Differences in Life Expectancy by Income Vary Geographically

It is not surprising that a new study on the relationship between income and longevity in the United States concludes that life expectancy increased with income. However, the study did shed light on the variabilities in the income-longevity relationship.

It is not surprising that a new study on the relationship between income and longevity in the United States concludes that life expectancy increased with income. However, the study did shed light on the variabilities in the income-longevity relationship.

The study used income data for the US population that were obtained from 1.4 billion deidentified tax records of individuals ages 40 to 76 years between 1999 and 2014. Social Security Administration death records provided mortality data. These data were used to estimate race- and ethnicity-adjusted life expectancy at 40 years of age by household income percentile, sex, and geographic area, and to analyze factors associated with differences in life expectancy. The main findings were as follows:

  • Higher income was associated with longer life at all income distributions. The gap in life expectancy between the richest 1% and the poorest 1% was 14.6 years for men and 10.1 years for women.
  • Inequality in life expectancy increased over time. Between 2001 and 2014 life expectancy increased by 2.34 years for men and 2.91 years for women in the top 5% of income distribution but by only 0.32 years for men and 0.04 years for women in the bottom 5%.
  • Life expectancy for low-income individuals varied substantially across local areas. In the bottom quartile of income, life expectancy differed by about 4.5 years between areas with the highest and lowest longevity. Between 2001 and 2014 changes in life expectancy ranged from increases of more than 4 years to losses of more than 2 years across areas.
  • There were geographic differences in life expectancy. These difference for those in the lowest income quartile were significantly correlated with health behaviors such as smoking, but were not significantly correlated with access to medical care, factors in the physical environment, income inequality, or labor market conditions. Life expectancy for low-income people was positively correlated with the fraction of immigrants, fraction of college graduates, and government expenditures in the local area.

The strongest pattern in the data was that low-income individuals tend to live longest and have more healthy behaviors in cities with highly educated populations, high incomes, and high levels of government expenditures such as New York City and San Francisco. In these cities, life expectancy for people in the bottom 5% of income distribution was approximately 80 years; in contrast, in cities such as Detroit, Michigan, the expected age at death for those in the bottom 5% was approximately 75 years.

Low-income individuals living in cities with highly educated populations and high incomes also had the largest gains in life expectancy during the 2000s, the authors said.

The researchers conclude that reducing gaps in longevity may require local policy responses, and that health professionals make targeted efforts to improve health among low-income populations with policy interventions focusing on changing health behaviors among low-income people. Tax policies and other local public policies may play a role in inducing such changes, they advise.