Imperial College London
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ProfessorGaryFrost

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

Chair in Nutrition & Dietetics
 
 
 
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Contact

 

+44 (0)20 7594 0959g.frost Website

 
 
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Location

 

Commonwealth BiuldingHammersmith HospitalHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Atanasova:2022:10.1016/j.ssmph.2022.101055,
author = {Atanasova, P and Kusuma, D and Pineda, E and Anjana, RM and De, Silva L and Hanif, AAM and Hasan, M and Hossain, MM and Indrawansa, S and Jayamanne, D and Jha, S and Kasturiratne, A and Katulanda, P and Khawaja, KI and Kumarendran, B and Mrida, MK and Rajakaruna, V and Chambers, JC and Frost, G and Sassi, F and Miraldo, M},
doi = {10.1016/j.ssmph.2022.101055},
journal = {SSM - Population Health},
pages = {101055--101055},
title = {Food environments and obesity: a geospatial analysis of the South Asia Biobank, income and sex inequalities.},
url = {http://dx.doi.org/10.1016/j.ssmph.2022.101055},
volume = {17},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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 = - 323; p < 00001, and waist circumference, β = -599; p = 00212) and obesity (Average Marginal Effect (AME): -018; p = 00009). 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: 009; p = 00234) and waist circumference (AME: 021; p = 00021). 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 o
AU  - Atanasova,P
AU  - Kusuma,D
AU  - Pineda,E
AU  - Anjana,RM
AU  - De,Silva L
AU  - Hanif,AAM
AU  - Hasan,M
AU  - Hossain,MM
AU  - Indrawansa,S
AU  - Jayamanne,D
AU  - Jha,S
AU  - Kasturiratne,A
AU  - Katulanda,P
AU  - Khawaja,KI
AU  - Kumarendran,B
AU  - Mrida,MK
AU  - Rajakaruna,V
AU  - Chambers,JC
AU  - Frost,G
AU  - Sassi,F
AU  - Miraldo,M
DO  - 10.1016/j.ssmph.2022.101055
EP  - 101055
PY  - 2022///
SN  - 2352-8273
SP  - 101055
TI  - Food environments and obesity: a geospatial analysis of the South Asia Biobank, income and sex inequalities.
T2  - SSM - Population Health
UR  - http://dx.doi.org/10.1016/j.ssmph.2022.101055
UR  - https://www.ncbi.nlm.nih.gov/pubmed/35252534
UR  - https://www.sciencedirect.com/science/article/pii/S2352827322000349?via%3Dihub
UR  - http://hdl.handle.net/10044/1/95424
VL  - 17
ER  -
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