Accessibility is a key indicator for assessing the spatial configuration of elderly care institutions (ECIs). Identification of its spatial disparities is crucial for improving resource allocation efficiency and promoting healthy aging. However, existing accessibility evaluations have insufficient modeling precision in terms of adapting to dynamic traffic conditions and the actual needs of elderly people. This study introduces a novel approach by integrating real-time navigation data, the elderly’s preferences, and traditional accessibility evaluations to analyse the accessibility of ECIs at district and street-scale spatial units in Fuzhou, China. Using interpolation, trend, and cluster analyses in ArcGIS and SPSS software, we further identified the spatial disparity characteristics of elderly care institution accessibility. The results show that the current spatial distribution of ECIs does not adequately align with the demand distribution of elderly populations. This is manifested in several ways: (1) inefficient allocation of elderly care resources, as evidenced by the fact that while the central areas and their surroundings offer a greater number of accessible ECIs, these areas also have a higher elderly population densities and generally longer service access times; (2) significant spatial disparities in elderly care institution accessibility with polarized characteristics: central areas characterized by intensive development exhibit markedly higher accessibility compared to peripheral areas; (3) mismatches between supply and demand (i.e., accessibility of ECIs and elderly population) in certain urban local areas, specifically within and around central areas, as well as certain coastal areas. These findings highlight the urgent need for implementing differentiated planning strategies and policy interventions to ensure a more equitable distribution of ECIs. The proposed method in this study provides urban planners and policymakers with a more refined scientific tool for effectively assessing the accessibility of ECIs, identifying shortcomings in resource allocation, and creating more age-friendly living environments. This approach can be adapted to support healthy aging initiatives in diverse urban contexts.
Ninglong You (Mon,) studied this question.