西华师范大学学报(自然科学版)

基于全国人口普查和抽样调查数据，以12个主要城市群作为研究区域，并以地级及以上城市作为空间单元，采用时序比较、核密度估计、马尔科夫链分析以及地理探测器模型，对2000—2020年我国城市群人口老龄化的时空演变及驱动因素进行了分析，研究结果表明：(1)我国城市群的人口老龄化整体呈现出加速深化趋势，但不同城市群在加深速度上存在着显著的差异；(2)随着时间的推移，城市群所辖城市人口老龄化的离散程度有明显扩大的趋势，考察期内不同城市群所辖城市人口老龄化的空间分布及其演进区别明显，城市的相对老龄化水平在保持较强惯性的同时，也体现出一定的动态变化性；(3)2010年，城市群人口老龄化主要受老年人口惯性的影响，而2020年，除老年人口惯性外，人口自然增长率和人口迁移也是引致城市群人口老龄化空间分异的重要因素。结果总体表明，近二十年来我国不同城市群的人口老龄化展现出明显的时空差异与动态演变特征，因此各城市群应有针对性地制定差异化的人口老龄化政策，以更有效地应对日益严峻的老龄化挑战。

Taking 12 major urban agglomerations as the study area and cities at the prefecture level and above as the spatial units, and utilizing the national population census and sampling survey data as the basis, the spatio-temporal evolution and driving factors of population aging in China's urban agglomerations from 2000 to 2020 are analyzed by the methods of time series comparison, Kernel density estimation, Markov chain analysis, and geographical detector model.The results are as follows:(1) Population aging within China's urban agglomerations has presented an overall trend of accelerating and deepening, but there are significant differences in the deepening speed of different urban agglomerations.(2) With the passage of time, the dispersion degree of population aging in cities under the jurisdiction of urban agglomerations has shown a trend of obvious expansion; during the survey period, the spatial distribution and evolution of population aging in cities under the jurisdiction of different urban agglomerations have differed apparently; while maintaining a strong inertia, the relative aging level of cities has also reflected a certain dynamic variability.(3) In 2010,the population aging of urban agglomerations was mainly affected by the inertia of the elderly population, while in 2020,in addition to this factor, the natural population growth rate and population migration are also important factors that lead to the spatial differentiation of population aging in urban agglomerations.The overall results indicate that the population aging of different urban agglomerations in China has shown significant spatio-temporal differences and dynamic evolution characteristics in the past two decades.Therefore, each urban agglomeration should formulate targeted and differentiated population aging policies to respond more effectively to the increasingly severe challenge of aging.