proficient schools would help ensure that persons with disabilities who need
accessibility features in their homes have a full range of neighborhood choices available to them.
Location of Employers
The location of employers is not a significant contributing factor to fair housing issues in Orange
County. There does not appear to be any clear relationship between patterns of occupancy by race
or ethnicity and where major job centers are in Orange County. In fact, there are areas of Hispanic
population concentration, particularly in Anaheim and Santa Ana, that are located near major
employment centers. Additionally, heavily Hispanic communities in Orange County have greater
access to job centers in Los Angeles County than do predominantly White communities due to the
routing of Metrolink through the central portion of the county rather than along the coast or through
the hills.
Location of Environmental Health Hazards
The location of environmental health hazards may be a significant contributing factor to fair
housing issues in Orange County. Data indicates communities with a high concentration of
Hispanics experience higher levels of environmental harms; exposure primarily stems from vehicle
emissions due to the proximity of major freeways and the settling of smog in the area between the
coast and the hills rather than the location of major industrial facilities. As a county that developed
as a predominantly suburban area, there is no long history of heavy industrial activity in the area.
Of the county’s four Superfund sites, one – Orange County North Basin on the border of Fullerton
and Anaheim – is located in a heavily Hispanic area. In light of these circumstances, efforts to
reduce vehicle emissions and efforts to increase access to coastal and hillside communities for
Hispanic residents would be most likely to reduce environmental health disparities.
Location of Proficient Schools and School Assignment Policies
The location of proficient schools and school assignment policies may be significant contributing
factors to fair housing issues in Orange County. The schools with the highest proficiency in Orange
County are generally located in coastal areas and hillside areas rather than in the center of the
county, though Irvine is an exception. This distribution of proficient schools maps on to patterns
of residential racial and ethnic segregation, with disproportionately White population in areas with
high performing schools and relatively low Hispanic population in those areas. Public education
in Orange County is highly fragmented with 27 school districts serving the county’s students.
District boundaries frequently map onto municipal boundaries, which in turn correlate to patterns
of segregation. Inter-district transfers are only available for extremely limited circumstances. This
Analysis did not reveal school assignment policies that contribute to segregation within individual
school districts.
309
Loss of Affordable Housing
The loss of affordable housing may be a significant contributing factor to fair housing issues in
Orange County. When subsidy contracts expire, the housing providers that often have the least
economic incentive to renew their affordability restrictions are those that are located in higher
opportunity areas or in areas that are gentrifying or at risk of gentrification. In Orange County,
according to the National Affordable Housing Preservation Database, there are 69 subsidized
properties with affordability restrictions that are scheduled to expire between now and the end of
2024. The loss of the developments among these that are most likely to be converted to market-
rate occupancy could contribute to segregation and fuel displacement.
Occupancy Codes and Restrictions
Occupancy codes and restrictions may be a significant contributing factor to fair housing issues in
Orange County. Specifically, there is a substantial recent history of municipal ordinances targeting
group homes, in general, and community residences for people in recovery from alcohol or
substance abuse disorders, in particular. In 2015, the City of Newport Beach entered into a $5.25
million settlement of a challenge to its ordinance, but that settlement did not including injunctive
relief calling for a repeal of that ordinance.41 Group home operators have also challenged the City
of Costa Mesa’s ordinance, though a jury found in the City’s favor.42 Following the jury’s verdict
in that case, there were reports that Orange County was considering similar restrictions for its
unincorporated areas.43 Although municipalities have an interest in protecting the health and safety
of group home residents, these types of restrictions may be burdensome for ethical, high-quality
group home operators. Occupancy codes and restrictions are not as high priority of a barrier as the
factors that hinder the development of permanent supportive housing, as group homes are
generally less integrated than independent living settings.
Private Discrimination
Private discrimination may be a significant contributing factor to fair housing issues in Orange
County. Although complaint data from local fair housing organizations was available, stakeholders
reported the persistent nature of housing discrimination, as revealed through individual complaints
and through fair housing testing.
Quality of Affordable Housing Information Programs
The quality of affordable housing information programs may be a significant contributing factor
to fair housing issues in Orange County. None of the housing authorities serving Housing Choice
Voucher holders in Orange County operate mobility counseling programs. Mobility counseling
programs that help inform voucher holders of opportunities to use their assistance in higher
opportunity areas, assist with applying for units in higher opportunity areas, and provide support
in adjusting to life in different neighborhoods have demonstrated effectiveness in helping voucher
41 Hannah Fry, Newport Will Pay Group Homes $5.25 Million Settlement, L.A. TIMES (July 16, 2015),
https://www.latimes.com/socal/daily-pilot/news/tn-dpt-me-0716-newport-group-home-settlement-20150716-
story.html.
42 Alicia Robinson, Federal Jury Sides with Costa Mesa in Sober Living Case, O.C. REGISTER (Dec. 7, 2018),
https://www.ocregister.com/2018/12/07/federal-jury-sides-with-costa-mesa-in-sober-living-case/.
43 Teri Sforza, Orange County, Following Costa Mesa’s Lead, May Regulate Sober Living Homes, O.C. REGISTER
(Sep. 20, 2019), https://www.ocregister.com/2019/09/20/orange-county-following-costa-mesas-lead-may-regulate-
sober-living-homes/.
310
holders make moves that foster integration.44 The lack of mobility counseling is not the only barrier
to voucher holders accessing higher opportunity areas, but, as the discussion of impediments to
mobility reveals, there may be some rental units available within housing authority payment
standards in higher opportunity areas, but the availability would be greater if housing authorities
implemented Small Area Fair Market Rents.
Regulatory Barriers to Providing Housing and Supportive Services for Persons with Disabilities
Regulatory barriers to providing housing and supportive services for persons with disabilities are
not a significant contributing factor to fair housing issues for persons with disabilities in Orange
County. The amount of affordable housing available (and its cost), the extent of outreach and
capacity among service providers, and the scope of service provision may be the major causes of
segregation for persons with disabilities. To the extent that barriers are regulatory in nature, they
typically overlap with the zoning and land use barriers to the construction of affordable housing.
This Analysis discusses those in detail in the analysis of the land use and zoning laws contributing
factor. This Analysis also discusses restrictions on group homes and community residences in
connection with the occupancy codes and restrictions contributing factor.
Siting Selection Policies, Practices, and Decisions for Publicly Supported Housing, Including
Discretionary Aspects of Qualified Allocation Plans and Other Programs
Siting selection policies, practices, and decisions for public supported housing, including
discretionary aspects of Qualified Allocation Plans and other programs may be a signif icant
contributing factor to fair housing issues. The main policy-driven factor related to the siting of
publicly supported housing is the heavy focus of affordable housing development efforts
throughout the state on transit-oriented development. Access to transportation is very uneven
throughout the county, and disproportionately White areas, which tend to have more proficient
schools and better environmental health, tend to have limited access to transportation. When real
affordability is built into transit-oriented development, these investments may have a positive
effect on stable integration in areas undergoing gentrification by arresting the process of
displacement. Additionally, transit expansion to higher opportunity areas may also help ensure that
prioritizing transit-oriented development contributes to integration.
The California Tax Credit Allocation Committee’s Qualified Allocation Plan (QAP) incentivizes
family-occupancy Low Income Housing Tax Credit (LIHTC) development in what it terms “High
Resource” or “Highest Resource” areas. As the map below illustrates, these areas are generally
high opportunity areas that are disproportionately white. LIHTC development in these areas would
contribute to greater residential racial integration. Developers have reported that the incentives to
build affordable housing in these areas may not be sufficient to overcome differences in land costs
between higher opportunity areas and historically disinvested areas. Nonetheless, in light of the
incentives for LIHTC development in High Resource and Highest Resource areas, the QAP does
not currently contribute to segregation. Other policy interventions, such as the donation of public
land and land held by charitable organizations, are necessary to ensure the efficacy of existing
incentives. As an additional note, the QAP includes a set-aside pool for Orange County of 7.3%,
which is slightly less than its share in the population of the state (8.1%).
44 Mary K. Cunningham et al., Moving to Better Neighborhoods with Mobility Counseling, URBAN INSTITUTE (Mar.
2005), https://www.urban.org/sites/default/files/publication/51506/311146 -Moving-to-Better-Neighborhoods-with-
Mobility-Counseling.PDF.
311
Source of Income Discrimination
Source of income discrimination may be a significant contributing factor to fair housing issues in
Orange County. In October of 2019, Governor Newsom signed into law SB 329, which prohibits
discrimination in housing based on use of a Housing Choice Voucher or other tenant-based rental
assistance. Previously, no protections for voucher holders had existed in Orange County. News
reports have indicated a high degree of difficulty in accessing housing that would accept a subsidy
in Orange County.45 Specifically, if a voucher holder does not access housing within a four month
window, they lose their voucher to the next person on the waiting list. Within the Orange County
Housing Authority as well as the Garden Grove Housing Authority, the rate of voucher loss was
22% in 2016. In Anaheim, the rate of voucher loss was 33%, and in Santa Ana it was a whopping
64%. Additionally, the vacancy rate in Orange County is only about 4%, with rent rising at a rate
of about 3% a year; even without source of income discrimination, it is nevertheless a difficult
market in which to use a voucher. As the source of income discrimination law has just been passed,
it is difficult to say whether (now) illegal discrimination will continue in Orange County. A
comprehensive landlord education campaign could help avert this, as well as comprehensive
voucher counseling to help voucher holders navigate this difficult market.
State of Local Laws, Policies, or Practices That Discourage Individuals with Disabilities from
Living in Apartments, Family Homes, Supportive Housing, and Other Integrated Settings
State or local laws, policies, or practices that discourage individuals with disabilities from living
in apartments, family homes, supportive housing, and other integrated settings are not a significant
contributing factor to fair housing issues in Orange County. A severe shortage of available,
integrated affordable housing is the primary driver of the segregation of persons with disabilities,
rather than laws, policies, or practices that discourage persons with disabilities from l iving in
integrated housing. This Analysis discusses restrictions on group homes and community
residences in connection with the occupancy codes and restrictions contributing factor.
