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Article

The Spatial Correlations of Health Resource Agglomeration Capacities and Their Influencing Factors: Evidence from China

by 1, 2,* and 1
1
School of Economics, Hainan University, Haikou 570228, China
2
School of Economics & Management, Nanchang University, Nanchang 330031, China
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(22), 8705; https://doi.org/10.3390/ijerph17228705
Received: 24 October 2020 / Revised: 19 November 2020 / Accepted: 20 November 2020 / Published: 23 November 2020
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 (strongest in the eastern region, second strongest in the central region, and weakest in the western region). (ii) The spatial network of such capacities became more densely connected, and the network density and level (efficiency) showed an upward (downward) trend. (iii) In terms of centrality, the high-ranking provinces (or municipalities) were Beijing, Shanghai, Jiangsu, Zhejiang, Guangdong, Shandong, Hunan, Hubei, Fujian, Anhui, Jiangxi, and Tianjin, while the low-ranking were Tibet, Qinghai, Gansu, Ningxia, Inner Mongolia, Heilongjiang, Yunnan, Guizhou, Xinjiang, Hainan, Shaanxi, and Shanxi. (iv) Block 1 (eight provinces or municipalities), including Beijing, Tianjin, and Hebei, had a “net spillover” effect in the spatial network of health resource agglomeration capacities; Block 2, (seven provinces or municipalities), including Shanghai, Jiangsu, and Zhejiang, had a “bidirectional spillover” effect in the spatial network; Block 3 (seven provinces or municipalities), including Anhui, Hubei, and Hunan, had a “mediator” effect in the network; and Block 4, (nine provinces or municipalities), including Sichuan, Guizhou, and Tibet, had a “net beneficial” effect in the network. (v) The economic development, urbanization wage, and financial health expenditure levels, and population size had significant positive correlations with the spatial network of health resource agglomeration capacities. Policy recommendations to enhance the radiating role of health resources in core provinces (or municipalities), rationally allocate health resources, and transform ideas to support public health resource services were provided. View Full-Text
Keywords: health resource agglomeration capacity; spatial correlation; influencing factors; China health resource agglomeration capacity; spatial correlation; influencing factors; China
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MDPI and ACS Style

Guo, Q.; Luo, K.; Hu, R. The Spatial Correlations of Health Resource Agglomeration Capacities and Their Influencing Factors: Evidence from China. Int. J. Environ. Res. Public Health 2020, 17, 8705. https://doi.org/10.3390/ijerph17228705

AMA Style

Guo Q, Luo K, Hu R. The Spatial Correlations of Health Resource Agglomeration Capacities and Their Influencing Factors: Evidence from China. International Journal of Environmental Research and Public Health. 2020; 17(22):8705. https://doi.org/10.3390/ijerph17228705

Chicago/Turabian Style

Guo, Qingbin, Kang Luo, and Ruodi Hu. 2020. "The Spatial Correlations of Health Resource Agglomeration Capacities and Their Influencing Factors: Evidence from China" International Journal of Environmental Research and Public Health 17, no. 22: 8705. https://doi.org/10.3390/ijerph17228705

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