The Opioid Hydra: Understanding Overdose Mortality Epidemics and Syndemics Across the Rural-Urban Continuum

David J. Peters, Shannon M. Monnat, Andrew L. Hochstetler, Mark T. Berg

Research output: Contribution to journalArticlepeer-review

65 Scopus citations

Abstract

The rapid increase of fatal opioid overdoses over the past two decades is a major U.S. public health problem, especially in non-metropolitan communities. The crisis has transitioned from pharmaceuticals to illicit synthetic opioids and street mixtures, especially in urban areas. Using latent profile analysis, we classify n = 3,079 counties into distinct classes using CDC fatal overdose rates for specific opioids in 2002–2004, 2008–2012, and 2014–2016. We identify three distinct epidemics (prescription opioids, heroin, and prescription-synthetic opioid mixtures) and one syndemic involving all opioids. We find that prescription-related epidemic counties, whether rural or urban, have been “left behind” the rest of the nation. These communities are less populated and more remote, older and mostly white, have a history of drug abuse, and are former farm and factory communities that have been in decline since the 1990s. Overdoses in these places exemplify the “deaths of despair” narrative. By contrast, heroin and opioid syndemic counties tend to be more urban, connected to interstates, ethnically diverse, and in general more economically secure. The urban opioid crisis follows the path of previous drug epidemics, affecting a disadvantaged subpopulation that has been left behind rather than the entire community. County data on opioid epidemic class membership are provided.

Original languageEnglish (US)
Pages (from-to)589-622
Number of pages34
JournalRural Sociology
Volume85
Issue number3
DOIs
StatePublished - Sep 1 2020

ASJC Scopus subject areas

  • Sociology and Political Science

Fingerprint

Dive into the research topics of 'The Opioid Hydra: Understanding Overdose Mortality Epidemics and Syndemics Across the Rural-Urban Continuum'. Together they form a unique fingerprint.

Cite this