Monitoring Californians' Mental Health

Population Surveillance Reveals Gender, Racial/Ethnic, Age, and Regional Disparities

by Nicole K. Eberhart, M. Audrey Burnam, Rachana Seelam, Olena Bogdan, Joshua Breslau

This Article

RAND Health Quarterly, 2019; 8(3):5

Abstract

Data from the California Health Interview Survey can facilitate the state, regional, and county tracking of key mental health indicators, including mental health services, service use, unmet need for services, and mental health–related functioning.

For more information, see RAND RR-2060-CMHSA at https://www.rand.org/pubs/research_reports/RR2060.html

Full Text

Population surveillance is critical for informing a public health approach to mental health. Ongoing monitoring of key mental health indicators is necessary for program and policy planning, as well as targeting and monitoring changes in response to policy initiatives or other important community changes. Surveillance enables the evaluation of programs and policies and facilitates problem-solving (e.g., Bonnie, Fulco, and Liverman, 1999). California has a unique population surveillance resource, the California Health Interview Survey (CHIS), which continuously interviews a representative sample of the state's population. The CHIS assesses mental health status of people in individual counties or groups of counties using standard population surveillance measures. Finally, the CHIS is administered in multiple languages—including Spanish, Chinese Mandarin and Cantonese dialects, Vietnamese, and Korean—so it is able to effectively survey California's diverse population.

The purpose of this study is to examine CHIS data from 2011 to 2013 to facilitate state, regional, and county tracking of key mental health indicators. The indicators we examine include need for mental health services, service use, unmet need for services, and mental health–related functioning. We chose CHIS indicators that could be useful to routinely monitor for statewide and county-level planning and improvement of prevention and early intervention (PEI) strategies. We selected indicators that are similar to measures in national surveillance surveys, such as the National Health Interview Survey (NHIS), Behavioral Risk Factor Surveillance System (BRFSS), and National Survey of Drug Use and Health (NSDUH). Further, the indicators we selected are relevant for tracking some of the negative outcomes that California's Mental Health Services Act (Proposition 63) seeks to improve through investment in PEI programs; these include suicide (although we are able to examine only suicide attempts, not completed suicides, in this study), unemployment, and other kinds of impairment (operationalized as work impairment) and prolonged suffering due to mental illness (operationalized as serious psychological distress). We focused on 2011–2013 because statewide PEI programs funded by the Mental Health Services Act and administered by the California Mental Health Services Authority (CalMHSA) were implemented in 2011, and this monitoring effort is part of a CalMHSA-funded statewide evaluation.

Survey Methods

The CHIS methodology is described in detail on its website (UCLA Center for Health Policy Research, undated). Briefly, the CHIS was designed to provide household population-based estimates for California, most of its counties, and all of its major racial/ethnic groups. CHIS data were continuously collected from California households by telephone from June 2011 through January 2013. Separate random-digit-dialing sampling frames were used for traditional landline households (approximately 80 percent of the sample) and for cell phone–only households (approximately 20 percent of the sample). The landline-sample response rate was 17 percent in 2011–2012 and 15 percent in 2013–2014, and the cell phone–sample response rate was 18 percent in 2011–2012 and 17 percent in 2013–2014.

Each of the landline and cell phone samples was stratified into 56 geographic areas, which are largely counties but also include regional groupings of very sparsely populated counties and some substrata within the two most highly populated counties. As a result of this stratified sampling strategy, CHIS data can be analyzed at the county level for 41 midsize to large counties and for three regions within which the remaining 17 smaller counties are grouped.

A supplemental surname list frame was used so that Korean and Vietnamese Californians were adequately represented in the survey. An American Indian/Alaska Native oversample was also drawn using a list provided by the Indian Health Service.

The CHIS randomly selected one adult in each household reached by telephone to participate in the interview. The CHIS surveyed adults, adolescents, and children, but the current analysis focuses on adults. Interviews were conducted in five languages (English, Spanish, Chinese Mandarin and Cantonese dialects, Vietnamese, and Korean) using a computer-assisted telephone interviewing (CATI) system.

The CHIS surveyed a wide variety of health issues (e.g., health status and conditions, health-related behaviors, health insurance, health service utilization), although the current analysis focuses on mental health.

Weighting and Variance Estimation

The CHIS weighted individuals completing the survey inversely to their probability of selection (UCLA Center for Health Policy Research, undated). Weights were developed in two steps. The first step was the development of a household weight that adjusted for probability of selection of the household from each stratum sampling frame, including adjustments for numbers never dialed, noncontacts and refusals, sample eligibility, screener interview nonresponse, and duplicate respondents. At the second step, the CHIS adjusted the household weight to create a person weight for each type of interview. For interviews with adults, this included adjustments for the probability of selection of the adult in the household, survey nonresponse among adults in the household, type of telephone, a composite weight adjustment for combining landline and cell phone samples, and a trimming and raking adjustment to produce population control totals consistent with the 2012 California Department of Finance (DOF) Population Estimates of noninstitutionalized household adults. The DOF population projections rely on the 2010 U.S. Census counts as a baseline and provide annually updated projections at the county level by race/ethnicity, gender, and age, based on fertility and mortality rates and life expectancy. The 2009–2011 California American Community Survey (ACS) and public-use microdata (PUMS) from the U.S. Census Bureau were used to produce 2012 DOF population counts by education and type of household.

Because the CHIS used a complex, stratified sampling design, our analyses use estimates of variances that take into account the complex design. These variance estimates, including standard errors and confidence intervals, are greater than what would be obtained if the design were a simple random sample of adults in the population. We estimate variances using a paired unit jackknife method that relies on replicate weights provided by the CHIS, employing the SUDAAN statistical package.

Sample

We examined 63,659 adults surveyed by the CHIS during the 2011–2013 period. Data were collected continuously during this time. Table 1 describes the demographic characteristics of this sample, which were self-reported by respondents. All results were weighted to be representative of the general population of California adults. Consequently, about half of the weighted CHIS sample was female, and 78 percent was either white or Latino.

Table 1. CHIS Sample Characteristics (Statewide %, 2011–2013)

Characteristic N (Unweighted) % (Weighted)
Gender
Male 26,174 48.79
Female 37,130 51.21
Race/ethnicity
White 38,900 43.93
Latino 13,665 34.13
Asian 5,721 13.63
Black 2,969 5.60
Other 2,049 2.70
Age range
18–24 years old 4,312 14.14
25–39 years old 8,356 27.29
40–49 years old 9,007 18.60
50–64 years old 19,982 24.43
65+ years old 21,647 15.54
Age (young adults vs. older adults)
18–24 years old 4,312 16.74
25–64 years old 37,345 83.26
Survey year
2011 22,580 32.71
2012 20,355 33.42
2013 20,724 33.86

Measures

The constructed measures are described in Table 2 and presented in detail below. To briefly summarize, we examine rates of serious psychological distress using a scoring cut point that is predictive of serious mental illness (SMI). We examine utilization of behavioral health services, which encompasses those who do not necessarily have SMI and those who sought help for substance use issues. The unmet-need measure is an indicator of how many people needed behavioral health services but did not receive any services at all, according to self-reported service utilization. Then we look at those who report being impaired by their mental health issues, regardless of whether they have utilized services. Finally, we examine reports of suicide attempts, which, like the serious distress measure, can be considered an additional indicator of mental health need.

