BHSOAC
Crhd Deliverable1aii Final 05 30 14
Read the report at Behavioral Health Services Oversight & Accountability Commission ↗
Analyzing the Impact of the Mental Health Services Act on
Reducing Disparities in Access
Deliverable 1aii
In-Depth Analysis of Trend Information on Access for All Clients as well as
Access Based on New Admissions to County Mental Health Systems
Principal Investigator
Sergio Aguilar-Gaxiola, M.D., Ph.D.
Professor of Clinical Internal Medicine
Director, Center for Reducing Health Disparities
Co-Principal Investigator
Estella M. Geraghty, M.D., M.S., M.P.H., GISP
Associate Professor of Clinical Internal Medicine
Funded by the Mental Health Services Oversight and Accountability Commission (MHSOAC)
May 30, 2014
Table of Contents
Introduction ........................................................................................................................................................ 2
The Mental Health Services Act (MHSA) ............................................................................................................ 3
Challenges Impacting the MHSA ......................................................................................................................... 4
Mental Health Needs in California ....................................................................................................................... 4
Factors Influencing Treatment Access ................................................................................................................ 5
Measuring Mental Health Disparities and Access ............................................................................................. 6
Methods ............................................................................................................................................................... 7
Client Services Information (CSI) Data ............................................................................................................... 7
California Health Interview Survey (CHIS) Data ................................................................................................ 8
Demographic Data ................................................................................................................................................. 9
Additional Analysis and Contextual Information................................................................................................. 9
Key Findings .................................................................................................................................................... 11
Client Services Information Data Findings ........................................................................................................ 11
Did the MHSA have an impact on reducing disparities in access to mental health care in California?... 71
California Health Interview Survey Findings ..................................................................................................... 72
What are the mental health needs for racial/ethnic, language, nativity, gender and age sub-groups in
California? .............................................................................................................................................................. 77
Overall Summary of Access to Mental Health Care Relative to Need ......................................................... 78
Conclusion ............................................................................................................................................................. 79
Appendix A. Detailed Methodology .............................................................................................................. 81
Appendix B. Contextual Information – A Historical Timeline .................................................................. 85
Appendix C. CSI Data Tables – State and Region Tables ........................................................................ 98
Appendix D. CSI Data Tables – County New Clients (in Alphabetical Order) ..................................... 122
Appendix E. CSI Data Tables – County All Clients (in Alphabetical Order) ....................................... 151
References ...................................................................................................................................................... 180
1
Introduction
The purpose of this analysis is to aid the Mental Health Services Oversight and Accountability
Commission (MHSOAC) in its efforts to ascertain the impact the Mental Health Services Act
(MHSA) has had on reducing disparities in access to treatment services and the quality of the
outcomes of the public mental health system. While there are various definitions of disparities,
in this report disparities refer to a difference in treatment, access or outcomes in certain
population groups that are not justified by differences in that group’s health status, preferences,
or socio-demographic composition in the general population. The MHSOAC selected the UC
Davis Center for Reducing Health Disparities (CRHD) to determine disparities in access by age,
gender, race/ethnicity, and primary language at county, region and statewide levels.
This report provides an in-depth quantitative data analysis of trends in the priority indicator of
“access to care” for systems of mental health care including community services and supports.
We utilized the Client Services Information (CSI) data to detect differences in access among
population subgroups, and the California Health Interview Survey (CHIS) to define mental health
status among population subgroups (at state and regional levels). Using these data, we made
analytic comparisons to determine disparities in access to mental health care guided by these
research questions:
o Did the MHSA have an impact on reducing disparities in access to mental health
care in California?
o What are the mental health needs for racial/ethnic, language, nativity, gender and
age sub-groups in California?
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The Mental Health Services Act (MHSA)
The Mental Health Services Act (MHSA), approved by California voters in November of 2004,
created an historic opportunity to expand programs to serve children, youth, adults, older adults,
and families with mental health needs. Inspired by innovative models of mental health treatment
offered in California, such as the successful AB 2034 that provided $10 million for pilot
programs to reduce homelessness among the mentally ill, the MHSA represents an unparalleled
effort to improve timely access to services for underserved populations and reform the
fragmentation of mental health systems and services (Cashin, Scheffler, Felton, Adams, &
Miller, 2008; UCLA, 2014). The MHSA increased funding for county mental health programs,
while monitoring progress in the improvement of services for children, transitional age youth,
older adults, and families (California Department of Mental Health, 2011). MHSA obtains its
funding from a 1% tax imposed on California residents whose income exceeds one million
dollars annually. To date, MHSA has provided an estimated $7.4 billion to counties during fiscal
years 2006-2007 to 2011-2012 (California State Auditor, 2013). By taxing Californians with the
highest incomes, the MHSA hoped to obtain the revenue to expand funds for mental health
services while protecting existing vital state services from reductions (California Department of
Mental Health, 2011).
The MHSA primarily sought to increase access to mental health care and develop a more
consumer-driven mental health system focused on resiliency and recovery by achieving the
following aims (California Department of Mental Health, 2011).
1. Define serious mental illness among children, adults and older adults as a condition
deserving priority attention, including prevention and early intervention services and
medical and supportive care.
2. Reduce the long-term adverse impact on individuals, families and state and local
budgets resulting from untreated serious mental illness.
3. Expand innovative service programs for children, adults and older adults already
existing in California, including culturally and linguistically competent approaches for
underserved populations. These programs have already demonstrated their
effectiveness in providing outreach and integrated services, including medically
necessary psychiatric services to individuals most severely affected by or at risk of
serious mental illness.
4. Provide state and local funds to adequately meet the needs of all children and adults
who can be identified and enrolled in programs under this measure. State funds shall
be available to provide services that are not already covered by federally sponsored
programs or by individuals’ or families’ insurance programs.
5. Ensure that all funds are expended in the most cost effective manner and services
are provided in accordance with recommended best practices subject to local and
state oversight to ensure accountability to taxpayers and to the public.
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To achieve these aims, the MHSA allocated funds to programs targeting Community Services
and Supports, Prevention and Early Intervention, Workforce Education and Training, Capital
and Information Technology, Innovation, and Community Program Planning and Administration.
Challenges Impacting the MHSA
Despite the potential of the MHSA and its development of multiple services and programs to
meet the mental health needs of Californians, it has encountered multiple challenges. The
recent MHSA state audit report found limitations in all of the following activities (California State
Auditor, 2013):
o Monitoring of funds provided to counties for MHSA programs
o Proper implementation of state approved MHSA plans
o The collection of county data relevant to service provision and the characteristics of
clients receiving services
o The evaluation and reporting of the effectiveness of MHSA programs
o Inability to confirm successes within county-specific programs due to inconsistent
approaches across counties to asses MHSA programs
o Although the MHSA was enacted with stakeholder input, the state audit indicated an
absence of specific strategies used for the acquisition of continued stakeholder input in
the planning and development of services
Through our analysis, we aim to provide the MHSOAC, mental health services providers,
consumers and their family members, as well as advocates and all other relevant stakeholders
a snapshot of current mental health disparities among underserved and inappropriately served
groups throughout the state.
Mental Health Needs in California
Mental health has been defined by the Institute of Medicine as “a state of well-being in which
every individual realizes his or her own potential, can cope with the normal stressors of life, can
work productively and fruitfully, and is able to make a contribution to her or his community.”
Unfortunately, many Californians suffer from mental ill-health, a condition in which psychological
distress leads to decreased functioning in one or more domains of life. California contains a
diverse population with need for mental health treatment. In a recent study utilizing the
California Health Interview Survey, one in five (or 4.9 million) adults in California reported
needing support for a mental health problem (Grant et al., 2011). After estimating the presence
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of serious psychological distress, it was noted that about two million adults met criteria for
having serious mental health needs. Of the two million Californians, only half accessed mental
health treatment in the past year, one quarter received some treatment, and the remaining
quarter received minimal treatment. Among disadvantaged groups, American Indians and
Alaska Natives, biracial Californians, sexual minorities, and single heads of household were
found to have high levels of mental health needs. U.S. born Latinos were also found to have
twice the risk for mental health needs in comparison to foreign-born Latinos. Young adults 18-
24, older adults 65 and older, those with low levels of education and limited English proficiency,
foreign-born Latinos and Asians, as well as Asian and African Americans were found to be less
likely to receive any form of treatment. Lack of insurance and access to public health insurance
were both associated with higher mental health needs among all adults interviewed, serving as
a reminder that access to health insurance does not necessarily improve mental health status
(Grant et al., 2011).
Other work exploring California Mental Health penetration rates among diverse groups has
confirmed poor access to care among ethnic groups. Using the California Department of Mental
Health’s (DMH) Medi-Cal Paid Claims File for service utilization information and the Client
Service Information System (CSI) data for consumer ethnic characteristics, Snowden, Masland,
Ma, and Ciemens (2006) found penetration rates for Asian Americans and Latinos to be
particularly low in comparison to other ethnic groups in California.
Factors Influencing Treatment Access
Disadvantaged groups encounter multiple difficulties in accessing mental health treatment. The
care they need is not readily available in the needed place and at the needed time. Often when
services are accessed, poor interactions with providers can reduce interest in continued care
(Lamb, Bower, Rogers, Dowrick & Gask, 2011; National Collaborating Centre for Mental Health
(UK), 2011). Additional barriers, both external and internal to the individual, can prevent access
to care among the underserved. For example, transportation, homelessness, lack of time for
appointments, not meeting eligibility criteria for treatment, and difficulty with understanding how
to navigate mental health systems present difficult barriers to overcome for several individuals
(Aguilar-Gaxiola et al., 2012; Lamb et al., 2011; Snowden et al., 2006). Further difficulties
include personal, cultural, and social beliefs surrounding mental health concerns and the stigma
associated care and treatment options (Lamb et al., 2011).
Access to care is clearly a complex issue for underserved groups. It is a subjective as well as
objective process whereby the individual assesses available resources and makes a judgment
based on their evaluation of the available resources. The decision to access care also includes
individual beliefs about one’s own resources to manage mental health needs (Lamb et al.,
2011). If the individual decides to access services, he/she will soon realize that entry into mental
health treatment is challenging, particularly for underserved groups, because there are several
steps involved in actually accessing mental health care. The individual must meet criteria for
care through qualified diagnoses and/or insurance coverage. If insurance coverage is lacking
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the individual must determine if he/she has the ability to pay for care. The individual must then
continue to navigate the mental health system to find a proper point of entry and treatment. The
individual then interacts with providers, who may or may not be culturally competent enough to
effectively explore his/her needs, and eventually receives a treatment recommendation. The
initial contact with mental health providers and systems is critical as it can determine if the
individual will successfully access treatment, remain in treatment, or decide not to pursue
continued mental health treatment (National Collaborating Centre for Mental Health (UK), 2011).
Measuring Mental Health Disparities and Access
Given the difficulty in accessing care among underserved groups, it is important to define
mental health disparities and measure their current status among the underserved. Through
standardized definitions and measures of mental health disparities among distinct underserved
groups, proper responses to disparities can ensue. The Institute of Medicine defines disparities
as follows: racial or ethnic differences in the quality of healthcare that are not due to access-
related factors or clinical needs, preferences, or appropriateness of intervention. This definition
considers differential impacts on groups based on the operation of health care systems and the
legal and regulatory climate in which health systems function; and discrimination encountered
by patients at the individual, and patient-provider level (National Research Council, 2003).
Broad recommendations for adequate measurement of mental health disparities among
underserved groups include assessment of services used by different individuals as well as
measures of care expenditures, mental health status, preferences for care, race and ethnicity,
and other demographic and socio-economic variables (Le Cook & McGuire, & Zaslavsky, 2012;
McGuire, Alegria, Cook, Wells, & Zaslavsky, 2006).
The purpose of this evaluation was to help the MHSOAC and county mental health programs
throughout the state in evaluating the impact of MHSA on the disparities in access to care,
quality of care, and outcomes of the public mental health system by race, age, gender, and
ethnicity. Our analysis provides an in-depth look at trends in access rates among mental health
consumers as well as trends in mental health needs across the California population. Through
our work, we seek to support steps toward reducing mental health disparities in access to care.
6
Methods
This analysis will focus on the individuals that are accessing mental health services through
MHSA’s Community Services and Supports (CSS) each year between January 2005 and
December 2012, spanning the time from the initiation of the MHSA (i.e., January of 2005) to the
most recent data available. We identified the demographic differences in access to mental
health care services for new clients (those without service for the prior six months) and for all
clients who received services via CSS each calendar year. We analyzed differences over time
to discern trends. From these emerging trends, we address the question, “Did the MHSA have
an impact on reducing disparities in access to care in California?” Our analytical methods to
address the above question are described next. We describe the data sources that were
accessed, managed and analyzed and provide an overview of the analytical methods employed.
For a description of our original analytic plan showing specific step-by-step methods and
variables used for our analysis please refer to Appendix A.
Client Services Information (CSI) Data
Our analysis builds on work done by the University of California at Los Angeles (UCLA) (Grant
et al., 2011). As part of their work, UCLA researchers developed a prioritized set of performance
indicators covering both individual client outcomes and county mental health system
performance. We chose to begin this in-depth evaluation in the latter area of county mental
health system performance because detecting the impact from the MHSA might be more
informative at the systems level, where practice and policy changes can be implemented. UCLA
researchers suggested “Indicator #34 – New clients by county by age, gender, race ethnicity for
FY 04/05 and FY 07/08” as an area for further research. We pursued this indicator and further
expanded upon it by examining new clients AND all clients for all calendar years from January
2005 to December 2012.
The best data source for our analysis of trends in priority indicators was the Client Services
Information (CSI) database. This database, which began on July 1, 1998 and replaced the
Client Discharge System (CDS), covered the entire study period (July 2004 to December 2012)
and provided data fields that facilitated the evaluation of the impact of MHSA on disparities in
access. The CSI system collects data pertaining to mental health clients and the services they
receive at the county level. The system reflects both Medi-Cal and non-Medi-Cal clients and
includes a full range of Axis I and Axis II disorders. Our first task was to obtain and ‘clean’ the
dataset. We carried out the latter task through an evaluation and correction of typographical
errors, review of frequencies and potential outliers, and data standardization measures (such as
aggregating the race categories across years of CSI data). No attempt was made to interpolate
missing or incomplete data. However, when variables of interest had large amounts of missing
or incomplete data, such is noted within the report.
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We began our analysis with the identification of new clients within the database to provide
insight about the MHSA’s impact on outreach efforts to the unserved in need of treatment.
Based on UCLA’s recommendations, new clients are defined as those without service for the
prior six months. We also analyzed all clients which included every unique client served within
a calendar year of the CSI database as a measure of how the system is doing overall in
reducing disparities in access to care. Both inpatient and outpatient services were included in
the analysis. We categorized clients according to varied demographic variables (such as age,
county of service, gender, race/ethnicity, language and nativity). For the demographic variables
of interest we calculated frequencies and, where possible, proportions by county, region and
statewide. Results are presented as trends over time using tabular and graphical methods with
descriptive text.
California Health Interview Survey (CHIS) Data
Our quantitative analysis also focused on mental health needs in California by population
subgroup. As noted in the introduction, in order to truly understand if disparities are present, one
must control for the health status of the population subgroup in question, since the literature tells
us that health status varies from one group to another and from one geographic place to
another. For that reason, we utilized the California Health Interview Survey (2005, 2007, 2009,
and 2011-2012) to provide context for mental health needs by subpopulation statewide and by
geographic region over time.
Mental health needs were assessed based on the method outlined in the report to the
Department of Mental Health (DMH) from November 2010 entitled, “Assessing Adult Mental
Health Needs in California Using the California Health Interview Survey (CHIS),” by Padilla-
Frausto, Grant and Aguilar-Gaxiola. In this report, mental health need was determined from a
combination of distress and functional impairment measures. The distress component was
based on a set of questions known as the Kessler-6 (K6). The K6, a continuous measure of
psychological distress during the respondent’s previous month, consists of six questions related
to psychological distress scored from 6 (indicating no distress) to 30 (indicating severe distress).
A low range score would be 6-11, a mild to moderate range score would be 12-19, and a high
range score would be 20-30. Functional impairment was determined from the Sheehan
Disability Score (SDS) which measured whether a respondent was experiencing impaired
function in any one of four life domains. The SDS consists of three main constructs, work and
school, social life, and family life and home responsibilities. Using a 10-point rating scale, these
constructs are assessed, where a score of “0” means unimpaired to “30” highly impaired.
Because the California Health Interview Survey is constantly evolving and changing, our ability
to consistently measure mental health needs was mildly impaired. Using the best information
available, we calculated mental health need as follows:
8
2005: Kessler-6 questions with a score ≥ 13 were determined to have mental health
need. No Sheehan Disability variables had been included in the survey in 2005 and thus
were not included in the calculation of need.
2007, 2009, & 2011-2012: Kessler-6 questions with a score ≥ 13 and a Sheehan
Disability Score > 0 indicated the presence of mental health need.
Based on the differences noted above, it is possible that mental health need is over-estimated
for 2005 which did not have the inclusion of the Sheehan Disability Score. However, the likely
over-estimation is small since the inclusion of the Sheehan Disability Score decreased the
number of survey respondents qualifying as having mental health needs by 1.07%, 0.92%, and
1.12% for years 2007, 2009 and 2011-2012 respectively.
Demographic Data
In addition to the two primary datasets noted above, CSI and CHIS, we collected demographic
data on California populations at the county and state level for each year of the study period. By
using population-level data, we have made an assumption that any individual is equally likely to
access mental health services provided by the county and similarly that any individual has an
equal risk to develop a mental health need. We drew our data primarily from the U.S. Census
Bureau’s American Community Survey (ACS) which began producing intercensal population
estimates with the year 2005 to provide communities with more current data than the decennial
census. We chose U.S. Census data because of its high quality, availability and convenience.
Should this work be replicated by counties in future years, census data are easy to obtain. The
ACS is a continuous annual survey that relies on a smaller population sample than the
decennial census, which surveys the entire U.S. population, and thus provides estimates of
population data. Estimates provided are considered stable for single years in communities with
>65,000 population (adequate for most California counties). Three years of data are combined
to create estimates for areas with populations with 20,000 or more and five-year estimates are
required to reduce the margin of error for populations with fewer than 20,000 individuals. Since
this study was conducted at the county, region and state levels and included a study period
beginning in 2005, one year estimates were used. This approach resulted in ‘no data’ for
several smaller counties in California. For those counties, a population estimate from the
California Department of Finance was used, covering the years 2005 to 2010. Based on our
unanticipated need to use two sources for demographic data, we performed additional analysis
relating to the use of demographic data for county-level studies. That analysis is provided in the
accompanying report, “Analyzing the Impact of the Mental Health Services Act on Reducing
Disparities in Access: Data Sources, Limitations and Recommendations.”
Additional Analysis and Contextual Information
We conducted one additional area of analysis to enhance and explain our quantitative findings
derived from the CSI and CHIS results. We sought to determine how mental health access
(from the CSI results) compared to mental health need (from the CHIS results) to further clarify
9
disparities in access to care. The results are explained in the figure captions associated with the
CHIS results. We also chose to provide some additional information by citing contextual factors
that occurred during our 9 year study period that may have impacted disparities in mental health
service access such as: the phasing-in schedule of the MHSA programs, socioeconomic
variables that serve as proxies for the economic downturn, and other environmental or policy-
related factors potentially associated with mental health access. Contextual factors were
organized as a historical timeline, adapted from the one originally created by a staff member of
the Mental Health Services Oversight and Accountability Commission. Additional elements were
determined through our literature review, stakeholder interviews from our qualitative analysis,
and expert opinion. This timeline can serve as a guide to interpretation of the quantitative results
and is included as Appendix B.
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Key Findings
Client Services Information Data Findings
Guide to Interpreting CSI Graphs
The results of the statewide and regional analyses of mental health access are presented as a
series of graphs with explanatory figure captions. Each figure contains two graphs. The first
graph, on the left side, marked ‘a,’ shows the data as simple frequencies over time for clients in
the CSI database. The term, ‘frequencies,’ refers to the number of times something occurred.
Therefore, in this study, ‘frequencies’ refers to the total number of unique clients who entered
the mental health system during a calendar year. This information contributes to our
understanding of whether the MHSA had an impact on reducing disparities in access to mental
health care in California by showing whether more clients are entering into the mental health
system each year. The right-sided graph, labeled ‘b,’ combines the frequency data with
demographic data to create a proportion. The equation for the proportion is:
This equation is applied to each segment of the population under analysis per year. For
example, the number of California women entering the mental health system in 2005 (the
frequency) is divided by the number of women in the California population (from the
demographic data), multiplied by 100,000:
The result of this equation could be read as, “609 of every 100,000 women in California
accessed mental health services in 2005.” The statistical term for this calculation is called
normalization. The purpose of normalizing the frequency data is to adjust for the differences in
the numbers of people in the underlying population subgroup. That way, the resulting number
(609 in this case) can be compared over time and among subgroups. For example, when this
calculation was applied to men in California for 2005, the result was 702, indicating that men in
the state were accessing mental health services at a higher rate than women in 2005.
Therefore, graph ‘b’ can be used to: 1) look at each subgroup’s mental health system access
over time while adjusting for changes in that subgroup’s population each year, and 2) compare
access to mental health systems among the different population subgroups and regions.
The data underlying the graphs in this report are available in Appendices B (for state and
regional data) and C (for county data).
While each graph tells a part of the story of the impact of the MHSA on reducing disparities in
access to mental health services, no graph tells the complete story on its own. For that reason,
a summary section will be provided at the end of each geographic review combining the results
for that area. Then, at the end of this report, an overall summary, integrating the results of all
analyses, will be included to make a determination about the overall impact of the MHSA on
reducing disparities in access to mental health services.
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Important notes: 1) Some large counties did not have complete CSI data (see Table 1). 2) For
those counties that submitted CSI data for 2012, the date range only covered January 1st
through November 30th. For this reason, the 2012 data are shown only in tables in appendices
C-E, as they represent an incomplete dataset for 2012. These data could be examined ‘within
county’ to make comparisons among population subgroups. But since the year is incomplete,
they cannot be used in trend analyses.
Table 1. Counties with incomplete
data for the specified years
County Missing Data
Inyo 2011, 2012
Marin 2012
Riverside 2012
Sacramento 2012
San Mateo 2012
Statewide Access to Mental Health Care Services
New Clients
Figure 1. California mental health access trends for the total population of new clients
obtaining services. Graph (a) shows frequencies or the actual number of new clients by year
of service while graph (b) shows the number of new clients as a proportion of the state’s overall
population. Both graphs in this case indicate that there was a small decrease in access to
mental health services in 2006, followed by increased access in 2007, peaking in 2008. Then, in
2009 and 2010, statewide access to mental health services decreased to below baseline levels
(2005), but then increased again in 2011.
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Figure 2. California mental health access trends by sex for new clients obtaining
services. Graph (a) shows the number of new clients by sex and year of service while graph (b)
shows the number of new clients as a proportion of the state’s population for sex subgroups.
Both graphs indicate increased access for males and females from the baseline year (2005) to
2008. In 2009 and 2010, statewide access for males and females decreased to 2006 levels, but
then increased again in 2011, more so for males than for females.
Figure 3. California mental health access trends by age group for new clients obtaining
services. Graph (a) shows the number of new clients by age group and year of service while
graph (b) shows the number of new clients as a proportion of the state’s population for age
subgroups. According to graph (a), the number of children, ages 0 to 15, that comprise the
Children, Youth and Families (CYF) group, experienced a slow but steady increase in numbers
accessing mental health services over the study period with the exception of a small drop in
2009. Transitional age youth (TAY), defined as the population age 16 to 25, also experienced
increased numbers accessing services from the inception of the MHSA to 2008, but then there
was a slow but continuing decrease in numbers through 2011. The adult population, ages 26-
59, comprise the dominant users (by overall numbers of new clients) of mental health services
statewide and experienced increased access through 2008, but also saw a decline during 2009
and 2010. Then, a sharp increase in the numbers accessing services was seen in 2011. Older
adults, those ages 60 plus, have the fewest numbers of new clients accessing mental health
services in California and no discernable trend over the study period is seen. When reviewing
the proportions accessing services by age group in graph (b), the CYF group showed increasing
access over the study period with a steep rise from 2009 to 2011. In fact, for 2011, the CYF
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group had the highest proportional levels of access among all age groups to the mental health
system. The TAY group had increased access from 2005 to 2008, but then declined through
2011. According to graph (b), although adults and older adults had an increase in access to
mental health services from 2005 to 2008, both groups are experiencing a relative disparity in
access to service compared to CYF and TAY groups.
Figure 4. California mental health access trends by older age group for new clients
obtaining services. Graph (a) shows the number of new clients by older age group and year of
service while the graph (b) shows the number of new clients as a proportion of the state’s
population for older age subgroups. Note that the older age group categories differ between the
two graphs (due to U.S. Census Bureau subdivision methods). Nonetheless, the trends are
clear. The number of older adults obtaining services (graph (a)) diminishes by increasing age,
likely a result of both decreasing lifespan and potentially a transfer to Medicare providers
working outside the county system. However, when normalized by the underlying population
(graph (b)), it is still the youngest group, age 60-64, that have the greatest relative access to
mental health care services. Access for this group increased through 2007, but then decreased
steadily through 2010. Individuals over the age of 65 appear to experience a relative disparity in
access compared to the 60-64 year olds and also have a general trend toward declining access
over most of the study period. Although new clients in this analysis were not asked to report on
their participation in Medicare, it is possible that older groups (i.e., age 65 and older) show a
greater disparity in access because as they become eligible for Medicare, they have less need
to use MHSA funded programs.
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Figure 5. California mental health access trends by racial groups for new clients
obtaining services. Graph (a) shows the number of new clients by racial group and year of
service. Based on the CSI data, racial disparities are impossible to detect. In graph (a), one can
see that the number of new clients with missing or unknown race data increased steadily over
the study period. When such a large percentage of the race information is missing then all of the
numbers must be considered unreliable. For that reason, no regional or county graphics will be
reported for race information from the CSI data in this report. However, the extent to which race
data are missing can be seen for each region and county in the tables in appendices C-E. Table
2 below indicates the percentages of the total, statewide dataset missing race information by
year.
Table 2. Summary of CSI data by year for new clients indicating the
percentage of observations with race information that is unknown
or missing
Year Race Known Race Unknown P e rcentage of Race
or Missing Unknown or Missing
2005 192,360 93,455 33%
2006 170,728 109,015 39%
2007 131,222 164,625 56%
2008 126,261 178,781 59%
2009 115,284 164,772 59%
2010 102,348 171,327 63%
2011 76,683 214,013 74%
2012 19,466 95,146 83%
All Clients
Figure 6. California mental health access trends for the total population of all clients
obtaining services. Graph (a) shows frequencies or the actual number of all clients by year of
service while graph (b) shows the number of all clients as a proportion of the state’s overall
population. Both graphs in this case indicate that there was a small decrease in access to
mental health services in 2006, followed by increased access in 2007, peaking in 2008. Then,
between 2009 and 2011, statewide access to mental health services decreased to below
baseline levels (2005). Data for 2012 were incomplete and therefore it is too early to reflect on
mental health access for all clients beyond 2011.
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Figure 7. California mental health access trends by sex for all clients obtaining services.
Graph (a) shows the number of all clients by sex and year of service while graph (b) shows the
number of all clients as a proportion of the state’s population for sex subgroups. Both graphs
indicate increased access for males and females from the baseline year 2005 to 2008. In 2009
and 2010, statewide access for males and females decreased to 2006 levels, but then
increased again in 2011 for males, while it decreased further for females.
Figure 8. California mental health access trends by age group for all clients obtaining
services. Graph (a) shows the number of all clients by age group and year of service while
graph (b) shows the number of all clients as a proportion of the state’s population for age
subgroups. Data were incomplete for 2012. According to graph (a), the number of children, ages
0 to 15, that comprise the CYF age group, experienced a slow but steady increase in numbers
accessing mental health services over the study period with the exception of a very small drop
in 2011. Transitional age youth (TAY), defined as the population age 16 to 25, also experienced
increased numbers accessing services from the inception of the MHSA to 2008, but then there
was a slow but continuing decrease in numbers through 2010. The adult population, ages 26-
59, comprise the dominant users (by overall numbers of clients) of mental health services
statewide and experienced increased access through 2008, but also saw a decline during 2009
and 2010. Then, a sharp increase in the numbers accessing services was seen in 2011. Older
adults, those ages 60 plus, have the fewest numbers of clients accessing mental health services
in California and no discernable trend over the study period is seen. When reviewing the
proportions accessing services by age group in graph (b), the CYF group showed increasing
access over the study period with a steep rise from 2009 to 2011. In fact, for 2011, the CYF
group had the highest proportional levels of access among all age groups to the mental health
16
system. The TAY group had increased access from 2005 to 2009, but then declined through
2011. According to graph (b), although adults and older adults had an increase in access to
mental health services from 2005 to 2008, both groups are experiencing a relative disparity in
access to service compared to CYF and TAY groups.
Figure 9. California mental health access trends by older age group for all clients
obtaining services. Graph (a) shows the number of all clients by older age group and year of
service while the graph (b) shows the number of all clients as a proportion of the state’s
population for older age subgroups. Note that the older age group categories differ between the
two graphs (due to U.S. Census Bureau subdivision methods). Nonetheless, the trends are
clear. The number of older adults obtaining services (graph (a)) diminishes by increasing age,
likely a result of both decreasing lifespan and potentially a transfer to Medicare providers
working outside the county system. However, when normalized by the underlying population
(graph (b)), it is still the youngest group, age 60-64, that have the greatest relative access to
mental health care services. Access for this group increased through 2008, but then decreased
steadily through 2011. Individuals over the age of 65 appear to experience a relative disparity in
access compared to the 60-64 year olds and also have a general trend toward declining access
over most of the study period.
Figure 10. California mental health access trends by racial/ethnic groups for all clients
obtaining services. Graph (a) shows the number of all clients by racial/ethnic group and year
of service. Based on the CSI data, racial disparities are impossible to detect. In graph (a), one
can see that the number of all clients with missing or unknown race data increased steadily over
17
the study period. When such a large percentage of the race information is missing then all of the
numbers must be considered unreliable. For that reason, no regional or county graphics will be
reported for race information from the CSI data in this report. However, the extent to which race
data are missing can be seen for each region and county in the tables in appendices C-E. Table
3 below indicates the percentages of the total, statewide dataset missing race information by
year.
Table 3. Summary of CSI data for all clients by year indicating the
percentage of observations with race/ethnicity information that is
unknown or missing
Year Race/Ethnicity Race/Ethnicity Percentage of
Known Unknown or Race/Ethnicity
Missing Unknown or Missing
2005 648,998 216,340 33%
2006 643,910 202,969 32%
2007 650,193 295,155 45%
2008 672,907 329,435 49%
2009 653,896 328,146 50%
2010 631,250 334,246 53%
2011 627,497 376,684 60%
2012 398,879 260,803 65%
Statewide Summary
Statewide CSI data indicate that there was a general trend toward increasing access to mental
health services among new and all clients following the implementation of the MHSA until 2008,
when increased numbers and proportions of clients receiving services were evident. This may
reflect improvements in both the outreach to unserved clients (vis a vis the increase in numbers
of new clients) and system wide changes to improve access to all clients following the MHSA.
However, many population subgroups saw declining access for 2009 and 2010 with an upturn in
2011. The greatest disparities in access to mental health services were seen in the adult age
group (ages 26 to 59) and in older adults (age 60 and beyond). It was impossible to detect
disparities by racial group since data were missing for the majority of the overall clients for most
years in the CSI database.
18
Regional Access to Mental Health Care Services
The same population subgroups described above were analyzed by region. We used the
regions originally operationalized by the California Mental Health Directors Association’s
(CMHDA) designated five Workforce Education and Training (WET) regions since these
regions correspond with other regional reports and programs such as CalMHSA, the California
Mental Health Services Authority. Please see figure 11 below for a map indicating which
counties are associated with the different WET regions.
Figure 11. California Workforce, Education and Training (WET) Program Regions and
their Associated Counties
The results of the regional analyses of mental health access are presented as a series of
graphs with explanatory figure captions. Each figure contains two graphs similar to the
statewide analysis above.
19
Important notes: 1) Some counties did not have complete CSI data (see Table 1). In addition,
the 2012 data received only covered January 1st through November 30th of the year. For this
reason, the 2012 data are unreliable in the regional analyses. 2) Regional demographic data
were prepared by summing data from individual counties composing a region. Eighteen
counties in California had populations too small (fewer than 65,000 individuals) to be included in
American Community Survey (ACS) 1-year estimates and we therefore relied on California
Department of Finance (DOF) population estimates covering 2005 to 2010. Table 4 lists the
counties and their associated region whose demographic data came from the DOF and were
limited to 2005 to 2010.
Table 4. Counties and their associated regions with populations fewer than 65,000 that
do not have 1-year demographic estimates available from the U.S. Census Bureau’s
American Community Survey and instead had 2005-2010 population estimates from the
California Department of Finance
County Region County Region
Alpine Central Modoc Superior
Amador Central Mono Central
Calaveras Central Plumas Superior
Colusa Superior San Benito Bay Area
Del Norte Superior Sierra Superior
Glenn Superior Siskiyou Superior
Inyo Central Tehama Superior
Lassen Superior Tuolumne Central
Mariposa Central Trinity Superior
The Superior Region is most impacted since 10 of the 16 associated counties have relatively
small populations without ACS demographic information. The Central Region is somewhat
impacted with 7 out of 20 associated counties without ACS demographic data. The Bay Area
region has only 1 out of 12 associated counties that did not have demographic data from ACS.
Both the Southern Region and the Los Angeles region are unaffected by this issue.
Superior Region
The Superior Region includes 16 counties in the
northernmost part of the state.
20
New Clients
Figure 11. Superior region mental health access trends for the total population of new
clients obtaining services. Graph (a) shows frequencies or the actual number of new clients
by year of service. Over the study period the trend is toward an increasing number of clients
accessing mental health services with only a small drop in 2007 and a slightly larger drop in
2009. Graph (b) shows the number of new clients as a proportion of the region’s overall
population. Here the trend is different. There is an increase in access between 2005 and 2006,
a levelling from 2006 to 2011.
Figure 12. Superior region mental health access trends by sex for new clients obtaining
services. Graph (a) shows the number of new clients by sex and year of service. Over the
study period the trend is similar to that seen in the overall population with an increasing number
of clients accessing mental health services, despite a small drop in 2007 and a slightly larger
drop in 2009. More females are obtaining services than males. Graph (b) shows the number of
new clients as a proportion of the region’s overall population. The trend shows a significant
increase in access between 2005 and 2006. From there, access is generally level through 2011.
21
Figure 13. Superior region mental health access trends by age group for new clients
obtaining services. Graph (a) shows the number of new clients by age group and year of
service while graph (b) shows the number of new clients as a proportion of the state’s
population for age subgroups. According to graph (a), the number of children, ages 0 to 15, that
comprise the Children, Youth and Families (CYF) group, experienced a significant increase in
numbers accessing mental health services between 2005 and 2006, but leveled off over the
next 3 years. Then another increase was seen in 2010 and 2011. Transitional Age Youth (TAY),
defined as the population age 16 to 25, trended toward slowly increasing numbers accessing
services from the inception of the MHSA to 2011. The adult population, ages 26-59, comprise
the dominant users (by overall numbers of new clients) of mental health services in the Superior
region and follow an up and down pattern in the numbers of new clients obtaining services over
the study period with a leveling off in 2011. Older adults, those ages 60 plus, have the fewest
numbers of new clients accessing mental health services in the Superior region and show a
slow rise in the numbers of older adults accessing services. When reviewing the proportions
accessing services by age group in graph (b), all age groups showed increasing access
between 2005 and 2006. The TAY group had additional increases in access between 2007
through 2009. During this period, the other age groups were level. From 2010 to 2011, all age
groups had declines in access. According to graph (b), although adults and older adults saw
some increases in access to mental health services overall, both groups are experiencing a
relative disparity in access to service compared to CYF and TAY groups.
22
Figure 14. Superior region mental health access trends by older age group for new
clients obtaining services. Graph (a) shows the number of new clients by older age group and
year of service while the graph (b) shows the number of new clients as a proportion of the
region’s population for older age subgroups. Note that the older age group categories differ
between the two graphs (due to U.S. Census Bureau subdivision methods). Nonetheless, the
trends are clear. The number of older adults obtaining services (graph (a)) diminishes by
increasing age, likely a result of both decreasing lifespan and potentially a transfer to Medicare
providers working outside the county system. However, when normalized by the underlying
population (graph (b)), it is still the youngest group, age 60-64, that have the greatest relative
access to mental health care services. Access for this group increased through 2006, but then
leveled and decreased through 2011. Individuals over the age of 65 appear to experience a
relative disparity in access compared to the 60-64 year olds and also have a general trend
toward level access over most of the study period. Furthermore, significant decreases in access
from 2005 levels are seen for the age 85 plus group.
Superior Region mental health access trends by race groups for new clients obtaining
services. Based on the CSI data, racial disparities are impossible to detect. When such a large
percentage of the race information is missing then all of the numbers must be considered
unreliable. Table 5 below indicates the percentages of the total dataset missing race information
by year.
