Study on the Spatiotemporal Pattern Evolution and Influencing Factors of Population Aging in Henan Province

Abstract

This study utilized census data from Henan Province for the years 2000, 2010, and 2020 to investigate the spatiotemporal evolution of population aging, defined by the proportion of the population aged 65 and above. Employing spatial analysis techniques such as spatial autocorrelation and the standard deviation ellipse, the research mapped out the progression and distribution of aging demographics. Furthermore, the study delved into the influencing factors of aging using an optimal parameters-based geographical detector. Results indicate a deepening degree of population aging in Henan Province, transitioning from an adult type to an old type structure. There is a marked positive spatial correlation among counties, with high-value aging areas initially decreasing, then increasing, and notably spreading from the central to the central and southern regions of the province. The center of gravity for population aging, specifically around Changge City and Xuchang City, exhibits a trajectory moving southeast before shifting northwest. Factor detection reveals that in 2000, 2010, and 2020, the elderly dependency ratio predominantly influences the aging trend, with explanatory powers of 88.4%, 87.9%, and 90.9%, respectively. Interaction analysis indicates that the interaction between the old-child ratio and the elderly dependency ratio has a strong explanatory power for the aging patterns in Henan Province, reaching 97.3%, 97.0%, and 97.4%, respectively.

Keywords

• |population aging|spatial pattern evolution|spatial autocorrelation|influencing factors|optimal parameters-based geographical detector