Neighborhoods
The Association Between Income and Life Expectancy in the United States, 2001-2014
Raj Chetty, Augustin Bergeron, David Cutler, Benjamin Scuderi, Michael Stepner, Nicholas Turner
The Journal of the American Medical Association 315(4), 2016
April 2016

How can we reduce socioeconomic disparities in health outcomes? Although it is well known that there are significant differences in health and longevity between income groups, debate remains about the magnitudes and determinants of these differences. We use new data from 1.4 billion anonymous earnings and mortality records to construct more precise estimates of the relationship between income and life expectancy at the national level than was feasible in prior work. We then construct new local area (county and metro area) estimates of life expectancy by income group and identify factors that are associated with higher levels of life expectancy for low-income individuals.

Our findings show that disparities in life expectancy are not inevitable. There are cities throughout America — from New York to San Francisco to Birmingham, AL — where gaps in life expectancy are relatively small or are narrowing over time. Replicating these successes more broadly will require targeted local efforts, focusing on improving health behaviors among the poor in cities such as Las Vegas and Detroit. Our findings also imply that federal programs such as Social Security and Medicare are less redistributive than they might appear because low-income individuals obtain these benefits for significantly fewer years than high-income individuals, especially in cities like Detroit.

Going forward, the challenge is to understand the mechanisms that lead to better health and longevity for low-income individuals in some parts of the U.S. To facilitate future research and monitor local progress, we have posted annual statistics on life expectancy by income group and geographic area (state, CZ, and county) at The Health Inequality Project website. Using these data, researchers will be able to study why certain places have high or improving levels of life expectancy and ultimately apply these lessons to reduce health disparities in other parts of the country.

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Table 1
Income and Life Expectancy: National Life Expectancy Estimates by Gender and Income Percentile

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Table 2
Life Expectancy Estimates by Year, Gender, and Income Percentile

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Table 3
State Life Expectancy Estimates by Gender and Income Percentile

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Table 4
State Life Expectancy Estimates by Gender and Income Quartile

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Table 5
State Life Expectancy Estimates by Year, Gender, and Income Quartile

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Table 6
Commuting Zone Life Expectancy Estimates by Gender and Income Quartile

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Table 7
Commuting Zone Life Expectancy Estimates by Gender and Income Ventile

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Table 8
Commuting Zone Life Expectancy Trends Estimates by Gender and Income Quartile

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Table 9
Commuting Zone Life Expectancy Estimates by Year, Gender, and Income Quartile

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Table 10
Commuting Zone Characteristics (Described in eTable 9)

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Table 11
County Life Expectancy Estimates by Gender and Income Quartile

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Table 12
County Characteristics (Described in eTable 9)

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Table 13
International Mean Life Expectancy at Age 40 by Country and Gender

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Table 14
National Population and Death Counts in Tax Data and NCHS Data by Gender, Age, and Year

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Table 15
National Mortality Rates by Gender, Age, Year, and Income Percentile

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Table 16
National Mortality Rates by Gender, Age, Year, and Individual Income Percentile

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Income and Life Expectancy: Complete Set of Formatted Data Tables with Codebook

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Income and Life Expectancy: Complete Set of Unformatted Data Tables

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Life Expectancy Rankings for 100 Most Populated Local Areas

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Income and Life Expectancy: Commuting Zone Boundaries (1990 Definition)

SHAPEFILE1990 COUNTY CROSSWALK

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Income and Life Expectancy: Data for Figures, Tables, and Numbers in Text of JAMA Manuscript

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Income and Life Expectancy: Replication Code and Data

CODE AND INSTRUCTIONSDATA ONLY (ZIP 1GB)Derived Results ZIP (2 GB)