ORIGINAL RESEARCH article
Front. Public Health
Sec. Aging and Public Health
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1598394
Spatial-Temporal Evolution and Associated Factors of Eldercare Institutions in Shanghai
Provisionally accepted
- 1School of Social Development, East China Normal University, Shanghai, China
- 2Center for Applied Science in Health and Aging, Bowling Green, Kentucky, United States
- 3Department of Economics, University of Wisconsin-Madison, Madison, Alabama, United States
- 4Department of Cognitive Studies, Vanderbilt University, Nashville, Georgia, United States
- 5Shanxi Provincial Water Conservancy Development Center, Taiyuan, China
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Background: Shanghai is one of the first Chinese cities to tackle the challenges presented by an aging population. In response, the city has been actively seeking solutions for eldercare within a metropolitan context. This study is based on data from 1,272 eldercare institutions in Shanghai. It uses spatial analysis methods to visually display the spatial evolution of eldercare institutions in the city and analyzes the influencing factors of their spatial distribution patterns using a geographic detector approach.Methods: The research methodology used in the study includes Kernel Density Estimation for visualizing the spatial distribution of eldercare institutions in Shanghai, the Rand Index for measuring the match between eldercare institutions and the older adult population, and Geographically Weighted Regression for addressing spatial heterogeneity by providing local estimates for regression coefficients at different geographical locations.Results: The number of eldercare institutions in Shanghai has seen significant growth over the past twenty years, increasing fourfold due to the rise in both public and private facilities. Eldercare institutions in Shanghai exhibit clear spatial clustering features, evolving from a central cluster to a pattern of one major center surrounded by multiple secondary centers. The distribution of eldercare institutions and the aging population shows a positive trend, with the matching degree constantly increasing. The mean deviation index (M) decreased from 0.015 in 2005 to 0.011 in 2020. However, resources for eldercare institutions in central urban areas remain relatively scarce, particularly in Xuhui, Jing'an, and Putuo districts. Factors influencing the distribution of eldercare institutions show spatial heterogeneity, with varying correlations with residential, recreational, commercial, transportation-related, and healthcare facilities.Conclusions: The findings suggest that Shanghai has made progress in expanding eldercare resources to meet the needs of its aging population. However, there are still disparities in the distribution of these facilities, particularly in central urban areas. Understanding the spatial patterns and factors influencing the location of eldercare institutions can guide future planning efforts to ensure equitable access to care for the older adults in Shanghai.
Keywords: Eldercare institutions, spatial distribution, geographically weighted regression (GWR), Shanghai Urbanization, Aging Population
Received: 23 Mar 2025; Accepted: 06 Jun 2025.
Copyright: © 2025 Yin, Cui, Wu, Cui and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Xingxing Yin, School of Social Development, East China Normal University, Shanghai, 200062, China
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