Objectives: As South Korea formally transitioned into a super-aged society at the close of 2024, with approximately one-fifth of its elderly population residing in Seoul, the agenda of both healthy aging and aging-in-place (AIP) at the local level has become a crucial policy priority. This challenge is particularly significant given the uneven distribution of public resources across communities within Seoul. Addressing this spatial inequality, the present study investigates the spatial patterns and determinants of elderly care facilities, specifically those providing in-home supportive and medical services, across 426 administrative districts in Seoul.Methods: This empirical research utilizes secondary spatial datasets, employing multiple regression methodologies: a global non-spatial regression model (ordinary least squares, OLS), a regional spatial regression model (geographically weighted regression, GWR), and a local spatial regression model (multiscale geographically weighted regression, MGWR), which were comparatively assessed to enhance methodological robustness.Results: Results from these spatial regression models consistently indicated that the densities of both types of elderly care facilities are significantly and positively associated with two primary predictors—high-density, low-rise housing configurations and population density. Importantly, the spatial analyses demonstrated that the MGWR model provided the most accurate and reliable insights by effectively capturing local variations across multiple spatial scales.Conclusions: These findings underscore the importance of context-sensitive policy interventions. Consequently, jurisdictions are encouraged to adopt spatially targeted strategies to adequately allocate social services and community resources, supporting elderly populations in successfully aging-in-place within the evolving demographic landscape of a super-aged era.
Yang et al. (Sat,) studied this question.