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2025 , Vol. 44 >Issue 10: 2825 - 2840

DOI: https://doi.org/10.11821/dlyj020241160

老年人行为与养老服务

中国社会养老服务资源空间分异格局、影响因素与老龄化效应

  • 唐红林 , 1, 2, 3 ,
  • 刘晔 , 1, 2, 3
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  • 1.中山大学地理科学与规划学院，广州 510006
  • 2.广东省城市化与地理环境空间模拟重点实验室，广州 510006
  • 3.广东省公共安全与灾害工程技术研究中心，广州 510006
刘晔（1986-），男，广东广州人，博士，教授，博士生导师，主要从事人口地理、健康地理和城市地理研究。 E-mail:

唐红林（1996-），男，甘肃甘南人，博士研究生，主要从事健康地理与人口地理研究。E-mail:

收稿日期: 2024-10-25

  录用日期: 2025-01-21

  网络出版日期: 2025-10-09

基金资助

国家自然科学基金项目(42171196)

国家自然科学基金项目(42471264)

国家自然科学基金国际（地区）合作与交流项目(W2421049)

广州市基础与应用基础研究项目（领航类）(2024A04J6320)

广州市哲学社会科学发展“十四五”规划课题(2023GZYB83)

广州市哲学社会科学发展“十四五”规划课题(2024GZYB05)

收起

Spatial pattern and influencing factors of elderly-support service resources and their alignment with population aging in China

  • TANG Honglin , 1, 2, 3 ,
  • LIU Ye , 1, 2, 3
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  • 1. School of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China
  • 2. Guangdong Provincial Key Laboratory for Urbanization and Geo-simulation, Guangzhou 510006, China
  • 3. Guangdong Provincial Engineering Research Center for Public Security and Disaster, Guangzhou 510006, China

Received date: 2024-10-25

  Accepted date: 2025-01-21

  Online published: 2025-10-09

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摘要

探究养老服务资源空间分异特征及影响因素是积极应对人口老龄化战略和健康中国战略的基础性工作。以中国340个地级及以上行政单元为研究对象，结合统计年鉴、人口普查、遥感信息产品和民政部养老机构登记信息4类数据，运用综合指数法、泰尔指数及其分解技术和参数最优地理探测器等方法，基于总量和人均两类指标，刻画社会（机构）养老服务资源的空间分异格局，揭示养老服务资源的空间不均衡性，进而识别其影响因素，并探讨人口老龄化对养老服务资源配给的作用效应。结果表明：① 胡焕庸线是养老服务资源空间分布的重要分界线，养老服务资源总量呈现“东南半壁高，西北半壁低”的空间分布格局，人均养老服务资源则呈现“西北内陆高，东南沿海低”的空间分布格局。② 养老服务资源在总量和人均层面均具有空间不均衡性，Theil指数分别为0.283和0.066，养老服务资源区域间差异对总差异的贡献高于区域内部差异。③ 老龄化进程和财政投入是养老服务资源空间分异最重要的驱动因素。相较总量层面，政策倾斜力度对人均养老服务资源分布具有重要的均衡功能，而经济发展水平的影响能力趋弱。老龄化进程和经济发展水平与其他因子正向交互均会显著增强因子对养老服务资源总量和人均养老服务资源空间分异的解释力。④ 人口老龄化对养老服务资源配给具有非线性效应，拟合结果呈U型曲线，拐点大约在老龄化系数22.37%时，跨越拐点后养老服务资源水平随着人口老龄化深化而增加。

关键词： 人口老龄化; 养老服务资源; 空间分异; 参数最优地理探测器; 中国

本文引用格式

唐红林 , 刘晔 . 中国社会养老服务资源空间分异格局、影响因素与老龄化效应[J]. 地理研究, 2025 , 44(10) : 2825 -2840 . DOI: 10.11821/dlyj020241160

Abstract

Exploring the spatial differentiation characteristics and influencing factors of elderly-support service resources (ESSR) is essential for actively supporting the national strategies on population aging and Healthy China. Employing 340 prefecture-level and higher administrative units as the study subjects, this research integrates four data categories—statistical yearbooks, population censuses, remote sensing products, and registration records of elderly care institutions from the Ministry of Civil Affairs. Using the Comprehensive Index Method, the Theil Index and its decomposition, and the Optimal Parameters-based Geographical Detector Model, the study assesses the distribution level and pattern of ESSR from both aggregate and per capita perspectives. This approach characterizes the spatial disparities in ESSR allocation and identifies key influencing factors and underlying mechanisms. Furthermore, the impact and implications of population aging on the allocation of ESSR are also examined. The results show that: (1) Hu Line is an important dividing line of the spatial distribution of ESSR. The total ESSR presents a spatial pattern of “high in the southeastern half and low in the northwestern half”, while the per capita ESSR presents a pattern is featured by “high in the northwest inland and low in the southeast coast”. (2) ESSR is spatially uneven at both the total and per capita levels, with Theil index values of 0.283 and 0.066, respectively. The contribution of regional differences in ESSR to the total difference is higher than that of regional differences. (3) Population aging process and financial investment are the most critical driving factors behind the spatial differentiation of ESSR. Compared with the total level, the policy tilt at the per capita level plays a significant balancing role, whereas the influence of economic development is relatively limited. The positive interaction between the aging process and the level of economic development and other factors will significantly enhance the explanatory power of factors at the total and per capita levels. (4) Population aging has a nonlinear effect on the rationing of ESSR, and the fitting results show a U-shaped curve, with a turning point of approximately 22.37%. After that, as population aging intensifies, the level of per capita ESSR is expected to correspondingly rise.

Key words： population aging; elderly-support service resources; spatial distribution; Optimal Parameters-based Geographical Detector Model; China

致谢：真诚感谢二位匿名评审专家在论文评审中所付出的时间和精力，评审专家对本文影响因素选取依据、指标体系表达、结果分析、研究展望等方面的修改意见，使本文获益匪浅。

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[State Council. Notice of the State Council on Issuance of Five-Year Action Plan for the In-Depth Implementation of the People-Oriented New Urbanization Strategy. (2024-07-28) [2024-10-23].https://www.gov.cn/zhengce/content/202407/content_6965542.htm#.]

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