Table 5. Summary of CSI data by year for new clients in the Superior
Region indicating the percentage of observations with race
information that is unknown or missing
Year Race Known Race Unknown P e rcentage of Race
or Missing Unknown or Missing
2005 4,869 1,216 20%
2006 4,209 4,050 49%
2007 1,802 6,286 78%
2008 1,999 6,651 77%
2009 1,568 6,430 80%
2010 1,599 7,587 83%
2011 1,531 7,551 83%
2012 989 5,306 84%
Counties of the Superior Region – Summaries of New Client Trends
Butte County
Overall, Butte County showed a general trend of increasing levels of access to mental health
services between 2005 and 2011. The CYF group not only had the greatest levels of increased
access, but this group had the overall highest rate of mental health care access per 100,000 of
the CYF population. Other groups with consistently increasing access were: Females, Males,
TAY, Adults and Older Adults. Notably, Older Adults had much lower access than the above
mentioned groups per 100,000 population of older adults and the increase in access was less
dramatic than the other groups. In Butte County, race data were missing for 25-87% of the
population over the study period (average 71%), making racial disparities impossible to reliably
detect.
23
Colusa County
In Colusa County, other than Older Adults, all age groups had increase access between 2005
and 2006. The TAY age group continued to see an increase in access through 2007. However,
all age groups declined in access through 2010 but remained above baseline levels (2005).
Race data were missing for 12-89% of the population over the study period (average 64%),
making racial disparities impossible to reliably detect.
Del Norte County
In Del Norte County, the TAY and Older Adult age groups saw mild to moderate increases in
access between 2005 and 2006. However, all age groups saw much less access to mental
health services in 2010 compared to the baseline year of 2005. In Del Norte County, race data
were missing for 11-85% of the population over the study period (average 65%), making racial
disparities impossible to reliably detect.
Glenn County
Following the implementation of the MHSA in Glenn County, there was a drop in all age groups
other than Older Adults in access to mental health services (2005 to 2007). Then, the overall
trend was an increase in access for all age groups through 2010, excepting a drop in 2009 for
Older Adults and the CYF group (both of which recovered to higher levels of access in 2010).
The TAY and CYF age groups had the highest levels of access per 100,000 population while
Older Adults had the lowest levels. In Glenn County, race data were missing for 31-92% of the
population over the study period (average 76%), making racial disparities impossible to reliably
detect.
Humboldt County
The trend for mental health services access in Humboldt County was similar for both sexes and
all age groups. From 2005 to 2006 there was a moderate increase in access with a mild to
moderate decrease in 2007. Steep increases were seen between 2007 and 2009. But then
significant decreases in access were seen for all groups through 2007 to at or below the
baseline levels of 2005. The CYF and TAY groups consistently had the highest levels of access
while the Older Adult group consistently had the least access. In Humboldt County, race data
were missing for 7-81% of the population over the study period (average 60%), making racial
disparities impossible to reliably detect.
Lake County
In Lake County, there were increases in access for all sex and age groups between 2005 and
2007, with the CYF and TAY groups having the highest access and Older Adults having the
lowest access. Between 2007 and 2010 only the Older Adults group saw mild improvements or
stabilization of their access to mental health services. All other groups had declines to the 2005
level. More access was experienced in the county in 2011, but did not reflect a full recovery to
2007 peak levels. In Lake County, race data were missing for 0-86% of the population over the
study period (average 66%), making racial disparities impossible to reliably detect.
Lassen County
During the first two years after passage of the MHSA, Lassen County had increased levels of
access to mental health services for all age groups. While a dip in access was seen in 2008,
there was a surge in access to 2010. CYF and TAY groups had the greatest access and Older
Adults had the least access. In Lassen County, race data were missing for 65-94% of the
24
population over the study period (average 86%), making racial disparities impossible to reliably
detect.
Mendocino County
Mendocino County provided increased access to mental health services between 2005 and
2008/2009 (except for a small dip for Adults and Older Adults in 2007). Then all groups showed
a decline through 2011 to baseline levels (2005). CYF and TAY age groups had the greatest
access while Older Adults had the lowest overall access per 100,000 population. In Mendocino
County, race data were missing for 25-90% of the population over the study period (average
74%), making racial disparities impossible to reliably detect.
Modoc County
In Modoc County, the TAY age group has experienced significant increases in mental health
service access since the inception of the MHSA and enjoys by far the highest levels of access
per 100,000 population as compared to other groups. The other age groups show some
increased access during the first year after implementation (2006), but then have a pattern of
increases and decreases each year through 2010. However, the access in 2010 is slightly
increased overall from the baseline year of 2005 in every age group except for Older Adults in
which case the access is slightly lower than baseline. In Modoc County, race data were missing
for 11-78% of the population over the study period (average 62%), making racial disparities
impossible to reliably detect.
Nevada County
The pattern of access to mental health services in Nevada County resembles a ‘U’ shaped
curve in which all age groups (except Older Adults) and sexes saw large increases in access
between 2005 and 2006. Then there were significant decreases from 2006 to 2007 that
remained through 2010. Then there was a surge in access between 2010 and 2011 for all
groups (including Older Adults). The CYF group, followed by TAY had the highest levels of
access each year while the Older Adults had the lowest. In Nevada County, race data were
missing for 52-92% of the population over the study period (average 77%), making racial
disparities impossible to reliably detect.
Plumas County
In Plumas County, there is essentially a ‘flat’ line when reviewing the access to mental health
services for age and sex groups. The only significant changes seen in this county include an
increase in access for the CYF group from 2008 to 2010 with a concomitant decrease in service
for the TAY group during that period. However, both of these young age groups had the highest
levels of access in the county over the entire study period while Older Adults had the lowest
levels of access. In Plumas County, race data were missing for 16-99% of the population over
the study period (average 68%), making racial disparities impossible to reliably detect.
Shasta County
All age and sex groups in Shasta County experienced increased access over the entire study
period. The greatest increases were seen between 2005 and 2006, but the trend continued
through 2011. Consistent with the other counties of this region, the CYF and TAY age groups
had the greatest levels of access while Older Adults had the lowest levels. In Shasta County,
race data were missing for 16-83% of the population over the study period (average 67%),
making racial disparities impossible to reliably detect.
25
Sierra County
The CYF and TAY age groups both saw dramatic increases in access to mental health services
in Sierra County, the former from 2005 to 2007 and the latter from 2008-2009. The CYF group
had a decrease in access in 2008, but then leveled off through 2010 at a level significantly
higher than baseline (2005). For the TAY group, there was a sharp decline in access between
2009 and 2010 that returned the levels to baseline. While the Older Adult age group had the
least access to services in this county, the rate of access per 100,000 population was steady
with a mild increase by 2010. In Sierra County, race data were missing for 13-97% of the
population over the study period (average 54%), making racial disparities impossible to reliably
detect.
Siskiyou County
In Siskiyou County, all age groups had immediate increases in access between 2005 and 2006.
The TAY group continued the trend of increasing access through 2010. For the CYF, Adult and
Older Adult age groups, a slow decline in access was seen by 2010, but remained above
baseline levels (2005). In Siskiyou County, race data were missing for 7-81% of the population
over the study period (average 62%), making racial disparities impossible to reliably detect.
Tehama County
For the TAY, Adult and Older Adult age groups in Tehama County, increased access to mental
health services occurred from inception of the MHSA through 2008. Despite small dips in 2009,
all of these groups had higher levels of access in 2010 compared to baseline (2005). The CYF
group had a large increase in access between 2005 and 2006, but then experienced a sharp
decline between 2006 and 2009, with a hint toward recovery in 2010. Overall, the CYF group
also had much higher levels of access in 2010 as compared to 2005. In Tehama County, race
data were missing for 30-85% of the population over the study period (average 71%), making
racial disparities impossible to reliably detect.
Trinity County
There does not appear to be a generalizable pattern to mental health service access in Trinity
County. Over the study period, the county experienced ups and down in the different age
groups and ended in 2010 with access levels near or below baseline (2005). Similar to other
counties in the region, the CYF and TAY groups had by far the highest levels of access and the
Older Adult group had the lowest levels. In Trinity County, race data were missing for 10-88% of
the population over the study period (average 69%), making racial disparities impossible to
reliably detect.
26
All Clients
Figure 15. Superior region mental health access trends for the total population of all
clients obtaining services. Graph (a) shows frequencies or the actual number of all clients by
year of service while graph (b) shows the number of all clients as a proportion of Superior
Region’s overall population. Both graphs in this case indicate that there was an increase in
access to mental health services in 2006 and 2007, with the number of clients peaking in 2007
and client access peaking in 2008. Then, between 2009 and 2011, Superior Region access to
mental health services increased and remained well above baseline levels (2005). Data for
2012 were incomplete and are therefore not reliable.
Figure 16. Superior region mental health access trends by sex for all clients obtaining
services. Graph (a) shows the number of all Superior Region clients by sex and year of service
while graph (b) shows the number of all clients as a proportion of the Superior Region’s
population for sex subgroups. Graph (a) indicates increased access for males and females from
the baseline year (2005) to 2008. Between 2008 and 2009 there were decreases in the number
of both male and female clients, and then slight increases until 2011, finishing with numbers that
were well above the 2005 baseline. Graph (b) portrays a substantial increase from baseline
(2005) to 2007. Between 2007 and 2009, Superior Region mental health access for males and
females decreased, but then increased again slightly in 2010 and 2011.
27
Figure 17. Superior region mental health access trends by age group for all clients
obtaining services. Graph (a) shows the number of all Superior Region clients by age group
and year of service while graph (b) shows the number of all Superior Region clients as a
proportion of the region’s population for age subgroups. Data were incomplete for 2012.
According to graph (a), the number of children, ages 0 to 15, that comprise the CYF age group,
experienced a slow but steady increase in numbers accessing mental health services over the
study period. Transitional age youth (TAY), defined as the population age 16 to 25, also
experienced increased numbers accessing services from the inception of the MHSA to 2008,
but then there was a leveling off in the numbers through 2011. The adult population, ages 26-
59, comprise the dominant users (by overall numbers of clients) of mental health services
statewide and experienced increased access through 2008, but also saw a decline during 2009.
Then, the numbers of clients accessing services in the region leveled off between 2009 and
2011. Older adults, those ages 60 plus, have the fewest numbers of clients accessing mental
health services in the region and no discernible trend over the study period is seen. When
reviewing the proportions accessing services by age group in graph (b), the CYF group showed
increasing access over the study period with a steady rise from 2005 to 2008. In fact, for 2011,
the CYF group had the highest proportional levels of access among all age groups to the mental
health system. The TAY group had increased access from 2005 to 2007, but then declined
through 2009, and rose again in 2010 and 2011. According to graph (b), although adults had an
increase in access to mental health services from 2005 to 2007, and had a slight increase
between 2005 and 2008, both groups are experiencing a relative disparity in access to service
compared to CYF and TAY groups.
28
Figure 18. Superior region mental health access trends by older age group for all clients
obtaining services. Graph (a) shows the number of all clients by older age group and year of
service while the graph (b) shows the number of all clients as a proportion of the region’s
population for older age subgroups. Note that the older age group categories differ between the
two graphs (due to U.S. Census Bureau subdivision methods). The number of older adults
obtaining services (graph (a)) diminishes by increasing age, likely a result of both decreasing
lifespan and potentially a transfer to Medicare providers working outside the county system. The
youngest group, age 60-64, had the greatest relative access to mental health care services.
Access for this group increased through 2010, but then leveled off into 2011. However, when
normalized by the underlying population (graph (b)), it is still Individuals over the age of 65
appear to experience a relative disparity in access compared to the 60-64 year olds.
Superior region mental health access trends by race groups for all clients obtaining
services. Based on the CSI data, racial disparities are impossible to detect. When such a large
percentage of the race information is missing then all of the numbers must be considered
unreliable.
Counties of the Superior Region – Summaries of All Client Trends
Butte County
Overall, Butte County showed a general trend of increasing levels of access to mental health
services between 2005 and 2011. The CYF group had the overall highest rate of mental health
care access per 100,000 when compared to all other mental health client subgroups in the CSI
data. Other groups with overall increasing access were: Females, Males, TAY, Adults and Older
Adults. Notably, Older Adults had much lower access than the above mentioned groups per
100,000 population. In Butte County, race data were missing for 22-60% of the population over
the study period (average 50%), making racial disparities impossible to reliably detect.
Colusa County
In Colusa County, the primary group accessing mental health services is the adult age group.
Between 2005 and 2007 there was a very increase in the number and proportion of adults per
100,000 accessing services. Both the number and proportion doubled from 2005-2007. After
2007, however, the number and proportion of adults accessing services per 100,000 decreased
consistently through 2010. A general trend for the overall female population, and the CYF and
TAY age groups was a steady and steep increase in the proportion of individuals receiving
access between 2005 and 2008. Race data were missing for 8-55% of the population over the
study period (average 41%), making racial disparities impossible to reliably detect.
Del Norte County
In Del Norte County, while the numbers of individuals accessing services are understandably
lower than those observed in larger, more populated counties, the proportion of mental health
clients per 100,000 population are notably higher than those observed in many other counties
for males, females, CYF, TAY, adult, and several race subcategories. While the overall number
and proportion of clients accessing services in Del Norte County increased between 2005 and
2006, the trend for all groups in this county was one of decreasing access to services from 2007
to 2010. In Del Norte County, race data were missing for 7-56% of the population over the study
period (average 35%), making racial disparities impossible to reliably detect.
29
Glenn County
In Glenn County, the overall trend in the number and proportion of clients accessing mental
health services is one of steady increases from 2005 to 2008, accompanied by a leveling off
from 2008 to 2010. Similar trends were notable in the male, female, CYF, TAY, and Adult
subgroups. In Glenn County, race data were missing for 31-67% of the population over the
study period (average 56%), making racial disparities impossible to reliably detect.
Humboldt County
The trend for mental health services access in Humboldt County was similar for both sexes and
all age groups. From 2005 to 2006 there was a steep increase in access with a mild to
moderate decrease in 2007. The decrease was sustained until 2009 for Males, Females, Adults,
and the TAY group. Moderate to steep increases were seen between 2009 and 2010 in all
groups. But then significant decreases in access were seen for all groups in 2011 to levels that
were slightly above the baseline levels of 2005. The Older Adult group consistently had the least
access. In Humboldt County, race data were missing for 7-51% of the population over the study
period (average 39%), making racial disparities impossible to reliably detect.
Lake County
In Lake County, there were increases in access for all sex and age groups between 2005 and
2007, with the Older Adults having the lowest access. Between 2007 and 2008 the Older Adults,
TAY, and CYF groups saw moderate improvements in their access to mental health services.
From 2008 to 2010 all groups saw moderate to steep decreases. More access was
experienced in the county in 2011 for the TAY, CYF, and Female groups. By 2011, most groups
finished near baseline access levels of 2005. In Lake County, race data were missing for 0-53%
of the population over the study period (average 35%), making racial disparities impossible to
reliably detect.
Lassen County
During the first year after passage of the MHSA, Lassen County had increased levels of access
to mental health services for all age groups. While a dip or leveling in access was seen in 2007
and 2008, there was an increase in access in 2009 for all groups except Older Adults. The CYF
group had the greatest access and Older Adults had the least access. In Lassen County, race
data were missing for 65-94% of the population over the study period (average 86%), making
racial disparities impossible to reliably detect. In Lassen County, race data were missing for 65-
75% of the population over the study period (average 71%), making racial disparities impossible
to reliably detect.
Mendocino County
Mendocino County provided increased access to mental health services between 2005 and
2008/2009 (except for a dip for Adults and Older Adults in 2007). Then all groups except the
CYF and TAY groups showed a decline through 2011, below baseline levels (2005). The CYF
age group had the greatest access while Older Adults had the lowest overall access per
100,000 population. In Mendocino County, race data were missing for 16-54% of the population
over the study period (average 44%), making racial disparities impossible to reliably detect.
Modoc County
In Modoc County, the TAY age group has experienced significant increases in mental health
service access since the inception of the MHSA and enjoys by far the highest levels of access
per 100,000 population as compared to other groups. Although there was a decrease in access
from 2006 to 2007, the other age groups experienced increased access from 2007 through
30
2010. Access in 2010 is increased overall from the baseline year of 2005 in every age group,
and for Males and Females. Race data were missing for 14-60% of the Modoc County
population over the study period (average 47%), making racial disparities impossible to reliably
detect.
Nevada County
Access to mental health services in Nevada County across all age groups and sexes increased
in access between 2005 and 2006, followed by decreases from 2006 to 2007. Between 2007
and 2011, there were steady increases in access for all groups, ending at rates per 100,000
population that were well above baseline (2005) rates (except Older Adults). The CYF group
had the highest levels of access each year (except 2007) while the Older Adults had the lowest.
In Nevada County, race data were missing for 54-76% of the population over the study period
(average 67%), making racial disparities impossible to reliably detect.
Plumas County
In Plumas County, access to mental health services for age and sex groups remained relatively
level. The only changes of note seen in Plumas County include a large increase in access for
the CYF group from 2008 to 2010 with a concomitant decrease in service for the TAY group
during that period. However, both of these young age groups had the highest levels of access in
the county over the entire study period while Older Adults had the lowest levels of access. Race
data were missing for 12-60% of the population in Plumas County over the study period
(average 41%), making racial disparities impossible to reliably detect.
Shasta County
All age and sex groups in Shasta County experienced increased access between 2005 and
2006, decreased access between 2006 and 2007, and then increased access from 2007 to
2011 (except the CYF and Male groups). The CYF group experienced decreased access from
2008 to 2010, followed by an increase in 2011. The Male group saw a steady increase from
2007 to 2010, followed by a slight decrease during 2011. Consistent with the other counties of
this region, the CYF and TAY age groups had the greatest levels of access while Older Adults
had the lowest levels. In Shasta County, race data were missing for 18-56% of the population
over the study period (average 45%), making racial disparities impossible to reliably detect.
Sierra County
The CYF and TAY age groups both saw dramatic increases in access to mental health services
in Sierra County, the former from 2005 to 2008 and the latter from 2007-2010. The CYF group
had a decrease in access in 2008 to 2010, ending at a level substantially higher than baseline
(2005). While the Older Adult age group had the lowest access to services in this county, the
rate of access per 100,000 population was steady with an overall increase by 2010. In Sierra
County, race data were missing for 35-76% of the population over the study period (average
59%), making racial disparities impossible to reliably detect.
Siskiyou County
In Siskiyou County, all age groups had immediate increases in access between 2005 and 2007.
The TAY group continued the trend of increasing access through 2010. For the CYF, Adult and
Older Adult age groups, a leveling or a slower increased in access was seen by 2010, but
remained above baseline levels (2005). In Siskiyou County, race data were missing for 2-43%
of the population over the study period (average 29%), making racial disparities impossible to
reliably detect.
31
Tehama County
For all age groups and sexes, there was increased access to mental health services from
inception of the MHSA through 2006. The trend continued for the Adult and Female groups until
2008, and for the TAY and Older Adult groups through 2010. Despite a virtual leveling in access
from 2006-2009 for CYF and Males, these groups experienced increased access in 2010 and
had much higher levels in 2010 compared to baseline (2005). The TAY group had the highest
level of access over the course of the study period (except 2005) while the Older Adults had the
lowest access from 2005-2011. In Tehama County, race data were missing for 42-69% of the
population over the study period (average 63%), making racial disparities impossible to reliably
detect.
Trinity County
There does not appear to be a discernable pattern to mental health service access in Trinity
County. Over the study period, the county experienced ups and down in the different age
groups and ended in 2010 with access levels near or below baseline (2005). Similar to other
counties in the region, the CYF and TAY groups had by far the highest levels of access and the
Older Adult group had the lowest levels. In Trinity County, race data were missing for 6-55% of
the population over the study period (average 39%), making racial disparities impossible to
reliably detect.
Superior Region Summary – New Clients
New clients received increased access to mental health services in the Superior Region from
2005 to 2006 with few exceptions (Del Norte, Glenn and Plumas for a few population
subgroups). On average, access for these previously unserved clients remained steady during
the study period and then declined some in 2011. However, there were some counties that
showed consistent increases in access throughout the study period (Butte, Modoc and Shasta).
Males and females had similar trends with females showing slightly higher levels of access. For
age groups, the CYF and TAY groups had the highest proportion of access per 100,000
population and the older adults had the lowest.
Superior Region Summary – All Clients
All Clients of both sexes and all age groups received increased access to mental health
services in the Superior Region from 2005 to 2006 in most counties, with few exceptions (e.g.,
Plumas). The increasing trend in access continued into later years in number of counties for the
TAY and CYF age groups (Glenn, Lake, Mendocino, Sierra, Siskiyou). The TAY and CYF
groups consistently experienced the highest level of access within counties across the Superior
Region. On average, access for All Clients remained steady during the study period, finishing off
at levels similar to those seen at baseline (2005). However, there were some counties that
showed consistent increases in access throughout the study period (Butte and Modoc). Males
and females had similar trends with females showing slightly higher levels of access. For age
groups, the CYF and TAY groups had the highest proportion of access per 100,000 population
and the older adults had the lowest.
Superior Region Summary – All Data
The mental health services act appears to have increased access to mental health services for
both new and all clients in the early days of its inception. Several counties continued to develop
higher levels of access (Butte, Modoc and Shasta) throughout the study period. CYF and TAY
age groups experienced the highest levels of access while older adults had the lowest levels. By
the end of the study period, the overall level of access for all clients was at or near baseline –
reflecting no net change over time.
32
Bay Area Region
The Bay Area Region includes 12 counties
in the northwestern part of the state.
New Clients
Figure 19. Bay Area mental health access trends for the total population of new clients
obtaining services. Graph (a) shows frequencies or the actual number of new clients by year
of service while graph (b) shows the number of new clients as a proportion of the region’s
overall population. Both graphs in this case indicate that there was a small increase in access to
mental health services in 2006 (2007 for graph (b)), followed by a slow decline through 2011.
33
Figure 20. Bay Area mental health access trends by sex for new clients obtaining
services. Graph (a) shows the number of new clients by sex and year of service while graph (b)
shows the number of new clients as a proportion of the region’s population for sex subgroups.
Both graphs indicate increased access for males and females from the baseline year (2005) to
2006 but then a slow decline through 2011. Male and female clients have near identical access
to mental health services.
Figure 21. Bay Area mental health access trends by age group for new clients obtaining
services. Graph (a) shows the number of new clients by age group and year of service while
graph (b) shows the number of new clients as a proportion of the region’s population for age
subgroups. According to graph (a), the number of children, ages 0 to 15, that comprise the
Children, Youth and Families (CYF) group, experienced virtually no change in numbers
accessing mental health services over the study period. Transitional age youth (TAY), defined
as the population age 16 to 25, experienced an increase from 2005 to 2006, but little change
thereafter. The adult population, ages 26-59, comprise the dominant users (by overall numbers
of new clients) of mental health services in the Bay Area region and experienced increased
access from the baseline year (2005) through 2008, but then experienced a decline in total
numbers of new clients from 2008 to 2011. Older adults, those ages 60 plus, have the fewest
numbers of new clients accessing mental health services in the Bay Area region and no
discernable trend over the study period is seen. When reviewing the proportions accessing
services by age group in graph (b), all age groups followed a similar trend with increased
access during the 2005 to 2006 period, levelling through 2010 and then a decline in 2011 to
baseline numbers. Among all age groups, the TAY enjoys the greatest proportional access to
mental health services in the region. Both adult and older adult groups are experiencing a
relative disparity in access to service compared to CYF and TAY groups.
34
Figure 22. Bay Area mental health access trends by older age group for new clients
obtaining services. Graph (a) shows the number of new clients by older age group and year of
service while the graph (b) shows the number of new clients as a proportion of the region’s
population for older age subgroups. Note that the older age group categories differ between the
two graphs (due to U.S. Census Bureau subdivision methods). Nonetheless, the trends are
clear. The number of older adults obtaining services (graph (a)) diminishes by increasing age,
likely a result of both decreasing lifespan and potentially a transfer to Medicare providers
working outside the county system. However, when normalized by the underlying population
(graph (b)), it is still the youngest group, age 60-64, that have the greatest relative access to
mental health care services. Access for this group increased through 2007, but then decreased
steadily through 2010 with some recovery in 2011. Individuals over the age of 65 appear to
experience a relative disparity in access compared to the 60-64 year olds and also have a
general trend toward steady or declining access over most of the study period.
Bay Area Region mental health access trends by race groups for new clients obtaining
services. Based on the CSI data, racial disparities are impossible to detect. When such a large
percentage of the race information is missing then all of the numbers must be considered
unreliable. Table 6 below indicates the percentages of the total dataset missing race information
by year.
Table 6. Summary of CSI data by year for new clients in the Bay
Area Region indicating the percentage of observations with race
information that is unknown or missing
Year Race Known Race Unknown P e rcentage of Race
or Missing Unknown or Missing
2005 34,945 7,074 17%
2006 28,484 22,114 44%
2007 14,593 33,569 70%
2008 14,123 35,975 72%
2009 12,345 36,565 75%
2010 10,142 37,380 79%
2011 9,002 35,489 80%
2012 3,700 15,877 81%
35
Counties of the Bay Area Region – Summaries of New Client Trends
Alameda County
Alameda County showed significant and steady increases in mental health services access for
all sexes and age groups (except older adults) from 2005 to 2009/2010. All groups saw some
decline in 2011. While older adults did see increases in access, they peaked in 2008, then
slowly declined. Nevertheless, the level of access in 2011 was still well above baseline (2005)
for this group. In Alameda County, race data were missing for 6-80% of the population over the
study period (average 61%), making racial disparities impossible to reliably detect.
Contra Costa County
In Contra Costa County, the only group to see moderate increases in access to mental health
services was the TAY group. However, between 2010 and 2011, access for this age group
declined. The general trend for other age groups, both sexes and the total population was a mild
increase in access between 2005 and 2011. In Contra Costa County, race data were missing for
7-81% of the population over the study period (average 61%), making racial disparities
impossible to reliably detect.
Marin County
In Marin County, all age and sex groups had ups and downs during the study period. Initial
increases in access were seen for all groups between 2005 and 2006. Sharp declines in access
were seen in 2007 for the older adults and in 2008 for all others, with good recovery in 2009.
The older adult age group reached a peak level of access in 2010 as did the TAY group. Still,
older adults suffered a relative disparity in access as compared to all other groups. Additionally,
In Marin County, race data were missing for 8-79% of the population over the study period
(average 61%), making racial disparities impossible to reliably detect.
Monterey County
All sex and age groups in Monterey County show similar trends, in which access to mental
health services increases steadily through 2008, dips significantly in 2009 and then recovers
somewhat in 2010. However, declines in access occur between 2010 and 2011. The CYF and
TAY groups had the greatest proportional access (per 100,000 population) in the county while
the older adults had the lowest access. In Monterey County, race data were missing for 3-86%
of the population over the study period (average 66%), making racial disparities impossible to
reliably detect.
Napa County
In Napa County, the CYF group had a stark increase (>300%) in access to services between
2005 and 2011 (other than a small dip in 2008). In addition, the older age group had a general
trend toward increased access over the study period. The other groups: TAY, adults, males and
females had increased access between 2005 and 2006/2007, declines in 2008 and recovery by
2011. In Napa County, race data were missing for 58-96% of the population over the study
period (average 83%), making racial disparities impossible to reliably detect.
San Benito County
Mental health services access in San Benito County increased significantly for all age groups
between 2005 and 2007. Declines were seen to 2009 with recovery in 2010 (except for older
adults whose access remained steady in 2010). In San Benito County, race data were missing
36
for 0-96% of the population over the study period (average 77%), making racial disparities
impossible to reliably detect.
San Francisco County
In San Francisco County, all age (except older adults) and sex groups saw a trend toward
increasing access to services between 2005 and 2006, but then trended toward lower levels of
service than baseline by 2011. Older adults had an up and down pattern each year with little net
change until 2011 when a significant increase in access can be seen. In this county, CYF and
TAY age groups have the greatest access while older adults have the lowest access. Men
access services at a higher proportional rate than women. In San Francisco County, race data
were missing for 15-79% of the population over the study period (average 62%), making racial
disparities impossible to reliably detect.
San Mateo County
The TAY age group has by far the greatest proportional access to mental health services than
any other age or sex group. Other than older adults, all age and sex groups demonstrate overall
increases in access to 2009 with a small decline in 2010. The older adults had increases in
access in 2006, but a sharp decline in 2007. After a recovery in 2008, the levels of access
remained steady through the study period. In San Mateo County, race data were missing for 33-
89% of the population over the study period (average 76%), making racial disparities impossible
to reliably detect.
Santa Clara County
Every age and sex group in Santa Clara County experienced sharp decreases in access to
mental health services between 2005 and 2007. The rate of decline slowed, but the trend of
decreasing access continued through 2011. In Santa Clara County, race data were missing for
30-59% of the population over the study period (average 43%), making racial disparities
impossible to reliably detect.
Santa Cruz County
Mental health access increased for all sex and age groups between 2005 and 2006 and for
most groups increased again in 2007 (except TAY and older adults groups). From 2007 to 2010,
decreases in access were seen for TAY, Adult, Male and Female groups. All groups recovered
in 2011 to levels above baseline, except for the TAY group, which although access increased in
2011, it did not return to baseline (2005) levels. The older adult group had the lowest overall
access, but had the most consistent improvement in access over the study period. In Santa
Cruz County, race data were missing for 2-80% of the population over the study period (average
60%), making racial disparities impossible to reliably detect.
Solano County
The general trend in mental health access for age and sex groups in Solano County was toward
increased access to 2008 and then declines to baseline by the end of the study period. Only the
CYF group showed significant increases in access from 2005 to 2011. Older adults had the
lowest access to services overall. In Solano County, race data were missing for 12-85% of the
population over the study period (average 67%), making racial disparities impossible to reliably
detect.
Sonoma County
In Sonoma County, increased access can be seen between 2005 and 2006. While there are a
few ups and downs between 2006 and 2011, the overall trend appears relatively flat with slightly
37
increased access for all groups by 2011. The In Sonoma County, race data were missing for 9-
83% of the population over the study period (average 65%), making racial disparities impossible
to reliably detect.
All Clients
Figure 23. Bay Area region mental health access trends for the total population of all
clients obtaining services. Graph (a) shows frequencies or the actual number of all clients by
year of service while graph (b) shows the number of all clients as a proportion of the Bay Area’s
overall population. Both graphs in this case indicate that there was an increase in access to
mental health services in 2006, and then a leveling off in the number of clients and client access
through 2010, before both decreased between 2010 and 2011. By 2011, Bay Area access to
mental health services returned to levels that were below initial baseline (2005) levels. Data for
2012 were incomplete and are therefore not reliable.
Figure 24. Bay Area region mental health access trends by sex for all clients obtaining
services. Graph (a) shows the number of all Bay Area clients by sex and year of service while
graph (b) shows the number of all clients as a proportion of the Bay Area’s population for sex
subgroups. Graph (a) indicates increased access for males and females from the baseline year
(2005) to 2006, and then a decrease between 2006 and 2007. Between 2009 and 2011, there
were decreases in the number of both male and female clients. Graph (b) portrays a general
38
increase from baseline (2005) to 2008. The decline continued for females in the Bay Area into
2011, while there was a leveling off in access among males between 2010-2011.
Figure 25. Bay Area region mental health access trends by age group for all clients
obtaining services. Graph (a) shows the number of all clients by age group and year of service
while graph (b) shows the number of all Bay Area clients as a proportion of the region’s
population for age subgroups. According to graph (a), the number of children, ages 0 to 15, that
comprise the CYF age group, were accessing mental health services at an increased from 2005
to 2006, remained relatively level from 2006 to 2009, and then decreased in 2010 and 2011.
Transitional age youth (TAY), defined as the population age 16 to 25, also experienced
increased numbers accessing services from the inception of the MHSA to 2006, but then there
was a virtual leveling off in the numbers through 2011. The adult population, ages 26-59,
comprise the dominant users (by overall numbers of clients) of mental health services in the
region and experienced increased access in 2006, but saw little change between 2006 and
2009, when a decline began and lasted into 2011. Older adults, those ages 60 plus, have the
fewest numbers of clients accessing mental health services in the Bay Area and no discernible
trend over the study period is seen. When reviewing the proportions accessing services by age
group in graph (b), all groups showed increasing access between 2005 and 2006. The CYF and
TAY age groups remained relatively stable over the remainder of the study period. After the
increase in the initial year post MHSA initiation, the adult age group experienced a slow and
steady decrease in access over the study period.
39
Figure 26. Bay Area region mental health access trends by older age group for all clients
obtaining services. Graph (a) shows the number of all clients by older age group and year of
service while the graph (b) shows the number of all clients as a proportion of the region’s
population for older age subgroups. Note that the older age group categories differ between the
two graphs (due to U.S. Census Bureau subdivision methods). The number of older adults
obtaining services (graph (a)) diminishes by increasing age, likely a result of both decreasing
lifespan and potentially a transfer to Medicare providers working outside the county system. The
youngest group, age 60-64, had the greatest relative access to mental health care services.
Access for this group increased through 2010, but then leveled off into 2011. However, when
normalized by the underlying population (graph (b)), it is still Individuals over the age of 65
appear to experience a relative disparity in access compared to the 60-64 year olds.
Bay Area Region mental health access trends by race groups for all clients obtaining
services. Based on the CSI data, racial disparities are impossible to detect. When such a large
percentage of the race information is missing then all of the numbers must be considered
unreliable.
Counties of the Bay Area Region – Summaries of All Client Trends
Alameda County
Alameda County showed significant and steady increases in mental health services access for
all sexes and age groups (except Older Adults) from 2005 to 2009/2010. All groups saw some
decline in 2011. While older adults did see increases in access, they peaked in 2009, then
slowly declined. Nevertheless, the level of access in 2011 was still well above baseline (2005)
for this group, as well as all other groups. In Alameda County, race data were missing for 7-64%
of the population over the study period (average 46%), making racial disparities impossible to
reliably detect.
Contra Costa County
In Contra Costa County, all groups saw a general increasing trend in access to mental health
services between the baseline 2005 and 2011. For TAY, despite a decrease in access from
2010 to 2011, the group had the highest access to mental health services of all groups over the
course of the study. Older Adults had the lowest level of access. In Contra Costa County, race
data were missing for 4-54% of the population over the study period (average 39%), making
racial disparities impossible to reliably detect.
Marin County
In Marin County, all age and sex groups had ups and downs resembling an “m-shaped” trend
during the study period. Initial increases in access were seen for all groups between 2005 and
2006 (2007 for TAY), followed by intermittent decreases and increases. Over the course of the
study period (2005-2011), a general declining trend was seen in all age groups and sexes
except for Older Adults. The Older Adult age group suffered a relative disparity in access as
compared to all other groups, while the TAY group had the great level of access. In Marin
County, race data were missing for 3-44% of the population over the study period (average
29%), making racial disparities impossible to reliably detect.
40
Monterey County
All sex and age groups (except Older Adults) in Monterey County show similar trends, in which
access to mental health services increases steadily through 2008, and then decreases between
2008 and 2011, back to levels that are not much higher than those seen at baseline (2005). The
CYF and TAY groups had the greatest proportional access (per 100,000 population) in
Monterey county while the older adults had the lowest access. Race data were missing for 2-
51% of the Monterey County population over the study period (average 37%), making racial
disparities impossible to reliably detect.
Napa County
In Napa County, there were no discernible trends in access to mental services in any of the sex
and age groups with the exception of CYF. The CYF age group saw a steep increase in access
over the study period, and attained levels of access far above those of all other age and sex
groups. The Older Age group had lower levels of access to mental health services than all other
groups and finished at a level that was lower than those experienced at baseline (2005). In
Napa County, race data were missing for 54-75% of the population over the study period
(average 67%), making racial disparities impossible to reliably detect.
San Benito County
Mental health services access in San Benito County increased substantially for all age groups
and sexes between 2005 and 2008 (2010 for TAY). Declines were seen to 2009 with recovery in
2010 (except for older adults whose access continued to decrease slightly in 2010). The Older
Age group experienced the greatest disparity in mental health services when compared to all
other age groups and sexes. In San Benito County, race data were missing for 0-67% of the
population over the study period (average 51%), making racial disparities impossible to reliably
detect.
San Francisco County
In San Francisco County, all age (except TAY and Older Age) and sex groups saw a trend
toward increasing access to services between 2005 and 2006, but then trended toward lower
levels of service than baseline by 2011. TAY and Older Adult age groups had an up and down
(“M”) pattern with little net change until 2010 and 2011, respectively, when a steep decrease in
access can be seen. In San Francisco County, the CYF age group has the greatest access.
Men access mental health services at a higher proportional rate than women. Race data were
missing for 18-57% of the San Francisco County population over the study period (average
41%), making racial disparities impossible to reliably detect.
San Mateo County
In San Mateo County, the TAY age group has by far the greatest proportional access to mental
health services than any other age or sex group. Other than older adults, all age and sex groups
demonstrate overall increases in access to 2009/2010 with a decline in 2011. The older adults
had increases in access in 2006, but a sharp decline in 2007. After a recovery in 2008, and an
additional increase in 2009, the levels of access decreased again in 2011. Over the course of
the study period, most age and sex groups finished only slightly above baseline (2005) access
levels. In San Mateo County, race data were missing for 35-67% of the population over the
study period (average 60%), making racial disparities impossible to reliably detect.
Santa Clara County
Every age and sex group in Santa Clara County experienced sharp decreases in access to
mental health services between 2005 and 2007. The rate of decline slowed, but the trend of
41
decreasing access continued through 2011. The CYF age group had substantially lower access
than all other age and sex groups between 2007 and 2011. In Santa Clara County, race data
were missing for 50-69% of the population over the study period (average 61%), making racial
disparities impossible to reliably detect.
