Neighborhood Disadvantage and Tobacco Retail Outlet and Vape Shop Outlet Rates

Abstract

Neighborhood-level socioeconomic variables, such as the proportion of minority and low-income residents, have been associated with a greater density of tobacco retail outlets (TROs), though less is known about the degree to which these neighborhood indicators are related to vape shop outlet (VSO) density. Many studies of TROs and neighborhood characteristics include only a small set of variables and also fail to take into account the correlation among these variables. Using a carefully curated database of all TROs and VSOs in Virginia (2016–2018), we developed a Bayesian model to estimate a neighborhood disadvantage index and examine its association with rates of outlets across census tracts while also accounting for correlations among variables. Models included 12 census tract variables from the American Community Survey. Results showed that increasing neighborhood disadvantage was associated with a 63% and 64% increase in TRO and VSO risk, respectively. Important variables associated with TRO rates included % renter occupied housing, inverse median gross rent, inverse median monthly housing costs, inverse median monthly housing costs, and % vacant housing units. Important variables associated with VSO rates were % renter occupied housing and % Hispanic population. There were several spatial clusters of significantly elevated risk for TROs and VSOs in western and eastern Virginia.

Bayesian Group Index Regression for Modeling Chemical Mixtures and Cancer Risk

“…The Bayesian framework for the group index model also allows for more straightforward extension to more complex models that include individual and spatial random effects [ 20 , 21 , 22 ]. We have previously used both exchangeable and spatially correlated random effects in Bayesian single index models.…”

“…We propose to use a Bayesian framework to create a more flexible and complex GWQS model that does not require two-step estimation. We have previously used Bayesian index regression to create single-index models of neighborhood deprivation and risk of elevated blood lead levels [ 20 , 21 ] and tobacco retail outlet rates [ 22 ]. In this paper, we extend the Bayesian index model to incorporate multiple exposure indices (similar to GWQS regression) and term the approach the Bayesian group index model, a new way to estimate the health effects of chemical mixtures.…”

Evaluation of neighborhood deprivation and store characteristics in relation to tobacco retail outlet sales violations

“…Bayesian index models. To model the likelihood of a sales violation among the TROs that had been visited for compliance checks, we used Bayesian index regression models [22,25,26]. This type of model allowed us to estimate the NDI while including store-level attributes and area-level random effects for unexplained risk at the census tract level.…”

“…The variables were: Gini index of income inequality, percent Black population, percent without a bachelor's degree, percent of families in poverty, percent of households with public assistance, percent vacant housing units, percent renter occupied housing units, median household income, per capita income, median gross rent, median monthly housing costs, percent of housing units with a mortgage, percent Hispanic population, and percent US citizen. We selected these candidate variables based on our experience estimating a neighborhood deprivation index (NDI) for TRO density using a Bayesian index model [13][14][15][16][17]22], as well as findings from previous studies that have examined neighborhood characteristics and sales violations [9,[13][14][15][16][17]. We included percent Black population in the index because it is a measure of Black racial segregation resulting from a history of discriminatory practices that have led to the devaluation and deprivation of resources within segregated neighborhoods.…”

Associations of Alcohol and Tobacco Retail Outlet Rates with Neighborhood Disadvantage

“…To inform such efforts, a number of studies have examined (1) retail density in relationship to sociospatial demographic predictors of health disparities to better understand where these retail environments cluster [10,11] and (2) the extent to which retail density might be linked to increased consumption of cancer-causing products [12]. With some caveats, findings from these studies reveal that both tobacco retail outlet (TRO) and alcohol retail outlet (ARO) density are greater in neighborhoods with lower median income households and higher percent minority residents [13,14]. However, few studies have examined the intersection of TROs and AROs and the extent to which they correlate with other socio-economic characteristics of the neighborhood environment.…”