45 Jeff Collins, No Voucher, No Vacancy, No Help: The Cruel Realities of Section 8 Housing in Orange County ,
O.C. REGISTER (Oct. 5, 2016), https://www.ocregister.com/2016/10/05/no-voucher-no-vacancy-no-help-the-cruel-
realities-of-section-8-housing-in-orange-county/.
312
Unresolved Violations of Fair Housing or Civil Rights Law
Unresolved violations of fair housing or civil rights law are not a significant contributing factor to
fair housing issues in Orange County. Although concerning, the only unresolved violations or
substantial allegations uncovered through this Analysis related to subject matter that is not closely
related to fair housing issues.
313
VIII. PUBLICLY SUPPORTED HOUSING APPENDIX
Table 1: Publicly Supported Housing Demographics and Surrounding Census Tract
Demographics, Orange County
Program
Type
Project
Name
Low
Income
Units vs.
Units in
Project
Propert
y
White
(%)
Proper
ty
Black
(%)
Proper
ty
Hispan
ic (%)
Propert
y
Asian
(%)
Households
with
children in
the
development
OR
Developmen
t Type
Censu
s
Tract
Numb
er
Tract
White
%
Tract
Black
(%)
Tract
Hispan
ic (%)
Tract
Asian
(%)
Censu
s Tract
Povert
y Rate
Project-
Based
Section
8
Laurel
Park
Manor 70 22% N/a 4% 74% N/a
1101.
13 49.1% 2.5% 18.7%
22.1
% 5.6%
Project-
Based
Section
8
Villa La
Jolla 55 36% 2% 36% 26% 45%
0117.
20 4.5% 2% 89.2% 3.2% 29.1%
Project-
Based
Section
8
Vista
Aliso 70 88% N/a 6% 4% N/a
0626.
32 81.6% 0.2% 8.9% 3.9% 4.1%
Project-
Based
Section
8
Rancho
Moulton 51 27% 8% 45% 20% 34%
0626.
25 52.4% 0% 34%
11.1
% 17.9%
Project-
Based
Section
8
Rancho
Niguel 51 14% 4% 58% 18% 26%
0626.
25 52.4% 0% 34%
11.1
% 17.9%
Project-
Based
Section
8
Cypress
Sunrise 74 30% N/a 4% 66% N/a
1101.
04 36.7% 2% 20% 38% 8.5%
Project-
Based
Section
8
Imperial
Villas 58 61% 6% 24% 9% 30%
0117.
17 54.3% 1.6% 20.4%
20.1
% 3.5%
Other
Multifa
mily
Hagan
Place 24 92% N/a 8% N/a N/a
626.0
5 84.2% 1.8% 8.7% 4.8% 10.6%
Other
Multifa
mily
Stanton
Accessibl
e 9 N/a N/a N/a N/a N/a
878.0
1 25.3% 1.8% 45.4%
24.9
% 11.7%
LIHTC
Stonegat
e II 25 26 0.00% 6.52%
21.74
% 0.00%
Large
Family
878.0
5 16.1% 4.0% 55.7%
22.9
% 16.2%
LIHTC
Birch
Hills
Apartme
nts 114
11
5
22.82
% 5.63%
62.82
%
13.80
%
Large
Family
218.1
4 47.7% 1.2% 24.3%
22.3
% 4.4%
LIHTC
Bonterra
Apartme
nts
Homes 93 94
26.13
% 5.23%
40.07
% 6.97%
Large
Family
218.1
5 42.7% 3.0% 17.9%
31.8
% 2.6%
LIHTC
Imperial
Park
Apartme
nts 91 92
10.95
% 1.09%
31.75
% 0.36%
Non
Targeted 15.03 48.5% 0.8% 35.8%
11.4
% 15.4%
LIHTC
Vintage
Canyon
Sr.
Apartme
nts 104
10
5
64.41
% 3.39%
16.95
%
17.80
% Senior 15.06 48.3% 0.0% 23.6%
25.5
% 12.2%
LIHTC
Walnut
Village 46 46 6.76% 2.03%
33.78
% 0.00%
Large
Family 15.03 48.5% 0.8% 35.8%
11.4
% 15.4%
314
Apartme
nts
LIHTC
Tara
Village
Apartme
nts
168
17
0
12.85
% 4.80% 8.05%
73.53
%
Large
Family
1101.
04
36.7% 2.0% 20.0%
38.8
% 8.5%
LIHTC
Glenneyr
e
Apartme
nts 26 27
84.62
% 3.85%
11.54
% 7.69% SRO
626.0
5 84.2% 1.8% 8.7% 4.9% 10.6%
LIHTC
Jackson
Aisle
Apartme
nts 29 30
76.67
%
10.00
%
16.67
% 6.67%
Special
Needs
997.0
2 21.2% 0.9% 23.8%
51.1
% 21.2%
LIHTC
Park
Stanton
Seniors
Apts 335
33
5
31.19
% 5.31% 9.29%
13.50
% Senior
881.0
1 27.8% 5.7% 43.1%
20.7
% 10.9%
LIHTC
Plaza
Court 102
10
3 4.64% 0.55%
67.49
% 1.09%
Large
Family
879.0
1 16.3% 1.5% 41.4%
39.6
% 21.7%
LIHTC
Continen
tal
Gardens
Apartme
nts 297
29
7 0.00% 0.00% 2.37%
32.69
%
Non
Targeted
878.0
3 7.9% 0.8% 65.3%
23.0
% 33.3%
LIHTC
Oakcrest
Heights
(Savi
Ranch II) 53 54
Large
Family
219.2
4 45.2% 4.3% 22.4%
23.1
% 5.8%
LIHTC
Oakcrest
Terrace 68 69
60.61
% 3.03%
51.52
% 2.02%
Large
Family
219.2
4 45.2% 4.3% 22.4%
23.1
% 5.8%
LIHTC
Parkwoo
d
Apartme
nts 100
10
1 0.00% 0.00% 0.00% 0.00% Senior
218.0
9 68.8% 1.0% 15.0% 9.1% 2.9%
LIHTC
Villa
Plumosa 75 76
55.10
% 0.00%
58.50
% 0.68%
Large
Family
218.0
2 60.8% 0.3% 28.0% 8.1% 9.5%
LIHTC
Vintage
at
Stonehav
en
Apartme
nts 124
12
5
57.24
% 1.97% 9.21% 7.89% Seniors
218.2
5 65.1% 0.3% 16.2%
16.3
% 4.2%
LIHTC
Yorba
Linda
Palms
Apartme
nts 43 44
31.58
% 9.21%
33.55
% 5.92%
Large
Family
218.0
2 60.8% 0.3% 28.0% 8.1% 9.5%
LIHTC
Sendero
Bluffs 106
10
7
58.91
% 1.55%
14.73
% 6.20% Seniors
320.5
6 61.8% 1.4% 17.8%
12.6
% 4.2%
LIHTC
Esencia
Norte
Apartme
nts 111
11
2
50.82
% 6.01%
53.28
% 4.10%
Large
Family
320.5
6 61.8% 1.4% 17.8%
12.6
% 4.2%
315
Table 2: Aliso Viejo
Progra
m Type
Project
Name
Low
Income
Units
vs.
Units in
Project
Propert
y
White
(%)
Propert
y Black
(%)
Propert
y
Hispani
c (%)
Propert
y Asian
(%)
Households
with
children in
the
developme
nt OR
Developme
nt Type
Census
Tract
Numbe
r
Tract
White
%
Tract
Black
(%)
Tract
Hispan
ic (%)
Tract
Asian
(%)
Cens
us
Tract
Pover
ty
Rate
LIHTC
Woodpark
Apartment
s
12
8
12
8 75.39% 6.94% 28.71% 4.73%
Large
Family 626.39 62.9% 4.3% 11.7% 14.4% 4.0%
Table 3: Anaheim
Program
Type
Project
Name
Low
Income
Units vs.
