2020
DOI: 10.3390/ijerph17228705
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The Spatial Correlations of Health Resource Agglomeration Capacities and Their Influencing Factors: Evidence from China

Abstract: We measured the health resource agglomeration capacities of 31 Chinese provinces (or municipalities) in 2004–2018 based on the entropy weight method. Using a modified spatial gravity model, we constructed and analyzed the spatial correlation network of these health resource agglomeration capacities and their influencing factors through social network analysis. We found that: (i) China’s health resource agglomeration capacity had a gradual strengthening trend, with capacity weakening from east to west (stronges… Show more

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Cited by 14 publications
(14 citation statements)
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“…Many factors such as socioeconomic status and health care access contribute to lymphoma burden [ 19 22 ]. The urban-rural discordance of mortality rates was partly due to poor availability of medical services and insufficient protection by healthcare insurance [ 3 ].…”
Section: Discussionmentioning
confidence: 99%
“…Many factors such as socioeconomic status and health care access contribute to lymphoma burden [ 19 22 ]. The urban-rural discordance of mortality rates was partly due to poor availability of medical services and insufficient protection by healthcare insurance [ 3 ].…”
Section: Discussionmentioning
confidence: 99%
“…In addition, provinces in the eastern region are, in general, economically developed; thus, health professionals might have more incentives to work in these areas driven by a higher salary. The marketization possibly further facilitates the outflow of health labor from underdeveloped to developed regions and then accelerate spatial agglomeration ( 57 ). In this case, it is necessary for the government to carry out more effective regional-specific policies targeted at backward areas with respect to health workforce configuration based on in-depth understanding of its influential factors.…”
Section: Discussionmentioning
confidence: 99%
“…This paper finds that factors such as children and elderly population, health care government investment, service industry added value, high quality population, medical insurance fund expenditure, and government revenue have a great direct influence on the geographical distribution of health resources, which further validates the findings of some scholars. For example, Li [ 108 ], Zheng [ 109 ], and Guo [ 110 ] found that economic development, urbanization wage, population ageing, financial health expenditure levels, and population size are key factors affecting the geographical distribution of medical resources in China. Song [ 111 ], Ding [ 112 ], and Guo [ 113 ] found that social, economic, and environmental factors have great influence on the geographical clustering and spatio-temporal evolution trends of medical resources by leveraging the Bayesian local spatiotemporal regression model and spatial econometric model.…”
Section: Discussionmentioning
confidence: 99%