Evidence map›Paper›PMID 29941794›Full record

ArticleInternational journal of environmental research and public health2018

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

David Imo, Holger Dressel, Katarzyna Byber, Christine Hitzke, Matthias Bopp, Marion Maggi, Stephan Bose-O'Reilly, Leonhard Held, Stefanie Muff

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 42% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 3 countries.

David ImoDivision of Occupational and Environmental Medicine, Epidemiology, Biostatistics and Prevention Institute, University of Zurich & University Hospital Zurich, Hirschengraben 84, 8001 Zurich, Switzerland. david.imo@uzh.ch.
Holger DresselDivision of Occupational and Environmental Medicine, Epidemiology, Biostatistics and Prevention Institute, University of Zurich & University Hospital Zurich, Hirschengraben 84, 8001 Zurich, Switzerland. holger.dressel@usz.ch.
Katarzyna ByberDivision of Occupational and Environmental Medicine, Epidemiology, Biostatistics and Prevention Institute, University of Zurich & University Hospital Zurich, Hirschengraben 84, 8001 Zurich, Switzerland. Katarzyna.Byber@usz.ch.
Christine HitzkeDivision of Occupational and Environmental Medicine, Epidemiology, Biostatistics and Prevention Institute, University of Zurich & University Hospital Zurich, Hirschengraben 84, 8001 Zurich, Switzerland. Christine.Hitzke@usz.ch.
Matthias BoppDivision of Chronic Disease Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001 Zurich, Switzerland. matthias.bopp@uzh.ch.ORCID 0000-0003-0766-3723
Marion MaggiDivision of Occupational and Environmental Medicine, Epidemiology, Biostatistics and Prevention Institute, University of Zurich & University Hospital Zurich, Hirschengraben 84, 8001 Zurich, Switzerland. Marion.Maggi-Beba@usz.ch.
Stephan Bose-O'ReillyInstitute 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. Stephan.Boeseoreilly@med.uni-muenchen.de.
Leonhard HeldDepartment of Biostatistics, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001 Zurich, Switzerland. leonhard.held@uzh.ch.
Stefanie MuffDepartment of Biostatistics, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001 Zurich, Switzerland. stefanie.muff@uzh.ch.
University of Zurich · CHUMIT - Private Universität für Gesundheitswissenschaften, Medizinische Informatik und Technik · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Environmental MonitoringMercurySoil PollutantsSpatial AnalysisAdultChildEnvironmental PollutionFemaleHousingHumansMothersRisk AssessmentSoilSwitzerlandMercurySoilSoil Pollutantschildren and mothersenvironmental epidemiologygeostatisticshealth risk assessmenthuman biomonitoringkrigingmercury

Identifiers

PMID29941794
PMCPMC6068646
OpenAlexW2811265572

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.