Dataset Information

Race, Neighborhood Economic Status, Income Inequality and Mortality.

ABSTRACT: Mortality rates in the United States vary based on race, individual economic status and neighborhood. Correlations among these variables in most urban areas have limited what conclusions can be drawn from existing research. Our study employs a unique factorial design of race, sex, age and individual poverty status, measuring time to death as an objective measure of health, and including both neighborhood economic status and income inequality for a sample of middle-aged urban-dwelling adults (N = 3675). At enrollment, African American and White participants lived in 46 unique census tracts in Baltimore, Maryland, which varied in neighborhood economic status and degree of income inequality. A Cox regression model for 9-year mortality identified a three-way interaction among sex, race and individual poverty status (p = 0.03), with African American men living below poverty having the highest mortality. Neighborhood economic status, whether measured by a composite index or simply median household income, was negatively associated with overall mortality (p<0.001). Neighborhood income inequality was associated with mortality through an interaction with individual poverty status (p = 0.04). While racial and economic disparities in mortality are well known, this study suggests that several social conditions associated with health may unequally affect African American men in poverty in the United States. Beyond these individual factors are the influences of neighborhood economic status and income inequality, which may be affected by a history of residential segregation. The significant association of neighborhood economic status and income inequality with mortality beyond the synergistic combination of sex, race and individual poverty status suggests the long-term importance of small area influence on overall mortality.

SUBMITTER: Mode NA

PROVIDER: S-EPMC4865101 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Race, Neighborhood Economic Status, Income Inequality and Mortality.

Mode Nicolle A NA Evans Michele K MK Zonderman Alan B AB

PloS one 20160512 5

Mortality rates in the United States vary based on race, individual economic status and neighborhood. Correlations among these variables in most urban areas have limited what conclusions can be drawn from existing research. Our study employs a unique factorial design of race, sex, age and individual poverty status, measuring time to death as an objective measure of health, and including both neighborhood economic status and income inequality for a sample of middle-aged urban-dwelling adults (N = ...[more]

PMID: 27171406

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Project description:BackgroundObesogenic environment is important in driving obesity epidemic. Children spend large amount of their time in schools. School neighborhood environment, as well as its interaction with socioeconomic status (SES) needs to be explored to provide evidence for children obesity prevention policies.MethodsObjective anthropometric measurement, a household structured questionnaire, and school geospatial analyses were carried out on 3670 children (aged 9-12 years) of 26 schools in northeast China. Interaction between SES inter-categorical intersectionality group and school neighborhood environment was tested for the effect on children's body mass index z scores (z-BMI) and waist-hip ratio z scores (z-WHR), following formulation of SES inter-categorical intersectionality group based on household wealth, parental education, and parental occupation.ResultsSES groups formed by household wealth, parental education and parental occupation was associated with z-BMI and z-WHR for girls. Those from moderate wealth & self-employed (M&S) families had the highest adjusted z-BMI and z-WHR among all SES groups. School neighborhood environment factors interacted with SES groups in association with WHR for girls. Number of school neighborhood supermarkets and residential sites were negatively associated with z-WHR for girls from M&S families (β= -0.45 (95%CI: -0.76, -0.15) for supermarkets; β= -0.01 (95%CI: -0.03, 0.00) for residential sites). Number of school neighborhood convenience stores and public transport stops were positively associated with z-WHR for girls from M&S families (β = 0.02 (95%CI: 0.00, 0.03) for convenience stores; β = 0.23 (95%CI: 0.15, 0.31) for public transport stops). While non-significant association was found for number of vegetable stores.ConclusionGirls from moderate wealth & self-employed families may be the group susceptible to school neighborhood environment. Local policies targeted at improving the school neighborhood environment may be one avenue for reducing socioeconomic disparities in obesity especially for girls.

Project description:IntroductionHealth-income inequality has been the focus of many studies. The relationship between economic conditions and health has also been widely studied. However, not much is known about how changes in aggregate economic conditions relate to health-income inequality. Nevertheless, such knowledge would have both scientific and practical value as substantial public expenditures are used to decrease such inequalities and opportunities to do so may differ over the business cycle. For this reason we examine the effect of the Icelandic economic collapse in 2008 on health-income inequality.MethodsThe data used come from a health and lifestyle survey carried out by the Public Health Institute of Iceland in 2007 and 2009. A stratified random sample of 9,807 individuals 18-79 years old received questionnaires and a total of 42.1% answered in both years. As measures of health-income inequality, health-income concentration indices are calculated and decomposed into individual-level determinants. Self-assessed health is used as the health measure in the analyses, but three different measures of income are used: individual income, household income, and equivalized household income.ResultsIn both years there is evidence of health-income inequality favoring the better off. However, changes are apparent between years. For males health-income inequality increases after the crisis while it remains fairly stable for females or slightly decreases. The decomposition analyses show that income itself and disability constitute the most substantial determinants of inequality. The largest increases in contributions between years for males come from being a student, having low education and being obese, as well as age and income but those changes are sensitive to the income measure used.ConclusionsChanges in health and income over the business cycle can differ across socioeconomic strata, resulting in cyclicality of income-related health distributions. As substantial fiscal expenditures go to limiting the relationship between income and health, the business-cycle effect on equality, which has up until now not received much attention, needs to be considered.

Dataset Information

Race, Neighborhood Economic Status, Income Inequality and Mortality.

Publications

Race, Neighborhood Economic Status, Income Inequality and Mortality.

Similar Datasets

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