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Disentangling the comparative roles of multilevel built environment on body mass index: Evidence from China
被引:19
|作者:
Wang, Xiaoquan
[1
]
Shao, Chunfu
[1
]
Yin, Chaoying
[2
]
Guan, Ling
[1
]
机构:
[1] Beijing Jiaotong Univ, Key Lab Transport Ind Big Data Applicat Technol C, Beijing, Peoples R China
[2] Nanjing Forestry Univ, Coll Automobile & Traff Engn, Nanjing, Peoples R China
来源:
基金:
中国国家自然科学基金;
关键词:
Built environment;
Relative importance;
Interactive effects;
Obesity;
Different geographic scales;
Machine learning method;
D O I:
10.1016/j.cities.2020.103048
中图分类号:
TU98 [区域规划、城乡规划];
学科分类号:
0814 ;
082803 ;
0833 ;
摘要:
One common goal of urban planning is to promote health, where the built environment (BE) is believed to play an essential role. This study provides new evidence for the links between body mass index (BMI) and the BE at different geographic scales in a unified framework. Based on a sample of 10,962 individuals across 95 cities in China, this study explores the collective effects of the BE attributes at neighborhood and city levels on BMI using a gradient boosting decision tree (GBDT) approach. Moreover, whether the relationships between the city-level BE attributes and BMI vary across social groups is revealed. The results indicate that the city-level BE attributes have larger collective effects on BMI than the neighborhood-level BE attributes. Specifically, population size is the greatest contributor to predicting BMI, with a relative importance of 13.92% among all influential factors. Moreover, it is found that the effects of city-level BE attributes vary across different social groups. These findings suggest it is of vital importance for urban planners to coordinate both neighborhoodand city-level BE planning to deter the risks of obesity, and urban planning can be more effective if it is implemented considering local socio-demographic characteristics.
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页数:12
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