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Shannon Monnat

Shannon Monnat

Mortality rates from drug poisoning, suicide, alcohol, and homicide vary significantly across the United States. This study explores localized relationships (i.e., geographically specific associations) between county-level economic and household distress and mortality rates from these causes among working-age adults (25–64).

Mortality data were from the National Vital Statistics System for 2014–2019. County-level socioeconomic distress (poverty, employment, income, education, disability, insurance) and household distress (single-parent, no vehicle, crowded housing, renter occupied) were from the 2009–2013 American Community Survey. We conducted Ordinary Least Squares (OLS) regression to estimate average associations and Geographically Weighted Regression (GWR) to estimate localized spatial associations between county-level distress and working-age mortality.

In terms of national average associations, OLS results indicate that a one standard deviation increase in socioeconomic distress was associated with an average of 6.1 additional drug poisoning deaths, 3.0 suicides, 2.1 alcohol-induced deaths, and 2.0 homicides per 100,000 population. A one standard deviation increase in household distress was associated with an average of 1.4 additional drug poisonings, 4.7 alcohol-induced deaths, and 1.1 homicides per 100,000 population. However, the GWR results showed that these associations vary substantially across the U.S., with socioeconomic and household distress associated with significantly higher mortality rates in some parts of the U.S than others, significantly lower rates in other parts of the U.S., and no significant associations in others. There were also some areas where distress overlapped to influence multiple causes of death, in a type of compounded disadvantage.

Socioeconomic and household distress are significant and substantial predictors of higher rates of drug poisoning mortality, suicide, alcohol-induced deaths, and homicide in specific regions of the U.S. However, these associations are not universal. Understanding the place-level factors that contribute to them can inform geographically tailored strategies to reduce rates from these preventable causes of death in different places.