Table 2. Description of How Measures Were Constructed

Measure Name Numerator Denominator Ratio/Rate
Serious distress (K-6 ≥ 13) Number who had K-6 score of 13 or higher All adults in sample 100 × numerator/ denominator
Saw PCP for mental health or substance use Number who saw a PCP for a mental or alcohol/drug problem in past year All adults in sample 100 × numerator/ denominator
Saw specialist for mental health or substance use Number who saw a psychiatrist/specialist for a mental or alcohol/drug problem in past year All adults in sample 100 × numerator/ denominator
Saw PCP or specialist for mental health or substance use Number who saw a PCP or mental health specialist for a mental or alcohol/drug problem in past year All adults in sample 100 × numerator/ denominator
Unmet need Number who reported needing help for emotional/mental or alcohol/drug problem in past year OR had serious psychological distress, as defined by a score of 13 or higher on the K-6 in past year, but reported not receiving any mental health or substance use treatment All adults in sample 100 × numerator/ denominator
Severe work impairment Number with severe work impairment in past year Adults 70 or younger who are employed 100 × numerator/ denominator
Missed 4+ days of work Number who missed 4 or more days of work in past year All adults in sample 100 × numerator/ denominator
Missed 9+ days of work Number who missed 9 or more days of work in past year All adults in sample 100 × numerator/ denominator
Attempted suicide Number who attempted suicide in past year All adults in sample 100 × numerator/ denominator
Serious Psychological Distress/Probable SMI

Psychological distress was measured using the Kessler-6 (K-6) scale, a widely used instrument for assessing clinically significant mental health problems (Kessler et al., 2003). A score of 13 or greater indicates serious psychological distress; Kessler and colleagues demonstrated that 13 is the optimal cutoff point for assessing prevalence of SMI in a population (Kessler et al., 2003). The numerator for this indicator is the number of individuals with K-6 scores at or above this threshold, and the denominator is all California adults in the sample.

Service Utilization

The CHIS asks first whether respondents have seen a primary care physician or general practitioner for "problems with your mental health, emotions, nerves, or your use of alcohol or drugs" in the past 12 months, and then asks whether they have seen any other professional—such as a counselor, psychiatrist, or social worker—for such problems. Using endorsements of these items as the numerator, we calculate the rates of seeing a primary care provider (PCP), rates of seeing a specialist, and rates of seeing either (yes to either question), with all California adults in the sample as the denominator.

Unmet Need

We identified unmet need based on information about use of services, perception of need for treatment, and psychological distress. As shown in Figure 1, individuals were considered to have unmet need if they did not receive mental health or substance use treatment and they either perceived a need for treatment or had serious psychological distress (i.e., a score of 13 or higher on the K-6, indicative of SMI). Perception of need was determined by a "yes" response to the question, "Was there ever a time during the past 12 months when you felt that you might need to see a professional because of problems with your mental health, emotions, nerves, or your use of alcohol or drugs?" This is a conservative measure of unmet need, as it does not capture individuals who received services that were inadequate in either amount or quality. The variable was constructed so that the denominator was all California adults in the sample.

Figure 1. Operational Definition of Unmet Need

Operational Definition of Unmet Need

NOTE: MH = mental health; SU = substance use.

Work Impairment

To measure self-reported severe work impairment, we calculated the proportion of respondents who said that their emotions interfered "a lot" (out of options "a lot," "some," or "not at all") with their performance at work, among those who are employed.

We also tabulated the number of respondents who endorsed missing significant amounts of work or daily activities in response to the question, "About how many days out of the past 365 days were you totally unable to work or carry out your normal activities because of your feeling nervous, depressed, or emotionally stressed?" We sought to set policy-relevant thresholds for this indicator. The California Healthy Workplace Healthy Family Act of 2014 requires employers to provide a minimum of three days sick leave per year, and under California workers' compensation rules, an individual may receive temporary disability benefits if an injury prevents the person from doing his or her usual job for more than three days; thus, more than three (four-plus) days of missed work was used as one threshold for the indicator. According to the Bureau of Labor Statistics (undated), the mean number of paid sick leave days provided annually among civilian workers who have sick leave plans is eight. Therefore, we also examined greater than eight (nine-plus) days of missed work as a more conservative threshold for work impairment.

The work impairment items were asked only of Californians who had at least mild to moderate distress on the K-6, so to report rates in the overall sample of California adults, we assumed that those who did not report even mild to moderate distress did not experience severe work impairment, and we included them in the denominator with the assumption that they would be a "no" on these indicators.

Attempted Suicide

To measure suicide attempt rates, we calculated the proportion of respondents who responded "yes" to the question, "Have you attempted suicide at any time in the past 12 months?" Since this item was asked only of those who reported having seriously thought about suicide in the past 12 months and had ever attempted suicide, to report rates in the overall sample of California adults, we included in the denominator those who were not administered this question and assumed that they would be a "no" on this indicator (i.e., those who had not thought about suicide in the past 12 months and who had never attempted suicide could be assumed to have not attempted suicide in the past 12 months).

Analysis

Descriptive statistics were computed to show average rates of the outcome measures statewide and across years, demographic groups, and regions of California. Ninety-five percent confidence intervals were computed for each estimated rate. Significant (p < 0.05) differences among the groups (e.g., younger and older Californians) were compared by examining whether either confidence interval contained the point estimate for the other group; if so, there is no significant difference between the groups, and if not, the groups are significantly different (Greenland et al., 2016).

Survey Results

Statewide Mental Health Indicators

Table 3 provides an overview of the key mental health indicators at the statewide level. Although CHIS data were collected continuously between 2011 and 2013, we briefly examined whether the mental health indicators shifted significantly over this time. There were some statistically significant differences across years, detailed in the table, but overall there was no a clear pattern of differences that were both statistically significant and sizable. Some indicators shifted in 2012 and then returned to 2011 levels in 2013. In addition, we were interested in longer-term trends in these mental health indicators, with 2011–2013 serving as a baseline. Thus, we discuss the overall results after combining samples interviewed in 2011–2013 in this study, both for simplicity and to maximize the sample size for subgroup analyses we present later. Across the years examined, almost 8 percent of the sample met the threshold for having serious psychological distress. About 12 percent of the sample had seen either a PCP or a specialist for problems with mental health or substance use in the last 12 months. However, 9 percent of the sample had unmet need—i.e., these respondents did not see a provider, but they either perceived a need for treatment or had a high level of psychological distress or probable SMI. About 4 percent self-reported that their mental health problems severely impaired their performance at work; 9 percent missed four or more days of work and 7 percent missed 9 or more days because of a mental health problem. About a quarter of a percent (0.23 percent) reported attempting suicide in the past 12 months.

Table 3. Statewide Mental Health Indicators (% Yes)

Measure 2011–2013 Pooled 2011 2012 2013
Serious distress (K-6 ≥ 13) 3.60 3.49 (3.09, 3.88) 3.46 (2.99, 3.92) 3.84 (3.29, 4.39)
Saw PCP for mental health or substance usea 7.21 7.11 (6.60, 7.61) 6.67 (6.13, 7.21) 7.84* (7.08, 8.60)
Saw specialist for mental health or substance use 9.09 9.20 (8.63, 9.78) 8.74 (8.11, 9.37) 9.34 (8.61, 10.07)
Saw PCP or specialist for mental health or substance usea 12.35 12.45 (11.81, 13.09) 11.81 (11.09, 12.53) 12.80* (11.92, 13.67)
Unmet need 8.96 8.95 (8.26, 9.65) 8.50 (7.77, 9. 23) 9.41 (8.47, 10.36)
Severe work impairmentb 4.42 4.02 (3.44, 4.59) 4.31 (3.85, 4.77) 4.92* (4.21, 5.63)
Missed 4+ days of workc 8.61 8.10 (7.48, 8.72) 8.36 (7.74, 8.99) 9.33* (8.49, 10.17)
Missed 9+ days of workd 7.04 6.54 (6.04, 7.04) 6.79 (6.24, 7.34) 7.77* (7.03, 8.51)
Attempted suicide 0.23 0.16 (0.08, 0.24) 0.28 (0.13, 0.42) 0.26 (0.15, 0.38)

NOTES: 95 percent confidence intervals are indicated in parentheses. We have indicated significant (p < 0.05) differences in the table with asterisks to indicate the groups with the higher rate.

