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Predicted Mercury Soil Concentrations from a Kriging Approach for Improved Human Health Risk Assessment

Author

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  • David Imo

    (Division of Occupational and Environmental Medicine, Epidemiology, Biostatistics and Prevention Institute, University of Zurich & University Hospital Zurich, Hirschengraben 84, 8001 Zurich, Switzerland)

  • Holger Dressel

    (Division of Occupational and Environmental Medicine, Epidemiology, Biostatistics and Prevention Institute, University of Zurich & University Hospital Zurich, Hirschengraben 84, 8001 Zurich, Switzerland)

  • Katarzyna Byber

    (Division of Occupational and Environmental Medicine, Epidemiology, Biostatistics and Prevention Institute, University of Zurich & University Hospital Zurich, Hirschengraben 84, 8001 Zurich, Switzerland)

  • Christine Hitzke

    (Division of Occupational and Environmental Medicine, Epidemiology, Biostatistics and Prevention Institute, University of Zurich & University Hospital Zurich, Hirschengraben 84, 8001 Zurich, Switzerland)

  • Matthias Bopp

    (Division of Chronic Disease Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001 Zurich, Switzerland)

  • Marion Maggi

    (Division of Occupational and Environmental Medicine, Epidemiology, Biostatistics and Prevention Institute, University of Zurich & University Hospital Zurich, Hirschengraben 84, 8001 Zurich, Switzerland)

  • Stephan Bose-O’Reilly

    (Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital Munich, LMU Munich, WHO Collaborating Centre for Occupational Health, Ziemssenstraße 1, D-80336 Munich, Germany
    Department of Public Health, Health Services Research and Health Technology Assessment, UMIT (University for Health Sciences, Medical Informatics and Technology), Eduard-Wallnöfer-Zentrum 1, 6060 Hall i.T., Austria)

  • Leonhard Held

    (Department of Biostatistics, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001 Zurich, Switzerland)

  • Stefanie Muff

    (Department of Biostatistics, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001 Zurich, Switzerland)

Abstract

Health-risks from contaminated soils are assessed all over the world. An aspect that many risk assessments share is the heterogeneity in the distribution of contaminants. In a preceding study, we assessed potential health-risks for mothers and children living on mercury-contaminated soils in Switzerland using human biomonitoring-values (HBM) and soil samples. We assessed 64 mothers and 107 children who had resided in a defined area for at least 3 months. HBM-concentrations for mercury in urine and hair were measured, a detailed questionnaire was administered for each individual, and more than 4000 individual mercury soil values were obtained in 2015. In this study, we aimed at investigating possible associations of mercury soil- and HBM-values by re-analyzing our data, using predictions of the mercury concentrations at the exact location of the participant’s homes with a kriging approach. Although kriging proved to be a useful method to predict mercury soil concentrations, we did not detect an association between mercury soil- and HBM-values, in agreement with earlier findings. Benefits of geostatistical methods seem to be limited in the context of our study. Conclusions made in our preceding study about potential health risks for the residential population are robust and not altered by the current study.

Suggested Citation

  • David Imo & Holger Dressel & Katarzyna Byber & Christine Hitzke & Matthias Bopp & Marion Maggi & Stephan Bose-O’Reilly & Leonhard Held & Stefanie Muff, 2018. "Predicted Mercury Soil Concentrations from a Kriging Approach for Improved Human Health Risk Assessment," IJERPH, MDPI, vol. 15(7), pages 1-14, June.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:7:p:1326-:d:154177
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    References listed on IDEAS

    as
    1. Muff, Stefanie & Ott, Manuela & Braun, Julia & Held, Leonhard, 2017. "Bayesian two-component measurement error modelling for survival analysis using INLA—A case study on cardiovascular disease mortality in Switzerland," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 177-193.
    2. Stefanie Muff & Andrea Riebler & Leonhard Held & Håvard Rue & Philippe Saner, 2015. "Bayesian analysis of measurement error models using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 64(2), pages 231-252, February.
    3. Hung-Yu Lai & Zeng-Yei Hseu & Ting-Chien Chen & Bo-Ching Chen & Horng-Yuh Guo & Zueng-Sang Chen, 2010. "Health Risk-Based Assessment and Management of Heavy Metals-Contaminated Soil Sites in Taiwan," IJERPH, MDPI, vol. 7(10), pages 1-20, October.
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    Cited by:

    1. Tine Bizjak & Marco Capodiferro & Deepika Deepika & Öykü Dinçkol & Vazha Dzhedzheia & Lorena Lopez-Suarez & Ioannis Petridis & Agneta A. Runkel & Dayna R. Schultz & Branko Kontić, 2022. "Human Biomonitoring Data in Health Risk Assessments Published in Peer-Reviewed Journals between 2016 and 2021: Confronting Reality after a Preliminary Review," IJERPH, MDPI, vol. 19(6), pages 1-18, March.

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