Units in
Project
Propert
y
White
(%)
Property
Black
(%)
Proper
ty
Hispa
nic
(%)
Propert
y Asian
(%)
Households
with
children in
the
developme
nt OR
Developme
nt Type
Census
Tract
Numbe
r
Tract
White
%
Tract
Black
(%)
Tract
Hispa
nic
(%)
Tract
Asian
(%)
Cens
us
Tract
Pove
rty
Rate
Project-
Based
Section
8
Village
Center
Apts 100 11% N/a 8% 81% N/a
0873.0
0 16.2% 0.8% 69.1%
11.7
%
19.7
%
Project-
Based
Section
8
Westchest
er
Housing 64 16% 25% 48% 11% 49%
0869.0
1 17.3% 6.1% 50.4%
24.6
%
26.4
%
Project-
Based
Section
8
Anaheim
Memorial
Manor 75 19% 1% 5% 73% N/a
0873.0
0 16.2% 0.8% 69.1%
11.7
%
19.7
%
Project-
Based
Section
8
Carbon
Creek
Shores 40 66% 11% 24% N/a 14% 864.07 18.9% 1.3% 63.7% 9.8%
15.7
%
LIHTC
Anton
Monaco
Apartment
s
22
9
23
2 26.39% 9.99%
50.21
% 9.13%
Non-
Targeted 871.02 16.8% 4.3% 62.1%
13.6
%
17.9
%
LIHTC
Arbor
View
Apartment
s 45 46 56.07% 4.62%
65.32
% 2.89%
Large
Family 870.02 24.9% 3.0% 48.9%
21.5
%
13.5
%
LIHTC
Avenida
Villas 28 29 41.67% 19.44%
13.89
% 11.11%
Special
Needs 877.01 19.8% 1.4% 57.4%
18.3
%
12.4
%
LIHTC
Avon
Dakota
Phase I 15 16 28.33% 3.33%
90.00
% 0.00%
Large
Family 874.04 4.1% 1.0% 91.5% 3.5%
24.9
%
LIHTC
Belage
Manor
Apartment
s
17
7
18
0 32.88% 7.66%
23.87
% 22.97% Senior 871.05 25.8% 0.5% 40.8%
24.7
%
21.7
%
LIHTC
Broadway
Village 45 46 79.40% 0.00%
95.98
% 0.00%
Large
Family 863.01 17.2% 1.2% 69.7%
11.2
%
15.7
%
LIHTC
Calendula
Court 31 32 24.04% 16.35%
36.54
% 11.54%
Large
Family 870.02 24.9% 3.0% 48.9%
21.5
%
13.5
%
LIHTC
California
Villas 33 34 31.11% 2.22%
26.67
% 35.56% Senior 870.02 24.9% 3.0% 48.9%
21.5
%
13.5
%
LIHTC
Casa
Alegre 22 23 41.38% 10.34%
31.03
% 10.34%
Special
Needs 870.01 17.8% 9.5% 51.9%
18.7
%
18.8
%
LIHTC
Cerritos
Avenue 59 60 16.48% 6.25%
13.07
% 2.84%
Large
Family 877.03 22.3% 1.9% 40.9%
29.7
%
16.9
%
316
Apartment
s
LIHTC
Cornersto
ne 48 49 2.41% 1.20% 9.64% 0.00%
Large
Family 877.01 19.8% 1.4% 57.4%
18.3
%
12.4
%
LIHTC
Diamond
Aisle
Apartment
s 24 25 54.84% 12.90%
19.35
% 6.45%
Special
Needs 872 22.6% 4.4% 61.7% 9.6%
15.9
%
LIHTC
Elm Street
Commons 51 52 68.69% 4.55%
77.78
% 2.02%
Large
Family 873 16.2% 0.8% 69.1%
11.8
%
19.7
%
LIHTC
Greenleaf
Apartment
s 19 20 55.56% 11.11%
55.56
% 4.76%
Large
Family 867.02 13.6% 2.5% 68.5%
11.9
%
23.1
%
LIHTC
Hermosa
Village
aka
Jeffrey-
Lynne
Perimeter
Re
11
1
11
8 18.40% 5.10%
72.28
% 3.55%
Large
Family 875.05 15.9% 1.1% 63.8%
15.2
%
24.3
%
LIHTC
Jeffrey
Lynne
Neighborh
ood
Revitalizat
ion Phase
IV 36 36 22.96% 8.89%
86.67
% 1.48%
Large
Family 875.05 15.9% 1.1% 63.8%
15.2
%
24.3
%
LIHTC
Jeffrey-
Lynne
Apartment
s Phase I
19
2
20
0 9.51% 7.61%
74.46
% 2.58%
Large
Family 875.05 15.9% 1.1% 63.8%
15.2
%
24.3
%
LIHTC
Jeffrey-
Lynne
Neighborh
ood
Revitalizat
ion Phase
3 76 85 11.90% 13.49%
64.29
% 10.71%
Large
Family 875.05 15.9% 1.1% 63.8%
15.2
%
24.3
%
LIHTC
Jeffrey-
Lynne
Neighborh
ood
Revitalizat
ion
PhaseII 99
10
0 20.67% 3.35%
73.46
% 6.15%
Large
Family 875.05 15.9% 1.1% 63.8%
15.2
%
24.3
%
LIHTC
Linbrook
Court 80 81 17.39% 0.00% 0.00% 78.26% Senior 871.01 25.4% 5.3% 40.1%
26.1
%
11.0
%
LIHTC
Lincoln
Anaheim
Phase I 71 72 31.29% 4.68%
35.97
% 9.71%
Large
Family 873 16.2% 0.8% 69.1%
11.8
%
19.7
%
LIHTC
Lincoln
Anaheim
Phase II 73 74 41.44% 4.79%
59.93
% 6.51%
Large
Family 873 16.2% 0.8% 69.1%
11.8
%
19.7
%
LIHTC
Magnolia
Acres 40 40 90.00% 0.00%
10.00
% 10.00% Senior 870.01 17.8% 9.5% 51.9%
18.7
%
18.8
%
LIHTC
Monarch
Pointe
Apartment
Homes 62 63 62.76% 7.14%
72.96
% 5.10%
Large
Family 867.02 13.6% 2.5% 68.5%
11.9
%
23.1
%
LIHTC
Palm West
Apartment
s 57 58 22.82% 7.38%
33.56
% 14.09%
Non-
Targeted
1102.0
2 28.5% 3.8% 37.6%
26.0
%
24.2
%
LIHTC
Park Vista
Apartment
s
39
0
39
2 2.95% 1.82%
63.14
% 1.13%
Non-
Targeted 866.01 6.8% 3.4% 82.5% 5.8%
26.0
%
LIHTC
Paseo
Village
Family
17
4
17
4 2.82% 7.13%
82.92
% 2.82%
Large
Family 866.01 6.8% 3.4% 82.5% 5.8%
26.0
%
317
Apartment
s
LIHTC
Pebble
Cove
11
0
11
1 31.58% 6.58%
37.28
% 14.91%
Non-
Targeted 878.06 18.7% 2.0% 56.6%
17.5
%
17.2
%
LIHTC
Renaissaa
nce Park
Apartment
s aka
Monterey
Apts.
12
4
12
6 8.27% 8.27%
24.41
% 3.94%
Non-
Targeted 869.01 17.3% 6.1% 50.4%
24.6
%
26.4
%
LIHTC
Rockwood
Apartment
s 51.43% 9.80%
54.29
% 4.49%
LIHTC
Solara
Court
13
1
13
2 14.86% 0.57%
11.43
% 76.00% Senior
1102.0
1 26.7% 4.1% 27.3%
38.3
%
17.3
%
LIHTC
South
Street
Anaheim
Housing
Partners
LP 91 92 30.47% 5.26%
40.72
% 14.68%
Large
Family 874.01 20.5% 1.1% 53.7%
21.6
%
8.7
%
LIHTC Stonegate 37 38 9.87% 4.61% 9.87% 1.32%
Large
Family 878.06 18.7% 2.0% 56.6%
17.5
%
17.2
%
LIHTC
The
Crossings
at Cherry
Orchard 44 44 4.46% 0.00% 8.28% 1.27%
Large
Family
1102.0
1 26.7% 4.1% 27.3%
38.3
%
17.3
%
LIHTC
The
Vineyard
Townhom
es 50.00% 14.29%
85.71
% 0.00% 873.00 16.2% 0.8% 69.1%
11.7
%
19.7
%
LIHTC
Tyrol
Plaza
Senior
Apartment
s 59 60 71.62% 6.76%
27.03
% 13.51% Senior 863.01 17.2% 1.2% 69.7%
11.2
%
15.7
%
LIHTC
Villa
Anaheim
13
4
13
5 26.44% 0.57%
18.97
% 37.36% Senior
1102.0
1 26.7% 4.1% 27.3%
38.3
%
17.3
%
Table 4: Buena Park
Program
Type
Project
Name
Low
Income
Units vs.
Units in
Project
Propert
y
White
(%)
Propert
y Black
(%)
Propert
y
Hispan
ic (%)
Propert
y Asian
(%)
Households
with
children in
the
developme
nt OR
Developme
nt Type
Censu
s
Tract
Numb
er
Tract
White
%
Tract
Black
(%)
Tract
Hispan
ic (%)
Trac
t
Asia
n
(%)
Censu
s
Tract
Pover
ty
Rate
Project-
Based
Section
8
Newport
House 10 73% 7% 13% 7% N/a
1103.
03 36.1% 0.8% 40.2%
18.2
% 5.2%
Project-
Based
Section
8
Casa
Santa
Maria 100 6% N/a 3% 91% N/a
1105.
00 15.2% 5.9% 54.9%
20.7
%
25.5
%
LIHTC
City Yard
Workforce
Housing 8.05% 15.44% 24.16% 35.57%
LIHTC
Dorado
Senior
Apartment
s
32.65
% 2.04% 15.31% 53.06%
868.0
3 25.2% 1.3% 44.9%
26.0
%
17.6
%
LIHTC
Emerald
Gardens
Apartment
s
18.21
% 10.49% 42.28% 7.10%
1102.
01 26.7% 4.1% 27.3%
38.3
%
17.3
%
318
LIHTC
Harmony
Park
Apartment
s
12.00
% 4.00% 6.67% 61.33%
1105.
00 15.2% 5.9% 54.9%
20.7
%
25.5
%
LIHTC
Park
Landing
Apartment
s
42.33
% 18.60% 40.93% 22.33%
868.0
1 29.3% 3.7% 40.7%
25.0
% 5.3%
LIHTC
Walden
Glen
Apartment
s
18
5 186
14.81
% 8.83% 22.22% 9.12%
Non-
targeted 1105 15.2% 5.9% 54.9%
20.7
%
25.5
%
Table 5: Costa Mesa
Progra
m Type
Project
Name
Low
Income
Units
vs.
Units in
Project
Propert
y
White
(%)
Propert
y Black
(%)
Propert
y
Hispani
c (%)
Propert
y Asian
(%)
Households
with
children in
the
developme
nt OR
Developme
nt Type
Census
Tract
Numbe
r
Tract
White
%
Tract
Black
(%)
Tract
Hispan
ic (%)
Tract
Asian
(%)
Censu
s
Tract
Pover
ty
Rate
Project
-Based
Section
8 Casa Bella 74 68% 1% 17% 14% N/a
0637.0
2 35.1% 0.7% 56.5% 4.7% 17%
Project
-Based
Section
8
St. Johns
Manor 36 77% N/a 9% 14% N/a
0632.0
2 35.1% 0.7% 56.5% 4.7% 17%
LIHTC
Tower on
19th
26
6
26
9 52.73% 2.12% 10.30% 17.58% Seniors 637.01 17.4% 0.8% 78.4% 2.5% 31.7%
Table 6: Fountain Valley
Program
Type
Project
Name
Low
Income
Units vs.
