Evidence map›Paper›PMID 24969305›Full record

ArticleEnvironmental geochemistry and health2015

Combining spatial distribution with oral bioaccessibility of metals in smelter-impacted soils: implications for human health risk assessment.

Aurélie Pelfrêne, Sébastien Détriché, Francis Douay

Abstract read
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Article in Environmental geochemistry and health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Article
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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

3 authors.

Aurélie PelfrêneGroupe ISA, Laboratoire Génie Civil et géo-Environnement (LGCgE), 48 boulevard Vauban, 59046, Lille Cedex, France, aurelie.pelfrene@isa-lille.fr.
Sébastien Détriché
Francis Douay

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Geostatistical analysis and GIS-based spatial mapping have been widely used for risk assessment of environmental pollution. The objectives of this study were to: (1) investigate the spatial variability of pseudototal concentrations of Cd, Pb, and Zn; (2) estimate the degree of contamination on the basis of pollution indexes; and (3) combine geostatistical analysis with oral bioaccessibility to better assess the population's exposure to metals in smelter-impacted soils. Implications for human health risks were assessed by considering soil as a contaminant source, a release mechanism of contaminated soil to the hands, ingestion as an exposure route, and metal bioaccessibility. The bioaccessibility data in the gastric (G) and gastrointestinal (GI) phases were integrated into the standard hazard quotient-based risk assessment method. Using pollution indices showed that the entire area studied was highly polluted in terms of soil metal concentrations. However, the spatial pattern of health risk levels did not coincide with the spatial distribution of the degree of soil contamination. Introducing the bioaccessible fraction of metals from soils into the exposure calculations resulted in a substantial decrease in calculated risk (HI, hazard index) and provided a more realistic estimate of exposure to the three metals. For the highly exposed population, 46% of the soils studied provided an HI-G > 1.0 and 15% provided an HI-GI > 1.0, suggesting probable adverse health effects in children. The present study highlights the importance of conducting studies taking into account metal bioaccessible values in risk assessment.

Indexed as

Environmental ExposureEnvironmental MonitoringEnvironmental PollutionFranceGeographic Information SystemsHumansMetallurgyMetals, HeavyRisk AssessmentSoilSoil PollutantsMetals, HeavySoilSoil Pollutants

Identifiers

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Registered trials

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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.