title: Aggregation and the measurement of income inequality: effects on morbidity.
abstract: This is a cross-sectional study using records from the National Health Interview Survey linked to Census geography. The sample is restricted to white males ages 25-64 in the United States from three years (1989-1991) of the National Health Interview Survey. Perceived health is used to measure morbidity. Individual covariates include income-to-needs ratio, education and occupation. Contextual level measures of income inequality, median household income and percent in poverty are constructed at the US census county and tract level. The association between inequality and morbidity is examined using logistic regression models. Income inequality is found to exert an independent adverse effect on self-rated health at the county level, controlling for individual socioeconomic status and median income or percent poverty in the county. This corresponding effect at the tract level is reduced. Median income or percent poverty and individual socioeconomic status are the dominant correlates of perceived health status at the tract level. These results suggest that the level of geographic aggregation influences the pathways through which income inequality is actualized into an individuals' morbidity risk. At higher levels of aggregation there are independent effects of income inequality, while at lower levels of aggregation, income inequality is mediated by the neighborhood consequences of income inequality and individual processes.
authors: Boston University and National Center for Health Statistics, USA.
authors: M J
authors: MJ
authors: Soobader
authors: F B
authors: FB
authors: LeClere
mesh_terms: D000328:Adult; D001294:Attitude to Health; D003430:Cross-Sectional Studies; D004522:Educational Status; D006305:Health Status Indicators; D006306:Health Surveys; D006801:Humans; D007182:Income / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D008571:Men / Q000523:psychology; D008875:Middle Aged; D009017:Morbidity; D009790:Occupations / Q000706:statistics & numerical data; D011203:Poverty / Q000706:statistics & numerical data*; D012111:Residence Characteristics / Q000706:statistics & numerical data*; D012307:Risk Factors; D014481:United States / Q000453:epidemiology; D044465:White People / Q000523:psychology / Q000706:statistics & numerical data