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Assessing Geographic Barriers to Access Long-Term Services and Supports in Chengdu, China: A Spatial Accessibility Analysis

Author

Listed:
  • Sen Lin

    (Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA)

  • Shikun Qin

    (School of Public Finance and Taxation, Southwestern University of Finance and Economics, Chengdu 611130, China)

  • Li Peng

    (College of Geography and Resources, Sichuan Normal University, Chengdu 610066, China)

  • Xueying Sun

    (School of Public Administration, Southwestern University of Finance and Economics, Chengdu 611130, China)

  • Xiaolu Dou

    (School of Urban and Environmental Science, Peking University, Beijing 100080, China)

Abstract

China’s rapidly aging population has intensified demand for long-term services and supports (LTSSs), yet geographic disparities in accessibility persist despite policy reforms like long-term care insurance (LTCI). This study evaluates spatial inequities in Chengdu, a megacity piloting LTCI, using an enhanced two-step floating catchment area (2SFCA) method with demand intensity coefficients and a spatial mismatch index (SMI). Results reveal critically low average accessibility: 0.126 LTSS beds and 0.019 formal caregivers per thousand recipients within a 60 min travel threshold. Accessibility declines sharply along urbanization gradients, with urban cores (“first loop”) exceeding suburban “second” and “third loop” by ratios of 1.5–2.1 and 2.0–8.0, respectively. Strong correlations with impervious surface ratios (R 2 = 0.513–0.643) highlight systemic urban bias in resource allocation. The SMI analysis uncovers divergent spatial mismatches: home care accessibility predominates in western suburbs due to decentralized small-scale providers, while institutional care clusters in eastern suburbs, reflecting government prioritization of facility-based services. Despite LTCI’s broad coverage (67% of Chengdu’s population), rural and peri-urban older adults face compounded barriers, including sparse LTSS facilities, inadequate transportation infrastructure, and reimbursement policies favoring urban institutional care. To address these inequities, this study proposes a multi-stakeholder framework: (1) strategic expansion of LTSS facilities in underserved suburban zones, prioritizing institutional care in the “third loop”; (2) road network optimization to reduce travel barriers in mountainous regions; (3) financial incentives (e.g., subsidies, tax breaks) to attract formal caregivers to suburban areas; (4) cross-regional LTCI coverage to enable access to adjacent district facilities; and (5) integration of informal caregivers into reimbursement systems through training and telehealth support. These interventions aim to reconcile spatial mismatches, align resource distribution with Chengdu’s urban–rural integration goals, and provide scalable insights for aging megacities in developing contexts. By bridging geospatial analytics with policy design, this study underscores the imperative of data-driven governance to ensure equitable aging-in-place for vulnerable populations.

Suggested Citation

  • Sen Lin & Shikun Qin & Li Peng & Xueying Sun & Xiaolu Dou, 2025. "Assessing Geographic Barriers to Access Long-Term Services and Supports in Chengdu, China: A Spatial Accessibility Analysis," Sustainability, MDPI, vol. 17(7), pages 1-22, April.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:7:p:3222-:d:1628240
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    References listed on IDEAS

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    1. Linggui Liu & Han Lyu & Yi Zhao & Dian Zhou, 2022. "An Improved Two-Step Floating Catchment Area (2SFCA) Method for Measuring Spatial Accessibility to Elderly Care Facilities in Xi’an, China," IJERPH, MDPI, vol. 19(18), pages 1-15, September.
    2. Youxu Zheng & Jiangdi Tan & Yaping Huang & Zhiyong Wang, 2022. "The Governance Path of Urban–Rural Integration in Changing Urban–Rural Relationships in the Metropolitan Area: A Case Study of Wuhan, China," Land, MDPI, vol. 11(8), pages 1-19, August.
    3. Hao Li & Jianshu Duan & Yidan Wu & Sizhuo Gao & Ting Li, 2021. "The Spatial Patterns of Service Facilities Based on Internet Big Data: A Case Study on Chengdu," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-12, September.
    4. Ye Han & Tong Shen, 2022. "Long-Term Care Insurance Pilot Programme in China: Policy Evaluation and Optimization Options—Taking the Pilot Programme in the Northeast of China as an Example," IJERPH, MDPI, vol. 19(7), pages 1-18, April.
    5. Wenqi Li & Li Zhang & Inhee Lee & Menelaos Gkartzios, 2023. "Overview of Social Policies for Town and Village Development in Response to Rural Shrinkage in East Asia: The Cases of Japan, South Korea and China," Sustainability, MDPI, vol. 15(14), pages 1-19, July.
    6. E Xie, 2011. "Income-Related Inequalities of Health and Health Care Utilization," Frontiers of Economics in China-Selected Publications from Chinese Universities, Higher Education Press, vol. 6(1), pages 131-156, March.
    7. Wencong Cai & Yuanjie Deng & Qiangqiang Zhang & Haiyu Yang & Xuexi Huo, 2021. "Does Income Inequality Impair Health? Evidence from Rural China," Agriculture, MDPI, vol. 11(3), pages 1-18, March.
    8. Shaoyao Zhang & Xueqian Song & Yongping Wei & Wei Deng, 2019. "Spatial Equity of Multilevel Healthcare in the Metropolis of Chengdu, China: A New Assessment Approach," IJERPH, MDPI, vol. 16(3), pages 1-15, February.
    9. Qin, Xuezheng & Hsieh, Chee-Ruey, 2014. "Economic growth and the geographic maldistribution of health care resources: Evidence from China, 1949-2010," China Economic Review, Elsevier, vol. 31(C), pages 228-246.
    10. E. Xie, 2011. "Income-related inequalities of health and health care utilization," Frontiers of Economics in China, Springer;Higher Education Press, vol. 6(1), pages 131-156, March.
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