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With the accelerated aging of China's population, equitable access to geriatric emergency medical services (EMS) has become increasingly critical. However, multiscale research on the dynamic accessibility and equity of geriatric EMS remains limited. This study examines the spatial equity of geriatric EMS accessibility in Zhengzhou, a rapidly developing city in central China, from a 15-minute city perspective, using a dynamic accessibility model incorporating real-time data on population distribution, EMS stations, and road networks. Key findings include: (1) At the city level, geriatric EMS accessibility and equity are significantly better in central urban areas than in peripheral zones, and are lower during weekday morning peak hours compared to non-working days, while evening peak and nighttime conditions remain relatively stable. (2) District-level disparities reveal superior accessibility and equity in higher-income districts, with lower-income peripheral districts experiencing persistent accessibility challenges; (3) At the neighborhood level, commercial-housing properties shows the highest accessibility and equity, resettlement housing the lowest, and medium-priced housing outperforms high-priced neighborhoods, particularly during peak hours. Our study highlights the value of a dynamic, multi-scalar approach to examining the changing supply-demand relationship of geriatric EMS accessibility and equity. By identifying spatial and temporal disparities at multiple levels, we provide actionable insights for policymakers aiming to optimize healthcare service delivery in rapidly urbanizing cities. We also emphasize the need for flexible and adaptive planning strategies to address spatial inequities and temporal fluctuations in healthcare. • Dynamic, multi-scale model reveals disparities in geriatric EMS accessibility and equity. • EMS accessibility is lower in peripheral areas and during peak hours on workdays. • Higher-income districts show better EMS accessibility, but disparities remain. • Findings provide insights for optimizing EMS allocation under the 15-minute city framework.
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Li et al. (2025) studied this question.
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