Impact of Medical and Recreational Marijuana Laws On Cannabis, Opioids And Psychiatric Medications: National Study of VA Patients, 2000 - 2024

医用和娱乐大麻法对大麻、阿片类药物和精神药物的影响：2000 年至 2024 年退伍军人事务部患者的全国研究

• 批准号: 10612385
• 负责人: DEBORAH S HASIN
• 金额: $ 74.64万
• 依托单位: NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10612385
• 关键词: Address; Adult; Affect; Age; Alcohol consumption; Alcohols; Anti-Anxiety Agents; Antidepressive Agents; Anxiety; Anxiety Disorders; Area; Attention; Behavior; Cannabis; Cannabis policy; Caring; Cessation of life; Characteristics; Computerized Medical Record; Data; Data Set; Depressive disorder; Diagnosis; Disease; Drug Prescriptions; Economic Factors; Epidemiology; Ethnic Origin; General Population; Health; Health Professional; Healthcare Systems; Impairment; Individual; Internal Medicine; Justice; Knowledge; Laws; Left; Link; Literature; Low income; Medical; Medical Marijuana; Medicare; Mental Depression; Mental disorders; Methods; Modeling; Modification; National Institute of Drug Abuse; Opioid; Outcome; Outcome Study; Overdose; Pain; Patients; Pharmaceutical Preparations; Policies; Policy Maker; Population; Post-Traumatic Stress Disorders; Prevalence; Public Health; Race; Recreation; Research; Research Personnel; Resources; Risk Factors; Symptoms; Testing; Text; Time; Tobacco; Tobacco use; United States Department of Veterans Affairs; Variant; Veterans Health Administration; Vulnerable Populations; addiction; adverse outcome; chronic pain; chronic painful condition; clinical practice; clinical risk; demographics; design; effective therapy; federal policy; high risk; human old age (65+); hypnotic; indexing; male; marijuana use; marijuana use disorder; medical examination; multilevel analysis; opioid epidemic; opioid policy; opioid use; opioid use disorder; overdose death; prescription opioid; public health priorities; sedative; sex; trend

Thirty states now have medical marijuana laws (MML), 9 have recreational marijuana laws (RML), and many more states are considering such laws. The health effects of cannabis laws are controversial; understanding them is a major public health and NIDA priority (PA-17-135). Thus far, only 3 studies of adults (2 of them ours; Hasin et al., 2017, Martins et al., 2016) used multi-level modeling to examine MML effects on cannabis outcomes with individual data. These studies suggested post-MML increases in cannabis use and Cannabis Use Disorder (CUD). However, they left many questions unanswered, including whether MML have stronger effects in those with key vulnerability factors (chronic pain, psychiatric disorders). In addition, soaring rates of opioid prescriptions and overdoses have led to calls for MML as part of the solution to the US opioid crisis, but most MML-opioid studies are ecological (a weak design to study individual behavior), and results from individual-level studies leave the evidence unclear. Ecological studies also suggest that through cannabis substitution, MML reduce medication prescriptions for common psychiatric disorders (e.g., PTSD, depression), but no individual-level studies of this have been conducted. Importantly, RML effects are almost entirely unknown, a major gap in knowledge. In Veterans Administration (VA) patients, CUD prevalence has doubled since 2002, and in those age ≥35, is 2-6 times higher than in the general population. VA patients also have high rates of opioid prescriptions, overdoses, and of chronic pain and psychiatric disorders that may increase their vulnerability to adverse MML and RML effects. They thus are a large, vulnerable population in whom MML and RML effects are unknown. We will investigate MML and RML effects utilizing a major resource, the individual data from the VA Electronic Medical Record, available since 2000 from the ~5,000,000 patients served each year by the VA healthcare system. We will create yearly EMR datasets, and merge this with National Death Index data, Medicare data (for those age ≥65) and state-year MML and RML variables that we will create. Using multi-level models and difference-in-difference tests, we will examine MML and RML effects on three main outcomes: cannabis (use, CUD), opioids (prescriptions, fatal and non-fatal overdoses, opioid use disorders), and psychotropic medication prescriptions (antidepressants, anxiolytics, sedatives/hypnotics). Importantly, we will determine if pain, psychiatric disorders or demographics (sex, age, race/ethnicity) modify MML/RML effects. We will also examine specific MML/RML provisions, time lags, and breakpoints in trends reflecting federal policy changes. Analyses will incorporate individual- and state-level confounders, e.g., state norms, economic factors. We will also explore alcohol and tobacco outcomes. The research team includes substance epidemiology/policy experts and VA addiction and internal medicine experts. Findings will be disseminated to clinicians and policy-makers. Determining MML/RML effects in VA patients will make a major contribution to the limited adult literature on MML/RML, contributing to knowledge that will inform policy and the care of individuals with vulnerability factors.