Santa Cruz County
In Santa Cruz County, mental health access increased for all sex and age groups between 2005
and 2006 and for most groups increased again in 2007 (except TAY and Older Age groups).
From 2007 to 2010, decreases in access were seen for TAY, Adult, Male and Female groups.
All groups recovered in 2011 to levels above baseline, except for the TAY group, which did not
return to baseline (2005) levels. The older adult group had the lowest overall access, but had
the most consistent improvement in access between 2005-2011. In Santa Cruz County, race
data were missing for 1-50% of the population over the study period (average 36%), making
racial disparities impossible to reliably detect.
Solano County
The general trend in mental health access for age and sex groups in Solano County was toward
increased access to 2008 and then declines to levels below baseline (2005) by the end of the
study period. Only the CYF group showed substantial increases in access from 2005 to 2011.
Older adults had the lowest access to services overall. In Solano County, race data were
missing for 11-53% of the population over the study period (average 40%), making racial
disparities impossible to reliably detect.
Sonoma County
Increased access can be seen between 2005 and 2006 in Sonoma County. While there are a
few increases and decreases between 2006 and 2011, the overall trend appears relatively flat,
except for the CYF age group which finishes a bit above baseline (2005) levels. The In Sonoma
County, race data were missing for 10-52% of the population over the study period (average
40%), making racial disparities impossible to reliably detect.
Bay Area Region Summary – New Clients
In the Bay Area Region, the overall trend was toward increasing access to mental health
services for new clients (previously unserved) between 2005 and 2006 (except Santa Clara
County). Overall, males had higher levels of access than females, but not significantly so. For
age groups, the TAY age group had the highest levels of access for the region and for most
counties (except Monterey, Napa and Solano) and older adults had the lowest levels (except in
Napa). Of interest, Napa County had very similar levels of access for all groups except the CYF
group which had higher levels of access. They were one of the few counties in which the older
adult age groups did not consistently have the lowest levels of access. Santa Clara County had
a dramatic reduction in access for new clients from 2005 to 2007 which then slowed through the
remained of the study period.
Bay Area Region Summary – All Clients
In the Bay Area Region, the overall trend was toward increasing access to mental health
services for all clients (previously served) between 2005 and 2006 with one exception (Santa
Clara County). Overall, males had slightly higher levels of access than females across the study
period. For age groups, the TAY age group had the highest levels of access for the region and
for most counties (except Santa Cruz, San Francisco) and older adults had the lowest levels
(except in San Francisco). Of interest, Napa County had relatively stable levels of access for all
groups except the CYF group which had higher levels of access, with a steep increase between
42
2007 and 2011. San Francisco was one of the few counties in which the Older Adult age groups
did not consistently have the lowest levels of access. Santa Clara County had a dramatic
reduction in access for all clients from 2005 to 2011.
Bay Area Region Summary – All Data
In the first years of the MHSA a significant increase in access was seen for new and all clients.
Males tended to have slightly higher access than females and the TAY age group had the
highest levels of access overall. Of interest, for Older Adults, Napa County showed
comparatively higher rates of access for the previously unserved and San Francisco had higher
levels of access for all older adults. Santa Clara County had dramatic reductions in access over
the study period showing a geographic disparity for this county.
Central Region
The Central Region
includes 20 counties in the
central valley of California.
New Clients
43
Figure 27. Central mental health access trends for the total population of new clients
obtaining services. Graph (a) shows frequencies or the actual number of new clients by year
of service while graph (b) shows the number of new clients as a proportion of the region’s
overall population. Both graphs in this case indicate that there was an increase in access in
2006 that remained relatively steady through 2008 and then a steep decline in access for this
region’s population through 2011.
Figure 28. Central mental health access trends by sex for new clients obtaining services.
Graph (a) shows the number of new clients by sex and year of service while graph (b) shows
the number of new clients as a proportion of the region’s population for sex subgroups. Both
graphs indicate increased access for males and females from the baseline year (2005) to 2008.
Access then significantly declined through 2011. Male and female clients have near identical
access to mental health services.
Figure 29. Central mental health access trends by age group for new clients obtaining
services. Graph (a) shows the number of new clients by age group and year of service while
graph (b) shows the number of new clients as a proportion of the region’s population for age
subgroups. According to graph (a), the number of children, ages 0 to 15, that comprise the
Children, Youth and Families (CYF) group, experienced some small increases in services to
44
new clients between 2005 and 2008, but then declined to below 2005 levels by 2011.
Transitional age youth (TAY), defined as the population age 16 to 25, experienced the same
pattern as the CYF group. The adult population, ages 26-59, comprise the dominant users (by
overall numbers of new clients) of mental health services in the Central region and experienced
greater increases in the number of new clients accessing services than other age groups.
However, this group also experienced the sharpest decline in access beginning in 2009 and
continuing through 2011. Older adults, those ages 60 plus, have the fewest numbers of new
clients accessing mental health services in the Central region and no discernable trend over the
study period is seen. When reviewing the proportions accessing services by age group in graph
(b), all age groups experienced increased access between 2005 and 2006. The TAY group
peaked in 2007 and then began a decline to baseline by 2011. The CYF age group had peak
access in 2008 but by 2011 had lower levels of access than in 2005. Adults had a slower
increase in access between 2005 and 2008, but then declined to below baseline levels by 2011.
Older adults saw little overall change in access over the study period. Among all age groups,
both the CYF and TAY groups have similar proportional access to mental health services in the
region. However, according to graph (b), the adult and older adult groups are experiencing a
relative disparity in access to service compared to CYF and TAY groups.
Figure 30. Central mental health access trends by older age group for new clients
obtaining services. Graph (a) shows the number of new clients by older age group and year of
service while the graph (b) shows the number of new clients as a proportion of the region’s
population for older age subgroups. Note that the older age group categories differ between the
two graphs (due to U.S. Census Bureau subdivision methods). Nonetheless, the trends are
clear. The number of older adults obtaining services (graph (a)) diminishes by increasing age,
likely a result of both decreasing lifespan and potentially a transfer to Medicare providers
working outside the county system. However, when normalized by the underlying population
(graph (b)), it is still the youngest group, age 60-64, that has the greatest relative access to
mental health care services. Access for this group increased between 2005 and 2006, but then
experienced ups and downs so that by 2011 access was just slightly over baseline levels. In the
75-84 year old age group, there were large increases in access in 2008 through 2010, but this
effect returned to baseline by 2011. The oldest age group (85+ years) continued to have the
lowest overall access to mental health services during the study period.
45
Central Region mental health access trends by race groups for new clients obtaining
services. Based on the CSI data, racial disparities are impossible to detect. When such a large
percentage of the race information is missing then all of the numbers must be considered
unreliable. Table 7 below indicates the percentages of the total dataset missing race information
by year.
Table 7. Summary of CSI data by year for new clients in the Central
Region indicating the percentage of observations with race
information that is unknown or missing
Year Race Known Race Unknown P e rcentage of Race
or Missing Unknown or Missing
2005 30,347 5,297 15%
2006 24,365 21,307 47%
2007 14,482 32,410 69%
2008 12,948 34,594 73%
2009 9,143 28,043 75%
2010 8,028 27,610 77%
2011 5,443 22,829 81%
2012 2,070 10,475 83%
Counties of the Central Region – Summaries of New Client Trends
Alpine County
The only age group in Alpine County that did not have an increase in mental health access
between 2005 and 2006 was the CYF group. However, the CYF group did see a significant
increase in access in 2007 and 2008. By 2010, however, the levels were significantly below
baseline. Similarly for the TAY and Adult age groups, the level of access seen in 2010 was
lower than in 2005. The older adult group, on the other hand, had a net increase in access
between 2005 and 2010. In Alpine County, race data were missing for 0-100% of the population
over the study period (average 69%), making racial disparities impossible to reliably detect.
Amador County
In Amador County, the CYF, TAY and Adult age groups had increased access between 2005
and 2007. The TAY group continued to have significant gains in access by 2010, surpassing the
baseline level by >400%. The CYF group had a decline in 2008 but recovered in 2009 and
2010. Similarly, adults declined in 2009 with recovery in 2010. The older adults showed modest
positive increases in access in 2007 and 2010, but remained the lowest access age group
throughout the study period. In Amador County, race data were missing for 8-87% of the
population over the study period (average 61%), making racial disparities impossible to reliably
detect.
Calaveras County
All age groups in Calaveras saw significantly escalating levels of access to mental health
services between 2005 and 2010. Only the older adult group had a slower increase. In
Calaveras County, race data were missing for 5-95% of the population over the study period
(average 67%), making racial disparities impossible to reliably detect.
46
El Dorado County
A trend of increased access to 2008, followed by decreased access was seen for Adults, Males
and Females. While older adults had year to year variations in access, the overall trend was low
access with no net increase or decrease over the study period. The greatest levels of mental
health care was seen for CYF and TAY groups with strong increases in access from 2005 to
2007, followed by a decline. In El Dorado County, race data were missing for 7-87% of the
population over the study period (average 69%), making racial disparities impossible to reliably
detect.
Fresno County
The following groups in Fresno County experienced increased access to mental health services
in the first year after implementation of the MHSA (2005-2006): TAY, CYF, Males, Females,
Adults and Older Adults. However, these groups joined all other groups in a significant
decreasing trend in access for the balance of the study period. In Fresno County, race data
were missing for 29-78% of the population over the study period (average 67%), making racial
disparities impossible to reliably detect.
Inyo County
Despite a few declines in access, the general trend for all age groups in Inyo County was one of
increased access to services. Peak years were 2008 and 2009. However, all age groups had
lower levels of service in 2010 than at baseline (2005). In Inyo County, race data were missing
for 13-86% of the population over the study period (average 63%), making racial disparities
impossible to reliably detect.
Kings County
Both sexes and all age groups (except older adults) had lower levels of access in 2011 than in
2005. Only Females, CYF and Older Adult groups saw an increase in access with the inception
of the MHSA between 2005 and 2006. In Kings County, race data were missing for 7-80% of the
population over the study period (average 62%), making racial disparities impossible to reliably
detect.
Madera County
Increased access to mental health services was seen in Madera County with the inception of
the MHSA (2005 to 2006) for CYF, TAY, and Older Adult age groups as well as for both sexes.
Adults did not see an increase in services until 2007. All groups experienced declining levels of
access from 2007 to 2009/2010 with mild upswings in access in 2011. The CYF and TAY age
groups have the highest levels of access in the county and the older age group has the lowest
levels – indicating a relative disparity in access. In Madera County, race data were missing for
1-86% of the population over the study period (average 66%), making racial disparities
impossible to reliably detect.
Mariposa County
In Mariposa County all age groups experience increases and decreases in access to services
over the study period. However, all groups had some increase between 2005 and 2006 and all
but the older adults had significant increases in 2010 to peak levels. The older age group had a
small net decrease in access. In Mariposa County, race data were missing for 14-90% of the
population over the study period (average 67%), making racial disparities impossible to reliably
detect.
47
Merced County
In Merced County, the following groups had significantly increasing levels of service access
from 2005 to 2008: TAY, Adults, Females, and Males. By 2010, all of these groups returned to
baseline levels of access which then leveled off. Both the CYF and Older Adult groups also had
increases in access, but more modest in nature. They too had declines in access by 2011. On
significant different seen in this county as compared to others is that the access for adults is
high and access for the CYF group is lower – a relative disparity. In Merced County, race data
were missing for 7-75% of the population over the study period (average 54%), making racial
disparities impossible to reliably detect.
Mono County
The younger age groups, CYF and TAY, in Mono County had dramatic increases in access from
2005 to 2010. While the adult and older adult age groups also ultimately had increased access
by 2010, the increase was more modest. In Mono County, race data were missing for 6-97% of
the population over the study period (average 79%), making racial disparities impossible to
reliably detect.
Placer County
Although both sexes and all age groups had gains in mental health services access in 2006 and
2007, the overarching trend for this county was a decline in access through 2011 to below
baseline levels. In Placer County, race data were missing for 74-96% of the population over the
study period (average 92%), making racial disparities impossible to reliably detect.
Sacramento County
Sacramento had moderately increasing mental health access for both sexes and all age groups
from 2005 to 2008, but then saw sharp declines through 2010 to near or below baseline levels.
In Sacramento County, race data were missing for 3-73% of the population over the study
period (average 56%), making racial disparities impossible to reliably detect.
San Joaquin County
In San Joaquin County, the TAY group has by far the greatest levels of access to services and
saw steep increases between 2005 and 2008 after the implementation of the MHSA. Older
adults had much lower access than other age and sex groups and saw declining service access
over the study period, indicating a relative disparity. The other groups – CYF, Adults, Females
and Males – had increased access from 2005 to 2007 and maintained that higher level of
access through 2011. In San Joaquin County, race data were missing for 6-78% of the
population over the study period (average 59%), making racial disparities impossible to reliably
detect.
Stanislaus County
While all sex and age groups experienced greater access to mental health services between
2005 and 2006, only CYF, TAY, Female, and Male groups continued that trend through the
entire study period. For Adults and Older Adults, the initial gains in access declined some.
Adults still had greater access in 2011 than in 2005, but the older adults had significant declines
in access. In Stanislaus County, race data were missing for 8-83% of the population over the
study period (average 65%), making racial disparities impossible to reliably detect.
48
Sutter/Yuba County
Sutter and Yuba counties showed steep increases in service access for all ages and sexes
throughout the study period .In Sutter/Yuba County, race data were missing for 44-85% of the
population over the study period (average 75%), making racial disparities impossible to reliably
detect.
Tuolumne County
The TAY, Adult and Older Adult age groups all experienced increased access from 2005 to
2008 with a levelling off from 2008-2010. The CYF age group had a rather steep incline in the
first year (2005 to 2006), followed by a steep drop through 2009 with moderate recovery in
2010. Older adults suffer a relative disparity compared to other age groups. In Tuolumne
County, race data were missing for 1-79% of the population over the study period (average
59%), making racial disparities impossible to reliably detect.
Tulare County
While Tulare County experienced ups and downs in access to mental health services from 2005
to 2011, the general trend is toward increased access. The CYF group has significantly higher
levels of access than other groups and the Older Adults have significantly less access –
indicating relative disparities. In addition, the adult age group also appears to have less access
than expected, producing a disparity. In Tulare County, race data were missing for 39-91% of
the population over the study period (average 78%), making racial disparities impossible to
reliably detect.
Yolo County
The pattern of service access in Yolo County looks like the letter ‘M” with two large peaks,
indicating increased levels of access, in 2007 and 2010. There is a significant valley between
those peaks (except for adults) during 2009. Access levels decline again in 2011, but remained
above baseline levels. In Yolo County, race data were missing for 2-90% of the population over
the study period (average 66%), making racial disparities impossible to reliably detect.
All Clients
Figure 31. Central region mental health access trends for the total population of all
clients obtaining services. Graph (a) shows frequencies or the actual number of all Central
Region clients by year of service while graph (b) shows the number of all clients as a proportion
of the Central Region’s overall population. Both graphs in this case indicate that there was an
49
increase in access to mental health services from 2005 and 2006, with the number and
proportion of clients leveling off between 2006 and 2008. Then, between 2008 and 2011,
Central Region access to mental health services decreased steadily and ended well below
baseline levels (2005). Data for 2012 were incomplete and are therefore not reliable.
Figure 32. Central region mental health access trends by sex for all clients obtaining
services. Graph (a) shows the number of all Central Region clients by sex and year of service
while graph (b) shows the number of all clients as a proportion of the Central Region’s
population for sex subgroups. Graphs (a) and (b) indicate increased access for males and
females from the baseline year (2005) to 2006. Between 2006 and 2008, the number and
proportion of both male and female clients remained relatively stable, and then decreased
steadily between 2008 and 2011, finishing with numbers and proportions that were well below
the 2005 baseline.
Figure 33. Central region mental health access trends by age group for all clients
obtaining services. Graph (a) shows the number of all Central Region clients by age group
and year of service while graph (b) shows the number of all Central Region clients as a
proportion of the region’s population for age subgroups. Data were incomplete for 2012.
According to graph (a), the number of children, ages 0 to 15, that comprise the CYF age group,
experienced an increase in numbers accessing mental health services from 2005 to 2006, a
leveling off in numbers between 2006 and 2008, and a steady decrease between 2008 and
2011. Transitional age youth (TAY), defined as the population age 16 to 25, slightly increased
50
numbers accessing services from the inception of the MHSA to 2008, but then there was a slow
by steady decrease in the numbers from 2008 through 2011. The adult population, ages 26-59,
comprise the dominant users (by overall numbers of clients) of mental health services in the
region and experienced increased access through 2008, but saw a steady and steep decline
from 2008 to 2011. Older adults, those ages 60 plus, have the fewest numbers of clients
accessing mental health services in the Central region and no discernible trend over the study
period is seen. When reviewing the proportions accessing services by age group in graph (b),
the CYF group showed cyclical increases and decreases from 2005 to 2008, followed by a
steady decrease from 2008 through 2011. For 2008 through 2011, the CYF group had the
highest proportional levels of access among all age groups to the mental health system. The
TAY group had increased access from 2005 to 2008, but then declined through 2011, well
below baseline (2005) levels. According to graph (b), although adults had an increase in access
to mental health services from 2005 to 2008, they had a steep decrease in access from 2008 to
2011. Older adults had somewhat stable access between 2005 and 2009, followed by a
decrease between 2010 and 2011. Both adults and older adults are experiencing a relative
disparity in access to service compared to CYF and TAY groups.
Figure 34. Central region mental health access trends by older age group for all clients
obtaining services. Graph (a) shows the number of all Central Region clients by older age
group and year of service while the graph (b) shows the number of all Central Region clients as
a proportion of the region’s population for older age subgroups. Note that the older age group
categories differ between the two graphs (due to U.S. Census Bureau subdivision methods).
The number of older adults obtaining services (graph (a)) diminishes by increasing age, likely a
result of both decreasing lifespan and potentially a transfer to Medicare providers working
outside the county system. The youngest group, age 60-64, had the greatest relative access to
mental health care services. Access for this group increased through 2010, but then leveled off
into 2011. However, when normalized by the underlying population (graph (b)), individuals over
the age of 65 appear to experience a relative disparity in access compared to the 60-64 year
olds.
Central Region mental health access trends by race groups for all clients obtaining
services. Based on the CSI data, racial disparities are impossible to detect. When such a large
percentage of the race information is missing then all of the numbers must be considered
unreliable.
51
Counties of the Central Region – Summaries of All Client Trends
Alpine County
The overall trend for the females, CYF, adults, and older adults show an increase in access to
mental health care between 2005 and 2008. For males and the TAY group, the trends varied.
The total population of approximately 456 people seems a bit small and hard to determine the
impact of MHSA on reducing disparities. However, the trends between 2009 and 2011 seem to
be steady. In Alpine County, race data were missing for 0-70% of the population over the study
period (average 44%), making racial disparities impossible to reliably detect.
Amador County
The following groups in Amador County experienced a moderate increase in access to mental
health care between 2005 and 2011: Females, males, and adults. Trends for CYF, TAY and
older adults varied from year to year. Overall, adults seem to show a moderate increase is their
access of mental health care with a strong and consistent numbers from 2005 to 2011 with
minor decreases 2009 and 2010. In Amador County, race data were missing for 7-61% of the
population over the study period (average 40%), making racial disparities impossible to reliably
detect.
Calaveras County
Both males and females showed consistent growth in access to services from 2005 to 2011. A
consistent level of growth in groups that access mental health care was seen for CYF and TAY
groups, and adults and older adults. These four groups show a positive direction in their access
to care. In Calaveras County, race data were missing for 4-71% of the population over the study
period (average 44%), making racial disparities impossible to reliably detect.
El Dorado County
An overall trend of increased access between from 2005 to 2009 was evident for females,
males, the CYF and TAY group. For adults and older adults, access to care decreased in 2010.
The greatest levels of mental health care was seen for the CYF group with a consistent increase
in access from 2005 to 2009. In El Dorado County, race data were missing for 6-57% of the
population over the study period (average 43%), making racial disparities impossible to reliably
detect.
Fresno County
Typically an overall trend of increased access between 2005 and 2008 was evident.
Specifically, adults experienced the greatest level of mental health care between 2005 and 2007
followed by the CYF group. Access for these two groups declined somewhat in 2008 and
continued decreasing from 2009 to 2011. Older adults showed a similar pattern with ages 70
and over having the least access to care. In Fresno County, race data were missing for 37-65%
of the population over the study period (average 58%), making racial disparities impossible to
reliably detect.
Inyo County
According to the frequencies, all groups showed modest increased access to services between
2005 and 2011. Adults seem to have the greatest level of access with 192 in 2009 compared to
older adults with a low of 59 that same year. Access care trend declined for these two groups
52
and others after 2009. In Inyo County, race data were missing for 10-50% of the population over
the study period (average 35%), making racial disparities impossible to reliably detect.
Kings County
Overall, modest increases in access to care were shown for all groups between 2005 and 2008.
Adults showed a higher level of access to care going from 1,560 in 2005 to 1,724 in 2008.
Numbers for adults decreased somewhat the years that followed. Even though older adults
indicated low to moderate increased access to care, they are doing the poorest in terms of
access when compared to the other groups. In Kings County, race data were missing for 4-52%
of the population over the study period (average 36%), making racial disparities impossible to
reliably detect.
Madera County
In general, all groups experienced increased access to mental health care between 2005 and
2008. For example, adults increased from 1,283 in 2005 to 1,536 in 2008, a modest increase of
253. However, from 2009 to 2011, the trend declined for all groups. Adults represented the
group with the greatest level of access with older adults showing the least level of access. In
Madera County, race data were missing for 0-55% of the population over the study period
(average 38%), making racial disparities impossible to reliably detect.
Mariposa County
Overall, the following groups in Mariposa County experienced a small to modest increase in
access to mental health care in the first five years (2005-2009): Females, males, CYF, and TAY.
Females, for example, their access increased by 102 and for males the increase was 43.. In
Mariposa County, race data were missing for 7-64% of the population over the study period
(average 44%), making racial disparities impossible to reliably detect.
Merced County
A positive trend in access to care was evident for the following groups after the implementation
of the MHSA (2005-2006): Females, males, TAY, adults, and older adults. The trend was not
positive for the CYF group after implementation. In fact, the CYF showed a decline after 2006.
Adults showed a higher level of access to care going from 1,704 in 2005 to 2,237 in 2009. In
Merced County, race data were missing for 3-47% of the population over the study period
(average 32%), making racial disparities impossible to reliably detect.
Mono County
The following groups had the highest access of care in 2010: Females, males, and CYF. The
trend leading to 2010 showed moderate levels of increased access for all groups. It is
noteworthy to say that the older adults showed less access to care when compared to other
groups. In Mono County, race data were missing for 2-71% of the population over the study
period (average 47%), making racial disparities impossible to reliably detect.
Placer County
The following groups experienced increased access to care between 2005 and 2007: Females,
males, and adults. For example in 2005, 1,557 females accessed care compared to 1,303
males. However, 1,957 females accessed care in 2007 compared to 1,837 males. Another
group that showed increase access from 2005 to 2007 were the adults (1,545 in 2005 and 2,047
in 2007). The CYF, TAY and older adults were among the groups with the lowest access to care
from 2005 to 2007. All groups showed a declining trend in access to care from 2008 to 20012.
53
In Placer County, race data were missing for 64-79% of the population over the study period
(average 75%), making racial disparities impossible to reliably detect.
Sacramento County
Overall, most groups showed an increase in access to mental health care (i.e. females, males,
CYF, TAY, adults and older adults) from 2005 to 2008. In particular, adults showed the highest
level of access with 12,493 using services in 2005 and 15,864 in 2008, an increase of 3,371 in
three years. The trend for most groups also declined after 2008, with older adults doing the
worst of the groups going from 1,683 in 2008 to 453 in 2011. Access to care for older adults
tend to decline even more the longer they live. In Sacramento County, race data were missing
for 2-40% of the population over the study period (average 28%), making racial disparities
impossible to reliably detect.
Stanislaus County
The highest access of services for groups in Stanislaus County between 2005 and 2011 were:
males, CTF, TAY, and adults. For females, their access to care varied with 3,365 in 2005, 4,153
in 2006, and 3,900 in 2011. A similar pattern is seen with older adults. The groups that seem to
have gained the most with regards to access were the males and CYF group. In Stanislaus
County, race data were missing for 6-48% of the population over the study period (average
35%), making racial disparities impossible to reliably detect.
Sutter/Yuba County
After the implementation of the MHSA in 2005, the majority of the groups experienced a positive
trend from all the way to 2011. For example, females showed in increase from 1,372 in 2006 to
1,887 in 2011; males also increased from 1,124 in 2006 to 1,629 in 2011. Another group with a
high access rate was the adults. The adults seemed to have gained the most from MHSA
services by improving their access from 1,377 in 2006 to 1,826 in 2011. The CYF and TAY
groups made moderate increases 586 in 2006 to 830 in 2011 and 350 in 2006 to 564 in 2011
respectively. In Sutter/Yuba County, race data were missing for 58-75% of the population over
the study period (average 69%), making racial disparities impossible to reliably detect.
Tuolumne County
The groups with highest level of access to care seem to be females, males, and adults. For
example, females showed an increase from 654 in 2005 to 859 in 2008. Along similar lines,
males increased from 506 to 698 and adults from 564 to 829. The group showing the least
access was the older adults. Although they made moderate increases, those over the age of 60
show a diminishing trend. Both the CYF and TAY groups also made moderate increases.
Tuolumne County, race data were missing for 1-49% of the population over the study period
(average 34%), making racial disparities impossible to reliably detect.
Tulare County
The groups showing the highest access to care in Tulare County are males, females, and the
CYF group. These three groups maintained a steady increase staying above 3,200. The TAY
group and adults followed with reasonable numbers. Interestingly, the older adults population
made slight increases from 2005 (n = 162) to 2008 (n = 250). The adults also maintained a
strong trend improving in 2005 to 2011. In Tulare County, race data were missing for 36-62% of
the population over the study period (average 55%), making racial disparities impossible to
reliably detect.
54
Yolo County
Overall, all groups Yolo County showed an increase in access between 2005 and 2007. For
adults, a positive trend was also evident between 2008 and 2010. Both females and adults had
the highest level of accessed care when compared to other groups. The CYF and TAY groups
also showed consistent numbers between 2005 and 2011. In Yolo County, race data were
missing for 1-53% of the population over the study period (average 36%), making racial
disparities impossible to reliably detect.
Central Region Summary – New Clients
Access for the previously unserved (new clients) in the Central Region improved after the
passage of the MHSA by 2006 for all counties except Kings County, which saw declines in
access for several subpopulations. Several counties maintained relatively consistent increases
in access including: Amador, Calaveras, Mono, Stanislaus and Sutter/Yuba. In this region
females had greater access than males but only slightly (except in Kings County where the
access for females was much higher than males). The TAY age group also tended to have the
greatest access, although in some counties the CYF group dominated (Alpine, Mono,
Stanislaus). Older adults tended to have the lowest levels of access overall and did not seen
much change in access based on the regional averages.
Central Region Summary – All Clients
Within the Central Region, access for the previously served (all clients) improved after the
passage of the MHSA in 2005 until 2006, then leveled off for a couple of years, before
decreasing steadily between 2008 and 2011. Men and women had virtually the same level of
access to mental health services, experiencing an initial increase in access followed by stable
rates for a couple of years, ultimately yielding to decreases in access in more recent years. The
TAY and CYF age groups also tended to have the greatest access, although in some counties
the CYF group dominated. Older adults tended to have the lowest levels of access overall and
did not see much change in access based on the regional averages.
Central Region Summary – All Data
In the Central Region, despite early gains in access in 2006, there is a trend toward levelling off
and for all clients, decline, to the end of the study period. Kings County notably did not have
initial increases in access and also had a disparity between the sexes such that females
enjoyed much greater access than males here. While CYF and TAY age groups still dominate
access to mental health services for new and all clients, the older adults saw little change at all
from their position of low access.
55
Southern Region
The Southern Region includes 9 counties
in the southernmost part of the state.
New Clients
Figure 35. Southern region mental health access trends for the total population of new
clients obtaining services. Graph (a) shows frequencies or the actual number of new clients
by year of service while graph (b) shows the number of new clients as a proportion of the
region’s overall population. Both graphs in this case indicate that there was a trend toward
increased access to mental health services throughout the study period, despite a small decline
in 2009.
56
Figure 36. Southern region mental health access trends by sex for new clients obtaining
services. Graph (a) shows the number of new clients by sex and year of service while graph (b)
shows the number of new clients as a proportion of the region’s population for sex subgroups.
Both graphs indicate increased access for males and females from the baseline year (2005) to
2008 that levels off through 2011. Males have slightly greater access to mental health services
in the region.
Figure 37. Southern region mental health access trends by age group for new clients
obtaining services. Graph (a) shows the number of new clients by age group and year of
service while graph (b) shows the number of new clients as a proportion of the region’s
population for age subgroups. According to graph (a), the number of children, ages 0 to 15, that
comprise the Children, Youth and Families (CYF) group, experienced increases in services to
new clients between 2005 through 2011 with a minimal dip in 2009. Transitional age youth
(TAY), defined as the population age 16 to 25, experienced the same pattern as the CYF group.
The adult population, ages 26-59, comprise the dominant users (by overall numbers of new
clients) of mental health services in the Southern region and experienced greater increases in
the number of new clients accessing services than other age groups. However, this group also
experienced a decline in access in 2009 with recovery to near peak levels through 2011. Older
adults, those ages 60 plus, have the fewest numbers of new clients accessing mental health
services in the Southern region and no discernable trend over the study period is seen. When
reviewing the proportions accessing services by age group in graph (b), all age groups
experienced increased access between 2005 and 2008. The TAY group peaked in 2008 and
then levelled off. The CYF age group steadily increased access through 2011. Adults had a
slower increase in access between 2005 and 2008 with mild decline and levelling by 2011.
Older adults saw little overall change in access over the study period. Among all age groups,
both the CYF and TAY groups have similar proportional access to mental health services in the
region. However, according to graph (b), the adult and older adult groups are experiencing a
relative disparity in access to service compared to CYF and TAY groups.
57
Figure 38. Southern region mental health access trends by older age group for new
clients obtaining services. Graph (a) shows the number of new clients by older age group and
year of service while the graph (b) shows the number of new clients as a proportion of the
region’s population for older age subgroups. Note that the older age group categories differ
between the two graphs (due to U.S. Census Bureau subdivision methods). Nonetheless, the
trends are clear. The number of older adults obtaining services (graph (a)) diminishes by
increasing age, likely a result of both decreasing lifespan and potentially a transfer to Medicare
providers working outside the county system. However, when normalized by the underlying
population (graph (b)), it is still the youngest group, age 60-64, that has the greatest relative
access to mental health care services. Access for this group increased between 2005 and 2008,
but then experienced ups and downs so that by 2011 access was just slightly over baseline
levels. The next two older age groups all had similar proportional access during the study period
which amounted to little overall change from baseline. The oldest age group, 85+ years,
experienced relative declines in access.
Southern Region mental health access trends by race groups for new clients obtaining
services. Based on the CSI data, racial disparities are impossible to detect. When such a large
percentage of the race information is missing then all of the numbers must be considered
unreliable. Table 8 below indicates the percentages of the total dataset missing race information
by year.
Table 8. Summary of CSI data by year for new clients in the Southern
Region indicating the percentage of observations with race
information that is unknown or missing
Year Race Known Race Unknown P e rcentage of Race
or Missing Unknown or Missing
2005 58,029 14,529 20%
2006 41,660 48,808 54%
2007 22,170 73,547 77%
2008 23,369 86,233 79%
2009 18,939 81,546 81%
2010 17,315 91,626 84%
2011 15,874 88,774 85%
2012 8,402 54,935 87%
58
Counties of the Southern Region – Summaries of New Client Trends
Imperial County
Several groups in Imperial County had initial decreases in access to mental health services
(CYF, TAY, Adults, Males), however the overall trend showed increasing access for all groups
by 2011. In Imperial County, race data were missing for 54-93% of the population over the study
period (average 85%), making racial disparities impossible to reliably detect.
Kern County
In Kern County, all age and sex groups enjoyed increased access to care between 2005 and
2011 except for older adults who had some variation but little net change overall. In Kern
County, race data were missing for 0-92% of the population over the study period (average
73%), making racial disparities impossible to reliably detect.
Orange County
Several groups in Orange County experienced increased access to mental health care between
2005 and 2010 including: Females, Adults, Males, CYF and TAY. All of these groups, however,
had decreasing access after 2010. The TAY group had, by far, the highest levels of access
overall while Older Adults had the lowest levels of access with no net change in access over the
study period. In Orange County, race data were missing for 38-91% of the population over the
study period (average 80%), making racial disparities impossible to reliably detect.
Riverside County
All sex and age groups in Riverside County saw increased access to mental health services
between 2005 and 2008. However, these levels of access declined for all groups by 2010, yet
remained well above baseline. In Riverside County, race data were missing for 16-82% of the
population over the study period (average 66%), making racial disparities impossible to reliably
detect.
San Bernardino County
In San Bernardino County, there is a trend toward increasing access to care from 2005 to 2011
with mild dips/levelling I 2009. The TAY group had the highest access while older adults had
much lower access than other groups, indicating a relative disparity. In San Bernardino County,
race data were missing for 27-86% of the population over the study period (average 72%),
making racial disparities impossible to reliably detect.
San Diego County
San Diego’s overall trend in mental health service access was positive between 2005 and 2011
with the exception of a mild dip/flattening of the trend between 2008 and 2010. The highest
levels of access were seen for the CYF group and the lowest levels occurred in the Older Adult
group. In San Diego County, race data were missing for 7-76% of the population over the study
period (average 60%), making racial disparities impossible to reliably detect.
San Luis Obispo County
The major trend seen in San Luis Obispo County is a mild to moderate increase in access
between 2005 and 2007, followed by decreasing access through 2011. Overall, the CYF group
had by far the greatest access. Conversely, the Older Adult group had by far the lowest access
to mental health services. In San Luis Obispo County, race data were missing for 8-96% of the
59
population over the study period (average 69%), making racial disparities impossible to reliably
detect.
Santa Barbara County
While ups and downs are seen on a year to year basis, the trend in Santa Barbara County for
TAY, Adults, Males and Females is one of decreasing access overall. Despite early increases
(2005-2006), the level of access for these groups in 2011 is lower than at baseline. The older
adult age group had a mild decline and the CYF group had a recovery in service access in 2011
that was higher than baseline levels. In Santa Barbara County, race data were missing for 10-
86% of the population over the study period (average 70%), making racial disparities impossible
to reliably detect.
Ventura County
In Ventura County, all groups saw increasing mental health access between 2005 and 2008, but
then had sharp decreases in 2009 and 2010. Then in 2011, significant recovery in access was
seen for all groups such that access in 2011 was higher than at baseline in 2005. In Ventura
County, race data were missing for 2-90% of the population over the study period (average
70%), making racial disparities impossible to reliably detect.
All Clients
Figure 39. Southern region mental health access trends for the total population of all
clients obtaining services. Graph (a) shows frequencies or the actual number of all Southern
Region clients by year of service while graph (b) shows the number of all clients as a proportion
of Southern Region’s overall population. Both graphs in this case indicate that there was an
increase in access to mental health services between 2005 and 2008. The number of clients
remained relatively stable between 2008 and 2011, finishing well above baseline (2005) levels.
The proportion of clients obtaining access peaked in 2010. Then, between 2010 and 2011,
Southern Region access to mental health services decreased once again, but remained well
above baseline levels (2005). Data for 2012 were incomplete and are therefore not reliable.
60
Figure 40. Southern region mental health access trends by sex for all clients obtaining
services. Graph (a) shows the number of all Southern Region clients by sex and year of service
while graph (b) shows the number of all clients as a proportion of the Southern Region’s
population for sex subgroups. Graph (a) indicates increased access for males and females from
the baseline year (2005) to 2008. Between 2008 and 2011, the number of both male and female
clients remained relatively stable, finishing with numbers that were well above the 2005
baseline. While both males and females started at similar levels, the number of males receiving
access outpaced those of female clients. Graph (b) portrays a substantial increase from
baseline (2005) to 2008. Between 2008 and 2011, Southern Region mental health access for
males and females decreased and increased in a cyclical fashion, but finished with access in
2011 that was above baseline levels.
Figure 41. Southern region mental health access trends by age group for all clients
obtaining services. Graph (a) shows the number of all Southern Region clients by age group
and year of service while graph (b) shows the number of all Southern Region clients as a
proportion of the region’s population for age subgroups. Data were incomplete for 2012.
According to graph (a), the number of children, ages 0 to 15, that comprise the CYF age group,
experienced a slow but steady increase in numbers accessing mental health services over the
study period. Transitional age youth (TAY), defined as the population age 16 to 25, also
experienced increased numbers accessing services from the inception of the MHSA to 2010,
but then there was a decrease in the numbers through 2011. The adult population, ages 26-59,
comprise the dominant users (by overall numbers of clients) of mental health services statewide
and experienced increased access through 2008, but also saw a decline during 2009. Then,
the numbers of clients accessing services in the region leveled off between 2009 and 2011.
61
Older adults, those ages 60 plus, have the fewest numbers of clients accessing mental health
services in the Southern Region and no discernible trend over the study period is seen. When
reviewing the proportions accessing services by age group in graph (b), the CYF group showed
increasing access over the study period with an overall rise from 2005 to 2010, followed by a
decrease in 2011. The TAY group had steady, increased access from 2005 to 2010. In fact,
from 2007 to 2011, the CYF group had the highest proportional levels of access among all age
groups within the Southern Region’s mental health system. According to graph (b), although
adults had an increase in access to mental health services from 2005 to 2008, followed by a
general leveling off, both groups are experiencing a relative disparity in access to service
compared to CYF and TAY groups.
