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Canadian Journal of Public Health

, Volume 107, Supplement 1, pp eS27–eS33 | Cite as

Relative and absolute availability of fast-food restaurants in relation to the development of diabetes: A population-based cohort study

  • Jane Y. PolskyEmail author
  • Rahim Moineddin
  • Richard H. Glazier
  • James R. Dunn
  • Gillian L. Booth
Quantitative Research

Abstract

OBJECTIVES: To determine whether residents living in areas with a high proportion of fast-food restaurants (FFR) relative to all restaurants are more likely to develop diabetes and whether the risk varies according to the volume of FFR.

METHODS: The study cohort consisted of adult respondents (20-84 years) to the Canadian Community Health Survey (cycles 2005, 2007/2008, 2009/2010) who resided within walking distance (720 m) of at least one restaurant in Toronto, Brampton, Mississauga or Hamilton, ON. The development of diabetes was established by linking participants to the Ontario Diabetes Database. Cox proportional hazards models were used to estimate hazard ratios (HRs) of incident diabetes associated with relative and absolute measures of restaurant availability.

RESULTS: During a median follow-up of 5 years, 347 of 7,079 participants (4.6%) developed diabetes. Among younger adults (20-65 years n = 5,806), a greater proportion of fast-food relative to all restaurants was significantly associated with incident diabetes after adjustment for a range of individual and area-level covariates, but only in areas with high volumes of fast-food retailers (3+ outlets) (HR = 1.79, 95% confidence interval: 1.03-3.12, across the interquartile range). Adjusting for body mass index rendered this association non-significant. No significant associations were observed in areas with low volumes of FFR or among older adults (65-84 years n = 1,273). bsolute availability (number) of fast-food and other restaurants was generally unrelated to incident diabetes.

CONCLUSION: Areas with the double burden of a high volume of FFR and few dining alternatives may represent an adverse environment for the development of diabetes.

KEY WORDS

Diabetes mellitus fast food restaurants body mass index cohort studies 

Résumé

OBJECTIFS : Déterminer si les résidents de secteurs comptant une proportion élevée de restaurants rapides (RR) par rapport à l’ensemble des restaurants sont plus susceptibles de contracter le diabète et si le risque varie selon le volume de RR.

MÉTHODE : Cette étude de cohorte comprenait les répondants adultes (20-84 ans) de l’Enquête sur la santé dans les collectivités canadiennes (cycles 2005, 2007-2008, 2009-2010) résidant à distance de marche (720 m) d’au moins un restaurant à Toronto, Brampton, Mississauga ou Hamilton (Ontario). Nous avons établi la survenue du diabète en reliant les participants à la base de données sur le diabète de l’Ontario. Nous avons utilisé des modèles à risques proportionnels de Cox pour estimer les coefficients de danger (QD) du diabète incident associés aux indicateurs relatifs et absolus de disponibilité des restaurants.

RÉSULTATS : Au cours d’un suivi médian de 5 ans, 347 des 7,079 participants (4.9 %) ont contracté le diabète. Chez les adultes les plus jeunes (20–65 ans, n = 5,806), une proportion plus élevée de restaurants rapides par rapport à l’ensemble des restaurants présentait une corrélation significative avec le diabète incident compte tenu d’une gamme de covariables individuelles et par secteur, mais seulement dans les secteurs ayant des volumes élevés de restaurants rapides (3 ou plus) (QD = 1.79, intervalle de confiance de 95 %: 1.03–3.12, dans tout l’écart interquartile). Si l’on tient compte de l’indice de masse corporelle, cette association devient non significative. Aucune association significative n’a été observée dans les secteurs ayant de faibles volumes de RR, ni chez les personnes âgées (65–84 ans, n = 1,273). La disponibilité absolue (le nombre) des restaurants rapides et des autres restaurants était en général sans rapport avec le diabète incident.

