ArticlePopulation health metrics2026
Clues to the origin of rising midlife mortality: associations between recent mortality outcomes and county-level economic, social, and employment changes over multiple time periods.
Article in Population health metrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundAll-cause midlife mortality rates have been increasing since 2010 in the United States. Using data from 1970 to 2010, this study investigates the association between county-level changes in economic, social, and employment sectors and changes in midlife mortality rates the occurred between 2010 and 2018. The study employs a novel approach to analyze temporal trends.
methodsCounty-level mortality data for 2009-2019 were obtained from the Centers for Disease Control and Prevention (CDC), while decennial data for 19 indicators-covering socioeconomic conditions, social factors, and employment sectors-were obtained from IPUMS NHGIS time series tables and the US Bureau of Economic Analysis, Economic Profile by County. Data were examined for 3,069 (97.6%) of the 3,143 U.S. counties and county equivalents. Absolute changes in county characteristics were measured over ten possible comparison periods: single decades, two decades, three decades, and four decades. LASSO regression was used to identify significant predictors and assess their impact over multiple time periods.
resultsWhile changes in some county characteristics (e.g., households headed by single mothers, employment in certain sectors, college education, and labor force participation), tend to be associated with higher or lower mortality risk; in many cases the strength and direction of observed associations differed depending on time period, place, and race. These results reveal the importance of historical and contextual factors in understanding mortality trends and highlight the complex interplay between social determinants and health outcomes.
conclusionsThis study provides insights into the drivers of midlife mortality and a nuanced look at the temporal dynamics and geographic variations in mortality trends. By identifying critical time periods and specific predictors associated with mortality changes, the study informs policy and public health efforts aimed at reducing mortality disparities and improving population health outcomes.
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