INTRODUCTION: There is great disparity in tobacco outlet density (TOD), with density highest in low-income areas and areas with greater proportions of minority residents, and this disparity may affect cancer incidence. We sought to better understand the nature of this disparity by assessing how these socio-demographic factors relate to TOD at the national level. METHODS: Using mixture regression analysis and all of the nearly 65,000 census tracts in the contiguous United States, we aimed to determine the number of latent disparity classes by modeling the relations of proportions of Blacks, Hispanics, and families living in poverty with TOD, controlling for urban/rural status. RESULTS: We identified six disparity classes. There was considerable heterogeneity in relation to TOD for Hispanics in rural settings. For Blacks, there was no relation to TOD in an urban moderate disparity class, and for rural census tracts, the relation was highest in a moderate disparity class. CONCLUSIONS: We demonstrated the utility of classifying census tracts on heterogeneity of tobacco risk exposure. This approach provides a better understanding of the complexity of socio-demographic influences of tobacco retailing and creates opportunities for policy makers to more efficiently target areas in greatest need.
INTRODUCTION: There is great disparity in tobacco outlet density (TOD), with density highest in low-income areas and areas with greater proportions of minority residents, and this disparity may affect cancer incidence. We sought to better understand the nature of this disparity by assessing how these socio-demographic factors relate to TOD at the national level. METHODS: Using mixture regression analysis and all of the nearly 65,000 census tracts in the contiguous United States, we aimed to determine the number of latent disparity classes by modeling the relations of proportions of Blacks, Hispanics, and families living in poverty with TOD, controlling for urban/rural status. RESULTS: We identified six disparity classes. There was considerable heterogeneity in relation to TOD for Hispanics in rural settings. For Blacks, there was no relation to TOD in an urban moderate disparity class, and for rural census tracts, the relation was highest in a moderate disparity class. CONCLUSIONS: We demonstrated the utility of classifying census tracts on heterogeneity of tobacco risk exposure. This approach provides a better understanding of the complexity of socio-demographic influences of tobacco retailing and creates opportunities for policy makers to more efficiently target areas in greatest need.
Authors: Andrew Hyland; Mark J Travers; K Michael Cummings; Joseph Bauer; Terry Alford; William F Wieczorek Journal: Am J Public Health Date: 2003-07 Impact factor: 9.308
Authors: Sarah D Mills; Rina S Fox; Sandy Bohan; Scott C Roesch; Georgia Robins Sadler; Vanessa L Malcarne Journal: Cultur Divers Ethnic Minor Psychol Date: 2019-04-01
Authors: Amanda Y Kong; Paul L Delamater; Nisha C Gottfredson; Kurt M Ribisl; Chris D Baggett; Shelley D Golden Journal: Health Place Date: 2021-08-27 Impact factor: 4.931
Authors: Andrew Anesetti-Rothermel; Peter Herman; Morgane Bennett; Ned English; Jennifer Cantrell; Barbara Schillo; Elizabeth C Hair; Donna M Vallone Journal: Ethn Dis Date: 2020-07-09 Impact factor: 1.847
Authors: Michael O Chaiton; Graham C Mecredy; Joanna E Cohen; Melodie L Tilson Journal: Int J Environ Res Public Health Date: 2013-12-17 Impact factor: 3.390
Authors: Brian P Jenssen; Robert Schnoll; Rinad Beidas; Justin Bekelman; Anna-Marika Bauer; Callie Scott; Sarah Evers-Casey; Jody Nicoloso; Peter Gabriel; David A Asch; Alison Buttenheim; Jessica Chen; Julissa Melo; Lawrence N Shulman; Alicia B W Clifton; Adina Lieberman; Tasnim Salam; Kelly Zentgraf; Katharine A Rendle; Krisda Chaiyachati; Rachel Shelton; E Paul Wileyto; Sue Ware; Frank Leone Journal: Implement Sci Date: 2021-07-15 Impact factor: 7.327