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Suspected heroin-related overdoses incidents in Cincinnati, Ohio: A spatiotemporal analysis

BACKGROUND: Opioid misuse and deaths are increasing in the United States. In 2017, Ohio had the second highest overdose rates in the US, with the city of Cincinnati experiencing a 50% rise in opioid overdoses since 2015. Understanding the temporal and geographic variation in overdose emergencies may...

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Autores principales: Li, Zehang Richard, Xie, Evaline, Crawford, Forrest W., Warren, Joshua L., McConnell, Kathryn, Copple, J. Tyler, Johnson, Tyler, Gonsalves, Gregg S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6850525/
https://www.ncbi.nlm.nih.gov/pubmed/31714940
http://dx.doi.org/10.1371/journal.pmed.1002956
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author Li, Zehang Richard
Xie, Evaline
Crawford, Forrest W.
Warren, Joshua L.
McConnell, Kathryn
Copple, J. Tyler
Johnson, Tyler
Gonsalves, Gregg S.
author_facet Li, Zehang Richard
Xie, Evaline
Crawford, Forrest W.
Warren, Joshua L.
McConnell, Kathryn
Copple, J. Tyler
Johnson, Tyler
Gonsalves, Gregg S.
author_sort Li, Zehang Richard
collection PubMed
description BACKGROUND: Opioid misuse and deaths are increasing in the United States. In 2017, Ohio had the second highest overdose rates in the US, with the city of Cincinnati experiencing a 50% rise in opioid overdoses since 2015. Understanding the temporal and geographic variation in overdose emergencies may help guide public policy responses to the opioid epidemic. METHODS AND FINDINGS: We used a publicly available data set of suspected heroin-related emergency calls (n = 6,246) to map overdose incidents to 280 census block groups in Cincinnati between August 1, 2015, and January 30, 2019. We used a Bayesian space-time Poisson regression model to examine the relationship between demographic and environmental characteristics and the number of calls within block groups. Higher numbers of heroin-related incidents were found to be associated with features of the built environment, including the proportion of parks (relative risk [RR] = 2.233; 95% credible interval [CI]: [1.075–4.643]), commercial (RR = 13.200; 95% CI: [4.584–38.169]), manufacturing (RR = 4.775; 95% CI: [1.958–11.683]), and downtown development zones (RR = 11.362; 95% CI: [3.796–34.015]). The number of suspected heroin-related emergency calls was also positively associated with the proportion of male population, the population aged 35–49 years, and distance to pharmacies and was negatively associated with the proportion aged 18–24 years, the proportion of the population with a bachelor's degree or higher, median household income, the number of fast food restaurants, distance to hospitals, and distance to opioid treatment programs. Significant spatial and temporal heterogeneity in the risks of incidents remained after adjusting for covariates. Limitations of this study include lack of information about the nature of incidents after dispatch, which may differ from the initial classification of being related to heroin, and lack of information on local policy changes and interventions. CONCLUSIONS: We identified areas with high numbers of reported heroin-related incidents and features of the built environment and demographic characteristics that are associated with these events in the city of Cincinnati. Publicly available information about opiate overdoses, combined with data on spatiotemporal risk factors, may help municipalities plan, implement, and target harm-reduction measures. In the US, more work is necessary to improve data availability in other cities and states and the compatibility of data from different sources in order to adequately measure and monitor the risk of overdose and inform health policies.
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spelling pubmed-68505252019-11-22 Suspected heroin-related overdoses incidents in Cincinnati, Ohio: A spatiotemporal analysis Li, Zehang Richard Xie, Evaline Crawford, Forrest W. Warren, Joshua L. McConnell, Kathryn Copple, J. Tyler Johnson, Tyler Gonsalves, Gregg S. PLoS Med Research Article BACKGROUND: Opioid misuse and deaths are increasing in the United States. In 2017, Ohio had the second highest overdose rates in the US, with the city of Cincinnati experiencing a 50% rise in opioid overdoses since 2015. Understanding the temporal and geographic variation in overdose emergencies may help guide public policy responses to the opioid epidemic. METHODS AND FINDINGS: We used a publicly available data set of suspected heroin-related emergency calls (n = 6,246) to map overdose incidents to 280 census block groups in Cincinnati between August 1, 2015, and January 30, 2019. We used a Bayesian space-time Poisson regression model to examine the relationship between demographic and environmental characteristics and the number of calls within block groups. Higher numbers of heroin-related incidents were found to be associated with features of the built environment, including the proportion of parks (relative risk [RR] = 2.233; 95% credible interval [CI]: [1.075–4.643]), commercial (RR = 13.200; 95% CI: [4.584–38.169]), manufacturing (RR = 4.775; 95% CI: [1.958–11.683]), and downtown development zones (RR = 11.362; 95% CI: [3.796–34.015]). The number of suspected heroin-related emergency calls was also positively associated with the proportion of male population, the population aged 35–49 years, and distance to pharmacies and was negatively associated with the proportion aged 18–24 years, the proportion of the population with a bachelor's degree or higher, median household income, the number of fast food restaurants, distance to hospitals, and distance to opioid treatment programs. Significant spatial and temporal heterogeneity in the risks of incidents remained after adjusting for covariates. Limitations of this study include lack of information about the nature of incidents after dispatch, which may differ from the initial classification of being related to heroin, and lack of information on local policy changes and interventions. CONCLUSIONS: We identified areas with high numbers of reported heroin-related incidents and features of the built environment and demographic characteristics that are associated with these events in the city of Cincinnati. Publicly available information about opiate overdoses, combined with data on spatiotemporal risk factors, may help municipalities plan, implement, and target harm-reduction measures. In the US, more work is necessary to improve data availability in other cities and states and the compatibility of data from different sources in order to adequately measure and monitor the risk of overdose and inform health policies. Public Library of Science 2019-11-12 /pmc/articles/PMC6850525/ /pubmed/31714940 http://dx.doi.org/10.1371/journal.pmed.1002956 Text en © 2019 Li et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Li, Zehang Richard
Xie, Evaline
Crawford, Forrest W.
Warren, Joshua L.
McConnell, Kathryn
Copple, J. Tyler
Johnson, Tyler
Gonsalves, Gregg S.
Suspected heroin-related overdoses incidents in Cincinnati, Ohio: A spatiotemporal analysis
title Suspected heroin-related overdoses incidents in Cincinnati, Ohio: A spatiotemporal analysis
title_full Suspected heroin-related overdoses incidents in Cincinnati, Ohio: A spatiotemporal analysis
title_fullStr Suspected heroin-related overdoses incidents in Cincinnati, Ohio: A spatiotemporal analysis
title_full_unstemmed Suspected heroin-related overdoses incidents in Cincinnati, Ohio: A spatiotemporal analysis
title_short Suspected heroin-related overdoses incidents in Cincinnati, Ohio: A spatiotemporal analysis
title_sort suspected heroin-related overdoses incidents in cincinnati, ohio: a spatiotemporal analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6850525/
https://www.ncbi.nlm.nih.gov/pubmed/31714940
http://dx.doi.org/10.1371/journal.pmed.1002956
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