MOTS CLÉS

diabète sucré aliments de restauration rapide restaurants indice de masse corporelle études de cohortes 

References

  1. 1.
    Canadian Diabetes Association (CDA). An Economic Tsunami: The Cost of Diabetes in Canada, 2009. Available at: http://www.diabetes.ca/CDA/media/documents/publications-and-newsletters/advocacy-reports/economic-tsunami-cost-of-diabetes-in-canada-english.pdf (Accessed April 19, 2016).Google Scholar
  2. 2.
    Hu FB. Globalization of diabetes: The role of diet, lifestyle, and genes. Diabetes Care 2011;34(6):1249–57. PMID: 21617109. doi: 10.2337/dc1 1-0442.CrossRefGoogle Scholar
  3. 3.
    Lipscombe LL, Hux JE. Trends in diabetes prevalence, incidence, and mortality in Ontario, Canada 1995-2005: A population-based study. Lancet 2007;369(9563):750–56. PMID: 17336651. doi: 10.1016/S0140-6736(07) 60361-4.CrossRefGoogle Scholar
  4. 4.
    Canadian Diabetes Association (CDA). Diabetes in Canada. Key Statistics. 2015. Available at: https://www.diabetes.ca/getmedia/513a0f6c-b1c9-4e56-a77c-6a492bf7350f/diabetes-charter-backgrounder-national-english.pdf.aspx (Accessed September 21, 2015).Google Scholar
  5. 5.
    Garriguet D. Canadians’ eating habits. Health Rep 2007;18(2):17–32. PMID: 17578013.Google Scholar
  6. 6.
    Prentice AM, Jebb SA. Fast foods, energy density and obesity: A possible mechanistic link. Obes Rev 2003;4(4):187–94. PMID: 14649369. doi: 10.1046/j.1467-789X.2003.00117.x.CrossRefGoogle Scholar
  7. 7.
    Krishnan S, Coogan PF, Boggs DA, Rosenberg L, Palmer JR. Consumption of restaurant foods and incidence of type 2 diabetes in African American women. Am J Clin Nutr 2010;91(2):465–71. PMID: 20016014. doi: 10.3945/ajcn.2009.28682.CrossRefGoogle Scholar
  8. 8.
    Duffey KJ, Gordon-Larsen P, Steffen LM, Jacobs Jr DR, Popkin BM. Regular consumption from fast food establishments relative to other restaurants is differentially associated with metabolic outcomes in young adults. J Nutr 2009;139(11):2113–18. PMID: 19776183. doi: 10.3945/jn.109.109520.CrossRefGoogle Scholar
  9. 9.
    Fleischhacker SE, Evenson KR, Rodriguez DA, Ammerman AS. A systematic review of fast food access studies. Obes Rev 2011;12(5):e460–71. PMID: 20149118. doi: 10.1111/j.1467-789X.2010.00715.x.CrossRefGoogle Scholar
  10. 10.
    Hollands S, Campbell MK, Gilliland J, Sarma S. Association between neighbourhood fast-food and full-service restaurant density and body mass index: A cross-sectional study of Canadian adults. Can J Public Health 2014; 105(3):e172–78. PMID: 25165835.CrossRefGoogle Scholar
  11. 11.
    Polsky JY, Moineddin R, Dunn JR, Glazier RH, Booth GL. Absolute and relative densities of fast-food versus other restaurants in relation to weight status: Does restaurant mix matter?Prev Med 2016;82:28–34. PMID: 26582211. doi: 10.1016/j.ypmed.2015.11.008.Google Scholar
  12. 12.
    Kestens Y, Lebel A, Chaix B, Clary C, Daniel M, Pampalon R, et al. Association between activity space exposure to food establishments and individual risk of overweight. PLoS One 2012;7(8):e41418. PMID: 22936974. doi: 10.1371/journal.pone.0041418.CrossRefGoogle Scholar
  13. 13.
    Zick C, Smith K, Fan J, Brown B, Yamada I, Kowaleski-Jones L. Running to the store? The relationship between neighborhood environments and the risk of obesity. Soc Sci Med 2009;69(10):1493–500. PMID: 19766372. doi: 10.1016/j. socscimed.2009.08.032.CrossRefGoogle Scholar