Rates of mental health service utilization were significantly higher in 2013 than 2012 but did not significantly differ from 2011.

Rates of self-reported severe work impairment were significantly higher in 2013 than in 2011.

Rates of missing 4+ days of work were significantly higher in 2013 than in 2011 or 2012.

Rates of missing 9+ days of work were significantly higher in 2013 than in 2011.

Mental Health Indicators in Different Demographic Groups

Table 4 summarizes mental health need, service utilization, and work impairment among different demographic groups for the state as a whole. The table presents weighted percentages of California adults, with 95 percent confidence intervals shown in parentheses.

Table 4. Statewide Demographic Differences in Key Mental Health Indicators: Distress, Service Utilization, Unmet Need, Suicide Attempts, and Impairment—Percentage and Confidence Interval

% Serious Distress (K-6 ≥ 13) % Saw PCP or Specialist % Unmet Need % Attempted Suicide % Severe Work Impairment % Missed 4+ Days of Work/ Daily Activities % Missed 9+ Days of Work/ Daily Activities
Statewide 3.60 (3.32, 3.87) 12.35 (11.92, 12.79) 8.96 (8.50, 9.41) 0.23 (0.17, 0.30) 4.42 (4.08, 4.75) 8.61 (8.20, 9.01) 7.04 (6.69, 7.39)
Gender
Male 3.12 (2.72, 3.52) 9.68 (9.12, 10.25) 8.31 (7.66, 8.96) 0.25 (0.14, 0.36) 3.84 (3.34, 4.35) 7.03 (6.47, 7.59) 5.72 (5.23, 6.22)
Female 4.05* (3.67, 4.44) 14.90* (14.25, 15.55) 9.57* (8.94, 10.21) 0.22 (0.13, 0.30) 5.00* (4.49, 5.51) 10.11* (9.50, 10.71) 8.29* (7.77, 8.81)
Race/ethnicitya
White 2.93 (2.60, 3.26) 15.35 (14.68, 16.03) 8.21 (7.62, 8.80) 0.18 (0.11, 0.25) 4.64 (4.14, 5.13) 7.89 (7.34, 8.45) 6.58 (6.09, 7.07)
Latino 4.52* (3.97, 5.06) 10.60* (9.73, 11.47) 9.94* (9.07, 10.81) 0.33 (0.17, 0.50) 4.46 (3.85, 5.06) 9.44* (8.70, 10.18) 7.45* (6.81, 8.09)
Asian 2.10* (1.53, 2.67) 5.89* (4.88, 6.91) 7.10 (5.88, 8.32) 0.07* (0.00, 0.14) 3.04* (2.21, 3.87) 6.05* (5.07, 7.04) 4.56* (3.69, 5.43)
Black 5.39* (3.89, 6.90) 13.38 (11.39, 15.37) 11.31* (9.22, 13.40) 0.41 (0.07, 0.75) 4.51 (2.95, 6.08) 11.95* (9.96, 13.94) 10.61* (8.65, 12.57)
Age
18–24 years old 2.77 (2.17, 3.37) 12.11 (10.86, 13.37) 11.96* (10.62, 13.30) 0.45 (0.20, 0.70) 5.76* (4.87, 6.66) 8.82 (7.72, 9.92) 6.78 (5.84, 7.71)
25–64 years old 4.06* (3.73, 4.40) 13.60* (13.06, 14.14) 9.47 (8.92, 10.03) 0.23 (0.15, 0.31) 4.39 (4.01, 4.77) 9.59 (9.07, 10.11) 7.87* (7.43, 8.31)

NOTES: 95 percent confidence intervals are indicated in parentheses. Asterisks indicate a statistically significant (p < 0.05) difference between demographic groups (i.e., gender, race/ethnicity, age).

White is used as the comparison group.

Gender Differences

Men and women significantly differed in the mental health indicators, with women having higher rates of serious psychological distress (about 4 percent of women versus 3 percent of men; see Figure 2) but also higher rates of mental health or substance use service utilization, with 15 percent of women seeing a provider for a mental health problem, as compared with 10 percent of men (Figure 3). Despite their higher levels of service utilization, women still had higher levels of unmet need for mental health treatment; among all women, 10 percent needed mental health services but did not get any services at all, as compared with about 8 percent of men (Figure 4). Women were also more impaired by mental health issues; 5 percent self-reported severe impairment at work as compared with about 4 percent of men (Figure 5) and were more likely to miss significant amounts of work or other daily activities because of a mental health problem (Figure 6). We found that 10 percent of women reported missing four or more days of work because of a mental health concern, as compared with 7 percent of men, and 8 percent of women reported missing nine or more work days, as compared with about 6 percent of men.

Figure 2. California Women Have Higher Rates of Serious Psychological Distress Than Men Do

California Women Have Higher Rates of Serious Psychological Distress Than Men Do

Figure 3. California Women Have Higher Rates of Mental Health or Substance Use Service Utilization Than Men Do

California Women Have Higher Rates of Mental Health or Substance Use Service Utilization Than Men Do

Figure 4. California Women Have Higher Rates of Unmet Need for Mental Health Treatment Than Men Do

California Women Have Higher Rates of Unmet Need for Mental Health Treatment Than Men Do

Figure 5. California Women Have Higher Rates of Self-Reported Severe Work Impairment Because of Mental Health Than Men Do

California Women Have Higher Rates of Self-Reported Severe Work Impairment Because of Mental Health Than Men Do

Figure 6. California Women Were More Likely to Be Unable to Work or Carry Out Normal Activities for a Significant Number of Days (in a 12-Month Period) Because of Mental Health Problems, Compared with Men

California Women Were More Likely to Be Unable to Work or Carry Out Normal Activities for a Significant Number of Days (in a 12-Month Period) Because of Mental Health Problems, Compared with Men
Racial/Ethnic Differences

Diverse racial/ethnic groups were compared with white Californians; we did not examine differences among different racial/ethnic minority groups. Black and Latino Californians had significantly higher rates of serious psychological distress (approximately 5 percent) than did white Californians (3 percent), while Asian Californians had a lower rate of serious distress than did whites (2 percent), as illustrated in Figure 7. Only 11 percent of Latino Californians and just 6 percent of Asian Californians reported having seen a PCP or mental health specialist for a mental health or substance use problem, which was significantly lower than the 15 percent of whites who reported mental health service utilization in the past year (see Figure 8). Rates of unmet need (i.e., needing mental health or substance use services but not getting them) were higher among Latino Californians and, especially, black Californians, as compared with white Californians; 10 percent of Latino and 11 percent of black Californians had unmet mental health need, as compared with 8 percent of white Californians (Figure 9).

