Columbia University, New York, NY, USA.
Addiction. 2017 Nov;112(11):1985-1991. doi: 10.1111/add.13904. Epub 2017 Jul 17.
Most US states have passed medical marijuana laws (MMLs), with great variation in program regulation impacting enrollment rates. We aimed to compare changes in rates of marijuana use, heavy use and cannabis use disorder across age groups while accounting for whether states enacted medicalized (highly regulated) or non-medical mml programs.
Difference-in-differences estimates with time-varying state-level MML coded by program type (medicalized versus non-medical). Multi-level linear regression models adjusted for state-level random effects and covariates as well as historical trends in use.
Nation-wide cross-sectional survey data from the US National Survey of Drug Use and Health (NSDUH) restricted use data portal aggregated at the state level.
Participants comprised 2004-13 NSDUH respondents (n ~ 67 500/year); age groups 12-17, 18-25 and 26+ years. States had implemented eight medicalized and 15 non-medical MML programs.
Primary outcome measures included (1) active (past-month) marijuana use; (2) heavy use (> 300 days/year); and (3) cannabis use disorder diagnosis, based on DSM-IV criteria. Covariates included program type, age group and state-level characteristics throughout the study period.
Adults 26+ years of age living in states with non-medical MML programs increased past-month marijuana use 1.46% (from 4.13 to 6.59%, P = 0.01), skewing towards greater heavy marijuana by 2.36% (from 14.94 to 17.30, P = 0.09) after MMLs were enacted. However, no associated increase in the prevalence of cannabis use disorder was found during the study period. Our findings do not show increases in prevalence of marijuana use among adults in states with medicalized MML programs. Additionally, there were no increases in adolescent or young adult marijuana outcomes following MML passage, irrespective of program type.
Non-medical marijuana laws enacted in US states are associated with increased marijuana use, but only among adults aged 26+ years. Researchers and policymakers should consider program regulation and subgroup characteristics (i.e. demographics) when assessing for population level outcomes. Researchers and policymakers should consider program regulation and subgroup characteristics (i.e. demographics) when assessing for population level outcomes.
大多数美国州都通过了医用大麻法（MML），但项目监管的巨大差异影响了入组率。我们旨在比较在考虑是否实施了医学化（高度监管）或非医学 MML 项目的情况下，不同年龄组的大麻使用、重度使用和大麻使用障碍的发生率变化。
采用差异中的差异估计，根据项目类型（医学化与非医学）对州级时间变化的 MML 进行编码。多水平线性回归模型调整了州级随机效应和协变量以及使用的历史趋势。
美国国家药物使用和健康调查（NSDUH）全国横断面调查数据，通过 NSDUH 限制使用数据门户汇总到州一级。
2004 年至 2013 年，参与调查的参与者为 NSDUH 受访者（每年约 67500 人）；年龄组为 12-17 岁、18-25 岁和 26 岁以上。各州实施了八项医学化和十五项非医学 MML 项目。
主要结局指标包括（1）过去一个月的活跃（使用）大麻；（2）重度使用（每年>300 天）；（3）基于 DSM-IV 标准的大麻使用障碍诊断。协变量包括整个研究期间的项目类型、年龄组和州级特征。
26 岁以上的成年人生活在非医学 MML 项目的州中，过去一个月的大麻使用率增加了 1.46%（从 4.13%增加到 6.59%，P=0.01），更多地倾向于重度使用大麻，增加了 2.36%（从 14.94%增加到 17.30%，P=0.09）。然而，在研究期间，大麻使用障碍的流行率没有发现增加。我们的研究结果表明，在实施医学化 MML 的州，成年人中大麻使用的流行率没有增加。此外，无论项目类型如何，青少年或年轻成年人的大麻结局都没有增加。
美国各州颁布的非医用大麻法与大麻使用率的增加有关，但仅与 26 岁以上的成年人有关。研究人员和政策制定者在评估人群水平结果时，应考虑项目监管和亚组特征（即人口统计学）。