Units in
Project
Property
White
(%)
Propert
y Black
(%)
Proper
ty
Hispan
ic (%)
Propert
y
Asian
(%)
Households
with
children in
the
developme
nt OR
Developme
nt Type
Censu
s
Tract
Numb
er
Tract
White
%
Trac
t
Blac
k
(%)
Tract
Hispani
c (%)
Trac
t
Asia
n
(%)
Censu
s
Tract
Povert
y Rate
Project-
Based
Section 8
Our Lady
of
Guadalup
e 71 15% N/a 1% 84% N/a
0992.
33 51.4% 0% 10.7%
37.1
% 4.4%
LIHTC
Fountain
Valley
Senior
The
Jasmine
15
4
156 49.00% 0.50%
12.00
% 46.00% Senior
992.5
0
39.5% 1.2% 28.5%
28.6
%
16.6%
Table 7: Fullerton
Program
Type
Project
Name
Low
Income
Units vs.
Units in
Project
Propert
y
White
(%)
Propert
y Black
(%)
Propert
y
Hispan
ic (%)
Propert
y Asian
(%)
Households
with
children in
the
developmen
t OR
Developmen
t Type
Censu
s
Tract
Numb
er
Tract
White
%
Trac
t
Blac
k
(%)
Tract
Hispan
ic (%)
Trac
t
Asia
n
(%)
Censu
s
Tract
Povert
y Rate
Project-
Based
Section 8
Amerige
Villa
Apts 101 9% N/a 1% 90% N/a
0112.
00 50.6%
1.4
% 34.4%
9.8
% 15.8%
319
Other
Multifamil
y
Casa
Maria
Del Rio 24 73% N/a 23% 4% N/a
0115.
02 30%
1.8
% 46.1% 19% 16.7%
Other
Multifamil
y
Harbor
View
Terrace 24 71% 13% 8% 8% 4%
0017.
06 50.1%
0.2
% 10.1%
34.8
% 8.9%
LIHTC
Courtya
rd
Apartme
nts
10
8 108 64.43% 3.08% 60.78% 26.89%
Large
Family 112 50.6%
1.4
% 34.4%
9.8
% 15.8%
LIHTC
East
Fullerto
n Villas 26 27 10.64% 2.13% 82.98% 6.38%
Large
Family
115.0
2 30%
1.8
% 46.1% 19% 16.7%
LIHTC
Fullerto
n City
Lights
Resident
ial Hotel
13
4 137 63.19% 9.03% 13.89% 4.17% SRO 113 58.7%
4.3
% 19.3%
11.1
% 12.0%
LIHTC
Fullerto
n
Family
Housing 54 55 30.61%
15.65
% 60.54% 12.93%
Large
Family 113 58.7%
4.3
% 19.3%
11.1
% 12.0%
LIHTC
Fullerto
n
Heights 35 36 43.18% 9.09% 39.77% 12.50%
Special
Needs 1162
LIHTC
Garnet
Lane
Apartme
nts 17 18 2.60% 0.00% 61.04% 0.00%
Large
Family
117.1
1 30.6%
3.6
% 43.7%
20.2
% 11.7%
LIHTC
Klimpel
Manor 58 59 48.00% 2.00% 22.00% 32.00% Senior 113 58.7%
4.3
% 19.3%
11.1
% 12.0%
LIHTC
North
Hills
Apartme
nts
20
3 204 54.76% 1.57% 67.91% 0.60%
Non-
Targeted 16.01 44.8%
2.3
% 23.3%
26.6
% 9.2%
LIHTC
Palm
Garden
Apartme
nts
22
3 224 0.28% 0.00% 20.51% 0.14%
Non-
Targeted
116.0
1 9.4%
5.3
% 75.1%
9.5
% 30.1%
LIHTC
Ventana
Senior
Apartme
nts 18.25% 4.76% 4.76% 29.37% Senior
Table 8: Garden Grove
Progra
m Type
Project
Name
Low
Income
Units vs.
Units in
Project
Property
White
(%)
Propert
y Black
(%)
Propert
y
Hispani
c (%)
Proper
ty
Asian
(%)
Households
with
children in
the
developmen
t OR
Developmen
t Type
Censu
s
Tract
Numb
er
Tract
White
%
Tract
Black
(%)
Tract
Hispan
ic (%)
Trac
t
Asia
n
(%)
Censu
s
Tract
Povert
y Rate
Project
-Based
Section
8
Donald
Jordan
Senior
Manor 65 8% 2% 2% 89% N/a
0886.
02 19.7% 1.1% 35.6%
39.1
% 12.4%
Project
-Based
Section
8
Acacia
Villa Apts 160 4% 1% 1% 94% N/a
0886.
01 18.7% 1.4% 30.2%
47.8
% 12.5%
LIHTC
Briar
Crest+
Rosecrest
Apartments 40 41 53.78% 0.00% 89.92% 0.84%
Large
Family
885.0
1 14.6% 0.8% 54.4%
28.8
% 16.6%
LIHTC
Garden
Grove 84 85 13.79% 0.86% 6.90%
74.14
% Senior
885.0
2 12.0% 0.7% 47.0%
36.8
% 21.1%
320
Senior
Apartments
LIHTC
Grove Park
Apartments
10
3
10
4 3.30% 6.60% 33.02%
55.66
% At-Risk
891.0
4 2.2% 0.2% 79.8%
17.5
% 22.7%
LIHTC
Malabar
Apartments
12
5
12
5 12.90% 2.30% 26.04% 3.00%
Large
Family
882.0
3 25.3% 0.6% 30.4%
37.2
% 18.6%
LIHTC
Stuart
Drive Apts.
Rose
Garden
Apts.
23
9
23
9 2.16% 0.00% 16.19%
39.41
%
Non-
Targeted
885.0
1 14.6% 0.8% 54.4%
28.8
% 16.6%
LIHTC
Sungrove
Sr. Apts 80 82 33.00% 4.00% 13.00%
42.00
% Senior
885.0
2 12.0% 0.7% 47.0%
36.8
% 21.1%
Table 9: Huntington Beach
Program
Type
Project
Name
Low
Income
Units vs.
Units in
Project
Property
White
(%)
Propert
y Black
(%)
Propert
y
Hispan
ic (%)
Proper
ty
Asian
(%)
Households
with
children in
the
developmen
t OR
Developme
nt Type
Census
Tract
Number
Tract
White
%
Trac
t
Blac
k
(%)
Tract
Hispan
ic (%)
Tract
Asian
(%)
Cens
us
Tract
Pover
ty
Rate
Project-
Based
Section
8
Huntingt
on
Gardens 185 60% 2% 5% 33% N/a 0994.13 64.3%
0.2
% 17.5%
16.5
%
12.9
%
Project-
Based
Section
8
Huntingt
on Villa
Yorba 192 20% 1% 17% 63% 12% 0992.41 43.9% 3% 21%
27.1
% 9.5%
LIHTC
Beachvie
w Villa
10
6 107 39.05% 5.71% 18.10% 3.81% SRO 992.35 66.7%
2.2
% 20.5% 8.5%
12.4
%
LIHTC
Bowen
Court 20 20 60.87% 0.00% 17.39%
26.09
% Senior 993.05 57.1%
0.7
% 30.1% 5.4% 7.3%
LIHTC
Emerald
Cove
Senior
Apartme
nts
16
2 164 20.71% 1.78% 0.59% 0.00% Senior 994.13 64.3%
0.2
% 17.5%
16.5
%
12.9
%
LIHTC
Hermosa
Vista
Apartme
nts 87 88 50.71% 1.90% 62.56% 7.58%
Non
Targeted 996.05 57.6%
0.0
% 20.7%
16.7
% 5.2%
LIHTC
Oceana
Apartme
nts 77 78 52.63% 14.04% 39.04% 1.32%
Large
Family 994.13 64.3%
0.2
% 17.5%
16.5
%
12.9
%
LIHTC
Pacific
Court
Apartme
nts 47 48 88.96% 0.00% 48.05% 0.65%
Large
Family 993.05 57.1%
0.7
% 30.1% 5.4% 7.3%
LIHTC
Pacific
Sun
Apartme
nts 6 6 34.78% 0.00% 13.04% 0.00%
Special
Needs 994.02 20.0%
0.4
% 68.3% 6.6%
35.4
%
LIHTC
Quo
Vadis
Apartme
nts
10
2 104 69.01% 2.92% 19.88% 8.77%
Non
Targeted 994.13 64.3%
0.2
% 17.5%
16.5
%
12.9
%
321
Table 10: Irvine
Program
Type
Project
Name
Low
Income
Units vs.
Units in
Project
Proper
ty
White
(%)
Propert
y Black
(%)
Propert
y
Hispani
c (%)
Propert
y Asian
(%)
Households
with
children in
the
developmen
t OR
Developmen
t Type
Censu
s
Tract
Numb
er
Tract
White
%
Tract
Blac
k (%)
Tract
Hispa
nic
(%)
Tract
Asian
(%)
Censu
s
Tract
Pover
ty
Rate
Project-
Based
Section 8
Woodbri
dge
Manor I,
Ii & Iii 165 64% N/a 1% 34% N/a
0525.
11 54.7% 1.9% 6.4% 30.3% 6.2%
Project-
Based
Section 8
Access
Irvine,
Inc.(aka
Skyloft) 39 64% 8% 5% 23% N/a
0626.
11 35.3% 6.8% 9.9%
43.9
%
34.7
%
Project-
Based
Section 8
The
Parkland
s 120 41% 4% 8% 48% 25%
0525.
25 31.3% 1.9% 9.6%
49.9
% 9.7%
Project-
Based
Section 8
Windwo
od Knoll 60 49% 10% 11% 30% 14%
0525.