Figure 7. Black and Latino Californians Exhibited Higher Rates of Serious Psychological Distress Than Whites Did

Black and Latino Californians Exhibited Higher Rates of Serious Psychological Distress Than Whites Did

NOTE: Asterisk indicates a statistically significant different (p < 0.05) from white Californians.

Figure 8. Latino Californians and Asian Californians Had Lower Mental Health or Substance Use Service Utilization Than Whites Did

Latino Californians and Asian Californians Had Lower Mental Health or Substance Use Service Utilization Than Whites Did

NOTE: Asterisks indicate a statistically significant difference (p < 0.05) from white Californians.

Figure 9. Latino and Black Californians Had Higher Rates of Unmet Need for Mental Health Services

Latino and Black Californians Had Higher Rates of Unmet Need for Mental Health Services

NOTE: Asterisks indicate a statistically significant difference (p < 0.05) from white Californians.

Rates of suicide attempts were similar among different racial/ethnic groups, with the exception of Asian Californians, who had significantly lower rates of suicide attempts than did white Californians—0.07 percent versus 0.18 percent, respectively (Figure 10).

Figure 10. Asian Californians Had Lower Rates of Suicide Attempts

Asian Californians Had Lower Rates of Suicide Attempts

NOTE: Asterisk indicates a statistically significant different (p < 0.05) from white Californians.

Only 3 percent of Asian Californians reported severe work impairment because of mental health concerns, a rate that is significantly less than the 5 percent of white Californians who self-reported severe work impairment (Figure 11). Asian Californians were less likely than white Californians to miss a significant number of work or daily activities days because of feeling nervous, depressed, or emotionally stressed, whether a threshold of four or nine days per year was used. Conversely, Latino and, especially, black Californians were more likely than white Californians to miss a significant number of days of work or other daily activities because of mental health concerns (Figure 12). At the four-day threshold, rates of missed work were 12 percent among black Californians, 9 percent among Latino Californians, 8 percent among white Californians, and just 6 percent among Asian Californians.

Figure 11. Asian Californians Self-Reported Lower Rates of Severe Work Impairment Than Whites Did

Asian Californians Self-Reported Lower Rates of Severe Work Impairment Than Whites Did

NOTE: Asterisk indicates a statistically significant different (p < 0.05) from white Californians.

Figure 12. Asian Californians Were Less Likely to Miss a Significant Number of Work or Daily Activity Days Because of Mental Health; Latino and Black Californians Were More Likely to Miss Work or Daily Activities

Asian Californians Were Less Likely to Miss a Significant Number of Work or Daily Activity Days Because of Mental Health; Latino and Black Californians Were More Likely to Miss Work or Daily Activities

NOTE: Asterisks indicate a statistically significant difference (p < 0.05) from white Californians.

Age Differences

We examined differences in key mental health indicators between young adults ages 18–24 and adults ages 25–64. We found that young adults had significantly lower rates of serious distress (3 percent among young adults, compared with 4 percent among other adults; see Figure 13), as well as lower rates of mental health service utilization (12 percent among young adults, compared with 14 percent among other adults; see Figure 14). Consistent with their lower rates of service utilization, younger adults had higher rates of unmet need for mental health or substance use services (12 percent, compared with 9 percent among other adults; see Figure 15) and were more likely to report severe impairment in work and daily activities because of mental health concerns (6 percent of young adults, compared with 4 percent of other adults; see Figure 16). Despite self-reporting higher rates of severe work impairment, younger adults also reported lower rates of missing work because of a mental health concern; about 7 percent missed nine or more days, compared with 8 percent of other adults (see Figure 17).

Figure 13. Young Adults Had Lower Rates of Serious Psychological Distress

Young Adults Had Lower Rates of Serious Psychological Distress

Figure 14. Young Adults Had Lower Rates of Mental Health or Substance Use Service Utilization

Young Adults Had Lower Rates of Mental Health or Substance Use Service Utilization

Figure 15. Young Adults Had Higher Rates of Unmet Need for Mental Health or Substance Use Services

Young Adults Had Higher Rates of Unmet Need for Mental Health or Substance Use Services

Figure 16. Younger Adults Endorsed Higher Rates of Severe Work Impairment Because of Mental Health

Younger Adults Endorsed Higher Rates of Severe Work Impairment Because of Mental Health

Figure 17. Younger Adults Were Less Likely to Miss a Significant Number of Work or Daily Activity Days Because of Mental Health

Younger Adults Were Less Likely to Miss a Significant Number of Work or Daily Activity Days Because of Mental Health

Mental Health Indicators by Region and County

We examined CHIS mental health indicators in the California mental health regions and the counties that compose those regions. CalMHSA has identified five regions of California for program planning purposes: the Superior region (northernmost region), the Bay Area, the Central region, the Southern region (Southern California, except Los Angeles), and the Los Angeles region. Table 5 presents the counties that compose each CalMHSA region and summarizes how the mental health indicators vary between regions and counties. Only regions will be discussed in the text below. Results are not reported when the denominator (i.e., total number of respondents) for an item is fewer than 100 or when the number of individuals in any single respondent category is fewer than three. County-level results are consistently not reported for the suicide-attempt variable, given that very few counties had a large enough sample size to make the rate reliable.

Table 5. Mental Health Indicators by California Region and County: Percentages and Confidence Intervals for Serious Distress, Service Utilization, Unmet Need, Suicide Attempts, and Impairment