Figure 42. Southern region mental health access trends by older age group for all clients
obtaining services. Graph (a) shows the number of all Southern Region clients by older age
group and year of service while the graph (b) shows the number of all Southern Region clients
as a proportion of the region’s population for older age subgroups. Note that the older age group
categories differ between the two graphs (due to U.S. Census Bureau subdivision methods).
The number of older adults obtaining services (graph (a)) diminishes by increasing age, likely a
result of both decreasing lifespan and potentially a transfer to Medicare providers working
outside the county system. The youngest group, age 60-64, had the greatest relative access to
mental health care services. Access for this group increased through 2010, but then decreased
into 2011. However, when normalized by the underlying population (graph (b)), it is still
Individuals over the age of 65 appear to experience a relative disparity in access compared to
the 60-64 year olds.
Southern Region mental health access trends by race groups for all clients obtaining
services. Based on the CSI data, racial disparities are impossible to detect. When such a large
percentage of the race information is missing then all of the numbers must be considered
unreliable.
Counties of the Southern Region – Summaries of All Client Trends
Imperial County
Overall, most groups in Imperial County showed moderate to high increases in their access to
mental health care between 2005 and 2011 including: Females, males, adults, and CYF. For
example, male’s access to mental health care increased from 1,408 in 2005 to more than 2,000
in 2011. Similarly, adult’s access to care also increased in 2005 to 2011. Males and adults seem
62
to have the highest level of access compared to other groups. The TAY group and older adults
had moderate increases. Specifically, from 2005 to 2011, the TAY group increased by 522 and
the older adults by 160. In Imperial County, race data were missing for 45-69% of the population
over the study period (average 63%), making racial disparities impossible to reliably detect.
Kern County
The majority of groups in Kern County experienced increased access to mental health care
between 2005 and 2011. For example, the adult group showed the highest level of access when
compared to the TAY, CYF, and older adult groups. The older adults showed the lowest levels
of access the older in age. In Kern County, race data were missing for 0-61% of the population
over the study period (average 41%), making racial disparities impossible to reliably detect.
Orange County
The trend for groups in Orange County demonstrated an increase in access to mental health
care between 2005 and 2010. With regards to gender, both females and males experienced
increased access from 17,157 in 2005 to 23,407 in 2010 and 18,281 in 2005 and 25,853 in
2010 respectively. The CYF, TAY, and adults also showed increase levels of access. Although
all groups had decreasing access to care after 2010, the older adults continue to be the group
that fares the worst when compared to other groups. In Orange County, race data were missing
for 44-74% of the population over the study period (average 67%), making racial disparities
impossible to reliably detect.
Riverside County
Between 2005 and 2010 most groups in Riverside County experienced increased access to
mental health care including: Females, males, adults, CYF, and TAY. Older adults showed
moderate to low increased access to care. For example, the CYF group’s access to mental
health care increased from 6,277 in 2005 to 8,075 in 2010. Similarly, the TAY group’s access to
care also increased from 5,237 on 2005 to 9,787 in 2010. All groups, however, showed a
decrease in access in 2011. For instance, from 2010 to 2011, the adult’s access to care
decreased by 5,442 followed by the TAY group with a decrease of 3,302, and CYF with 2,080.
In Riverside County, race data were missing for 13-60% of the population over the study period
(average 46%), making racial disparities impossible to reliably detect.
San Bernardino County
While the majority of groups in San Bernardino County showed moderate increased between
2005 and 2011, access decreased after 2011. For example, between 2005 and 2007 females
increase by 3,048, but decreased by 728 between 2008 and 2011. A similar trend is found for
males, an increase by 3,157 between 2005 and 2007 and decrease by 91 between 2008 and
2011. However, decrease in access for both genders were more severe after 2011. A similar
trend can be seen for adults. For the CYF and TAY groups, access after 2011 decreased by
500 and 836 respectively. Older adults showed a moderate to low decrease after 2011. In San
Bernardino County, race data were missing for 29-64% of the population over the study period
(average 55%), making racial disparities impossible to reliably detect.
San Diego County
Between 2005 and 2011 most groups in San Diego County experienced increased access to
mental health care including: Females, males, adults, CYF, and TAY. Older adults showed low
to moderate increased access to care. For example, the CYF group’s access to mental health
care increased from 10,448 in 2005 to 13,458 in 2011. Similarly, the TAY group’s access to care
also increased from 5,015 on 2005 to 10,264 in 2011. With regards to gender, both females and
63
males also experienced an increase in access to care with females increasing from 19,701 in
2005 to 25,546 in 2011 and males from 18,586 in 2005 to 30,598 in 2011. In general, the trend
indicates that the older people get, the more access to care decreases. In San Diego County,
race data were missing for 6-51% of the population over the study period (average 36%),
making racial disparities impossible to reliably detect.
San Luis Obispo County
The overarching goal of MHSA is to reduce disparities in access to mental health care. Based
on frequencies from 2005 to 2010, access to care did increase moderately for several groups.
For example, the CYF group’s access to care increased from 950 in 2005 to 1,236 in 2010 and
continued to 1,245 for 2011. For adults, on the other hand, access increased to 2,120 in 2010,
deceased to 1,930 in 2011. The trend pattern seen for adults also explains the trends for the
other groups. In San Luis Obispo County, race data were missing for 6-58% of the population
over the study period (average 40%), making racial disparities impossible to reliably detect.
Santa Barbara County
Consistent with other counties in this region, most groups in Santa Barbara experienced an
increase in access to mental health care with much of the increase occurring between 2005 and
2011. With the exception of older adults, other groups showed a decrease in access after 2011
including: Females, males, adults, CYF, and TAY. The disparity in access to care does not
seem to be huge for older adults over age 60. Traditionally, this group experience higher
disparities the higher in age. In Santa Barbara County, race data were missing for 5-48% of the
population over the study period (average 35%), making racial disparities impossible to reliably
detect.
Ventura County
We see a consistent pattern in that the majority of groups in Ventura County show an increase
in access to mental health services between 2005 and 2011. Again with the older adults, their
access to care declines the older they get. For example, in 2011 322 older adults had access to
care compared to 37 individuals over 85 that same year. Again, the number of older adults
accessing mental health care is relatively low. In Ventura County, race data were missing for 1-
55% of the population over the study period (average 37%), making racial disparities impossible
to reliably detect.
Southern Region Summary – New Clients
In the Southern Region of the state the overall trend was toward increasing access to mental
health services for the previously unserved between 2005 and 2008. Only Imperial County did
not have immediate increases in access after the implementation of the MHSA. Males and
females had similar trends of increased access to 2008 and then levelling off to 2010 with males
having slightly more access overall. In 2011, the only age group to see increased access was
the CYF group. The TAY, Adult and Older Adult groups had mild decreases in access that year.
Four counties experienced increased access throughout the study period including: Kern,
Orange, San Bernardino and San Diego. Santa Barbara had a trend toward decreasing access
over the study period.
Southern Region Summary – All Clients
In the Southern Region of the state the overall trend was toward increasing access to mental
health services for the previously served (all clients) between 2005 and 2008. Males had slightly
higher access to services than females, and both sex groups had similar trends of increased
access to 2010 and then a decrease to 2011. From baseline (2005) until 2010, the CYF and
64
TAY age groups to saw increases in access, and these two groups experienced greater
proportional access to services per 100,000 when compared to the other age groups.
Southern Region Summary – All Data
More than other regions, the Southern Region experienced a more prolonged (2005-2008)
increase in access to mental health services following the MHSA implementation. In fact, four
counties had sustained increases in access to 2011 for previous unserved clients: Kern,
Orange, San Bernardino and San Diego. The CYF and TAY groups continued to exhibit greater
access for new and all clients as compared to adults and older adults.
Los Angeles Region
The Los Angeles Region includes Los
Angeles County, located in the southwestern
part of the state.
New Clients
Figure 43. Los Angeles region mental health access trends for the total population of
new clients obtaining services. Graph (a) shows frequencies or the actual number of new
clients by year of service while graph (b) shows the number of new clients as a proportion of the
region’s overall population. Both graphs in this case indicate that there was a trend toward
increased access to mental health services through 2007, then a steady decline through 2010
with a sharp increase in 2011.
65
Figure 44. Los Angeles region mental health access trends by sex for new clients
obtaining services. Graph (a) shows the number of new clients by sex and year of service
while graph (b) shows the number of new clients as a proportion of the region’s population for
sex subgroups. Both graphs indicate increased access for males and females from the baseline
year (2005) to 2007, followed by a steady decline to near or below baseline levels through 2010,
then a sharp increase in 2011. Males have significantly greater access to mental health services
in the region.
Figure 45. Los Angeles region mental health access trends by age group for new clients
obtaining services. Graph (a) shows the number of new clients by age group and year of
service while graph (b) shows the number of new clients as a proportion of the region’s
population for age subgroups. According to graph (a), the number of children, ages 0 to 15, that
comprise the Children, Youth and Families (CYF) group, experienced mild increases in services
to new clients between 2005 through 2011. Transitional age youth (TAY), defined as the
population age 16 to 25, saw increases in access through 2008, with slow decline through 2010
and recovery in 2011. The adult population, ages 26-59, comprise the dominant users (by
overall numbers of new clients) of mental health services in the Los Angeles region and
experienced greater increases in the number of new clients accessing services than other age
groups, peaking in 2007. However, this group also experienced a decline in access between
2007 and 2010 with recovery to near peak levels in 2011. Older adults, those ages 60 plus,
have the fewest numbers of new clients accessing mental health services in the Los Angeles
region and no discernable trend over the study period is seen. When reviewing the proportions
accessing services by age group in graph (b), all age groups experienced increased access
66
between 2005 and 2006. The TAY group peaked in 2007, and then declined to below baseline
by 2010 with recovery to peak levels in 2011. The CYF age group steadily increased access
through 2011. Adults had an increase in access between 2005 and 2007 with decline to below
baseline to 2010 and recovery in 2011 to near peak levels. Older adults saw little overall change
in access over the study period except for a noticeable bump in access n 2011. Among all age
groups, both the CYF and TAY groups have greater proportional access to mental health
services in the region as compared to adult and older adult groups.
Figure 46. Los Angeles region mental health access trends by older age group for new
clients obtaining services. Graph (a) shows the number of new clients by older age group and
year of service while the graph (b) shows the number of new clients as a proportion of the
region’s population for older age subgroups. Note that the older age group categories differ
between the two graphs (due to U.S. Census Bureau subdivision methods). Nonetheless, the
trends are clear. The number of older adults obtaining services (graph (a)) diminishes by
increasing age, likely a result of both decreasing lifespan and potentially a transfer to Medicare
providers working outside the county system. However, when normalized by the underlying
population (graph (b)), it is still the youngest group, age 60-64, that has the greatest relative
access to mental health care services. Access for this group increased between 2005 and 2007,
but then decreased through 2010 and bumped up again in 2011.
Los Angeles Region mental health access trends by race groups for new clients
obtaining services. Based on the CSI data, racial disparities are impossible to detect. When
such a large percentage of the race information is missing then all of the numbers must be
considered unreliable. Table 9 below indicates the percentages of the total dataset missing race
information by year.
67
Table 9. Summary of CSI data by year for new clients in the Los
Angeles Region indicating the percentage of observations with race
information that is unknown or missing
Year Race Known Race Unknown P e rcentage of Race
or Missing Unknown or Missing
2005 64,170 11,144 15%
2006 72,010 12,736 15%
2007 78,175 18,812 19%
2008 73,882 15,325 17%
2009 73,289 12,188 14%
2010 65,266 7,124 10%
2011 44,833 59,370 57%
2012 4,305 8,571 67%
All Clients
Figure 47. Los Angeles region mental health access trends for the total population of all
clients obtaining services. Graph (a) shows frequencies or the actual number of all Los
Angeles Region clients by year of service while graph (b) shows the number of all clients as a
proportion of the Los Angeles Region’s overall population. Both graphs in this case indicate that
there was an increase in access to mental health services in 2006 and 2007, followed by a slow
gradual decrease through 2010, and a sharp increase into 2011. Los Angeles Region access to
mental health services finished well above baseline levels (2005). Data for 2012 were
incomplete and are therefore not reliable.
68
Figure 48. Los Angeles region mental health access trends by sex for all clients
obtaining services. Graph (a) shows the number of all Los Angeles Region clients by sex and
year of service while graph (b) shows the number of all clients as a proportion of the Los
Angeles Region’s population for sex subgroups. Graph (a) indicates increased access for
females from the baseline year (2005) to 2011, finishing well above baseline (2005) levels.
There was increased access for males between 2005 and 2007, followed by decreasing trend
from 2007 to 2010, and a steep increase between 2010 and 2011. Graph (b) portrays similar
patterns in access to mental health services, with a general, steady increase among females.
Among males in the Los Angeles Region, there was increased access between 2005 and 2007,
followed by decreases between 2007 to 2010, and a steep increase between 2010 and 2011.
Figure 49. Los Angeles region mental health access trends by age group for all clients
obtaining services. Graph (a) shows the number of all Los Angeles Region clients by age
group and year of service while graph (b) shows the number of all Los Angeles Region clients
as a proportion of the region’s population for age subgroups. Data were incomplete for 2012.
According to graph (a), the number of children, ages 0 to 15, that comprise the CYF age group,
experienced a steady increase in numbers accessing mental health services over the study
period. Transitional age youth (TAY), defined as the population age 16 to 25, also experienced
increased numbers accessing services from the inception of the MHSA to 2008, but then there
was a decrease into 2010 followed by an increase in 2011. The adult population, ages 26-59,
comprise the dominant users (by overall numbers of clients) of mental health services in Los
Angeles, and experienced increased access through 2007, but also saw a steady decline
between 2007 and 2010. Then, the numbers of clients accessing services in the region
increased between 2010 and 2011. Older adults, those ages 60 plus, have the fewest numbers
of clients accessing mental health services in Los Angeles and no discernible trend over the
study period is seen. When reviewing the proportions accessing services by age group in graph
(b), the CYF group showed increasing access over the study period with a steady rise from
2005 to 2011. In fact, from 2008 to 2011, the CYF group had the highest proportional levels of
access among all age groups to the mental health system. The TAY group had increased
access from 2005 to 2009, but then declined through 2010, and rose again in 2011. According
to graph (b), adults had an increase in access to mental health services from 2005 to 2007,
followed by steady decrease from 2007 to 2010. Both the adult and older adult groups the Los
Angeles Region are experiencing a relative disparity in access to service compared to CYF and
TAY groups.
69
Figure 50. Los Angeles region mental health access trends by older age group for all
clients obtaining services. Graph (a) shows the number of all Los Angeles Region clients by
older age group and year of service while the graph (b) shows the number of all clients as a
proportion of the Los Angeles Region’s population for older age subgroups. Note that the older
age group categories differ between the two graphs (due to U.S. Census Bureau subdivision
methods). The number of older adults obtaining services (graph (a)) diminishes by increasing
age, likely a result of both decreasing lifespan and potentially a transfer to Medicare providers
working outside the county system. The youngest group, age 60-64, had the greatest relative
access to mental health care services. Access for this group increased substantially between
2005 and 2011. However, when normalized by the underlying population (graph (b)), it is still
Individuals over the age of 65 appear to experience a relative disparity in access compared to
the 60-64 year olds.
Los Angeles Region mental health access trends by race groups for all clients obtaining
services. Based on the CSI data, racial disparities are impossible to detect. When such a large
percentage of the race information is missing then all of the numbers must be considered
unreliable.
Los Angeles Region Summary – New Clients
The Los Angeles Region saw increased access to mental health services from the inception of
the MHSA to 2007. Then a decline occurred to 2010 with recover to peak levels in 2011.
Previously unserved men had significantly higher access than women but both sexes followed
the same overall access trend noted. The CYF age group was the only group to have
consistently increasing access to mental health services over the entire study period. Older
adults saw little change from baseline levels.
Los Angeles Region Summary – All Clients
In the Los Angeles Region, overall access to mental health services among previously served
(all clients) increased from 2005 to 2007, followed by a leveling off until 2009, and increase in
2011. Males and female access trends paralleled those of overall trends, but males had higher
access to services than females throughout the study period. The CYF age group experienced
increasing access from baseline (2005) through 2011. From 2008-2011 the CYF age group had
the greatest overall access to services when compared to all age groups in Los Angeles, and
the Older Age group had the greatest disparity in access. Of note, the age groups other than
CYF maintained relatively stable access to mental health services throughout the study period.
70
Los Angeles Region Summary – All Data
Overall, in Los Angeles Region, access for new and all clients looked very similar. Major trends
were increasing access for the CYF group and higher levels of access for males versus
females. While access appeared to increase in the first few years due to the MHSA, there was a
trend toward stable levels of access overall.
Key Findings for Research Question 1:
Did the MHSA have an impact on reducing disparities
in access to mental health care in California?
The increased levels of mental health services for all subpopulations in the majority of counties
and regions in California provides convincing evidence that the implementation of the MHSA
has had an impact and led to the growth of mental health access for all subpopulations in the
state. Unfortunately, for the majority of counties and regions, the impact did not appear to be
sustained during the entire study period. We explore this negative outcome in the analyses that
following in the next section.
71
California Health Interview Survey Findings
In California, mental health need varies by population subgroup, by geography and over time.
Mental health need could be considered an opposite of mental health which has been defined
by the Institute of Medicine as “a state of well-being in which every individual realizes his or her
own potential, can cope with the normal stressors of life, can work productively and fruitfully,
and is able to make a contribution to her or his community.” Many Californians suffer from
mental ill-health, herein defined as a condition in which severe psychological distress leads to
decreased functioning in one or more domains of life. The following graphs and explanatory text
come from data provided by the California Health Interview Survey and are meant to
supplement our understanding of the access patterns seen in the state, regions and counties
previously described. Although we use CHIS data to highlight the need for mental health care
and enhance our findings regarding access to care patterns using CSI data, our analyses of
these finding should be viewed with some caution because the CSI and CHIS may vary in data
collection procedures and aims (please refer back to remarks about each dataset in the
Methodology section).
23
22.5
22
21.5
21
20.5
20
19.5
19
18.5
2005 2007 2009 2011-2012
Figure 51. California mental health needs by sex. A slightly higher percentage of men
qualified has having severe mental distress than women, but the percentage of distressed men
and women both are clearly declining over time (please note that the scale increments are
small on the Y-axis). Nevertheless, when this trend is compared to figure 2, the statewide
access for new clients by sex and figure 7, the statewide access for all clients by sex, one
should note that the access trends are quite steady over time. Therefore, if access is stable and
need is decreasing, then one may conclude that there is increased access to mental health
services, for both sexes, relative to need. One should also note that a higher percentage of
males have severe mental distress than females based on the CHIS, and similarly have slightly
greater access to services as shown in figures 2 and 7. Hence, there does not appear to be a
gender disparity in access on a statewide level.
72
ssertsiD
htiw
deyevruS
%
Male
Female
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
2005 2007 2009 2011-2012
Figure 52. California mental health needs by age group. A lower percentage of individuals
60 and older appear to have severe mental distress relative to everyone else, while the 26-59
year old age group has the highest percentage with severe mental distress. Please note,
however, that the range on the Y-axis is quite small and differences may not be statistically
significant. All groups seem to be improving in need from 2005-2009, and then need appears to
increase again from 2009-2011/2012. These trends can be compared to the data in figures 3
and 8 showing statewide access to mental health services for new clients and all clients
respectively. The older adult age group (ages >60) has, by far, the lowest levels of access to
mental health care services and these levels remain generally stable between 2005 and 2011.
As previously mentioned, this may be related to an overall transition of older adult care to the
Medicare system, outside of the county mental health system. Based on these data alone, with
the mental health need for older adults trending toward a decline, this could indicate some
increased access relative to need in this population. However, the percentage of survey
respondents with severe mental distress in the older adults age group is similar, in general, to
the percentage of survey respondents with severe mental distress in the TAY age group (ages
16-25). However, in figures 3 and 8, the TAY group has among the highest levels of access to
care. This may signify a relative disparity for older adults as compared to the TAY population.
Adults, in this CHIS sample had the highest percentages of respondents reflecting mental
distress, indicating higher levels of mental health service need. In figures 3 and 8, adults have
increasing access between 2005 and 2007, decreased access in 2009 and another increase in
2011. The trend follows the trend for mental health needs nicely. However, the expectation for
access, based on this figure, would be that adults would have a higher proportional access to
care than other groups. Since this is not the case, it may indicate a relative disparity for adults in
access to care, relative to need.
73
ssertsiD
htiw
deyevruS
%
16-25
26-59
60 and older
5
s 4.5
s
e r 4
t
s iD 3.5
h 3
t
iw
2.5
60-64
d
e 2 65-69
y
e 1.5
v
r 70-74
u 1
S
% 0.5 75-79
0
80 and older
2005 2007 2009 2011-2012
Figure 53. California mental health needs by older age group. The pattern of declining need
from 2005-2009 is replicated in the older adult age group, with percentages of severe mental
distress somewhat increasing from 2009-2011/2012 (again, please note the small range of y-
axis values and interpret with caution). The general trend among these age groups seems to be
that as one ages, he/she appears to have less mental distress and thus less presumed need for
mental health services. A similar pattern was reflected in figures 4 and 9, showing the statewide
trends for access to mental health services for older adults who are new clients and all clients
respectively. In these figures it is also clear that the older the adult, the less access to mental
health services is seen (potentially due to a transition to Medicare).Among the older adult age
groups, there may not be a relative disparity as access is compared to mental health needs. In
figure 9, the older adult age groups all show a relatively steady level of access between 2005
and 2011. This may indicate that access improved compared to need between 2005 and 2009.
However, by the same token, there may have been a relative decrease in access in 2011. In the
‘new client’ analysis represented in figure 4, although the levels of access vary gently over the
study period, we can see an increase in access between 2005 and 2006/2007, followed by
decreasing access to 2010 with a small increase in access in 2011. This follows the pattern of
need shown above very closely. One might then posit that for new clients there was some
increase in access associated with the early years of the MHSA, but then a stable pattern of
access compared to need.
74
6
5
s s Superior
e
r
t
s 4
iD
h
Central
t
iw 3
d Bay Area
e
y
e 2
v
r
u Southern
S
% 1
Los Angeles
0
2005 2007 2009 2011-2012
Figure 54. California mental health needs by WET Region. The trend of decreasing need
until 2009 is replicated in the region data. Superior region has the highest percentage of
individuals with need, with the Bay Area having the lowest. In figure 11, the total Superior
Region population levels of access for new clients to mental health care services, we see that
access increased between 2005 and 2006, was steady until 2010 and then declined in 2011.
When considering the need indicated above, that would translate to increased access between
2005 and 2009, but decreased access in 2011 relative to need. For all clients in the Superior
Region (figure 15), there is a stronger message indicating increased to stable access
throughout the study period. In the Bay Area Region, new clients (figure 19) and all clients
(figure 23) saw improved access relative to need until 2011 when there was a decrease. The
pattern of access versus need is similar in the Central Region. This region had significantly
improved access for new clients (figure 27) and all clients (figure 31) through 2009 but had
declining access in 2011 compared to need. The Southern Region had similar, though slightly
lower, mental health needs, but when evaluated against access (see figures 35 and 39) had
improvements throughout the study period for both new and all clients. The Los Angeles Region
has a nearly flat curve indicating that mental health need over the study period changed very
little. Mental health access for new and all clients (figures 43 and 47) in the Los Angeles Region
increased to 2007, decreased to 2010 and then increased again in 2011. This tells us that the
Los Angeles Region kept pace with mental health need and likely improved access in 2011
relative to need. In reviewing the regions relative to one another, the Los Angeles Region
provided the highest levels of access to new clients, followed by the Superior Region. The
Central and Southern Regions had the next highest levels of proportional access and the Bay
Area Region had the lowest levels. Thus there may be a relative geographic disparity in access
to mental health services relative to need in the Superior Region. For all clients, the highest
access was seen in the Superior Region, followed by the Los Angeles Region, then Central,
Bay Area and Southern Regions. If a geographic disparity exists for all clients, then it is in
slightly less access according to need for the Southern Region.
75
50
45
40
35
30
25
20
15
10
5
0
2005 2007 2009 2011-2012
76
ssertsiD
htiw
deyevruS
%
White
Hispanic
African American
Native Amer/Alaska
Nat
Asian
Figure 55. California mental health needs by race. There is a slow decline in mental health
need for Hispanics, African Americans, Asians and Whites and multi-race individuals over the
study period. The decline in need was more significant for Pacific Islanders through 2009, but
increased to baseline levels by 2011-2012. Native American/Alaskan Natives had a varying
level of need over the study period with no net change from 2005 to 2011-2012. As previously
noted, due to missing race/ethnicity data from the CSI database, comparisons to mental health
access cannot be made. However, information on the relative levels of need for mental health
services by racial/ethnic group in California is useful when considering outreach efforts.
7
6
5
4
3
2
1
0
2005 2007 2009 2011-2012
Figure 56. California mental health needs by language spoken at home. In 2005, those
who spoke Asian languages at home had the highest levels of mental health need. However,
those levels decreased dramatically for 2007 through 2011-2012. From 2007 on, Spanish
speakers had the highest need for mental health services.
ssertsiD
htiw
deyevruS
%
English
Spanish
Asian language
Other
2 or more
languages
30
25
20
15
10
5
0
2005 2007 2009 2011-2012
Figure 57. California mental health needs by nativity status. Those who were born in the
U.S. have the highest level of need, but for both U.S. born and foreign-born individuals, need
slightly decreased over time. There may be many reasons for these trends. Foreign-born
residents may feel less comfortable discussing mental health issues and mental health needs
due to different definitions and cultural views of “distress” and “mental health.” As a result, it is
possible that “distress” is under-reported in foreign-born populations. It is also possible that the
CHIS sample relies on a smaller sample of foreign-born respondents, which is not
representative of all foreign-born people in California. Further, undocumented, foreign-born
residents may feel less comfortable participating in health surveys, especially if they are
sponsored by the government. Finally, a number of studies indicate that health and mental
health complications are positively associated with assimilation to U.S. culture. The level of
assimilation among foreign-born CHIS respondents may be positively associated with distress
levels and other mental health indicators among foreign-born respondents and, if newly arrived
foreign-born respondents (who are less assimilated) are oversampled, they may have
substantially lower levels of distress.
Key Findings for Research Question 2:
What are the mental health needs for racial/ethnic, language, nativity,
gender and age sub-groups in California?
In California, according to the analysis of respondents to the California Health Interview Survey,
the highest levels of mental health needs are seen for the following population sub-groups in
general highest to lowest order: multi-racial, Hispanic, US born, African American and American
Indian/Alaskan Native, men, women, Asian/Pacific Islander, White, Spanish language, adults
and older adults.
77
ssertsiD
htiw
deyevruS
%
Foreign-born
U.S. born
Overall Summary of Access to Mental Health Care Relative to Need
By comparing the results of the study of mental health access to mental health needs, an
encouraging picture emerges. Overall, most groups enjoyed increased access to mental health
services based on varying levels of need over time, geography and population subgroup. No
gender disparity was detected at all. It is possible that there is some age disparity in access for
adults and older adults. However, the disparity for older adults is not as dire as the analysis
without need would have indicated. Older adults, according to the CHIS analysis, have
significantly lower levels of mental distress and so less access is expected for this group.
Adults, however, have the highest levels of mental distress, but have lower relative access than
the younger age groups, CYF and TAY. This may be indicative of a more important disparity.
Geograhically, for new clients – those previously unserved by the county mental health system
– the Superior Region may have a disparity in access based on the higher levels of need for this
region. For the Southern region, there may be a mild disparity in access for all clients since
there were relatively higher levels of need for this county versus access. This analysis provides
important perspective in interpretation of the CSI data analysis for access.
78
Conclusion
This study provides evidence that the implementation of the MHSA has led to a notable growth
of mental health access overall, and for all subpopulations, at the state and regional levels, and
in most of the 58 California counties. The most notable trend was increasing access to mental
health care services between 2005 and 2006. Based on a historical timeline providing
contextual information on events occurring during the study period (see Appendix B), there were
a number of planning activities in 2005 and 2006 related to the implementation of the MHSA
which likely contributed to the addition or growth of programs that improved access to mental
health care. Tracking requirements during these early years, especially those that focused on
financial components of the MHSA, may have also encouraged early growth and monitoring of
programs. It is also likely that the new law led to a generalized energy and enthusiasm among
professionals working in the county mental health programs, recognizing the importance of their
work with a large infusion of resources. This, coupled with the interest among professionals in
seeing positive outcomes, may have also contributed to the increased provision of services and
access to care observed in our analysis in the first years of implementation of the MHSA.
Despite the early promise of the MHSA, there were declines in access to mental health services
that varied geographically and by population subgroup. However, the majority of these declines
occurred between 2008 and 2010. Based on the historical timeline, it is likely that the economic
downturn both nationwide and in California led to decreased access to mental health care. This
may have occurred both at the personal level, as patients could not afford or get to care
appointments, and at the county level, as mental health systems may have shifted resources
away from programs that were successful in promoting access to care.
Another notable finding in the CSI data was an increase in service access in 2011. This upturn
appears to coincide with both economic recovery and policy changes such as Assembly Bill
114, providing additional funding for mental health educational resources to counties, and AB
100 which provided a framework within which to streamline funding and management of county
mental health systems.
Overall, the results of our analysis points to a number of positive outcomes in mental health
service access and utilization following implementation of the MHSA in California. Our analysis
also helps to highlight gaps in services and a number of areas for improvement from a mental
health service perspective, and from a program evaluation perspective. Although our analysis
did not allow for a thorough assessment of mental health disparities by race/ethnicity (the data
was not available), we were able to analyze disparities overall, and by gender, age groups and
geography. When we compared the levels of access to county mental health services with the
overall population need for mental health services (by age and gender groups as well as
geographic region) we found that the groups most likely to be experiencing disparities were
adults (ages 26-59), older adults (ages 60 plus), and those living in the Superior Region of the
state. Future MHSA program planning, interventions, and evaluations should aim to address
these disparities, assess whether other disparities exist (aided by improved data collection),
79
work to further strengthen mental health service access and utilization, and prioritize and
implement systematic and thorough evaluation of future outcomes.
80
Appendix A. Detailed Methodology
Client Services Information (CSI) Dataset Analysis
We began with the identification of new clients within the database. Based on UCLA’s
recommendations, new clients were defined as those without service for the prior six months
(i.e. 182 days). Our method for determination of new clients was as follows:
1. Data were collected in 1.5 year groupings as follows:
a. July 1, 2004 – December 31, 2005
b. July 1, 2005 – December 31, 2006
c. July 1, 2006 – December 31, 2007
d. July 1, 2007 – December 31, 2008
e. July 1, 2008 – December 31, 2009
f. July 1, 2009 – December 31, 2010
g. July 1, 2010 – December 31, 2011
h. July 1, 2011 – December 31, 2012
2. For each County Client Number (CCN),1 we reviewed ADMISSION-DATE and
SERVICE-DATE fields. According to the CSI data dictionary, the SERVICE-DATE
“identifies the date of service for non-24-hour mode of services.” We confirmed with the
Department of Health Care Services (DHCS) that this date refers to outpatient types of
service (also validated using the MODE OF SERVICE field which distinguishes inpatient
and outpatient types of service). In addition, the field, ADMISSION-DATE, “identifies the
date the client was admitted,” and is an indicator of inpatient services. Thus the two
fields are complementary (one inpatient and one outpatient) and were used to create a
new date field, DATE-OF-SERVICE, that was used to determine a new patient without
service in the prior 6 months.
3. The DATE-OF-SERVICE from step 2 was selected and used in Step 4.
4. Using statistical software, we converted the date field to a format that allows for date
calculations:
a. The first instance of a CCN in each service calendar year was flagged. We
decided to utilize calendar years because:
i. The use of calendar year corresponds to other data sources, particularly
the U.S. Census Bureau, which we used to compare proportions of
population subgroups who are accessing county mental health services.
This comparison is particularly important for counties that may have
significant shifts in their populations over time. The flagged dates were
1 Capitalized words generally refer to CSI variable names.
81
then analyzed to determine if the client is new by subtracting 182 days
and checking if any prior visits/encounters fall within that 182 day period.
Those without a prior visit/encounter were considered ‘new’ clients.
5. We also performed an analysis of all clients in the CSI database during the above noted
study period. In this case, data were aggregated in typical 1-calendary year groupings.
Similar to the new client process, we reviewed ADMISSION-DATE and SERVICE-DATE
fields to create our DATE-OF-SERVICE variable. We found that there were some clients
who had an ADMISSION-DATE from a prior year, indicating continuous inpatient status
beginning before the calendar year of interest. Those clients were excluded from the
analysis, leaving only unique clients (based on CCN) with a DATE-OF-SERVICE for
each study year.
Both new and all clients were categorized as follows:
Belonging to the county in which they received services.2 In the CSI dataset this is the
variable designated as SUBMITTING COUNTY CODE which identifies the
County/City/Mental Health Plan submitting the record.
Belonging to a region3
Belonging to the State of California
Age groups.4 The client’s age was calculated by subtracting the DATE-OF-BIRTH from
the DATE-OF-SERVICE.
Sex, including Male, Female, Other and Unknown/Not Reported using the CSI data field,
GENDER5
2 We note the limitation caused by not having the patient’s actual county of residence and simply assuming that they
reside in the county in which they receive services.
3 We used the regions originally operationalized by the California Mental Health Directors Association’s (CMHDA)
designated five Workforce, Education and Training (WET) regions since these regions will correspond with other
regional reports and programs such as CalMHSA. See
http://www.cmhda.org/go/aboutcmhda/organizationalstructure.aspx for a regional definition map.
4 Age groups to be used in all analyses include: Children Youth and Families (CYF) 0-15 years, Transitional Age
Youth (TAY) 16-25 years, Adults 26-59 years, Older Adults 60+ years. In addition, the category of Older Adults (age
60+) was further disaggregated as follows: 60-64, 65-69, 70-74, 75-80, 80-84, 85+. This will more accurately
document the access for the last 40 years of the individual’s life.
5 We will provide frequency statistics for the Other and Unknown/Not Reported categories. However, these categories
are not large enough for multi-dimensional analysis.
82
RACE, including Caucasian, Hispanic, African American, Asian, Hawaiian/Pacific
Islander, American Indian/Alaskan Native, Other, Two or More Races, and Unknown
Race6
ETHNICITY to identify whether the client is Hispanic or Latino7
PRIMARY LANGUAGE used by the client8
Nativity using POB-COUNTRY.
For each categorical variable above, we calculated frequencies and proportions by county,
region, and state, and presented trend information over time using appropriate tabular and
graphical methods.
California Health Interview Survey (CHIS) Analysis
Although our CSI analysis focuses on mental health access in California by population
subgroup, we assert that in order to truly understand if disparity is present, one must control for
the health status of the population subgroup in question; since the literature tell us that health
status varies from one group to another and from one geographic place to another. For that
reason, we also utilized the California Health Interview Survey (CHIS) to better understand how
mental health needs differ by population and place. Our method for analysis of CHIS data was
as follows:
We provide state and regional information on mental health needs across time (via CHIS9) in
California for 2005, 2007, 2009, and 2011-2012.
o The method is based on the report to DMH from 11/2010 entitled, “Assessing Adult
Mental Health Needs in California Using the California Health Interview Survey
6 Apparently, there was a change in CSI reporting requirements in 2006 to expand the reporting of ethnicity and race.
This led to an uneven implementation of this change by counties and lack of consistency of information before and
after 2006. We will make adjustments as necessary due to this change in the collection of race/ethnicity data in
2006. We will analyze the differences in reporting of ethnicity and race and create an approach that will maximize
homogeneity in the data. Most likely, this will involve ‘up aggregating’ ethnic groups to the most common level (e.g.,
Chinese, Korean and Vietnamese may need to be aggregated to a category of Asian/Pacific Islander). In the event
that some larger counties have consistently collected expanded race/ethnicity categories, we will perform our analysis
for those counties at the subgroup, more granular level.
7 Within the CSI database, race and ethnicity are treated separately. In addition, the U.S. Census Bureau takes the
same approach. Therefore, to allow comparisons to larger populations, we will treat race and ethnicity as separate
variables.
8 Similar to footnote 7 above, we expect that primary and preferred language fields will need to be ‘aggregated’ to
ensure adequate power for analysis. According to the 2000 U.S. Census, there were over 150 different languages
spoken in U.S. households. Potential solutions include classification according to root languages or by consistency
with Race/Ethnicity categories.
9 The California Health Interview Survey is conducted every other year (e.g., 2005 results were collected between
July 2005 and April 2006). The determination of mental health need developed by UCLA/UCD uses a set of mental
health and substance use related questions that became a part of the survey in 2005.
83
(CHIS)” by Padilla-Frausto, Grant and Aguilar-Gaxiola (see references for details on
the methodology).
o In this report, mental health need was determined from a combination of distress and
functional impairment measures. The distress component was based on a set of
questions known as the Kessler 6, resulting in a continuous measure of
psychological distress during the respondents previous month. Functional
impairment was determined from the Sheehan Disability Score which measured
whether a respondent was experiencing impaired function in any one of four life
domains.
o Because the California Health Interview Survey is constantly evolving and changing,
our ability to measure mental health needs consistently was impaired. Using the best
information available, we calculated mental health needs as follows:
o 2005: includes distress measure only as Sheehan variables were not yet part of
the survey
o 2007 & 2009: used both distress and functional impairment measures
o 2011-2012: also used both distress and functional impairment measures,
however the distress scores have a higher qualifying score this year than in 2007
and 2009 and are therefore not fully comparable.
