Associations between cannabis policies and state-level specialty cannabis use disorder treatment in the United States, 2004-2019.

Cannabis Cannabis policy Medical cannabis law Policy Recreational cannabis law Treatment

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 Apr 2024
Historique:
received: 08 08 2023
revised: 23 01 2024
accepted: 26 01 2024
pubmed: 22 2 2024
medline: 22 2 2024
entrez: 21 2 2024
Statut: ppublish

Résumé

Cannabis use disorder (CUD) treatment prevalence decreased in the US between 2002 and 2019, yet structural mechanisms for this decrease are poorly understood. We tested associations between cannabis laws becoming effective and self-reported CUD treatment. Restricted-use 2004-2019 National Surveys on Drug Use and Health included people ages 12+ classified as needing CUD treatment (i.e., past-year DSM-5-proxy CUD or last/current specialty treatment for cannabis). Time-varying indicators of medical cannabis laws (MCL) with/without cannabis dispensary provisions differentiated state-years before/after laws using effective dates. Multi-level logistic regressions with random state intercepts estimated individual- and state-adjusted CUD treatment odds by MCLs and model-based changes in specialty CUD treatment state-level prevalence. Secondary analyses tested associations between CUD treatment and MCL or recreational cannabis laws (RCL). Using a broad treatment need sample definition in 2004-2014, specialty CUD treatment prevalence decreased by 1.35 (95 % CI = -2.51, -0.18) points after MCL without dispensaries and by 2.15 points (95 % CI = -3.29, -1.00) after MCL with dispensaries provisions became effective, compared to before MCL. Among people with CUD in 2004-2014, specialty treatment decreased only in MCL states with dispensary provisions (aPD = -0.91, 95 % CI = -1.68, -0.13). MCL were not associated with CUD treatment use in 2015-2019. RCL were associated with lower CUD treatment among people classified as needing CUD treatment, but not among people with past-year CUD. Policy-related reductions in specialty CUD treatment were concentrated in states with cannabis dispensary provisions in 2004-2014, but not 2015-2019, and partly driven by reductions among people without past-year CUD. Other mechanisms (e.g., CUD symptom identification, criminal-legal referrals) could contribute to decreasing treatment trends.

Sections du résumé

BACKGROUND BACKGROUND
Cannabis use disorder (CUD) treatment prevalence decreased in the US between 2002 and 2019, yet structural mechanisms for this decrease are poorly understood. We tested associations between cannabis laws becoming effective and self-reported CUD treatment.
METHODS METHODS
Restricted-use 2004-2019 National Surveys on Drug Use and Health included people ages 12+ classified as needing CUD treatment (i.e., past-year DSM-5-proxy CUD or last/current specialty treatment for cannabis). Time-varying indicators of medical cannabis laws (MCL) with/without cannabis dispensary provisions differentiated state-years before/after laws using effective dates. Multi-level logistic regressions with random state intercepts estimated individual- and state-adjusted CUD treatment odds by MCLs and model-based changes in specialty CUD treatment state-level prevalence. Secondary analyses tested associations between CUD treatment and MCL or recreational cannabis laws (RCL).
RESULTS RESULTS
Using a broad treatment need sample definition in 2004-2014, specialty CUD treatment prevalence decreased by 1.35 (95 % CI = -2.51, -0.18) points after MCL without dispensaries and by 2.15 points (95 % CI = -3.29, -1.00) after MCL with dispensaries provisions became effective, compared to before MCL. Among people with CUD in 2004-2014, specialty treatment decreased only in MCL states with dispensary provisions (aPD = -0.91, 95 % CI = -1.68, -0.13). MCL were not associated with CUD treatment use in 2015-2019. RCL were associated with lower CUD treatment among people classified as needing CUD treatment, but not among people with past-year CUD.
CONCLUSIONS CONCLUSIONS
Policy-related reductions in specialty CUD treatment were concentrated in states with cannabis dispensary provisions in 2004-2014, but not 2015-2019, and partly driven by reductions among people without past-year CUD. Other mechanisms (e.g., CUD symptom identification, criminal-legal referrals) could contribute to decreasing treatment trends.

Identifiants

pubmed: 38382162
pii: S0376-8716(24)00034-6
doi: 10.1016/j.drugalcdep.2024.111113
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

111113

Subventions

Organisme : NIDA NIH HHS
ID : K01 DA049950
Pays : United States
Organisme : NIDA NIH HHS
ID : R01 DA048860
Pays : United States
Organisme : NIDA NIH HHS
ID : K01 DA045224
Pays : United States
Organisme : NIDA NIH HHS
ID : R36 DA058180
Pays : United States
Organisme : NIDA NIH HHS
ID : T32 DA031099
Pays : United States
Organisme : NIDA NIH HHS
ID : R01 DA037866
Pays : United States

Informations de copyright

Copyright © 2024. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

Conflict of interest Dr. H. Samples has received consulting fees from the American Society of Addiction Medicine and The Pew Charitable Trusts; other authors report no potential conflicts of interest.

Auteurs

Pia M Mauro (PM)

Department of Epidemiology, Columbia University Mailman School of Public Health, United States. Electronic address: pm2838@cumc.columbia.edu.

Sarah Gutkind (S)

Department of Epidemiology, Columbia University Mailman School of Public Health, United States.

Melanie S Askari (MS)

Department of Epidemiology, Columbia University Mailman School of Public Health, United States.

Deborah S Hasin (DS)

Department of Epidemiology, Columbia University Mailman School of Public Health, United States; New York State Psychiatric Institute, United States.

Hillary Samples (H)

Center for Pharmacoepidemiology and Treatment Science, Rutgers Institute for Health, Health Care Policy and Aging Research, United States; Department of Health Behavior, Society & Policy, Rutgers University School of Public Health, United States.

Christine M Mauro (CM)

Department of Biostatistics, Columbia University Mailman School of Public Health, United States.

Erin M Annunziato (EM)

Department of Epidemiology, Columbia University Mailman School of Public Health, United States.

Anne E Boustead (AE)

School of Government & Public Policy, University of Arizona, United States.

Silvia S Martins (SS)

Department of Epidemiology, Columbia University Mailman School of Public Health, United States.

Classifications MeSH