Location % Serious Distress (K-6 ≥ 13)a % Saw PCPb % Saw Specialistc % Saw PCP or Specialistd % Unmet Neede % Attempted Suicidef % Severe Work Impairment % Missed 4+ Days of Workg % Missed 9+ Days of Workh
Superior 4.64 (3.69, 5.60) 8.82 (7.70, 9.95) 9.40 (8.20, 10.60) 13.97 (12.61, 15.34) 8.76 (7.38, 10.13) 0.14 (0.01, 0.27) 4.56 (3.56, 5.57) 9.20 (8.05, 10.35) 7.72 (6.62, 8.81)
Butte 6.77 (3.70, 9.84) 9.34 (6.42, 12.25) 9.94 (7.14, 12.73) 14.62 (11.23, 18.01) 10.71 (5.86, 15.55) 5.61 (2.46, 8.76) 10.00 (6.69, 13.31) 8.73 (5.59, 11.87)
Del Norte / Siskiyou / Lassen / Trinity / Modoc / Plumas / Sierra 3.40 (1.33, 5.47) 7.94 (4.54, 11.34) 6.83 (3.67, 9.99) 11.72 (7.65, 15.80) 5.14 (2.82, 7.46) 1.92 (0.37, 3.47) 5.63 (3.51, 7.74) 5.17 (3.05, 7.30)
Humboldt 3.71 (0.24, 7.19) 11.09 (7.04, 15.15) 12.96 (9.94, 15.99) 19.86 (15.34, 24.37) 10.65 (6.43, 14.86) 4.09 (1.82, 6.35) 9.25 (5.20, 13.29) 7.40 (3.65, 11.15)
Lake 4.86 (2.02, 7.70) 10.40 (5.82, 14.99) 9.22 (4.34, 14.10) 13.37 (8.37, 18.37) 5.53 (2.68, 8.39) 5.46 (1.66, 9.25) 9.03 (5.06, 12.99) 5.57 (3.22, 7.91)
Mendocino 2.59 (0.88, 4.30) 7.04 (4.15, 9.92) 6.73 (3.85, 9.60) 10.67 (7.20, 14.13) 11.98 (7.90, 16.06) 5.16 (1.84, 8.47) 8.29 (5.50, 11.09) 6.54 (4.15, 8.93)
Nevada 4.44 (1.39, 7.48) 8.20 (5.35, 11.05) 11.84 (7.97, 15.72) 15.35 (11.27, 19.44) 6.69 (3.64, 9.74) 5.11 (1.85, 8.37) 10.14 (6.72, 13.56) 8.15 (5.02, 11.28)
Shasta 5.88 (3.30, 8.45) 7.67 (5.40, 9.95) 9.21 (6.16, 12.27) 12.88 (9.42, 16.34) 8.88 (5.55, 12.21) 4.91 (2.45, 7.37) 10.20 (6.98, 13.43) 8.68 (5.72, 11.64)
Tehama / Glenn / Colusa 2.85 (1.03, 4.66) 9.35 (5.41, 13.28) 7.96 (4.32, 11.61) 12.50 (8.06, 16.94) 8.79 (4.87, 12.71) 4.30 (0.85, 7.76) 10.80 (6.46, 15.13) 10.13 (5.85, 14.41)
Bay Area 2.98 (2.47, 3.50) 7.21 (6.48, 7.93) 10.84 (9.97, 11.71) 13.78 (12.84, 14.73) 9.20 (8.37, 10.03) 0.10 (0.03, 0.16) 4.78 (4.10, 5.45) 7.96 (4.15, 8.77) 6.12 (5.40, 6.85)
Alameda 1.97 (1.09, 2.85) 6.53 (4.82, 8.25) 11.74 (9.44, 14.04) 14.48 (11.97, 16.99) 8.46 (6.61, 10.31) 5.41 (3.59, 7.23) 8.68 (6.57, 10.80) 7.18 (5.20, 9.16)
Contra Costa 3.81 (2.10, 5.53) 7.76 (5.50, 10.03) 10.94 (8.39, 13.48) 13.70 (11.01, 16.39) 8.82 (6.40, 11.24) 4.10 (2.12, 6.09) 7.38 (5.13, 9.64) 6.16 (4.07, 8.26)
Marin 2.30 (0.57, 4.03) 4.51 (2.35, 6.67) 15.06 (10.05, 20.07) 17.64 (12.45, 22.84) 6.97 (3.51, 10.43) 4.39 (1.78, 7.01) 7.11 (3.86, 10.37) 4.10 (2.20, 6.00)
Monterey 4.34 (2.43, 6.25) 7.39 (4.81, 9.96) 8.67 (5.67, 11.67) 12.33 (9.05, 15.6) 9.73 (6.79, 12.67) 5.36 (2.54, 8.18) 9.92 (6.77, 13.07) 6.71 (4.23, 9.20)
Napa 3.10 (0.55, 5.66) 6.96 (3.30, 10.62) 7.96 (4.81, 11.11) 11.14 (6.98, 15.29) 9.87 (5.15, 14.59) 6.35 (1.84, 10.86) 7.54 (3.75, 11.32) 6.21 (2.64, 9.79)
San Benito 1.26 (0.00, 2.59) 4.90 (1.99, 7.82) 4.64 (1.51, 7.76) 7.61 (3.56, 11.67) 12.19 (5.15, 19.24) 2.02 (0.00, 4.14) 5.90 (2.46, 9.35) 4.60 (1.47, 7.73)
San Francisco 4.04 (1.86, 6.22) 10.12 (6.86, 13.38) 13.72 (10.50, 16.95) 17.54 (13.84, 21.25) 13.60 (9.99, 17.21) 6.31 (3.37, 9.25) 9.46 (6.25, 12.67) 7.67 (4.69, 10.64)
San Mateo 2.31 (0.50, 4.12) 5.61 (3.18, 8.04) 9.65 (6.69, 12.61) 11.70 (8.54, 14.87) 8.58 (5.22, 11.93) 3.06 (1.50, 4.62) 6.91 (3.91, 9.92) 3.90 (1.94, 5.86)
Santa Clara 2.75 (1.73, 3.77) 6.04 (4.59, 7.49) 8.11 (6.45, 9.77) 10.82 (8.93, 12.72) 8.25 (6.43, 10.08) 4.05 (2.66, 5.44) 7.21 (5.51, 8.91) 5.53 (4.08, 6.98)
Santa Cruz 3.14 (1.05, 5.24) 7.77 (4.51, 11.03) 15.38 (10.85, 19.91) 17.53 (12.93, 22.12) 11.18 (7.10, 15.25) 7.42 (3.60, 11.24) 9.76 (6.22, 13.31) 6.30 (3.66, 8.93)
Solano 2.57 (1.15, 3.99) 9.06 (5.54, 12.59) 11.12 (7.51, 14.73) 14.63 (10.43, 18.84) 8.97 (6.06, 11.88) 4.25 (1.99, 6.50) 7.53 (4.80, 10.26) 6.43 (3.93, 8.93)
Sonoma 3.95 (1.60, 6.29) 9.09 (5.98, 12.20) 12.35 (8.83, 15.86) 16.36 (12.57, 20.16) 7.34 (4.76, 9.91) 5.23 (2.68, 7.77) 7.01 (4.05, 9.97) 5.84 (3.05, 8.62)
Central 3.63 (3.05, 4.21) 7.51 (6.57, 8.45) 7.88 (6.99, 8.77) 11.81 (10.75, 12.88) 8.20 (7.28, 9.12) 0.35 (0.10, 0.60) 4.01 (3.23, 4.79) 8.80 (7.82, 9.78) 7.43 (6.57, 8.29)
El Dorado 3.17 (1.00, 5.33) 5.82 (3.95, 7.69) 7.86 (5.21, 10.50) 11.03 (7.98, 14.08) 5.79 (2.58, 9.00) 1.92 (0.75, 3.10) 7.30 (4.15, 10.45) 6.91 (3.81, 10.02)
Fresno 3.77 (2.24, 5.30) 8.26 (5.07, 11.44) 8.56 (6.11, 11.01) 12.39 (8.9, 15.87) 9.24 (6.51, 11.98) 3.91 (1.68, 6.14) 11.06 (7.80, 14.32) 8.36 (5.80, 10.91)
Kings 6.65 (3.13, 10.17) 9.06 (3.39, 14.72) 8.60 (2.25, 14.95) 13.23 (6.82, 19.65) 6.08 (2.53, 9.63) 4.51 (1.41, 7.61) 8.72 (4.61, 12.83) 8.49 (4.40, 12.58)
Madera 9.14 (4.36, 13.92) 5.39 (2.50, 8.28) 7.71 (3.77, 11.65) 9.85 (5.73, 13.97) 15.69 (9.42, 21.95) 4.19 (0.27, 8.11) 13.22 (7.71, 18.72) 12.92 (7.42, 18.42)
Merced 3.62 (1.67, 5.58) 4.91 (2.60, 7.22) 4.61 (2.95, 6.27) 7.23 (4.73, 9.73) 8.67 (5.02, 12.32) 1.73 (0.33, 3.13) 5.60 (2.83, 8.37) 5.38 (2.62, 8.14)
Placer 2.79 (0.47, 5.12) 7.84 (4.21, 11.47) 10.10 (6.26, 13.93) 15.08 (10.30, 19.86) 7.52 (4.12, 10.91) 2.11 (0.70, 3.53) 5.75 (3.02, 8.49) 4.84 (2.18, 7.49)
Sacramento 2.89 (1.81, 3.96) 7.09 (4.99, 9.19) 8.53 (6.49, 10.57) 11.78 (9.35, 14.21) 8.44 (6.60, 10.28) 4.57 (2.75, 6.39) 7.49 (5.56, 9.43) 6.68 (4.85, 8.50)
San Joaquin 3.89 (1.75, 6.02) 9.16 (6.04, 12.27) 6.68 (3.97, 9.39) 12.25 (9.00, 15.50) 8.55 (5.52, 11.59) 6.29 (3.33, 9.26) 11.08 (7.67, 14.49) 8.79 (5.77, 11.82)
Stanislaus 1.71 (0.45, 2.97) 5.75 (3.25, 8.24) 4.84 (2.70, 6.97) 7.98 (5.24, 10.72) 3.74 (2.05, 5.43) 1.55 (0.40, 2.71) 6.67 (3.85, 9.48) 5.81 (3.13, 8.48)
Sutter 5.54 (2.73, 8.36) 9.96 (6.55, 13.37) 9.76 (5.94, 13.57) 15.70 (11.21, 20.20) 7.80 (4.14, 11.45) 7.17 (2.78, 11.55) 13.76 (8.90, 18.63) 11.29 (6.76, 15.82)
Tulare 5.75 (3.15, 8.35) 5.94 (3.45, 8.44) 6.92 (3.87, 9.96) 10.13 (6.54, 13.72) 10.05 (6.58, 13.53) 4.25 (1.66, 6.84) 9.56 (6.22, 12.89) 8.33 (5.28, 11.38)
Tuolumne / Calaveras / Amador / Inyo / Mariposa / Mono / Alpine 3.16 (1.54, 4.78) 13.16 (8.16, 18.17) 8.96 (5.48, 12.43) 16.74 (11.52, 21.95) 7.47 (3.86, 11.08) 8.05 (2.79, 13.31) 12.06 (7.39, 16.73) 10.02 (6.11, 13.92)
Yolo 0.93 (0.20, 1.67) 6.87 (3.44, 10.30) 11.49 (7.19, 15.78) 14.83 (10.08, 19.58) 6.71 (3.89, 9.52) 1.79 (0.61, 2.98) 5.60 (2.54, 8.67) 4.16 (1.35, 6.97)
Yuba 8.39 (4.45, 12.33) 9.21 (5.26, 13.17) 6.97 (3.59, 10.36) 12.52 (8.05, 17.00) 8.71 (5.11, 12.31) 2.29 (0.53, 4.05) 11.51 (7.17, 15.85) 9.17 (5.58, 12.76)
Southern 3.57 (3.06, 4.08) 7.47 (6.78, 8.16) 8.78 (8.11, 9.45) 12.36 (11.54, 13.17) 9.04 (8.17, 9.91) 0.27 (0.14, 0.39) 4.38 (3.77, 5.00) 8.24 (7.51, 8.97) 6.85 (6.21, 7.49)
Imperial 2.94 (1.55, 4.34) 3.76 (2.05, 5.47) 4.04 (2.33, 5.76) 5.26 (3.37, 7.15) 10.25 (5.97, 14.53) 1.61 (0.35, 2.87) 12.09 (5.95, 18.24) 10.48 (4.60, 16.35)
Kern 7.12 (3.46, 10.78) 11.08 (6.59, 15.58) 11.02 (7.07, 14.97) 15.80 (11.02, 20.58) 11.38 (7.36, 15.40) 5.43 (2.21, 8.65) 12.43 (8.17, 16.69) 11.53 (7.39, 15.66)
Orange 2.89 (1.82, 3.96) 6.53 (5.36, 7.70) 8.63 (7.31, 9.96) 11.51 (9.95, 13.06) 7.99 (6.41, 9.58) 4.34 (2.90, 5.79) 6.19 (4.89, 7.49) 4.56 (3.48, 5.63)
Riverside 4.74 (3.37, 6.11) 8.67 (6.55, 10.79) 8.16 (6.37, 9.96) 12.94 (10.56, 15.31) 9.43 (7.31, 11.54) 4.29 (2.68, 5.89) 8.70 (7.00, 10.39) 7.50 (5.90, 9.10)
San Bernardino 2.99 (2.14, 3.84) 7.80 (5.62, 9.97) 7.26 (5.32, 9.21) 11.73 (9.29, 14.17) 9.13 (6.96, 11.30) 4.58 (2.78, 6.39) 9.73 (7.64, 11.82) 7.88 (6.07, 9.69)
San Diego 3.02 (2.20, 3.85) 7.02 (5.81, 8.23) 9.54 (8.32, 10.76) 12.55 (11.14, 13.95) 9.18 (7.76, 10.60) 4.58 (3.35, 5.80) 7.84 (6.62, 9.07) 6.70 (5.59 7.81)
San Luis Obispo 2.43 (0.86, 4.00) 7.63 (4.69, 10.57) 11.84 (7.45, 16.23) 16.96 (12.55, 21.36) 4.54 (2.11, 6.98) 3.18 (1.18, 5.19) 9.34 (5.52, 13.16) 7.62 (4.19, 11.04)
Santa Barbara 2.56 (0.99, 4.13) 7.49 (4.88, 10.11) 8.41 (5.71, 11.12) 12.45 (9.02, 15.88) 8.67 (5.18, 12.16) 6.05 (3.14, 8.95) 8.32 (5.15, 11.48) 7.66 (4.69, 10.63)
Ventura 4.43 (2.39, 6.47) 6.27 (3.88, 8.66) 9.59 (6.85, 12.34) 11.45 (8.62, 14.28) 10.61 (7.49, 13.73) 2.74 (1.28, 4.20) 7.95 (5.20, 10.71) 6.46 (3.95, 8.97)
Los Angeles 3.99 (3.44, 4.55) 6.53 (5.79, 7.27) 8.70 (7.98, 9.42) 11.29 (10.45, 12.14) 9.09 (8.25, 9.93) 0.25 (0.09, 0.40) 4.38 (3.66, 5.09) 9.43 (8.59, 10.27) 7.74 (6.98, 8.50)

