Literature DB >> 31219718

Using Census Data to Understand County-Level Differences in Overall Drug Mortality and Opioid-Related Mortality by Opioid Type.

Shannon M Monnat1, David J Peters1, Mark T Berg1, Andrew Hochstetler1.   

Abstract

Objectives. To examine associations of county-level demographic, socioeconomic, and labor market characteristics on overall drug mortality rates and specific classes of opioid mortality. Methods. We used National Vital Statistics System mortality data (2002-2004 and 2014-2016) and county-level US Census data. We examined associations between several census variables and drug deaths for 2014 to 2016. We then identified specific classes of counties characterized by different levels and rates of growth in mortality from specific opioid types between 2002 to 2004 and 2014 to 2016. We ran multivariate and multivariable regression models to predict probabilities of membership in each "opioid mortality class" on the basis of county-level census measures. Results. Drug mortality rates overall are higher in counties characterized by more economic disadvantage, more blue-collar and service employment, and higher opioid-prescribing rates. High rates of prescription opioid overdoses and overdoses involving both prescription and synthetic opioids cluster in more economically disadvantaged counties with larger concentrations of service industry workers. High heroin and "syndemic" opioid mortality counties (high rates across all major opioid types) are more urban, have larger concentrations of professional workers, and are less economically disadvantaged. Syndemic opioid counties also have greater concentrations of blue-collar workers. Conclusions. Census data are essential tools for understanding the importance of place-level characteristics on opioid mortality. Public Health Implications. National opioid policy strategies cannot be assumed universally applicable. In addition to national policies to combat the opioid and larger drug crises, emphasis should be on developing locally and regionally tailored interventions, with attention to place-based structural economic and social characteristics.

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Year:  2019        PMID: 31219718      PMCID: PMC6611117          DOI: 10.2105/AJPH.2019.305136

Source DB:  PubMed          Journal:  Am J Public Health        ISSN: 0090-0036            Impact factor:   9.308


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Journal:  Am J Prev Med       Date:  2018-03-26       Impact factor: 5.043

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8.  Environmental Predictors of US County Mortality Patterns on a National Basis.

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9.  Assessment of Changes in the Geographical Distribution of Opioid-Related Mortality Across the United States by Opioid Type, 1999-2016.

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10.  County Poverty Concentration and Disparities in Unintentional Injury Deaths: A Fourteen-Year Analysis of 1.6 Million U.S. Fatalities.

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  17 in total

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4.  Enhancing the Utility of the Health and Retirement Study (HRS) to Identify Drivers of Rising Mortality Rates in the United States.

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6.  The spatio-temporal distribution of naloxone administration events in rural Ohio 2010-16.

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7.  Heterogeneity in Prescription Opioid Pain Reliever Misuse Across Age Groups: 2015-2017 National Survey on Drug Use and Health.

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Review 8.  The Geography of Opioid Use Disorder: A Data Triangulation Approach.

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9.  Identifying counties at risk of high overdose mortality burden during the emerging fentanyl epidemic in the USA: a predictive statistical modelling study.

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10.  Trends and disparities in American Indian/Alaska Native unintentional injury mortality from 1999 to 2016.

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