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Food environment and diabetes mellitus in South Asia: A geospatial analysis of health outcome data
BACKGROUND: The global epidemic of type 2 diabetes mellitus (T2DM) renders its prevention a major public health priority. A key risk factor of diabetes is obesity and poor diets. Food environments have been found to influence people’s diets and obesity, positing they may play a role in the prevalenc...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9041866/ https://www.ncbi.nlm.nih.gov/pubmed/35472059 http://dx.doi.org/10.1371/journal.pmed.1003970 |
Sumario: | BACKGROUND: The global epidemic of type 2 diabetes mellitus (T2DM) renders its prevention a major public health priority. A key risk factor of diabetes is obesity and poor diets. Food environments have been found to influence people’s diets and obesity, positing they may play a role in the prevalence of diabetes. Yet, there is scant evidence on the role they may play in the context of low- and middle-income countries (LMICs). We examined the associations of food environments on T2DM among adults and its heterogeneity by income and sex. METHODS AND FINDINGS: We linked individual health outcome data of 12,167 individuals from a network of health surveillance sites (the South Asia Biobank) to the density and proximity of food outlets geolocated around their homes from environment mapping survey data collected between 2018 and 2020 in Bangladesh and Sri Lanka. Density was defined as share of food outlets within 300 m from study participant’s home, and proximity was defined as having at least 1 outlet within 100 m from home. The outcome variables include fasting blood glucose level, high blood glucose, and self-reported diagnosed diabetes. Control variables included demographics, socioeconomic status (SES), health status, healthcare utilization, and physical activities. Data were analyzed in ArcMap 10.3 and STATA 15.1. A higher share of fast-food restaurants (FFR) was associated with a 9.21 mg/dl blood glucose increase (95% CI: 0.17, 18.24; p < 0.05). Having at least 1 FFR in the proximity was associated with 2.14 mg/dl blood glucose increase (CI: 0.55, 3.72; p < 0.01). A 1% increase in the share of FFR near an individual’s home was associated with 8% increase in the probability of being clinically diagnosed as a diabetic (average marginal effects (AMEs): 0.08; CI: 0.02, 0.14; p < 0.05). Having at least 1 FFR near home was associated with 16% (odds ratio [OR]: 1.16; CI: 1.01, 1.33; p < 0.05) and 19% (OR: 1.19; CI: 1.03, 1.38; p < 0.05) increases in the odds of higher blood glucose levels and diagnosed diabetes, respectively. The positive association between FFR density and blood glucose level was stronger among women than men, but the association between FFR proximity and blood glucose level was stronger among men as well as among those with higher incomes. One of the study’s key limitations is that we measured exposure to food environments around residency geolocation; however, participants may source their meals elsewhere. CONCLUSIONS: Our results suggest that the exposure to fast-food outlets may have a detrimental impact on the risk of T2DM, especially among females and higher-income earners. Policies should target changes in the food environments to promote better diets and prevent T2DM. |
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