NOTES: 95 percent confidence intervals are indicated in parentheses. Because the number of affirmative responses for suicide attempts is too low to be reportable for most counties, suicide attempts are systematically not reported for any counties. All five regions were compared with each other, and significant (p < 0.05) differences are described below.

The Superior region had higher levels of serious distress than the Bay Area, the Central region, and the Southern region. The Bay Area had lower levels of serious distress than all other regions.

Rates of seeing a PCP for mental health were significantly higher in the Superior region than in each of the other regions. Rates of seeing a PCP for mental health were lower in the Los Angeles region than in the Central and Southern regions.

Specialist service utilization was higher in the Bay Area than in each of the other regions. Specialist service utilization was lower in the Central region than in the Superior and Southern regions.

Rates of any mental health service utilization (PCP or specialist) were higher in the Bay Area and the Superior region than in the Central, Southern, or Los Angeles regions.

Rates of unmet need were higher in the Bay Area than in the Central region.

Rates of attempted suicide were higher in the Southern region than in the Bay Area.

Rates of missing 4+ days of work because of mental health were higher in the Los Angeles region than in the Southern region.

Rates of missing 9+ days of work because of mental health were higher in Los Angeles region than in the Bay Area and the Central region. Rates of missed work were also lower in the Bay Area than in the Superior and Central regions (in addition to the Los Angeles region).

