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. 2019 Sep;29(5):674-687.
doi: 10.1038/s41370-018-0081-6. Epub 2018 Oct 18.

Assessing the contributions of metals in environmental media to exposure biomarkers in a region of ferroalloy industry

Lindsey Butler  1 , Chris Gennings  2 , Marco Peli  3 , Laura Borgese  4 , Donatella Placidi  5 , Neil Zimmerman  6 , Hsiao-Hsien L Hsu  2 , Brent A Coull  7 , Robert O Wright  2 , Donald R Smith  8 , Roberto G Lucchini  2   5   8 , Birgit Claus Henn  9
Affiliations

Assessing the contributions of metals in environmental media to exposure biomarkers in a region of ferroalloy industry

Lindsey Butler et al. J Expo Sci Environ Epidemiol. 2019 Sep.

Abstract

Residential proximity to ferroalloy production has been associated with increased manganese exposure, which can adversely affect health, particularly among children. Little is known, however, about which environmental samples contribute most to internal levels of manganese and other ferroalloy metals. We aimed to characterize sources of exposure to metals and evaluate the ability of internal biomarkers to reflect exposures from environmental media. In 717 Italian adolescents residing near ferromanganese industry, we examined associations between manganese, lead, chromium, and copper in environmental samples (airborne particles, surface soil, indoor/outdoor house dust) and biological samples (blood, hair, nails, saliva, urine). In multivariable regression analyses adjusted for child age and sex, a 10% increase in soil Mn was associated with increases of 3.0% (95% CI: 1.1%, 4.9%) in nail Mn and 1.6% (95% CI: -0.2%, 3.4%) in saliva Mn. Weighted-quantile-sum (WQS) regression estimated that higher soil and outdoor dust Mn accounted for most of the effect on nail Mn (WQS weights: 0.61 and 0.22, respectively, out of a total of 1.0). Higher air and soil Mn accounted for most of the effect on saliva Mn (WQS weights: 0.65 and 0.29, respectively). These findings can help inform biomarker selection in future epidemiologic studies and guide intervention strategies in exposed populations.

Keywords: Chromium; Copper; Ferroalloy; Lead; Manganese; Weighted quantile sum regression.

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Conflict of interest statement

Conflict of Interest: The authors declare no conflict of interest.

Figures

Figure 1.
Figure 1.
Map of the province of Brescia, Italy. Ferroalloy plants in Valcamonica (Sellero, Breno, and Darfo Boario plants) and in Bagnolo Mella are shown with their respective operating periods. Residential drinking water is provided from public drinking water supply systems that are fed by the drinking water sources depicted on the map.
Figure 2.
Figure 2.
Results of weighted quantile sum regression for (A) manganese, (B) lead, (C) chromium, and (D) copper. The y-axis, Weighted Mean Contribution, indicates the relative contributions of environmental sources to each biomarker. The height of the bar for each biomarker is scaled by the magnitude of that biomarker’s beta coefficient in the weighted regression model. The colors within the bar indicate the proportion contributed by each environmental source.
Figure 2.
Figure 2.
Results of weighted quantile sum regression for (A) manganese, (B) lead, (C) chromium, and (D) copper. The y-axis, Weighted Mean Contribution, indicates the relative contributions of environmental sources to each biomarker. The height of the bar for each biomarker is scaled by the magnitude of that biomarker’s beta coefficient in the weighted regression model. The colors within the bar indicate the proportion contributed by each environmental source.
See this image and copyright information in PMC

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