Department of Behavioral and Community Health Sciences, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, USA.
College of Social Work, The Ohio State University, Columbus, OH, USA.
Addiction. 2021 Jul;116(7):1908-1913. doi: 10.1111/add.15420. Epub 2021 Feb 10.
To estimate associations between both current- and prior-year medical cannabis dispensary densities and hospitalizations for cannabis use disorder in California, USA between 2013 and 2016.
Spatial analysis of ZIP code-level hospitalization discharge data using Bayesian Poisson hierarchical space-time models over 4 years.
California, USA from 2013 to 2016 (6832 space-time ZIP code units).
We assessed associations of annual hospitalizations for cannabis use disorder [assignment of a primary or secondary code for cannabis abuse and/or dependence using ICD-9-CM or ICD-10-CM (outcome)] with the total number of medical cannabis dispensaries per square mile in a ZIP code as well as dispensary temporal and spatial lags (primary exposures). Other exposure covariates included alcohol outlet densities, manual labor and retail sales densities and ZIP code-level economic and demographic conditions.
One additional dispensary per square mile was associated with a median risk ratio of 1.021 (95% credible interval 1.001, 1.041). Prior-year dispensary density did not appear to be associated with hospitalizations (median risk ratio = 1.006, 95% CrI = 0.986, 1.026). Higher median household income, higher unemployment, greater off-premises alcohol outlet density and lower on-premises alcohol outlet density and poverty were all associated with decreased ZIP code-level risk of cannabis abuse/dependence hospitalizations.
In California, USA, the increasing density of medical cannabis dispensaries appears to be positively associated with same-year but not next-year hospitalizations for cannabis use disorder.
估计 2013 年至 2016 年期间，美国加利福尼亚州当前和前一年度医用大麻药房密度与大麻使用障碍住院治疗之间的关联。
使用贝叶斯泊松分层时空模型对 4 年来邮政编码级住院数据进行空间分析。
美国加利福尼亚州，2013 年至 2016 年（6832 个时空邮政编码单位）。
我们评估了大麻使用障碍的年度住院率[使用 ICD-9-CM 或 ICD-10-CM（结果）为大麻滥用和/或依赖分配一个主要或次要代码]与邮政编码内每平方英里医用大麻药房总数以及药房时间和空间滞后（主要暴露）之间的关联。其他暴露协变量包括酒精销售点密度、体力劳动和零售销售密度以及邮政编码级经济和人口状况。
每平方英里增加一家药房与中位风险比 1.021（95%可信区间 1.001，1.041）相关。前一年度的药房密度似乎与住院治疗无关（中位风险比=1.006，95%CrI=0.986，1.026）。较高的家庭中位数收入、较高的失业率、较高的场外酒精销售点密度和较低的场内酒精销售点密度以及贫困率均与大麻滥用/依赖住院治疗的邮政编码级风险降低相关。
在美国加利福尼亚州，医用大麻药房密度的增加似乎与当年而非次年的大麻使用障碍住院治疗呈正相关。
