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探讨科罗拉多州娱乐用大麻政策对阿片类药物过量率的影响。

Exploring the effect of Colorado's recreational marijuana policy on opioid overdose rates.

机构信息

University of Southern California, Sol Price School of Public Policy, 650 Childs Way, Los Angeles, CA 90089, USA.

出版信息

Public Health. 2020 Aug;185:8-14. doi: 10.1016/j.puhe.2020.04.007. Epub 2020 Jun 3.

Abstract

OBJECTIVES

Opioid overdose death rates have continued to spike exponentially from the start of the 21st century, creating what is known to be one of the worst public health crises in the United States. Simultaneously, as more states began passing medical cannabis laws (MCLs), the idea that marijuana was the solution to the opioid crisis began to spread nationwide. As some states have maintained strict medical marijuana policies, others-such as Colorado-have expanded their statutes to allow recreational marijuana sales within their state. Researchers have been able to provide sense of the public health implications resulting from MCLs, but little is known about the effects of this marijuana policy expansion. This preliminary study will focus on exploring the statewide effects of Colorado's recreational marijuana policy on the state's opioid overdose death rates.

STUDY DESIGN

Because Colorado has existing panel data for opioid overdose death rates, we can use statistical software to define and create an optimal control group to adequately resemble Colorado's outcome variable of interest. This process known as the synthetic control method can provide a valid counterfactual for Colorado's opioid overdose outcomes in the absence of this policy-a Colorado that did not expand marijuana policy to the point recreational dispensaries were established.

METHODS

Opioid overdose death rate data from the Centers for Disease Control and Prevention's Wide-ranging Online Data for Epidemiologic Research (WONDER) will be used to construct a synthetic control unit composed of a donor pool of states resembling Colorado's regulatory environment pertaining to marijuana before legalization. The synthetic control unit allows for a comparative observation of overdose rate trends in Colorado and its synthetic counterpart for the years 1999-2017, all while including a set of predictor variables for robustness checks. A difference-in-difference estimate will then help us observe the effects of the treatment given to Colorado. Inference tests will be conducted to evaluate the method's predictive power and significance of the results.

RESULTS

The results of the synthetic control model and its outcomes showed that the estimated negative 5% drop in overdose death rates was deemed insignificant on conducting a placebo in-space analysis, meaning there is not enough evidence to prove that opening recreational dispensaries as a result of recreational marijuana legislation was instrumental in reducing Colorado's ongoing opioid crisis depicted through opioid overdose deaths.

CONCLUSION

Owing to the lack of additional post-treatment data and captured lagged effects, it is too soon to dismiss this policy as inadequate in combating the opioid epidemic. Once additional post-treatment data become available, the study can be reproduced to obtain more robust results and achieve a clearer understanding of the policy implications shown.

摘要

目的

从 21 世纪初开始,阿片类药物过量致死率呈指数级持续飙升,这被认为是美国最严重的公共卫生危机之一。与此同时,随着越来越多的州开始通过医用大麻法(MCL),大麻是解决阿片类药物危机的想法开始在全国范围内传播。一些州维持严格的医用大麻政策,而另一些州,如科罗拉多州,则扩大了法规,允许在州内销售娱乐用大麻。研究人员已经能够了解 MCL 带来的公共卫生影响,但对于这种大麻政策扩张的影响知之甚少。这项初步研究将重点探讨科罗拉多州娱乐用大麻政策对该州阿片类药物过量致死率的全州影响。

研究设计

由于科罗拉多州有阿片类药物过量致死率的现有面板数据,我们可以使用统计软件来定义和创建一个最佳对照组,以充分模拟科罗拉多州的感兴趣的结果变量。这个过程称为合成控制法,可以为科罗拉多州没有扩大大麻政策到设立娱乐用大麻药房的情况下的阿片类药物过量结果提供一个有效的反事实情况。

方法

将使用疾病控制与预防中心的广泛在线流行病学研究数据(WONDER)中的阿片类药物过量致死率数据,构建一个由与科罗拉多州大麻合法化前的监管环境相似的州组成的捐赠池的合成对照组。合成对照组允许对科罗拉多州和其合成对照组在 1999-2017 年的过量率趋势进行比较观察,同时包括一组预测变量以进行稳健性检查。然后,将进行差分估计,以观察给予科罗拉多州的治疗效果。将进行推断测试,以评估该方法的预测能力和结果的显著性。

结果

合成对照组模型及其结果表明,在进行空间安慰剂分析时,估计的 5%的过量死亡率下降被认为是不显著的,这意味着没有足够的证据证明娱乐用大麻立法导致的娱乐用大麻药房的开设有助于减轻科罗拉多州持续的阿片类药物危机,这反映在阿片类药物过量死亡上。

结论

由于缺乏额外的治疗后数据和捕获的滞后效应,现在就认为这项政策在对抗阿片类药物流行方面不够充分还为时过早。一旦获得更多的治疗后数据,就可以重复该研究以获得更稳健的结果,并更清楚地了解政策影响。

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