The relationship between primary care, income inequality, and mortality in US States, 1980-1995.

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Abstract
Objectives: This study tests the robustness of the relationships between primary care, income inequality, and population health by (1) assessing the relationship during 4 time periods—1980, 1985, 1990 and 1995; (2) examining the independent effect of components of the primary care physician supply; (3) using 2 different measures of income inequality (Robin Hood index and Gini coefficient); and (4) testing the robustness of the association by using 5-year time-lagged independent variables. Data Sources/Study Setting: Data are derived from the Compressed Mortality Files, the US Department of Commerce and the Census Bureau, the National Center for Health Statistics, the Centers for Disease Control and Prevention, and the American Medical Association Physician Master File. The unit of analysis was the 50 US states over a 15-year period. Study Design: Ecological, cross-sectional design for 4 selected years (1980, 1985, 1990, 1995), and incorporating 5-year time-lagged independent variables. The main outcome measure is age-standardized, all-cause mortality per 100,000 population in all 50 US states in all 4 time periods. Data Collection/Extraction Methods: The study used secondary data from publicly available data sets. The CDC WONDER/PC software was used to obtain mortality data and directly standardize them for age to the 1980 US population. Data used to calculate the income inequality measure came from the US census population and housing summary tapes for the years 1980 to 1995. Counts of the number of households that fell into each income interval along with the total aggregate income and the median household income were obtained for each state. The Gini coefficient for each state was calculated using software developed for this purpose. Results: In weighted multivariate regressions, both contemporaneous and time-lagged income inequality measures (Gini coefficient, Robin Hood Index) were significantly associated with all-cause mortality (P < .05 for both measures for all time periods). Contemporaneous and time-lagged primary care physician-to-population ratios were significantly associated with lower all-cause mortality (P < .05 for all 4 time periods), whereas specialty care measures were associated with higher mortality (P < .05 for all time periods, except 1990, where P < .1). Among primary care subspecialties, only family medicine was consistently associated with lower mortality (P < .01 for all time periods). Conclusions: Enhancing primary care, particularly family medicine, even in states with high levels of income inequality, could lead to lower all-cause mortality in those states.