Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/164384
Title: Food environments and obesity: a geospatial analysis of the South Asia Biobank, income and sex inequalities
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
Mrida, Malay K.
Rajakaruna, Vindya
Chambers, John Campbell
Frost, Gary
Sassi, Franco
Miraldo, Marisa
Keywords: Science::Medicine
Issue Date: 2022
Source: Atanasova, P., Kusuma, D., Pineda, E., Anjana, R. M., De Silva, L., Hanif, A. A. M., Hasan, M., Hossain, M. M., Indrawansa, S., Jayamanne, D., Jha, S., Kasturiratne, A., Katulanda, P., Khawaja, K. I., Kumarendran, B., Mrida, M. K., Rajakaruna, V., Chambers, J. C., Frost, G., ...Miraldo, M. (2022). Food environments and obesity: a geospatial analysis of the South Asia Biobank, income and sex inequalities. SSM - Population Health, 17, 101055-. https://dx.doi.org/10.1016/j.ssmph.2022.101055
Journal: SSM - Population Health
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.
URI: https://hdl.handle.net/10356/164384
ISSN: 2352-8273
DOI: 10.1016/j.ssmph.2022.101055
Schools: Lee Kong Chian School of Medicine (LKCMedicine) 
Rights: © 2022 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:LKCMedicine Journal Articles

Files in This Item:
File Description SizeFormat 
1-s2.0-S2352827322000349-main.pdf877.04 kBAdobe PDFThumbnail
View/Open

SCOPUSTM   
Citations 20

11
Updated on Apr 17, 2024

Web of ScienceTM
Citations 20

7
Updated on Oct 30, 2023

Page view(s)

85
Updated on Apr 13, 2024

Download(s) 50

40
Updated on Apr 13, 2024

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.