With the deepening of population ageing, the spatial planning of an elderly care service system faces unprecedented challenges. Building an elderly care service network that aligns with the pace of population ageing has become increasingly important and urgent. Based on annual longitudinal data on older adults’ health status and care service utilization from Japan’s Long-Term Care Insurance (LTCI) system, this study quantifies the relationship between changes in health status and elderly care service demand using a discrete time homogeneous Markov model and Poisson regression analysis. Subsequently, Geographic Information System (GIS) techniques are applied to conduct spatial analysis of the urban built environment to identify living service centres for older adults. Indicators including distance, supply–demand balance, and service capacity are then integrated through multi-objective clustering optimization to construct a multi-level elderly care service network system, achieving a quantitative linkage between elderly health status and spatial demand-oriented planning. Finally, the proposed integrated framework, which combines health status transitions, service demand estimation, and spatial allocation, is applied to Qinhuai district in Nanjing, China, generating practical policy recommendations that promote the integration of healthy ageing and precision service delivery.
Wang et al. (Sun,) studied this question.