84
Appendix B. Contextual Information –
A Historical Timeline
A detailed timeline, organizing contextual factors surrounding the implementation of the MHSA
and other statutes, regulations, policies and external forces impacting mental health access is
provided over the following several pages.
MHSA Timeline10
November 2004 Proposition 63 (Mental Health Services Act) passed
Includes funding “formulas” (WIC sections 5891 and 5892) for
Community Services and supports, Innovation, Capital
Facilities and Technological Needs, Workforce Education and
Training, Local Prudent Reserve and Administrative costs.
Includes required information for Community Planning process
(5848), Development of three year program and expenditure
plans and annual updates (5847), requirements for MHSOAC
(5845), Human Resources, education and training (later called
Workforce Education and Training) (5820), Innovative
Programs (5830), MHSA fiscal requirements (5890 and 5891 in
addition to the allocation amounts described in 5892.
January 2005 DMH Letter 05-01; Instruction to counties regarding how to
make MHSA funding requests for Community Planning
June 2005 DMH Letter 05-02; Notification of Planning Estimates
July 2005 DMH Letter 05-04; Instruction to counties regarding non-
supplantation of MHSA funds (5891)
August 2005 DMH Letter 05-05; Instruction to counties regarding how to
develop three year program and expenditure plans for the
community services and supports component of the MHSA
September 2005 DMH Letter 05-06; instruction to counties on how to use start-
up funding and the Local Prudent Reserve
October 2005 DMH Letter 05-08; Instruction to counties as to funding
requirement of the MHSA
10 The timeline used in this report was originally created by a staff member of the Mental Health Services Oversight
and Accountability Commission with a focus on the significant events related to the Mental Health Services Act
(MHSA). We have added additional information to this historical timeline to highlight other events that may be
related to access to mental health care and therefore to our evaluation of the impact of the MHSA.
85
April 2006 DMH Information Notice 06-02; Instruction to counties
regarding costs and program oversight tracking requirements
under federal accountability reporting req1uirements
August 2006 DMH Information Notice 06-08; Instruction to counties
regarding implementation of integrated three year program and
expenditure plans (5847, 5848 and 5892)
October 2006 DMH Information Notice 06-12; Instruction to counties
regarding pilot for cash flow statement
November 2006 DMH Information Notice 06-13; Allowable use of CSS funds for
enhancing local infrastructure
December 2006 DMH Information Notice 06-15; instruction to counties
regarding performance contract amendment process to capture
CSS component
February 2007 CSS Regulations Promulgated; codifies fiscal and programmatic
requirements of MHSA funds to the counties. Defines terms,
defines parameters of supplant, defines and codifies full
service partnerships, outreach and engagement, general
system delivery. Defines and codifies community planning
process, defines and codifies some fiscal policies. Codifies
reporting requirements.
July 2007 DMH Information Notice 07-14; Mental Health Services Act
(MHSA) Workforce Education and Training Component -
Proposed Three Year Program and Expenditure Plan Guidelines,
Fiscal Years 2006-07, 2007-08, and 2008-09
September 2007 DMH Information Notice 07-19; Mental Health Services Act
(MHSA) Prevention and Early Intervention Component —
Proposed Three-Year Program and Expenditure Plan Guidelines,
Fiscal Years 2007-08 and 2008-09
December 2007 DMH Information Notice 07-25; Mental Health Services Act
Fiscal Policy Changes
Accounting changes from quarterly payments to 75% and 25%
depending on successful submission of Revenue and
Expenditure report, cash flow statements. Information Notice
also clarifies and defines interest earned on the mental health
services fund, local prudent reserve, component allocations,
unexpended funds. Program sustainability, one time funding,
cash management, MHSA agreement, payments to the counties
DMH Information Notice 07-26; Implementation of the Annual
Mental Health Services Act (MHSA) Revenue and Expenditure
Report for Fiscal Year 2006-07; (WIC 5847)
86
End of Year 2007 Beginning of economic crisis. By year end, the U.S. foreclosure
rate was up 75% from 2006. More than 1% of all households
were in some stage of foreclosure during 2007.
January 2008 DMH Information Notice 08-01; Request to dedicate funds to
the Mental Health Services Act Community Services and
Supports Prudent Reserve. (WIC 5847)
January 2-21, 2008 Stock market downturn.
March 2008 DMH Information Notice 08-07; Mental Health Services Act
(MHSA) Reversion Policy (WIC 5892)
DMH Information Notice 08-08; Implementation Progress
Report for the Community Services and Supports (CSS)
Component of the Three-Year Program and Expenditure Plan for
Calendar Year 2007
DMH Information Notice 08-09; Mental Health Services Act
Capital Facilities and Technological Needs Component - Three-
Year Program and Expenditure Plan Guidelines (WIC 5847, 5848,
5892)
April 2008 DMH Information Notice 08-10; Community Services and
Supports (CSS) Plan Update Guidelines for Fiscal Year (FY)
2008/09 (5847, 5878.3, 5892)
DMH Information Notice 08-11; Assignment of Community
Services and Supports (CSS) Funds for the Mental Health
Services Act (MHSA) Housing Program
DMH Information Notice 08-12; Community Services and
Supports General System Development Housing
July 2008 DMH Information Notice 08-16; Plan Update Guidelines for
Fiscal Year 2008/09 Addendum—Modified Process
Changes counties’ use of unexpended funds, delays deadline for
prudent reserve plan, allows for continuation of previously
approved WET and CFTN projects.
July 30, 2008 Housing and Economic Recovery Act of 2008.
October 2008 DMH Information Notices 08-28; Proposed Guidelines for the
Mental Health Services Act (MHSA) Fiscal Year (FY) 2009/2010
Annual Update to the Three-Year Program and Expenditure Plan
(5847)
87
End of Year 2008 Foreclosure rate up 81% from 2007. More than 1.84% of all
households were in some stage of foreclosure during 2008.
January 2009 DMH Information Notice 09-01; Implementation of the Annual
Mental Health Services Act (MHSA) Revenue and Expenditure
Report for FY 2007-08 (5847)
January 5, 2009 AB5XXX, amends WIC Sections 5845, 5846 and 5847 of the
MHSA
5845: (paraphrased) That the commission will administers its
operations separate from the State Department of Mental
Health, that the commission may enter into contracts, that
the commission may obtain data and information form the
State Department of Mental Health, or other state or local
entities that receive Mental Health Services Act Funds, for the
commission to utilize its oversight, review and evaluation
capacity regarding projects and programs supported with
Mental Health Services Act funds, participate in the joint state-
county decision making process, as contained in Section 4061,
for training, technical resources to meet the mission and goals
of the state’s mental health system.
5846: The commission shall place a county
expenditure plan for consideration on a meeting
agenda no later than 60 days after receipt, The
commission shall issue guidelines for expenditures
pursuant to Part 3.2 (commencing with Section
5830), for innovative programs, and Part 3.6
(commencing with Section 5840), for prevention
and early intervention, no later than 180 days
before the fiscal year for which the funds will
apply
5847:
(a) It is the intent of the Legislature to streamline the approval
processes of the State Department of Mental Health and the
Mental Health Services Oversight and Accountability
Commission of programs developed pursuant to Sections 5891
and 5892
(g) (1) The department shall evaluate each proposed
expenditure plan and determine the extent to which each
county has the capacity to serve the proposed number of
children, adults and seniors pursuant to Part 3 (commencing
with Section 5800), and Part 4 (commencing with Section 5850);
88
the extent to which there is an unmet need to serve that
number of children, adults and seniors; and determine the
amount of available funds; and provide each county with an
allocation from the funds available. The department shall give
greater weight for a county or a population which has been
significantly underserved for several years. The department
shall approve, deny, or request information on a county
expenditure plan or update no later than 60 days upon receipt.
(g)(2) The department shall only evaluate those programs in a
county expenditure plan or update that have not previously
been approved or that have previously identified problems
which have been conveyed to the county. The department shall
distribute the funds for renewal of the previously approved
programs contained in the county expenditure plan or update
prior to approval of the county expenditure plan or update.
January 30, 2009 DMH Innovation Notice 09-02: Proposed Guidelines for the
Innovation Component (WIC 5830)
March 2009 DMH Information Notice 09-03: State Administered Mental
Health Loan Assumption Program (WET)
August 2009 DMH Information Notice 09-16: MHSA Prudent Reserve
ABX3 5 amended WIC 5847(b) (7) and expanded
Prudent reserve to include CSS and PEI programs; changed sue
date for level of funding of prudent reserve to June 30, 2011;
prior to FY 2008-09 both CSS and PEI funds may be used to fund
the prudent reserve; access to local prudent reserve effective
July 1, 2010; 50% prudent reserve requirement suspended
December 2009 DMH Information Notice 09-20: Planning Estimates for FY
2010-11.
Limit on the use of CSS funds in addition to estimates for CSS,
PEI, and INN
DMH Information Notice 09-22: MHSA Revenue and
Expenditure report for Fiscal Year 2008-09
Workforce Education and Training Component Regulations
promulgated.
End of Year 2009 Foreclosure rate up 21% from 2008. More than 2.21% of all
households were in some stage of foreclosure during 2009.
2010 The Patient Protection and Affordable Care Act includes
measures to expand affordable forms of health insurance
89
coverage and identifies mental health and substance abuse as
one of 10 essential areas of coverage.
January 2010 DMH Information Notice 10-01: Proposed Guidelines for the
Mental Health Services Act (MHSA) Fiscal Year 2010/11 Annual
Update to the Three-Year Program and Expenditure Plan
Provides fiscal distinction for reporting previously approved,
new, eliminated and consolidated component services and
programs to meet criteria established in AB X3 5. Fiscal
distinction for administrative and operating costs, suspension of
50% funding level requirement for local prudent reserve for FY
10-11
March 17, 2010 DMH Information Notice 10-04: Clarification and Modifications
to Enclosures for the Proposed Guidelines for the Mental
Health Services Act (MHSA) Fiscal Year 2010/11 Annual Update
to the Three-Year Program and Expenditures Plan
This Department of Mental Health (DMH) Information Notice
provides an update and clarification to Counties about policies
related to the Proposed Guidelines for the Mental Health
Services Act (MHSA) Fiscal Year (FY) 2010/11 annual update to
the Three-Year Program and Expenditure Plan released on
January 19, 2010. (Information Notice No. 10-01) This has been
prepared to summarize the changes made by DMH and the
Mental Health Services Oversight and Accountability
Commission (MHSOAC) to some exhibits as a result of Counties’
questions and inquiries on the exhibits released. Please
continue to use the exhibits in Information Notice No. 10-01,
unless the exhibit has been replaced with one of the exhibits
listed below. Specifically, this Information Notice addresses the
following topics:
1. Exhibit C1, Implementation Progress Report on FY 08/09
Activities
2. Exhibit D, Previously Approved Program for Community
Services and Supports (CSS), Workforce Education and
Training (WET), Prevention and Early Intervention (PEI), and
Innovation (INN) components
3. Exhibit E4, PEI Budget Summary
5. Exhibit F3, TN New and Existing Project Description
6. Exhibit F4, PEI New Program Description
7. Exhibit F5, INN New Program Description
8. Exhibit I, Training, Technical Assistance and Capacity
Building Funds Request Form (Prevention
and Early Intervention Statewide Project)
90
March 29, 2010 DMH Information Notice 10-05: Assignment of MHSA
Prevention and Early Intervention Funds for Statewide
Programs (Suicide Prevention, Student Mental Health
Initiative, Stigma and Discrimination Reduction)
Provides the counties ways to make these assignments:
To DMH for statewide administration of PEI programs
To DMH to enter into contract with CalMHSA for
administration of the programs or
A county may enter into an agreement with other
counties to implement a statewide program
DMH Information Notice 10-06: Guidelines for Prevention
and Early Intervention Statewide Programs
May 25, 2010 DMH Information Notice 10-12: Clarification and
Modification to the Annual MHSA Revenue and Expenditure
Report for FY 2008-09
Provides an update and clarification to Counties about guidance
for the Mental Health Services Act (MHSA) Annual Revenue and
Expenditure Report (Revenue and Expenditure Report)
requirements for Fiscal Year (FY) 2008-09 released on December
28, 2009 (Information Notice No. 09-22).
This update is necessary to:
1. Allow Counties to report expenditures of Prevention and
Early Intervention (PEI) Statewide Training, Technical Assistance
and Capacity Building funds, and
2. Instruct Counties on the reporting of expenditures when
Counties incur expenditures prior to the disbursement of funds.
June 17, 2010 DMH Information Notice 10-13: Reversion Policy of MHSA
Prevention and Early Intervention Funds for Component
Allocation for the PEI Statewide Programs.
This is later changed with a letter to CalMHSA
however the Information Notice is not rescinded. The letter
advises CalMHSA that funds “assigned” to them are
considered spent and therefore will not revert, in the same
way that MHSA Housing funds were assigned to CalHFA and
not subject to reversion.
November 24, 2010 DMH Information Notice 10-26: Implementation of the Annual
MHSA Revenue and Expenditure Report for Fiscal Year 2009-
10 Superseded by Information Notice 10-29
91
Includes revision dated 03-08-2011 to the County RER
Summary, enclosure 11
December 2, 2010 DMH Information Notice 10-27: Implementation of the State-
Administered Mental Health Loan Assumption Program for state
Fiscal Year 29010-11
December 8, 2010 DMH Information Notice 10-29: Clarification to Implementation
of the Annual Mental Health Services Act Revenue and
Expenditure Report for Fiscal Year 2009-10; supersedes
Information Notice 10-26
This Information Notice supersedes Information Notice No. 10-
26, which was released November 24, 2010.
Paragraph two of Information Notice No. 10-26 is revised to
read as follows:
The MHSA intends that Counties use other available
funding sources to offer mental health services prior to
the expenditure of MHSA dollars. Currently, Counties
report the expenditure of other funds, including FFP, in
aggregate for all ages on the Revenue and Expenditure
Report. Next year, Counties will be expected to report
leveraged FFP funding separately for children (under
age 21) and for adults. In preparation for the reporting
of this data, Counties are advised to begin to establish
necessary tracking mechanisms, if not already in place.
Please note that other than the minor revision made in the
above paragraph, other information and forms listed in
Information Notice No. 10-26 remain the same and in effect.
December 21, 2010 DMH Information Notice 10-21: Guidelines for FY 2011-12
Annual Update. Supersedes Information Notices 10-01 and 10-
04
Fully implements the previously approved, new, elimination and
consolidation of programs definitions.
Defines unexpended and unapproved funds. Defines
administrative costs (direct service and indirect administrative
costs), operating reserve, provides access and procedural access
to local prudent reserve.
End of Year 2010 Foreclosure rate up 2% from 2009. More than 2.23% of all
households were in some stage of foreclosure during 2010.
92
2011 Realignment 2011 gives counties more money and more
responsibility for a range of mental health, substance abuse,
and criminal justice services. Assembly Bill 114 transfers
responsibility and funding for educationally related mental
health services from county mental health departments
to county education departments.
March 24, 2011 Governor Brown signed into law AB 100, an urgency bill which
went into effect immediately. Some of the major changes
included:
Deleted requirement that the Department of Mental Health
(DMH) and the Mental Health Services Oversight and
Accountability Commission (MHSOAC) annually review and
approve county plans and updates.
Deleted requirement that a county annually update the 3-year
plan but still required that there be updates.
The Commission, instead of DMH, may provide technical
assistance to any county mental health plan as needed.
The “state” instead of DMH will administer the Mental Health
Services Fund (MHSF).
The “state” instead of DMH will issue regulations.
Starting July 1, 2012 the Controller shall distribute on a monthly
basis to counties all unexpended and unreserved (“Unreserved
funds” are those funds that are not held in trust or are not set
forth in component allocations) funds on deposit in the MHSF as
of the last day of the prior month.
Reduced the administrative funds reserved for DMH, MHSOAC,
and California Mental Health Planning Council (CMHPC) from
five percent (5%) to three and half percent (3.5%) and that
these funds are subject to legislative appropriation.
Provided for a one time transfer of $862M from the MHSF
which is not subject to repayment to be distributed in the
following order:
$183,600,000 for Medi-Cal Specialty Health Managed Care;
$98,586,000 for mental health services for special education
pupils (generally referred to as AB 3632);
50% of each county’s 2011/12 MHSA component allocations not
to exceed $488,000,000;
$579,000,000 for Early and Periodic Screening, Diagnostics and
Treatment (EPSDT); and
The remainder of each county’s 2011/12 component allocation.
Established monthly distributions to counties by SCO
commencing April 30, 2012
Unstated were issues related to revenue and expenditure
report, when and how and to whom should it be reported;
93
annual update, to whom should it go and other oversight and
fiduciary responsibilities previously held by DMH, MHSOAC, etc.
This bill along with AB 102, passed in the same year, sets into
motion the elimination of the Department of Mental Health and
call various other departments (Alcohol and Drug Programs,
Health Care Services, Public Health as well as DMH) to
commence with stakeholder meetings and to begin to prepare
transition plans for programs and staff that were remaining
after the initial reduction in force of 119 DMH employees.
April 8, 2011 DMH Information Notice 11-05: MHSA Prudent Reserve Fiscal
Policy Change
Welfare and Institutions Code (Welf. & Inst. Code) section 5847,
subdivision (b)(7), requires Counties to include in their Three-Year
Program and Expenditure Plans or updates a prudent reserve to
ensure that the County programs will continue to be able to serve
those currently being served should MHSA revenues decrease.
DMH Information Notice No.: 07-25 required that Counties
establish and maintain a Local Prudent Reserve equal to 50
percent of the amount approved from Community Services and
Supports (CSS) for services in the fiscal year. The 50 percent Local
Prudent Reserve requirement is rescinded by the publication of
this Information Notice. Please note that, other than this
change in fiscal policy, all other policy and guidance on the Local
Prudent Reserve remains in effect. With the rescission of this
policy, Counties may fund the Local Prudent Reserve to a level the
County determines is appropriate consistent with Welf. & Inst.
Code § 5892, subd. (b).
Welfare & Institutions Code section 5892, subdivision (b) permits a
County to use up to 20 percent of the average amount of funds
allocated to that county for the previous five years to fund for
technological needs and capital facilities, human resource needs,
and a prudent reserve. This change in policy permits a County to
use the total of this amount to fund its Local Prudent Reserve
needs, if it elects to do so, even if this amount exceeds the
previously required 50 percent level.
Mid-Year 2011 Foreclosure rate down 34% from 2010. A total of 0.9% of all
households were in some stage of foreclosure during the first
half of 2011.
October 27, 2011 DMH Information Notice 11-13 Implementation of the State –
Administered Mental Health loan Assumption Program.
94
December 5, 2011 DMH Information Notice 11-15: Calculation of Reversion of MHSA
Innovation Component Funds
Section 5892(h) of WIC requires the reversion of funds
which have not been spent for their authorized purpose
within specified timeframes to the state Mental Health
Services Fund. In calculating reversion of unexpended funds
Counties should consider Innovation funds that have been
expended as part of their CSS and PEI expenditures, with 20
percent of the Innovation expenditures associated with PEI
and 80 percent associated with CSS.
To determine the amounts of funds subject to reversion,
Counties are instructed to total their expenditures and
subtract these expenditures from the distribution for the
year for which funds are reverting separately for PEI and CSS.
If the total expenditures for CSS or PEI (including Innovation
funds) are greater than the amount distributed for CSS or PEI
(including Innovation funds), no funds will revert. If
expenditures are less than the amount distributed, the
difference is the amount of funds that will revert to the State
Mental Health Services Fund.
December 27, 2011 DMH Information Notice 11-16: Amendment of the Annual
MHSA Revenue and Expenditure Report for Fiscal Years 2008-
09 and 2009-10
This Department of Mental Health (DMH) Information Notice
provides clarification and guidance to Counties for the Annual
Mental Health Services Act (MHSA) Revenue and Expenditure
Report (Revenue and Expenditure Report) for Fiscal Years (FY)
2008-09 and 2009-10. This clarification and guidance is
necessary to address how to report the expenditures of
approved funds released to some Counties over two fiscal years
and to provide a simplified reporting format.
In order to simplify the completion of the Revenue and
Expenditure Report, the State has amended and consolidated
the required information. This Information Notice
supersedes previous guidance provided in DMH Information
Notice Nos.: 09-22, 10-12, and 10-26.
2012 Legislature eliminates the Department of Mental Health,
95
creates the Department of State Hospitals, and transitions
responsibility for managing all community mental health
services functions to the Department of Health Care Services.
May 17, 2012 DMH Information Notice 12-04: Implementation of the
Annual MHSA Revenue and Expenditure Report for Fiscal
Year 2010-11
Expenditures should be reported using the modified accrual
basis of accounting. The modified accrual basis of accounting
requires expenditures to be reported in the fiscal year in
which the fund liability is incurred, whether or not the e
expenditure has been paid. This is to acknowledge some
situations where Counties were approved for a level of funds
and received the funds over two fiscal years.
May 18, 2012 Final draft of DMH Transition Plan. Required by AB 102, the
Department of Mental Health was required to develop a
transition plan, based on input from its stakeholders,
reporting the process for transferring its staff, programs and
financing to other State Departments. Complete copy of
text below:
http://www.dsh.ca.gov/Publications/docs/Transition_Plan/D
MHTransitionPlan.pdf
July 1, 2012 AB 1467 introduced January 2012, approved June 27, 2012,
effective July 1, 2012
Completes the transfer of DMH MHSA programs and staff to
other state departments
Clarifies approval process for Innovation, annual updates,
promulgation of regulations, fiscal reporting requirements,
stakeholder processes, other fiscal issues
Clarifies departmental roles in providing technical assistance,
revenue and expenditure reporting, annual update review
and approval process at county
Complete copy of text below:
http://legiscan.com/CA/text/AB100/id/222597
2013 The State Auditor Completes Audit on the MHSA
The 2010 Cultural Competence Plans under review.
96
The Obama administration will issue long-awaited final rules
requiring all private American insurance plans — in the
individual, group, and employer markets — to cover mental
health treatments on equal footing with more traditional
physical medical care. The new rules are the final step in
implementing the 2008 Wellstone-Domenici Mental Health
Parity and Addiction Equity Act and add to Affordable Care Act
requirements that will extend mental health benefits to millions
of Americans for the first time, making the regulations one of
the single biggest expansions of mental health coverage in
American history.
The Affordable Care Act builds on the Mental Health Parity and
Addictions Equity Act to expand mental health and substance
use disorder benefits and federal parity protections for more
than 60 million Americans. New health plans are now required
to cover preventive services like depression screenings for
adults and behavioral assessments for children at no additional
cost. And starting next year, insurance companies will no longer
be able to deny health care coverage to anyone because of a
pre-existing mental health condition.
June 2013 White House has National Conference on Mental Health
2013 Ongoing shootings throughout the nation may have impacted
stigma toward mental illness.
Government shut down stalled monthly benefits to veterans
and the unemployed, and may also have affected disability
payments. Some people with mental illness get disability
because of their diagnosis.
We are having a cold winter. When the weather gets cold some
homeless people with mental illness exacerbate their symptoms
so that they can be detained (via psychiatric hold). They lack
housing. Without proper housing they cannot have proper
recovery.
97
Appendix C. CSI Data Tables – State and Region Tables
Note: NEW client tables are green, ALL client tables are blue. 2012 has been shaded in grey to
indicate data are incomplete. The 2012 data can, however, be used to compare between
subgroups for the year, but is not appropriate for trending analysis.
Statewide – New Clients Frequencies (Actual Counts of New Clients)
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 108,254 128,266 135,232 139,012 129,181 129,742 131,965 52,883
Male 122,886 150,273 159,520 165,039 150,375 143,415 158,252 61,496
Other Sex 11 18 16 21 26 24 23 13
Unknown Sex 54,664 1,186 1,078 970 474 494 456 238
CYF 69,209 78,253 82,679 85,301 83,947 86,758 88,693 31,394
TAY 47,212 60,578 63,780 69,420 63,632 61,627 61,023 25,026
Adults 106,313 128,668 136,075 136,349 120,176 113,212 127,172 52,134
Older Adults 8,842 12,192 13,248 13,891 12,196 11,856 12,944 5,314
Age 60-64 3,799 4,932 5,807 5,937 5,630 6,006 6,600 2,742
Age 65-69 1,620 2,307 2,579 2,682 2,426 2,256 2,628 1,102
Age 70-74 1,062 1,448 1,619 1,705 1,461 1,260 1,450 571
Age 75-79 930 1,287 1,228 1,323 1,054 936 931 354
Age 80-84 746 1,060 1,070 1,121 825 696 679 290
Age 85+ 685 1,158 945 1,123 800 702 656 255
Age Missing 54,239 52 64 81 105 222 864 762
Hispanic 22,207 51,113 80,890 91,413 90,155 92,246 97,776 38,991
Not Hispanic 37,272 74,854 112,623 124,728 115,140 116,222 116,074 50,669
Unknown Ethnicity 226,336 153,776 102,333 88,901 74,761 65,207 76,846 24,970
White 75,885 64,070 42,559 40,125 34,385 30,269 24,969 8,880
Hispanic 63,969 57,167 49,243 48,116 46,778 43,844 27,743 5,451
Black 39,456 37,946 30,776 29,903 26,681 22,226 19,660 3,956
Asian 6,272 5,139 4,068 3,672 3,332 2,767 1,889 440
Native Hawaiian/Pacific Islander 389 276 190 186 154 139 108 33
American Indian/Alaskan Native 1,868 1,551 1,060 906 818 710 560 234
Other Race 4,445 4,524 3,304 3,334 3,123 2,381 1,742 467
Two or More Races 76 55 22 19 13 12 12 5
Unknown Race 93,455 109,015 164,624 178,781 164,772 171,327 214,013 95,164
USA Born 163,878 195,177 208,816 222,128 208,499 206,521 212,356 86,055
Foreign Born 67,299 83,940 86,544 82,494 71,196 66,901 78,052 28,450
Unknown Place of Birth 54,638 626 486 420 361 253 288 125
Language Reported 53,330 64,420 70,805 63,865 47,998 31,398 29,952 8,067
Language Unknown 232,485 215,323 225,041 241,177 232,058 242,277 260,744 106,563
Total Population 285,815 279,743 295,846 305,042 280,056 273,675 290,696 114,630
98
Statewide - New Clients Proportions per 100,000
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 609 704 740 757 700 691 697 277
Male 702 825 873 898 812 772 844 325
CYF 860 992 1,071 1,104 1,072 1,135 1,162 412
TAY 957 1,114 1,160 1,263 1,189 1,099 1,086 444
Adults 618 724 765 767 671 631 702 286
Older Adults 173 227 239 242 207 193 204 81
Age 60-64 270 341 374 364 324 319 340 139
Age 65-74 138 187 205 206 178 153 172 66
Age 75-84 125 168 163 175 137 120 116 46
Age 85+ 163 221 174 191 134 114 104 39
Total Population 810 767 809 830 758 733 771 301
99
Statewide-All Clients Frequencies (Actual Counts of All Clients)
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 256,442 300,956 302,969 313,356 307,021 298,940 291,596 186,659
Male 273,653 326,341 332,612 345,393 334,033 320,909 326,243 205,664
Other Sex 40 47 40 46 56 47 52 37
Unknown Sex 104,453 2,111 2,248 2,015 1,007 1,004 765 471
CYF 141,397 165,515 166,635 173,004 175,529 176,997 176,283 108,337
TAY 86,852 112,409 115,740 124,281 122,416 119,916 116,998 70,909
Adults 272,693 314,441 316,707 321,579 302,367 282,671 284,771 184,513
Older Adults 30,331 36,988 38,665 41,810 41,644 41,033 39,609 28,083
Age 60-64 15,958 18,427 20,008 21,561 22,144 22,562 22,241 16,318
Age 65-69 6,471 8,070 8,433 9,204 9,262 9,004 8,671 6,176
Age 70-74 3,227 4,074 4,243 4,615 4,581 4,272 4,128 2,786
Age 75-79 2,227 2,840 2,675 2,867 2,623 2,461 2,202 1,396
Age 80-84 1,404 1,895 1,860 1,938 1,665 1,538 1,337 845
Age 85+ 1,044 1,682 1,446 1,625 1,369 1,196 1,030 562
Age Missing 103,315 102 122 136 161 283 995 989
