Schroeder Institute at Truth Initiative, Washington, DC.
NORC at the University of Chicago, Chicago, IL.
Ethn Dis. 2020 Jul 9;30(3):479-488. doi: 10.18865/ed.30.3.479. eCollection 2020 Summer.
Studies assessing sociodemographic disparities in the tobacco retail environment have relied heavily on non-spatial analytical techniques, resulting in potentially misleading conclusions. We utilized a spatial analytical framework to evaluate neighborhood sociodemographic disparities in the tobacco retail environment in Washington, DC (DC) and the DC metropolitan statistical area (DC MSA).
Retail tobacco availability for DC (n=177) and DC MSA (n=1,428) census tract was assessed using adaptive-bandwidth kernel density estimation. Density surfaces were constructed from DC (n=743) and DC MSA (n=4,539) geocoded tobacco retailers. Sociodemographics were obtained from the 2011-2015 American Community Survey. Spearman's correlations between sociodemographics and retail density were computed to account for spatial autocorrelation. Bivariate and multivariate spatial lag models were fit to predict retail density.
DC and DC MSA neighborhoods with a higher percentage of Hispanics were positively correlated with retail density (rho = .3392, P = .0001 and rho = .1191, P = .0000, respectively). DC neighborhoods with a higher percentage of African Americans were negatively correlated with retail density (rho = -.3774, P = .0000). This pattern was not significant in DC MSA neighborhoods. Bivariate and multivariate spatial lag models found a significant inverse relationship between the percentage of African Americans and retail density (Beta = -.0133, P = .0181 and Beta = -.0165, P = .0307, respectively).
Associations between neighborhood sociodemographics and retail density were significant, although findings regarding African Americans are inconsistent with previous findings. Future studies should analyze other geographic areas, and account for spatial autocorrelation within their analytic framework.
评估烟草零售环境中社会人口统计学差异的研究严重依赖于非空间分析技术,这可能导致误导性的结论。我们利用空间分析框架评估了华盛顿特区(DC)和 DC 都会统计区(DC MSA)邻里社会人口统计学差异的烟草零售环境。
使用自适应带宽核密度估计评估了 DC(n=177)和 DC MSA(n=1428)普查区的零售烟草供应情况。密度曲面是从 DC(n=743)和 DC MSA(n=4539)地理编码的烟草零售商中构建的。社会人口统计学数据来自 2011-2015 年美国社区调查。为了考虑空间自相关,计算了社会人口统计学与零售密度之间的斯皮尔曼相关性。拟合了双变量和多变量空间滞后模型来预测零售密度。
DC 和 DC MSA 邻里中西班牙裔比例较高的地区与零售密度呈正相关(rho =.3392,P =.0001 和 rho =.1191,P =.0000)。DC 邻里中非洲裔美国人比例较高的地区与零售密度呈负相关(rho = -.3774,P =.0000)。在 DC MSA 邻里中,这种模式并不显著。双变量和多变量空间滞后模型发现,非洲裔美国人比例与零售密度之间存在显著的负相关关系(Beta = -.0133,P =.0181 和 Beta = -.0165,P =.0307)。
邻里社会人口统计学与零售密度之间的关联是显著的,尽管关于非裔美国人的发现与以前的发现不一致。未来的研究应该分析其他地理区域,并在分析框架中考虑空间自相关。