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Spatially Varying Associations of Neighborhood Disadvantage with Alcohol and Tobacco Retail Outlet Rates

Author

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  • David C. Wheeler

    (Department of Biostatistics, Virginia Commonwealth University, Richmond, VA 23298, USA)

  • Joseph Boyle

    (Department of Biostatistics, Virginia Commonwealth University, Richmond, VA 23298, USA)

  • D. Jeremy Barsell

    (Department of Health Behavior and Policy, Virginia Commonwealth University, Richmond, VA 23298, USA)

  • Trevin Glasgow

    (Department of Health Behavior and Policy, Virginia Commonwealth University, Richmond, VA 23298, USA)

  • F. Joseph McClernon

    (Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC 27705, USA)

  • Jason A. Oliver

    (Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC 27705, USA
    Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
    Department of Psychiatry and Behavioral Sciences, Oklahoma State University Center for Health Sciences, Tulsa, OK 74107, USA)

  • Bernard F. Fuemmeler

    (Department of Health Behavior and Policy, Virginia Commonwealth University, Richmond, VA 23298, USA
    Massey Cancer Center, Virginia Commonwealth University, Richmond, VA 23298, USA)

Abstract

More than 30% of cancer related deaths are related to tobacco or alcohol use. Controlling and restricting access to these cancer-causing products, especially in communities where there is a high prevalence of other cancer risk factors, has the potential to improve population health and reduce the risk of specific cancers associated with these substances in more vulnerable population subgroups. One policy-driven method of reducing access to these cancer-causing substances is to regulate where these products are sold through the placement and density of businesses selling tobacco and alcohol. Previous work has found significant positive associations between tobacco, alcohol, and tobacco and alcohol retail outlets (TRO, ARO, TARO) and a neighborhood disadvantage index (NDI) using Bayesian shared component index modeling, where NDI associations differed across outlet types and relative risks varied by population density (e.g., rural, suburban, urban). In this paper, we used a novel Bayesian index model with spatially varying effects to explore spatial nonstationarity in NDI effects for TROs, AROs, and TAROs across census tracts in North Carolina. The results revealed substantial variation in NDI effects that varied by outlet type. However, all outlet types had strong positive effects in one coastal area. The most important variables in the NDI were percent renters, Black racial segregation, and the percentage of homes built before 1940. Overall, more disadvantaged areas experienced a greater neighborhood burden of outlets selling one or both of alcohol and tobacco.

Suggested Citation

  • David C. Wheeler & Joseph Boyle & D. Jeremy Barsell & Trevin Glasgow & F. Joseph McClernon & Jason A. Oliver & Bernard F. Fuemmeler, 2022. "Spatially Varying Associations of Neighborhood Disadvantage with Alcohol and Tobacco Retail Outlet Rates," IJERPH, MDPI, vol. 19(9), pages 1-13, April.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:9:p:5244-:d:802253
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    References listed on IDEAS

    as
    1. David Wheeler & Lance Waller, 2009. "Comparing spatially varying coefficient models: a case study examining violent crime rates and their relationships to alcohol outlets and illegal drug arrests," Journal of Geographical Systems, Springer, vol. 11(1), pages 1-22, March.
    2. Gelfand A.E. & Kim H-J. & Sirmans C.F. & Banerjee S., 2003. "Spatial Modeling With Spatially Varying Coefficient Processes," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 387-396, January.
    3. David C. Wheeler & Elizabeth K. Do & Rashelle B. Hayes & Kendall Fugate-Laus & Westley L. Fallavollita & Colleen Hughes & Bernard F. Fuemmeler, 2020. "Neighborhood Disadvantage and Tobacco Retail Outlet and Vape Shop Outlet Rates," IJERPH, MDPI, vol. 17(8), pages 1-12, April.
    4. Nelson, D.E. & Jarman, D.W. & Rehm, J. & Greenfield, T.K. & Rey, G. & Kerr, W.C. & Miller, P. & Shield, K.D. & Ye, Y. & Naimi, T.S., 2013. "Alcohol-attributable cancer deaths and years of potential life lost in the United States," American Journal of Public Health, American Public Health Association, vol. 103(4), pages 641-648.
    5. Berke, E.M. & Tanski, S.E. & Demidenko, E. & Alford-Teaster, J. & Shi, X. & Sargent, J.D., 2010. "Alcohol retail density and demographic predictors of health disparities: A geographic analysis," American Journal of Public Health, American Public Health Association, vol. 100(10), pages 1967-1971.
    6. David C. Wheeler & Joseph Boyle & D. Jeremy Barsell & Trevin Glasgow & F. Joseph McClernon & Jason A. Oliver & Bernard F. Fuemmeler, 2022. "Associations of Alcohol and Tobacco Retail Outlet Rates with Neighborhood Disadvantage," IJERPH, MDPI, vol. 19(3), pages 1-13, January.
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