Objective: 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).
Methods: 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.
Results: 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).
Conclusions: 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.
Keywords: Disparities; Point-of-Sale; Retail Density; Tobacco.
Copyright © 2020, Ethnicity & Disease, Inc.