Hispanic 53,787 92,624 139,706 165,630 175,251 180,752 186,209 115,580
Not Hispanic 121,374 174,017 235,957 263,837 262,596 256,999 246,755 154,955
Unknown Ethnicity 459,427 362,814 262,206 231,343 204,270 183,149 185,692 122,296
White 174,952 173,035 130,353 121,849 110,410 97,383 83,533 50,468
Hispanic 121,395 127,653 106,693 108,172 108,314 104,275 84,992 43,036
Black 85,484 89,625 76,151 72,953 67,984 60,795 53,869 26,352
Asian 18,992 18,706 15,397 14,851 14,327 13,077 10,451 6,690
Native Hawaiian/Pacific Islander 736 682 516 473 437 387 317 179
American Indian/Alaskan Native 4,285 4,336 3,288 2,989 2,730 2,398 1,982 1,269
Other Race 12,301 12,335 10,243 10,036 9,728 8,304 6,797 4,008
Two or More Races 103 114 73 52 41 35 31 26
Unknown Race 216,340 202,969 295,155 329,435 328,146 334,246 376,684 260,803
USA Born 387,145 457,841 467,403 491,631 485,318 471,480 459,935 286,319
Foreign Born 142,544 169,653 168,740 167,862 155,723 148,673 157,993 105,982
Unknown Place of Birth 104,899 1,961 1,726 1,317 1,076 747 728 530
Language Reported 119,487 142,670 147,851 145,809 128,776 105,534 94,997 62,319
Language Unknown 515,101 486,785 490,018 515,001 513,341 515,366 523,659 330,512
Total Population 634,588 629,455 637,869 660,810 642,117 620,900 618,656 392,831
Statewide-All Clients Proportion of All Clients per 100,000 Population
100
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,442 1,651 1,658 1,706 1,665 1,592 1,539 976
Male 1,564 1,791 1,819 1,879 1,804 1,728 1,740 1,087
CYF 1,758 2,098 2,158 2,238 2,242 2,316 2,311 1,421
TAY 1,760 2,068 2,105 2,260 2,287 2,138 2,082 1,258
Adults 1,586 1,771 1,781 1,808 1,689 1,575 1,573 1,013
Older Adults 594 688 696 728 708 667 625 427
Age 60-64 1,134 1,275 1,290 1,323 1,274 1,200 1,147 828
Age 65-74 499 606 619 649 635 579 538 353
Age 75-84 271 338 322 343 313 293 255 159
Age 85+ 248 321 266 277 230 195 163 86
Total Population 1,799 1,727 1,745 1,798 1,737 1,662 1,641 1,033
101
Superior Region – New Clients Frequencies (Actual Counts of New Clients)
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 3,248 4,401 4,291 4,569 4,111 4,679 4,743 3,208
Male 2,816 3,837 3,770 4,025 3,857 4,493 4,323 3,056
Other Sex 0 1 0 2 1 0 1 2
Unknown Sex 21 20 27 54 29 14 15 29
CYF 1,715 2,442 2,451 2,424 2,443 2,803 2,667 1,735
TAY 1,196 1,688 1,646 1,813 1,656 1,948 1,909 1,349
Adults 2,936 3,785 3,597 4,011 3,524 3,979 4,037 2,852
Older Adults 234 343 391 401 374 452 467 348
Age 60-64 110 169 170 181 184 212 219 157
Age 65-69 39 58 95 91 76 97 118 92
Age 70-74 27 34 46 51 43 61 53 48
Age 75-79 19 30 39 36 34 36 29 22
Age 80-84 11 25 29 18 21 29 21 15
Age 85+ 28 27 12 24 16 17 27 14
Age Missing 4 1 3 1 1 4 2 11
Hispanic 196 419 675 891 910 1,138 1,198 801
Not Hispanic 2,044 3,701 4,882 5,924 6,034 6,930 6,730 4,592
Unknown Ethnicity 3,845 4,139 2,531 1,835 1,054 1,118 1,154 902
White 4,026 3,546 1,523 1,678 1,313 1,338 1,280 832
Hispanic 300 276 110 121 89 80 97 43
Black 119 83 39 44 39 37 40 18
Asian 44 32 9 17 13 10 5 8
Native Hawaiian/Pacific Islander 6 1 2 1 1 2 1 1
American Indian/Alaskan Native 299 212 94 97 81 88 74 61
Other Race 75 59 25 41 32 43 34 26
Two or More Races 0 0 0 0 0 1 0 0
Unknown Race 1,216 4,050 6,286 6,651 6,430 7,587 7,551 5,306
USA Born 5,426 7,396 7,410 7,997 7,480 8,635 8,501 5,844
Foreign Born 652 830 663 626 488 536 558 430
Unknown Place of Birth 7 33 15 27 30 15 23 21
Language Reported 557 751 511 517 328 159 137 85
Language Unknown 5,528 7,508 7,577 8,133 7,670 9,027 8,945 6,210
Total Population 6,085 8,259 8,088 8,650 7,998 9,186 9,082 6,295
Superior Region–New Clients Proportion of New Clients per 100,000 Population
102
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 580 766 762 802 720 769 795 473
Male 528 704 698 738 687 779 750 462
CYF 1,075 1,472 1,472 1,483 1,464 1,535 1,206 712
TAY 1,177 1,516 1,523 1,623 1,697 1,519 1,002 597
Adults 748 919 923 984 874 904 641 405
Older Adults 161 232 211 238 227 224 206 140
Age 60-64 285 384 319 331 354 255 215 139
Age 65-74 107 142 218 196 136 204 129 102
Age 75-84 58 119 128 115 157 109 78 45
Age 85+ 143 214 47 110 62 108 111 57
Total Population 731 939 935 969 902 910 663 403
103
Superior Region-All Clients Frequencies (Actual Counts of All Clients)
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 9,697 12,085 12,022 12,419 11,558 11,593 11,846 9,993
Male 8,141 10,289 10,360 10,789 10,308 10,744 10,899 9,171
Other Sex 1 2 2 2 3 1 2 3
Unknown Sex 27 27 36 75 57 32 26 43
CYF 4,586 5,973 6,182 6,337 6,275 6,338 6,571 5,336
TAY 2,690 3,754 3,681 3,938 3,785 3,987 4,103 3,407
Adults 9,565 11,420 11,151 11,553 10,481 10,523 10,568 9,009
Older Adults 1,021 1,251 1,401 1,454 1,382 1,516 1,525 1,443
Age 60-64 520 636 701 729 729 802 802 772
Age 65-69 239 291 349 378 350 360 382 373
Age 70-74 106 129 152 176 144 185 181 160
Age 75-79 80 100 108 87 90 86 68 67
Age 80-84 39 47 60 46 43 55 53 42
Age 85+ 37 48 31 38 26 28 39 29
Age Missing 4 5 5 3 3 6 6 15
Hispanic 731 1,097 1,625 2,007 2,194 2,477 2,726 2,272
Not Hispanic 8,543 11,454 14,216 16,092 16,543 17,061 17,280 14,507
Unknown Ethnicity 8,592 9,852 6,579 5,186 3,189 2,832 2,767 2,431
White 11,407 11,768 7,494 7,019 6,011 5,579 5,103 4,082
Hispanic 758 838 501 484 387 360 328 250
Black 302 323 197 162 147 134 134 107
Asian 210 227 172 166 136 115 99 73
Native Hawaiian/Pacific Islander 15 9 13 9 7 9 8 11
American Indian/Alaskan Native 698 703 425 385 310 310 261 228
Other Race 342 338 279 268 246 231 211 170
Two or More Races 0 0 0 0 0 1 0 0
Unknown Race 4,134 8,197 13,339 14,792 14,682 15,631 16,629 14,289
USA Born 16,287 20,357 20,600 21,556 20,440 20,918 21,263 17,872
Foreign Born 1,566 2,000 1,781 1,678 1,430 1,410 1,462 1,296
Unknown Place of Birth 13 46 39 51 56 42 48 42
Language Reported 1,291 1,720 1,529 1,535 1,320 956 841 616
Language Unknown 16,575 20,683 20,891 21,750 20,606 21,414 21,932 18,594
Total Population 17,866 22,403 22,420 23,285 21,926 22,370 22,773 19,210
104
Superior Region-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 2,526 3,048 3,513 3,126 2,926 2,941 3,010 2,550
Male 2,188 2,704 3,086 2,836 2,675 2,759 2,797 2,335
CYF 3,311 4,503 4,721 4,822 4,588 4,668 4,984 4,104
TAY 2,359 2,966 3,451 3,213 2,988 3,406 3,534 2,953
Adults 2,698 3,143 3,694 3,211 3,052 3,028 3,025 2,613
Older Adults 924 1,094 1,017 1,231 1,136 1,217 1,184 1,070
Age 60-64 1,348 1,587 1,854 1,590 1,403 1,369 1,403 1,293
Age 65-74 627 756 302 939 750 805 786 703
Age 75-84 291 353 171 327 353 394 299 268
Age 85+ 254 280 212 206 144 133 234 157
White 1,873 1,887 1,409 1,142 981 916 845 676
Hispanic 953 1,012 631 62 50 46 42 32
Black 4,900 3,860 2648 2,043 1,735 1,617 1,643 1,106
Asian 1,303 1,224 1019 800 657 586 504 321
Native Hawaiian/Pacific Islander 1,272 929 1209 854 146 368 463 865
American Indian/Alaskan Native 3,622 3,709 2166 2,087 1,768 1,627 1,355 1,312
Other Race 13,545 91,351 - 40,729 47,036 16,643 22,281 25,185
Two or More Races 0 0 0 0 0 4 0 0
Total Population 2,363 2,883 3310 2,994 2,810 2,855 2,907 2,448
105
Bay Area Region – New Clients Frequencies (Actual Counts of New Clients)
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 20,521 24,369 23,105 24,412 23,885 23,178 21,457 9,548
Male 21,428 26,107 24,953 25,606 24,935 24,212 22,890 9,990
Other Sex 6 8 12 11 10 8 11 4
Unknown Sex 64 114 92 72 80 124 133 35
CYF 11,803 13,319 12,389 12,108 12,265 12,601 11,964 5,321
TAY 8,122 10,577 10,179 10,839 10,581 10,298 9,015 4,043
Adults 20,120 24,065 23,107 24,299 23,387 22,098 20,840 9,185
Older Adults 1,973 2,632 2,486 2,855 2,677 2,525 2,670 1,025
Age 60-64 885 1,077 1,135 1,310 1,263 1,219 1,386 562
Age 65-69 396 521 495 593 557 533 585 213
Age 70-74 240 341 322 362 336 287 315 101
Age 75-79 213 262 225 247 207 204 174 77
Age 80-84 145 214 178 186 174 133 115 45
Age 85+ 94 217 131 157 140 149 95 27
Age Missing 1 5 1 0 0 0 2 3
Hispanic 4,995 8,220 10,216 11,104 11,638 12,370 11,686 5,884
Not Hispanic 8,785 14,269 18,641 18,293 18,340 17,895 17,382 6,189
Unknown Ethnicity 28,239 28,109 19,305 20,704 18,932 17,257 15,423 7,504
White 13,917 11,238 5,894 5,520 4,833 4,082 3,656 1,735
Hispanic 8,340 6,197 2,783 2,623 2,336 1,959 1,579 712
Black 8,848 7,797 4,630 4,639 4,062 3,251 2,970 981
Asian 2,189 1,616 688 718 583 440 442 132
Native Hawaiian/Pacific Islander 97 91 32 38 31 25 15 6
American Indian/Alaskan Native 299 245 134 104 101 72 74 39
Other Race 1,238 1,280 429 476 398 308 264 95
Two or More Races 17 20 3 5 1 5 2 0
Unknown Race 7,074 22,114 33,569 35,978 36,565 37,380 35,489 15,877
USA Born 28,955 34,580 32,989 33,468 33,166 32,789 30,995 12,755
Foreign Born 13,035 16,002 15,163 16,615 15,729 14,694 13,464 6,813
Unknown Place of Birth 29 16 10 18 15 39 32 9
Language Reported 6,867 8,437 8,024 7,578 4,406 2,285 2,074 680
Language Unknown 35,152 42,161 40,138 42,523 44,504 45,237 42,417 18,897
Total Population 42,019 50,598 48,162 50,101 48,910 47,522 44,491 19,577
106
Bay Area Region – New Clients Proportion of New Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 504 611 603 610 578 547 501 318
Male 532 640 638 629 601 585 549 332
CYF 717 896 878 899 848 905 853 538
TAY 824 1,026 1,013 1,056 1,040 997 776 470
Adults 471 573 622 607 561 560 477 295
Older Adults 185 249 194 272 257 244 245 124
Age 60-64 218 275 298 290 264 245 262 146
Age 65-74 113 169 162 194 173 155 157 69
Age 75-84 100 126 137 133 130 119 85 53
Age 85+ 80 136 115 108 96 105 65 25
Total Population 510 631 656 651 610 610 527 325
107
Bay Area Region-All Clients Frequencies (Actual Counts of All Clients)
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 50,857 58,583 56,419 57,538 57,567 56,362 48,636 30,237
Male 52,370 61,397 59,323 60,473 60,277 59,463 51,908 33,467
Other Sex 29 29 25 29 29 22 22 16
Unknown Sex 150 218 195 187 189 232 236 115
CYF 24,140 28,268 26,639 26,547 26,465 26,999 25,440 16,874
TAY 15,237 19,994 19,444 20,182 20,236 20,223 17,846 10,752
Adults 55,741 62,532 60,398 61,272 60,790 58,314 49,056 30,682
Older Adults 8,287 9,428 9,479 10,225 10,571 10,543 8,458 5,523
Age 60-64 4,184 4,304 4,563 4,981 5,284 5,337 4,458 2,978
Age 65-69 1,875 2,277 2,263 2,431 2,506 2,445 1,946 1,309
Age 70-74 972 1,178 1,164 1,240 1,311 1,315 1,044 650
Age 75-79 669 791 729 778 698 717 525 318
Age 80-84 384 512 462 477 456 412 292 176
Age 85+ 203 366 298 318 316 317 193 92
Age Missing 1 5 2 1 0 0 2 4
Hispanic 12,071 17,361 21,154 23,265 24,948 26,257 24,470 16,597
Not Hispanic 30,361 39,412 47,745 49,192 50,041 49,211 41,757 24,741
Unknown Ethnicity 60,974 63,454 47,063 45,770 43,073 40,611 34,575 22,497
White 33,375 32,395 23,722 21,389 19,377 17,399 13,808 9,257
Hispanic 15,828 15,333 9,662 8,517 7,716 6,830 5,394 3,692
Black 20,253 20,661 15,647 14,469 13,461 11,980 9,470 5,700
Asian 6,706 6,291 4,714 4,326 3,986 3,658 2,528 1,638
Native Hawaiian/Pacific Islander 206 212 133 115 107 88 57 33
American Indian/Alaskan Native 671 661 495 428 375 303 239 155
Other Race 3,894 3,149 2,124 1,969 1,831 1,640 1,163 709
Two or More Races 24 32 14 13 7 7 6 2
Unknown Race 22,449 41,493 59,451 67,001 71,202 74,174 68,137 42,649
USA Born 71,643 84,631 82,360 83,184 83,516 82,721 74,026 46,948
Foreign Born 31,713 35,562 33,577 35,013 34,519 33,301 26,712 16,849
Unknown Place of Birth 50 34 25 30 27 57 64 38
Language Reported 17,250 20,653 20,097 19,979 16,567 12,710 8,657 5,137
Language Unknown 86,156 99,574 95,865 98,248 101,495 103,369 92,145 58,698
Total Population 103,406 120,227 115,962 118,227 118,062 116,079 100,802 63,835
108
Bay Area Region-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,375 1,542 1,487 1,514 1,476 1,445 1,216 756
Male 1,415 1,616 1,552 1,551 1,546 1,525 1,331 837
CYF 1,601 1,903 1,694 1,821 1,780 1,847 1,733 1,144
TAY 1,713 2,025 1,861 1,981 2,055 1,973 1,750 1,046
Adults 1,468 1,609 1,579 1,566 1,534 1,474 1,228 759
Older Adults 1,004 1,069 777 1,102 1,132 1,100 855 534
Age 60-64 1,280 1,255 1,317 1,273 1,273 1,194 974 652
Age 65-74 661 771 262 759 794 735 562 345
Age 75-84 364 418 152 408 368 372 266 156
Age 85+ 191 301 236 233 226 221 128 61
White 982 926 685 611 554 527 418 281
Hispanic 931 852 524 111 99 88 68 46
Black 4,410 4,258 3,206 3,031 2,837 2,517 1,989 1,230
Asian 447 419 300 270 249 215 149 91
Native Hawaiian/Pacific Islander 550 511 317 285 263 191 126 71
American Indian/Alaskan Native 2,789 2,900 2,045 2,170 1,564 1,285 1,076 733
Other Race 11,936 9,491 - 6,063 8,285 8,360 5,150 3,099
Two or More Races 13 17 6 6 3 3 2 7,143
Total Population 1,397 1,582 1,513 1,535 1,514 1,488 1,276 798
109
Central Region – New Clients Frequencies (Actual Counts of New Clients)
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 18,015 22,429 23,046 23,381 18,738 17,816 14,234 6,452
Male 17,566 23,196 23,794 24,109 18,360 17,710 13,994 6,074
Other Sex 1 2 1 2 3 2 1 2
Unknown Sex 62 45 51 50 85 108 43 17
CYF 11,601 13,841 14,076 14,551 12,585 13,037 9,238 3,811
TAY 7,473 10,421 10,589 10,917 8,425 8,138 6,276 2,726
Adults 15,488 19,826 20,623 20,387 14,931 13,379 11,816 5,523
Older Adults 1,080 1,580 1,597 1,678 1,235 1,070 923 473
Age 60-64 472 656 752 746 550 540 474 259
Age 65-69 205 342 303 352 273 234 194 92
Age 70-74 139 197 210 219 175 126 104 48
Age 75-79 108 150 140 147 95 83 63 37
Age 80-84 88 116 94 118 74 46 53 19
Age 85+ 68 119 98 96 68 41 35 18
Age Missing 2 4 7 9 10 12 19 12
Hispanic 4,169 7,707 13,144 14,060 12,000 11,924 10,825 4,877
Not Hispanic 10,235 17,184 25,711 27,455 20,252 19,729 14,812 6,550
Unknown Ethnicity 21,240 20,781 8,037 6,027 4,934 3,983 2,635 1,118
White 14,843 11,902 7,086 6,431 4,479 3,999 2,782 1,090
Hispanic 8,591 6,767 3,753 3,322 2,465 2,094 1,622 628
Black 4,867 4,018 2,717 2,451 1,626 1,441 731 226
Asian 886 715 363 275 226 200 131 51
Native Hawaiian/Pacific Islander 35 32 14 13 10 9 9 1
American Indian/Alaskan Native 403 289 214 166 131 106 82 37
Other Race 719 636 332 290 206 177 86 37
Two or More Races 3 6 3 0 0 0 0 0
Unknown Race 5,297 21,307 32,410 34,594 28,043 27,610 22,829 10,475
USA Born 30,279 38,536 39,810 40,916 32,329 30,851 23,919 10,730
Foreign Born 5,351 7,111 7,056 6,574 4,802 4,738 4,321 1,805
Unknown Place of Birth 14 25 26 52 55 47 32 10
Language Reported 3,969 5,532 5,797 4,749 2,738 1,605 1,150 408
Language Unknown 31,675 40,140 41,095 42,793 34,448 34,031 27,122 12,137
Total Population 35,644 45,672 46,892 47,542 37,186 35,636 28,272 12,545
110
Central Region – New Clients Proportion of New Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 629 759 803 809 693 653 610 379
Male 561 694 746 759 616 609 577 337
CYF 920 1,019 1,031 1,293 980 1,026 814 441
TAY 865 1,169 1,299 1,220 1,082 1,107 851 517
Adults 672 777 786 801 685 644 560 358
Older Adults 153 273 195 259 221 258 202 125
Age 60-64 186 282 279 289 206 345 204 153
Age 65-74 99 262 193 164 150 186 123 64
Age 75-84 75 111 120 260 226 79 97 57
Age 85+ 104 124 109 103 91 77 77 48
Total Population 653 789 796 851 699 698 592 357
111
Central Region-All Clients Frequencies (Actual Counts of All Clients)
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 44,656 53,624 53,807 53,454 48,336 41,737 35,894 23,462
Male 41,836 51,687 52,799 53,014 46,849 41,687 35,549 22,719
Other Sex 3 4 4 3 4 3 4 5
Unknown Sex 75 73 67 68 103 155 77 31
CYF 24,497 29,491 29,498 29,991 28,158 27,000 22,186 12,770
TAY 13,869 18,975 19,532 19,944 17,360 15,710 13,044 7,722
Adults 43,744 51,374 51,987 50,792 44,289 36,152 31,927 22,330
Older Adults 4,446 5,532 5,632 5,780 5,452 4,684 4,325 3,367
Age 60-64 2,160 2,629 2,837 2,954 2,822 2,522 2,346 1,863
Age 65-69 1,028 1,302 1,310 1,341 1,278 1,101 1,008 802
Age 70-74 522 671 681 706 677 543 507 365
Age 75-79 367 440 398 393 349 274 238 181
Age 80-84 215 277 224 226 190 150 146 98
Age 85+ 154 213 182 160 136 94 80 58
Age Missing 14 16 28 32 33 36 42 28
Hispanic 11,218 16,763 25,282 28,111 26,489 25,313 23,898 16,091
Not Hispanic 33,361 44,827 59,367 63,076 55,633 47,568 39,546 24,745
Unknown Ethnicity 41,991 43,798 22,028 15,352 13,170 10,701 8,080 5,381
White 35,936 34,765 24,865 22,137 18,657 14,506 11,239 6,972
Hispanic 16,662 16,013 9,982 9,005 7,650 6,250 5,093 3,271
Black 10,621 10,485 7,926 7,172 5,774 4,359 2,900 1,390
Asian 3,181 3,093 2,321 2,004 1,823 1,442 1,200 866
Native Hawaiian/Pacific Islander 85 84 64 47 47 32 25 10
American Indian/Alaskan Native 1,070 996 762 679 613 509 404 283
Other Race 2,303 2,379 1,864 1,671 1,479 1,054 801 522
Two or More Races 4 7 6 0 0 0 0 0
Unknown Race 16,708 37,566 58,887 63,824 59,249 55,430 49,862 32,903
USA Born 71,521 87,453 88,978 90,020 80,998 71,088 60,155 38,419
Foreign Born 14,988 17,861 17,610 16,398 14,157 12,366 11,267 7,731
Unknown Place of Birth 61 74 89 121 137 128 102 67
Language Reported 11,020 13,753 14,256 13,116 10,498 7,272 5,815 4,009
Language Unknown 75,550 91,635 92,421 93,423 84,794 76,310 65,709 42,208
Total Population 86,570 105,388 106,677 106,539 95,292 83,582 71,524 46,217
112
Central Region-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,718 2,062 1,991 1,980 1,790 1,304 1,282 838
Male 1,673 1,988 1,960 1,963 1,735 1,345 1,317 811
CYF 1,995 2,446 2,148 2,470 2,245 1,892 1,770 1,018
TAY 1,793 2,262 2,358 2,416 2,126 1,611 1,516 903
Adults 1,861 2,072 2,156 2,027 1,787 1,252 1,268 886
Older Adults 872 1,019 716 1,013 949 677 705 522
Age 60-64 1,096 1,336 1,293 1,338 1,166 824 862 666
Age 65-74 570 706 231 692 633 441 455 324
Age 75-84 318 376 114 323 293 191 198 143
Age 85+ 281 292 242 193 167 98 93 64
White 1,437 1,391 956 885 746 518 468 291
Hispanic 980 890 545 170 142 99 93 58
Black 3,976 3,750 2,780 2,455 2,017 1,443 1,020 483
Asian 686 635 479 419 373 250 227 158
Native Hawaiian/Pacific Islander 517 444 290 248 219 127 94 39
American Indian/Alaskan Native 2,833 2,818 2,073 2,042 1,845 1,488 1,188 1,049
Other Race 17,137 16,597 - 11,260 9,538 15,436 5,887 4,857
Two or More Races 4 6 4 0 0 0 0 0
Total Population 1,697 2,027 1,976 1,973 1,765 1,327 1,300 825
113
Southern Region – New Clients Frequencies (Actual Counts of New Clients)
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 35,295 43,523 45,642 49,540 45,824 49,853 47,439 28,346
Male 36,949 45,961 49,187 59,291 54,397 58,849 56,981 34,838
Other Sex 4 7 3 6 12 14 10 5
Unknown Sex 310 977 885 765 252 225 218 148
CYF 22,193 24,966 26,436 28,091 27,158 29,309 29,126 18,096
TAY 14,721 19,407 20,571 26,158 24,697 25,718 23,441 14,132
Adults 32,530 41,662 43,845 49,981 44,155 48,603 46,702 27,502
Older Adults 3,077 4,391 4,812 5,301 4,381 5,105 4,538 2,871
Age 60-64 1,246 1,651 1,925 2,167 2,059 2,776 2,268 1,427
Age 65-69 496 729 864 912 833 872 840 580
Age 70-74 360 498 584 628 478 490 484 313
Age 75-79 354 534 491 551 396 367 357 194
Age 80-84 296 447 480 483 306 304 281 184
Age 85+ 325 532 468 560 309 296 308 173
Age Missing 37 42 53 71 94 206 841 736
Hispanic 12,847 24,184 31,743 38,029 36,930 38,874 40,154 25,553
Not Hispanic 16,208 30,151 43,177 51,044 48,990 52,702 54,083 31,687
Unknown Ethnicity 43,503 36,133 20,797 20,529 14,565 17,365 10,411 6,097
White 28,886 21,463 12,015 12,256 9,813 9,100 8,469 4,381
Hispanic 18,791 12,244 5,790 6,257 5,180 4,731 4,013 2,217
Black 6,775 5,228 3,144 3,504 2,847 2,574 2,483 1,320
Asian 1,575 1,123 513 605 454 359 356 169
Native Hawaiian/Pacific Islander 172 86 50 48 38 31 35 19
American Indian/Alaskan Native 508 375 201 211 163 179 159 77
Other Race 1,266 1,112 441 474 432 335 349 214
Two or More Races 56 29 16 14 12 6 10 5
Unknown Race 14,529 48,808 73,547 86,233 81,546 91,626 88,774 54,935
USA Born 55,091 66,531 71,583 82,612 78,477 82,169 83,597 51,776
Foreign Born 17,086 23,391 23,707 26,675 21,748 26,621 20,852 11,476
Unknown Place of Birth 381 546 427 315 260 151 199 85
Language Reported 10,140 13,476 15,126 15,870 8,731 4,574 3,863 2,112
Language Unknown 62,418 76,992 80,591 93,732 91,754 104,367 100,785 61,225
Total Population 72,558 90,468 95,717 109,602 100,485 108,941 104,648 63,337
114
Southern Region – New Clients Proportion of New Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 618 721 737 780 736 753 762 578
Male 665 733 761 899 824 853 851 651
CYF 933 1,001 959 1,144 1,073 1,118 1,212 915
TAY 830 947 1,026 1,199 1,180 1,164 1,097 836
Adults 580 687 717 775 709 734 716 546
Older Adults 242 315 230 345 296 320 316 253
Age 60-64 278 361 341 397 331 368 351 283
Age 65-74 135 189 196 209 180 187 184 158
Age 75-84 142 194 176 181 144 143 150 107
Age 85+ 225 236 181 211 130 131 134 116
Total Population 643 731 747 843 784 807 810 618
115
Southern Region-All Clients Frequencies (Actual Counts of All Clients)
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 77,525 93,902 96,358 102,883 101,153 102,642 99,427 71,087
Male 79,290 95,975 99,724 112,741 111,826 115,232 113,943 82,429
Other Sex 7 12 9 12 20 21 24 13
Unknown Sex 964 1,757 1,917 1,643 614 545 362 249
CYF 42,705 50,177 50,715 53,051 53,860 55,295 55,183 41,439
TAY 26,268 34,436 36,420 43,051 44,375 45,778 43,294 30,046
Adults 79,871 95,629 98,648 107,643 102,346 103,475 101,290 71,475
Older Adults 8,869 11,328 12,138 13,434 12,907 13,651 13,044 9,876
Age 60-64 4,907 5,879 6,520 7,200 7,289 8,003 7,626 5,935
Age 65-69 1,606 2,072 2,235 2,509 2,585 2,695 2,592 1,942
Age 70-74 839 1,094 1,216 1,353 1,224 1,211 1,209 881
Age 75-79 645 910 858 953 800 755 715 500
Age 80-84 452 659 689 709 534 556 468 351
Age 85+ 420 714 620 710 475 431 434 267
Age Missing 73 76 87 100 125 241 945 942
Hispanic 29,767 46,818 59,907 69,822 72,455 74,878 76,572 57,898
Not Hispanic 49,109 68,773 89,222 102,463 104,349 107,927 108,782 77,629
Unknown Ethnicity 78,910 76,055 48,879 44,994 36,809 35,635 28,402 18,251
White 62,479 58,593 40,821 38,816 34,619 31,036 28,433 18,882
Hispanic 33,768 30,260 18,325 17,789 16,063 14,431 12,742 8,431
Black 14,079 13,353 9,436 9,351 8,529 7,744 7,247 4,664
Asian 3,982 3,671 2,537 2,529 2,321 2,087 1,816 1,349
Native Hawaiian/Pacific Islander 285 219 134 119 101 90 95 68
American Indian/Alaskan Native 1,100 1,057 742 678 601 535 496 323
Other Race 2,803 2,923 1,949 1,825 1,692 1,518 1,407 1,051
Two or More Races 75 75 53 39 34 27 25 24
Unknown Race 39,215 81,495 124,011 146,133 149,653 160,972 161,495 118,986
USA Born 120,061 143,705 149,943 165,895 166,957 169,026 168,144 123,197
Foreign Born 36,189 46,149 46,502 50,280 45,801 48,895 45,100 30,198
Unknown Place of Birth 1,536 1,792 1,563 1,104 855 519 512 383
Language Reported 22,282 28,409 30,640 32,682 25,754 18,593 14,478 9,753
Language Unknown 135,504 163,237 167,368 184,597 187,859 199,847 199,278 144,025
Total Population 157,786 191,646 198,008 217,279 213,613 218,440 213,756 153,778
116
Southern Region-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,292 1,515 1,553 1,659 1,606 1,711 1,530 1,077
Male 1,344 1,548 1,592 1,790 1,747 1,921 1,753 1,249
CYF 1,528 1,824 1,683 1,932 1,931 2,150 2,010 1,510
TAY 1,524 1,784 1,882 2,192 2,285 2,384 2,103 1,451
Adults 1,407 1,613 1,713 1,804 1,710 1,820 1,651 1,157
Older Adults 723 872 668 986 929 1,020 881 638
Age 60-64 1,092 1,287 1,300 1,387 1,281 1,406 1,190 912
Age 65-74 384 483 179 556 520 544 475 330
Age 75-84 241 330 148 347 289 304 249 180
Age 85+ 311 425 363 376 244 229 212 121
White 1,116 1,028 710 681 618 609 517 343
Hispanic 767 658 387 137 124 120 98 65
Black 2,750 2,409 1,656 1,705 1,513 1,397 1,267 803
Asian 362 334 227 230 211 174 140 104
Native Hawaiian/Pacific Islander 850 626 369 318 274 265 262 166
American Indian/Alaskan Native 1,982 1,969 1,327 1,308 1,269 1,147 956 652
Other Race 4,762 4,759 - 6,042 4,784 6,784 7,843 5,494
Two or More Races 37 32 20 15 13 9 8 8
Total Population 1,326 1,546 1,581 1,738 1,682 1,820 1,644 1,165
117
Los Angeles Region-New Clients Frequencies (Actual Counts of New Clients)
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 31,175 33,544 39,148 37,110 36,623 34,216 44,092 5,329
Male 44,127 51,172 57,816 52,008 48,826 38,151 60,064 7,538
Other Sex 0 0 0 0 0 0 0 0
Unknown Sex 12 30 23 29 28 23 47 9
CYF 21,897 23,685 27,327 28,127 29,496 29,008 35,698 2,431
TAY 15,700 18,485 20,795 19,693 18,273 15,525 20,382 2,776
Adults 35,239 39,330 44,903 37,671 34,179 25,153 43,777 7,072
Older Adults 2,478 3,246 3,962 3,656 3,529 2,704 4,346 597
Age 60-64 1,086 1,379 1,825 1,533 1,574 1,259 2,253 337
Age 65-69 484 657 822 734 687 520 891 125
Age 70-74 296 378 457 445 429 296 494 61
Age 75-79 236 311 333 342 322 246 308 24
Age 80-84 206 258 289 316 250 184 209 27
Age 85+ 170 263 236 286 267 199 191 23
Age Missing 0 0 0 0 0 0 0 0
Hispanic 0 10,583 25,112 27,329 28,677 27,940 33,913 1,876
Not Hispanic 0 9,549 20,212 22,012 21,524 18,966 23,067 1,651
Unknown Ethnicity 75,314 64,614 51,663 39,806 35,276 25,484 47,223 9,349
White 14,213 15,921 16,041 14,240 13,947 11,750 8,782 842
Hispanic 27,947 31,683 36,807 35,793 36,708 34,980 20,432 1,851
Black 18,847 20,820 20,246 19,265 18,107 14,923 13,436 1,411
Asian 1,578 1,653 2,495 2,057 2,056 1,758 955 80
Native Hawaiian/Pacific Islander 79 66 92 86 74 72 48 6
American Indian/Alaskan Native 359 430 417 328 342 265 171 20
Other Race 1,147 1,437 2,077 2,053 2,055 1,518 1,009 95
Two or More Races 0 0 0 0 0 0 0 0
Unknown Race 11,144 12,736 18,812 15,325 12,188 7,124 59,370 8,571
USA Born 44,127 48,134 57,024 57,135 57,047 52,077 65,344 4,950
Foreign Born 31,175 36,606 39,955 32,004 28,429 20,312 38,857 7,926
Unknown Place of Birth 12 6 8 8 1 1 2 0
Language Reported 31,797 36,224 41,347 35,151 31,795 22,775 22,728 4,782
Language Unknown 43,517 48,522 55,640 53,996 53,682 49,615 81,475 8,094
Total Population 75,314 84,746 96,987 89,147 85,477 72,390 104,203 12,876
118
Los Angeles Region-New Clients Proportion of New Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 636 671 785 742 732 684 882 107
Male 919 1,044 1,182 1,061 996 795 1,226 154
CYF 959 1,065 1,217 1,343 1,424 1,481 1,837 126
TAY 1,146 1,249 1,401 1,316 1,291 1,030 1,357 185
Adults 737 811 964 786 698 521 899 145
Older Adults 260 320 286 346 338 252 395 52
Age 60-64 295 361 476 363 371 272 475 69
Age 65-74 154 198 246 213 205 143 235 30
Age 75-84 128 160 178 186 165 125 149 14
Age 85+ 169 195 176 191 175 129 117 14
Total Population 776 856 992 900 863 739 1,053 130
119
Los Angeles Region-All Clients Frequencies (Actual Counts of All Clients)
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 73,707 82,762 84,363 87,062 88,407 86,606 95,793 51,880
Male 92,016 106,993 110,406 108,376 104,773 93,783 113,944 57,878
Other Sex 0 0 0 0 0 0 0 0
Unknown Sex 14 36 33 42 44 40 64 33
CYF 45,469 51,606 53,601 57,078 60,771 61,365 66,903 31,918
TAY 28,788 35,250 36,663 37,166 36,660 34,218 38,711 18,982
Adults 83,772 93,486 94,523 90,319 84,461 74,207 91,930 51,017
Older Adults 7,708 9,449 10,015 10,917 11,332 10,639 12,257 7,874
Age 60-64 4,187 4,979 5,387 5,697 6,020 5,898 7,009 4,770
Age 65-69 1,723 2,128 2,276 2,545 2,543 2,403 2,743 1,750
Age 70-74 788 1,002 1,030 1,140 1,225 1,018 1,187 730
Age 75-79 466 599 582 656 686 629 656 330
Age 80-84 314 400 425 480 442 365 378 178
Age 85+ 230 341 315 399 416 326 284 116
Age Missing 0 0 0 0 0 0 0 0
Hispanic 0 10,585 31,738 42,425 49,165 51,827 58,543 22,722
Not Hispanic 0 9,551 25,407 33,014 36,030 35,232 39,390 13,333
Unknown Ethnicity 165,737 169,655 137,657 120,041 108,029 93,370 111,868 73,736
White 31,755 35,514 33,451 32,488 31,746 28,863 24,950 11,275
Hispanic 54,379 65,209 68,223 72,377 76,498 76,404 61,435 27,392
Black 40,229 44,803 42,945 41,799 40,073 36,578 34,118 14,491
Asian 4,913 5,424 5,653 5,826 6,061 5,775 4,808 2,764
Native Hawaiian/Pacific Islander 145 158 172 183 175 168 132 57
American Indian/Alaskan Native 746 919 864 819 831 741 582 280
Other Race 2,959 3,546 4,027 4,303 4,480 3,861 3,215 1,556
Two or More Races 0 0 0 0 0 0 0 0
Unknown Race 30,611 34,218 39,467 37,685 33,360 28,039 80,561 51,976
USA Born 107,633 121,695 125,522 130,976 133,407 127,727 136,347 59,883
Foreign Born 58,088 68,081 69,270 64,493 59,816 52,701 73,452 49,908
Unknown Place of Birth 16 15 10 11 1 1 2 0
Language Reported 67,644 78,135 81,329 78,497 74,637 66,003 65,206 42,804
Language Unknown 98,093 111,656 113,473 116,983 118,587 114,426 144,595 66,987
Total Population 165,737 189,791 194,802 195,480 193,224 180,429 209,801 109,791
120
Los Angeles Region-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,504 1,655 1,692 1,741 1,768 1,732 1,916 1,038
Male 1,917 2,184 2,256 2,212 2,138 1,954 2,325 1,181
CYF 1,991 2,320 2,387 2,726 2,935 3,132 3,444 1,650
TAY 2,101 2,383 2,471 2,484 2,591 2,270 2,577 1,262
Adults 1,751 1,928 2,029 1,884 1,726 1,537 1,888 1,042
Older Adults 809 932 723 1,035 1,087 993 1,114 688
Age 60-64 1,136 1,304 1,407 1,347 1,418 1,272 1,478 980
Age 65-74 495 598 198 667 692 598 666 398
Age 75-84 226 282 122 322 326 288 298 141
Age 85+ 228 253 236 267 273 211 174 72
White 1,134 1,225 1,177 1,160 1,134 1,069 924 418
Hispanic 1,182 1,387 1,485 731 781 780 621 274
Black 4,768 5,179 5,013 5,002 4,903 4,532 4,266 1,813
Asian 378 417 445 448 466 444 370 197
Native Hawaiian/Pacific Islander 559 664 729 757 713 767 540 254
American Indian/Alaskan Native 3,396 3,603 4,161 3,880 4,238 4,829 3,619 1,626
Other Race 7,527 8,773 - 15,451 15,050 18,455 17,430 5,244
Two or More Races 0 0 0 0 0 0 0 0
Total Population 1,709 1,917 1,993 1,975 1,952 1,841 2,119 1,109
121
Appendix D. CSI Data Tables –
County New Clients (in Alphabetical Order)
Alameda County Proportions per 100,000
Bay Area Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 774 907 926 956 1,067 1,040 938 129
Male 840 1,029 1,045 1,090 1,146 1,149 1,094 172
CYF 1,018 1,269 1,213 1,301 1,491 1,601 1,518 215
TAY 1,221 1,373 1,377 1,621 1,904 1,727 1,691 251
Adults 795 967 979 982 1,021 1,015 913 139
Older Adults 277 337 273 448 440 405 366 54
Age 60-64 344 411 526 548 529 471 432 71
Age 65-74 173 221 221 262 300 224 212 24
Age 75-84 93 104 133 146 120 132 121 22
Age 85+ 78 117 73 115 75 72 54 8
Total Population 809 972 981 1,025 1,109 1,098 1,018 151
Alpine County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 4,315 2,232 3,466 6,515 2,181 855 NA NA
TAY 2,015 3,345 3,819 1,761 893 990 NA NA
Adults 2,316 2,702 1,513 2,067 1,752 1,064 NA NA
Older Adults - 929 444 425 373 1,449 NA NA
Age 60-64 - - - - - 2,727 NA NA
Age 65-74 - 2,036 1,049 - - 917 NA NA
Age 75-84 - - - 2,369 2,079 - NA NA
Age 85+ - - - - - - NA NA
Total Population 2,235 2,390 1,923 2,566 1,441 1,106 NA NA
122
Amador County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 197 475 578 287 397 542 NA NA
TAY 268 574 797 730 817 1,056 NA NA
Adults 214 345 334 511 291 511 NA NA
Older Adults 21 21 51 39 18 89 NA NA
Age 60-64 41 77 - 67 31 236 NA NA
Age 65-74 28 - 80 51 23 45 NA NA
Age 75-84 - - 81 - - - NA NA
Age 85+ - - - - - - NA NA
