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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). 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. 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. 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. [ABSTRACT FROM AUTHOR]

In their seminal 2002 paper, "Causal Knowledge as a Prerequisite for Confounding Evaluation: An Application to Birth Defects Epidemiology," Hernán et al. (Am J Epidemiol. 2002;155(2):176–184) emphasized the importance of using theory rather than data to guide confounding control, focusing on colliders as variables that share characteristics with confounders but whose control may actually introduce bias into analyses. In this commentary, we propose that the importance of this paper stems from the connection the authors made between nonexchangeability as the ultimate source of bias and structural representations of bias using directed acyclic graphs. This provided both a unified approach to conceptualizing bias and a means of distinguishing between different sources of bias, particularly confounding and selection bias. Drawing on examples from the paper, we also highlight unresolved questions about the relationship between collider bias, selection bias, and generalizability and argue that causal knowledge is a prerequisite not only for identifying confounders but also for developing any hypothesis about potential sources of bias. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Purpose: To outline a method for obtaining more accurate estimates of drug use in the United States (US) general population by correcting survey data for underreported and unknown drug use.Methods: We simulated a population (n = 100,000) reflecting the demographics of the US adult population per the 2018 American Community Survey. Within this population, we simulated the "true" and self-reported prevalence of past-month cannabis and cocaine use by using available estimates of underreporting. We applied our algorithm to samples of the simulated population to correct self-reported estimates and recover the "true" population prevalence, validating our approach. We applied this same method to 2018 National Survey on Drug Use and Health (NSDUH) data to produce a range of underreporting-corrected estimates.Results: Simulated self-report sensitivities varied by drug and sampling method (cannabis: 77.6%-78.5%, cocaine: 14.3%-22.1%). Across repeated samples, mean corrected prevalences (calculated by dividing self-reported prevalence by estimated sensitivity) closely approximated simulated "true" prevalences. Applying our algorithm substantially increased 2018 NSDUH estimates (self-report: cannabis = 10.5%, cocaine = 0.8%; corrected: cannabis = 15.6%-16.6%, cocaine = 2.7%-5.5%).Conclusions: National drug use prevalence estimates can be corrected for underreporting using a simple method. However, valid application of this method requires accurate data on the extent and correlates of misclassification in the general US population. [ABSTRACT FROM AUTHOR]

Cannabis use has been more prevalent among men than women and prior work has found differing impact of recreational cannabis laws (RCL) by age. We examined changes in the prevalence of past-year and past-month cannabis use, past-month daily cannabis use, and DSM-5-proxy cannabis use disorder (CUD) in the past-year before and after RCL enactment by gender alone and stratified by age using 2008–2017 repeated cross-sectional samples of the US National Survey on Drug Use and Health. Changes in cannabis outcomes were estimated using adjusted multi-level logistic regression with state random intercepts and two-way and three-way interactions between RCL, gender, and age group. Enactment of RCL was associated with higher increases in the past-year (+ 3.2%; aOR = 1.30 [95%CI = 1.19 to 1.41]) and past-month (+ 2.3; 1.37 [1.24 to 1.51]) cannabis use in women than men (+ 2.1%; 1.15 [1.06 to 1.25] and + 1.7%; 1.19 [1.08 to 1.30]). No increases in past-month daily cannabis use and past-year DSM-5 CUD among those using cannabis were observed after RCL enactment. There were no increases in any cannabis outcomes after RCL enactment among those 12–20 years old. RCL enactment may contribute to the narrowing of the cannabis gender gap. Ongoing surveillance is essential to ensure that the social justice aims of legalization are achieved without negative public health consequences. [ABSTRACT FROM AUTHOR]

The impact of state-level medical cannabis laws (MCL) on individual-level opioid outcomes is inconclusive. We analyzed representative samples of U.S. adults ≥ 21 years reporting past-year non-medical prescription opioid (NMPO) use in the 2004–2014 National Surveys on Drug Use and Health. Multi-level mixed effects models estimated associations of state-level MCL with individual-level NMPO use frequency, categorized as occasional (1–12 days), regular (13–52 days), or frequent (53–365 days). Further analyses stratified by past-year cannabis use and disorder (no use, use only, DSM-IV cannabis use disorder). MCL was associated with increases in occasional NMPO use (2.1% points, 95% CI: 0.5, 3.8) alongside reductions in regular (-0.6% points, 95% CI: -1.1, -0.1) and frequent NMPO use (-1.5% points, 95% CI: -2.7, -0.4). In stratified analyses, significant changes were observed only for adults with cannabis use disorder, including increases in occasional NMPO use (5.6% points, 95% CI: 1.5, 9.6) and decreases in frequent NMPO use (-4.9% points, 95% CI: -8.1, -1.8). The association of MCL with lower frequency of NMPO use was driven by individuals with cannabis use disorder, highlighting the importance of identifying tradeoffs of cannabis legalization as an intervention to reduce opioid-related harms. [ABSTRACT FROM AUTHOR]

