Food environments and obesity: A geospatial analysis of the South Asia Biobank, income and sex inequalities. (March 2022)

• Record Type: Journal Article
• Authors: Atanasova, Petya; Kusuma, Dian; Pineda, Elisa; Anjana, Ranjit Mohan; De Silva, Laksara; Hanif, Abu A.M.; Hasan, Mehedi; Hossain, Md Mokbul; Indrawansa, Susantha; Jayamanne, Deepal; Jha, Sujeet; Kasturiratne, Anuradhani; Katulanda, Prasad; Khawaja, Khadija I.; Kumarendran, Balachandran; Mridha, Malay K.; Rajakaruna, Vindya; Chambers, John C.; Frost, Gary; Sassi, Franco; Miraldo, Marisa
• Is Part Of: SSM - population health. Volume 17(2022)
• Publication Date: 2022-03
• Subjects: Food environment -- Obesity -- BMI -- Low- and middle- income countries -- South Asia; Social medicine -- Periodicals; Medical anthropology -- Periodicals; Public health -- Periodicals; Psychology -- Periodicals; Medicine -- Periodicals; 362.105
• DOI: 10.1016/j.ssmph.2022.101055
• Languages: English
• ISSNs: 2352-8273

Abstract

Abstract: Introduction: In low-middle income countries (LMICs) the role of food environments on obesity has been understudied. We address this gap by 1) examining the effect of food environments on adults' body size (BMI, waist circumference) and obesity; 2) measuring the heterogeneity of such effects by income and sex. Methods: This cross-sectional study analysed South Asia Biobank surveillance and environment mapping data for 12, 167 adults collected between 2018 and 2020 from 33 surveillance sites in Bangladesh and Sri Lanka. Individual-level data (demographic, socio-economic, and health characteristics) were combined with exposure to healthy and unhealthy food environments measured with geolocations of food outlets (obtained through ground-truth surveys) within 300 m buffer zones around participants' homes. Multivariate regression models were used to assess association of exposure to healthy and unhealthy food environments on waist circumference, BMI, and probability of obesity for the total sample and stratified by sex and income. Findings: The presence of a higher share of supermarkets in the neighbourhood was associated with a reduction in body size (BMI, β = - 3∙23; p < 0∙0001, and waist circumference, β = −5∙99; p = 0∙0212) and obesity (Average Marginal Effect (AME): −0∙18; p = 0∙0009). High share of fast-food restaurants in the neighbourhood was not significantly associated with body size, but it significantly increased the probability of obesity measured by BMI (AME: 0∙09; p = 0∙0234) and waist circumference (AME: 0∙21; p = 0∙0021). These effects were stronger among females and low-income individuals. Interpretation: The results suggest the availability of fast- food outlets influences obesity, especially among female and lower-income groups. The availability of supermarkets is associated with reduced body size and obesity, but their effects do not outweigh the role of fast-food outlets. Policies should target food environments to promote better diets and reduce obesity. Highlights: Healthy and unhealthy food environments in LMICs are significantly associated with BMI, waist circumference and obesity. There is social inequality in this effect as female and low-income individuals are most affected. Low-middle income countries show similar trends in obesity prevalence as high-income countries.