US-based indices of area-level deprivation: results from HealthCare for Communities.
In this analysis we create census-tract level indices of area deprivation for the US that parallel similar indices developed in Britain, and we determine whether these indices are related to physical and mental health outcomes. Data for the indices come from the 2000 Census Summary File Tapes and the 2001 Zip Code Business Patterns Files. These indices are then linked by census tract to cross-sectional data from the HealthCare for Communities (HCC) study, and equations are estimated using multi-level models with census-tract random effects. We find that area-level deprivation predicts poor mental and physical health outcomes, but different components of deprivation have different effects. When we measure deprivation using three factor scores that emerged from our analysis (rather than combining all measures of deprivation into a single index), we find that access to services has a more pronounced association with physical health, whereas racial composition and local language barriers are more strongly correlated with mental health. These findings suggest that grouping all variables into a single index may mask important heterogeneity in the ways in which area characteristics affect health outcomes.
Eibner
Christine
C
RAND Corporation, Arlington, VA 22202, USA. eibner@rand.org
Sturm
Roland
R
D000328:Adult; D000368:Aged; D002391:Catchment Area, Health; D019352:Censuses; D003153:Community Health Services / Q000600:supply & distribution*; D003156:Community Mental Health Services / Q000600:supply & distribution*; D003430:Cross-Sectional Studies; D005260:Female; D006297:Health Services Accessibility; D006305:Health Status Indicators; D006801:Humans; D008297:Male; D008875:Middle Aged; D011204:Poverty Areas; D012111:Residence Characteristics / Q000145:classification*; D012923:Social Class; D012959:Socioeconomic Factors; D014481:United States / Q000453:epidemiology; D035862:Vulnerable Populations / Q000523:psychology / Q000706:statistics & numerical data*