The Influence and Prediction of Built Environment on the Subjective Well-Being of the Elderly Based on Random Forest: Evidence from Guangzhou, China

Yiwen Zhang, Haizhi Luo, Jiami Xie, Xiangzhao Meng () and Changdong Ye ()
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Yiwen Zhang: College of Horticulture, China Agricultural University, Beijing 100193, China
Haizhi Luo: Institute of the Building Environment & Sustainability Technology, School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Jiami Xie: College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China
Xiangzhao Meng: Institute of the Building Environment & Sustainability Technology, School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Changdong Ye: College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China

Land, 2023, vol. 12, issue 10, 1-16

Abstract: Aging and urbanization significantly impact the physical and mental well-being of the elderly population. Empirical investigations have highlighted the contribution of the built environment to promoting elderly health. However, there is a need for further exploration of the factors within the built environment that impact the subjective well-being (SWB) of the elderly. To address this, this study selected 50 communities in Guangzhou, where 1403 elderly people were surveyed. Employing the random forest, we have identified contributing factors of the built environment affecting the SWB of the elderly. Meanwhile, we used a prediction model constructed by random forest to predict the SWB level of the elderly. The results indicated that accessibility to parks (positive emotions (PA): 0.822, positive experiences (PE): 0.235), hospitals (PA: 0.680, PE: 0.546), and supermarkets (PA: 0.237, PE: 0.617) significantly contributed to PA and PE. On the other hand, factors such as population density had a significant contribution to negative emotions (NA: 0.431) and negative experiences (NE: 0.194). Based on the prediction results, the spatial distribution of SWB among the elderly can be derived. Overall, our study can provide planning and improvement strategies for built environments that promote SWB among the elderly.

Keywords: the elderly; subjective well-being; built environment; random forest; individual characteristic (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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