Overview
Research Objective:
Landmark research by Raj Chetty and colleagues finds wide geographic and intertemporal variation in the relationship between income and life expectancy in the U.S., using 1.4 billion administrative tax records from the IRS linked to nearly 7 million federal death records. Many questions remain about the underlying causes of these findings and their implications for policy. This study links Chetty’s income and life expectancy data with the 1998-2014 National Longitudinal Survey of Public Health Systems to examine whether the existence and strength of multi-sector population health improvement activities influence income-related disparities in life expectancy over time.
Study Design:
Our retrospective cohort design follows more than 350 U.S. metropolitan communities over time using survey data collected initially in 1998 and again in 2006, 2012, and 2014. Local public health officials report on the implementation of 20 nationally-recommended public health activities in the community, and on the organizations that contribute to performing each activity including hospitals, primary care providers, insurers, employers, schools, and community-based organizations. We classify communities into one of seven categories of multi-sector population health activity based on a cluster analysis of the scope of recommended activities contributed by each type of organization, along with the density of relationships connecting these organizations. Using geographic identifiers, we link these survey data with Chetty’s county-specific estimates of life expectancy by income quartile from 1999 to 2014, along with measures of community demographic, socioeconomic, and health resource characteristics from other data sources. Random-effects models with instrumental-variables are used to estimate whether changes in multi-sector population health activities lead to changes life expectancy by income quartile, while controlling for both observable and unmeasured confounders.
Population Studied:
We include 354 metropolitan communities, representing more than 70% of the total U.S. population.
Principal Findings:
Communities attaining the highest level of multi-sector population health activities increased from 24% of the sample in 1998 to 37% in 2006, but fell to 31% in 2012 and recovered modestly to 33% in 2014. Within sectors, hospitals increased their contributions to population health activities by nearly 20% between 2012 and 2014, while insurers, employers, and nonprofit community-based organizations showed smaller but significant increases in contributions (p<0.05). Residing in a community with the highest level of population health activity was associated with a 3.9 year gain in life expectancy for individuals in the bottom quartile of the income distribution after controlling for observed and unmeasured confounders (p<0.05), but no significant gain in life expectancy for the top income quartile. Differences in life expectancy between the top and bottom income quartiles declined by an estimated 2.1 years in communities with the highest level of activity (p<0.01).
Conclusions:
Community capacity to implement widely-recommended population health activities is one important contributor to geographic variation in the relationship between income and life expectancy.
Implications for Policy or Practice:
Policies that encourage multi-sector contributions to population health activities, such as hospital community benefit standards and accountable health community (AHC) models, may reduce socioeconomic and geographic disparities in health status.
Details
Project: Multi-Sector Population Health Activities Reduce Income-related Disparities in Life Expectancy
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Authors: Mays GP