地理学报 ›› 2017, Vol. 72 ›› Issue (6): 1001-1016.doi: 10.11821/dlxb201706005

• 城市研究 • 上一篇    下一篇

中国城市群人口老龄化时空格局

王录仓1(), 武荣伟2,3, 李巍1   

  1. 1. 西北师范大学地理与环境科学学院,兰州 730070
    2. 中国科学院新疆生态与地理研究所,乌鲁木齐 830011
    3. 中国科学院大学,北京 100049
  • 收稿日期:2016-07-04 修回日期:2017-01-06 出版日期:2017-06-25 发布日期:2017-07-13
  • 作者简介:

    作者简介:王录仓(1967-), 男, 甘肃天水人, 博士, 教授, 研究方向为城乡发展与规划研究。E-mail: wanglc007@nwnu.edu.cn

  • 基金资助:
    国家自然科学基金项目(41261042)

Spatial-temporal patterns of population aging on China's urban agglomerations

Lucang WANG1(), Rongwei WU2,3, Wei LI1   

  1. 1. College of Geography and Environment Science, Northwest Normal University, Lanzhou 730070, China
    2. Xinjiang Institute of Ecology and Geography, CAS, Urumqi 830011, China
    3. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2016-07-04 Revised:2017-01-06 Online:2017-06-25 Published:2017-07-13
  • Supported by:
    National Natural Science Foundation of China, No.41261042

摘要:

老龄化和城市化是当今世界面临的两大人口问题。城市群是城市发展到成熟阶段的空间组织形态,是老龄化的特殊区域。本文基于2000年和2010年全国人口普查分县数据,综合应用地理探测器和变异系数等方法,清晰地刻画了中国20个城市群人口老龄化的空间格局及其变化特征,审视了人口老龄化变化的影响因素。结果表明:① 2000年中国城市群人口老龄化平均水平为7.32%,其中12个城市群的人口属于成年型,到2010年时人口老龄化平均水平已上升为9.00%,除珠三角与宁夏沿黄城市群外,其余18个城市群均步入了老年型人口,表现出明显的水平升级与类型替变态势。② 老龄化高值、较高值区域不断向内陆城市群跃迁。③ 城市群老龄化的增量和增速存在显著的区域差异,老龄化水平的低值区和高值区增量少、增速慢,而较低值、中值和较高值区增量多、增速快。总体上表现出区域性城市群——国家级城市群——地区性城市群老龄化速度递减的态势。④ 在城市群内部,老龄化分布格局表现出隆升—塌缩并存的现象。国家级城市群内部老龄化分布格局从隆升结构向塌缩结构转变,城市群中心区人口老龄化水平降低;而地区性城市群和区域性城市群内部老龄化分布格局则从均质结构向隆升结构转变,中心区人口老龄化水平上升。⑤ 城市群人口老龄化是内外因素综合影响的结果,基期老龄化程度、人口年龄结构替变和人口流动性是主导性因素。其中人口年龄结构的普遍性抬升是城市群老龄化升级与类型替变的关键,低龄人口迁入到城市群对人口老龄化则起到“稀释作用”,城市群发育阶段不同引致的聚集和扩散效应对老龄化则起到诱导作用。

关键词: 城市群, 人口老龄化, 时空格局, 影响因素, 地理探测器, 中国

Abstract:

Aging and urbanization are two major population issues currently facing the world. Urban agglomeration is an advanced form of urbanization that encompasses the spatial organization of cities within a specific geographical area, and in which the process of aging differs from that in other regions. Based on county-specific data from population surveys in 2000 and 2010, we determined the spatial patterns and variations of aging populations in 20 urban agglomerations in China using geographical detector-based and coefficient of variation methods. We also examined the contributing factors of population aging variability. Results demonstrated that in 2000, older people accounted for 7.32% of the urban agglomeration demographic structure, with 12 of the 20 urban agglomerations defined as adult-type populations. In 2010, however, older people accounted for 9.00% of the urban agglomeration demographic structure and, except for those in the Pearl River Delta and Ningxia areas along the Yellow River, all the urban agglomerations entered the elderly population stage. Moreover, high-age and moderately high-age regions expanded towards inland urban agglomerations, with population aging increasing obviously and population type changing from adult to aging. In addition, significant regional differences in the incremental increases in the number of older people and growth rates of the aging populations existed in the urban agglomerations. Low-age and high-age regions had smaller increments and growth rates, whereas moderately low-age, mid-age, and moderately high-age regions had greater increments and growth rates, indicating a declining aging rate in the order of regional, national, and local urban agglomerations. Within each urban agglomeration, the distribution pattern of aging showed the coexistence of uplift and collapse. The distribution pattern of aging within national urban agglomerations changed from an increasing to collapsing structure, and population aging in central China reduced. Conversely, regional urban agglomerations changed from a homogeneous to an increasing structure, and population aging in the central region increased. Population aging of urban agglomerations was the result of internal and external factors, with changes in base period aging, population age structure, and population fluidity being the predominant factors. Universal uplift of the population age structure was a key factor affecting aging and population types in urban agglomerations. Furthermore, low-age population immigration into urban agglomerations had a "diluting effect" on population aging, and aggregation and diffusion effects caused by different development stages of urban agglomeration played important roles in aging and population migration.

Key words: urban agglomeration, population ageing, spatial-temporal patterns, influencing factors, geographical detector tool, China