27 37.1% 5.6% 7.5%
42.1
% 8.5%
Project-
Based
Section 8
Woodbri
dge Oaks 120 68% 1% 6% 25% 21%
0525.
14 50.9% 0.2%
13.8
%
31.7
% 8.9%
Project-
Based
Section 8
Woodbri
dge
Villas 60 73% 5% 3% 17% 18%
0525.
19 51.4% 2.5% 5.8%
33.4
%
10.8
%
Project-
Based
Section 8
Orchard
Park
Apts 59 58% 5% 10% 27% 27%
0525.
17 44.2% 5.6% 4.5%
42.2
% 9.2%
Project-
Based
Section 8
Harvard
Manor 100 60% 2% 9% 29% 17%
0626.
27 33.4% 1.9%
13.1
%
47.9
%
38.3
%
Project-
Based
Section 8
Sutton
Irvine
Residenc
es 9 100% N/a 0% N/a N/a
525.2
6 38.8% 0.9%
16.4
%
37.5
% 5.8%
Other
Multifam
ily
Villa
Hermosa
- Irvine 24 50% 25% 4% 21% 4%
0525.
27 37.1% 5.6% 7.5%
42.1
% 8.5%
LIHTC
Anesi
Apartme
nts (aka
Alegre
Apts)
10
2 104
21.52
% 7.62% 21.19% 36.42%
Large
Family
525.1
8 61.0% 1.8% 6.6%
26.8
%
11.3
%
LIHTC
Anton
Portola
Apartme
nts
25
3 256 9.04% 1.69% 3.95% 3.58%
Non-
Targeted
524.0
4 30.2% 2.9%
29.7
%
37.3
% 0.0%
LIHTC
Cadence
Family
Irvine
Housing
(aka
Luminara
) 81 82
36.06
% 3.35% 14.50% 7.43%
Large
Family
524.0
4 30.2% 2.9%
29.7
%
37.3
% 0.0%
LIHTC
D1
Senior
Irvine
Housing
(aka
Luxaira)
15
6 156
18.66
% 0.48% 4.31% 15.31% Seniors
524.0
4 30.2% 2.9% 29.7%
37.3
% 0.0%
LIHTC
Parc
Derian
Apartme
nts 79 80
67.38
% 10.73% 31.76% 10.30%
Large
Family
755.1
5 27.4% 1.1%
36.0
%
31.7
%
19.4
%
322
LIHTC
Doria
Apartme
nt Homes
Phase I 59 60
18.31
% 3.52% 12.68% 23.94%
Large
Family
524.2
6 45.10%
0.50
%
9.50
%
39.7
0% 6.1%
LIHTC
Doria
Apartme
nts
Homes
Phase II 74 74
21.84
% 1.72% 9.77% 15.52%
Large
Family
755.0
5 41.5% 2.8%
38.8
%
12.5
% 8.3%
LIHTC
Granite
Court 71 71
45.36
% 1.64% 20.22% 9.29%
Non
Targeted
755.1
5 27.4% 1.1%
36.0
%
31.7
%
19.4
%
LIHTC
Irvine
Inn
19
2 192
19.05
% 2.65% 2.65% 4.76% SRO
755.1
5 27.4% 1.1%
36.0
%
31.7
%
19.4
%
LIHTC
Laguna
Canyon
Apartme
nts
12
0 120
47.57
% 0.00% 30.10% 4.85%
Large
Family
525.1
8 61.0% 1.8% 6.6%
26.8
%
11.3
%
LIHTC
Montecit
o Vista
Apartme
nt Homes
16
1 162 9.24% 8.84% 14.86% 17.27%
Large
Family
525.2
5 31.3% 1.9% 9.6%
50.6
% 9.7%
LIHTC
Paramou
nt Family
Irvine
Housing
Partners
LP
(aka
Espaira) 83 84
21.82
% 4.89% 15.31% 5.21%
Large
Family
524.0
4 30.2% 2.9%
29.7
%
37.3
% 0.0%
LIHTC
Pavilion
Park
Senior I
Housing
Partners
LP
(aka
Solaira)
21
9 221
19.54
% 0.99% 1.99% 15.56% Seniors
524.2
6 45.1% 0.5% 9.5%
39.7
% 6.1%
LIHTC
San
Paulo
Apartme
nts
15
3 382
37.31
% 2.09% 11.94% 5.67%
Non
Targeted
525.2
1 38.3% 3.6%
20.1
%
33.8
%
15.6
%
LIHTC
Santa
Alicia
Apartme
nts 84 84
31.82
% 0.00% 10.00% 18.18%
Large
Family
525.1
5 36.9% 0.3% 9.0%
46.7
%
12.7
%
LIHTC
The
Arbor at
Woodbur
y 90 90 2.12% 6.36% 8.05% 24.15%
Large
Family
524.1
8 32.6% 3.0% 6.5%
53.8
%
14.0
%
LIHTC
The Inn
At
Woodbri
dge
12
0 120
64.05
% 1.31% 7.84% 15.03% Senior
525.2
1 38.3% 3.6%
20.1
%
33.8
%
15.6
%
LIHTC
Windrow
Apartme
nts 96 96
21.80
% 4.51% 18.80% 16.54%
Large
Family
524.1
7 37.0% 1.2% 7.5%
49.9
% 9.8%
LIHTC
Woodbur
y Walk
15
0 150
49.01
% 0.00% 12.58% 17.88%
Large
Family
524.1
8 32.6% 3.0% 6.5%
53.8
%
14.0
%
323
Table 11: La Habra
Program
Type
Project
Name
Low
Income
Units
vs.
Units in
Project
Propert
y
White
(%)
Propert
y Black
(%)
Propert
y
Hispani
c (%)
Propert
y Asian
(%)
Households
with
children in
the
developme
nt OR
Developme
nt Type
Census
Tract
Numbe
r
Tract
White
%
Tract
Black
(%)
Tract
Hispan
ic (%)
Tract
Asian
(%)
Censu
s
Tract
Pover
ty
Rate
Project-
Based
Section 8
Las
Lomas
Gardens 93 44% 1% 44% 11% 47%
0013.0
3 24.3% 1.4% 59.1%
13.6
% 9.2%
Project-
Based
Section 8
Casa El
Centro
Apts. 55 11% N/a 21% 68% N/a
0012.0
2 12.7% 0.2% 85.1% 1.8% 15.1%
Table 12: La Palma
Program
Type
Project
Name
Low
Income
Units vs.
Units in
Project
Propert
y
White
(%)
Propert
y Black
(%)
Propert
y
Hispani
c (%)
Propert
y Asian
(%)
Households
with
children in
the
developme
nt OR
Developme
nt Type
Census
Tract
Numbe
r
Tract
White
%
Tract
Black
(%)
Tract
Hispan
ic (%)
Tract
Asian
(%)
Cens
us
Tract
Pove
rty
Rate
LIHTC
Camden
Place
Apartment
s 35 35 9.30% 9.30% 9.30% 65.12% Senior
1101.1
6 24.5% 5.6% 17.6%
47.0
% 8.4%
LIHTC
Casa La
Palma
Apartment
s
26
9
26
9 15.93% 3.53% 17.29% 48.46%
Non
Targeted
1101.1
6 24.5% 5.6% 17.6%
47.0
% 8.4%
Table 13: Lake Forest
Program
Type
Project
Name
Low
Income
Units
vs.
Units in
Project
Property
White
(%)
Propert
y Black
(%)
Propert
y
Hispani
c (%)
Propert
y Asian
(%)
Households
with
children in
the
developme
nt OR
Developme
nt Type
Census
Tract
Numbe
r
Tract
White
%
Tract
Black
(%)
Tract
Hispan
ic (%)
Tract
Asia
n (%)
Censu
s
Tract
Pover
ty
Rate
LIHTC
Baker
Ranch
Affordab
le (aka
Arroyo at
Baker
Ranch)
18
7
18
9 7.45% 7.45% 36.86% 5.49%
Large
Family
524.22
55.5% 2% 20.2%
13.7
% 7%
Table 14: Laguna Niguel
Program
Type
Project
Name
Low
Income
Units vs.
Units in
Project
Propert
y
White
(%)
Propert
y Black
(%)
Propert
y
Hispani
c (%)
Propert
y Asian
(%)
Households
with
children in
the
developme
nt OR
Developme
nt Type
Census
Tract
Number
Tract
White
%
Tract
Black
(%)
Tract
Hispan
ic (%)
Tract
Asian
(%)
Cens
us
Tract
Pove
rty
Rate
Project-
Based
Section
8
Village La
Paz 100
84% 2% 7% 7% 11% 0423.34 55.5% 2% 20.2%
13.7
% 7%
324
Project-
Based
Section
8
Alicia
Park
Apartment
s 56
75% 4% 13% 8% 17% 0423.26 62% 4.7% 19.1% 8% 8.6%
Table 15: Mission Viejo
Program
Type
Project
Name
Low
Income
Units
vs.
Units in
Project
Propert
y
White
(%)
Propert
y
Black
(%)
Propert
y
Hispani
c (%)
Propert
y Asian
(%)
Household
s with
children in
the
developm
ent OR
Developm
ent Type
Census
Tract
Numbe
r
Tract
White
%
Tract
Black
(%)
Tract
Hispan
ic (%)
Tract
Asian
(%)
Census
Tract
Povert
y Rate
LIHTC
Arroyo
Vista
Apartmen
ts
15
5
15
5 64.75% 1.36% 37.97% 15.93%
Large
Family 320.22 38.9% 1.4% 47.2% 8.3% 7.5%
LIHTC
Heritage
Villas
Senior
Housing
14
1
14
3 6.37% 0.00% 0.00% 0.00%
Non
Targeted 320.13 74.5% 4.3% 10.0% 3.3% 4.8%
Table 16: Newport Beach
Program
Type
Project
Name
Low
Income
Units vs.
