Cannabis Recreational Legalization and Prevalence of Simultaneous Cannabis and Alcohol Use in the United States.

BACKGROUND: Simultaneous cannabis/alcohol use, using both substances within a short time interval so that their effects overlap, has a greater risk of potential negative consequences than single-substance use and is more common in younger age. Relationships between recreational cannabis laws (RCLs) and changes in simultaneous cannabis/alcohol use prevalence remain untested. OBJECTIVE: To examine trends in simultaneous cannabis/alcohol use from 2008 to 2019, and investigate associations between implementation of RCLs (i.e., presence of active legal dispensaries or legal home cultivation) and simultaneous cannabis/alcohol use in the United States (U.S.). DESIGN: Repeated cross-sectional samples from the 2008-2019 U.S. National Survey on Drug Use and Health (NSDUH). PARTICIPANTS: Respondents (51% female) aged 12 and older. INTERVENTIONS: Changes in simultaneous cannabis/alcohol use before and after RCL implementation (controlling for medical cannabis law implementation) were compared in different age groups (12-20, 21-30, 31-40, 41-50, 51+), using adjusted multi-level logistic regression with state random intercepts and an RCL/age group interaction. MEASUREMENTS: Self-reported simultaneous cannabis/alcohol use. RESULTS: From 2008 to 2019, the overall prevalence of simultaneous cannabis/alcohol use declined among those aged 12-20 but increased in adults aged 21+. Model-based simultaneous cannabis/alcohol use prevalence increased after RCL implementation among respondents aged 21-30 years (+1.2%; aOR= 1.15 [95%CI = 1.04-1.27]), 31-40 years (+1.0; 1.15 [1.04-1.27]), and 41-50 years (+1.75; 1.63 [1.34-1.98]), but not in individuals aged <21 or 51+ years. CONCLUSIONS: Implementation of recreational cannabis policies resulted in increased simultaneous use of cannabis and alcohol, supporting the complementarity hypothesis, but only among adults aged 21+. Efforts to minimize harms related to simultaneous cannabis/alcohol use are critical, especially in states with RCLs. Future studies should investigate cultural norms, perceived harm, and motives related to simultaneous use.

Association Between Marijuana Laws and Suicide Among 12- to 25-Year-Olds in the United States From 2000 to 2019.

OBJECTIVE: Cannabis use is associated with suicide-related outcomes in both adolescents and adults, and may be increasing amid shifting cannabis policies. However, little is known about the impact of medical marijuana legalization (MML) and recreational marijuana legalization (RML) policies on youth suicide. Using 20 years of national data, we examined associations between MML, RML, and suicide-related mortality among US individuals aged 12 to 25 years, and assessed whether they varied based on age and sex. METHOD: Suicide deaths (N = 113,512) from the 2000-2019 National Vital Statistics System Multiple Cause of Death files for age groups 12 to 13, 14 to 16, 17 to 19, 20 to 22, and 23 to 25 years were examined in relation to time-varying cannabis law status using a staggered adoption difference-in-difference (DiD) approach with a negative binomial regression to determine associations between MML, RML, and suicide rates, controlling for individual- and state-level covariates and accounting for the varying effective dates of MML and RML by state. RESULTS: The overall unadjusted annual suicide rate was 10.93/100,000, varying from 9.76 (states without marijuana laws (ML)) to 12.78 (MML states) to 16.68 (RML states). In multivariable analysis, both MML (incidence rate ratio [IRR] = 1.10, 95% CI: 1.05-1.15) and RML (IRR = 1.16, 95% CI: 1.06-1.27) were associated with higher suicide rates among female youth compared to those in states without ML. Youth aged 14 to 16 years had higher rates of suicide in states with RML compared to states with MML (IRR = 1.14, 95% CI: 1.00-1.30) and states without ML (IRR = 1.09, 95% CI: 1.00-1.20). Findings were consistent across sensitivity analyses. CONCLUSION: MML and RML were associated with increased suicide-related mortality in female youth and 14- to- 16-year-old individuals of both sexes. Mechanisms through which cannabis policies are related to increased youth suicide warrant further study and should inform legislative reform.

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

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: 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: 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: 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.

Cannabis and Alcohol Use by U.S. Young Adults, 2008-2019: Changes in Prevalence After Recreational Cannabis Legalization.

