Background: Since 2004, South Korea has maintained the highest suicide rate among OECD countries, marking it as a critical public health crisis. Beyond individual factors, suicide is deeply influenced by regional contexts, necessitating a comprehensive analysis of both spatial and temporal dimensions.
Objective: This study analyzes spatiotemporal distribution patterns of suicide mortality and identifies protective factors by comparing "cold spot" regions with nationwide trends.
Methods: Age-standardized suicide rates and regional characteristics for 229 administrative districts were collected from 2012 to 2023. Spatial autocorrelation was assessed using Moran's I, and spatiotemporal clusters were identified through Emerging Hot Spot Analysis. To identify unique protective factors, panel regression models incorporating one-year lagged effects, including pooled OLS, fixed-effects, and random-effects, were applied to compare 70 cold spots against the nationwide sample.
Results: Suicide rates showed significant spatial autocorrelation, identifying 70 cold spots and 5 hot spots. Panel regression revealed that the proportion of the elderly population was a protective factor nationwide (b = -0.331, p < 0.01); however, this effect was substantially stronger in cold spots (b = -0.548, p < 0.001). Notably, higher social welfare facilities significantly reduced suicide mortality specifically in cold spots (b = -0.117, p < 0.05).
Conclusion: Suicide rates in South Korea exhibit clear spatiotemporal disparities. The protective effect of the elderly population is stronger in cold spots, suggesting that well-established social welfare infrastructure in urban cold spot regions may amplify the protective effect of aging populations. These findings necessitate a shift from uniform national strategies to region-specific policies that leverage local welfare assets.
Keywords: Geographic information systems (GIS); Regional disparities; South Korea; Spatial analysis; Suicide; Suicide prevention.
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