Pub Date : 2023-07-23DOI: 10.1101/2023.07.18.23292832
Gene M Heyman, Ehri Ryu, Hiram Brownell, Gene Heyman
In 2017, the Acting U.S. Secretary of Health and Human Services declared the opioid crisis a nation-wide health emergency. However, the crisis geography was not nation-wide. Many counties and towns had no overdose deaths, whereas others were home to hundreds. According to many influential research reports and news stories, geographic variation in overdose deaths was due to geographic variation in opioid prescription rates and/or geographic variation in socioeconomic factors, such as unemployment. Our goal was to test the degree to which prescription rates and socioeconomic correlates of income inequality predicted overdose deaths in the 1055 U.S. Midwest (Heartland) counties over the years 2006 to 2020. We used multilevel regression models to gauge the predictive strength of overdose rates and six socioeconomic measures that are correlated with income inequality. There were significant state-level and county-level differences. Intergenerational income mobility was the strongest predictor of overdose deaths, with regression coefficients that averaged about twice as large as the coefficients for opioid prescription rates. Every year, counties with greater upward intergenerational income mobility had lower overdose death rates. Social capital had the second largest regression coefficients, albeit by a small margin. Counties are the smallest demographic unit for which drug overdose rates are available; the results of this study link growing income inequality and drug overdose deaths at the county level.
{"title":"Evidence that intergenerational income mobility is the strongest predictor of drug overdose deaths in U. S. Heartland counties","authors":"Gene M Heyman, Ehri Ryu, Hiram Brownell, Gene Heyman","doi":"10.1101/2023.07.18.23292832","DOIUrl":"https://doi.org/10.1101/2023.07.18.23292832","url":null,"abstract":"In 2017, the Acting U.S. Secretary of Health and Human Services declared the opioid crisis a nation-wide health emergency. However, the crisis geography was not nation-wide. Many counties and towns had no overdose deaths, whereas others were home to hundreds. According to many influential research reports and news stories, geographic variation in overdose deaths was due to geographic variation in opioid prescription rates and/or geographic variation in socioeconomic factors, such as unemployment. Our goal was to test the degree to which prescription rates and socioeconomic correlates of income inequality predicted overdose deaths in the 1055 U.S. Midwest (Heartland) counties over the years 2006 to 2020. We used multilevel regression models to gauge the predictive strength of overdose rates and six socioeconomic measures that are correlated with income inequality. There were significant state-level and county-level differences. Intergenerational income mobility was the strongest predictor of overdose deaths, with regression coefficients that averaged about twice as large as the coefficients for opioid prescription rates. Every year, counties with greater upward intergenerational income mobility had lower overdose death rates. Social capital had the second largest regression coefficients, albeit by a small margin. Counties are the smallest demographic unit for which drug overdose rates are available; the results of this study link growing income inequality and drug overdose deaths at the county level.","PeriodicalId":501282,"journal":{"name":"medRxiv - Addiction Medicine","volume":"13 84","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}