INTRODUCTION: Young adults' cannabis and alcohol use patterns have changed after state recreational cannabis legalization according to studies based on college samples but not nationally representative samples. Associations between recreational cannabis legalization and changes in cannabis and alcohol use outcomes among young adults were examined, including differences by college enrollment and minor status (ages 18-20 vs 21-23 years). METHODS: Repeated cross-sectional data (2008-2019) were collected from college-eligible participants aged 18-23 years in the National Survey on Drug Use and Health. Self-reported past-month cannabis use and frequent use (≥20 days) and a proxy for past-year DSM-5 cannabis use disorder were primary outcomes; past-month frequent alcohol use and binge drinking were secondary outcomes. Multilevel logistic regression models quantified changes in outcome prevalence from the study years before to after recreational cannabis legalization, adjusting for secular trends. Analyses were conducted on March 22, 2022. RESULTS: Prevalence increased from before to after recreational cannabis legalization for past-month cannabis use (from 21% to 25%) and past-year proxy cannabis use disorder (from 11% to 13%); the increases were statistically significant [adjusted odds ratio (95% CI) = 1.20 (1.08-1.32) and 1.14 (1.003-1.30), respectively]. Increases were detected for young adults who were not in college and who were aged 21-23 years. Recreational cannabis legalization impacts were not detected for secondary outcomes. CONCLUSIONS: Some young adults appear sensitive to state recreational cannabis legalization, including in terms of cannabis use disorder risk. Additional prevention efforts should be directed to young adults who are not in college and timed to occur before age 21 years.

Recreational cannabis legislation and binge drinking in U.S. adolescents and adults.

BACKGROUND: Recreational cannabis laws (RCLs) may have spillover effects on binge drinking. Our aims were to investigate binge drinking time trends and the association between RCLs and changes in binge drinking in the United States (U.S.). METHODS: We used restricted National Survey on Drug Use and Health data (2008-2019). We examined trends in the prevalence of past-month binge drinking by age groups (12-20, 21-30, 31-40, 41-50, 51+). Then, we compared model-based prevalences of past-month binge drinking before and after RCL by age group, using multi-level logistic regression with state random intercepts, an RCL by age group interaction term, and controlling for state alcohol policies. RESULTS: Binge drinking declined overall from 2008 to 2019 among people aged 12-20 (17.54% to 11.08%), and those aged 21-30 (43.66% to 40.22%). However, binge drinking increased among people aged 31+ (ages 31-40: 28.11% to 33.34%, ages 41-50: 25.48% to 28.32%, ages 51+: 13.28% to 16.75%). When investigating model-based prevalences after versus before RCL, binge drinking decreased among people aged 12-20 (prevalence difference=-4.8%; adjusted odds ratio (aOR)=0.77, [95% confidence interval (CI) 0.70-0.85]), and increased among participants aged 31-40 (+1.7%; 1.09[1.01-1.26]), 41-50 (+2.5; 1.15[1.05-1.26]) and 51+ (+1.8%; 1.17[1.06-1.30]). No RCL-related changes were noted in respondents ages 21-30. CONCLUSIONS: Implementation of RCLs was associated with increased past-month binge drinking in adults aged 31+ and decreased past-month binge drinking in those aged < 21. As the cannabis legislative landscape continues to change in the U.S., efforts to minimize harms related to binge drinking are critical.

Medical conditions of primary care patients with documented cannabis use and cannabis use disorder in electronic health records: a case control study from an academic health system in a medical marijuana state.

BACKGROUND: Approximately 3.8% of adults worldwide have used cannabis in the past year. Understanding how cannabis use is associated with other health conditions is crucial for healthcare providers seeking to understand the needs of their patients, and for health policymakers. This paper analyzes the relationship between documented cannabis use disorders (CUD), cannabis use (CU) and other health diagnoses among primary care patients during a time when medical use of marijuana was permitted by state law in California, United States of America. METHODS: The study utilized primary care electronic health record (EHR) data from an academic health system, using a case-control design to compare diagnoses among individuals with CUD/CU to those of matched controls, and those of individuals with CUD diagnoses with individuals who had CU otherwise documented. Associations of documented CU and CUD with general medical conditions and health conditions associated with cannabis use (both medical and behavioral) were analyzed using conditional logistic regression. RESULTS: Of 1,047,463 patients with ambulatory encounters from 2013-2017, 729 (0.06%) had CUD diagnoses and 3,731 (0.36%) had CU documented in their EHR. Patients with documented CUD and CU patients had significantly (p < 0.01) higher odds of most medical and behavioral diagnoses analyzed. Compared to matched controls, CUD-documented patients had highest odds of other substance use disorders (OR = 21.44: 95% CI 9.43-48.73), any mental health disorder (OR = 6.99; 95% CI 5.03-9.70) social anxiety disorder (OR = 13.03; 95% CI 2.18-77.94), HIV/AIDS (OR = 7.88: 95% CI 2.58-24.08), post-traumatic stress disorder (OR = 7.74: 95% CI 2.66-22.51); depression (OR = 7.01: 95% CI 4,79-10.27), and bipolar disorder (OR = 6.49: 95% CI 2.90-14.52). Compared to matched controls, CU-documented patients had highest odds of other substance use disorders (OR = 3.64; 95% CI 2.53-5.25) and post-traumatic stress disorder (OR = 3.41; 95% CI 2.53-5.25). CUD-documented patients were significantly more likely than CU-documented patients to have HIV/AIDS (OR = 6.70; 95% CI 2.10-21.39), other substance use disorder (OR = 5.88; 95% CI 2.42-14.22), depression (OR = 2.85; 95% CI 1.90-4.26), and anxiety (OR = 2.19: 95% CI 1.57-3.05) diagnoses. CONCLUSION: The prevalence of CUD and CU notation in EHR data from an academic health system was low, highlighting the need for improved screening in primary care. CUD and CU documentation were associated with increased risk for many health conditions, with the most elevated risk for behavioral health disorders and HIV/AIDS (among CUD-documented, but not CU-documented patients). Given the strong associations of CUD and CU documentation with health problems, it is important for healthcare providers to be prepared to identify CU and CUD, discuss the pros and cons of cannabis use with patients thoughtfully and empathically, and address cannabis-related comorbidities among these patients.

