Unveiling Spatial Dynamics and Determinants of Home-based and Institutional Long-term Care Services for the Elderly: Insights from MGWR

Objectives: This research aims to explore the spatial inequality of long-term care service uptake by using the spatial datasets of 229 administrative districts and spatial techniques. Methods: After undertaking the preliminary measure of exploratory spatial data analysis (ESDA), this research employed multiscale geographically weighted regression (MGWR) to identify the determinants of the spatial variations. Results: Ordinary least squares (OLS) reveals that home-based care service uptake was significantly affected by proportion of one-person elderly households, proportion of old dwellings aged 30 years or older, and the number of care workers per 1,000 elderly recipients. Also the institutional care service uptake was strongly influenced by proportion of old dwellings, and the number of care workers. Thus, MGWR demonstrates that the proportion of old dwellings is the most influential variable in contributing institutional care service uptake while the number of care workers is an important factor in explaining home-based care service uptake. Conclusions: MGWR is the best-fit-model to explain the variables affecting the spatial inequality of the long-term care services. The distinctive demand for the two types of care services across various districts underscores the public interventions to address the spatial inequality and to ensure health equity for the elderly.