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Density and proximity of fast food restaurants and body mass index among African Americans

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  • Reitzel, L.R.
  • Regan, S.D.
  • Nguyen, N.
  • Cromley, E.K.
  • Strong, L.L.
  • Wetter, D.W.
  • McNeill, L.H.

Abstract

Objectives: The purpose of this study was to address current gaps in the literature by examining the associations of fast food restaurant (FFR) density around the home and FFR proximity to the home, respectively, with body mass index (BMI) among a large sample of African American adults from Houston, Texas. Methods: We used generalized linear models with generalized estimating equations to examine associations of FFR density at 0.5-, 1-, 2-, and 5-mile road network buffers around the home with BMI and associations of the closest FFR to the home with BMI. All models were adjusted for a range of individual-level covariates and neighborhood socioeconomic status. We additionally investigated the moderating effects of household income on these relations. Data were collected from December 2008 to July 2009. Results: FFR density was not associated with BMI in the main analyses. However, FFR density at 0.5, 1, and 2 miles was positively associated with BMI among participants with lower incomes (P ≤.025). Closer FFR proximity was associated with higher BMI among all participants (P

Suggested Citation

  • Reitzel, L.R. & Regan, S.D. & Nguyen, N. & Cromley, E.K. & Strong, L.L. & Wetter, D.W. & McNeill, L.H., 2014. "Density and proximity of fast food restaurants and body mass index among African Americans," American Journal of Public Health, American Public Health Association, vol. 104(1), pages 110-116.
    • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2012.301140_1
    DOI: 10.2105/AJPH.2012.301140
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    Cited by:

    1. Hall, Brian J. & Huang, Lei & Yi, Grace & Latkin, Carl, 2021. "Fast food restaurant density and weight status: A spatial analysis among Filipina migrant workers in Macao (SAR), People's Republic of China," Social Science & Medicine, Elsevier, vol. 269(C).
    2. Zaynel Sushil & Stefanie Vandevijvere & Daniel J. Exeter & Boyd Swinburn, 2017. "Food swamps by area socioeconomic deprivation in New Zealand: a national study," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 62(8), pages 869-877, November.
    3. Shervin Assari & Shanika Boyce & Mohsen Bazargan & Ron Mincy & Cleopatra H. Caldwell, 2019. "Unequal Protective Effects of Parental Educational Attainment on the Body Mass Index of Black and White Youth," IJERPH, MDPI, vol. 16(19), pages 1-14, September.
    4. Brennan Davis & Cornelia Pechmann, 2023. "When Students Patronize Fast-Food Restaurants near School: The Effects of Identification with the Student Community, Social Activity Spaces and Social Liability Interventions," IJERPH, MDPI, vol. 20(5), pages 1-24, March.
    5. Adriana Dornelles, 2019. "Impact of multiple food environments on body mass index," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-14, August.
    6. Suzanne J. Carroll & Michael J. Dale & Anne W. Taylor & Mark Daniel, 2020. "Contributions of Multiple Built Environment Features to 10-Year Change in Body Mass Index and Waist Circumference in a South Australian Middle-Aged Cohort," IJERPH, MDPI, vol. 17(3), pages 1-18, January.
    7. Timothy F. Ledoux & Igor Vojnovic & June Manning Thomas & Kameshwari Pothukuchi, 2017. "Standing in the Shadows of Obesity: The Local Food Environment and Obesity in Detroit," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 108(5), pages 605-624, October.
    8. Hao Huang, 2022. "Food Environment Inequalities and Moderating Effects of Obesity on Their Relationships with COVID-19 in Chicago," Sustainability, MDPI, vol. 14(11), pages 1-17, May.
    9. Jennifer J. Salinas & Bassent Abdelbary & Kelly Klaas & Beatriz Tapia & Ken Sexton, 2014. "Socioeconomic Context and the Food Landscape in Texas: Results from Hotspot Analysis and Border/Non-Border Comparison of Unhealthy Food Environments," IJERPH, MDPI, vol. 11(6), pages 1-11, May.
    10. Ran Xu & Xiao Huang & Kai Zhang & Weixuan Lyu & Debarchana Ghosh & Zhenlong Li & Xiang Chen, 2023. "Integrating human activity into food environments can better predict cardiometabolic diseases in the United States," Nature Communications, Nature, vol. 14(1), pages 1-9, December.

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