Abstract
This study measured geographic variation in depression hospitalizations and identified community-level risk factors. Depression hospitalizations were identified from the Statewide Inpatient Database. The dependent variable was specified as the indirectly standardized hospitalization rate. County-level data for 14 states were collected from federal agencies. The Bayesian spatial regression model included socio-demographic, economic, and health system characteristics as independent variables. There were 8.5 depression hospitalizations per 1,000 residents. 8.8% of counties had hospitalization rates 33% greater than the standardized rate. Significant risk factors included unemployment, poverty, physician supply, and hospital bed supply. Significant protective factors included rurality, economic dependence, and housing stress.
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