Education, income inequality, and mortality: a multiple regression analysis.
OBJECTIVE
To test whether the relation between income inequality and mortality found in US states is because of different levels of formal education.


METHODS
Cross sectional, multiple regression analysis.


METHODS
All US states and the District of Columbia (n=51).


METHODS
US census statistics and vital statistics for the years 1989 and 1990.


METHODS
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.
Muller
Andreas
A
Department of Health Services Administration, University of Arkansas at Little Rock, 207 Ross Hall, 2801 South University Ave, Little Rock, AR 72204, USA. axmuller@ualr.edu
D000328:Adult; D000368:Aged; D003430:Cross-Sectional Studies; D004522:Educational Status; D006801:Humans; D007182:Income / Q000706:statistics & numerical data; D008875:Middle Aged; D009026:Mortality; D011203:Poverty / Q000706:statistics & numerical data*; D012044:Regression Analysis; D012307:Risk Factors; D014481:United States / Q000453:epidemiology