IDEAS home Printed from https://ideas.repec.org/a/plo/pgph00/0001069.html
   My bibliography  Save this article

Association of the retail food environment, BMI, dietary patterns, and socioeconomic position in urban areas of Mexico

Author

Listed:
  • Elisa Pineda
  • Diana Barbosa Cunha
  • Mansour Taghavi Azar Sharabiani
  • Christopher Millett

Abstract

The retail food environment is a key modifiable driver of food choice and the risk of non-communicable diseases (NCDs). This study aimed to assess the relationship between the density of food retailers, body mass index (BMI), dietary patterns, and socioeconomic position in Mexico. Cross-sectional dietary data, BMI and socioeconomic characteristics of adult participants came from the nationally representative 2012 National Health and Nutrition Survey in Mexico. Geographical and food outlet data were obtained from official statistics. Densities of food outlets per census tract area (CTA) were calculated. Dietary patterns were determined using exploratory factor analysis and principal component analysis. The association of food environment variables, socioeconomic position, BMI, and dietary patterns was assessed using two-level multilevel linear regression models. Three dietary patterns were identified—the healthy, the unhealthy and the carbohydrates-and-drinks dietary pattern. Lower availability of fruit and vegetable stores was associated with an unhealthier dietary pattern whilst a higher restaurant density was associated with a carbohydrates-and-drinks pattern. A graded and inverse association was observed for fruit and vegetable store density and socioeconomic position (SEP)—lower-income populations had a reduced availability of fruit and vegetable stores, compared with higher-income populations. A higher density of convenience stores was associated with a higher BMI when adjusting for unhealthy dietary patterns. Upper-income households were more likely to consume healthy dietary patterns and middle-upper-income households were less likely to consume unhealthy dietary patterns when exposed to high densities of fruit and vegetable stores. When exposed to a high concentration of convenience stores, lower and upper-lower-income households were more likely to consume unhealthy dietary patterns. Food environment and sociodemographic conditions within neighbourhoods may affect dietary behaviours. Food environment interventions and policies which improve access to healthy foods and restrict access to unhealthy foods may facilitate healthier diets and contribute to the prevention of NCDs.

Suggested Citation

  • Elisa Pineda & Diana Barbosa Cunha & Mansour Taghavi Azar Sharabiani & Christopher Millett, 2023. "Association of the retail food environment, BMI, dietary patterns, and socioeconomic position in urban areas of Mexico," PLOS Global Public Health, Public Library of Science, vol. 3(2), pages 1-20, February.
  • Handle: RePEc:plo:pgph00:0001069
    DOI: 10.1371/journal.pgph.0001069
    as

    Download full text from publisher

    File URL: https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0001069
    Download Restriction: no

    File URL: https://journals.plos.org/globalpublichealth/article/file?id=10.1371/journal.pgph.0001069&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pgph.0001069?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Raphael Thomadsen, 2007. "Product Positioning and Competition: The Role of Location in the Fast Food Industry," Marketing Science, INFORMS, vol. 26(6), pages 792-804, 11-12.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Little, Cedric & Felzensztein, Christian & Gimmon, Eli & Muñoz, Pablo, 2015. "The business management of the Chilean salmon farming industry," Marine Policy, Elsevier, vol. 54(C), pages 108-117.
    2. Isabelle M. Nilsson & Oleg A. Smirnov, 2017. "Clustering vs. relative location: Measuring spatial interaction between retail outlets," Papers in Regional Science, Wiley Blackwell, vol. 96(4), pages 721-741, November.
    3. Philip G. Gayle & Zijun Luo, 2015. "Choosing between Order-of-Entry Assumptions in Empirical Entry Models: Evidence from Competition between Burger King and McDonald's Restaurant Outlets," Journal of Industrial Economics, Wiley Blackwell, vol. 63(1), pages 129-151, March.
    4. Mitsukuni Nishida, 2015. "Estimating a Model of Strategic Network Choice: The Convenience-Store Industry in Okinawa," Marketing Science, INFORMS, vol. 34(1), pages 20-38, January.
    5. Oksana Loginova & X. Hnery Wang, 2010. "Customization in an Endogenous-Timing Game with Vertical Differentiation," Working Papers 1008, Department of Economics, University of Missouri.
    6. Takeshi Ebina & Katsumasa Nishide, 2024. "Sequential product positioning and entry timing under differential costs in a continuous-time model," Annals of Operations Research, Springer, vol. 332(1), pages 277-301, January.
    7. Morgan, Carissa J. & Dominick, S.R. & Widmar, Nicole J. Olynk & Yeager, Elizabeth A. & Croney, Candace C., 2016. "Perceptions of Corporate Social Responsibility of Prominent Fast Food Establishments by University Students," Journal of Food Distribution Research, Food Distribution Research Society, vol. 47(3), pages 1-14, November.
    8. Jacint Balaguer Coll & José C. Pernías, 2010. "Spatial density, average prices and price dispersion. Evidence from the Spanish hotel industry," Working Papers. Serie EC 2010-03, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    9. Ali Umut Guler, 2018. "Inferring the Economics of Store Density from Closures: The Starbucks Case," Marketing Science, INFORMS, vol. 37(4), pages 611-630, August.
    10. Richards, Timothy J. & Gómez, Miguel I. & Pofahl, Geoffrey, 2012. "A Multiple-discrete/Continuous Model of Price Promotion," Journal of Retailing, Elsevier, vol. 88(2), pages 206-225.
    11. Petros G. Sekeris & Kevin Siqueira, 2021. "Payoff-Improving Competition: Games with Negative Externalities," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 58(3), pages 455-474, May.
    12. Chloe Kim Glaeser & Marshall Fisher & Xuanming Su, 2019. "Optimal Retail Location: Empirical Methodology and Application to Practice," Service Science, INFORMS, vol. 21(1), pages 86-102, January.
    13. Qiaowei Shen & Ping Xiao, 2014. "McDonald's and KFC in China: Competitors or Companions?," Marketing Science, INFORMS, vol. 33(2), pages 287-307, March.
    14. Chakravarthi Narasimhan & Özge Turut, 2013. "Differentiate or Imitate? The Role of Context-Dependent Preferences," Marketing Science, INFORMS, vol. 32(3), pages 393-410, May.
    15. Debjit Roy & Eirini Spiliotopoulou & Jelle de Vries, 2022. "Restaurant analytics: Emerging practice and research opportunities," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3687-3709, October.
    16. Kazuhiro Takauchi & Tomomichi Mizuno, 2022. "Endogenous transport price, R&D spillovers, and trade," The World Economy, Wiley Blackwell, vol. 45(5), pages 1477-1500, May.
    17. Kazuhiro Takauchi & Tomomichi Mizuno, 2019. "Is competition in the transport industry bad?A welfare analysis of R&D with inter-regional transportation," Discussion Papers 1910, Graduate School of Economics, Kobe University.
    18. Yongmin Chen & Michael H. Riordan, 2008. "Price‐increasing competition," RAND Journal of Economics, RAND Corporation, vol. 39(4), pages 1042-1058, December.
    19. Lee, Hanna & Jang, Seongsoo & Kim, Jinwon, 2024. "Spatial coopetition and peer-to-peer accommodation price," Annals of Tourism Research, Elsevier, vol. 109(C).
    20. Sumon Datta & K. Sudhir, 2023. "The Agglomeration-Differentiation Tradeoff in Spatial Location Choice," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 10(1), pages 1-25, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pgph00:0001069. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: globalpubhealth (email available below). General contact details of provider: https://journals.plos.org/globalpublichealth .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.