Evidence map›Paper›PMID 42618932›Full record

ArticleBMC health services research2026

Temporal-spatial analysis and driving factors of coupling coordination between population and health services systems in China, 2010-2022.

Linbin Luo, Ruibo He, Yiqing Xing, Weicun Ren, Liang Zhang

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Article in BMC health services research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Linbin LuoSchool of Political Science and Public Administration, Wuhan University, Wuhan, Hubei, China.
Ruibo HeSchool of Finance and Public Administration, Hubei University of Economics, Wuhan, Hubei, China.
Yiqing XingCollege of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
Weicun RenSchool of Political Science and Public Administration, Wuhan University, Wuhan, Hubei, China.
Liang ZhangSchool of Political Science and Public Administration, Wuhan University, Wuhan, Hubei, China. Zhangchunliang@whu.edu.cn.

Funding

e National Natural Science Foundation of China 72474162the National Natural Science Foundation of China 72104073
6 · The paper itself

Abstract

backgroundDemographic transitions are reshaping health needs and challenging the sustainability of health governance, with the coordination of population and health services systems closely connected to these processes. This study investigates China's population and health services systems from 2010 to 2022, aiming to explore the spatiotemporal evolution and key driving factors of their coupling coordination.

methodsData were obtained from the China Statistical Yearbook and China Health Statistics Yearbook, covering 31 provinces from 2010 to 2022. An evaluation model was developed to assess the coupling coordination degree (CCD) between the population and health services systems. Spatial autocorrelation analysis was employed to examine spatial dependence, and a Spatial Durbin Model (SDM) was applied to identify key driving factors.

resultsFrom 2010 to 2022, the development indices of China's population and health services systems rose steadily, with the CCD increasing from 0.407 to 0.835, indicating a progression from initial imbalance toward advanced coordination. Regionally, the pattern of "east-strong, central-rising, west-weak" persisted, though disparities have diminished as central and western regions steadily caught up. Spatial analysis confirmed significant dependence and stable in provincial CCD, with patterns dominated by "high-high" clusters in the Yangtze River Delta and Beijing-Tianjin-Hebei region, which gradually extended into central provinces, and by persistent "low-low" clusters in the west and northeast, alongside several outliers. Spatial econometric results identified government health expenditure, health insurance coverage, digital and transport infrastructure as significant positive drivers, with government health expenditure and digital development showing stronger cross-regional spillovers.

conclusionCoordination between the population and health services systems improved substantially, although regional disparities persisted. Further progress requires closer alignment between demographic change and health service capacity. Differentiated regional strategies are therefore needed: economically and resource-advantaged regions could harness agglomeration and spillover effects through cross-regional collaboration; central provinces should consolidate their catch-up momentum and strengthen their regional service capacity; and western and other low-coordination regions, facing population mobility and ageing pressures, should prioritise targeted fiscal transfers, workforce retention incentives and improved service accessibility to promote more equitable and sustainable development.

Indexed as

Delivery of Health CarePopulation DynamicsChinaHumansSpatio-Temporal AnalysisCoupling coordination degreeHealth services systemPopulation systemSpatiotemporal evolution

Identifiers

PMID42618932
PMCPMC13488232

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.