Spatial heterogeneity of the associations of economic and health care factors with infant mortality in China using geographically weighted regression and spatial clustering
文献类型：期刊论文
| 作者 | Wang, Shaobin1; Wu, Jun2 |
| 刊名 | SOCIAL SCIENCE & MEDICINE
 |
| 出版日期 | 2020-10-01 |
| 卷号 | 263页码:9 |
| 关键词 | Infant mortality rate Economic factors Health care Geographically weighted regression Spatial heterogeneity |
| ISSN号 | 0277-9536 |
| DOI | 10.1016/j.socscimed.2020.113287 |
| 通讯作者 | Wang, Shaobin(wangshaobin@igsnrr.ac.cn) ; Wu, Jun(junwu@uci.edu) |
| 英文摘要 | Economic factors and health care resources are important influential factors of infant mortality. We aimed to examine prefecture-level spatial heterogeneity and clustering of the associations of economic and health care factors with infant mortality rates (IMR) in China. IMR data in 348 prefectures were calculated and adjusted, and economic and health care data were collected in each prefecture in China, 2010. Stepwise regression was used to select important variables, and geographically weighted regression (GWR) was applied to examine the spatial variations of the relationships between economic and health care factors and IMR. The k-means clustering was developed to elucidate the spatial clustering patterns of the GWR coefficients. The results showed that three important variables were selected in the multivariable regression model, including per capita income of rural residents, Engel's coefficient of rural residents, and proportion of government health expenditure. The GWR with these three variables revealed spatial heterogeneity of the associations between IMR and economic and health care factors; western China generally had higher GWR R-squares and stronger associations between IMR and all the three variables than the middle-eastern part of China. Based on the GWR coefficients, three distinct spatial clusters were identified. This study contributes new findings on the spatial heterogeneity of the associations between economic and health care factors and infant mortality rate in China, which calls for region-specific policies to reduce infant mortality in China. |
| WOS关键词 | CHILD-MORTALITY ; AIR-POLLUTION ; INCOME INEQUALITY ; UNDER-5 MORTALITY ; SOCIOECONOMIC INEQUALITIES ; INDUSTRIALIZED COUNTRIES ; DEVELOPED-COUNTRIES ; MIDDLE-INCOME ; BIOMASS FUEL ; DETERMINANTS |
| 资助项目 | Chinese Academy of Sciences (CAS) Scholarship ; Open Foundation of Key Laboratory of Coal Resources Exploration and Comprehensive Utilization, Ministry of Land and Resources, P. R. China[KF2018-7] ; Key Research and Development Project of Shaanxi Province[2017ZDXM-GY-075] ; National Natural Sciences Foundation of China[41502329] |
| WOS研究方向 | Public, Environmental & Occupational Health ; Biomedical Social Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:000579852400006 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| 资助机构 | Chinese Academy of Sciences (CAS) Scholarship ; Open Foundation of Key Laboratory of Coal Resources Exploration and Comprehensive Utilization, Ministry of Land and Resources, P. R. China ; Key Research and Development Project of Shaanxi Province ; National Natural Sciences Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/156801]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Wang, Shaobin; Wu, Jun |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China 2.Univ Calif Irvine, Susan & Henry Samueli Coll Hlth Sci, Program Publ Hlth, Irvine, CA 92697 USA |
| 推荐引用方式 GB/T 7714 | Wang, Shaobin,Wu, Jun. Spatial heterogeneity of the associations of economic and health care factors with infant mortality in China using geographically weighted regression and spatial clustering[J]. SOCIAL SCIENCE & MEDICINE,2020,263:9. |
| APA | Wang, Shaobin,&Wu, Jun.(2020).Spatial heterogeneity of the associations of economic and health care factors with infant mortality in China using geographically weighted regression and spatial clustering.SOCIAL SCIENCE & MEDICINE,263,9. |
| MLA | Wang, Shaobin,et al."Spatial heterogeneity of the associations of economic and health care factors with infant mortality in China using geographically weighted regression and spatial clustering".SOCIAL SCIENCE & MEDICINE 263(2020):9. |
入库方式： OAI收割
来源：地理科学与资源研究所
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