There were a number of statistically significant (p < 0.05) differences between regions. Regional rates of serious distress ranged from 3 to 5 percent; the Superior region's 5 percent rate of serious psychological distress was significantly higher than the Bay Area's, Central region's, or Southern region's, where rates of serious distress were 3–4 percent (see Figure 18). Indeed, the Bay Area's 3 percent rate of serious distress was significantly lower than all other regions.

Figure 18. Levels of Serious Distress Were Relatively High in the Superior Region and Relatively Low in the Bay Area

Levels of Serious Distress Were Relatively High in the Superior Region and Relatively Low in the Bay Area

Further, there were some regional differences in mental health or substance use service utilization. We provide the results for PCPs and specialists separately for the regional data, because the patterns of findings were different for the different kinds of providers (this was not true when we examined demographic differences, thus we reported results for PCP and specialist together). Rates of PCP mental health service utilization ranged from 6.5 to 9 percent among the regions; the Superior region's 9 percent rate of PCP mental health service utilization was significantly higher than each of the other regions, and Los Angeles' 6.5 percent rate was significantly lower than the Central and Southern regions where PCP mental health service utilization was 7.5 percent (Figure 19). At 11 percent, the rate of seeing a specialist for behavioral health care was higher in the Bay Area than in every other region, where rates ranged from 8 to 9 percent. The Central region's 8 percent rate of specialist service utilization was significantly lower than the Superior and Southern regions' 9 percent rates. When we examined the rates of seeing either a PCP or a specialist, mental health or substance use service utilization rates were significantly higher in the Bay Area and the Superior region than in the Central, Southern, and Los Angeles regions.

Figure 19. Regional Differences in Mental Health or Substance Use Service Utilization: Overall Service Utilization Rates Were Higher in the Bay Area and the Superior Region Than in Other Regions

Regional Differences in Mental Health or Substance Use Service Utilization: Overall Service Utilization Rates Were Higher in the Bay Area and the Superior Region Than in Other Regions

Rates of unmet need were 1 percent higher in the Bay Area than in the Central region and ranged from 8 to 9 percent across all the regions (Figure 20). It is difficult to detect statistically significant differences in rates of suicide attempts, because of their low incidence, but one statistically significant difference emerged: Rates of attempted suicide were higher in the Southern region (0.27 percent) than in the Bay Area (0.10 percent), which had the lowest rate in the state (Figure 21). The highest suicide attempt rate was 0.35 percent, found in the Central region; however, statistically significant differences could not be detected between the Central region and any other region.

Figure 20. Rates of Unmet Need for Mental Health or Substance Use Services Were Higher in the Bay Area Than in the Central Region

Rates of Unmet Need for Mental Health or Substance Use Services Were Higher in the Bay Area Than in the Central Region

Figure 21. Rates of Suicide Attempts Were Higher in the Southern Region Than in the Bay Area

Rates of Suicide Attempts Were Higher in the Southern Region Than in the Bay Area

Finally, there were also regional differences in rates of missing a significant number of days of work or daily activities because of mental health issues, as shown in Figure 22. Rates of missing four-plus days of work because of mental health were higher in the Los Angeles region (9 percent) than in the Southern region (8 percent) and ranged from 8 to 9 percent across all regions. Rates of missing nine-plus days of work because of mental health ranged from 6 percent to 8 percent and were higher in the Los Angeles region (8 percent) than in the Bay Area (6 percent) and the Central (7 percent) region. Rates of missed work were also lower in the Bay Area, compared with the Superior (8 percent) and Central regions (in addition to Los Angeles).

Figure 22. There Are Regional Differences in Rates of Missing Work Because of Mental Health Problems

There Are Regional Differences in Rates of Missing Work Because of Mental Health Problems

Discussion

Population surveillance is essential for understanding public health needs, tracking how they change over time, designing programs and policies, evaluating their impact, and in turn guiding policy and programmatic decisionmaking (see, e.g., Bonnie et al., 1999). We used the CHIS, a large-scale survey measuring the health of Californians, to examine some key mental health indicators among adults in the state.

The CHIS is an important public health surveillance survey for the state of California because the survey draws large, representative samples on an ongoing basis, which allows for tracking change over time. Another important strength of this surveillance survey is that it is designed to sample sufficient numbers of survey respondents to provide information at the county level—with the exception of some sparsely populated counties that are grouped with others in the same geographic area to allow for regional estimates. Mental health is one of the many aspects of health encompassed by the CHIS, and our purpose in this study is to illustrate the utility of the CHIS for state, regional, and county tracking of some important mental health indicators.

For the state as a whole, it is also possible to compare CHIS results on some mental health indicators with nationwide results from other ongoing national surveillance surveys. Rates of serious psychological distress in the past 30 days for the U.S. adult population, based on the NHIS, were 3.4 percent in 2011, 3.0 percent in 2012, and 3.8 percent in 2013 (Clarke, Ward, and Schiller, 2016). This is similar to the rate of 3.6 percent we observed in California during the same period. Rates of serious psychological distress in the U.S. adult population are also tracked as part of the BRFSS, where rates for U.S. adults were reported as 4.0 percent in 2007 and 3.9 percent in 2009; rates were somewhat lower for California, also based on the BRFSS (3.5 percent and 3.2 percent, respectively, for the same years). The rate of reported suicide attempts among all U.S. adults in the past year, based on the 2015 NSDUH, was 0.6 percent (Park-Lee et al., 2016; Piscopo et al., 2016), which is higher than what we found in our analysis of CHIS data for California adults (0.2 percent).

The NSDUH also includes questions about mental health service use, perceived need for help, and K-6 items to assess serious psychological distress, which can all be used to construct a measure of unmet need for mental health services that is close to, but not exactly the same as, what we defined in our CHIS analysis because questions on mental health service use and perceived need are different across the NSDUH and the CHIS. We conducted an analysis of NSDUH data to construct this similar measure of unmet need, and we estimated that 8.8 percent of U.S. adults had unmet need in 2011, 9.7 percent in 2012, and 9.3 percent in 2013—rates that are similar to our CHIS finding of 9 percent for the state over the same period.

California's Mental Health Service Act explicitly aimed to reduce disparities in the state (Scheffler and Adams, 2005); as a result, one of CalMHSA's core values is to "reduce disparities in access, utilization and outcomes by age, race, ethnicity and gender, sexual orientation, nationality and disability" (CalMHSA, undated). California's goals mirror the U.S. Department of Health and Human Services' Healthy People 2020 goal to "achieve health equity, eliminate disparities, and improve the health of all groups" (U.S. Department of Health and Human Services, 2010). Given the importance of understanding and addressing disparities at both statewide and national levels, we examined how mental health indicators varied according to gender, race/ethnicity, and age.

To begin, mental health issues seemed to more adversely affect California women, as compared with men. Women in the state had slightly higher rates of serious psychological distress than men did, and women in turn had much higher rates of mental health or substance use service utilization than men did (15 percent versus 10 percent). Our findings are consistent with national data from the NHIS, which found that women experienced higher rates of serious psychological distress than men did (Clarke et al., 2016), as well as with a broader literature that has documented that women have higher rates of internalizing disorders, such as depression and anxiety (see, e.g., Kessler, 2003). Women's increased rates of depression and related problems may be due to a variety of factors related to their gender roles and the kinds of stressors they experience (see, e.g., Nolen-Hoeksema, 2001; Shih et al., 2006).

