Data used in the study come from The National Latino and Asian American Study (NLAAS), a 2002−2003 survey of non-institutionalized Asian and Latin American adults residing in the coterminous United States. The goal of the survey was to measure psychiatric diagnoses and mental health service usage among Asian and Latino Americans. The NLAAS is a nationally representative household sample of 4,864 individuals ages 18 and over, including 2,554 Latinos, 2,095 Asians, and 215 Whites (who were not included in this paper). NLAAS interviews were conducted in English, Spanish, Chinese (Mandarin), Tagalog and Vietnamese, based on the respondents’ language preferences. Originally, all interviews had been planned to be conducted in-person, but due to budgetary constraints, approximately 1,000 interviews were conducted by telephone. The weighted response rates for the NLAAS samples were: 73.2% for the total sample; 75.5% for the Latino Sample; and 65.6% for the Asian sample [49
]. We limit the analysis samples to 2,228 Latino respondents (1,016 males and 1,212 females) and 1,818 Asians (864 males and 954 females) between 18 and 65 years old who are not in school at the time of the survey. All models are estimated separately by gender and broad ethnic group (Latino or Asian) with techniques that acknowledge the complex survey design.5
We consider the following three, self-reported labor market outcomes as dependent variables in this analysis: (1) a dummy variable indicating whether or not the respondent is currently employed; (2) among employed individuals, the number of weeks during which the respondent was employed in the past year; and (3) among employed individuals, whether or not the respondent missed at least one day of work in the past month. The employment indicator was created from a survey question regarding the respondent's work situation “as of today.” Employed persons include respondents who work full or part time and respondents who report that they are self-employed. In the employment models, the omitted category combines individuals who are unemployed with individuals who are out of the labor force, such as homemakers, early retirees and discouraged workers. (Students and persons over 65 are excluded from the analysis samples.) In order to distinguish the effects of mental illness on unemployment and out of labor force status, we experiment with some multinomial logit models that allow for three, qualitative categories as the dependent variable (out of labor force, unemployed, with employed as the omitted category). Results from this analysis are discussed later in the paper.
The NLAAS contains detailed information on psychiatric disorders that were collected by trained, lay interviewers using the World Mental Health Survey Initiative version of the World Health Organization Composite International Diagnostic Interview (WMH-CIDI). This fully structured diagnostic instrument is based on the criteria of the Diagnostic and Statistics Manual of Mental Disorders, Version 4 (DSM-IV). The CIDI has been tested extensively for test-retest reliability and validity [50
]. The NLAAS includes prior, 12 month and 30 days diagnoses for a range of psychiatric disorders. The survey also includes scales of mental distress [51
] and psychiatric impairment [52
Our main measure of recent psychiatric disorder is a dummy variable indicating whether or not the respondent met diagnostic criteria for any psychiatric disorder in the past 12 months. Any psychiatric disorder includes the following diagnoses: (1) major depression; (2) dysthymia; (3) agoraphobia; (4) generalized anxiety disorder (GAD); (5) panic attack; (6) panic disorder; (7) social phobia; (8) alcohol abuse; (9) alcohol dependence; (10) illicit drug abuse; (11) illicit drug dependence; (12) post-traumatic stress disorder; (13) anorexia; and (3) bulimia. We also consider the effect of three broad classes of psychiatric disorders separately (any affective disorder, any anxiety disorder, any substance use disorder – see for definitions of these disorder classes), and the effects of mental distress, on labor market outcomes. To capture mental distress, we use the respondent's continuous score on the K10, a 10 question scale of non-specific psychological distress (see Kessler et al. [53
] for a description of this scale). The K10 has demonstrated, strong psychometric properties in demographic sub-samples [53
]. Because of multicollinearity between the psychiatric measures, we include each of the diagnosis and mental distress measures separately in the models.
