Mental well being and neighborhood socioeconomic context: Comparing measures of mental health in a multiethnic urban environment

Background: Research using multilevel models has found consistent effects of neighborhood characteristics on mental health, above and beyond individual characteristics. However, which dimensions of mental health are affected by different aspects of neighborhoods is not well understood, particularly within predominantly low income urban communities. This study compares the relationships between neighborhood income composition and two dimensions of mental health, psychological distress and psychological well being, in a multiethnic urban sample. Methods: Data were collected through the Healthy Environments Partnership, a community-based participatory research project assessing contributions of the physical and social environments to health disparities in Detroit, Michigan. US Census block group data (n=69) are linked with individual data from a stratified proportional sample survey of 919 residents of Detroit (57% African American, 20% Latino, and 23% White; median income $15-19,999). Dependent variables include two measures of psychological distress, depressive symptoms (CES-D) and depression (CIDI), and one measure of psychological well being, a single-item measure of life satisfaction. Neighborhood income composition is measured as percent poverty and percent middle income and above. We use multilevel models (HLM) to examine relationships between neighborhood income composition and each mental health measure. Results: We present frequency distributions, subgroup differences, and strengths of association between neighborhood context and each of our three indicators of mental health. We discuss similarities and differences across models, and how socioeconomic context may contribute to understanding geographic variation in specific dimensions of mental health. Finally, we discuss implications for interventions to improve the mental well being of urban residents.