Rating the comparative efficacy of state-level cannabis policies on recreational cannabis markets in the United States.

BACKGROUND: Cannabis policy is developing faster than empirical evidence about policy effects. With a panel of experts in substance use policy development and research, we identified key cannabis policies and their provisions enacted by U.S. states; rated their theoretical efficacy in a restrictive form for reducing problematic use and impaired driving in the context of a recreational cannabis market as judged by experts; and rated the strength of evidence for each policy. METHODS: Using a modified Delphi approach, 9 panelists rated the comparative efficacy of 18 state cannabis policies for reducing youth use of cannabis, excessive cannabis use among the general population, and cannabis-impaired driving. Each outcome was rated separately using a Likert scale, and panelists also rated the strength of evidence supporting each efficacy rating. Investigators provided descriptions of each policy so that the nine panelists had similar conceptions of each policy. RESULTS: State monopoly (state owns all production, manufacturing, wholesale, and retail operations) was rated as the most effective policy for all three outcome areas. Restrictions on retail physical availability, taxes, retail price restrictions, and retail operations restrictions were also highly rated for all three outcomes. Policies regulating cannabis businesses and products were judged more effective than policies targeting consumer use and behavior. Panelists reported there was little or no direct evidence from the cannabis policy literature for most of the included policies. CONCLUSION: These ratings can facilitate research as well as policy-making decisions. A relatively small number of policies were judged to be highly effective across all three domains, indicating that for the most part adult excessive use, youth use, and impaired driving can all be reduced with the same set of policies; these policies tended to target the behaviors of businesses rather than consumers. The low levels of direct evidence available to inform policy ratings, as reported by the policy panelists, makes clear the need for ongoing and sustained cannabis policy research.

Medical marijuana laws and adolescent marijuana use in the United States: a systematic review and meta-analysis.

AIMS: To conduct a systematic review and meta-analysis of studies in order to estimate the effect of US medical marijuana laws (MMLs) on past-month marijuana use prevalence among adolescents. METHODS: A total of 2999 papers from 17 literature sources were screened systematically. Eleven studies, developed from four ongoing large national surveys, were meta-analyzed. Estimates of MML effects on any past-month marijuana use prevalence from included studies were obtained from comparisons of pre-post MML changes in MML states to changes in non-MML states over comparable time-periods. These estimates were standardized and entered into a meta-analysis model with fixed-effects for each study. Heterogeneity among the study estimates by national data survey was tested with an omnibus F-test. Estimates of effects on additional marijuana outcomes, of MML provisions (e.g. dispensaries) and among demographic subgroups were abstracted and summarized. Key methodological and modeling characteristics were also described. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. RESULTS: None of the 11 studies found significant estimates of pre-post MML changes compared with contemporaneous changes in non-MML states for marijuana use prevalence among adolescents. The meta-analysis yielded a non-significant pooled estimate (standardized mean difference) of -0.003 (95% confidence interval = -0.012, +0.007). Four studies compared MML with non-MML states on pre-MML differences and all found higher rates of past-month marijuana use in MML states pre-MML passage. Additional tests of specific MML provisions, of MML effects on additional marijuana outcomes and among subgroups generally yielded non-significant results, although limited heterogeneity may warrant further study. CONCLUSIONS: Synthesis of the current evidence does not support the hypothesis that US medical marijuana laws (MMLs) until 2014 have led to increases in adolescent marijuana use prevalence. Limited heterogeneity exists among estimates of effects of MMLs on other patterns of marijuana use, of effects within particular population subgroups and of effects of specific MML provisions.