Colleen M Heflin1, John Iceland2. 1. Truman School of Public Affairs, University of Missouri, heflincm@missouri.edu. 2. Department of Sociology and Criminology, The Pennsylvania State University, jdi10@psu.edu.
Abstract
OBJECTIVE: Mental health disorders are of great social, economic, and policy concern. A higher incidence of major depressive disorder has been reported among those living in or near poverty. Our study examines the extent to which the relationship between income and depression is mediated by measures of material hardship. METHODS: We use measures of depression at two points in time from the longitudinal Fragile Families Survey to better discern the causal direction of the relationship between income poverty, hardship, and depression. More specifically, we use conditional logistic fixed-effect models that control for time-invariant unmeasured heterogeneity in the sample. RESULTS: We found a strong relationship between hardships and depression. The most prominent hardships were problems paying bills and phone turned off. We also found that hardship helped mediate much, though not all, of the link between poverty and depression in the conditional fixed effect logistic regression models. CONCLUSION: Our policy simulations suggest that public health efforts to reduce depression may be enhanced from efforts that focus on specific forms of material hardship.
OBJECTIVE:Mental health disorders are of great social, economic, and policy concern. A higher incidence of major depressive disorder has been reported among those living in or near poverty. Our study examines the extent to which the relationship between income and depression is mediated by measures of material hardship. METHODS: We use measures of depression at two points in time from the longitudinal Fragile Families Survey to better discern the causal direction of the relationship between income poverty, hardship, and depression. More specifically, we use conditional logistic fixed-effect models that control for time-invariant unmeasured heterogeneity in the sample. RESULTS: We found a strong relationship between hardships and depression. The most prominent hardships were problems paying bills and phone turned off. We also found that hardship helped mediate much, though not all, of the link between poverty and depression in the conditional fixed effect logistic regression models. CONCLUSION: Our policy simulations suggest that public health efforts to reduce depression may be enhanced from efforts that focus on specific forms of material hardship.
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