Inequalities in Life Expectancy Among US Counties, 1980 to 2014

Abstract

IMPORTANCEExamining life expectancy by county allows for tracking geographic disparities over time and assessing factors related to these disparities. This information is potentially useful for policy makers, clinicians, and researchers seeking to reduce disparities and increase longevity.OBJECTIVE To estimate annual life tables by county from 1980 to 2014; describe trends in geographic inequalities in life expectancy and age-specific risk of death; and assess the proportion of variation in life expectancy explained by variation in socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors.DESIGN, SETTING, AND PARTICIPANTS Annual county-level life tables were constructed using small area estimation methods from deidentified death records from the National Center for Health Statistics (NCHS), and population counts from the US Census Bureau, NCHS, and the Human Mortality Database. Measures of geographic inequality in life expectancy and age-specific mortality risk were calculated. Principal component analysis and ordinary least squares regression were used to examine the county-level association between life expectancy and socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors. EXPOSURES County of residence.MAIN OUTCOMES AND MEASURES Life expectancy at birth and age-specific mortality risk. RESULTSCounties were combined as needed to create stable units of analysis over the period 1980 to 2014, reducing the number of areas analyzed from 3142 to 3110. In 2014, life expectancy at birth for both sexes combined was 79.1 (95% uncertainty interval [UI], 79.0-79.1) years overall, but differed by 20.1 (95% UI,) years between the counties with the lowest and highest life expectancy. Absolute geographic inequality in life expectancy increased between 1980 and 2014. Over the same period, absolute geographic inequality in the risk of death decreased among children and adolescents, but increased among older adults. Socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors explained 60%, 74%, and 27% of county-level variation in life expectancy, respectively. Combined, these factors explained 74% of this variation. Most of the association between socioeconomic and race/ethnicity factors and life expectancy was mediated through behavioral and metabolic risk factors.CONCLUSIONS AND RELEVANCE Geographic disparities in life expectancy among US counties are large and increasing. Much of the variation in life expectancy among counties can be explained by a combination of socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors. Policy action targeting socioeconomic factors and behavioral and metabolic risk factors may help reverse the trend of increasing disparities in life expectancy in the United States.

Health Departments With A Commitment To Health Equity: A More Skilled Workforce And Higher-Quality Collaborations

“…If health equity is siloed in a separate office, chronic disease practitioners may not identify it as a primary area of their work or may not be collaborating with that office. (9–11) This is likely compounded by public health departments that are often organized into separate program areas that address specific diseases or risk factors and that are not well connected (often due to how funding is allocated at federal and state levels). It is also possible that the 9% of respondents who identify health equity as one of several work areas may be conceptualizing health equity as embedded in their primary areas of work, rather than as a specific area of focus.…”

“…(10) In 2017, Dwyer-Lindgren and colleagues found that the association between life expectancy and socioeconomic and race/ethnicity factors was largely mediated by behavioral and metabolic risk factors such as obesity, physical activity, hypertension, and diabetes. (11) These are the domains of chronic disease prevention and control. (12) Consequently, state-level chronic disease practitioners are uniquely situated to not only bear witness to health inequities but also intervene upon them.…”

America’s Declining Well-Being, Health, and Life Expectancy: Not Just a White Problem

“…42 It is possible that when immigration to the United States leveled off, immigrants stopped contributing to life expectancy gains and that this drove recent declines in overall life expectancy in the United States. 14 The migration story is supported by a relatively strong correlation between mortality and in-migration trends and the fact that areas without major urban centers that attract healthy international migrants have experienced a leveling off in life expectancy over the past decade. 43 …”

“…Although mortality increases among those with declining socioeconomic mobility, particularly in Southern “stroke belt” counties and among White women, had been previously noted, 14 Case and Deaton provided a narrative with media resonance. They termed this excess mortality “deaths of despair,” on the basis of their finding that mortality increases were largely driven by suicide, cirrhosis of the liver, and fatal opioid-related overdoses— causes that suggest victims are likely to be suffering from psychological distress 16,17 .…”

“…5,9 As a result, the long-term relative decline in life expectancy culminated in a multiyear absolute decline in life expectancy in the United States in 2015 and 2016. 11–14 One of the drivers of this absolute decline in life expectancy is an ongoing opioid-related mortality epidemic, which contributed to more than 60 000 lives lost in 2016. 15 However, absolute declines in life expectancy were observed for some groups and localities starting at least as early as 1980—decades before the opioid epidemic began.…”