节点文献

中国典型城市群人口老龄化时空特征及影响因素研究

Research on Spatiotemporal Characteristics and Influencing Factors of Population Aging in Typical Urban Agglomerations in China

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 贾雨飞刘静玉张涛袁旺敏

【Author】 JIA Yufei;LIU Jingyu;ZHANG Tao;YUAN Wangmin;Research Center of Regional Development and Planning/College of Geographic Sciences/Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Region, Ministry of Education,Faculty of Geographical Science and Engineering, Henan University;

【通讯作者】 刘静玉;

【机构】 河南大学地理科学与工程学部区域发展与规划研究中心/地理科学学院/黄河中下游数字地理技术教育部重点实验室

【摘要】 中国2001年65岁以上人口占比7.1%标志正式进入老龄化社会,2021年65岁以上人口占比14.2%步入深度老龄化,中国老龄化速度快、老龄化现象日益严重.城市群是中国社会经济发展的重要载体,也是人口集聚的主体,其人口老龄化更易引发社会各界关注,不同特征城市群的人口老龄化研究具有重要的典型性和指示意义.以中原城市群、京津冀城市群和长三角城市群为案例,选取老年人口规模、老龄化率等指标,运用空间自相关分析和地理探测器等方法,在县域尺度对比研究2000-2020年城市群人口老龄化的时空特征及影响因素.结果表明:(1)3个城市群老龄化类型演变进程有所不同.2000-2020年中原城市群老龄化持续加深,长三角城市群老龄化普遍加深,京津冀城市群老龄化进程更快.同时,中原城市群表现出老龄化水平低、进程快的特点.(2)3个城市群老年人口都有明显的集聚态势和显著的空间关联特征.(3)3个城市群老龄化主导因素及变化趋势有明显差异.人口因素是各城市群老龄化的长期主导因素,各个影响因子交互作用对3个典型城市群人口老龄化的解释力均较强.该研究不仅可以为各城市群应对人口老龄化提供决策依据,而且对我国全域解决此问题具有重要的国家战略意义和示范带头作用.

【Abstract】 In 2001, 7.1% of population aged over 65 years marked the official entry into an ageing society, and in 2021, 14.2% of the population aged over 65 years stepped into deep ageing. China’s aging rate is fast and the aging phenomenon is becoming increasingly serious. Urban agglomerations are important carriers of China’s socio-economic development as well as the main body of population agglomeration, and their aging population is more likely to attract attention from all sectors of society. The study of population ageing in urban agglomerations with different characteristics has important typical and indicative significance. Taking the Central Plains, Beijing-Tianjin-Hebei, and the Yangtze River Delta as examples, this paper selected the number of elderly population and aging coefficient to compare the spatiotemporal characteristics and influencing factors of population aging at the county level. The results show that:(1) The distribution of main aging types in the three urban agglomerations were different. The aging of the Central Plains Urban Agglomeration continued to deepen from 2000 to 2020, the aging of the Yangtze River Delta Urban Agglomeration generally deepened, and the aging process of the Beijing-Tianjin-Hebei Urban Agglomeration was faster. At the same time, the Central Plains Urban Agglomeration exhibited a low level of ageing and a rapid process.(2) The elderly population in the three city clusters all have obvious agglomeration trends and significant spatial correlation characteristics.(3) There are obvious differences in the dominant factors and changing trends of ageing in the three city clusters. Demographic factors are the long-term dominant factors of ageing in each city cluster. The explanatory power of the interaction of various influencing factors on the aging of population in the three typical urban agglomerations is stronger. The study not only provides a decision-making basis for each urban agglomeration to cope with population ageing, but also has important national strategic significance and demonstration leading role in solving this problem throughout China.

【基金】 2024年度河南省哲学社会科学规划项目(2024BJJ016);河南省高校人文社会科学研究一般项目(2025-ZDJH-356);2025年度省软科学研究计划项目(252400411185)
  • 【文献出处】 河南大学学报(自然科学版) ,Journal of Henan University(Natural Science) , 编辑部邮箱 ,2025年05期
  • 【分类号】C924.24
  • 【下载频次】139
节点文献中: 

本文链接的文献网络图示:

本文的引文网络