Quantifying and explaining variation in life expectancy at census tract, county, and state levels in the United States

초록

Studies on geographic inequalities in life expectancy in the United States have exclusively focused on single-level analyses of aggre-gated data at state or county level. This study develops a multi-level perspective to understanding variation in life expectancy by simultaneously modeling the geographic variation at the levels of census tracts (CTs), counties, and states. We analyzed data from 65,662 CTs, nested within 3,020 counties and 48 states (plus Dis-trict of Columbia). The dependent variable was age-specific life expectancy observed in each of the CTs. We also considered the following CT-level socioeconomic and demographic characteristics as independent variables: population density; proportions of pop-ulation who are black, who are single parents, who are below the federal poverty line, and who are aged 25 or older who have a bachelor's degree or higher; and median household income. Of the total geographic variation in life expectancy at birth, 70.4% of the variation was attributed to CTs, followed by 19.0% for states and 10.7% for counties. The relative importance of CTs was greater for life expectancy at older ages (70.4 to 96.8%). The CT-level inde-pendent variables explained 5 to 76.6% of between-state varia-tion, 11.1 to 58.6% of between-county variation, and 0.7 to 44.9% of between-CT variation in life expectancy across different age groups. Our findings indicate that population inequalities in lon-gevity in the United States are primarily a local phenomenon. There is a need for greater precision and targeting of local geog-raphies in public policy discourse aimed at reducing health inequal-ities in the United States.

키워드