Evidence that intergenerational income mobility is the strongest predictor of drug overdose deaths in U. S. Midwest counties

Abstract

Background

Our goal in this report was to quantify the degree to which opioid prescription rates and socioeconomic correlates of income inequality predicted overdose deaths in the 1055 U.S. Midwest counties. The study follows up a state-level analysis which reported that opioid prescription rates, social capital and unemployment explained much of the variance in opioid overdose death rates (Heyman, McVicar, & Brownell, 2019).

Methods

We created a data set that included drug overdose death rates, opioid prescription rates, and correlates of income inequality. Given that the variables of interest varied at the state and county level, multilevel regression was our statistical approach.

Results

From 2006 to 2021, Midwest overdose drug deaths increased according to an exponential equation that closely approximated the equation that describes the increases in overdose deaths for the entire U.S. from 1978 to 2016 (e.g., Jalal et al., 2018). Retail opioid prescription sales increased from 2006 to 2012, but then declined so that by 2017 they were lower than in 2006. The regression analyses revealed that intergenerational income mobility was the strongest predictor of overdose deaths. The other consistently statistically significant predictors were opioid prescription rates, social capital, and unemployment rates. Together these predictors, plus pupil teacher ratios, single parent families, and attending college accounted for approximately 47 % of the variance in overdose death rates each year. In keeping with the decline in opioid prescription rates, the explanatory power of opioid prescription rates weakened over the course of the study.

Conclusions

Overdose deaths increased at a constant exponential rate for the years that it was possible to apply our regression model. This occurred even though access to legal opioids decreased. What remained invariant was the predictive strength of intergenerational income mobility; each year it was the predictor that explained the most variance in overdose deaths.