Total Population 170 308 347 370 282 446 NA NA
Butte County Proportions per 100,000
Superior Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 500 643 635 738 570 1,124 1,316 961
Male 461 604 652 726 558 1,092 1,207 958
CYF 887 1,184 1,153 1,147 1,151 2,272 2,320 1,674
TAY 461 666 694 790 548 1,292 1,382 1,149
Adults 492 618 633 812 562 1,025 1,317 974
Older Adults 99 115 162 206 150 359 387 385
Age 60-64 210 183 287 217 138 363 369 424
Age 65-74 57 75 151 187 130 237 257 287
Age 75-84 26 51 111 87 64 170 180 110
Age 85+ 20 71 56 83 73 101 244 101
Total Population 481 624 649 733 567 1,111 1,264 963
123
Calaveras County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 328 247 389 360 534 626 NA NA
TAY 307 155 295 772 669 603 NA NA
Adults 190 155 273 268 327 341 NA NA
Older Adults 17 17 56 54 36 65 NA NA
Age 60-64 30 29 110 130 98 118 NA NA
Age 65-74 20 - 58 18 17 52 NA NA
Age 75-84 - - - - - - NA NA
Age 85+ - 115 - 112 - 103 NA NA
Total Population 181 135 237 271 309 331 NA NA
Colusa County Proportions per 100,000
Superior Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 236 872 731 762 648 724 NA NA
TAY 289 906 1,040 727 809 575 NA NA
Adults 282 643 546 468 362 379 NA NA
Older Adults 97 95 62 90 144 112 NA NA
Age 60-64 352 113 109 103 297 - NA NA
Age 65-74 - 172 84 81 74 219 NA NA
Age 75-84 - - - - 127 - NA NA
Age 85+ - - - 307 - 287 NA NA
Total Population 243 661 592 524 465 453 NA NA
124
Contra Costa County Proportions per 100,000
Bay Area Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 620 750 723 849 808 832 835 663
Male 614 744 762 818 787 827 796 683
CYF 812 998 870 951 1,025 1,035 1,059 816
TAY 1,030 1,331 1,429 1,396 1,459 1,563 1,411 1,203
Adults 571 661 688 828 739 783 794 673
Older Adults 228 303 202 387 314 315 306 248
Age 60-64 246 273 328 439 355 315 362 317
Age 65-74 128 213 74 268 183 216 195 138
Age 75-84 116 150 49 132 121 121 75 90
Age 85+ 100 180 70 48 65 69 51 26
Total Population 617 747 741 834 798 829 816 673
Del Norte County Proportions per 100,000
Superior Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 2,542 2,293 2,691 2,319 2,484 1,660 NA NA
TAY 3,522 3,643 3,026 3,349 2,300 1,895 NA NA
Adults 2,171 1,975 1,982 2,132 1,559 1,248 NA NA
Older Adults 494 548 576 617 457 356 NA NA
Age 60-64 1,139 1,337 910 1,185 974 344 NA NA
Age 65-74 428 211 627 511 331 464 NA NA
Age 75-84 80 318 314 308 78 158 NA NA
Age 85+ - 236 - - 231 438 NA NA
Total Population 2,137 2,009 2,012 2,051 1,618 1,237 NA NA
125
El Dorado County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 618 843 886 888 643 695 725 224
Male 590 726 758 877 665 626 754 225
CYF 786 866 847 1,557 1,107 1,117 1,343 334
TAY 857 1,139 1,519 1,252 1,120 1,303 1,116 410
Adults 611 823 871 790 570 534 689 230
Older Adults 269 370 232 371 232 311 283 63
Age 60-64 250 375 358 276 224 347 211 72
Age 65-74 185 267 216 231 120 147 153 39
Age 75-84 102 92 145 183 58 166 205 23
Age 85+ 105 199 73 167 133 29 178 0
Total Population 604 786 816 883 657 661 739 225
Fresno County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,013 1,135 1,070 969 732 618 579 116
Male 1,035 1,335 1,199 1,109 837 707 604 108
CYF 1,169 1,425 1,205 1,282 982 950 682 129
TAY 1,400 1,786 1,674 1,501 1,137 888 792 162
Adults 1,039 1,216 1,178 1,014 752 608 637 116
Older Adults 326 410 209 218 188 144 139 30
Age 60-64 377 403 385 267 260 173 171 44
Age 65-74 182 299 186 153 139 95 71 15
Age 75-84 182 206 103 84 49 43 57 10
Age 85+ 244 192 82 37 7 7 38 0
Total Population 1,029 1,240 1,138 1,043 788 665 593 112
126
Glenn County Proportions per 100,000
Superior Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 702 584 478 848 629 987 NA NA
TAY 563 563 374 919 1,033 939 NA NA
Adults 428 334 315 537 577 643 NA NA
Older Adults 42 104 184 180 58 232 NA NA
Age 60-64 - 238 78 151 144 209 NA NA
Age 65-74 55 109 265 154 - 342 NA NA
Age 75-84 - - 161 322 82 169 NA NA
Age 85+ 220 - 206 - - - NA NA
Total Population 450 389 343 605 556 693 NA NA
Humboldt County Proportions per 100,000
Superior Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 417 572 550 683 798 737 395 259
Male 497 588 556 628 838 703 382 253
CYF 366 574 530 968 1,220 1,007 449 216
TAY 692 724 723 824 974 998 493 357
Adults 539 688 625 659 843 747 473 332
Older Adults 128 205 125 282 364 270 89 57
Age 60-64 121 292 267 360 390 296 77 69
Age 65-74 114 86 84 158 185 136 70 45
Age 75-84 37 81 70 115 209 163 37 -
Age 85+ 128 109 - 69 87 - - -
Total Population 456 580 537 656 818 720 389 256
127
Imperial County Proportions per 100,000
Southern Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 867 892 860 960 1,017 987 1,112 1,121
Male 1,188 980 969 1,053 1,125 1,126 1,210 1,120
CYF 1,848 1,689 1,351 1,817 1,822 1,846 1,998 1,851
TAY 1,054 973 1,265 1,097 1,496 1,396 1,534 1,469
Adults 771 715 656 758 743 762 866 871
Older Adults 271 361 292 381 385 461 523 540
Age 60-64 437 611 374 427 448 433 578 653
Age 65-74 168 271 322 292 268 316 326 368
Age 75-84 101 122 229 198 202 333 327 221
Age 85+ 63 60 64 139 61 152 77 373
Total Population 1,025 939 890 1,009 1,077 1,065 1,173 1,133
Inyo County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 1,146 1,259 1,052 1,333 1,270 848 NA NA
TAY 1,197 1,254 1,279 1,502 1,217 678 NA NA
Adults 693 804 899 615 880 396 NA NA
Older Adults 222 310 285 389 455 144 NA NA
Age 60-64 275 627 437 830 156 149 NA NA
Age 65-74 178 237 59 235 444 165 NA NA
Age 75-84 156 161 486 321 730 84 NA NA
Age 85+ 442 211 209 - 586 192 NA NA
Total Population 720 820 819 789 878 442 NA NA
128
Kern County Proportions per 100,000
Southern Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 653 800 762 883 987 977 1,131 879
Male 660 769 812 946 1,094 1,258 1,335 1,065
CYF 1,113 1,060 1,017 1,225 1,393 1,467 1,873 1,297
TAY 681 996 956 1,300 1,600 1,660 1,642 1,379
Adults 474 698 729 806 862 991 994 874
Older Adults 422 355 122 288 367 341 415 331
Age 60-64 211 260 212 356 356 324 391 335
Age 65-74 235 190 118 156 224 175 247 179
Age 75-84 409 310 43 117 225 205 247 152
Age 85+ 669 438 38 188 170 171 197 128
Total Population 657 784 773 916 1,043 1,123 1,236 975
Kings County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,212 1,404 1,346 1,444 1,247 1,091 1,120 922
Male 941 807 848 902 741 773 748 673
CYF 982 1,432 1,127 1,410 1,102 920 980 735
TAY 1,720 1,406 1,623 1,622 1,382 1,466 1,446 1,359
Adults 1,129 915 958 1,012 876 849 841 757
Older Adults 378 532 321 444 437 497 481 349
Age 60-64 370 549 433 251 214 460 359 372
Age 65-74 257 392 350 375 385 316 387 191
Age 75-84 145 218 244 399 349 215 197 240
Age 85+ 312 215 - 75 79 307 172 142
Total Population 1,076 1,064 1,047 1,132 953 914 909 784
129
Lake County Proportions per 100,000
Superior Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 561 770 1,040 983 668 520 687 349
Male 521 671 842 837 594 642 657 263
CYF 755 1,280 1,311 1,343 1,038 827 981 404
TAY 760 848 1,656 1,493 1,085 677 1,108 573
Adults 597 720 1,001 946 581 669 711 327
Older Adults 128 244 233 348 322 328 334 145
Age 60-64 200 304 351 312 377 236 381 113
Age 65-74 20 194 218 207 177 275 195 88
Age 75-84 116 80 130 194 186 144 85 59
Age 85+ 60 - 222 154 58 51 132 205
Total Population 541 722 953 911 631 581 672 306
Lassen County Proportions per 100,000
Superior Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 502 877 1,227 820 1,117 967 NA NA
TAY 498 1,014 877 852 783 1,525 NA NA
Adults 317 561 529 410 600 819 NA NA
Older Adults 139 179 213 103 135 151 NA NA
Age 60-64 161 304 209 192 170 218 NA NA
Age 65-74 120 118 227 112 205 151 NA NA
Age 75-84 188 92 266 - - - NA NA
Age 85+ - 276 - - - 223 NA NA
Total Population 356 640 660 504 638 845 NA NA
130
Los Angeles County Proportions per 100,000
Los Angeles Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 636 671 785 742 732 684 882 107
Male 919 1,044 1,182 1,061 996 795 1,226 154
CYF 959 1,065 1,217 1,343 1,424 1,481 1,837 126
TAY 1,146 1,249 1,401 1,316 1,291 1,030 1,357 185
Adults 737 811 964 786 698 521 899 145
Older Adults 260 320 286 346 338 252 395 52
Age 60-64 295 361 476 363 371 272 475 69
Age 65-74 154 198 246 213 205 143 235 30
Age 75-84 128 160 178 186 165 125 149 14
Age 85+ 169 195 176 191 175 129 117 14
Total Population 776 856 992 900 863 739 1,053 130
Madera County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,039 1,064 1,127 1,046 822 788 831 679
Male 740 941 974 952 711 741 775 516
CYF 1,104 1,340 1,171 1,320 1,030 1,074 943 667
TAY 1,127 1,307 1,699 1,527 1,243 1,118 1,175 805
Adults 957 940 1,016 896 684 703 806 657
Older Adults 171 387 290 358 328 216 355 247
Age 60-64 103 329 290 237 222 173 212 213
Age 65-74 125 283 329 313 210 136 229 141
Age 75-84 129 349 224 153 215 143 276 142
Age 85+ 83 163 298 415 108 274 372 209
Total Population 886 1,006 1,050 1,001 768 765 804 600
131
Marin County Proportions per 100,000
Bay Area Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 470 539 543 423 566 481 233 NA
Male 455 499 480 391 507 466 256 NA
CYF 752 775 676 608 818 707 423 NA
TAY 819 850 1,005 732 878 992 481 NA
Adults 436 511 504 377 516 422 218 NA
Older Adults 206 240 177 250 319 327 130 NA
Age 60-64 208 236 240 225 281 289 95 NA
Age 65-74 107 121 128 132 141 199 97 NA
Age 75-84 81 121 161 147 267 125 70 NA
Age 85+ 209 242 190 245 212 434 73 NA
Total Population 466 519 510 407 536 475 245 225
Mariposa County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 1,577 1,863 1,455 1,753 1,770 2,355 NA NA
TAY 1,677 2,569 2,303 1,987 2,846 3,010 NA NA
Adults 1,468 1,514 1,289 1,341 1,188 1,625 NA NA
Older Adults 261 340 166 240 355 240 NA NA
Age 60-64 537 754 515 349 717 377 NA NA
Age 65-74 214 155 - 242 315 311 NA NA
Age 75-84 92 272 89 87 81 - NA NA
Age 85+ - - - 289 - - NA NA
Total Population 1,202 1,381 1,126 1,175 1,203 1,463 NA NA
132
Mendocino County Proportions per 100,000
Superior Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,185 1,412 1,436 1,434 1,244 1,133 988 352
Male 917 1,196 1,249 1,214 1,113 1,013 830 362
CYF 1,671 2,074 2,256 2,174 2,209 2,170 1,907 755
TAY 1,442 1,638 2,094 2,007 1,814 1,517 1,506 476
Adults 1,031 1,317 1,159 1,297 1,087 932 720 350
Older Adults 313 521 314 414 334 334 247 100
Age 60-64 480 652 413 450 294 334 205 102
Age 65-74 136 276 349 273 215 137 163 79
Age 75-84 143 312 263 173 167 208 154 -
Age 85+ 77 114 - 191 86 109 119 -
Total Population 1,056 1,313 1,326 1,338 1,182 1,075 908 365
Merced County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 446 626 746 783 799 465 455 410
Male 360 525 778 757 649 409 396 394
CYF 380 532 561 490 519 369 300 373
TAY 592 841 1,023 1,106 1,149 551 580 546
Adults 422 604 928 964 824 519 516 454
Older Adults 162 261 218 342 344 228 200 156
Age 60-64 151 256 340 467 294 138 238 218
Age 65-74 72 161 146 184 220 176 117 79
Age 75-84 90 68 144 105 185 166 100 24
Age 85+ 262 431 354 265 438 125 33 110
Total Population 403 575 750 770 724 437 426 402
133
Modoc County Proportions per 100,000
Superior Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 766 1,629 1,457 1,576 1,583 1,343 NA NA
TAY 818 1,650 1,563 2,598 2,806 3,138 NA NA
Adults 1,127 1,126 882 1,641 1,316 1,402 NA NA
Older Adults 173 340 208 402 374 146 NA NA
Age 60-64 319 155 296 272 996 363 NA NA
Age 65-74 216 211 209 712 187 90 NA NA
Age 75-84 - 348 173 176 - - NA NA
Age 85+ - 1,569 - - - - NA NA
Total Population 793 1,089 897 1,403 1,256 1,208 NA NA
Mono County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 496 639 1,071 751 1,170 2,466 NA NA
TAY 143 635 505 623 474 1,325 NA NA
Adults 189 147 240 616 310 531 NA NA
Older Adults 60 55 52 201 44 137 NA NA
Age 60-64 158 - 140 268 122 123 NA NA
Age 65-74 - 125 - 120 - 217 NA NA
Age 75-84 - - - 281 - - NA NA
Age 85+ - - - - - - NA NA
Total Population 225 304 408 583 440 944 NA NA
134
Monterey County Proportions per 100,000
Bay Area Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 477 584 662 784 525 653 602 530
Male 394 522 575 656 456 594 553 520
CYF 717 915 1,030 1,173 676 1,052 1,005 901
TAY 671 828 881 1,033 820 983 898 773
Adults 319 412 462 573 412 479 435 409
Older Adults 84 130 99 174 151 163 165 161
Age 60-64 148 157 219 184 123 138 150 148
Age 65-74 30 85 68 128 140 91 104 106
Age 75-84 28 67 33 84 61 101 68 87
Age 85+ 60 17 51 16 14 119 102 59
Total Population 436 552 616 718 489 627 582 526
Napa County Proportions per 100,000
Bay Area Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 161 239 226 131 175 166 237 190
Male 147 177 179 102 164 184 259 166
CYF 202 273 276 214 390 477 670 494
TAY 245 328 345 172 209 225 297 195
Adults 166 221 204 99 127 108 173 120
Older Adults 36 58 45 56 70 53 37 36
Age 60-64 55 47 42 39 74 79 12 46
Age 65-74 12 65 44 63 38 29 36 18
Age 75-84 18 14 59 31 64 14 30 28
Age 85+ - 40 30 - - - 26 -
Total Population 157 212 206 118 172 178 250 178
135
Nevada County Proportions per 100,000
Superior Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 343 413 206 184 218 239 503 555
Male 342 442 206 191 218 215 499 487
CYF 594 918 263 346 395 466 1,264 1,215
TAY 489 550 368 344 358 404 926 933
Adults 343 417 205 184 223 209 409 461
Older Adults 177 139 94 40 71 74 179 192
Age 60-64 94 146 127 15 74 80 190 153
Age 65-74 64 71 77 33 50 29 105 141
Age 75-84 34 17 100 - - 88 31 102
Age 85+ 716 252 42 103 91 - 179 70
Total Population 353 432 204 187 218 227 501 522
Orange County Proportions per 100,000
Southern Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 528 650 687 704 644 879 759 539
Male 590 751 809 829 760 994 935 725
CYF 638 791 807 885 821 1,068 956 771
TAY 971 1,163 1,223 1,293 1,239 1,387 1,348 1,029
Adults 535 682 740 728 642 919 835 614
Older Adults 341 470 385 468 353 580 345 270
Age 60-64 274 367 420 375 342 822 366 312
Age 65-74 161 236 299 249 202 213 165 147
Age 75-84 255 390 429 356 223 232 206 141
Age 85+ 486 522 500 470 259 272 233 135
Total Population 563 722 771 781 704 938 848 630
136
Placer County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 413 454 486 441 248 274 266 240
Male 339 440 466 417 232 269 257 220
CYF 625 786 544 615 319 369 412 342
TAY 541 678 882 778 456 528 510 388
Adults 364 404 513 423 247 278 261 242
Older Adults 63 91 89 85 46 32 28 46
Age 60-64 130 188 182 212 73 52 52 80
Age 65-74 27 46 70 16 33 17 10 24
Age 75-84 6 33 32 20 - 6 - 11
Age 85+ - - 35 16 12 - - 13
Total Population 378 448 482 432 242 273 265 232
Plumas County Proportions per 100,000
Superior Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 2,409 2,158 2,398 2,115 2,500 2,728 NA NA
TAY 3,032 3,401 2,600 3,020 2,610 2,244 NA NA
Adults 1,520 1,788 1,571 1,559 1,546 1,604 NA NA
Older Adults 333 311 251 314 198 296 NA NA
Age 60-64 637 561 356 448 424 466 NA NA
Age 65-74 233 230 362 262 118 197 NA NA
Age 75-84 78 158 - 164 - 334 NA NA
Age 85+ 500 241 - 453 232 - NA NA
Total Population 1,529 1,632 1,461 1,453 1,406 1,449 NA NA
137
Riverside County Proportions per 100,000
Southern Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 682 838 841 941 798 901 492 NA
Male 756 923 936 1,538 1,144 1,161 586 NA
CYF 826 953 795 908 808 908 485 NA
TAY 1,125 1,391 1,496 2,264 1,845 1,758 865 NA
Adults 720 866 974 1,354 1,108 1,135 591 NA
Older Adults 184 266 216 367 323 305 162 NA
Age 60-64 317 392 369 570 404 412 205 NA
Age 65-74 100 182 185 251 204 188 101 NA
Age 75-84 74 121 133 142 138 118 48 NA
Age 85+ 65 89 146 132 122 89 101 NA
Total Population 721 882 886 1,228 974 1,033 540 NA
Sacramento County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 762 924 900 990 607 542 41 NA
Male 925 1,141 1,130 1,141 645 590 44 NA
CYF 1,370 1,617 1,449 1,568 1,298 1,387 101 NA
TAY 1,282 1,663 1,520 1,708 945 804 60 NA
Adults 677 849 896 922 412 314 25 NA
Older Adults 174 219 178 347 173 94 6 NA
Age 60-64 218 332 352 389 179 121 10 NA
Age 65-74 112 137 165 224 95 60 3 NA
Age 75-84 80 75 59 178 89 17 - NA
Age 85+ 41 69 63 135 124 4 - NA
Total Population 842 1,030 1,012 1,065 629 571 42 NA
138
San Benito County Proportions per 100,000
Bay Area Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 447 894 1,175 1,147 923 1,109 NA NA
TAY 652 896 1,679 1,488 1,546 1,813 NA NA
Adults 418 617 1,140 945 723 1,114 NA NA
Older Adults 75 118 273 264 221 214 NA NA
Age 60-64 150 144 232 267 242 233 NA NA
Age 65-74 - 160 233 337 210 201 NA NA
Age 75-84 123 61 369 184 238 297 NA NA
Age 85+ - - 324 156 146 - NA NA
Total Population 417 670 1,113 983 819 1,082 NA NA
San Bernardino County Proportions per 100,000
Southern Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 675 767 798 826 759 781 812 674
Male 666 745 814 937 888 882 918 775
CYF 801 841 851 1,045 981 1,055 1,146 932
TAY 847 1,010 1,102 1,286 1,286 1,265 1,208 972
Adults 671 759 842 818 733 709 738 644
Older Adults 189 269 204 287 266 282 298 252
Age 60-64 266 372 390 385 312 310 358 293
Age 65-74 101 182 161 159 142 164 165 132
Age 75-84 59 56 71 65 91 93 78 74
Age 85+ 13 40 115 93 87 71 32 54
Total Population 672 758 810 883 824 833 866 725
139
San Diego County Proportions per 100,000
Southern Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 575 637 703 768 748 707 758 380
Male 576 643 698 815 799 772 993 509
CYF 858 1,002 977 1,104 1,119 1,190 1,250 657
TAY 661 704 755 1,025 1,099 982 1,112 560
Adults 536 625 687 735 675 648 854 397
Older Adults 246 328 277 452 333 304 366 183
Age 60-64 317 389 443 470 462 378 453 233
Age 65-74 141 157 217 251 160 155 185 99
Age 75-84 106 162 179 256 129 135 132 72
Age 85+ 222 452 311 406 132 119 144 75
Total Population 579 649 700 797 774 742 876 445
San Francisco County Proportions per 100,000
Bay Area Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 906 1,056 1,025 1,047 875 685 730 232
Male 1,100 1,370 1,338 1,272 1,136 860 869 273
CYF 1,360 1,824 1,731 1,718 1,388 1,305 1,230 417
TAY 1,518 2,253 1,391 2,196 1,869 1,065 768 262
Adults 1,042 1,161 1,151 1,110 992 779 817 270
Older Adults 551 656 533 622 568 429 800 164
Age 60-64 689 884 880 751 682 453 917 205
Age 65-74 369 436 482 417 379 248 559 112
Age 75-84 338 341 387 327 226 196 268 52
Age 85+ 187 323 290 307 230 221 178 11
Total Population 1,005 1,222 1,147 1,165 1,010 776 806 255
140
San Joaquin County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 735 879 940 933 955 895 901 288
Male 605 716 845 885 845 874 864 292
CYF 638 698 708 973 821 898 1,025 314
TAY 925 1,170 1,389 1,518 1,513 1,492 1,380 465
Adults 727 852 1,013 859 938 882 849 297
Older Adults 328 453 349 417 393 307 337 94
Age 60-64 317 425 607 452 397 382 444 123
Age 65-74 212 285 207 274 283 205 211 49
Age 75-84 201 286 247 222 140 81 110 28
Age 85+ 129 387 403 189 134 115 56 21
Total Population 670 797 894 909 900 885 882 290
San Luis Obispo County Proportions per 100,000
Southern Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 711 860 929 880 855 819 749 490
Male 631 693 737 778 719 732 663 450
CYF 1,060 1,143 1,268 1,359 1,278 1,323 1,327 848
TAY 798 838 970 937 838 934 775 557
Adults 695 829 847 828 883 777 714 472
Older Adults 195 357 243 407 254 329 301 216
Age 60-64 346 445 414 507 260 356 358 187
Age 65-74 87 247 155 273 190 245 182 175
Age 75-84 91 224 217 183 89 104 105 100
Age 85+ 185 136 178 196 108 163 163 64
Total Population 671 774 824 827 785 774 706 470
141
San Mateo County Proportions per 100,000
Bay Area Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 495 683 710 736 800 675 452 NA
Male 400 602 591 600 654 620 393 NA
CYF 586 771 868 827 1,045 933 540 NA
TAY 944 1,310 1,329 1,271 1,422 1,353 870 NA
Adults 391 546 546 614 612 526 393 NA
Older Adults 195 468 247 389 439 399 214 NA
Age 60-64 223 295 324 316 329 338 209 NA
Age 65-74 110 302 233 252 284 267 132 NA
Age 75-84 120 361 188 229 269 251 124 NA
Age 85+ 100 520 243 332 334 236 69 NA
Total Population 448 643 653 669 727 649 424 NA
Santa Barbara County Proportions per 100,000
Southern Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 531 629 564 533 365 369 478 334
Male 542 647 563 575 381 386 469 334
CYF 893 1,069 981 1,075 694 676 991 622
TAY 654 685 584 655 370 478 578 418
Adults 482 596 542 487 369 351 368 286
Older Adults 173 235 151 203 158 160 158 132
Age 60-64 191 253 232 276 217 176 216 148
Age 65-74 121 145 154 118 93 155 112 112
Age 75-84 89 177 110 122 50 21 60 34
Age 85+ 182 171 62 41 69 44 51 48
Total Population 540 639 577 574 387 394 483 340
142
Santa Clara County Proportions per 100,000
Bay Area Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 347 276 71 61 48 48 31 26
Male 372 286 80 66 56 53 39 28
CYF 644 435 85 61 45 39 27 18
TAY 641 481 148 139 105 105 65 44
Adults 242 226 68 58 52 50 39 33
Older Adults 179 110 23 30 27 33 13 13
Age 60-64 212 116 29 39 30 41 16 17
Age 65-74 110 68 29 20 20 23 9 8
Age 75-84 91 64 11 7 11 8 2 6
Age 85+ 20 60 4 4 4 - 4 -
Total Population 360 281 76 63 52 51 35 27
Santa Cruz County Proportions per 100,000
Bay Area Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 550 738 759 677 643 618 650 365
Male 743 932 993 909 857 803 891 421
CYF 1,060 1,373 1,413 1,422 1,142 1,263 1,407 726
TAY 951 1,226 1,040 1,044 978 804 858 449
Adults 563 708 782 706 717 679 727 364
Older Adults 118 201 166 192 227 265 306 139
Age 60-64 103 281 343 184 245 274 325 164
Age 65-74 103 110 109 124 143 142 171 70
Age 75-84 33 66 77 100 67 61 65 59
Age 85+ 76 48 24 - - 40 45 19
Total Population 647 835 856 794 750 711 770 393
143
Shasta County Proportions per 100,000
Superior Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 477 784 706 790 822 862 883 362
Male 431 726 681 831 801 1,009 926 452
CYF 741 1,412 1,248 1,470 1,345 1,463 1,519 717
TAY 638 1,097 1,076 1,211 1,136 1,516 1,601 693
Adults 452 663 651 760 839 962 859 392
Older Adults 110 182 129 235 167 219 206 101
Age 60-64 94 257 182 316 214 328 282 110
Age 65-74 66 67 111 183 82 94 114 75
Age 75-84 67 117 126 42 92 81 59 41
Age 85+ 131 151 54 46 50 45 104 22
Total Population 454 756 718 823 814 934 904 407
Sierra County Proportions per 100,000
Superior Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 193 1,553 2,804 2,216 2,295 2,321 NA NA
TAY 1,113 1,160 1,606 1,436 3,977 1,095 NA NA
Adults 361 846 1,427 1,401 1,079 1,156 NA NA
Older Adults 113 220 109 213 299 196 NA NA
Age 60-64 414 793 372 686 302 289 NA NA
Age 65-74 - - - - - 253 NA NA
Age 75-84 - - - - 1,000 - NA NA
Age 85+ - - - - - - NA NA
Total Population 350 818 1,286 1,188 1,264 1,019 NA NA
144
Siskiyou County Proportions per 100,000
Superior Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 1,388 1,878 1,747 1,906 2,018 1,683 NA NA
TAY 1,005 1,523 1,535 1,565 1,754 1,982 NA NA
Adults 659 968 1,079 1,060 978 888 NA NA
Older Adults 81 178 192 178 232 175 NA NA
Age 60-64 170 195 310 320 321 209 NA NA
Age 65-74 97 240 142 136 166 223 NA NA
Age 75-84 - 137 208 35 285 74 NA NA
Age 85+ - - - 269 88 87 NA NA
Total Population 703 1,005 1,030 1,046 1,052 951 NA NA
Solano County Proportions per 100,000
Bay Area Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 425 551 629 676 492 446 447 408
Male 442 492 592 640 483 429 476 413
CYF 516 632 728 801 673 737 874 771
TAY 629 748 871 903 629 553 571 534
Adults 432 517 599 667 489 394 386 343
Older Adults 137 202 178 311 198 185 199 165
Age 60-64 143 239 266 339 184 174 198 159
Age 65-74 114 126 195 210 163 131 113 77
Age 75-84 66 101 90 160 48 51 67 108
Age 85+ 18 39 38 56 55 39 63 82
Total Population 434 521 605 658 487 438 462 411
145
Sonoma County Proportions per 100,000
Bay Area Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 315 401 360 374 358 378 355 318
Male 340 390 386 378 366 445 411 310
CYF 487 595 469 562 565 607 632 481
TAY 569 693 659 671 664 780 627 524
Adults 282 332 337 328 326 375 349 301
Older Adults 134 170 113 143 112 140 158 138
Age 60-64 90 217 143 151 98 139 166 186
Age 65-74 97 115 131 118 77 84 101 69
Age 75-84 94 65 89 47 69 68 43 29
Age 85+ 108 42 40 18 18 36 45 25
Total Population 329 396 367 378 364 412 384 316
Stanislaus County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 440 628 733 694 777 725 743 66
Male 380 633 673 699 746 749 790 71
CYF 615 975 1,026 1,332 1,470 1,509 1,602 163
TAY 479 803 872 908 1,067 1,003 1,022 90
Adults 357 512 618 487 506 464 493 37
Older Adults 188 316 221 167 112 125 98 3
Age 60-64 186 260 269 189 112 177 145 4
Age 65-74 103 240 225 125 84 65 43 -
Age 75-84 91 181 195 81 60 52 23 6
Age 85+ 224 281 130 27 12 - 23 -
Total Population 410 630 708 697 762 738 767 69
146
Sutter/Yuba Counties Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 202 296 428 511 631 812 721 496
Male 157 224 341 410 537 640 700 452
CYF 164 228 370 505 624 745 765 460
TAY 290 328 596 730 895 1,174 1,033 720
Adults 202 318 445 461 631 790 798 532
Older Adults 40 75 52 135 170 234 216 190
Age 60-64 49 112 73 227 265 195 238 289
Age 65-74 - 43 60 75 78 152 121 89
Age 75-84 57 16 33 33 - 118 87 48
Age 85+ 58 - - 42 - 173 - -
Total Population 179 260 388 460 585 727 710 474
Tehama County Proportions per 100,000
Superior Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 460 1,496 1,233 1,089 882 1,137 NA NA
TAY 958 1,587 1,798 2,026 1,869 1,881 NA NA
Adults 662 913 1,096 1,129 1,022 1,002 NA NA
Older Adults 40 111 186 189 144 191 NA NA
Age 60-64 63 244 379 274 230 197 NA NA
Age 65-74 40 78 173 132 142 245 NA NA
Age 75-84 32 64 - 222 95 158 NA NA
Age 85+ - - 180 90 - - NA NA
Total Population 528 968 1,027 1,033 905 963 NA NA
147
Tuolumne County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 460 1,496 1,233 1,089 882 1,137 NA NA
TAY 958 1,587 1,798 2,026 1,869 1,881 NA NA
Adults 662 913 1,096 1,129 1,022 1,002 NA NA
Older Adults 40 111 186 189 144 191 NA NA
Age 60-64 63 244 379 274 230 197 NA NA
Age 65-74 40 78 173 132 142 245 NA NA
Age 75-84 32 64 - 222 95 158 NA NA
Age 85+ - - 180 90 - - NA NA
Total Population 528 968 1,027 1,033 905 963 NA NA
Trinity County Proportions per 100,000
Superior Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female NA NA NA NA NA NA NA NA
Male NA NA NA NA NA NA NA NA
CYF 2,992 2,773 2,031 2,634 1,907 2,808 NA NA
TAY 2,553 3,281 3,332 2,810 3,301 2,623 NA NA
Adults 986 1,124 1,075 748 802 784 NA NA
Older Adults 116 227 332 - 176 148 NA NA
Age 60-64 97 375 454 - 320 154 NA NA
Age 65-74 71 140 410 - 122 179 NA NA
Age 75-84 129 127 126 - 120 - NA NA
Age 85+ 435 407 - - - 388 NA NA
Total Population 1,269 1,389 1,262 1,056 1,038 1,088 NA NA
148
Tulare County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 409 538 542 563 433 484 617 509
Male 415 525 507 537 447 499 661 558
CYF 789 890 830 948 753 822 1,133 996
TAY 408 637 663 674 554 679 792 574
Adults 278 407 381 391 311 339 443 375
Older Adults 79 111 92 176 103 130 160 129
Age 60-64 111 136 118 260 115 173 214 162
Age 65-74 35 55 106 92 82 57 89 75
Age 75-84 15 67 60 78 41 58 22 44
Age 85+ 81 39 40 - 15 60 51 35
Total Population 412 531 522 550 440 491 639 534
Ventura County Proportions per 100,000
Southern Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 340 419 487 529 455 355 570 210
Male 374 450 509 622 503 369 545 233
CYF 363 461 582 883 743 527 884 346
TAY 683 762 877 930 851 616 812 306
Adults 334 411 434 465 370 318 486 208
Older Adults 158 197 184 254 222 115 275 100
Age 60-64 141 158 219 212 174 104 234 104
Age 65-74 99 93 159 128 135 72 177 55
Age 75-84 98 179 169 192 147 44 147 60
Age 85+ 136 217 216 234 166 98 206 49
Total Population 358 435 493 576 482 364 564 226
149
Yolo County Proportions per 100,000
Central Region
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 265 323 427 440 425 450 321 222
Male 242 312 435 421 341 434 333 199
CYF 334 355 515 487 392 509 480 340
TAY 243 328 429 462 312 475 303 172
Adults 271 351 474 452 499 485 360 239
Older Adults 113 175 210 327 247 266 121 62
Age 60-64 167 271 313 340 201 241 150 110
Age 65-74 82 131 187 259 178 149 46 8
Age 75-84 49 29 129 124 125 191 88 55
Age 85+ - 45 203 99 86 68 - -
Total Population 254 318 438 431 384 442 327 211
150
Appendix E. CSI Data Tables –
County All Clients (in Alphabetical Order)
Alameda County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,763 2,040 2,044 2,081 2,220 2,218 2,086 844
Male 1,818 2,136 2,176 2,252 2,380 2,437 2,378 1,078
CYF 2,095 2,598 2,513 2,770 3,061 3,346 3,340 1,735
TAY 2,202 2,556 2,453 2,847 3,393 3,186 3,175 1,315
Adults 1,898 2,179 2,209 2,174 2,194 2,218 2,059 796
Older Adults 905 1,042 804 1,234 1,302 1,279 1,209 509
Age 60-64 1,257 1,397 1,599 1,622 1,719 1,552 1,534 665
Age 65-74 553 680 708 731 823 739 675 282
Age 75-84 218 256 290 305 294 313 321 132
Age 85+ 108 150 105 163 119 121 82 36
Total Population 1,797 2,096 2,101 2,174 2,307 2,335 2,238 962
Alpine County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 3,448 4,134 4,344 6,195 5,265 4,042 NA NA
Male 2,708 4,768 3,234 3,190 3,441 2,640 NA NA
CYF 5,274 6,251 6,499 9,120 7,850 5,556 NA NA
TAY 2,015 4,683 3,819 3,522 1,785 1,980 NA NA
Adults 3,551 4,954 3,783 4,452 4,904 3,191 NA NA
Older Adults 0 929 887 1,275 1,120 2,174 NA NA
Age 60-64 0 0 0 1,105 902 4,545 NA NA
Age 65-74 0 2,036 2,098 1,083 988 917 NA NA
Age 75-84 0 0 0 2,369 2,079 0 NA NA
Age 85+ 0 0 0 0 0 0 NA NA
Total Population 3,974 5,578 4,968 6,374 5,847 4,426 NA NA
151
Amador County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 971 1,297 1,540 1,381 1,268 1,263 NA NA
Male 540 801 819 923 797 757 NA NA
CYF 986 1,409 1,769 1,284 1,227 1,252 NA NA
TAY 950 1,548 1,928 1,839 1,813 1,932 NA NA
Adults 896 1,195 1,195 1,388 1,225 1,210 NA NA
Older Adults 160 239 374 332 266 187 NA NA
Age 60-64 371 542 685 433 462 442 NA NA
Age 65-74 167 191 372 435 234 112 NA NA
Age 75-84 0 81 163 166 166 42 NA NA
Age 85+ 0 0 0 0 0 0 NA NA
Total Population 893 1,251 1,428 1,331 1,190 1,163 NA NA
Butte County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,755 2,126 2,159 2,284 1,919 2,325 2,801 2,510
Male 1,575 1,948 2,048 2,190 1,818 2,123 2,633 2,328
CYF 2,698 3,598 3,406 3,764 3,335 4,032 4,820 4,113
TAY 1,226 1,673 1,798 1,905 1,371 2,151 2,608 2,424
Adults 1,897 2,234 2,386 2,519 2,194 2,351 2,958 2,635
Older Adults 701 743 672 898 762 996 1,142 1,162
Age 60-64 1,344 1,291 1,249 1,155 973 1,049 1,251 1,377
Age 65-74 594 654 748 838 620 775 809 795
Age 75-84 104 194 281 237 202 292 386 313
Age 85+ 61 125 150 167 127 152 366 302
Total Population 2,161 2,650 2,756 2,877 2,450 2,908 3,526 3,106
152
Calaveras County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 638 793 862 840 1,040 1,143 NA NA
Male 492 583 627 622 870 955 NA NA
CYF 857 1,000 862 948 1,353 1,644 NA NA
TAY 855 977 1,270 1,474 1,873 1,898 NA NA
Adults 658 840 947 848 1,125 1,212 NA NA
Older Adults 94 116 152 162 182 210 NA NA
Age 60-64 212 261 302 414 440 473 NA NA
Age 65-74 20 20 38 37 34 52 NA NA
Age 75-84 0 0 0 0 35 0 NA NA
Age 85+ 0 115 0 112 0 103 NA NA
Total Population 717 867 901 904 1,194 1,325 NA NA
