Is the number of fast-food outlets in the neighbourhood related to screen-detected type 2 diabetes mellitus and associated risk factors?

Abstract

Objective: We investigated whether a higher number of fast-food outlets in an individual's home neighbourhood is associated with increased prevalence of type 2 diabetes mellitus and related risk factors, including obesity. Design: Cross-sectional study. Setting: Three UK-based diabetes screening studies (one general population, two high-risk populations) conducted between 2004 and 2011. The primary outcome was screen-detected type 2 diabetes. Secondary outcomes were risk factors for type 2 diabetes. Subjects: In total 10 461 participants (mean age 59 years; 53 % male; 21 % nonWhite ethnicity).Results: There was a higher number of neighbourhood (500 m radius from home postcode) fast-food outlets among non-White ethnic groups (P < 0·001) and in socially deprived areas (P < 0·001). After adjustment (social deprivation, urban/ rural, ethnicity, age, sex), more fast-food outlets was associated with significantly increased odds for diabetes (OR = 1·02; 95 % CI 1·00, 1·04) and obesity (OR = 1·02; 95 % CI 1·00, 1·03). This suggests that for every additional two outlets per neighbourhood, we would expect one additional diabetes case, assuming a causal relationship between the fast-food outlets and diabetes. Conclusions: These results suggest that increased exposure to fast-food outlets is associated with increased risk of type 2 diabetes and obesity, which has implications for diabetes prevention at a public health level and for those granting planning permission to new fast-food outlets.

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

“…These findings contrast with those of the only previously published investigation of diabetes risk related to FFR exposure, which observed an elevated risk of prevalent diabetes among adults living within walking distance of a greater number of FFR. 33 However, when excess weight is considered, our results are in line with several Canadian and US reports observing lower weight status among residents of areas with a greater volume of FFR, other restaurants and food retail in general. [11][12][13] Such findings reflect the common coexistence of higher volumes of food retail in areas that Table 2.…”

Neighborhood social and physical environments and type 2 diabetes mellitus in African Americans: The Jackson Heart Study

“…reported greater fast food restaurants availability was associated with higher energy intake in the same cohort (Hickson et al, 2011). We are aware of only one study in UK that investigated that association between density of fast-food stores and T2DM and found significant positive association between the number of fast-food outlets in individual’s neighborhood and prevalence of T2DM (Bodicoat et al, 2015). However, this study was cross-sectional and used less comprehensive measure of unfavorable food stores compared to our study.To the best of our knowledge, this study is the first to report an association between density of unfavorable food stores and incidence of T2DM in a large sample of African Americans.…”

How different data sources and definitions of neighbourhood influence the association between food outlet availability and body mass index: a cross-sectional study

“…4 9 Bodicoat et al (2015) showed that fast-food outlets were weakly but positively associated with type II diabetes in smaller radial buffers but not obesity (100m or 250m). 9 However, within larger neighbourhood definitions (500m, 750m, 1000m) the number of fast-food outlets were associated with type II diabetes, obesity and fasting glucose. James et al (2014) also showed that for intersection count the strongest effect sizes were seen in the 400m buffers; effects reduced as buffer sizes got larger i.e.…”

“…9 Only supermarkets exhibited some differences across neighbourhood definitions and datasets in both strength and direction of associations with BMI. This finding is particularly interesting considering the PoI dataset contained only eight fewer supermarkets and that more supermarkets are associated with an increase in BMI, opposite to the hypothesised direction.…”