Geographic disparities in life expectancy across US counties may be due to socioeconomic, race, and behavioral factors
1. This county-level American cross-sectional study found geographic disparities in life expectancy, wherein life expectancy differed by as much as 20 years between counties with the lowest and highest life expectancy.
2. Socioeconomic, race/ethnicity, behavioral and metabolic risk factors, and health care factors explained 74% of the variation seen in life expectancy. Most of the association between socioeconomic and race/ethnicity factors, and life expectancy was mediated by behavioral and metabolic risk factors.
Evidence Rating Level: 3 (Fair)
Study Rundown: It is important to understand the social determinants of health to minimize health care inequality. Understanding the causes of geographic disparities, for example, can be useful for policy makers and clinicians to help improve health care and decrease imbalances across populations. This cross-sectional study described trends in geographic inequalities in life expectancy and risk of death, and assessed the variation in life expectancy based on social factors like socioeconomic status, race, health care factors, behavioral and metabolic factors.
There was considerable variation in mortality risk and life expectancy at the county level in all study years. In 2014, the life expectancy at birth for both sexes of all counties combined was 79.1 years for males and 81.5 years for females. There was a 6.2-year gap between the 10th and 90th percentile, 10.7-year gap between the 1st and 99th percentile, and 20.1-year gap between the counties with the lowest and highest life expectancy. Absolute geographic inequality in life expectancy increased over the study period. Socioeconomic, race/ethnicity, behavioral and metabolic risk factors, and health care factors explained 74% of the variation seen in life expectancy. Most of the association between socioeconomic and race and longevity was mediated through behavioral and metabolic risk factors. Strengths of this study included using a smaller ecological unit, the county, to study the impact of social health factors on life expectancy. However, further cohort studies would be needed to clarify these trends.
Click to read the study, published in JAMA Internal Medicine
Relevant Reading: The Association Between Income and Life Expectancy in the United States, 2001-2014
In-Depth [cross-sectional study]: This study was conducted from 1980 to 2014 using county-level life tables from the National Center for Health Statistics (NCHS) and population counts from the US Census Bureau, NCHS, and the Human Mortality Database. The unit of study was the US county and the outcome of interest was life expectancy and social health factors (socioeconomic status, race/ethnicity, behavioral and metabolic risk factors and health care factors). Through this, measures of geographic inequality in life expectancy and age-specific mortality risk were calculated. Principal component analysis and least square regression models were used for statistical analysis.
A total of 3110 counties were used in this analysis. Life expectancy in 2014 was 79.1 years for males and 81.5 years for females. There was a 6.2-year gap (95% uncertainty interval [UI] 6.1-6.2) between the 10th and 90th percentile, 10.7-year gap (95% UI 10.5-11.0) between the 1st and 99th percentile and 20.1-year gap (95% UI 19.1-21.3) between the counties with the lowest and highest life expectancy. Native American reserve counties in North and South Dakota, counties in Mississippi, Eastern Kentucky and South-western Virginia were among the areas with the lowest life expectancies, whereas counties in Colorado had the highest life expectancies. Socioeconomic, race/ethnicity, behavioral and metabolic risk factors, and health care factors explained 60%, 74% and 27% of county-level variation respectively. Combining these factors explained 74% of variation.
Image: PD
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