Urban and individual correlates of subjective well-being in China: An application of gradient boosting decision trees

Frontiers in Public Health

Public Health

Chenchen Kang¹  Yu Li¹  Xiaoyan Huang¹  Chun Yin² 

[1] Northwest Land and Resources Research Center, Global Regional and Urban Research Institute, Shaanxi Normal University, Xi’an, China;School of Resource and Environmental Sciences, Wuhan University, Wuhan, China;International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China;

关键词: happiness;    life satisfaction;    built environment;    urban environment;    threshold effect;    China;    health city;    machine learning;   

DOI  :  10.3389/fpubh.2023.1090832

 received in 2022-11-06, accepted in 2023-03-22,  发布年份 2023

来源: Frontiers

【 摘 要 】

IntroductionSubjective well-being (SWB) is attributable to both individual and environmental attributes. However, extant studies have paid little attention to the contribution of environmental attributes at the urban level to SWB or their nonlinear associations with SWB.MethodsThis study applies a machine learning approach called gradient boosting decision trees (GBDTs) to the 2013 China Household Income Survey data to investigate the relative importance of urban and individual attributes to and their nonlinear associations with SWB.ResultsThe urban and individual attributes make similar relative contributions to SWB. Income and age are the most important predictors. Urban facilities make a larger contribution than urban development factors. Moreover, urban attributes exert nonlinear and threshold effects on SWB. Cultural facilities and green space have inverted U-shaped correlations with SWB. Educational facilities, medical facilities, and population size are monotonically associated with SWB and have specific thresholds.DiscussionImproving urban attributes is important to enhancing residents’ SWB.

【 授权许可】

Unknown   
Copyright © 2023 Huang, Kang, Yin and Li.