ArticleDrug and alcohol dependence2025
Examining trends in polydrug overdose deaths across rural Midwest counties in the United States, 2022 through 2024.
Article in Drug and alcohol dependence, 2025. 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
purposeTo examine trends in overdose deaths and the presence of xylazine in postmortem toxicology in a highly rural region of northern Minnesota with a significant American Indian/Alaska Native (AI/AN) population, using real-time local surveillance data.
methodsWe analyzed drug overdose death data from the Midwest Medical Examiner's Office, covering 36 counties from January 1, 2022 to December 31, 2024. Data included demographic characteristics, place of death, and substances detected in toxicology results. Age-adjusted mortality rates and disparities across racial/ethnic groups were calculated, and polydrug combinations were explored using network analysis.
findingsAmong 967 overdose deaths, most decedents were white (71.7 %), AI/AN (13.4 %), or Black/African American (10.3 %) with an overall mortality rate of 76.1. Mortality rates declined during the study period for white and AI/AN populations and increased slightly for Black/African American populations. However, rates remained disproportionately high for AI/AN populations, who were 6.19 times more likely to die of overdose than non-AI/AN in 2024. Xylazine was detected only in combination with fentanyl, with no racial/ethnic differences in its presence. Distinct polydrug patterns were observed by race: fentanyl-cocaine combinations were more prevalent among Black/African Americans, while fentanyl-methamphetamine combinations predominated among AI/AN and White decedents.
conclusionsLocal surveillance in rural areas can detect emerging threats like xylazine and illuminate racial disparities obscured in national datasets. Findings highlight the urgent need for real-time, locally driven data to inform targeted prevention and harm reduction, particularly for AI/AN populations in rural communities.
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