Abstract
Studies have documented significant geographic divergence in U.S. mortality in recent decades. However, few studies have examined the extent to which county-level trends in mortality can be explained by national, state, and metropolitan-level trends, and which county-specific factors contribute to remaining variation. Combining vital statistics data on deaths and Census data with time-varying county-level contextual characteristics, we use a spatially explicit Bayesian hierarchical model to analyze the associations between working-age mortality, state, metropolitan status and county-level socioeconomic conditions, family characteristics, labor market conditions, health behaviors, and population characteristics between 2000 and 2017. Additionally, we employ a Shapley decomposition to illustrate the additive contributions of each changing county-level characteristic to the observed mortality change in U.S. counties between 1999–2001 and 2015–2017 over and above national, state, and metropolitan–nonmetropolitan mortality trends. Mortality trends varied by state and metropolitan status as did the contribution of county-level characteristics. Metropolitan status predicted more of the county-level variance in mortality than state of residence. Of the county-level characteristics, changes in percent college-graduates, smoking prevalence and the percent of foreign-born population contributed to a decline in all-cause mortality over this period, whereas increasing levels of poverty, unemployment, and single-parent families and declines manufacturing employment slowed down these improvements, and in many nonmetropolitan areas were large enough to overpower the positive contributions of the protective factors.
Highlights
Geography, reflecting the social and political context of one’s area of residence, has long been recognized as an important factor influencing an individual’s exposures to health-related risks, access to health services, and educational and economic opportunities over a person’s life course (Chetty et al, 2014; Hillman, 2016; Krieger et al, 2005; Wen et al, 2003)
This paper contributes to the above literature by examining to what extent the variation in county-level mortality can be attributed to national, state, and metropolitan–nonmetropolitan-level mortality trends and which changing county-level characteristics, including socioeconomic, labor market and family characteristics, health behaviors and population composition, contribute to the remaining variation
Contributions from the decomposition can be interpreted as a conditional expectation under our model: the change in expected mortality associated with a change in the given time-varying county-level characteristic, compared to expected mortality if that characteristic had not changed since 2000
Summary
Geography, reflecting the social and political context of one’s area of residence, has long been recognized as an important factor influencing an individual’s exposures to health-related risks, access to health services, and educational and economic opportunities over a person’s life course (Chetty et al, 2014; Hillman, 2016; Krieger et al, 2005; Wen et al, 2003). In the United States, recent studies have documented large geographic inequalities in health and mortality across Census regions and divisions (Elo et al, 2019; Fenelon, 2013), commuting zones (Chetty et al, 2016b), states (Montez et al, 2019; Montez et al, 2017; Montez et al, 2016; Wilmoth et al, 2011; Woolf & Schoomaker, 2019), metropolitan and nonmetropolitan areas (Cossman et al, 2010; Eberhardt & Pamuk, 2004; Elo et al, 2019; James, 2014; James et al, 2018; Singh & Siahpush, 2014), and counties (Dwyer-Lindgren et al, 2017; Wang et al, 2013). The respective figures were 2.7 years in the Northeast, 3.9 years in the Midwest, and 3.6 years in the continental West (Woolf & Schoomaker, 2019).
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