  14. 14.
    Clary CM, Ramos Y, Shareck M, Kestens Y. Should we use absolute or relative measures when assessing foodscape exposure in relation to fruit and vegetable intake? Evidence from a wide-scale Canadian study. PrevMed 2015;71:83–87. PMID: 25481095. doi: 10.1016/j.ypmed.2014.11.023.Google Scholar
  15. 15.
    Beland Y. Canadian community health survey - Methodological overview. Health Rep 2002;13(3):9–14. PMID: 12743956.PubMedGoogle Scholar
  16. 16.
    Hux JE, Ivis F, Flintoft V, Bica A. Diabetes in Ontario: Determination of prevalence and incidence using a validated administrative data algorithm. Diabetes Care 2002;25(3):512–16. PMID: 11874939. doi: 10.2337/diacare.25.3. 512.CrossRefGoogle Scholar
  17. 17.
    World Health Organization (WHO). Diabetes. Fact Sheet no. 312, 2015. Available at: http://www.who.int/mediacentre/factsheets/fs312/en/ (Accessed January 25, 2016).Google Scholar
  18. 18.
    Ohri-Vachaspati P, Martinez D, Yedidia MJ, Petlick N. Improving data accuracy of commercial food outlet databases. Am J Health Promot 2011; 26(2):116–22. PMID: 22040393. doi: 10.4278/ajhp.100120-QUAN-21.CrossRefGoogle Scholar
  19. 19.
    Engler-Stringer R, Le H, Gerrard A, Muhajarine N. The community and consumer food environment and children’s diet: A systematic review. BMC Public Health 2014;14(1):522. PMID: 24884443. doi: 10.1186/1471-2458-14-522.CrossRefGoogle Scholar
  20. 20.
    Cobb LK, Appel LJ, Franco M, Jones-Smith JC, Nur A, Anderson CAM. The relationship of the local food environment with obesity: A systematic review of methods, study quality, and results. Obesity 2015;23(7):1331–44. PMID: 26096983. doi: 10.1002/oby.21118.CrossRefGoogle Scholar
  21. 21.
    Connor Gorber S, Shields M, Tremblay MS, McDowell I. The feasibility of establishing correction factors to adjust self-reported estimates of obesity. Health Rep 2008;19(3):71–82. PMID: 18847148.PubMedGoogle Scholar
  22. 22.
    Glazier RH, Creatore MI, Weyman JT, Fazli G, Matheson FI, Gozdyra P, et al. Density, destinations or both? A comparison of measures of walkability in relation to transportation behaviors, obesity and diabetes in Toronto, Canada. PLoS One 2014;9(1):e85295. PMID: 24454837. doi: 10.1371/journal.pone. 0085295.CrossRefGoogle Scholar
  23. 23.
    Polsky JY, Moineddin R, Glazier RH, Dunn JR, Booth GL. Foodscapes of southern Ontario: Neighbourhood deprivation and access to healthy and unhealthy food retail. Can J Public Health 2014;105(5):e369–75. PMID: 25365272.CrossRefGoogle Scholar
  24. 24.
    Booth GL, Creatore MI, Moineddin R, Gozdyra P, Weyman JT, Matheson FI, et al. Unwalkable neighborhoods, poverty, and the risk of diabetes among recent immigrants to Canada compared with long-term residents. Diabetes Care 2013;36(2):302–8. PMID: 22988302. doi: 10.2337/dc12-0777.CrossRefGoogle Scholar
  25. 25.
    Health Canada. Measuring the Food Environment in Canada. Ottawa: Health Canada, 2013. Available at: http://www.hc-sc.gc.ca/fn-an/nutrition/pol/som-ex-sum-environ-eng.php (Accessed September 22, 2015).Google Scholar
  26. 26.
    Matheson FI, Dunn JR, Smith KLW, Moineddin R, Glazier RH. Development of the Canadian marginalization index: A new tool for the study of inequality. Can J Public Health 2012;103(Suppl 2):S12–16. PMID: 23618065.PubMedGoogle Scholar
