Journal article 621 views
Estimating neighbourhood-level prevalence of adult obesity by socio-economic, behavioural and built environment factors in New York City
Yeran Sun,
S. Wang,
X. Sun
Public Health, Volume: 186, Pages: 57 - 62
Swansea University Author: Yeran Sun
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DOI (Published version): 10.1016/j.puhe.2020.05.003
Abstract
ObjectivesSome studies reveal that socio-economic status, behavioural factors, accessibility to supermarket or food store, are associated with the prevalence of obesity and overweight. In this study, we aimed to examine to what extent socio-economic, behavioural and built environment characteristics...
| Published in: | Public Health |
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| ISSN: | 0033-3506 |
| Published: |
Elsevier BV
2020
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa56128 |
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| Abstract: |
ObjectivesSome studies reveal that socio-economic status, behavioural factors, accessibility to supermarket or food store, are associated with the prevalence of obesity and overweight. In this study, we aimed to examine to what extent socio-economic, behavioural and built environment characteristics can contribute to spatial disparities in adult obesity.Study designThe spatial analysis was undertaken to understand the association of spatial disparities in adult obesity and spatial disparities in socio-economic, behavioural and built environment characteristics.MethodsA spatial regression model which can remove the impact of auto-correlation in the residuals of conventionally regression models was applied to modelling local-scale rate of adult obesity (N = 59).ResultsOwing to the presence of residual spatial auto-correlation in the non-spatial regression model estimated, a spatial regression model was set up successfully to model local-scale rate of adult obesity across New York City (R2 = 0.8353, N = 59). Compared with socio-economic and built environment factors, behavioural factors make statistically significant contributions to spatial disparities in the prevalence of adult obesity (POAO). Particularly, two behavioural factors (‘sugary drinks consumption’ and ‘fruits and vegetable consumption’) can explain more than 70% of the variance of POAO (adjusted R2 = 0.7323, N = 59). Surprisingly, physical activity prevalence (percent of physically active adults) makes no statistically significant contributions.ConclusionsThe results further suggest that the reduction of adult obesity prevalence could benefit more from decreasing intake of sugary drinks than increasing physical activity. The local government and policy are advised to prioritise decreasing exposure of residents to sugary drinks through restricting advertising or increasing taxes rather than increasing neighbourhoods’ walkability through urban planning. |
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| Keywords: |
Adult obesity; Spatial regression model; Behavioural factors; Socio-economic factors; Built environment |
| College: |
Faculty of Science and Engineering |
| Start Page: |
57 |
| End Page: |
62 |