Primary care, social inequalities and all-cause, heart disease and cancer mortality in US counties: a comparison between urban and non-urban areas.
OBJECTIVE
The objective of this study was to test whether the association between primary care and income inequality on all-cause, heart disease and cancer mortality at county level differs in urban (Metropolitan Statistical Area-MSA) compared with non-urban (non-MSA) areas.


METHODS
The study consisted of a cross-sectional analysis of county-level data stratified by MSA and non-MSA areas in 1990. Dependent variables included age and sex-standardized (per 100,000) all-cause, heart disease and cancer mortality. Independent variables included primary care resources, income inequality, education levels, unemployment, racial/ethnic composition and income levels.


METHODS
One-way analysis of variance and multivariate ordinary least squares regression were employed for each health outcome.


RESULTS
Among non-MSA counties, those in the highest income inequality category experienced 11% higher all-cause mortality, 9% higher heart disease mortality, and 9% higher cancer mortality than counties in the lowest income inequality quartile, while controlling for other health determinants. Non-MSA counties with higher primary care experienced 2% lower all-cause mortality, 4% lower heart disease mortality, and 3% lower cancer mortality than non-MSA counties with lower primary care. MSA counties with median levels of income inequality experienced approximately 6% higher all-cause mortality, 7% higher heart disease mortality, and 7% higher cancer mortality than counties in the lowest income inequality quartile. MSA counties with low primary care (less than 75th percentile) had significantly lower levels of all-cause, heart disease and cancer mortality than those counties with high primary care.


CONCLUSIONS
In non-MSA counties, increasing primary physician supply could be one way to address the health needs of rural populations. In MSA counties, the association between primary care and health outcomes appears to be more complex and is likely to require intervention that focuses on multiple fronts.
Shi
L
L
Department of Health Policy and Management, The Johns Hopkins Bloomberg School of Public Health, 624 N. Broadway, Room 406, Baltimore, MD 21205, USA. lshi@jhsph.edu
Macinko
J
J
Starfield
B
B
Politzer
R
R
Wulu
J
J
Xu
J
J
D000704:Analysis of Variance; D003430:Cross-Sectional Studies; D006297:Health Services Accessibility; D006331:Heart Diseases / Q000401:mortality*; D006801:Humans; D007182:Income; D016018:Least-Squares Analysis; D009369:Neoplasms / Q000401:mortality*; D011320:Primary Health Care / Q000706:statistics & numerical data*; D012424:Rural Population; D012959:Socioeconomic Factors; D014481:United States / Q000453:epidemiology; D014505:Urban Population