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Influence and Mechanism of a Multi-Scale Built Environment on the Leisure Activities of the Elderly: Evidence from Hefei City in China

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  • Huiran Han

    (School of Geography and Tourism, Anhui Normal University, No. 189 Huajinnan Street, Yijiang District, Wuhu 241002, China)

  • Kai Yang

    (School of Geography and Tourism, Anhui Normal University, No. 189 Huajinnan Street, Yijiang District, Wuhu 241002, China)

  • Chengfeng Yang

    (School of Geography and Tourism, Anhui Normal University, No. 189 Huajinnan Street, Yijiang District, Wuhu 241002, China)

  • Gang Yang

    (School of Geography and Tourism, Anhui Normal University, No. 189 Huajinnan Street, Yijiang District, Wuhu 241002, China)

  • Lingyi Xu

    (School of Geography and Tourism, Anhui Normal University, No. 189 Huajinnan Street, Yijiang District, Wuhu 241002, China)

Abstract

Built environment characteristics such as walkability, land use diversity, infrastructure accessibility and attractiveness may support or hinder the elderly’s leisure activities, which in turn affects their health. Promoting the elderly’s leisure activities through the creation of a positive built environment is of great relevance to healthy aging. In the context of the continuous increasing of aging in China, promoting leisure activities for the elderly through improving the built environment has become an essential issue in urban geography and urban planning. Based on the questionnaire survey data of the elderly in Hefei City, a multilevel ordered probit regression model was used to investigate the mechanism of the multi-scale built environment on leisure activities of the elderly. The results show that: (1) more than 60% of the elderly can carry out leisure activities more than seven times a week, more than 50% of the elderly have a duration of fewer than 30 min for each leisure activity, and there are significant spatial differences in the frequency and duration of their trips at multiple scales in city, community and residential district. (2) Residential quality and community-level land use mixture, the density of leisure facilities, proximity to high-level urban roads, community security, living in the old city, and individual characteristic variables such as age, education, and satisfaction with neighborhood interaction positively contribute to the leisure activities of the elderly. In contrast, the community activity participation and the location close to expressways and railway lines have a significantly negative impact on the leisure activities of the elderly. (3) The mechanism of interactions between multi-scale built environments on the leisure activities of the elderly is mainly summarized as the transmission effect and substitution effect. The transmission effect shows that the differences in the community-level built environment are primarily caused by the differences in the city-level built environment. In contrast, the substitution effect shows that the multi-scale built environment such as residential districts, communities, and cities jointly affect the leisure activities of the elderly. Based on the mechanism of the built environment at different scales, this study can provide theoretical references and planning implications to improve the built environment through planning means such as enhancing the walkability of streets, the accessibility of facilities and the scale of greenery in order to promote active leisure activities and improve the health of the elderly.

Suggested Citation

  • Huiran Han & Kai Yang & Chengfeng Yang & Gang Yang & Lingyi Xu, 2022. "Influence and Mechanism of a Multi-Scale Built Environment on the Leisure Activities of the Elderly: Evidence from Hefei City in China," IJERPH, MDPI, vol. 19(15), pages 1-24, July.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:15:p:9237-:d:874299
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    References listed on IDEAS

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    1. Reid Ewing & Robert Cervero, 2010. "Travel and the Built Environment," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 265-294.
    2. Ta, Na & Zhao, Ying & Chai, Yanwei, 2016. "Built environment, peak hours and route choice efficiency: An investigation of commuting efficiency using GPS data," Journal of Transport Geography, Elsevier, vol. 57(C), pages 161-170.
    3. Hou, Yuting & Yap, Winston & Chua, Rochelle & Song, Siqi & Yuen, Belinda, 2020. "The associations between older adults’ daily travel pattern and objective and perceived built environment: A study of three neighbourhoods in Singapore," Transport Policy, Elsevier, vol. 99(C), pages 314-328.
    4. Cheng, Long & Shi, Kunbo & De Vos, Jonas & Cao, Mengqiu & Witlox, Frank, 2021. "Examining the spatially heterogeneous effects of the built environment on walking among older adults," Transport Policy, Elsevier, vol. 100(C), pages 21-30.
    5. Handy, Susan & Cao, Xinyu & Mokhtarian, Patricia L., 2005. "Correlation or causality between the built environment and travel behavior? Evidence from Northern California," University of California Transportation Center, Working Papers qt5b76c5kg, University of California Transportation Center.
    6. Bindong Sun & Chun Yin, 2020. "Impacts of a multi-scale built environment and its corresponding moderating effects on commute duration in China," Urban Studies, Urban Studies Journal Limited, vol. 57(10), pages 2115-2130, August.
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    Cited by:

    1. Junyu Lu & Meilin Dai & Fuhan Li & Ludan Qin & Bin Cheng & Zhuoyan Li & Zikun Yao & Rong Wu, 2023. "The Impact of Urban Built Environments on Elderly People’s Sense of Safety and Adaptation to Aging: A Case Study of Three Major Urban Agglomerations in China," Land, MDPI, vol. 12(8), pages 1-18, July.
    2. Yiwen Zhang & Haizhi Luo & Jiami Xie & Xiangzhao Meng & Changdong Ye, 2023. "The Influence and Prediction of Built Environment on the Subjective Well-Being of the Elderly Based on Random Forest: Evidence from Guangzhou, China," Land, MDPI, vol. 12(10), pages 1-16, October.
    3. Yuan Zheng & Bin Cheng & Letian Dong & Tianxiang Zheng & Rong Wu, 2024. "The Moderating Effect of Social Participation on the Relationship between Urban Green Space and the Mental Health of Older Adults: A Case Study in China," Land, MDPI, vol. 13(3), pages 1-21, March.

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