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A Pooled Data Analysis to Determine the Relationship between Selected Metals and Arsenic Bioavailability in Soil

Chronic exposure to arsenic (As) is a global concern due to worldwide exposure and adverse effects, and the importance of incorporating bioavailability in the exposure assessment and risk assessment of As is increasing acknowledged. The bioavailability of As is impacted by a number of soil propertie...

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Autores principales: Yan, Kaihong, Naidu, Ravi, Liu, Yanju, Wijayawardena, Ayanka, Duan, Luchun, Dong, Zhaomin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5981927/
https://www.ncbi.nlm.nih.gov/pubmed/29710849
http://dx.doi.org/10.3390/ijerph15050888
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author Yan, Kaihong
Naidu, Ravi
Liu, Yanju
Wijayawardena, Ayanka
Duan, Luchun
Dong, Zhaomin
author_facet Yan, Kaihong
Naidu, Ravi
Liu, Yanju
Wijayawardena, Ayanka
Duan, Luchun
Dong, Zhaomin
author_sort Yan, Kaihong
collection PubMed
description Chronic exposure to arsenic (As) is a global concern due to worldwide exposure and adverse effects, and the importance of incorporating bioavailability in the exposure assessment and risk assessment of As is increasing acknowledged. The bioavailability of As is impacted by a number of soil properties, such as pH, clay and metal concentrations. By retrieving 485 data from 32 publications, the aim of this study was to determine the relationship between selected metals (Fe and Al) and As bioavailability. In present study, the bioaccessibility (BAC) data measured by in vitro approaches were converted into bioavailability data based on the previously determined relationship between BAC and bioavailability. The As relative bioavailability (RBA) was summarized to be 24.36 ± 18.49%, which is in the range previously reported. A significant association between Fe concentration and the bioavailability of As was observed while this association varied for different types of RBA data. This disparity may suggest a non-reliable association between Fe and As bioavailability. The correlations between logarithmically transformed total content of Fe + Al and As bioavailability is then outlined: RBA = (−8.40 ± 1.02) × Ln(Fe + Al) + (58.25 ± 4.09), R(2) = 0.25, p < 0.001, n = 212. Jackknife resampling was also applied to validate the relation between total content of (Fe + Al) and As bioavailability, which suggested that the relation is robust. This is the first pooled study to address the relations between selected metal concentrations and As bioavailability, which may provide some implications to establish soil properties-based RBA prediction for As.
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spelling pubmed-59819272018-06-07 A Pooled Data Analysis to Determine the Relationship between Selected Metals and Arsenic Bioavailability in Soil Yan, Kaihong Naidu, Ravi Liu, Yanju Wijayawardena, Ayanka Duan, Luchun Dong, Zhaomin Int J Environ Res Public Health Article Chronic exposure to arsenic (As) is a global concern due to worldwide exposure and adverse effects, and the importance of incorporating bioavailability in the exposure assessment and risk assessment of As is increasing acknowledged. The bioavailability of As is impacted by a number of soil properties, such as pH, clay and metal concentrations. By retrieving 485 data from 32 publications, the aim of this study was to determine the relationship between selected metals (Fe and Al) and As bioavailability. In present study, the bioaccessibility (BAC) data measured by in vitro approaches were converted into bioavailability data based on the previously determined relationship between BAC and bioavailability. The As relative bioavailability (RBA) was summarized to be 24.36 ± 18.49%, which is in the range previously reported. A significant association between Fe concentration and the bioavailability of As was observed while this association varied for different types of RBA data. This disparity may suggest a non-reliable association between Fe and As bioavailability. The correlations between logarithmically transformed total content of Fe + Al and As bioavailability is then outlined: RBA = (−8.40 ± 1.02) × Ln(Fe + Al) + (58.25 ± 4.09), R(2) = 0.25, p < 0.001, n = 212. Jackknife resampling was also applied to validate the relation between total content of (Fe + Al) and As bioavailability, which suggested that the relation is robust. This is the first pooled study to address the relations between selected metal concentrations and As bioavailability, which may provide some implications to establish soil properties-based RBA prediction for As. MDPI 2018-04-30 2018-05 /pmc/articles/PMC5981927/ /pubmed/29710849 http://dx.doi.org/10.3390/ijerph15050888 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yan, Kaihong
Naidu, Ravi
Liu, Yanju
Wijayawardena, Ayanka
Duan, Luchun
Dong, Zhaomin
A Pooled Data Analysis to Determine the Relationship between Selected Metals and Arsenic Bioavailability in Soil
title A Pooled Data Analysis to Determine the Relationship between Selected Metals and Arsenic Bioavailability in Soil
title_full A Pooled Data Analysis to Determine the Relationship between Selected Metals and Arsenic Bioavailability in Soil
title_fullStr A Pooled Data Analysis to Determine the Relationship between Selected Metals and Arsenic Bioavailability in Soil
title_full_unstemmed A Pooled Data Analysis to Determine the Relationship between Selected Metals and Arsenic Bioavailability in Soil
title_short A Pooled Data Analysis to Determine the Relationship between Selected Metals and Arsenic Bioavailability in Soil
title_sort pooled data analysis to determine the relationship between selected metals and arsenic bioavailability in soil
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5981927/
https://www.ncbi.nlm.nih.gov/pubmed/29710849
http://dx.doi.org/10.3390/ijerph15050888
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