Spatial analysis demonstrates the bidirectional relationship between healthcare decline and depopulation, suggesting urgent policy interventions.
Depopulation has become a pressing structural issue in many countries, with South Korea experiencing one of the most rapid national decreases in recent years. Depopulation and medical service provision are closely interconnected; however, existing studies have predominantly examined their relationship in a unidirectional manner, overlooking the dynamic interplay between the two. Using spatial analysis, Granger causality tests, and spatial panel modeling, this study demonstrates the spatiotemporal relationship between population decline and healthcare contraction. Our analysis reveals that regions experiencing population loss tend to have fewer medical institutions, indicating significant spatial dependence. We also find that primary medical services play a key role in preventing population decline, advanced medical services, meanwhile, tend to follow rather than prevent population trends, deepening disparities in underserved regions. These sequential relationships suggest the potential for a self-reinforcing cycle of regional decline. Our findings highlight the urgent need for integrated policies that sustain essential healthcare in underserved regions. Such strategies should combine short-term interventions with long-term planning to mitigate the adverse effects of depopulation on healthcare infrastructure and local resilience. • The study identifies a bidirectional feedback loop between population loss and healthcare infrastructure decline. • Primary medical institutions significantly help mitigate depopulation through early intervention and improved living conditions. • Advanced medical services tend to follow population trends, making them vulnerable in shrinking regions. • Spatial analysis reveals that depopulated areas often overlap with low medical service density. • Policy must prioritize healthcare investment in depopulating regions to prevent further decline and regional inequality.
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Lee et al. (2026) studied this question.
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