The Importance of Place in Predicting Differences in Depressive Symptoms

Abstract

This study is concerned with understanding how predictors of depressive symptoms vary across place. The cross-sectional study utilized Southern Community Cohort Study (SCCS) and US census data to create Hierarchical Linear Models (HLM) with two levels. Level 1 was individual differences and level 2 was place. The HLM models evaluated levels of depressive symptoms indicated by a composite CES-D score. The intercepts as outcomes model was significant for two place factors, Stable Suburban and Black Single Mother Headed Households. The slopes as outcomes model was significant for Black, Social Support, Unemployed, SleepLinear, SleepQuad, and Smoke Now. Results from this study indicate that depressive symptoms do vary among place and certain individual characteristics within places are more important as predictors of higher depressive symptoms.