Author(s)

Ke Wen, Xueqian Song, Huayue Long

Corresponding Author

Xueqian Song

Abstract

Health is essential to national welfare and people's livelihood, and healthy environment is conducive to promote a healthy population. This paper constructed a health environment index system and applied the entropy-weighted analytic hierarchy process method, spatial autocorrelation Moran's index (Moran's I) and econometric model based on the environmental and socio-economic data in 31 provinces in 2017 to evaluate the spatial pattern of the levels of health environment and its influences in China. The results show that, 1). There are significant spatial differences in the level of health environment in China, the overall level is mainly higher and unevenly distributed, with a significant spatial aggregation effect. North China and surrounding provinces are low-value aggregation areas, and high-value aggregation areas are mainly distributed in Guangdong. Guangxi, Hainan, 2). The multiple regression model optimized by stepwise regression method shows that in 2017, urban per capita disposable income plays a significantly positive role in the levels of health environment value, while the ratio of the secondary and tertiary industries to GDP, and population density have significant negative impacts. Conclusion, in 2017, there are obvious spatial inequity existing of the levels of health environment in China, and it is affected by many factors. In order to further improve the overall level of health environment, targeted policies should be made according to the influencing factors.

Keywords

Health environment; Entropy-weighted AHP method; Spatial autocorrelation model; Influencing factors