The Relationship between Tobacco Retailer Density and Neighborhood Demographics in Ohio

Abstract

Introduction: Studies from various parts of the country suggest that tobacco-related health disparities are exacerbated by disparities in the distribution of tobacco retailers (convenience stores, tobacco shops, etc.). The purpose of the present study was to use advanced spatial modeling techniques for count data to estimate current disparities in tobacco retailer density in Ohio.

Methods: We identified and geocoded 11,392 tobacco retailers in Ohio. Next, we obtained census tract-level information on race/ethnicity, poverty, and age and obtained county-level information on whether an area was Urban, Suburban, or Rural. Finally, we used negative binomial generalized linear models, adapted for residual spatial dependence, to determine the association between per capita tobacco retailer density and demographic characteristics-summarized by adjusted rate ratios.

Results: There were more (from 1.4-1.9 times as many) retailers per capita in high-poverty, vs. low-poverty tracts. Poverty also interacted with age: the association between high poverty and high retailer density was stronger for tracts with a low youth population. Density was also greater in tracts with a high (vs. low) prevalence of African Americans (1.1 times as many) and Hispanics (1.2 times as many). Finally, density was generally greater in rural (vs. suburban or urban) tracts, although the effect was modified by a three-way interaction: density was particularly high for rural tracts that also had both a high prevalence of poverty and a low youth population.

Discussion: Overall, our findings indicate that Ohio's vulnerable populations are exposed to a greater per capita density of tobacco retailers.

Public health implications: There is a need for state and local-level tobacco control policies that will improve equity and reduce health disparities.

Keywords: Tobacco retailer density; disparities; spatial modeling.

Figure 1.

Left panels: Maps of the log tobacco retailers per thousand people in each census tract for all of Ohio (top row), Franklin county (middle row), and Southeast Ohio (bottom row; Athens, Hocking, Meigs, Noble, Perry, and Washington counties). The five levels of shading are defined by the quintiles of this log retailer distribution. Darker shading indicates a higher retailer density. Census tracts shaded in white were omitted from the analysis due to low population counts. Right panels: Maps of the expected log retailers per thousand people in each census tract as estimated from the negative binomial model.

Figure 2.

Boxplots of the observed log rate of tobacco retailers in Ohio, by demographic characteristics.

Figure 3.

Summaries of the negative binomial models fit to the tobacco retailer counts in Ohio, adjusted for residual spatial dependence. The circles in the left panel show the estimated adjusted retailer rate ratios for different prevalence of race/ethnicity (comparing higher versus lower prevalence for each race/ethnicity). The circles in the right panel indicate the estimated retailer rate ratios comparing tracts with higher and lower prevalence of poverty for urban, suburban and rural tracts, as the prevalence of people aged under 18 in the population is varied (lower prevalence of under 18s in gray; higher prevalence in black). In each panel, the vertical lines denote 95% confidence intervals for each rate ratio.