TY - JOUR
T1 - Using census data to understand county-level differences in overall drug mortality and opioid-related mortality by opioid type
AU - Monnat, Shannon M.
AU - Peters, David J.
AU - Berg, Mark T.
AU - Hochstetler, Andrew
N1 - Publisher Copyright:
© 2019 American Public Health Association Inc.. All rights reserved.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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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U2 - 10.2105/AJPH.2019.305136
DO - 10.2105/AJPH.2019.305136
M3 - Article
C2 - 31219718
AN - SCOPUS:85068704443
SN - 0090-0036
VL - 109
SP - 1084
EP - 1091
JO - American Journal of Public Health
JF - American Journal of Public Health
IS - 8
ER -