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Multiple pesticide analysis in hair samples of pregnant French women: Results from the ELFE national birth cohort.
- Source :
-
Environment international [Environ Int] 2018 Nov; Vol. 120, pp. 43-53. Date of Electronic Publication: 2018 Jul 29. - Publication Year :
- 2018
-
Abstract
- Background: A growing body of evidence suggests that prenatal exposure to pesticides might impair fetal development. Nonetheless, knowledge about pesticide exposure of pregnant women, especially in Europe, is largely restricted to a limited panel of molecules.<br />Aim: To characterize the concentration of 140 pesticides and metabolites in hair strands from women in the ELFE French nationwide birth cohort.<br />Methods: Among cohort members who gave birth in northeastern and southwestern France in 2011, we selected those with a sufficient available mass of hair (n = 311). Bundles of hair 9 cm long were collected at delivery. We screened 111 pesticides and 29 metabolites, including 112 selected a priori based on their reported usage or detection in the French environment. The bundles of hair from 47 women were split into three segments to explore the intraindividual variability of the exposure. Intraclass correlation coefficients (ICCs) were computed for the chemicals with a detection frequency >70%.<br />Results: We detected a median of 43 chemicals per woman (IQR 38-47). Overall, 122 chemicals (>20 chemical families) were detected at least once, including 28 chemicals detected in 70-100% of hair samples. The highest median concentrations were observed for permethrin (median: 37.9 pg/mg of hair), p-nitrophenol (13.2 pg/mg), and pentachlorophenol (10.0 pg/mg). The ICCs for the 28 chemicals studied ranged from 0.59 to 0.94.<br />Conclusion: Pregnant women are exposed to multiple pesticides simultaneously from various chemical families, including chemicals suspected to be reproductive toxicants or endocrine disruptors. The ICCs suggest that the intraindividual variability of pesticide concentrations in hair is lower than its interindividual variability.<br /> (Copyright © 2018 Elsevier Ltd. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1873-6750
- Volume :
- 120
- Database :
- MEDLINE
- Journal :
- Environment international
- Publication Type :
- Academic Journal
- Accession number :
- 30064054
- Full Text :
- https://doi.org/10.1016/j.envint.2018.07.023