Units in
Project
Propert
y
White
(%)
Propert
y Black
(%)
Property
Hispani
c (%)
Property
Asian
(%)
Househ
olds
with
children
in the
develop
ment
OR
Develop
ment
Type
Census
Tract
Numbe
r
Tract
White
%
Tract
Black
(%)
Tract
Hispan
ic (%)
Tract
Asian
(%)
Censu
s
Tract
Pover
ty
Rate
Project-
Based
Section 8
Seaview
Luthera
n Plaza 100 86% N/a 4% 10% N/a 0626.44 84.4% 0% 6% 8.9% 9.2%
LIHTC
Bayvie
w
Landing
11
9 120
79.43
% 1.42% 6.38% 5.67% Senior 630.04 82.3% 2.9% 7.4% 6.6% 4.8%
LIHTC
Lange
Drive
Family 74 74
50.81
% 1.61% 55.24% 1.61%
Large
Family 740.03 20.7% 1.6% 64.9%
11.3
%
12.2
%
LIHTC
Newport
Veteran
s
Housing 12 12 0.00% 15.38% 7.69% 0.00%
Non-
Targete
d 636.03 75.8% 0.3% 15.7% 4.7% 6.1%
Table 17: Orange (City)
Program
Type
Project
Name
Low
Income
Units vs.
Units in
Project
Propert
y
White
(%)
Propert
y Black
(%)
Propert
y
Hispan
ic (%)
Propert
y Asian
(%)
Household
s with
children in
the
developme
nt OR
Developme
nt Type
Censu
s
Tract
Numb
er
Tract
Whit
e %
Tract
Black
(%)
Tract
Hispan
ic (%)
Tract
Asian
(%)
Census
Tract
Povert
y Rate
Project-
Based
Section
8
Triangle
Terrace 75 57% 3% 24% 15% N/a
0759.0
2
56.3
% 1% 37.3% 3.7% 18.3%
Project-
Based
Section
8
Casa
Ramon 75 19% N/a 77% 3% 37%
0759.0
1
51.9
% 1.4% 41.9% 2.8% 24.1%
325
Project-
Based
Section
8
Casas Del
Rio 39 89% N/a 8% N/a N/a 758.06
46.6
% 0.4% 47.6% 3.8% 15.7%
Project-
Based
Section
8
Friendly
Center 8 N/a N/a N/a N/a N/a 759.01
51.9
% 1.4% 41.9% 2.8% 24.1%
LIHTC
Buena
Vista
Apartment
s 17 17 66.18% 0.00% 64.71% 1.47%
Large
Family 762.02
52.7
% 1.0% 38.3% 7.1% 7.4%
LIHTC
Chestnut
Place
(Fairway
Manor
LP) 49 50 46.15% 1.54% 15.38% 24.62%
Large
Family 758.06
46.6
% 0.4% 47.6% 3.8% 15.7%
LIHTC
Citrus
Grove
Apartment
s 56 57 85.65% 3.59% 81.17% 0.00%
Large
Family 762.04
11.6
% 1.3% 79.6% 5.7% 23.1%
LIHTC
Communit
y Garden
Towers
33
2
33
3 2.44% 0.00% 0.44% 4.44% Senior 761.02
28.7
% 7.0% 47.1%
16.1
% 19.4%
LIHTC
Harmony
Creek
Apartment
s 83 83 39.13% 1.09% 13.04% 9.78% Senior 758.06
46.6
% 0.4% 47.6% 3.8% 15.7%
LIHTC
Orangeval
e
Apartment
s 64 64 9.76% 1.63% 82.52% 2.44%
Non
Targeted 762.05
52.0
% 0.7% 32.5%
11.0
% 14.0%
LIHTC
Serrano
Woods 62 63 83.81% 2.02% 85.02% 0.00%
Large
Family 758.11
35.2
% 0.2% 53.7% 9.6% 18.1%
LIHTC
Stonegate
Senior
Apartment
s 19 20 62.50% 4.17% 37.50% 0.00% Senior 758.16
34.7
% 1.7% 47.1%
11.0
% 17.2%
LIHTC
The
Knolls
Apartment
s aka Villa
Santiago
26
0
26
0 33.80% 2.66% 71.18% 5.90%
Non
Targeted 758.16
34.7
% 1.7% 47.1%
11.0
% 17.2%
LIHTC
Walnut-
Pixley 22 22 88.89% 1.85% 72.22% 1.85%
Large
Family 760
33.1
% 2.5% 49.9%
12.9
% 15.1%
Table 18: San Clemente
Program
Type
Project
Name
Low
Income
Units vs.
Units in
Project
Property
White
(%)
Propert
y Black
(%)
Propert
y
Hispani
c (%)
Propert
y Asian
(%)
Households
with
children in
the
developme
nt OR
Developme
nt Type
Census
Tract
Numbe
r
Tract
White
%
Tract
Black
(%)
Tract
Hispan
ic (%)
Trac
t
Asia
n
(%)
Censu
s
Tract
Povert
y Rate
Project-
Based
Section
8
Casa De
Seniors 72 78% N/a 15% 7% N/a
0421.1
3 82.8% 0.4% 15.2% 1% 9.4%
LIHTC
Cottons
Point
Senior
Apartment
s 75.82% 0.00% 7.69% 7.69%
LIHTC
Las
Palmas
Village
(aka 18 19 30.77% 0.00% 42.31% 3.85%
Large
Family 421.08 69.9% 0.0% 26.3%
1.4
% 12.1%
326
Avenida
Serra)
LIHTC
Talega
Jamboree
Apartment
s Phase I
12
3 124 48.60% 1.40% 64.02% 1.87%
Large
Family 320.23 75.5% 0.7% 11.4%
6.3
% 2.2%
LIHTC
Talega
Jamboree
Apt Ph. II
Mendocin
o at
Talega II 61 62 52.25% 2.25% 51.35% 2.70%
Large
Family 320.23 75.5% 0.7% 11.4%
6.3
% 2.2%
LIHTC
The
Presidio
(formerly
known as
Wycliffe
Casa de S 71 72 76.74% 0.00% 16.28% 10.47% Seniors 421.13 82.8% 0.4% 15.2% 1% 9.4%
LIHTC
Vintage
Shores
12
0 122 91.24% 1.46% 8.76% 2.19% Senior 422.06 79.5% 2.8% 14.3%
1.9
% 4.2%
Table 19: San Juan Capistrano
Program
Type
Project
Name
Low
Income
Units vs.
Units in
Project
Property
White
(%)
Propert
y Black
(%)
Propert
y
Hispani
c (%)
Property
Asian
(%)
Househol
ds with
children
in the
developm
ent OR
Develop
ment
Type
Censu
s Tract
Numb
er
Tract
White
%
Tract
Blac
k (%)
Tract
Hispani
c (%)
Tract
Asian
(%)
Censu
s
Tract
Pover
ty
Rate
LIHTC
Seasons
Senior
Apartme
nts at
San Juan
Capistra
no
11
2
11
2 78.99% 1.45% 10.87% 2.17% Senior
423.1
2 25.2% 0.0% 68.0% 3.0%
19.4
%
LIHTC
Villa
Paloma
Senior
Apartme
nts 66 84 85.14% 0.00% 16.22% 2.70% Senior
423.1
2 25.2% 0.0% 68.0% 3.0%
19.4
%
LIHTC
Seasons
II Senior
Apartme
nts 37 38 83.33% 2.38% 7.14% 0.00% Senior
423.1
2 25.2% 0.0% 68.0% 3.0%
19.4
%
Table 20: Santa Ana
Program
Type
Project
Name
Low
Income
Units vs.
Units in
Project
Property
White
(%)
Propert
y Black
(%)
Propert
y
Hispani
c (%)
Prope
rty
Asian
(%)
Households
with
children in
the
developmen
t OR
Developmen
t Type
Censu
s
Tract
Numb
er
Tract
White
%
Tract
Black
(%)
Tract
Hispan
ic (%)
Tract
Asian
(%)
Census
Tract
Povert
y Rate
Project-
Based
Section 8
Flower
Terrace 140 7% 1% 13% 78% N/a
0751.
00 17.3% 1.2% 77% 3.7% 23.8%
Project-
Based
Section 8
Flower
Park
Plaza 199 3% 1% 14% 59% N/a
0749.
01 0.9% 0% 94.7% 4.3% 25.8%
Project-
Based
Section 8
Highland
Manor
Apts. 12 18% N/a 82% N/a 36%
749.0
2 2.9% 0.1% 95.8% 1.3% 26.9%
327
Project-
Based
Section 8
Rosswoo
d Villa 198 3% 1% 33% 62% N/a
0750.
02 6% 0.3% 86.5% 5.8% 37.8%
Project-
Based
Section 8
Santa
Ana
Towers 198 4% 2% 24% 69% N/a
0750.
02 6% 0.3% 86.5% 5.8% 37.8%
Project-
Based
Section 8
Sullivan
Manor 54 33% N/a 52% 15% 49%
0748.