现已有 30 个州制定了医用大麻法 (MML)，9 个州制定了娱乐性大麻法 (RML)，还有许多州制定了娱乐性大麻法 (RML)。 更多的州正在考虑此类法律。大麻法对健康的影响存在争议；理解 它们是公共卫生和 NIDA 的主要优先事项 (PA-17-135)。到目前为止，只有 3 项针对成年人的研究（其中 2 项是我们的； Hasin 等人，2017 年，Martins 等人，2016 年）使用多级模型来检查 MML 对大麻结果的影响 与个人数据。这些研究表明 MML 后大麻使用和大麻使用障碍有所增加 （CUD）。然而，他们留下了许多悬而未决的问题，包括 MML 是否对这些方面有更强的影响。 具有关键的脆弱因素（慢性疼痛、精神疾病）。此外，阿片类药物处方率飙升 过量服用导致人们呼吁将 MML 作为解决美国阿片类药物危机的一部分，但大多数 MML-阿片类药物 研究是生态的（研究个人行为的薄弱设计），个人层面的研究结果离开 证据不明确。生态研究还表明，通过大麻替代，MML 可以减少 针对常见精神疾病（例如创伤后应激障碍（PTSD）、抑郁症）的药物处方，但没有个人层面的药物处方 对此进行了研究。重要的是，RML 效应几乎完全未知，这是 知识。在退伍军人管理局 (VA) 患者中，CUD 患病率自 2002 年以来翻了一番，并且在这些患者中 年龄≥35岁，是一般人群的2-6倍。 VA 患者阿片类药物使用率也很高 处方药、服药过量以及慢性疼痛和精神疾病可能会增加他们对这些疾病的脆弱性 MML 和 RML 的不良影响。因此，他们是一个庞大的弱势群体，MML 和 RML 的影响对他们来说很严重。 未知。我们将利用主要资源（来自 VA 的个人数据）研究 MML 和 RML 效应 电子病历，自 2000 年起可从 VA 每年服务的约 5,000,000 名患者中获取 医疗保健系统。我们将创建年度 EMR 数据集，并将其与国家死亡指数数据、医疗保险合并 我们将创建的数据（对于年龄≥65 岁的人）以及州年 MML 和 RML 变量。使用多层次模型 和双重差异检验，我们将检查 MML 和 RML 对三个主要结果的影响： 大麻 （使用、CUD）、阿片类药物（处方、致命和非致命过量、阿片类药物使用障碍）和精神药物 药物处方（抗抑郁药、抗焦虑药、镇静剂/安眠药）。重要的是，我们将确定是否 疼痛、精神疾病或人口统计（性别、年龄、种族/民族）会改变 MML/RML 效应。我们还将 检查反映联邦政策变化的具体 MML/RML 规定、时间滞后和趋势断点。 分析将纳入个人和国家层面的混杂因素，例如国家规范、经济因素。我们将 还探讨酒精和烟草的结果。研究团队包括物质流行病学/政策专家 以及 VA 成瘾和内科专家。研究结果将分发给临床医生和政策制定者。 确定 MML/RML 对 VA 患者的影响将为有限的成人文献做出重大贡献 MML/RML，贡献知识，为具有脆弱性因素的个人制定政策和护理提供信息。

项目成果

Correction to Lancet Psychiatry 10: 877-86.

《柳叶刀精神病学》10 更正：877-86。

• DOI: 10.1016/s2215-0366(23)00362-0
• 发表时间: 2023
• 期刊: The lancet. Psychiatry

Prevalence and Correlates of Cannabis Use and Cannabis Use Disorder Among U.S. Veterans: Results From the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC-III).

• DOI: 10.1176/appi.ajp.2021.20081202
• 发表时间: 2022-01
• 期刊: The American journal of psychiatry
• 作者: Browne KC;Stohl M;Bohnert KM;Saxon AJ;Fink DS;Olfson M;Cerda M;Sherman S;Gradus JL;Martins SS;Hasin DS
• 通讯作者: Hasin DS

Substance, use in relation to COVID-19: A scoping review.

物质，与COVID-19的使用：范围审查。

• DOI: 10.1016/j.addbeh.2021.107213
• 发表时间: 2022-04
• 期刊: Addictive behaviors
• 影响因子: 4.4
• 作者: Kumar N;Janmohamed K;Nyhan K;Martins SS;Cerda M;Hasin D;Scott J;Sarpong Frimpong A;Pates R;Ghandour LA;Wazaify M;Khoshnood K
• 通讯作者: Khoshnood K

Implications of Medical and Recreational Marijuana Laws for Neuroscience Research: a Review.

• DOI: 10.1007/s40473-020-00222-5
• 发表时间: 2020-12
• 期刊: Current behavioral neuroscience reports
• 影响因子: 1.7
• 作者: Hasin DS;Aharonovich E
• 通讯作者: Aharonovich E

Trends over time in adult cannabis use: A review of recent findings.

• DOI: 10.1016/j.copsyc.2021.03.005
• 发表时间: 2021-04
• 期刊: Current opinion in psychology
• 影响因子: 5.9
• 作者: Hasin D;Walsh C
• 通讯作者: Walsh C