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relationships between poverty and unemployment, and between per capita retail opioid sales and overdose death rates, are not as systematic as previously described. A fraction of U.S. counties had relatively higher rates of drug measures yet low poverty and unemployment rates. In these counties, poorer economic conditions do not predict as strongly, if at all, the prevalence of retail opioid sales and overdose deaths, suggesting the presence of other contributing factors. These counties were more likely to be in New England and the Mid-Atlantic, as well as parts of the West. A second set of counties had higher relative poverty and unemployment rates, while having lower rates of overdose deaths and opioid prescriptions. In these counties, despite worse economic conditions, opioid sales and overdose death rates were relatively low. To the extent that these two indicators reflect the ongoing epidemic of substance and opioid use, they may indicate that other factors protected these counties. These counties were more likely to be in the South, and further analysis revealed that these counties were more likely to have a larger minority population and to have had improvements in unemployment or poverty rates, compared with other counties. ASSOCIATION OF ECONOMIC OPPORTUNITY WITH SUBSTANCE USE AND OPIOID MEASURES We have identified geographic diversity in the relationship between economic opportunity, substance use and opioid prevalence measures. Counties differ in their economic, demographic, cultural, and political contexts, all of which may account for this diversity. These factors can also confound the underlying relationship between economic opportunity and the opioid epidemic. By adjusting for some of these variables in statistical models, we can better identify how unemployment and poverty relate to the four measures of opioid prescribing and substance use. On average, there is a strong statistical link between county poverty and unemployment rates and measures of the opioid crisis. Table 1 shows results from statistical models that adjust for several countyTable 1. Change in Opioid and Substance Use Measures Associated with a One-Point Increase in Economic Measures Retail Opioid Sales, Per Capita Medicare Part D Opioid Prescriptions, Per Capita Opioid-Related Hospitalization Rates Drug Overdose Death Rates Poverty rate 1.4%* 3.3%* 2.4%* 1.7%* Unemployment rate 3.8%* 1.9%* 5.1%* 4.6%* Employment-topopulation ratio −0.5%* −0.5%* −0.3% 0.5%* Notes: N ranges from 30,220 to 34,405 for models of retail opioid sales, Medicare part D opioid prescriptions, and overdose deaths. N ranges from 5,820 to 5,831 for models of hospitalizations. Data are from 2006 through 2016 for retail opioid sales, Medicare prescriptions, and overdose deaths and from 2011 through 2014 for hospitalizations. * statistically significant at p < 0.05. Results are from statistical models adjusting for various factors. For details on sample sizes and results, see Tables A4 and A5 in the Appendix. 9 level demographic factors, such as population size, race/ethnicity, and urbanicity. From 2006 through 2016, on average, an increase of 1 percentage point in a county’s poverty rate was associated with a 1.4 percent increase in per capital retail opioid sales, a 3.3 percent increase in the Medicare Part D opioid prescription rate, and a 1.7 percent increase in the overdose death rate. From 2011 through 2014, on average, an increase of 1 percentage point in a county’s poverty rate was associated with a 2.4 percent increase in the rate of opioid-related hospitalizations. Similarly, measures of employment were associated with higher overdose death rates. Table 1 shows that an increase of 1 percentage point in a county’s unemployment rate was associated with a 3.8 percent increase in per capita opioid sales, a 1.9 percent increase in per capita Medicare Part D opioid prescriptions, and a 4.6 percent increase in the overdose death rate, in the period from 2006 to 2016. Even more dramatic, from 2011 through 2014, an increase of 1 percentage point in a county’s unemployment rate was associated with a 5.1 percent increase in the opioid-related hospitalization rate. Using the employment-to-population ratio provides