Effects of built environment factors on obesity risk across three types of residential community in Beijing

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Article number101382
Journal / PublicationJournal of Transport and Health
Volume25
Online published14 May 2022
Publication statusPublished - Jun 2022

Abstract

Introduction: There is strong evidence in Western cities that neighborhood-level characteristics of the built environment are linked with a higher risk of overweight or obesity among residents. Due to the rapid urbanization during the last several decades, many types of residential community have formed and coexisted in the major cities of China. These communities provide residents with different built-environment features and lifestyles. However, it remains unclear whether the community type affects the risk of overweight and obesity among residents. Methods: The present study investigated the associations of built-environment characteristics and the bodyweight status (normal vs. overweight or obese) of 4,440 residents from three main types of community (i.e., commercial, work-unit, and traditional communities) in Shijingshan district, Beijing. Multilevel logistic regression and the random forest approach were adopted to investigate both the significance and relative importance of neighborhood-level factors of the built environment. Results: The results of multilevel logistic regression suggest that the community type has a significant association with the obesity risk. In addition, the land-use mix, the number of water features, the number of supermarkets and groceries, street intersections, and the normalized difference vegetation index are negatively related to the odds of obesity. The number of transit stops is positively associated with the odds of obesity. Random forest analysis reveals significant disparities in the relative importance of population structure and the built environment factors among the three types of community. Furthermore, we find a notable difference between the results of the multilevel logistic model and random forest model. Hence, both the significance and relative importance of neighborhood-level factors of the built environment should be considered. Conclusions: The findings indicate that the community type has a significant association with the risk of overweight. Tailored policies and urban renewal interventions should be developed for different community types.

Research Area(s)

  • Built environment, Community type, Multilevel logistic model, Random forest, Risk of obesity