Study on the differences and influencing factors of spatial distribution of population aging at township scale: a case study of township research units in Anshun City, China - Zhang, Xuebin; Shi, Jing; Chao, Meng; Yin, Junfeng (Frontiers in Public Health, 2024)
Population aging is one of the main feature of China's current population structure change, and it is a key area that needs to be paid attention to to achieve high-quality population development. Because of its unique geographical environment, economic conditions and socialcultural background, the study of population aging in karst region of southwest China has particularity and complexity. However, There is a lack of research to explore regional differentiation of population aging and its influencing factors in the karst regions of southwest China. In light of this, we have chosen Anshun City, located in Guizhou Province's southwest, as the case study area, uses the Lorentz curve and spatial autocorrelation to study the differences in the spatial distribution pattern of population aging, and introduces Multi-scale Geographical Weighted Regression to explore its influencing factors. The results show that Anshun City's older people population proportion (OPP) is generally high and that there are more than 7% of the older people there, making it part of an aging society. The OPP appeared "high in the east and low in the west" in spatial distribution, the older people population density OPD presents a trend of increasing gradually from south to north in space. At the township scale, both the OPP and the OPD showed significant spatial positive correlation, and the spatial agglomeration characteristics are obvious. The OPD and OPP have a positive spatial correlation in global scope, and townships with similar OPP or OPD were spatially adjacent. Spatial distribution characteristics of population aging was the consequence of complex contributions such as natural factors, social factors, economic factors, and karst factors. The spatial distribution pattern of aging is determined by a variety of influence factors, which have different directions and intensities. Therefore, it is necessary to formulate and implement corresponding policies and strategies to deal with the aging problem in the future.