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GIS-Based Analysis of Elderly Care Facility Distribution and Supply–Demand Coordination in the Yangtze River Delta

Author

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  • Huihua Hu

    (School of Geomatics Science and Technology, Nanjing Tech University, Nanjing 211816, China)

  • Hua Shao

    (School of Geomatics Science and Technology, Nanjing Tech University, Nanjing 211816, China)

  • Yang Li

    (Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China
    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 211212, China)

  • Mengfan Guan

    (School of Geomatics Science and Technology, Nanjing Tech University, Nanjing 211816, China)

  • Jiaxing Tong

    (School of Geomatics Science and Technology, Nanjing Tech University, Nanjing 211816, China)

Abstract

This study addresses the challenges related to the distribution of elderly care facilities in the Yangtze River Delta (YRD) region, which is experiencing a rapidly aging population. With over 176 million people aged 65 and above in China as of 2019 and the elderly population in the YRD continuing to grow, the study analyzes the spatial distribution, evolution, and supply–demand balance of elderly care facilities. Using GIS technologies, multi-source data analysis, and spatial autocorrelation techniques, the research identifies key regional patterns. Shanghai exhibits a clear hierarchical distribution of facilities, Jiangsu shows a “south strong, north weak” trend, while Zhejiang and Anhui demonstrate the opposite. The study also highlights a shift towards smaller, community-based care facilities, reflecting the growing demand for more localized services. It uncovers significant spatial mismatches and low coordination between supply and demand, particularly in rural and urban fringe areas, indicating the need for better regional coordination and more balanced resource distribution. To address these challenges, the study recommends (a) establishing cross-regional elderly care resource-sharing mechanisms; (b) promoting the development of small, community-based facilities; (c) integrating urban and rural services; and (d) leveraging technology for smart elderly care, including the use of big data and AI to optimize service delivery. These strategies aim to improve the equity and accessibility of elderly care services, ensuring that underserved areas receive better support. The findings provide a comprehensive framework for elderly care policies, offering valuable insights for other rapidly urbanizing regions and countries facing similar demographic challenges.

Suggested Citation

  • Huihua Hu & Hua Shao & Yang Li & Mengfan Guan & Jiaxing Tong, 2025. "GIS-Based Analysis of Elderly Care Facility Distribution and Supply–Demand Coordination in the Yangtze River Delta," Land, MDPI, vol. 14(4), pages 1-24, March.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:4:p:723-:d:1622304
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    References listed on IDEAS

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