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Geographical Distribution Patterns of Iodine in Drinking-Water and Its Associations with Geological Factors in Shandong Province, China

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  • Jie Gao

    (Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China
    Key Laboratory of Public Health Safety, Ministry of Education, Shanghai 200032, China
    Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai 200032, China
    Shandong Institute of Prevention and Control for Endemic Disease, Jinan 250014, China)

  • Zhijie Zhang

    (Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China
    Key Laboratory of Public Health Safety, Ministry of Education, Shanghai 200032, China
    Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai 200032, China)

  • Yi Hu

    (Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China
    Key Laboratory of Public Health Safety, Ministry of Education, Shanghai 200032, China
    Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai 200032, China)

  • Jianchao Bian

    (Shandong Institute of Prevention and Control for Endemic Disease, Jinan 250014, China)

  • Wen Jiang

    (Shandong Institute of Prevention and Control for Endemic Disease, Jinan 250014, China)

  • Xiaoming Wang

    (Shandong Institute of Prevention and Control for Endemic Disease, Jinan 250014, China)

  • Liqian Sun

    (Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China
    Key Laboratory of Public Health Safety, Ministry of Education, Shanghai 200032, China
    Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai 200032, China)

  • Qingwu Jiang

    (Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China
    Key Laboratory of Public Health Safety, Ministry of Education, Shanghai 200032, China
    Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai 200032, China)

Abstract

County-based spatial distribution characteristics and the related geological factors for iodine in drinking-water were studied in Shandong Province (China). Spatial autocorrelation analysis and spatial scan statistic were applied to analyze the spatial characteristics. Generalized linear models (GLMs) and geographically weighted regression (GWR) studies were conducted to explore the relationship between water iodine level and its related geological factors. The spatial distribution of iodine in drinking-water was significantly heterogeneous in Shandong Province (Moran’s I = 0.52, Z = 7.4, p < 0.001). Two clusters for high iodine in drinking-water were identified in the south-western and north-western parts of Shandong Province by the purely spatial scan statistic approach. Both GLMs and GWR indicated a significantly global association between iodine in drinking-water and geological factors. Furthermore, GWR showed obviously spatial variability across the study region. Soil type and distance to Yellow River were statistically significant at most areas of Shandong Province, confirming the hypothesis that the Yellow River causes iodine deposits in Shandong Province. Our results suggested that the more effective regional monitoring plan and water improvement strategies should be strengthened targeting at the cluster areas based on the characteristics of geological factors and the spatial variability of local relationships between iodine in drinking-water and geological factors.

Suggested Citation

  • Jie Gao & Zhijie Zhang & Yi Hu & Jianchao Bian & Wen Jiang & Xiaoming Wang & Liqian Sun & Qingwu Jiang, 2014. "Geographical Distribution Patterns of Iodine in Drinking-Water and Its Associations with Geological Factors in Shandong Province, China," IJERPH, MDPI, vol. 11(5), pages 1-14, May.
  • Handle: RePEc:gam:jijerp:v:11:y:2014:i:5:p:5431-5444:d:36213
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    References listed on IDEAS

    as
    1. Aletta Dijkstra & Fanny Janssen & Marinus De Bakker & Jens Bos & René Lub & Leo J G Van Wissen & Eelko Hak, 2013. "Using Spatial Analysis to Predict Health Care Use at the Local Level: A Case Study of Type 2 Diabetes Medication Use and Its Association with Demographic Change and Socioeconomic Status," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-9, August.
    2. Zhao, J. & Wang, P. & Shang, L. & Sullivan, K.M. & Van der Haar, F. & Maberly, G., 2000. "Endemic goiter associated with high iodine intake," American Journal of Public Health, American Public Health Association, vol. 90(10), pages 1633-1635.
    3. Chia-Hsien Lin & Tzai-Hung Wen, 2011. "Using Geographically Weighted Regression (GWR) to Explore Spatial Varying Relationships of Immature Mosquitoes and Human Densities with the Incidence of Dengue," IJERPH, MDPI, vol. 8(7), pages 1-18, July.
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