Sex differences on the relation between major depressive disorder and labor market outcomes: A national prospective study.

To ascertain the direction of causality and differences by sex between major depressive disorder (MDD) and labor market outcomes in the US population, we used structural equation models separately for males and females to assess prospectively the interdependency of depression and labor market outcomes at Waves 1 (2001-2002) and 2 (2004-2005) of the National Epidemiologic Survey on Alcohol and Related Conditions. Diagnosis of MDD used DSM-IV criteria. We found that MDD at Wave 1 predicted being out of the labor force for males at Wave 2 (p = 0.006) and being in the labor force at Wave 1 was associated with lower probability of MDD at Wave 2 (p = 0.049). Among males in the labor force, MDD at Wave 1 was negatively associated with employment at Wave 2 (p = 0.047), and employment at Wave 1 was negatively associated with MDD at Wave 2 (p < 0.001). For women, there was no association between MDD and labor force participation. However, among women in the labor force, MDD at Wave 1 was negatively associated with employment at Wave 2 (p = 0.013) and being employed at Wave 1 was negatively associated with MDD at Wave 2 (p < 0.0001). These results indicate that MDD and negative labor market outcomes are associated with one another at both time points, but the effects differ by sex. To reduce the economic and social burden of MDD, these differences should be considered in clinical practice, vocational rehabilitation, and in the design of social policies.

Impact of Mental Disorders on Employment and Receipt of Public Assistance: An Instrumental Variables Approach.

BACKGROUND: Unlike other disorders, much of the economic burden of mental disorders is not due to direct costs of care, but due to indirect costs such as loss of employment and the receipt of public assistance. AIMS: The goal of this paper is to estimate how having a mental disorder impacts employment outcomes, receipt of public assistance and food assistance. METHODS: We estimate the impact of having a mental disorder on employment and the receipt of public assistance using instrumental variable (IV) methods and a longitudinal dataset: National Epidemiologic Survey on Alcohol and Related Conditions. Having a mental disorder is instrumented by whether the individual has any close family members with a history of alcohol, drug or behavioral disorders. We use bivariate probit models that control for individual socio-demographic characteristics and health status variables. RESULTS: Results show that having any mental disorders is associated with a significant reduction in the probability of being employed by 0.09 (or 9 percentage points), and in the probability of being employed full-time by 0.10. For public assistance outcomes, having any mental disorders is associated with a significant increase in the probability of receiving public assistance and food assistance by 0.10 and 0.15, respectively. These estimated marginal effects using instrumental variable methods are greater than the standard probit model estimates for all outcomes, implying that the true impact of having a mental disorder is underestimated by standard models that do not employ an identifying strategy that controls for endogeneity. DISCUSSION: The relatively large marginal effects on employment and public assistance suggest that effective diagnosis and treatment of individuals with mental disorders in the workforce can have a significant impact on productivity and public assistance programs.