02 1.6% 0.5% 88.1% 9.3% 25.5%
LIHTC
Andaluci
a
Apartme
nts (aka
815 N.
Harbor) 56 70 70.00% 2.35% 85.00% 2.65%
Large
Family
891.0
5 1.7% 0.0% 89.1% 9.2% 27.0%
LIHTC
City
Gardens
Apartme
nts
27
4 274 7.24% 0.30% 84.77% 1.36%
Non
Targeted
753.0
1 21.1% 1.5% 66.6% 9.5% 16.6%
LIHTC
Depot at
Santiago
Apartme
nts 69 70 89.80% 0.78% 91.37% 1.57%
Large
Family
744.0
5 5.3% 1.3% 89.8% 2.8% 20.8%
LIHTC
Guest
House 71 72 1.22% 10.98% 30.49% 1.22%
Special
Needs
749.0
1 0.9% 0.0% 94.7% 4.3% 25.8%
LIHTC
Heninger
Village
Apartme
nts 57 58 17.33% 5.33% 45.33%
37.33
% Senior
750.0
2 6.0% 0.3% 86.5% 5.9% 37.8%
LIHTC
La Gema
Del
Barrio 6 6 0.00% 0.00%
100.00
% 0.00%
Large
Family
740.0
3 20.70%
1.60
%
64.90
%
11.30
% 12.2%
LIHTC
Lacy &
Raitt
Apartme
nts 34 35 86.32% 0.85% 88.03% 0.00%
Large
Family
748.0
6 1.4% 1.3% 93.0% 4.3% 30.8%
LIHTC
Raitt
Street
Apartme
nts 6 6 0.00% 0.00%
100.00
% 0.00%
Large
Family
748.0
2 1.6% 0.5% 88.1% 9.5% 25.5%
LIHTC
Ross_Du
rant
Apartme
nts 48 49 78.95% 0.00% 88.89% 0.00%
Large
Family
750.0
3 2.5% 0.1% 94.8% 1.6% 32.3%
LIHTC
Santa
Ana Infill 50 51 94.00% 0.00% 95.60% 3.20%
Large
Family
750.0
2 6.0% 0.3% 86.5% 5.9% 37.8%
LIHTC
Santa
Ana
Station
District
Phase I 73 74 10.09% 1.26% 95.58% 0.32%
Large
Family
744.0
5 5.3% 1.3% 89.8% 2.8% 20.8%
LIHTC
Santa
Ana
Station
District
Phase II 39 40 16.46% 1.27% 89.24% 0.00%
Large
Family
744.0
5 5.3% 1.3% 89.8% 2.8% 20.8%
LIHTC
Vista Del
Rio
Apartme
nts 40 41 78.33% 11.67% 41.67% 1.67%
Special
Needs
891.0
7 8.9% 0.0% 55.4%
35.2
% 8.3%
LIHTC
Wakeha
m Grant
Apartme
nts
12
6 127 8.83% 1.42% 84.33% 5.98%
Non
Targeted
745.0
1 1.0% 0.9% 91.2% 6.6% 39.8%
LIHTC
Wilshire
& Minnie
Apartme
nts
14
3 144 97.57% 0.00% 97.76% 1.12%
Large
Family
744.0
3 3.6% 0.0% 93.9% 2.5% 28.8%
328
Table 21: Tustin
Program
Type
Project
Name
Low
Income
Units vs.
Units in
Project
Property
White
(%)
Propert
y Black
(%)
Propert
y
Hispani
c (%)
Propert
y Asian
(%)
Households
with
children in
the
developmen
t OR
Developmen
t Type
Censu
s
Tract
Numb
er
Tract
White
%
Tract
Black
(%)
Tract
Hispan
ic (%)
Tract
Asian
(%)
Censu
s
Tract
Pover
ty
Rate
Project-
Based
Section
8
Tustin
Gardens 100 29% N/a 12% 59% N/a
755.0
5 41.5% 2.8% 38.8% 9.2% 8.3%
LIHTC
Anton
Legacy
Apartment
s
16
1
22
5 37.90% 7.83% 33.10% 16.90%
Non-
Targeted
755.1
5 27.4% 1.1% 36.0%
31.7
% 19.4%
LIHTC
Coventry
Court 97
24
0 40.47% 5.06% 8.56% 26.85% Senior
755.0
7 31.1% 3.8% 45.0%
16.7
% 13.2%
LIHTC
Hampton
Square
Apartment
s
21
2
35
0 12.16% 1.54% 78.08% 1.03%
Non-
Targeted
744.0
7 10.8% 1.3% 84.1% 2.0% 22.9%
LIHTC
Heritage
Place At
Tustin 53 54 38.81% 2.99% 13.43% 25.37% Senior
755.1
5 27.4% 1.1% 36.0%
31.7
% 19.4%
LIHTC
Westchest
er Park
14
9
15
0 13.12% 3.38% 75.35% 7.16%
Non
Targeted
755.1
3 14.4% 3.6% 57.9%
20.5
% 9.8%
Table 22: Westminster
Program
Type
Project
Name
Low
Income
Units vs.
Units in
Project
Property
White
(%)
Proper
ty
Black
(%)
Propert
y
Hispani
c (%)
Propert
y
Asian
(%)
Households
with
children in
the
developme
nt OR
Developme
nt Type
Censu
s
Tract
Numb
er
Tract
White
%
Tract
Black
(%)
Tract
Hispan
ic (%)
Tract
Asian
(%)
Censu
s
Tract
Povert
y Rate
Project-
Based
Section
8
Pacific
Terrace
Apts 97 3% N/a 1% 96% N/a
0997.
02 21.2% 0.9% 23.8%
51.1
% 21.2%
LIHTC
Cambrid
ge
Heights
Senior
Apartme
nts 21 22 33.33% 0.00% 3.70%
55.56
% Senior
998.0
2 14.5% 1.0% 32.1% 49.7%
30.3
%
LIHTC
Coventry
Heights 75 76 9.90% 0.00% 3.96%
67.33
% Senior
998.0
2 14.5% 1.0% 32.1% 49.7%
30.3
%
LIHTC
Royale
Apartme
nts 35 36 18.05% 5.26% 49.62%
12.03
%
Large
Family
998.0
1 14.5% 0.6% 40.4% 44.2%
26.7
%
LIHTC
The
Rose
Gardens
13
2
13
3
9.15% 0.61% 3.05%
84.76
%
Large
Family
998.0
3 17.5% 0.0% 24.4% 54.3%
23.0
%
LIHTC
Westmin
ster
Senior
Apartme
nts 91 91 9.38% 0.00% 4.69%
81.25
% Senior
998.0
2 14.5% 1.0% 32.1% 49.7%
30.3
%
LIHTC
Windsor
Court -
Stratford
Place 85 86 20.30% 5.08% 19.80%
55.84
%
Large
Family
998.0
3 17.5% 0.0% 24.4% 54.3%
23.0
%
329
IX. GLOSSARY
Accessibility: whether a physical structure, object, or technology is able to be used by people with
disabilities such as mobility issues, hearing impairment, or vision impairment. Accessibility
features include wheelchair ramps, audible crosswalk signals, and TTY numbers. See: TTY
Affirmatively Further Fair Housing (AFFH): a requirement under the Fair Housing Act that
local governments take steps to further fair housing, especially in places that have been historically
segregated. See: Segregation
American Community Survey (ACS): a survey conducted by the US Census Bureau that
regularly gathers information about demographics, education, income, language proficiency,
disability, employment, and housing. Unlike the Census, ACS surveys are conducted both yearly
and across multiple years. The surveys study samples of the population, rather than counting every
person in the U.S. like the Census.
Americans With Disabilities Act (ADA): federal civil rights law that prohibits discrimination
against people with disabilities.
Annual Action Plan: an annual plan used by local jurisdictions that receive money from HUD to
plan how they will spend the funds to address fair housing and community development. The
Annual Action Plan carries out the larger Consolidated Plan. See also: Consolidated Plan
CDBG: Community Development Block Grant. Money that local governments receive from HUD
to spend of housing and community improvement
Census Tract: small subdivisions of cities, towns, and rural areas that the Census uses to group
residents together and accurately evaluate the demographics of a community. Several census tracts,
put together, make up a town, city, or rural area.
Consent Decree: a settlement agreement that resolves a dispute between two parties without
admitting guilt or liability. The court maintains supervision over the implementation of the consent
decree, including any payments or actions taken as required by the consent decree.
Consolidated Plan (Con Plan): a plan that helps local governments evaluate their affordable
housing and community development needs and market conditions. Local governments must use
their Consolidated Plan to identify how they will spend money from HUD to address fair housing
and community development. Any local government that receives money from HUD in the form
of CDBG, HOME, ESG, or HOPWA grants must have a Consolidated Plan. Consolidated Plans
are carried out through annual Action Plans. See: Action Plan, CDBG, HOME, ESG, HOPWA.
Consortium: in this analysis, the terms “the Consortium” and “the Taunton Consortium” are used
interchangeably. The Consortium refers to the cities of Taunton and Attleboro, and the towns of
Berkley, Carver, Dighton, Freetown, Lakeville, Mansfield, Middleboro, North Attleboro, Norton,
Plainville, Raynham, and Seekonk.
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Continuum of Care (CoC): a HUD program designed to promote commitment to the goal of
ending homelessness. The program provides funding to nonprofits and state and local governments
to quickly rehouse homeless individuals and families, promote access to and effect utilization of
mainstream programs by homeless individuals, and optimize self-sufficiency among individuals
and families experiencing homelessness.
Data and Mapping Tool (AFFHT): an online HUD resource that combines Census data and
American Community Surveys data to generate maps and tables evaluating the demographics of
an area for a variety of categories, including race, national origin, disability, Limited English
Proficiency, housing problems, environmental health, and school proficiency, etc.
De Facto Segregation: segregation that is not created by the law, but which forms a pattern as a
result of various outside factors, including former laws.
De Jure Segregation: segregation that is created and enforced by the law. Segregation is currently
illegal.
Density Bonus: an incentive for developers that allows developers to increase the maximum
number of units allowed at a building site in exchange for either affordable housing funds or
making a certain percentage of the units affordable.
Disparate Impact: practices in housing that negatively affect one group of people with a protected
characteristic (such as race, sex, or disability, etc.) more than other people without that
characteristic, even though the rules applied by landlords do not single out that group.
Dissimilarity Index: measures the percentage of a certain group’s population that would have to
move to a different census tract in order to be evenly distributed with a city or metropolitan area
in relation to another group. The higher the Dissimilarity Index, the higher the level of segregation.
For example, if a city’s Black/White Dissimilarity Index was 65, then 65% of Black residents
would need to move to another neighborhood in order for Blacks and Whites to be evenly
distributed across all neighborhoods in the city.
