Geospatial Analysis of Healthcare and Elderly Care Institutions in Wuhan: A Multi-method Approach to Assessing Spatial Equity

Yi Li^1,2,3*BO Li⁴Long Jingyi^2,5

• ¹Department of Public Administration, School of Public Administration, China University of Geosciences Wuhan, Wuhan, Hubei Province, China
• ²Wuhan Mental Health Center, Wuhan, Hubei Province, China
• ³Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
• ⁴School of Public Administration, China University of Geosciences Wuhan, Wuhan, Hubei Province, China
• ⁵Wuhan Mental Health Center, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China

Background: Achieving spatial equity in healthcare and elderly care services is critical for ensuring fair and effective service access among ageing populations. In rapidly urbanizing cities like Wuhan, the spatial distribution of facilities directly influences accessibility and integration outcomes. While existing research has primarily focused on service demand, the spatial distribution of medical and elderly care institutions which is a key factor for achieving effective integration remains underexplored. Method: The current study classifies medical and elderly care institutions into four categories and employs multiple spatial analysis methods such as Ripley's K-function (K), the geographical concentration index (G), the imbalance index (S), and kernel density analysis using Geographic Information System (GIS) to examine their spatial distribution in Wuhan. The spatial characteristics, distribution patterns, and interrelationships among these institutions are examined in the context of Wuhan, China. These spatial analysis methods are employed to assess disparities in the geographic distribution of institutions, highlighting spatial inequity between urban and peripheral areas.Results: Ripley’s K-analysis reveals significant spatial clustering across all four institution categories, with observed K-values exceeding expected thresholds and high confidence levels.The geographical concentration index G_0 = 27.73, with G values surpassing this threshold for all four categories, indicates a pronounced spatial concentration.The imbalance index (S > 0) indicates considerable disparities in the spatial distribution of resources across all categories.kernel density analysis identifies a strong concentration of institutions in central urban areas, highlighting notable urban‒rural disparities in service accessibility. Conclusion: The results reveal significant spatial clustering and disparities in the distribution of elderly care institutions, highlighting challenges in equitable resource allocation and urban planning. Ultimately limiting the accessibility, availability and equity of services for the elderly population. To address these disparities, policymakers should prioritize spatial equity in planning decisions, ensuring balanced service distribution that supports healthy ageing objectives and the goals of “Healthy China 2030. Such effort are essential to improving system efficiency and enhancing the quality of life for China’s ageing population, both in Wuhan and across the nation.