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Spatiotemporal Distribution of U5MR and Their Relationship with Geographic and Socioeconomic Factors in China

Author

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  • Zeng Li

    (College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing), Ding No.11 Xueyuan Road, Haidian District, Beijing 100083, China
    These authors contributed equally to this work.)

  • Jingying Fu

    (Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China
    College of Resource and Environment, University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China
    These authors contributed equally to this work.)

  • Dong Jiang

    (Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China
    College of Resource and Environment, University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China)

  • Gang Lin

    (Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China)

  • Donglin Dong

    (College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing), Ding No.11 Xueyuan Road, Haidian District, Beijing 100083, China)

  • Xiaoxi Yan

    (Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China
    College of Resource and Environment, University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China)

Abstract

Epidemiological studies conducted around the world have reported that the under-five mortality rate (U5MR) is closely associated with income and educational attainment. However, geographic elements should also remain a major concern in further improving child health issues, since they often play an important role in the survival environment. This study was undertaken to investigate the relationship between the U5MR, geographic, and socioeconomic factors, and to explore the associated spatial variance of the relationship in China using the geographically weighted regression (GWR) model. The results indicate that the space pattern of a high U5MR had been narrowed notably during the period from 2001 to 2010. Nighttime lights (NL) and the digital elevation model (DEM) both have obvious influences on the U5MR, with the NL having a negative impact and DEM having a positive impact. Additionally, the relationship between the NL and DEM varied over space in China. Moreover, the relevance between U5MR and DEM was narrowed in 2010 compared to 2001, which indicates that the development of economic and medical standards can overcome geographical limits.

Suggested Citation

  • Zeng Li & Jingying Fu & Dong Jiang & Gang Lin & Donglin Dong & Xiaoxi Yan, 2017. "Spatiotemporal Distribution of U5MR and Their Relationship with Geographic and Socioeconomic Factors in China," IJERPH, MDPI, vol. 14(11), pages 1-12, November.
    • Handle: RePEc:gam:jijerp:v:14:y:2017:i:11:p:1428-:d:119772
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    References listed on IDEAS

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    1. Fangyu Ding & Quansheng Ge & Dong Jiang & Jingying Fu & Mengmeng Hao, 2017. "Understanding the dynamics of terrorism events with multiple-discipline datasets and machine learning approach," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-11, June.
    2. Corsi, Daniel J & S V Subramanian, 2017. "Association between economic growth, coverage of maternal and child health interventions, and under-five mortality: a repeated cross-sectional analysis of 36 sub-Saharan African countries," Working Paper 144146, Harvard University OpenScholar.
    3. Wang, Limin, 2003. "Determinants of child mortality in LDCs: Empirical findings from demographic and health surveys," Health Policy, Elsevier, vol. 65(3), pages 277-299, September.
    4. Yee Leung & Chang-Lin Mei & Wen-Xiu Zhang, 2000. "Statistical Tests for Spatial Nonstationarity Based on the Geographically Weighted Regression Model," Environment and Planning A, , vol. 32(1), pages 9-32, January.
    5. Gang Lin & Jingying Fu & Dong Jiang & Wensheng Hu & Donglin Dong & Yaohuan Huang & Mingdong Zhao, 2013. "Spatio-Temporal Variation of PM 2.5 Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China," IJERPH, MDPI, vol. 11(1), pages 1-14, December.
    6. Yonglong Lu & Nebojsa Nakicenovic & Martin Visbeck & Anne-Sophie Stevance, 2015. "Policy: Five priorities for the UN Sustainable Development Goals," Nature, Nature, vol. 520(7548), pages 432-433, April.
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    1. Ling Yao & Changchun Huang & Wenlong Jing & Xiafang Yue & Yuyue Xu, 2018. "Quantitative Assessment of Relationship between Population Exposure to PM 2.5 and Socio-Economic Factors at Multiple Spatial Scales over Mainland China," IJERPH, MDPI, vol. 15(9), pages 1-13, September.

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    Keywords

    U5MR; nighttime lights; digital elevation model; GWR;
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