The Correlation Between Aging Population and Public Transit-Based Medical Accessibility in Rural Areas - Focusing on Rural Townships in Seobuk-gu, Cheonan -

Medical accessibility has gained critical importance for elderly health and rural community sustainability in Korea’s rapidly aging rural areas. This study analyzes differences between car and public transportation access to major medical facilities across four townships in Seobuk-gu, Cheonan, and examines relationships with elderly population changes. QGIS network analysis and mobile-based location information services were employed to calculate travel times from each township center to ten major hospitals by automobile and public transit, with 2019-2024 aging rate changes examined using Pearson and Spearman correlations. Substantial differences emerged between transportation modes: car access enabled reaching 2 hospitals within 30 minutes and 7-10 hospitals within 60 minutes across all townships, whereas public transit permitted access to only 1-2 facilities within the optimal 20-40-minute range and 3-5 within 60 minutes. A strong positive relationship was identified between elderly population growth rates and 20-40-minute public transit hospital access (Pearson r=0.977, p=0.023), while 60-minute accessibility showed strong positive correlation approaching significance (Spearman ρ=0.949, p=0.051). However, no significant correlation was detected between elderly population changes and shortest travel times. The analysis revealed that the number of accessible hospitals demonstrated stronger correlation with aging rates than travel time efficiency, indicating that medical service options are more critical than speed for elderly populations. Areas experiencing population decline alongside aging exhibited different patterns, suggesting varying residential requirements across age groups. These results indicate that public transit route diversification to multiple medical facilities may prove more effective than single-route speed improvements for elderly-oriented rural policies, providing empirical evidence for differentiated living condition improvements based on demographic composition and population change patterns.