Weighted Means and Standard Errors
Our models include a rich set of covariates that are intended to control for personal characteristics that may be correlated with both labor market outcomes and mental illness. These variables are: (1) sub-ethnicity (within the broader Latino and Asian categories); (2) age in years; (3) education (high school, at least some college, with high school dropout as the baseline); (4) marital status (married/cohabiting, widowed/divorced/separated with single as the baseline); (5) the number of children in the household; (6) whether the respondent is not English proficient; (7) immigrant; (8) US citizen; (9) a set of dummy indicators for current physical health conditions – asthma, diabetes, chronic obstructive pulmonary disease, cancer, cardiovascular conditions; and (10) the state unemployment rate in the interview year. The sub-ethnicity variables for the Latino samples are: Puerto Rican; Cuban; and Mexican, with Other Latino as the baseline. For the Asian samples, the sub-ethnicity variables are: Chinese; Vietnamese; Filipino, with Other Asian as the baseline. The identifying variables used in the bivariate probit and TSLS models are two dummy indicators of frequent religious attendance (at least weekly) and often using religious means to handle life's problems, as well as a continuous measure of the number of psychiatric disorders with onset during childhood.
As described earlier, in some models we include measures of both prior and current disorder. Prior disorder is measured by a dummy variable indicating whether the respondent met lifetime diagnostic criteria for any psychiatric disorder, but whose most recent symptoms occurred prior to the past year. Thus, this variable excludes disorders and symptoms that occurred in the past 12 months. It is important to note that in the models where both prior and recent disorder measures are included as covariates, the number of incident cases is relatively small in some cases (e.g. number of cases where a respondent without any prior disorder develops a disorder in the past 12 months). The number of incident cases was 107 for Latino females, 48 for Latino males, 38 for Asian females, and 33 for Asian males.
Observations were dropped if they had missing information on employment status (n=2), marital status (n = 2), English proficiency (n=4), immigrant (n=2), US citizen (n=7), state unemployment rate (n = 2), religious service attendance (n = 14), reliance on religious means to deal with problems (n = 4), K10 distress score (n = 1). In models of absences and labor supply, we also dropped respondents with missing information on work absences and the number of weeks worked.
Across the samples, 81 to 84 percent of males and 56 to 64 percent of females are currently employed (). In the female analysis samples, 27 to 36 percent of respondents are out of the labor force, which includes individuals who are homemakers, retired, disabled or not looking for work. Approximately 11 to 12 percent of males report being out of the labor force. Among employed respondents, the number of weeks worked in the past year ranged from about 47 to 50 weeks. In the male samples, 20 to 25 percent of respondents reported missing at least one day of work in the past month; among females, 27 to 28 percent responded missing at least one day of work in the past month.
The unemployment rate is about 8−9 percent in the female samples, and ranges from 5 to 8 percent in the male samples. The sample unemployment rates are consistent with national unemployment rates for Latinos during the time period when the NLAAS data were collected. In January 2003, the unemployment rate for Latino women age 20 and over was 8.4 percent, and the unemployment rate for Latino males age 20 and over was 7.5 percent [19
]. Nationally, the unemployment rate for Asian males was 6 percent and the unemployment rate for females was 5 percent in 2002.
Recent psychiatric conditions are relatively common in all four samples, with the highest rates among Latino females. Among Latino females, 17 percent meet diagnostic criteria for at least one psychiatric disorder in the past 12 months – a large proportion of these women are experiencing affective disorders (9 percent) and/or anxiety disorders (12 percent), but very few have a diagnosis of substance abuse or dependence (1 percent). Among Latino males, 14 percent have a 12 month DSM-IV diagnosis for at least one disorder, with 6 percent experiencing affective disorders, 7 percent having an anxiety disorder, and 5 percent having a diagnosis of substance abuse or dependence. In the Asian samples, rates of psychiatric disorders are lower (9 percent of males and 10 percent of females report any past year psychiatric disorder), but the degree of mental distress, as measured by the K10, is similar to what is experienced in the Latino samples.
All four samples consist of individuals who mainly are of working age (25 to 64 years old) because persons over 65 years old and students were excluded from the analysis. The largest ethnic group among the Latinos is the Mexican Americans; in the Asian samples, the largest ethnic group is Chinese Americans. In the Latino samples, about 42 percent of male and 43 percent of female respondents have less than a high school education (data not shown), and 59−78 percent of the Latino and Asian samples are immigrants. These characteristics are very different from those of other samples used to study psychiatric disorders and labor market outcomes. For example, in the NCS sample used by Ettner et al. (1997), only 13 percent of females and 16 percent of males had less than a high school education, and 6 to 7 percent were immigrants. Individuals who are foreign born and have less than a high school education are likely to face quite different job circumstances, and possibly different labor market consequences of mental illness, compared to American born, more educated workers.