Opioid-related mortality: Dynamic temporal and spatial trends by drug type and demographic subpopulations, Massachusetts, 2005-2021.


Journal

Drug and alcohol dependence
ISSN: 1879-0046
Titre abrégé: Drug Alcohol Depend
Pays: Ireland
ID NLM: 7513587

Informations de publication

Date de publication:
01 05 2023
Historique:
received: 13 01 2023
revised: 03 03 2023
accepted: 06 03 2023
pmc-release: 01 05 2024
medline: 25 4 2023
pubmed: 18 3 2023
entrez: 17 3 2023
Statut: ppublish

Résumé

Fatal opioid-related overdoses (OOD) present significant public health challenges. Intuitive and replicable analytical approaches are needed to inform targeted public health responses. We obtained fatal OOD data for 2005-2021 from the Massachusetts Registry of Vital Records and Statistics. We conducted heatmap analyses to assess trends in fatal OOD rates per 100,000 residents, visualizing rates by death year and decedent age at one-year intervals, stratifying by race/ethnicity, sex, rurality, and involved substances. We calculated Getis-Ord Gi* statistics to identify spatial clusters of OOD rates. Among 20,774 fatal OODs, rates were higher among males, and highly variable by race/ethnicity, age group, and rurality. While fatal OOD rates increased in urban before rural communities, rates were higher in rural communities by 2018-2019. Stimulant-related fatal OODs were elevated in 2020 and 2021. Fatal OOD rates involving fentanyl and stimulants increased precipitously and simultaneously in the non-Hispanic Black population in 2020 and 2021, with a bimodal age distribution peaking among those in their 40s and 60s. Elevated rates among 30-to-60 year old Hispanic residents were largely tied to synthetic opioids from 2015 to 2021. Spatial clusters were detected for prescription opioids, heroin, and stimulants in western Massachusetts. For synthetic opioids, hotspots became more ubiquitous across the state from 2016 to 2021, intensifying in southeastern Massachusetts. Our novel approach uncovered new time varying and spatial patterns in fatal OOD rates not previously reported. Identified shifts in fatal OOD rates by sex, age, and race/ethnicity can inform location-specific field actions targeting subpopulations at disproportionally high risk.

Sections du résumé

BACKGROUND
Fatal opioid-related overdoses (OOD) present significant public health challenges. Intuitive and replicable analytical approaches are needed to inform targeted public health responses.
METHODS
We obtained fatal OOD data for 2005-2021 from the Massachusetts Registry of Vital Records and Statistics. We conducted heatmap analyses to assess trends in fatal OOD rates per 100,000 residents, visualizing rates by death year and decedent age at one-year intervals, stratifying by race/ethnicity, sex, rurality, and involved substances. We calculated Getis-Ord Gi* statistics to identify spatial clusters of OOD rates.
RESULTS
Among 20,774 fatal OODs, rates were higher among males, and highly variable by race/ethnicity, age group, and rurality. While fatal OOD rates increased in urban before rural communities, rates were higher in rural communities by 2018-2019. Stimulant-related fatal OODs were elevated in 2020 and 2021. Fatal OOD rates involving fentanyl and stimulants increased precipitously and simultaneously in the non-Hispanic Black population in 2020 and 2021, with a bimodal age distribution peaking among those in their 40s and 60s. Elevated rates among 30-to-60 year old Hispanic residents were largely tied to synthetic opioids from 2015 to 2021. Spatial clusters were detected for prescription opioids, heroin, and stimulants in western Massachusetts. For synthetic opioids, hotspots became more ubiquitous across the state from 2016 to 2021, intensifying in southeastern Massachusetts.
CONCLUSION
Our novel approach uncovered new time varying and spatial patterns in fatal OOD rates not previously reported. Identified shifts in fatal OOD rates by sex, age, and race/ethnicity can inform location-specific field actions targeting subpopulations at disproportionally high risk.

Identifiants

pubmed: 36931131
pii: S0376-8716(23)00074-1
doi: 10.1016/j.drugalcdep.2023.109836
pmc: PMC10121848
mid: NIHMS1885749
pii:
doi:

Substances chimiques

Analgesics, Opioid 0
Fentanyl UF599785JZ

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

109836

Subventions

Organisme : NIDA NIH HHS
ID : R01 DA054267
Pays : United States

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Conflict of interest No conflict declared.

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Auteurs

Thomas J Stopka (TJ)

Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States. Electronic address: thomas.stopka@tufts.edu.

Marc R Larochelle (MR)

Clinical Addiction Research and Education Unit, Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine and Boston Medical Center, United States.

Xiaona Li (X)

Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States.

Dana Bernson (D)

Office of Population Health, Department of Public Health, Commonwealth of Massachusetts, Boston, MA, United States.

Wenjun Li (W)

Center for Health Statistics and Department of Public Health, University of Massachusetts Lowell, Lowell, MA, United States.

Leland K Ackerson (LK)

Center for Health Statistics and Department of Public Health, University of Massachusetts Lowell, Lowell, MA, United States.

Ric Bayly (R)

Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States.

Olaf Dammann (O)

Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States; Department of Gynecology and Obstetrics, Hannover Medical School, Hannover, Germany.

Cici Bauer (C)

Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States.

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Classifications MeSH