Spatial Heterogeneity, Temporal Evolution, and Matching Levels of Population Aging, Nurses, and Elderly Care Facilities in China
Wei Li, XiaoXia Yu, YouChao Xu, Attiq‐Ur Rehman, Xi‐Yuan Peng, Wei Du, Juan Miao, Li Shi, XinRui Lu, SiQi Gao, Kang Zhong, Rui Feng, Yan Qian, Hong‐Lin ChenABSTRACT
Aim
The increasingly severe aging situation has imposed a burden on the healthcare system, and society needs to allocate more elderly care resources to meet the demand for elderly care services. This study aims to examine the spatiotemporal matching levels between the number of registered nurses, the number of beds in elderly care institutions, and the number of elderly care institutions at the provincial level in China from 2002 to 2023 and the degree of population aging.
Design
This is an ecological longitudinal study.
Methods
Spatial autocorrelation analysis was performed in ArcGIS version 10.8. Bayesian spatiotemporal modeling was conducted in R version 4.5.1 using the CARBayesST package, with four independent Markov chains constructed to examine spatiotemporal interactions. Additionally, an index was developed to evaluate the matching level between the degree of population aging and aging‐related care resources.
Results
The analysis of the matching level between population aging and elderly care resources revealed that approximately one‐third of the provinces in mainland China exhibited relatively high matching degrees. Beijing, Shanghai, Jiangxi, Jilin, Zhejiang, and Hubei demonstrated consistently favorable matching levels across all years.
Conclusions
Although spatiotemporal inequalities in the alignment between population aging and elderly care resource availability persist across mainland China, such disparities are gradually narrowing. The spatial distribution of nursing homes and care workers within provincial‐level administrative regions should be optimized to progressively reduce the inequality between aging and elderly care resource allocation.