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Elderly Residents’ Uses of and Preferences for Community Outdoor Spaces during Heat Periods

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  • Xiaolin Yang

    (College of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China)

  • Yini Fan

    (College of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China)

  • Dawei Xia

    (College of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China)

  • Yukai Zou

    (College of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China)

  • Yuwen Deng

    (College of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China)

Abstract

The downtown cores of many cities are characterized by aged communities that tend to host a relatively high population of elderly retirement residents. The availability and usage of outdoor spaces within these communities play a crucial role in promoting active aging, providing essential locations for rest, activities, and social interaction among the elderly. However, in the planning and design of these spaces, attention is often focused on the safety and mobility requirements of the elderly population, while a lack of research is apparent in the area of elderly-specific preferences for spaces designed for relaxation and communication. In this study, we selected an aging community as the research target and conducted a detailed investigation of the outdoor spaces where the elderly residents gather and build up spontaneously in summer. Our objective was to evaluate the environmental factors influencing the selection of these outdoor spaces by the elderly for relaxation and communication. We analyzed the correlations between these factors and the number of occupants in these spaces and developed predictive models accordingly. The findings indicate that the environmental factors impacting the utilization of outdoor spaces by the elderly during heat periods within the community are, in order of importance: temperature, relative humidity, human traffic flow, and noise levels. These factors include physical and social aspects; temperature is a negative correlation factor affecting the use of outdoor space by the elderly, and the rest are positive correlation factors. This shows that the elderly like to gather and chat in a cool, crowded, and lively environment. Through the data analysis, it was determined that the random forest regression model was the most effective in predicting the number of residents remaining in these spaces. With a coefficient of determination ( R 2 ) of 0.7958, the model can assist in community update planning and design, help in selecting outdoor spaces, and improve the quality of the outdoor environment. This study discusses the factors influencing the elderly’s use of community outdoor space from the physical and social levels, and the prediction model is significant for the optimization of spatial elements and spatial location.

Suggested Citation

  • Xiaolin Yang & Yini Fan & Dawei Xia & Yukai Zou & Yuwen Deng, 2023. "Elderly Residents’ Uses of and Preferences for Community Outdoor Spaces during Heat Periods," Sustainability, MDPI, vol. 15(14), pages 1-20, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11264-:d:1197751
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    References listed on IDEAS

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    1. Karmele Herranz-Pascual & Ioseba Iraurgi & Itziar Aspuru & Igone Garcia-Pérez & Alvaro Santander & José Luis Eguiguren, 2022. "Integrating Soundscape Criteria in Urban Sustainable Regeneration Processes: An Example of Comfort and Health Improvement," Sustainability, MDPI, vol. 14(6), pages 1-15, March.
    2. Shiwang Yu & Na Guo & Caimiao Zheng & Yu Song & Jianli Hao, 2021. "Investigating the Association between Outdoor Environment and Outdoor Activities for Seniors Living in Old Residential Communities," IJERPH, MDPI, vol. 18(14), pages 1-16, July.
    3. Wei-Yin Loh, 2014. "Fifty Years of Classification and Regression Trees," International Statistical Review, International Statistical Institute, vol. 82(3), pages 329-348, December.
    4. Finlay, Jessica M., 2018. "‘Walk like a penguin’: Older Minnesotans' experiences of (non)therapeutic white space," Social Science & Medicine, Elsevier, vol. 198(C), pages 77-84.
    5. Sugiyama, T. & Gunn, L.D. & Christian, H. & Francis, J. & Foster, S. & Hooper, P. & Owen, N. & Giles-Corti, B., 2015. "Quality of public open spaces and recreational walking," American Journal of Public Health, American Public Health Association, vol. 105(12), pages 2490-2495.
    6. Sungduck Lee & Emily Talen, 2014. "Measuring Walkability: A Note on Auditing Methods," Journal of Urban Design, Taylor & Francis Journals, vol. 19(3), pages 368-388, May.
    7. Atuoye, Kilian Nasung & Luginaah, Isaac & Hambati, Herbert & Campbell, Gwyn, 2019. "Politics, economics, how about our health? Impacts of large-scale land acquisitions on therapeutic spaces and wellbeing in coastal Tanzania," Social Science & Medicine, Elsevier, vol. 220(C), pages 283-291.
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