ESG: Emergency Solutions Grant. Funding provided by HUD to 1) engage homeless individuals
and families living on the street, 2) improve the number and quality of emergency shelters for
homeless individuals and families, 3) help operate these shelters, 4) provide essential services to
shelter residents, 5) rapidly re-house homeless individuals and families, and 6) prevent
families/individuals from becoming homeless
Entitlement Jurisdiction: a local government that receives funds from HUD to be spent on
housing and community development. See also: HUD Grantee
Environmental Health Index: a HUD calculation based on potential exposure to harmful toxins
at a neighborhood level. This includes air quality carcinogenic, respiratory, and neurological
hazards. The higher the number, the less exposure to toxins harmful to human health.
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Environmental Justice: the fair treatment and meaningful involvement of all people, especially
minorities, in the development, implementation, and enforcement of environmental laws,
regulations, and policies. In the past, environmental hazards have been concentrated near
segregated neighborhoods, making minorities more likely to experience negative health effects.
Recognizing this history and working to make changes in future environmental planning are
important pieces of environmental justice.
Exclusionary Zoning: the use of zoning ordinances to prevent certain land uses, especially the
building of large and affordable apartment buildings for low-income people. A city with
exclusionary zoning might only allow single-family homes to be built in the city, excluding people
who cannot afford to buy a house.
Exposure Index: a measurement of how much the typical person of a specific race is exposed to
people of other races. A higher number means that the average person of that race lives in a census
tract with a higher percentage of people from another group.
Fair Housing Act: a federal civil rights law that prohibits housing discrimination on the basis of
race, class, sex, religion, national origin, or familial status. See also: Housing Discrimination.
Federal Uniform Accessibility Standards (UFAS): a guide to uniform standards for design,
construction, and alternation of buildings so that physically handicapped people will be able to
access and use such buildings.
Gentrification: the process of renovating or improving a house or neighborhood to make it more
attractive to middle-class residents. Gentrification often causes the cost of living in the
neighborhood to rise, pushing out lower-income residents and attracting middle-class residents.
Often, these effects which are driven by housing costs have a corresponding change in the racial
demographics of an area.
High Opportunity Areas/Low Opportunity Areas: High Opportunity Areas are communities
with low poverty, high access to jobs, and low concentrations of existing affordable housing.
Often, local governments try to build new affordable housing options in High Opportunity Areas
so that the residents will have access to better resources, and in an effort to desegregate a
community, as minorities are often concentrated in low opportunity areas and in existing
affordable housing sites.
HOME: HOME Investment Partnership. HOME provides grants to States and localities that
communities use (often in partnership with nonprofits) to fund activities such as building, buying,
and/or rehabilitating affordable housing for rent or ownership, or providing direct rental assistance
to low-income people.
Housing Choice Voucher (HCV)/Section 8 Voucher: a HUD voucher issued to a low-income
household that promises to pay a certain amount of the household’s rent. Prices are set based on
the rent in the metropolitan area, and voucher households must pay any difference between the
rent and the voucher amount. Voucher holders are often the subject of source of income
discrimination. See also: Source of Income Discrimination.
332
Housing Discrimination: the refusal to rent to or inform a potential tenant about the availability
of housing. Housing discrimination also applies to buying a home or getting a loan to buy a home.
The Fair Housing Act makes it illegal to discriminate against a potential tenant/buyer/lendee based
on that person’s race, class, sex, religion, national origin, or familial status.
HUD Grantee: a jurisdiction (city, country, consortium, state, etc.) that receives money from
HUD. See also: Entitlement Jurisdiction
Inclusionary Zoning: a zoning ordinance that requires that a certain percentage of any newly built
housing must be affordable to people with low and moderate incomes.
Individuals With Disabilities Education Act (IDEA): a federal civil rights law that ensures
students with a disability are provided with Free Appropriate Public Education that is tailored to
their individual needs.
Integration: the process of reversing trends of racial or other segregation in housing patterns.
Often, segregation patterns continue even though enforced segregation is now illegal, and
integration may require affirmative steps to encourage people to move out of their historic
neighborhoods and mix with other groups in the community.
Isolation Index: a measurement of how much the typical person of a specific race is only exposed
to people of the same race. For example, an 80% isolation index value for White people would
mean that the population of people the typical White person is exposed to is 80% White.
Jobs Proximity Index: a HUD calculation based on distances to all job locations, distance from
any single job location, size of employment at that location, and labor supply to that location. The
higher the number, the better the access to employment opportunities for residents in a
neighborhood.
Labor Market Engagement Index: a HUD calculation based on level of employment, labor force
participation, and educational attainment in a census tract. The higher the number, the higher the
labor force participation and human capital in the neighborhood.
Limited English Proficiency (LEP): residents who do not speak English as a first language, and
who speak English less than “very well”
Local Data: any data used in this analysis that is not provided by HUD through the Data and
Mapping Tool (AFFHT), or through the Census or American Community Survey
Low Income Housing Tax Credit (LIHTC): provides tax incentives to encourage individual and
corporate investors to invest in the development, acquisition, and rehabilitation of affordable rental
housing.
Low Poverty Index: a HUD calculation using both family poverty rates and public assistance
receipt in the form of cash-welfare (such as Temporary Assistance for Needy Families (TANF)).
333
This is calculated at the Census Tract level. The higher the score, the less exposure to poverty in
the neighborhood.
Low Transportation Cost Index: a HUD calculation that estimates transportation costs for a
family of 3, with a single parent, with an income at 50% of the median income for renters for the
region. The higher the number, the lower the cost of transportation in the neighborhood.
Market Rate Housing: housing that is not restricted by affordable housing laws. A market rate
unit can be rented for any price that the market can support.
NIMBY: Not In My Back Yard. A social and political movement that opposes housing or
commercial development in local communities NIMBY complaints often involve affordable
housing, with reasons ranging from traffic concerns to small town quality to, in some cases, thinly-
veiled racism.
Poverty Line: the minimum level of yearly income needed to allow a household to afford the
necessities of life such as housing, clothing, and food. The poverty line is defined on a national
basis. The US poverty line for a family of 4 with 2 children under 18 is $22,162.
Project-Based Section 8: a government-funded program that provides rental housing to low-
income households in privately owned and managed rental units. The funding is specific to the
building. If you move out of the building, you will no longer receive the funding.
Publicly Supported Housing: housing assisted with funding through federal, State, or local
agencies or programs, as well as housing that is financed or administered by or through any such
agencies or programs.
Quintile: twenty percent of a population; one-fifth of a population divided into five equal groups
Reasonable Accommodation: a change to rules, policies, practices, or services which would
allow a handicapped person an equal opportunity to use and enjoy their housing, including in
public and common use areas. It is a violation of the Fair Housing Act to refuse to make a
reasonable accommodation when such accommodation is necessary for the handicapped person to
have equal use and enjoyment of the housing.
R/ECAPs: Racially and Ethnically Concentrated Areas of Poverty. This is a HUD-defined term
indicating a census tract that has more than 50% Non-White residents, and 40% or more of the
population is in poverty OR where the poverty rate is greater than three times the average poverty
rate in the area. In the HUD Data and Mapping Tool (AFFHT), R/ECAPS are outlined in pink.
See also: Census Tract
Region: the Taunton Consortium is located within the HUD-designated Taunton Consortium
Custom Region, which covers Bristol, Plymouth, and Norfolk Counties. However, the individual
CDBG jurisdictions of Attleboro and Taunton are actually part of the Providence-Warwick, RI-
MA Region. Both Regions are used in this analysis, but are always clearly delineated by name and
with maps.
334
Rehabilitation Act (Section 504): a federal civil rights law that prohibits discrimination on the
basis of disability in programs conducted by federal agencies, in programs receiving federal
financial assistance, in federal employment and in the employment practices of federal contractors.
School Proficiency Index: a HUD calculation based on performance of 4th grade students on state
exams to describe which neighborhoods have high-performing elementary schools nearby and
which are near lower performing elementary schools. The higher the number, the higher the school
system quality is in a neighborhood.
Segregation: the illegal separation of racial or other groups in the location of housing and
neighborhoods. Segregation can occur within a city or town, or in comparing multiple cities. Even
though segregation is now illegal, often, housing continues to be segregated because of factors that
make certain neighborhoods more attractive and expensive than others, and therefore more
accessible to affluent White residents. See also: Integration.
Source of Income Discrimination: housing discrimination based on whether a potential tenant
plans to use a Housing Choice Voucher/Section 8 Voucher to pay part of their rent. Source of
income discrimination is illegal under Massachusetts state law. See also: Housing Choice
Voucher/Section 8 Voucher.
Superfund Sites: any land in the U.S. that has been contaminated by hazardous waste and
identified by the EPA as a candidate for cleanup because it poses a risk to human health and/or the
environment
Supplemental Security Income (SSI): benefits paid to disabled adults and children who have
limited income and resources, or to people 65 and older without disabilities who meet the financial
limits.
Testers: people who apply for housing to determine whether the landlord is illegally
discriminating. For example, Black and White testers will both apply for housing with the same
landlord, and if they are treated differently or given different information about available housing,
their experiences are compared to show evidence of discrimination.
Transit Trips Index: a HUD calculation that estimates transit trips taken for a family of 3, with a
single parent, with an income of 50% of the median income for renters for the region. The higher
the number, the more likely residents in that neighborhood utilize public transit.
TTY/TDD: Text Telephone/Telecommunication Device for the Deaf. TTY is the more widely
used term. People who are deaf or hard of hearing can use a text telephone to communicate with
other people who have a TTY number and device. TTY services are an important resource for
government offices to have so that deaf or hard of hearing people can easily communicate with
them.
Violence Against Women Act (VAWA): a federal law protecting women who have experienced
domestic and/or sexual violence. The law establishes several programs and services including a
federal rape shield law, community violence prevention programs, protections for victims who are
335
evicted because of events related to domestic violence or stalking, funding for victim assistance
services, like rape crisis centers and hotlines, programs to meet the needs of immigrant women
and women of different races or ethnicities, programs and services for victims with disabilities,
and legal aid for survivors of domestic violence.