Bridging the healthcare gap for aging populations: rethinking spatial equity in high-density cities based on the SDMI index

Against the backdrop of global population aging and adjustments in health policies, the fair and efficient allocation of urban health resources for older adults has become a key issue in urban planning and resource management. From a supply-demand matching perspective, this study proposes a classification method for urban health resources for older adults, categorizing them into three types: uniform distribution, hierarchical, and independent. A classification and evaluation system is constructed based on four core dimensions: accessibility, service load, selectivity, and suitability. This study highlights the importance of spatial heterogeneity analysis and multi-source data integration. By combining GIS spatial analysis, network modeling, and the Analytic Hierarchy Process, a Spatial Demand-Supply Matching Index (SDMI) calculation model is developed. Through weighted evaluation, the model quantifies the degree of matching between supply and demand, assessing the balance of elderly health resource distribution across different regions. Using Chongqing, a typical high-density megacity, as a case study, the proposed evaluation framework effectively identifies areas with uneven resource distribution, excessive burden, or limited accessibility, providing data-driven optimization strategies. The results indicate that this method can systematically assess resource accessibility, supply-demand matching, and the rationality of spatial distribution across urban areas, thereby supporting improvements in equity and accessibility of healthcare resources allocation. This approach can be adapted to other high-density cities with context-specific calibration of indicators and weights, contributing to more efficient health resource provision in aging societies and the sustainable development of urban health service systems.