Intersectional inequities and longitudinal prevalence estimates of opioid use disorder in Massachusetts 2014-2020: a multi-sample capture-recapture analysis.
Capture-recapture
Health disparities
Healthcare based surveillance data
Opioid use disorder
Population size estimation
Journal
Lancet regional health. Americas
ISSN: 2667-193X
Titre abrégé: Lancet Reg Health Am
Pays: England
ID NLM: 9918232503006676
Informations de publication
Date de publication:
Apr 2024
Apr 2024
Historique:
received:
17
09
2023
revised:
18
02
2024
accepted:
20
02
2024
medline:
21
3
2024
pubmed:
21
3
2024
entrez:
21
3
2024
Statut:
epublish
Résumé
As overdoses continue to increase worldwide, accurate estimates are needed to understand the size of the population at risk and address health disparities. Capture-recapture methods may be used in place of direct estimation at nearly any geographic level (e.g., city, state, country) to estimate the size of the population with opioid use disorder (OUD). We performed a multi-sample capture-recapture analysis with persons aged 18-64 years to estimate the prevalence of OUD in Massachusetts from 2014 to 2020, stratified by sex and race/ethnicity. We used seven statewide administrative data sources linked at the individual level. We developed log-linear models to estimate the unknown OUD-affected population. Uncertainty was characterized using 95% confidence intervals (95% CI) on the total counts and prevalence estimates. The estimated OUD prevalence increased from 5.47% (95% CI = 4.89%, 5.98%) in 2014 to 5.79% (95% CI = 5.34%, 6.19%) in 2020. Prevalence among Hispanic females doubled (2.46% in 2014 to 4.23% in 2020) and prevalence rose to nearly 10% among Black non-Hispanic males and Hispanic males from 2014 through 2019. Estimates for Black non-Hispanic females more than doubled from 2014 through 2019 (3.39% to 7.09%), and then decreased to 5.69% in 2020. This study is the first to provide OUD prevalence trend estimates by binary sex and race/ethnicity at a state level using capture-recapture methods. Using these methods as the international overdose crisis worsens can allow jurisdictions to appropriately allocate resources and targeted interventions to marginalised populations. NIDA.
Sections du résumé
Background
UNASSIGNED
As overdoses continue to increase worldwide, accurate estimates are needed to understand the size of the population at risk and address health disparities. Capture-recapture methods may be used in place of direct estimation at nearly any geographic level (e.g., city, state, country) to estimate the size of the population with opioid use disorder (OUD). We performed a multi-sample capture-recapture analysis with persons aged 18-64 years to estimate the prevalence of OUD in Massachusetts from 2014 to 2020, stratified by sex and race/ethnicity.
Methods
UNASSIGNED
We used seven statewide administrative data sources linked at the individual level. We developed log-linear models to estimate the unknown OUD-affected population. Uncertainty was characterized using 95% confidence intervals (95% CI) on the total counts and prevalence estimates.
Findings
UNASSIGNED
The estimated OUD prevalence increased from 5.47% (95% CI = 4.89%, 5.98%) in 2014 to 5.79% (95% CI = 5.34%, 6.19%) in 2020. Prevalence among Hispanic females doubled (2.46% in 2014 to 4.23% in 2020) and prevalence rose to nearly 10% among Black non-Hispanic males and Hispanic males from 2014 through 2019. Estimates for Black non-Hispanic females more than doubled from 2014 through 2019 (3.39% to 7.09%), and then decreased to 5.69% in 2020.
Interpretation
UNASSIGNED
This study is the first to provide OUD prevalence trend estimates by binary sex and race/ethnicity at a state level using capture-recapture methods. Using these methods as the international overdose crisis worsens can allow jurisdictions to appropriately allocate resources and targeted interventions to marginalised populations.
Funding
UNASSIGNED
NIDA.
Identifiants
pubmed: 38510791
doi: 10.1016/j.lana.2024.100709
pii: S2667-193X(24)00036-X
pmc: PMC10951507
doi:
Types de publication
Journal Article
Langues
eng
Pagination
100709Informations de copyright
© 2024 The Authors.
Déclaration de conflit d'intérêts
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dr. White reports grant support for the research presented in this manuscript, which was paid to her respective institution. Dr. Kline reports grant support from National Institute on Drug Abuse for the research presented in this manuscript (R01DA052214). Dr. Barocas also reports membership on the scientific advisory committee for eMed. All other authors have declared that no financial support was received for the research of this manuscript and that there are no financial interests or personal relationships which have, or could be perceived to have, influenced the work reported in this paper.