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<p>Primary healthcare centers (PHCs) play a crucial role in China’s hierarchical medical system by providing essential community-level services. This study takes Tianjin, a major northern metropolis, as a case study to evaluate the spatial accessibility of PHCs and identify intra-city disparities. Using POI data to locate PHCs, population data to model healthcare demand, and road network data to simulate travel times, the Gaussian Two-Step Floating Catchment Area method was applied to measure primary healthcare accessibility within a 15&#xa0;min travel threshold. The results revealed that PHC accessibility declined from the city center to the periphery, influenced by population density, economic development, and road network. Central districts like Heping and Nankai exhibited high accessibility, while Wuqing and Jizhou also performed well due to their strategic locations. In contrast, suburban and outer suburban districts such as Dongli, Jinghai, and Ninghe faced significant shortages in primary healthcare services. Spatial autocorrelation analysis using Global and Local Moran’s I identified high-accessibility clusters in Nankai Beichen, Wuqing, and Jizhou, and low-accessibility clusters mainly in the outer suburbs. Furthermore, K-means clustering analysis categorized Tianjin into four groups, suggesting targeted policies to enhance healthcare equity by redistributing resources, improving transport infrastructure, and expanding telemedicine, particularly in underserved areas.</p>

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Spatial accessibility evaluation and clustering analysis of primary healthcare within 15 min circles in a northern Chinese megacity

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月13日

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  • Jiarui Han,
  • Liping Fu,
  • Xiaowang Zhang,
  • Tong Pei,
  • Huayu Long

摘要

Primary healthcare centers (PHCs) play a crucial role in China’s hierarchical medical system by providing essential community-level services. This study takes Tianjin, a major northern metropolis, as a case study to evaluate the spatial accessibility of PHCs and identify intra-city disparities. Using POI data to locate PHCs, population data to model healthcare demand, and road network data to simulate travel times, the Gaussian Two-Step Floating Catchment Area method was applied to measure primary healthcare accessibility within a 15 min travel threshold. The results revealed that PHC accessibility declined from the city center to the periphery, influenced by population density, economic development, and road network. Central districts like Heping and Nankai exhibited high accessibility, while Wuqing and Jizhou also performed well due to their strategic locations. In contrast, suburban and outer suburban districts such as Dongli, Jinghai, and Ninghe faced significant shortages in primary healthcare services. Spatial autocorrelation analysis using Global and Local Moran’s I identified high-accessibility clusters in Nankai Beichen, Wuqing, and Jizhou, and low-accessibility clusters mainly in the outer suburbs. Furthermore, K-means clustering analysis categorized Tianjin into four groups, suggesting targeted policies to enhance healthcare equity by redistributing resources, improving transport infrastructure, and expanding telemedicine, particularly in underserved areas.