2003-2013年中国居民健康水平的区域差异（英文）

编号 zgly0001583956

文献类型 期刊论文

文献题名 2003-2013年中国居民健康水平的区域差异（英文）

作者 赵雪雁  王伟军  万文玉 

作者单位 CollegeofGeographyandEnvironmentScience  NorthwestNormalUniversity 

母体文献 Journal of Geographical Sciences 

年卷期 2018年06期

年份 2018 

分类号 R195 

关键词 residents  healthstatus  regionalinequity  influencingfactors  China 

文摘内容 Health inequality is an increasing concern worldwide.Using the coefficient of variation,Theil index,exploratory spatial data analysis,and spatial panel econometric model,we examined the regional inequality,spatio-temporal dynamic patterns,and key factors in the health status of Chinese residents from 2003 to 2013.We found that China’s residential health index(RHI) decreased from 0.404 to 0.295 in 2003–2013 at an annual rate of 2.698%.Spatially,resident health status,based on the RHI,has improved faster in the western region than in the eastern and central regions.Inequality in resident health status continued to increase between 2003 and 2013;inequality between regions decreased,but health status inequality expanded within regions.Furthermore,disparities in health status grew faster in western regions than in the eastern and central regions.The spatial distribution of resident health status formed a T-shaped pattern across China,decreasing from east to center then to the west with a symmetric decrease north and south.Using the change in Moran’s I from 2003 to 2008 and 2013,we found that the distribution of resident health status across China has narrowed.All the hot spots and cold spots have decreased,but they are also stable.Resident health status formed a stable cold spot in the western regions,while the east coastal area formed a stable hot spot.Selected explanatory variables have significant direct impacts on resident health status in China:increasing per capita GDP,per capita spending on health,and urbanization,and improving environmental quality all lead to better resident health status.Finally,we highlight the need for additional research on regional inequality of resident health status across multiple time,spatial,and factor domains.