  27. 27.
    Narayan KMV, Boyle JP, Thompson TJ, Gregg EW, Williamson DF. Effect of BMI on lifetime risk for diabetes in the U.S. Diabetes Care 2007;30(6):1562–66. PMID: 17372155. doi: 10.2337/dc06-2544.CrossRefGoogle Scholar
  28. 28.
    Mercille G, Richard L, Gauvin L, Kestens Y, Shatenstein B, Daniel M, et al. Associations between residential food environment and dietary patterns in urban-dwelling older adults: Results from the VoisiNuAge study. Public Health Nutr 2012;15(11):2026–39. PMID: 22789436. doi: 10.1017/S136898001200273X.CrossRefGoogle Scholar
  29. 29.
    Mehta NK, Chang VW. Weight status and restaurant availability a multilevel analysis. Am J Prev Med 2008;34(2):127–33. PMID: 18201642. doi: 10.1016/j. amepre.2007.09.031.CrossRefGoogle Scholar
  30. 30.
    Wansink B. Environmental factors that increase the food intake and consumption volume of unknowing consumers. Annu Rev Nutr 2004; 24:455–79. PMID: 15189128. doi: 10.1146/annurev.nutr.24.012003.132140.CrossRefGoogle Scholar
  31. 31.
    Yeh MC, Matsumori B, Obenchain J, Viladrich A, Das D, Navder K. Validity of a competing food choice construct regarding fruit and vegetable consumption among urban college freshmen. J Nutr Educ Behav 2010;42(5):321–27. PMID: 20655281. doi: 10.1016/j.jneb.2009.08.004.CrossRefGoogle Scholar
  32. 32.
    Paquet C, Dubé L, Gauvin L, Kestens Y, Daniel M. Sense of mastery and metabolic risk: Moderating role of the local fast-food environment. Psychosom Med 2010;72(3):324–31. PMID: 20100887. doi: 10.1097/PSY. 0b013e3181cdf439.CrossRefGoogle Scholar
  33. 33.
    Bodicoat DH, Carter P, Comber A, Edwardson C, Gray LJ, Hill S, et al. Is the number of fast-food outlets in the neighbourhood related to screen-detected type 2 diabetes mellitus and associated risk factors? Public Health Nutr 2015;18(9):1698–705. PMID: 25358618. doi: 10.1017/S1368980014002316.CrossRefGoogle Scholar
  34. 34.
    Burgoine T, Forouhi NG, Griffin SJ, Wareham NJ, Monsivais P. Associations between exposure to takeaway food outlets, takeaway food consumption, and body weight in Cambridgeshire, UK: Population based, cross sectional study. Br Med J 2014;348:g1464. PMID: 24625460. doi: 10.1136/bmj.g1464.CrossRefGoogle Scholar
  35. 35.
    Sturm R, Hattori A. Diet and obesity in Los Angeles county 2007-2012: Is there a measurable effect of the 2008 “fast-food ban?” Soc Sci Med 2015; 133:205–11. PMID: 25779774. doi: 10.1016/j.socscimed.2015.03.004.CrossRefGoogle Scholar

Copyright information

© The Canadian Public Health Association 2016

Authors and Affiliations

  • Jane Y. Polsky
    • 1
    • 2
    Email author
  • Rahim Moineddin
    • 3
    • 4
  • Richard H. Glazier
    • 1
    • 2
    • 3
    • 4
  • James R. Dunn
    • 4
    • 5
  • Gillian L. Booth
    • 2
    • 4
  1. 1.Dalla Lana School of Public HealthUniversity of TorontoTorontoCanada
  2. 2.Centre for Research on Inner City Health, Keenan Research CentreLi Ka Shing Knowledge Institute of St. Michael’s HospitalTorontoCanada
  3. 3.Department of Family and Community MedicineUniversity of TorontoTorontoCanada
  4. 4.Institute for Clinical Evaluative SciencesTorontoCanada
  5. 5.Department of Health, Aging and SocietyMcMaster UniversityHamiltonCanada

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