Disparities in premature mortality between high- and low-income US counties

Prev Chronic Dis. 2012;9:E75. Epub 2012 Mar 22.

Abstract

Introduction: Several well-established determinants of health are associated with premature mortality. Using data from the 2010 County Health Rankings, we describe the association of selected determinants of health with premature mortality among counties with broadly differing levels of income.

Methods: County-level data on 3,139 US counties from the 2010 County Health Rankings were linked to county mortality data from the Centers for Disease Control and Prevention Compressed Mortality database. We divided counties into 3 groups, defined by sample median household income levels: low-income (≤25th percentile, $29,631), mid-income (25th-75th percentile, $29,631-$39,401), and high-income (≥75th percentile, ≥$39,401). We analyzed group differences in geographic, sociodemographic, racial/ethnic, health care, social, and behavioral factors. Stratified multivariable linear regression explored the associations of these health determinants with premature mortality for high- and low-income groups.

Results: The association between income and premature mortality was stronger among low-income counties than high-income counties. We found differences in the pattern of risk factors between high- and low-income groups. Significant geographic, sociodemographic, racial/ethnic, health care, social, and behavioral disparities exist among income groups.

Conclusion: Geographic location and the percentages of adult smokers and adults with a college education were associated with premature mortality rates in US counties. These relationships varied in magnitude and significance across income groups. Our findings suggest that population health policies aimed at reducing mortality disparities require an understanding of the socioeconomic context within which modifiable variables exist.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Health Status Disparities*
  • Humans
  • Mortality, Premature* / ethnology
  • Regression Analysis
  • Socioeconomic Factors
  • United States / epidemiology