We found that California women were more likely than men to get help for a mental health or substance use issue, which is consistent with other studies that have found that men were less willing to use mental health services than women were (see, e.g., Cook and Wang, 2010). Despite this higher rate of service utilization, California women were still somewhat more likely to have unmet need; among all California women, 10 percent needed mental health services but did not receive any services at all, as compared with 8 percent of California men. Given these somewhat higher rates of unmet need, it is not surprising that women were slightly more likely than men to self-report that their work was severely impaired because of their mental health and somewhat more likely to report higher rates of missed work because of mental health. The California Healthy Workplace Healthy Family Act of 2014 requires employers to provide a minimum of three days of sick leave per year, but 10 percent of women reported missing more than three days of work because of mental health issues (versus 7 percent of men). According to the Bureau of Labor Statistics, many employers exceed this minimum requirement; therefore, the mean number of paid sick leave days is eight rather than three—8 percent of women reported exceeding this threshold as well (versus 6 percent of men). Thus, when women report missing more days of work because of mental health than men do, this also could mean that they are at greater risk of having unpaid leave from work or even losing their jobs because of mental health problems.

We also found some key racial/ethnic differences in how Californians were faring with respect to the mental health indicators examined. Most notably, Latino and black Californians exhibited the highest mental health disparities in the state. Both groups had somewhat higher rates of serious psychological distress, compared with white Californians (5 percent in both groups versus 3 percent in whites), as well as higher rates of unmet need for mental health or substance use services (10–11 percent among these diverse groups, versus 8 percent among whites). Consistent with higher rates of unmet need, Latino and black Californians also have higher rates of missed work or other daily activities because of mental health problems. We found that 9 percent of Latinos and as many as 12 percent of black Californians reported missing more work or daily activities because of mental health than the three days of sick leave that California employers are required to provide (versus 8 percent of white Californians). This could have important repercussions for Latino and, especially, black Californians' ability to earn income and stay employed in the face of mental health problems.

Our finding of higher rates of serious psychological distress among Latino and black Californians appears to be inconsistent with national data from the NHIS, which did not detect significant differences in serious distress among different racial/ethnic groups (Clarke et al., 2016). However, the pattern of results is still similar, with both the CHIS and the NHIS finding rates of serious distress of about 3 percent in whites, while the Latino and black rates are 4 percent in the national NHIS sample, compared with 5 percent in California using the CHIS. It is possible that the results in California represent an exacerbation of a national trend, but given that the methodology used by the CHIS is not perfectly equivalent to the NHIS and other measures, we are not able to directly compare the results of California with the rest of the country.

The higher rates of serious distress we detected among black and Latino Californians are consistent with evidence that perceived discrimination and other forms of minority stress contribute to disparities in psychological health among minority groups (see, e.g., Link and Phelan, 2001; Williams and Mohammed, 2009). Black and Latino Californians' higher rates of unmet need are consistent with evidence that racial and ethnic minorities tend to have lower rates of mental health service utilization (see, e.g., Alegria et al., 2008; McGuire, 2008). These lower rates of service utilization may be due to a variety of factors, such as mistrust of the health system, concerns about providers' competence working with specific cultural groups, perceived discrimination, affordability and availability of treatment, and stigma-related concerns (see, e.g., Gary, 2005; Van Houtven et al., 2005; Whaley, 1997).

Young adults (ages 18–24) are another group of Californians not faring as well with respect to mental health indicators. Compared with adults ages 25–64, young adults had somewhat higher rates of unmet need for mental health or substance use services (12 percent versus 9 percent) and were somewhat more likely to report severe impairment in work or daily activities because of mental health concerns (6 percent versus 4 percent).

These findings are consistent with national data from the NSDUH, which reported higher rates of unmet need among younger adults (Park-Lee et al., 2016). Young adulthood is a critical developmental phase for completing education, launching careers, and forming key relationships; thus, untreated mental health problems during this transitional period may be especially problematic.

There were some regional differences in rates of serious distress and mental health or substance use service utilization, but given that the only detectable difference in unmet need was minimal (i.e., only 1 percent), the rates of service utilization may roughly correspond to levels of need in the respective regions. Some regions differed in rates of use of primary care versus specialty care, and counties and regions may want to consider whether there is a need to boost a particular kind of service utilization. We did detect some regional differences in rates of missed work because of mental health, but they were small (at most 1.5 percent).

Taken together, these findings suggest that, in an environment of limited resources, mental health program planning and policymaking in California may benefit from a focus on improving outcomes for women, Latino and black Californians, and young adults. Indeed, CalMHSA's statewide mental health PEI programs have continually focused efforts on diverse racial/ethnic groups and on young adults. In the programs' latest phase, they are continuing their emphasis on young adults and intensifying their efforts on Latino populations (see CalMHSA's website, www.calmhsa.org, for program overviews). If successful, such efforts may improve the mental health of these populations and reduce disparities.

CHIS data, in combination with other information, could provide a more comprehensive picture of mental health in California and its counties. There are various sources of California surveillance data available, and each data source provides some information but only one piece of the story regarding the mental health of California's population. For example, the Centers for Disease Control and Prevention's website provides statistics on suicide rates and emergency department visits and hospitalizations related to mental health, which can complement the limited information the CHIS provides related to serious distress and reported suicide attempts. Our previous study, Evaluating the Impact of Prevention and Early Intervention Activities on the Mental Health of California's Population (Watkins et al., 2012), provides detailed information regarding existing data sources for mental health population surveillance.

While the CHIS data have some unique strengths—including a very large sample and a sampling frame designed to provide county-level information for all but the very smallest counties, use of some well-validated measures, and administration in multiple languages—they also have some weaknesses. Most notably, because the CHIS was designed to be an overall measure of the health of Californians, not a specific measure of mental health, it is lacking some mental health measures that would be very useful for population surveillance. In particular, the CHIS does not include measures of stigma and discrimination—key indicators that reflect barriers to treatment and the environment in the state for those with mental health issues and, therefore, key targets for statewide mental health PEI initiatives. Another limitation is that, although the sample size is quite large overall, it is too small to examine demographic differences in some mental health indicators, such as reported suicide attempts, at the county level.

Over time, surveillance data can help evaluate the impact of PEI efforts. The current study presents three years of data (2011, 2012, and 2013), but even a three-year period is relatively short to see differences in mental health indicators that may change rather slowly in response to social marketing campaigns and other statewide programs focused on mental health PEI. It can take several years to see population-level changes in distal indicators of mental health; in this way, the current analysis could be considered a baseline from which to compare future data. It should also be noted that CalMHSA's implementation of statewide PEI programs took place during a period of important policy change: the Affordable Care Act increased access to behavioral health care during this time by expanding access to Medicaid and identifying mental health and substance use treatment as "essential benefits" that must be included in all health plans. Therefore, it is hard to distinguish between the impact of statewide mental health PEI programming and the impact of broader policy changes.

Given that change in population-level indicators can be observed and understood only over longer periods, we are conducting an update of this study with 2014–2015 CHIS data and plan to conduct analyses of 2016–2017 data once they are released. Ongoing analysis and reporting of mental health indicators using existing surveillance data, including the CHIS, can inform county- and state-level planning and decisions about how to invest mental health and other public health resources. Long-term tracking of mental health indicators can provide decisionmakers with valuable information about changing population needs and the extent to which policies and services designed to prevent and treat mental health conditions are having intended effects.

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The research described in this article was funded by the California Mental Health Services Authority (CalMHSA) and conducted by RAND Health.

RAND Health Quarterly is produced by the RAND Corporation. ISSN 2162-8254.