Colusa County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,132 1,848 2,331 2,470 2,198 1,999 NA NA
Male 943 1,481 2,050 1,989 1,753 1,725 NA NA
CYF 1,054 1,761 2,263 2,320 2,241 2,349 NA NA
TAY 964 2,007 2,584 2,943 2,763 2,603 NA NA
Adults 1,265 1,895 2,499 2,407 1,933 1,691 NA NA
Older Adults 420 475 835 961 976 896 NA NA
Age 60-64 822 905 1,744 1,238 1,285 1,486 NA NA
Age 65-74 174 258 336 733 445 439 NA NA
Age 75-84 0 0 0 0 0 0 NA NA
Age 85+ 0 0 0 307 300 287 NA NA
Total Population 1,318 2,135 2,808 2,862 2,576 2,479 NA NA
153
Contra Costa County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,243 1,469 1,421 1,593 1,676 1,784 1,818 1,661
Male 1,241 1,458 1,439 1,543 1,558 1,689 1,706 1,579
CYF 1,728 2,055 1,785 2,015 1,927 2,076 2,134 1,918
TAY 1,748 2,214 2,373 2,286 2,405 2,705 2,544 2,312
Adults 1,185 1,361 1,361 1,557 1,656 1,764 1,839 1,718
Older Adults 491 600 418 754 859 912 942 880
Age 60-64 603 655 719 880 992 1,020 1,112 1,129
Age 65-74 286 416 424 526 564 610 610 533
Age 75-84 171 220 182 221 238 270 253 242
Age 85+ 128 208 94 75 98 84 89 77
Total Population 1,613 1,882 1,836 1,968 2,013 2,161 2,191 2,000
Del Norte County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 5,590 6,205 5,686 5,228 3,734 3,125 NA NA
Male 4,015 4,271 3,947 3,828 3,094 2,483 NA NA
CYF 5,729 6,246 6,095 5,701 5,316 4,029 NA NA
TAY 6,169 7,152 6,619 6,199 4,797 3,818 NA NA
Adults 5,080 5,413 4,785 4,518 3,169 2,762 NA NA
Older Adults 1,379 1,583 1,627 1,696 1,078 873 NA NA
Age 60-64 2,961 3,566 3,221 3,094 2,132 1,263 NA NA
Age 65-74 214 105 366 256 236 325 NA NA
Age 75-84 159 80 392 385 78 238 NA NA
Age 85+ 0 471 0 0 231 656 NA NA
Total Population 5,848 6,362 5,927 5,583 4,401 3,523 NA NA
154
El Dorado County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,160 1,534 1,537 1,618 1,352 1,155 1,187 647
Male 1,113 1,400 1,393 1,598 1,416 1,245 1,301 751
CYF 1,540 1,865 1,528 2,675 2,483 2,322 2,451 1,375
TAY 1,335 1,804 2,502 2,089 1,990 2,159 1,858 960
Adults 1,199 1,549 1,569 1,516 1,224 926 1,086 664
Older Adults 517 715 463 806 562 508 490 222
Age 60-64 521 740 687 686 533 536 428 293
Age 65-74 361 526 478 497 345 313 282 112
Age 75-84 161 198 263 305 117 191 260 70
Age 85+ 105 239 109 209 133 29 178 0
Total Population 1,418 1,784 1,781 2,066 1,862 1,631 1,680 936
Fresno County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 2,165 2,460 2,260 2,014 1,658 1,487 1,366 842
Male 2,067 2,508 2,362 2,183 1,800 1,629 1,410 839
CYF 2,087 2,588 2,178 2,314 1,932 1,880 1,555 863
TAY 2,259 2,873 2,860 2,560 2,067 1,734 1,548 852
Adults 2,453 2,749 2,653 2,251 1,836 1,652 1,530 978
Older Adults 1,195 1,358 847 978 862 801 766 575
Age 60-64 1,586 1,646 1,636 1,290 1,267 1,017 986 791
Age 65-74 784 979 793 677 568 522 476 356
Age 75-84 423 469 349 306 243 180 185 124
Age 85+ 477 329 164 105 49 35 53 13
Total Population 2,666 3,136 2,912 2,674 2,219 2,024 1,772 1,053
155
Glenn County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,819 1,908 1,838 2,414 2,251 2,326 NA NA
Male 972 1,257 1,266 1,493 1,583 1,536 NA NA
CYF 1,824 1,975 1,967 2,325 2,348 2,561 NA NA
TAY 1,743 2,331 1,896 2,621 2,650 2,217 NA NA
Adults 1,436 1,609 1,601 2,031 1,990 2,004 NA NA
Older Adults 399 395 592 741 600 677 NA NA
Age 60-64 961 794 862 905 935 1,116 NA NA
Age 65-74 111 109 106 360 193 342 NA NA
Age 75-84 80 0 0 0 82 253 NA NA
Age 85+ 220 424 411 208 206 0 NA NA
Total Population 1,871 2,102 2,074 2,560 2,513 2,564 NA NA
Humboldt County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,431 1,836 1,763 1,699 1,669 1,863 1,595 1,616
Male 1,436 1,758 1,699 1,662 1,658 1,869 1,591 1,622
CYF 1,282 1,746 1,569 1,918 2,090 2,305 1,835 1,826
TAY 1,576 1,894 1,803 1,718 1,644 2,214 1,690 1,884
Adults 1,734 2,223 2,074 1,970 1,940 2,068 1,905 1,888
Older Adults 742 825 623 926 955 1,058 890 942
Age 60-64 885 922 1,070 1,079 1,107 1,137 963 1,196
Age 65-74 620 640 645 707 576 651 548 564
Age 75-84 352 227 280 287 323 428 276 223
Age 85+ 171 383 123 104 87 34 80 120
Total Population 1,668 2,089 1,965 2,005 2,017 2,253 1,894 1,920
156
Imperial County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,469 1,842 1,820 1,953 2,133 2,105 2,318 2,460
Male 2,004 2,251 2,286 2,384 2,630 2,665 2,797 2,813
CYF 2,745 3,484 2,918 3,573 3,924 4,062 4,292 4,392
TAY 1,540 1,912 2,288 2,027 2,736 2,964 2,981 3,084
Adults 1,589 1,733 1,703 1,906 1,869 1,798 2,058 2,125
Older Adults 662 917 806 1,104 1,214 1,221 1,333 1,390
Age 60-64 973 1,702 1,479 1,693 1,775 1,617 1,721 1,989
Age 65-74 492 653 765 760 781 759 811 900
Age 75-84 220 274 408 356 405 586 607 521
Age 85+ 125 60 64 209 122 152 116 456
Total Population 2,462 2,893 2,789 3,043 3,392 3,380 3,607 3,693
Inyo County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 2,030 2,245 2,289 2,204 2,357 1,882 NA NA
Male 1,791 2,086 1,785 2,082 1,893 2,021 NA NA
CYF 2,234 2,747 2,217 2,723 2,484 2,778 NA NA
TAY 2,441 2,749 2,508 2,952 2,805 3,337 NA NA
Adults 2,257 2,411 2,266 2,423 2,493 2,160 NA NA
Older Adults 776 996 768 972 869 1,108 NA NA
Age 60-64 1,191 1,702 1,137 1,578 1,245 1,718 NA NA
Age 65-74 178 237 177 235 166 440 NA NA
Age 75-84 234 322 243 321 243 418 NA NA
Age 85+ 1,105 421 1,047 417 586 384 NA NA
Total Population 2,334 2,687 2,575 2,655 2,851 2,222 NA NA
157
Kern County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,533 1,866 1,750 1,919 1,998 1,796 1,912 1,705
Male 1,588 1,810 1,763 1,952 2,083 2,183 2,264 2,016
CYF 2,280 2,623 2,117 2,509 2,630 2,697 3,134 2,655
TAY 1,369 1,800 1,825 2,289 2,681 2,717 2,701 2,424
Adults 1,451 1,717 1,787 1,865 1,875 1,772 1,723 1,639
Older Adults 913 1,021 456 826 878 765 816 724
Age 60-64 854 1,046 869 1,149 1,087 826 940 820
Age 65-74 538 590 406 485 513 425 476 378
Age 75-84 591 629 147 238 336 306 314 262
Age 85+ 775 828 103 201 204 196 246 170
Total Population 2,167 2,483 2,314 2,559 2,721 2,672 2,874 2,527
Kings County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,533 1,866 1,750 1,919 1,998 1,796 1,912 1,705
Male 1,588 1,810 1,763 1,952 2,083 2,183 2,264 2,016
CYF 2,280 2,623 2,117 2,509 2,630 2,697 3,134 2,655
TAY 1,369 1,800 1,825 2,289 2,681 2,717 2,701 2,424
Adults 1,451 1,717 1,787 1,865 1,875 1,772 1,723 1,639
Older Adults 913 1,021 456 826 878 765 816 724
Age 60-64 854 1,046 869 1,149 1,087 826 940 820
Age 65-74 538 590 406 485 513 425 476 378
Age 75-84 591 629 147 238 336 306 314 262
Age 85+ 775 828 103 201 204 196 246 170
Total Population 2,167 2,483 2,314 2,559 2,721 2,672 2,874 2,527
158
Lake County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,795 2,159 2,759 2,770 2,211 1,250 1,432 1,192
Male 1,408 1,804 2,229 2,279 1,970 1,424 1,365 896
CYF 1,747 2,700 3,137 3,378 2,948 1,768 1,972 1,306
TAY 1,623 2,039 3,188 3,489 3,255 1,308 2,015 1,810
Adults 2,087 2,357 3,100 2,889 2,248 1,673 1,550 1,121
Older Adults 580 750 635 1,063 949 789 770 624
Age 60-64 999 1,038 1,078 1,014 1,151 758 925 717
Age 65-74 316 544 569 736 562 535 466 394
Age 75-84 202 213 364 420 447 253 142 118
Age 85+ 60 0 296 307 58 102 198 274
Total Population 1,929 2,489 3,135 3,120 2,643 1,649 1,716 1,258
Lassen County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,977 2,908 2,679 2,423 2,544 2,805 NA NA
Male 885 1,210 1,091 1,094 1,300 1,245 NA NA
CYF 1,925 2,916 2,891 2,827 3,205 2,480 NA NA
TAY 1,566 2,344 2,167 2,157 2,310 2,914 NA NA
Adults 1,193 1,635 1,415 1,324 1,542 1,686 NA NA
Older Adults 417 515 490 393 404 433 NA NA
Age 60-64 646 837 698 706 622 764 NA NA
Age 65-74 120 59 114 112 154 101 NA NA
Age 75-84 188 92 355 90 94 0 NA NA
Age 85+ 0 553 0 0 0 223 NA NA
Total Population 1,616 2,319 2,143 2,033 2,249 2,192 NA NA
159
Los Angeles County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,504 1,655 1,692 1,741 1,768 1,732 1,916 1,038
Male 1,917 2,184 2,256 2,212 2,138 1,954 2,325 1,181
CYF 1,991 2,320 2,387 2,726 2,935 3,132 3,444 1,650
TAY 2,101 2,383 2,471 2,484 2,591 2,270 2,577 1,262
Adults 1,751 1,928 2,029 1,884 1,726 1,537 1,888 1,042
Older Adults 809 932 723 1,035 1,087 993 1,114 688
Age 60-64 1,136 1,304 1,407 1,347 1,418 1,272 1,478 980
Age 65-74 495 598 635 667 692 598 666 398
Age 75-84 226 282 289 322 326 288 298 141
Age 85+ 228 253 236 267 273 211 174 72
Total Population 2,177 2,438 2,541 2,551 2,566 2,467 2,795 1,431
Madera County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 2,095 2,178 2,309 2,259 2,018 1,810 1,718 1,530
Male 1,533 1,859 1,956 2,068 1,770 1,641 1,607 1,286
CYF 1,911 2,344 2,225 2,599 2,215 2,116 1,815 1,312
TAY 1,890 2,190 2,750 2,800 2,554 2,043 2,021 1,765
Adults 2,204 2,167 2,339 2,151 1,965 1,819 1,835 1,667
Older Adults 712 998 753 1,108 1,092 836 946 852
Age 60-64 617 1,184 1,016 1,168 876 1,051 774 829
Age 65-74 539 823 818 1,005 724 595 677 564
Age 75-84 313 554 448 306 454 286 466 337
Age 85+ 166 204 417 461 162 319 497 313
Total Population 2,284 2,564 2,717 2,761 2,448 2,219 2,081 1,725
160
Marin County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,217 1,360 1,358 1,223 1,329 1,122 819 NA
Male 1,232 1,341 1,310 1,207 1,247 1,167 908 NA
CYF 1,637 1,825 1,531 1,606 1,770 1,514 1,126 NA
TAY 1,738 1,891 2,242 1,616 1,876 1,962 1,373 NA
Adults 1,302 1,433 1,411 1,290 1,318 1,130 887 NA
Older Adults 693 742 591 850 890 880 679 NA
Age 60-64 796 875 964 942 903 937 640 NA
Age 65-74 394 412 550 537 547 571 505 NA
Age 75-84 195 281 298 327 404 294 210 NA
Age 85+ 358 352 277 359 376 547 219 NA
Total Population 1,517 1,651 1,614 1,472 1,590 1,410 1,057 NA
Mariposa County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 2,093 2,917 2,947 3,026 3,197 3,062 NA NA
Male 2,094 2,635 2,243 2,283 2,534 2,535 NA NA
CYF 2,818 3,127 3,043 3,506 3,779 4,247 NA NA
TAY 2,439 4,110 4,606 4,081 5,583 5,072 NA NA
Adults 2,760 3,505 3,170 3,295 3,283 3,227 NA NA
Older Adults 479 786 497 500 785 628 NA NA
Age 60-64 690 1,508 957 698 1,565 1,258 NA NA
Age 65-74 268 258 149 338 270 222 NA NA
Age 75-84 0 91 89 0 0 0 NA NA
Age 85+ 0 0 0 289 0 0 NA NA
Total Population 2,619 3,322 3,096 3,225 3,468 3,446 NA NA
161
Mendocino County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 2,629 3,140 3,173 3,182 2,984 2,574 2,279 1,394
Male 1,999 2,516 2,568 2,688 2,622 2,410 2,092 1,438
CYF 3,064 4,052 4,223 4,983 4,970 5,046 4,857 3,301
TAY 2,518 3,148 3,698 3,739 3,846 3,274 3,615 2,171
Adults 2,625 3,063 2,821 2,850 2,696 2,144 1,566 1,058
Older Adults 956 1,369 936 1,352 1,179 1,060 762 558
Age 60-64 1,352 1,779 1,564 1,856 1,276 1,211 865 575
Age 65-74 452 775 889 820 731 533 466 385
Age 75-84 500 755 549 345 334 347 256 124
Age 85+ 231 152 56 255 130 109 178 0
Total Population 2,910 3,560 3,683 3,844 3,739 3,426 3,077 2,025
Merced County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,466 1,775 1,789 1,744 1,786 1,386 1,348 1,235
Male 1,213 1,415 1,621 1,556 1,474 1,124 1,135 1,091
CYF 1,117 1,330 1,149 1,096 1,018 857 855 849
TAY 1,470 1,818 1,901 1,872 2,028 1,303 1,230 1,158
Adults 1,639 1,936 2,241 2,166 2,084 1,652 1,660 1,539
Older Adults 730 833 658 940 1,053 907 838 789
Age 60-64 866 919 1,054 1,311 1,210 914 1,121 1,055
Age 65-74 462 586 578 581 723 614 484 448
Age 75-84 313 314 327 301 419 402 287 204
Age 85+ 299 467 673 265 548 250 98 220
Total Population 1,645 1,941 2,009 1,932 1,897 1,477 1,456 1,379
162
Modoc County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 2,512 3,066 2,445 2,857 3,434 4,035 NA NA
Male 1,670 2,461 2,146 2,611 2,533 2,891 NA NA
CYF 2,025 3,203 2,537 2,994 3,218 3,330 NA NA
TAY 1,909 3,209 3,125 4,364 4,884 6,904 NA NA
Adults 2,830 3,379 2,809 3,305 3,706 4,328 NA NA
Older Adults 821 1,061 831 924 1,010 1,025 NA NA
Age 60-64 1,436 1,397 1,481 952 1,744 1,572 NA NA
Age 65-74 0 106 105 407 373 451 NA NA
Age 75-84 346 174 173 353 0 175 NA NA
Age 85+ 0 2,093 512 488 0 441 NA NA
Total Population 2,472 3,372 2,784 3,325 3,613 4,099 NA NA
Mono County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 802 1,119 1,283 1,326 1,180 1,818 NA NA
Male 511 669 783 1,041 1,126 1,550 NA NA
CYF 1,106 1,428 2,295 2,096 2,542 4,135 NA NA
TAY 573 1,362 1,516 1,439 1,423 2,307 NA NA
Adults 634 709 613 1,018 929 1,076 NA NA
Older Adults 60 166 262 401 220 365 NA NA
Age 60-64 158 303 699 805 367 492 NA NA
Age 65-74 0 0 0 120 0 108 NA NA
Age 75-84 0 0 0 0 0 0 NA NA
Age 85+ 0 0 0 0 0 0 NA NA
163
Monterey County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,075 1,308 1,409 1,615 1,399 1,332 1,275 1,158
Male 1,027 1,185 1,306 1,437 1,306 1,263 1,278 1,217
CYF 1,435 1,850 2,003 2,369 1,914 1,952 1,983 1,803
TAY 1,394 1,681 1,791 1,941 1,895 1,883 1,815 1,621
Adults 949 1,060 1,153 1,300 1,181 1,102 1,069 1,021
Older Adults 436 487 393 636 664 580 608 625
Age 60-64 698 627 769 752 730 596 605 632
Age 65-74 316 372 390 508 530 414 442 488
Age 75-84 83 155 127 176 151 197 210 196
Age 85+ 60 17 51 16 28 136 102 71
Total Population 1,413 1,676 1,846 2,063 1,793 1,735 1,728 1,597
Napa County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 615 825 869 691 753 688 770 730
Male 633 743 818 653 756 770 904 887
CYF 781 1,019 990 1,099 1,220 1,411 1,700 1,691
TAY 676 953 1,161 758 852 965 1,195 1,027
Adults 702 842 907 655 765 597 666 664
Older Adults 455 490 364 433 413 427 404 370
Age 60-64 465 583 575 499 395 511 525 497
Age 65-74 332 430 383 324 366 317 289 274
Age 75-84 235 196 235 168 145 113 135 71
Age 85+ 37 79 121 143 92 65 79 78
Total Population 800 991 1,061 885 1,000 1,005 1,161 1,127
164
Nevada County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 877 1,095 912 963 1,084 1,125 1,447 1,507
Male 812 1,067 869 1,000 1,035 1,134 1,464 1,474
CYF 1,097 1,765 1,024 1,728 1,913 2,151 3,459 3,844
TAY 787 1,161 1,013 1,178 1,405 1,597 2,149 2,129
Adults 1,041 1,209 1,073 1,075 1,138 1,160 1,382 1,393
Older Adults 468 537 350 386 428 468 503 485
Age 60-64 439 583 619 529 457 528 571 470
Age 65-74 255 357 276 272 279 271 281 364
Age 75-84 170 155 232 72 167 243 155 153
Age 85+ 763 419 125 138 137 76 223 70
Total Population 1,027 1,343 1,064 1,218 1,342 1,466 1,960 2,027
Orange County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,144 1,363 1,378 1,420 1,359 1,560 1,428 1,169
Male 1,219 1,477 1,511 1,569 1,523 1,724 1,683 1,470
CYF 1,260 1,513 1,469 1,636 1,596 1,835 1,729 1,556
TAY 1,718 2,041 2,074 2,186 2,267 2,337 2,313 1,967
Adults 1,251 1,474 1,546 1,520 1,385 1,626 1,537 1,313
Older Adults 916 1,120 878 1,152 967 1,176 870 753
Age 60-64 1,254 1,454 1,560 1,455 1,371 1,754 1,217 1,173
Age 65-74 371 502 569 538 464 468 370 321
Age 75-84 389 566 635 563 379 381 321 251
Age 85+ 587 719 708 622 369 365 307 183
Total Population 1,488 1,796 1,840 1,878 1,784 2,017 1,905 1,619
165
Placer County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 978 1,134 1,156 1,087 832 628 596 561
Male 841 1,025 1,122 1,047 811 686 625 548
CYF 1,246 1,526 1,187 1,335 946 850 822 744
TAY 1,072 1,319 1,702 1,570 1,270 1,105 1,124 865
Adults 990 1,151 1,336 1,161 933 686 633 599
Older Adults 331 384 324 378 284 219 191 203
Age 60-64 518 754 677 762 483 322 280 355
Age 65-74 213 234 277 231 183 141 99 106
Age 75-84 74 106 96 50 43 46 37 53
Age 85+ 47 38 69 16 12 14 14 26
Total Population 1,148 1,355 1,419 1,310 1,011 826 776 701
Plumas County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 3,177 3,767 3,586 3,628 3,597 3,619 NA NA
Male 2,555 2,972 2,666 2,802 2,643 2,839 NA NA
CYF 4,043 4,372 4,111 3,996 4,629 5,039 NA NA
TAY 4,280 5,838 4,689 5,191 4,707 4,301 NA NA
Adults 3,352 3,902 3,782 3,931 3,883 4,026 NA NA
Older Adults 630 806 806 889 691 805 NA NA
Age 60-64 1,211 1,746 1,545 1,735 1,430 1,606 NA NA
Age 65-74 186 0 271 350 158 237 NA NA
Age 75-84 78 0 0 82 0 167 NA NA
Age 85+ 500 241 0 453 232 0 NA NA
Total Population 3,567 4,124 3,826 3,884 3,873 4,019 NA NA
166
Riverside County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,270 1,584 1,595 1,693 1,636 1,738 1,318 NA
Male 1,403 1,696 1,715 2,395 2,019 2,038 1,447 NA
CYF 1,376 1,719 1,428 1,621 1,497 1,582 1,175 NA
TAY 1,807 2,260 2,472 3,250 2,998 2,848 1,856 NA
Adults 1,464 1,709 1,907 2,286 2,189 2,169 1,596 NA
Older Adults 545 671 530 825 855 856 713 NA
Age 60-64 998 1,172 1,091 1,461 1,239 1,247 1,008 NA
Age 65-74 345 458 450 576 547 562 463 NA
Age 75-84 133 190 209 207 223 217 150 NA
Age 85+ 111 149 172 168 181 127 158 NA
Total Population 1,668 2,037 2,031 2,403 2,177 2,258 1,658 NA
Sacramento County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,884 2,192 2,233 2,306 1,941 1,253 534 NA
Male 2,054 2,458 2,492 2,495 1,954 1,380 599 NA
CYF 2,749 3,300 2,999 3,255 2,977 2,716 1,202 NA
TAY 2,290 3,021 2,884 3,160 2,375 1,612 640 NA
Adults 1,924 2,195 2,399 2,332 1,793 957 400 NA
Older Adults 755 857 691 1,065 983 503 275 NA
Age 60-64 1,062 1,309 1,397 1,462 1,253 661 371 NA
Age 65-74 534 611 677 724 653 320 189 NA
Age 75-84 193 227 187 296 250 80 38 NA
Age 85+ 90 119 102 162 209 17 12 NA
Total Population 2,603 3,040 3,062 3,099 2,587 1,895 818 NA
167
San Benito County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,226 1,783 2,214 2,226 2,026 2,373 NA NA
Male 1,117 1,469 1,845 2,066 1,840 1,976 NA NA
CYF 1,300 1,863 2,133 2,253 2,058 2,254 NA NA
TAY 1,421 1,964 2,678 2,881 2,962 3,086 NA NA
Adults 1,208 1,662 2,136 2,240 1,904 2,294 NA NA
Older Adults 450 574 703 834 779 756 NA NA
Age 60-64 902 961 881 1,067 969 1,010 NA NA
Age 65-74 161 279 117 449 315 269 NA NA
Age 75-84 184 184 184 184 238 178 NA NA
Age 85+ 0 172 485 156 146 0 NA NA
Total Population 1,525 2,126 2,600 2,745 2,463 2,748 NA NA
San Bernardino County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,435 1,650 1,687 1,774 1,761 1,666 1,701 1,609
Male 1,447 1,592 1,682 1,880 1,950 1,841 1,871 1,763
CYF 1,622 1,803 1,654 2,012 2,072 2,026 2,149 2,064
TAY 1,471 1,746 1,957 2,166 2,389 2,264 2,191 1,931
Adults 1,577 1,746 1,918 1,898 1,860 1,691 1,692 1,620
Older Adults 616 733 577 888 878 863 877 828
Age 60-64 940 1,143 1,179 1,248 1,112 1,045 1,106 1,027
Age 65-74 323 433 460 502 493 487 469 429
Age 75-84 117 127 152 168 190 195 179 180
Age 85+ 39 46 141 132 130 121 72 109
Total Population 1,863 2,062 2,140 2,318 2,367 2,248 2,310 2,184
168
San Diego County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,407 1,504 1,582 1,680 1,695 1,628 1,597 1,162
Male 1,328 1,430 1,494 1,634 1,700 1,640 1,912 1,414
CYF 1,646 1,948 1,887 1,998 2,123 2,198 2,244 1,633
TAY 1,293 1,345 1,381 1,699 1,982 1,884 2,073 1,449
Adults 1,484 1,621 1,680 1,784 1,682 1,621 1,828 1,308
Older Adults 763 884 695 1,102 1,054 1,020 1,075 841
Age 60-64 1,291 1,474 1,498 1,592 1,546 1,406 1,465 1,253
Age 65-74 418 472 510 617 559 546 555 444
Age 75-84 196 259 272 371 303 324 278 204
Age 85+ 275 512 355 469 241 203 216 140
Total Population 1,745 1,882 1,933 2,080 2,138 2,060 2,177 1,597
San Francisco County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 2,628 2,922 2,846 2,790 2,617 2,410 1,260 1,051
Male 3,071 3,434 3,386 3,270 3,103 2,850 1,543 1,258
CYF 3,386 3,910 3,886 3,794 3,531 3,480 2,287 1,672
TAY 2,950 3,895 2,520 3,956 3,655 2,566 1,359 1,075
Adults 3,040 3,276 3,217 3,068 2,879 2,713 1,411 1,175
Older Adults 2,509 2,782 2,248 2,728 2,848 2,898 1,350 1,256
Age 60-64 3,497 3,958 4,228 3,774 3,542 3,226 1,640 1,494
Age 65-74 1,883 2,151 2,162 2,026 2,126 2,050 928 922
Age 75-84 1,100 1,190 1,201 1,069 914 981 392 371
Age 85+ 522 680 718 623 667 635 217 140
Total Population 3,293 3,690 3,494 3,520 3,306 3,029 1,671 1,351
169
San Joaquin County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,847 2,030 2,037 2,067 2,073 1,965 1,981 1,306
Male 1,539 1,643 1,749 1,867 1,859 1,863 1,877 1,243
CYF 1,161 1,295 1,204 1,611 1,482 1,477 1,659 998
TAY 1,617 1,920 2,137 2,424 2,519 2,426 2,348 1,306
Adults 2,203 2,275 2,484 2,260 2,338 2,240 2,206 1,580
Older Adults 1,418 1,547 1,117 1,526 1,525 1,499 1,505 1,163
Age 60-64 1,547 1,847 1,928 1,939 1,654 1,883 1,954 1,343
Age 65-74 888 1,028 928 971 1,037 981 970 757
Age 75-84 711 715 643 676 529 507 483 325
Age 85+ 540 727 719 401 424 345 262 258
Total Population 1,984 2,143 2,222 2,351 2,333 2,270 2,326 1,512
San Luis Obispo County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,477 1,710 1,734 1,760 1,759 1,709 1,565 1,306
Male 1,358 1,466 1,466 1,585 1,564 1,583 1,521 1,267
CYF 2,320 2,686 2,540 3,015 2,940 3,011 3,083 2,581
TAY 1,372 1,428 1,579 1,707 1,581 1,696 1,447 1,207
Adults 1,556 1,738 1,715 1,689 1,858 1,715 1,611 1,358
Older Adults 396 625 454 724 580 645 644 541
Age 60-64 834 1,029 961 1,134 781 829 870 611
Age 65-74 209 404 315 442 371 467 418 396
Age 75-84 98 240 246 219 130 142 119 161
Age 85+ 231 166 196 213 123 163 196 76
Total Population 1,815 1,991 2,017 2,129 2,104 2,102 2,001 1,686
170
San Mateo County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,156 1,450 1,556 1,609 1,692 1,606 1,255 NA
Male 1,024 1,298 1,350 1,384 1,443 1,487 1,157 NA
CYF 1,089 1,401 1,570 1,634 1,797 1,797 1,241 NA
TAY 1,779 2,276 2,367 2,387 2,573 2,625 2,011 NA
Adults 1,121 1,358 1,403 1,480 1,497 1,441 1,195 NA
Older Adults 779 1,110 864 1,204 1,355 1,348 1,105 NA
Age 60-64 892 969 1,214 1,091 1,192 1,299 1,065 NA
Age 65-74 193 331 357 365 414 406 333 NA
Age 75-84 153 270 194 211 257 244 167 NA
Age 85+ 191 681 607 689 583 489 301 NA
Total Population 1,309 1,648 1,772 1,803 1,906 1,881 1,439 NA
Santa Barbara County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,373 1,658 1,613 1,562 1,293 1,391 1,351 1,142
Male 1,398 1,678 1,650 1,629 1,328 1,477 1,364 1,142
CYF 1,821 2,357 2,238 2,369 1,750 2,115 2,146 1,580
TAY 1,439 1,606 1,469 1,529 1,109 1,438 1,250 1,104
Adults 1,495 1,777 1,756 1,720 1,577 1,541 1,393 1,216
Older Adults 634 794 620 859 801 875 835 814
Age 60-64 902 1,112 1,135 1,211 1,066 1,172 1,323 1,148
Age 65-74 502 636 669 661 647 661 618 586
Age 75-84 198 319 274 289 176 203 197 220
Age 85+ 327 329 185 113 118 120 81 77
Total Population 1,779 2,144 2,084 2,078 1,677 1,866 1,771 1,445
171
Santa Clara County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,070 997 662 560 470 361 287 217
Male 1,045 1,018 649 548 465 387 310 246
CYF 1,113 1,119 484 324 197 163 116 81
TAY 1,263 1,271 685 558 433 358 285 206
Adults 1,047 991 762 662 584 462 368 297
Older Adults 1,179 938 554 707 662 540 447 330
Age 60-64 1,673 1,081 865 749 733 561 509 408
Age 65-74 668 700 605 523 515 410 343 230
Age 75-84 362 352 281 289 237 194 121 88
Age 85+ 143 215 119 96 86 65 61 31
Total Population 1,298 1,244 767 620 508 407 322 248
Santa Cruz County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,147 1,427 1,507 1,445 1,291 1,207 1,219 931
Male 1,495 1,836 1,969 1,938 1,886 1,733 1,811 1,298
CYF 1,908 2,509 2,681 2,971 2,679 2,744 2,847 2,188
TAY 1,808 2,188 2,121 2,237 1,962 1,709 1,651 1,209
Adults 1,261 1,503 1,560 1,492 1,448 1,317 1,371 951
Older Adults 368 460 385 542 540 645 766 614
Age 60-64 392 637 770 587 593 652 740 702
Age 65-74 292 291 289 311 334 377 500 364
Age 75-84 87 133 176 244 144 146 173 202
Age 85+ 114 48 24 0 32 60 90 56
Total Population 1,693 2,090 2,205 2,221 2,077 1,942 2,002 1,490
172
Shasta County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,794 2,172 2,057 2,089 2,205 2,173 2,092 1,410
Male 1,726 2,054 1,936 2,129 2,162 2,344 2,235 1,538
CYF 2,697 3,571 3,244 3,746 3,568 3,397 3,676 2,685
TAY 1,983 2,458 2,457 2,472 2,695 3,045 3,132 1,934
Adults 1,915 2,127 2,103 2,146 2,316 2,485 2,170 1,519
Older Adults 581 693 543 730 673 752 671 465
Age 60-64 728 1,084 996 1,051 969 1,049 962 620
Age 65-74 373 418 499 534 389 451 445 339
Age 75-84 193 253 283 137 150 185 109 93
Age 85+ 219 242 108 69 124 67 104 22
Total Population 2,280 2,758 2,719 2,798 2,863 2,888 2,827 1,937
Sierra County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,595 2,132 3,458 4,576 4,561 4,956 NA NA
Male 1,209 2,247 2,595 3,300 3,897 3,341 NA NA
CYF 1,929 3,494 5,207 7,454 7,095 6,329 NA NA
TAY 3,059 3,189 3,855 6,822 10,122 10,584 NA NA
Adults 1,262 2,174 3,225 4,011 4,250 3,946 NA NA
Older Adults 675 1,101 1,194 1,065 1,194 1,663 NA NA
Age 60-64 1,243 2,378 2,605 2,401 1,510 2,312 NA NA
Age 65-74 0 0 0 0 254 0 NA NA
Age 75-84 0 0 0 0 500 966 NA NA
Age 85+ 0 0 0 0 0 0 NA NA
Total Population 1,691 2,716 3,798 5,055 5,273 5,062 NA NA
173
Siskiyou County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 2,637 3,052 3,349 3,306 3,484 3,493 NA NA
Male 2,240 2,769 2,947 2,988 3,063 2,956 NA NA
CYF 4,701 5,514 5,811 5,518 5,922 5,886 NA NA
TAY 2,420 3,523 4,016 4,232 4,683 4,801 NA NA
Adults 2,568 2,953 3,278 3,333 3,382 3,338 NA NA
Older Adults 471 579 577 670 760 722 NA NA
Age 60-64 885 1,009 929 1,222 1,285 1,073 NA NA
Age 65-74 217 192 189 181 228 202 NA NA
Age 75-84 0 137 104 0 178 74 NA NA
Age 85+ 97 0 91 269 88 87 NA NA
Total Population 3,315 3,938 4,240 4,198 4,385 4,292 NA NA
Solano County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,017 1,148 1,223 1,254 1,147 1,030 787 681
Male 1,124 1,163 1,262 1,353 1,234 1,161 946 811
CYF 1,270 1,531 1,545 1,808 1,651 1,718 1,862 1,760
TAY 1,239 1,384 1,575 1,608 1,474 1,298 1,148 992
Adults 1,116 1,151 1,229 1,272 1,175 1,040 621 485
Older Adults 535 550 423 661 640 566 326 250
Age 60-64 634 648 678 752 672 566 305 258
Age 65-74 400 357 421 462 453 367 215 131
Age 75-84 263 275 228 293 175 160 100 121
Age 85+ 36 58 75 84 147 117 79 98
Total Population 1,367 1,484 1,581 1,675 1,532 1,439 1,235 1,088
174
Sonoma County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 813 946 858 809 781 803 805 714
Male 858 981 925 914 902 1,011 972 853
CYF 892 1,166 924 1,098 1,175 1,266 1,324 1,155
TAY 1,054 1,251 1,240 1,165 1,247 1,414 1,351 1,112
Adults 907 994 930 870 822 868 832 764
Older Adults 563 608 410 553 498 544 554 503
Age 60-64 570 686 625 617 493 514 530 547
Age 65-74 439 486 501 431 380 410 397 334
Age 75-84 268 242 201 194 171 198 186 168
Age 85+ 156 136 60 36 45 62 109 83
Total Population 1,012 1,181 1,065 1,060 1,059 1,136 1,126 989
Stanislaus County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,342 1,610 1,573 1,510 1,550 1,484 1,496 633
Male 1,324 1,642 1,611 1,555 1,618 1,600 1,637 747
CYF 1,931 2,527 2,277 2,712 2,831 2,922 3,048 1,303
TAY 1,310 1,758 1,835 1,781 1,966 1,887 1,862 714
Adults 1,251 1,396 1,446 1,190 1,183 1,096 1,121 529
Older Adults 760 941 582 637 560 546 538 358
Age 60-64 792 975 867 799 647 708 653 431
Age 65-74 477 659 628 487 413 352 354 233
Age 75-84 375 499 346 216 205 197 175 109
Age 85+ 430 609 188 82 36 13 23 12
Total Population 1,812 2,221 2,200 2,165 2,266 2,229 2,273 991
175
Sutter-Yuba Counties-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,381 1,720 1,847 1,909 2,084 2,276 2,245 2,041
Male 1,118 1,370 1,599 1,551 1,665 1,897 1,953 1,743
CYF 1,120 1,633 1,685 1,810 1,884 2,125 2,075 1,839
TAY 1,024 1,236 1,796 1,746 2,120 2,507 2,320 1,972
Adults 1,604 1,886 2,076 1,939 2,137 2,381 2,464 2,229
Older Adults 868 1,045 803 1,225 1,329 1,343 1,507 1,504
Age 60-64 1,137 1,189 1,347 1,603 1,472 1,324 1,471 1,803
Age 65-74 549 776 805 974 891 968 1,057 1,005
Age 75-84 364 328 364 397 322 400 462 461
Age 85+ 288 210 315 166 190 404 290 136
Total Population 1,523 1,905 2,172 2,152 2,319 2,587 2,595 2,319
Tehama County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,971 2,504 2,707 2,948 2,644 2,716 NA NA
Male 1,279 1,883 1,852 1,939 1,897 2,040 NA NA
CYF 1,088 2,305 2,317 2,255 2,030 2,414 NA NA
TAY 2,281 2,911 3,153 3,564 3,612 3,712 NA NA
Adults 2,322 2,770 2,826 3,152 2,901 2,860 NA NA
Older Adults 396 467 620 696 700 778 NA NA
Age 60-64 912 915 1,255 1,208 1,276 1,428 NA NA
Age 65-74 80 118 173 264 230 210 NA NA
Age 75-84 32 64 0 158 126 158 NA NA
Age 85+ 0 0 360 90 0 0 NA NA
Total Population 1,889 2,733 2,820 2,997 2,769 2,943 NA NA
176
Tuolumne County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 2,457 3,052 3,066 3,252 2,821 2,071 NA NA
Male 1,696 2,088 1,975 2,355 1,787 1,467 NA NA
CYF 3,803 4,342 3,743 3,533 2,552 2,188 NA NA
TAY 2,709 3,739 3,761 4,656 3,482 2,782 NA NA
Adults 2,137 2,702 2,846 3,236 2,899 2,110 NA NA
Older Adults 454 550 526 746 666 573 NA NA
Age 60-64 904 1,085 1,028 1,203 1,187 1,004 NA NA
Age 65-74 145 89 89 191 229 178 NA NA
Age 75-84 131 185 54 163 27 110 NA NA
Age 85+ 0 77 291 565 68 203 NA NA
Total Population 2,678 3,250 3,096 3,348 2,669 2,088 NA NA
Trinity County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 2,658 3,156 3,005 2,814 2,714 2,353 NA NA
Male 2,327 2,857 2,536 2,174 2,169 2,362 NA NA
CYF 4,769 5,634 4,581 4,793 4,479 5,341 NA NA
TAY 4,347 6,064 6,072 5,151 6,219 4,938 NA NA
Adults 2,382 2,734 2,580 2,244 2,230 2,031 NA NA
Older Adults 378 567 692 538 352 443 NA NA
Age 60-64 682 1,311 1,271 1,202 719 926 NA NA
Age 65-74 142 70 137 133 122 119 NA NA
Age 75-84 0 127 252 128 0 0 NA NA
Age 85+ 435 407 0 383 0 388 NA NA
Total Population 3,285 3,943 3,532 3,292 3,166 3,199 NA NA
177
Tulare County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,162 1,472 1,586 1,602 1,513 1,446 1,535 1,423
Male 1,215 1,497 1,593 1,666 1,644 1,600 1,707 1,669
CYF 2,002 2,548 2,429 2,819 2,709 2,627 2,857 2,768
TAY 1,002 1,458 1,677 1,722 1,709 1,809 1,843 1,638
Adults 1,000 1,170 1,292 1,246 1,170 1,075 1,158 1,126
Older Adults 443 554 448 611 553 564 581 562
Age 60-64 603 734 797 908 810 808 755 774
Age 65-74 267 358 420 351 335 311 357 328
Age 75-84 108 202 218 190 179 137 116 138
Age 85+ 81 39 100 80 45 100 51 35
Total Population 1,741 2,162 2,303 2,380 2,325 2,235 2,394 2,291
Ventura County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 816 989 1,100 1,181 1,138 969 1,267 908
Male 901 1,068 1,163 1,340 1,285 1,083 1,285 975
CYF 785 997 1,110 1,695 1,675 1,454 1,806 1,298
TAY 1,249 1,480 1,729 1,771 1,788 1,480 1,692 1,114
Adults 925 1,083 1,147 1,177 1,099 960 1,231 968
Older Adults 527 615 505 687 683 472 674 510
Age 60-64 560 677 772 697 679 519 723 636
Age 65-74 347 374 456 414 450 301 446 325
Age 75-84 261 348 345 367 313 144 232 175
Age 85+ 252 335 307 351 267 159 263 80
Total Population 1,040 1,247 1,386 1,619 1,574 1,335 1,659 1,213
178
Yolo County-All Clients Proportion of All Clients per 100,000 Population
Variable 2005 2006 2007 2008 2009 2010 2011 2012
Female 1,009 1,220 1,269 1,239 1,177 1,243 1,011 866
Male 879 1,037 1,119 1,164 985 1,170 980 775
CYF 1,056 1,317 1,262 1,314 998 1,170 1,133 992
TAY 639 819 898 1,016 696 972 753 542
Adults 1,184 1,367 1,513 1,399 1,508 1,517 1,243 1,027
Older Adults 543 805 701 975 974 1,048 762 669
Age 60-64 1,021 1,338 1,239 1,283 1,113 1,214 999 1,075
Age 65-74 309 501 627 658 581 616 463 313
Age 75-84 162 189 322 263 281 333 161 201
Age 85+ 55 181 405 246 171 204 101 0
Total Population 1,165 1,385 1,466 1,451 1,273 1,425 1,203 996
179
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