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Inequalities in Life Expectancy Among US Counties, 1980 to 2014: Temporal Trends and Key Drivers

TLDR
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.
Abstract
Importance Examining 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. Results Counties 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, 19.1-21.3) 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.

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Journal ArticleDOI

The State of US Health, 1990-2016: Burden of Diseases, Injuries, and Risk Factors Among US States

Ali H. Mokdad, +143 more
- 10 Apr 2018 - 
TL;DR: There are wide differences in the burden of disease at the state level and specific diseases and risk factors, such as drug use disorders, high BMI, poor diet, high fasting plasma glucose level, and alcohol use disorders are increasing and warrant increased attention.
Journal ArticleDOI

Global, regional, and national age-sex-specific mortality and life expectancy, 1950-2017: a systematic analysis for the Global Burden of Disease Study 2017

Daniel Dicker, +1158 more
- 10 Nov 2018 - 
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 as mentioned in this paper was the most recent iteration of the GBD, which used all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups.
Journal ArticleDOI

Risk of Police-Involved Death by Race/Ethnicity and Place, United States, 2012-2018.

TL;DR: Police homicide risk is higher than suggested by official data, and Black and Latino men are at higher risk for death than are White men, and these disparities vary markedly across place.
Journal ArticleDOI

Diverging Life Expectancies and Voting Patterns in the 2016 US Presidential Election.

TL;DR: Residents of counties left out from broader life expectancy gains abandoned the Democratic Party in the 2016 presidential election, and changes in county life expectancy from 1980 to 2014 were strongly negatively associated with Trump's vote share.
References
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Journal Article

R: A language and environment for statistical computing.

R Core Team
- 01 Jan 2014 - 
TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Journal ArticleDOI

Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015

Haidong Wang, +844 more
- 08 Oct 2016 - 
TL;DR: The Global Burden of Disease 2015 Study provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015, finding several countries in sub-Saharan Africa had very large gains in life expectancy, rebounding from an era of exceedingly high loss of life due to HIV/AIDS.
Journal ArticleDOI

The State of US Health, 1990-2010: Burden of Diseases, Injuries, and Risk Factors

Christopher J L Murray, +126 more
- 14 Aug 2013 - 
TL;DR: To measure the burden of diseases, injuries, and leading risk factors in the United States from 1990 to 2010 and to compare these measurements with those of the 34 countries in the Organisation for Economic Co-operation and Development (OECD), systematic analysis of descriptive epidemiology was used.
Journal ArticleDOI

Rising morbidity and mortality in midlife among white non-Hispanic Americans in the 21st century.

TL;DR: A marked increase in the all-cause mortality of middle-aged white non-Hispanic men and women in the United States between 1999 and 2013 reversed decades of progress in mortality and was unique to the United United States; no other rich country saw a similar turnaround.
Journal ArticleDOI

The Association Between Income and Life Expectancy in the United States, 2001-2014

TL;DR: In the United States between 2001 and 2014, higher income was associated with greater longevity, and differences in life expectancy across income groups increased over time, however, the association between life expectancy and income varied substantially across areas; differences in longevity acrossincome groups decreased in some areas and increased in others.
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Trending Questions (1)
What are the top medical determinants that contribute to variation in life expectancy across different populations?

Socioeconomic, race/ethnicity, behavioral, metabolic, and health care factors are the key medical determinants contributing to variations in life expectancy across different populations in the US counties.