PROGRESS IN GEOGRAPHY ›› 2018, Vol. 37 ›› Issue (3): 352-362.doi: 10.18306/dlkxjz.2018.03.006

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Spatiotemporal characteristics and influencing factors of population aging in Jilin Province

Lin MEI1,2(), Yanhua GUO1, Yan CHEN1   

  1. 1. College of Geographical Sciences, Northeast Normal University, Changchun 130024, China
    2. College of Humanities and Sciences of Northeast Normal University, Changchun 130017, China
  • Received:2017-04-14 Revised:2017-12-27 Online:2018-03-28 Published:2018-03-28
  • Supported by:
    National Natural Science Foundation of China, No.41471111

Abstract:

Rapid population aging has a broad and profound impact on the sustainable development of China's economy, and the country has implemented some policies and measures to tackle the problem of rapid population aging. Using ArcGIS 10.1, this study analyzed the spatiotemporal differentiation and influencing factors of population aging in Jilin Province by selecting the coefficient of aged population as the indicator of aging population. Data from the fourth, fifth, and sixth population census of Jilin Province were analyzed by using quantitative methods such as population gravity model, spatial autocorrelation, semi-variant function, and multiple linear regression. The results indicate that: (1) The difference of population aging in the counties and cities of Jilin Province is significant, and the progress is accelerating. The barycenter of population aging in had been moving from northwest to southeast of the province, but at a decreasing speed; (2) Through global spatial autocorrelation analysis, the population aging of Jilin Province presents a positive and enhancing spatial autocorrelation characteristics and trend; (3) Local spatial autocorrelation analysis indicates that the high-value areas of population aging cluster in the east of the province and low-value areas cluster in the west; (4) The spatiotemporal differentiation of aging in Jilin Province was mainly caused by structural factors, while random factors contributed less to the overall variation. In the other words, the spatial heterogeneity caused by spatial autocorrelation is more intense than that caused by random factors in the population aging. The eastern-western difference is the primary contributor to the spatial differentiation of population aging. (5) The main structural factors influencing population aging in the province were birth rate, per capita GDP, migration rate, and urbanization rate. The birth rate and per capita GDP factors have negative impacts on the population aging, however, migration rate and urbanization rate have positive impacts on population aging. Birth rate is the leading factor, and migration rate plays a key role in prompting population aging. Urbanization rate is increasingly more significant for population aging.

Key words: population aging, coefficient of aging population, spatiotemporal differentiation, influencing factors, Jilin Province