Population Well-Being Measures Help Explain Geographic Disparities In Life Expectancy At The County Level

Abstract

Geographic disparities in life expectancy are substantial and not fully explained by differences in race and socioeconomic status. To develop policies that address these inequalities, it is essential to identify other factors that account for this variation. In this study we investigated whether population well-being—a comprehensive measure of physical, mental, and social health—helps explain geographic variation in life expectancy. At the county level, we found that for every 1-standarddeviation (4.2-point) increase in the well-being score, life expectancy was 1.9 years higher for females and 2.6 years higher for males. Life expectancy and well-being remained positively associated, even after race, poverty, and education were controlled for. In addition, well-being partially mediated the established associations of race, poverty, and education with life expectancy. These findings highlight well-being as an important metric of a population’s health and longevity and as a promising focus for intervention.

Associations between community well-being and hospitalisation rates: results from a cross-sectional study within six US states

“…Community well-being is modifiable and supporting programmes and policies to foster community well-being should be a society’s end goal 25–27. Our results suggest that promoting community well-being may have an additional benefit of curbing unnecessary hospitalisation rates, as well as supporting other beneficial population health outcomes, including longer life expectancy and lower rates of preterm birth 28–30. Our team also recently reported that Medicare spent a mean of US$992 less per beneficiary who lived in counties with the highest quintile of well-being compared with those who lived in counties with the lowest quintile of well-being 11.…”

“…There are several potential mechanisms underlying this observed association. First, it is possible that the observed association is simply a result of aggregating individuals with higher well-being and their associated lower rate of hospitalisation 28. In two unique large employer-based populations, higher individual well-being predicted fewer hospitalisations and emergency department visits over the next 12 months 9 10.…”

Long-term trends in the contribution of major causes of death to the black-white life expectancy gap by US state

“…While we found that many states conformed to the national pattern of cause-of-death specific contributions, several states diverged in ways that either resulted in the near or total elimination of the life expectancy gap, or alternatively its exacerbation. In contrast to some recent work focused on county-level inequalities, 7,8 states have some substantial advantages as analysis units; They have large populations to generate stable estimates, tend to be more demographically stable over time, and they are policymaking entities, and so have divergent social agendas that are reflected in varying patterns of mortality by race.…”

Rural‐Urban Differences in Medicare Quality Scores Persist After Adjusting for Sociodemographic and Environmental Characteristics

“…We know that population health is influenced by factors outside of the clinical realm, including socioeconomic and demographic characteristics, health behaviors, and the environment . There are stark differences in physical environment, community characteristics, access to health care, and sociodemographic characteristics by rurality, which, in turn, could influence population health and health care quality scores . Findings linking health and geography are particularly salient in an era of assessment and payment of health care providers and facilities based on the quality outcomes of the population they serve .…”

“…2 There are stark differences in physical environment, community characteristics, access to health care, and sociodemographic characteristics by rurality, 7,8 which, in turn, could influence population health and health care quality scores. 3,9 Findings linking health and geography are particularly salient in an era of assessment and payment of health care providers and facilities based on the quality outcomes of the population they serve. 10 In particular, the Centers for Medicare & Medicaid Services are increasingly using value-based purchasing programs designed to incentivize high-quality care, rather than relying on a traditional fee-for-service model.…”