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March 26, 2026BMC Health Services Research0 citationsOpen Access

Regional disparities, dynamic evolution, and convergence of China’s resident health service development levels

XSXinmiao ShaoZWZhong Wu

Key Points

  • This study aims to evaluate and analyze the regional disparities in China’s health service development levels and propose recommendations for improvement.
  • Constructed a composite health service development level index using CRITIC weighting method.
  • Applied Dagum’s Gini coefficient to measure regional disparities in health service development.
  • Used kernel density estimation to analyze distribution patterns of health service levels.
  • Employed traditional and spatial Markov chain models to examine dynamic transitions in health service levels.
  • Utilized spatial econometric models to explore spatiotemporal evolution and convergence of health service levels.
  • China's health service development level steadily increased from 2012 to 2021, with a peak in 2020.
  • Eastern provinces consistently exhibited high health service development, while western provinces showed significant improvement.
  • Spatial analysis revealed clustering of high health service development in the east with notable disparities in the west.
  • Markov model comparisons indicated strong transition inertia and lock-in effects in low health service development regions.
  • Despite national advancements, regional imbalances and inequalities in resource distribution remain, especially in western provinces.

Abstract

China has achieved notable progress in economic and social development over the past decade. However, regional disparities—especially in Health Service Development Level (HSDL)—remain significant, challenging national health goals and public health sustainability. This study evaluates China’s HSDL, explores causes of regional inequality, and proposes policy recommendations to optimize resource allocation and address health disparities. We used panel data from 31 provinces (2012–2021) to build a composite HSDL index via the CRITIC weighting method. Dagum’s Gini coefficient measured regional disparities, and kernel density estimation analyzed distribution patterns. Moran’s I index assessed spatial autocorrelation. Traditional and spatial Markov chain models examined dynamic transitions, while spatial econometric models (SDM, SEM, SAR) explored spatiotemporal evolution and convergence. From 2012 to 2021, China’s HSDL rose steadily, peaking in 2020, mainly due to coordinated health policies and COVID-19 responses. Eastern provinces maintained high HSDL, while western regions improved significantly through health poverty alleviation efforts, narrowing interregional gaps. In 2021, a slight decline was observed, likely due to reduced public health investment and shifting policy priorities post-pandemic. Spatial analysis showed clustering of high HSDL in the east, with notable internal disparities in the west. Markov model comparisons revealed strong transition inertia and lock-in effects, especially in low-HSDL regions. Spatial econometric models confirmed a trend of spatial convergence, with shrinking gaps among eastern, central, and western areas. Despite national progress in HSDL, regional imbalances and unequal resource distribution persist, particularly in western provinces. Future strategies should focus on balanced development by improving basic healthcare services, promoting equitable resource allocation, and enhancing targeted policy support for underserved regions.

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Cite This Study

Shao et al. (2026) studied this question.

synapsesocial.com/papers/69c4cddcfdc3bde44891a9c6https://doi.org/10.1186/s12913-026-14426-0
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