Coupling coordination spatiotemporal dynamic evolution of population, medical care and public health multisystem in China in 2010-2021 and driving factor analysis
Authors: Luo Linbin , He Ruibo , Xing Yiqing , Ren Weicun , Zhang Liang 
Published: December 2024

Background: The coupling coordination of population, medical care and public health system is crucial for advancing health care development and improving health governance efficiency. The dramatic shifts in global population structures are reshaping health demands, placing unprecedented challenges on health care systems. This study investigates the population, medical care system and public health system in China from 2011 to 2021, revealing their spatiotemporal dynamic evolution. The findings are expected to provide valuable insights for promoting the coordinated development of population and health care system and improve health governance.
Methods: The data for this study were sourced from the China Statistical Yearbook and the China Health Statistics Yearbook. On the basis of relevant data, an evaluation model was developed to assess the coupling coordination degree of the population health multisystem. A quantile regression model was adopted to explore the influencing factors.
Results: From 2010 to 2021, China experienced significant improvements across the three major systems. The evaluation index for the medical care system increased from 0.109 to 0.782, whilst the population and public health indices rose from 0.195 and 0.008 to 0.702 and 0.842, respectively. This development can be categorised into two phases: ‘rapid growth’ (2010–2018) and ‘fluctuating growth’ (2019–2021). The coupling coordination degree amongst the three systems steadily increased from 0.155 in 2010 to 0.668 in 2021, with an average annual growth rate of 14.2%. This phenomenon marked a shift from a state of severe dysfunction to one of primary coordination. However, significant regional disparities persisted, with varying rates of development and coordination. The eastern regions consistently led, followed by the western and central regions. This study identified multiple factors influencing the coupling coordination of the population–health care multisystem, including population structure, economic income, medical service efficiency, public health resources and health management service. Notably, health management emerged as a crucial factor at Q1 (b=2.283, P=0.002), whilst population structure was the most significant factor at Q3 (b=3.439, P<0.001).
Conclusion: Structural adjustments for enhancing coupling coordination can effectively boost overall health sector efficiency and address reform challenges. Development strategies involve two pathways: economy- and policy-driven pathways. Economically disadvantaged areas should focus on policy-driven efforts to enhance coupling coordination, whereas economically developed areas should leverage economic momentum to accelerate the development of integrated health services to meet people’s needs throughout their life cycle. Additionally, considering population and regional characteristics is crucial, emphasising the need for health care systems tailored to the unique structural features and developmental strengths of each region.