Cannabis use and binge drinking are increasingly common in the United States, yet little is known about cannabis use patterns among people who engage in binge drinking. This study explored the relationship between several cannabis use outcomes and past-month binge drinking status. Pooled 2015-2018 National Surveys on Drug Use and Health data (N = 226,632) were used to explore the hypothesis that binge drinking is associated with higher prevalence of cannabis outcomes. Cannabis outcomes included past-month and past-year use, daily/almost daily use, and past-year DSM-IV/DSM-5 cannabis use disorder (CUD). Covariates included age, gender, race, total income, and study year. Separate weighted multivariable logistic regressions assessed associations between binge drinking and each cannabis outcome and provided adjusted prevalences of cannabis outcomes by binge drinking status. Past-month binge drinking was positively associated with past-month (OR: 3.72, 95 %CI: 3.56-3.93) and past-year (OR: 3.90, 95 %CI: 3.74-4.06) cannabis use in adjusted regressions. The adjusted odds of DSM-IV and DSM-5 CUD among people who used cannabis were 15 % and 12 % higher among people who engaged in binge drinking than those who did not, respectively (OR: 1.15, 95 %CI: 1.05, 1.26 and OR: 1.12, 95 %CI: 1.03, 1.21). Conversely, the odds of past-month daily cannabis use among people who used cannabis and reported binge drinking was 18 % lower than those who did not (OR: 0.82, 95 %CI: 0.74, 0.91). Our findings provide evidence of associations between binge drinking and cannabis use. Future studies should explore associations between cannabis and other alcohol use behaviors, including heavy drinking, and simultaneous alcohol and cannabis use. [ABSTRACT FROM AUTHOR]

Background: Prior work suggests that perceived risk and perceived availability of cannabis independently affect cannabis use. However, perceived risk likely modifies the effect of perceived availability, and vice versa. This study explored trends in joint perceived risk and availability of cannabis from 2002 to 2018 and the relationship between combined perceptions and cannabis use, frequent use, and cannabis use disorder (CUD).Methods: National Surveys on Drug Use and Health data (n = 949,285, ages 12+) were used to create combined categories of perceived risk of weekly cannabis use and perceived cannabis availability. Descriptive analyses compared joint perceived risk/availability trends (pre/post-2015 due to survey redesign) overall and stratified by age, gender, past-year cannabis use, frequent use, and CUD. Regression analysis estimated associations between perceived risk/availability and cannabis outcomes.Results: From 2002 to 2018, the prevalence of perceiving cannabis as low-risk doubled while perceiving cannabis as available remained unchanged. The proportion of individuals perceiving cannabis as Low-risk/Available increased by 86% from 2002 to 2014 (16.8%-31.2%) and 19% from 2015 to 2018 (30.1%-35.8%) while High-risk/Available and High-risk/Unavailable proportions declined. Differing patterns were observed by age and gender. Compared with individuals perceiving cannabis as High-risk/Unavailable, people in all other perception categories had greater risk of all cannabis outcomes. Results were consistent with additive interaction between perceived risk and availability in their effects on cannabis use.Conclusions: Trends and associations with cannabis outcomes differ when considering perceived risk and availability independently versus jointly. Longitudinal studies and cannabis policy evaluations would advance understanding of links between cannabis perceptions and use. [ABSTRACT FROM AUTHOR]

Background: Cannabis use disorder (CUD) prevalence among people reporting past-year cannabis use declined from 2002-2016. We examined whether similar reductions in CUD were observed among people reporting daily/almost daily cannabis use. We expected that CUD prevalence among people reporting daily/almost daily use would not decrease.Methods: We used 2002-2016 National Survey on Drug Use and Health (NSDUH) data, including 22,651 individuals using cannabis 300+ days in the past year. CUD was defined using DSM-IV criteria for cannabis abuse and/or dependence. Age categories included: 12-17, 18-25, and 26 + . Annual prevalence of CUD, cannabis dependence, cannabis abuse, and each individual abuse/dependence items accounted for the complex survey design. Differences in trends over time were examined by age group.Results: From 2002-2016, the prevalence of CUD among people reporting daily/almost daily cannabis use decreased by 26.8% in adolescents, by 29.7% in ages 18-25, and by 37.5% in ages 26 + . Prevalence of DSM-IV cannabis dependence decreased significantly among adolescents (-43.9%) and young adults (-26.8%) but remained stable in adults 26 + . Reductions in most dependence items were observed in young adults, with less consistent patterns in adolescents and adults 26 + . Prevalence of DSM-IV cannabis abuse decreased overall and for each abuse item across all age groups.Conclusions: Contrary to expectations, CUD prevalence decreased significantly across all ages reporting daily/almost daily cannabis use between 2002-2016. Cannabis dependence prevalence decreased for adolescents and young adults and was stable only among adults ages 26+ reporting daily/almost daily cannabis use. Potential drivers of this decrease should be further explored. [ABSTRACT FROM AUTHOR]

• Decreases in binge drinking in youth <21 after Recreational Cannabis Laws (RCLs). • Increases in binge drinking in adults 31+ were noted after RCLs. • There was no association between binge drinking and RCLs in adults aged 21-30 years. • Findings support complementary hypotheses in adults after RCLs. 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.). 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. 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. 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. [ABSTRACT FROM AUTHOR]