Education, income inequality, and mortality: a multiple regression analysis

Abstract Objective: To test whether the relation between income inequality and mortality found in US states is because of different levels of formal education. Design: Cross sectional, multiple regression analysis. Setting: All US states and the District of Columbia (n=51). Data sources: US census statistics and vital statistics for the years 1989 and 1990. Main outcome measure: Multiple regression analysis with age adjusted mortality from all causes as the dependent variable and 3 independent variables—the Gini coefficient, per capita income, and percentage of people aged ≥18 years without a high school diploma. Results: The income inequality effect disappeared when percentage of people without a high school diploma was added to the regression models. The fit of the regression significantly improved when education was added to the model. Conclusions: Lack of high school education accounts for the income inequality effect and is a powerful predictor of mortality variation among US states. What is already known on this topic Aggregate studies have shown a positive relation between income inequality and mortality and three possible explanations have been suggested (relative deprivation, absolute deprivation, and aggregation artefact) Income inequality may reflect the effects of other socioeconomic variables that are also related to mortality What this study adds Multiple regression analysis of the 50 US states and District of Columbia for 1989-90 indicates that the relation between income inequality and age adjusted mortality is due to differences in high school educational attainment: education absorbs the income inequality effect and is a more powerful predictor of variation in mortality among US states Lack of high school education seems to affect mortality by economic resource deprivation, risk of occupational injury, and learnt risk behaviour. It may also measure the lifetime, cumulative effect of adverse socioeconomic conditions

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