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.

An aging population is one of the main features of China's current population structure, and it is a key area that needs attention to achieve high-quality population development. Because of its unique geographical environment, economic conditions, and sociocultural background, the study of population aging in the karst region of southwest China is particularly important. However, there is a lack of research exploring the regional differentiation of population aging and its influencing factors in the karst regions of southwest China. In light of this, we chose Anshun City, located in Guizhou Province's southwest area, as the case study area. We used the Lorenz curve and spatial autocorrelation to study the differences in the spatial distribution pattern of population aging and introduced 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 with 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) revealed a gradually increasing trend from south to north. At the township scale, both the OPP and the OPD showed significant spatial positive correlation, and the spatial agglomeration characteristics were obvious. OPD and OPP have a positive spatial correlation at the global level, and townships with similar OPP or OPD were spatially adjacent. The spatial distribution characteristics of population aging are the consequence of complex contributions such as natural, social, economic, and karst factors. Further, the spatial distribution pattern of aging is determined by a variety of influencing 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.