Kephart Lindsay, Rees Vaughan W, Subramanian S V, Giovenco Daniel P
Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, 7th Floor, Boston, MA, 02115, USA.
Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, 7th Floor, Boston, MA, 02115, USA.
Health Place. 2025 Jan;91:103396. doi: 10.1016/j.healthplace.2024.103396. Epub 2024 Dec 12.
There is growing interest in the relationship between neighborhood disadvantage and increased cannabis retail density, driven by evidence suggesting higher density is associated with increased cannabis use. Yet little is known on how this relationship varies across different measures of cannabis retail density. This study explores how measures of neighborhood advantage and disadvantage relate to four cannabis retail density measures in the US.
Data on licensed recreational cannabis retailers (n = 5586) were obtained from 18 state agency websites, geocoded, and spatially joined to 3369 census tracts to calculate four retail density measures: count per tract, cannabis retailers per 1000 population, per square mile, and per 10 miles of roadway. Multilevel regression models assessed the association between three Index of Concentration at the Extremes (ICE) measures-capturing tract concentration of racial and economic advantage/disadvantage-and the four cannabis retail density measures.
Census tracts with the highest concentrations of economic and racialized/economic disadvantage exhibited greater odds of increased cannabis retail density across all measures, compared to tracts with the highest concentration of advantage. Tracts with the greatest concentration of racialized populations did not show a higher count or density per population but did exhibit higher density per square mile and per roadway.
On average, cannabis retail density is higher in neighborhoods with the greatest structural disadvantage. Researchers, public health agencies, and policymakers should use multiple measures of cannabis retailer density in surveillance and evaluation efforts to identify policy strategies that would most effectively reduce the clustering of cannabis retailers in areas primarily occupied by low-income or racialized populations.
邻里劣势与大麻零售密度增加之间的关系正受到越来越多的关注，有证据表明更高的密度与大麻使用增加有关。然而，对于这种关系如何因大麻零售密度的不同衡量标准而变化，人们知之甚少。本研究探讨了邻里优势和劣势的衡量标准与美国四种大麻零售密度衡量标准之间的关系。
从18个州机构网站获取了持牌休闲大麻零售商的数据（n = 5586），进行地理编码，并在空间上与3369个人口普查区进行关联，以计算四种零售密度衡量标准：每个普查区的数量、每1000人口的大麻零售商数量、每平方英里的数量以及每10英里道路的数量。多级回归模型评估了三种极端集中度指数（ICE）衡量标准（用于捕捉种族和经济优势/劣势的普查区集中度）与四种大麻零售密度衡量标准之间的关联。
与优势集中度最高的普查区相比，经济和种族化/经济劣势集中度最高的普查区在所有衡量标准下大麻零售密度增加的几率都更大。种族化人口集中度最高的普查区在人均数量或密度方面没有显示出更高，但在每平方英里和每条道路上的密度确实更高。
平均而言，在结构劣势最大的社区，大麻零售密度更高。研究人员､公共卫生机构和政策制定者应在监测和评估工作中使用多种大麻零售商密度衡量标准，以确定最有效地减少大麻零售商在主要由低收入或种族化人口居住地区聚集的政策策略。
