Variability of urinary concentrations of non-persistent chemicals in pregnant women and school-aged children
Exposome studies are challenged by exposure misclassification for non-persistent chemicals, whose temporal variability contributes to bias in dose-response functions. We evaluated the variability of urinary concentrations of 24 non-persistent chemicals: 10 phthalate metabolites, 7 phenols, 6 organop...
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| Vydané v: | Environment international Ročník 121; číslo Pt 1; s. 561 - 573 |
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| Hlavní autori: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Netherlands
Elsevier Ltd
01.12.2018
Elsevier |
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| ISSN: | 0160-4120, 1873-6750, 1873-6750 |
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| Abstract | Exposome studies are challenged by exposure misclassification for non-persistent chemicals, whose temporal variability contributes to bias in dose-response functions.
We evaluated the variability of urinary concentrations of 24 non-persistent chemicals: 10 phthalate metabolites, 7 phenols, 6 organophosphate (OP) pesticide metabolites, and cotinine, between weeks from different pregnancy trimesters in pregnant women, and between days and between seasons in children.
154 pregnant women and 152 children from six European countries were enrolled in 2014–2015. Pregnant women provided three urine samples over a day (morning, midday, and night), for one week in the 2nd and 3rd pregnancy trimesters. Children provided two urines a day (morning and night), over two one-week periods, six months apart. We pooled all samples for a given subject that were collected within a week. In children, we also made four daily pools (combining morning and night voids) during the last four days of the first follow-up week. Pools were analyzed for all 24 metabolites of interest. We calculated intraclass-correlation coefficients (ICC) and estimated the number of pools needed to obtain an ICC above 0.80.
All phthalate metabolites and phenols were detected in >90% of pools whereas certain OP pesticide metabolites and cotinine were detected in <43% of pools. We observed fair (ICC = 0.40–0.59) to good (0.60–0.74) between-day reliability of the pools of two samples in children for all chemicals. Reliability was poor (<0.40) to fair between trimesters in pregnant women and between seasons in children. For most chemicals, three daily pools of two urines each (for weekly exposure windows) and four weekly pools of 15–20 urines each would be necessary to obtain an ICC above 0.80.
This quantification of the variability of biomarker measurements of many non-persistent chemicals during several time windows shows that for many of these compounds a few dozen samples are required to accurately assess exposure over periods encompassing several trimesters or months.
•Urinary measurement variability can bias dose-response functions.•We evaluated the variability of 24 metabolites in pregnant women and children.•An alternative sampling strategy based on pooled urine is proposed.•The pooling strategy does not solve variability for most of these metabolites. |
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| AbstractList | Exposome studies are challenged by exposure misclassification for non-persistent chemicals, whose temporal variability contributes to bias in dose-response functions.We evaluated the variability of urinary concentrations of 24 non-persistent chemicals: 10 phthalate metabolites, 7 phenols, 6 organophosphate (OP) pesticide metabolites, and cotinine, between weeks from different pregnancy trimesters in pregnant women, and between days and between seasons in children.154 pregnant women and 152 children from six European countries were enrolled in 2014–2015. Pregnant women provided three urine samples over a day (morning, midday, and night), for one week in the 2nd and 3rd pregnancy trimesters. Children provided two urines a day (morning and night), over two one-week periods, six months apart. We pooled all samples for a given subject that were collected within a week. In children, we also made four daily pools (combining morning and night voids) during the last four days of the first follow-up week. Pools were analyzed for all 24 metabolites of interest. We calculated intraclass-correlation coefficients (ICC) and estimated the number of pools needed to obtain an ICC above 0.80.All phthalate metabolites and phenols were detected in >90% of pools whereas certain OP pesticide metabolites and cotinine were detected in <43% of pools. We observed fair (ICC = 0.40–0.59) to good (0.60–0.74) between-day reliability of the pools of two samples in children for all chemicals. Reliability was poor (<0.40) to fair between trimesters in pregnant women and between seasons in children. For most chemicals, three daily pools of two urines each (for weekly exposure windows) and four weekly pools of 15–20 urines each would be necessary to obtain an ICC above 0.80.This quantification of the variability of biomarker measurements of many non-persistent chemicals during several time windows shows that for many of these compounds a few dozen samples are required to accurately assess exposure over periods encompassing several trimesters or months. Exposome studies are challenged by exposure misclassification for non-persistent chemicals, whose temporal variability contributes to bias in dose-response functions. We evaluated the variability of urinary concentrations of 24 non-persistent chemicals: 10 phthalate metabolites, 7 phenols, 6 organophosphate (OP) pesticide metabolites, and cotinine, between weeks from different pregnancy trimesters in pregnant women, and between days and between seasons in children. 154 pregnant women and 152 children from six European countries were enrolled in 2014–2015. Pregnant women provided three urine samples over a day (morning, midday, and night), for one week in the 2nd and 3rd pregnancy trimesters. Children provided two urines a day (morning and night), over two one-week periods, six months apart. We pooled all samples for a given subject that were collected within a week. In children, we also made four daily pools (combining morning and night voids) during the last four days of the first follow-up week. Pools were analyzed for all 24 metabolites of interest. We calculated intraclass-correlation coefficients (ICC) and estimated the number of pools needed to obtain an ICC above 0.80. All phthalate metabolites and phenols were detected in >90% of pools whereas certain OP pesticide metabolites and cotinine were detected in <43% of pools. We observed fair (ICC = 0.40–0.59) to good (0.60–0.74) between-day reliability of the pools of two samples in children for all chemicals. Reliability was poor (<0.40) to fair between trimesters in pregnant women and between seasons in children. For most chemicals, three daily pools of two urines each (for weekly exposure windows) and four weekly pools of 15–20 urines each would be necessary to obtain an ICC above 0.80. This quantification of the variability of biomarker measurements of many non-persistent chemicals during several time windows shows that for many of these compounds a few dozen samples are required to accurately assess exposure over periods encompassing several trimesters or months. •Urinary measurement variability can bias dose-response functions.•We evaluated the variability of 24 metabolites in pregnant women and children.•An alternative sampling strategy based on pooled urine is proposed.•The pooling strategy does not solve variability for most of these metabolites. Background: Exposome studies are challenged by exposure misclassification for non-persistent chemicals, whose temporal variability contributes to bias in dose-response functions. Objectives: We evaluated the variability of urinary concentrations of 24 non-persistent chemicals: 10 phthalate metabolites, 7 phenols, 6 organophosphate (OP) pesticide metabolites, and cotinine, between weeks from different pregnancy trimesters in pregnant women, and between days and between seasons in children. Methods: 154 pregnant women and 152 children from six European countries were enrolled in 2014–2015. Pregnant women provided three urine samples over a day (morning, midday, and night), for one week in the 2nd and 3rd pregnancy trimesters. Children provided two urines a day (morning and night), over two one-week periods, six months apart. We pooled all samples for a given subject that were collected within a week. In children, we also made four daily pools (combining morning and night voids) during the last four days of the first follow-up week. Pools were analyzed for all 24 metabolites of interest. We calculated intraclass-correlation coefficients (ICC) and estimated the number of pools needed to obtain an ICC above 0.80. Results: All phthalate metabolites and phenols were detected in >90% of pools whereas certain OP pesticide metabolites and cotinine were detected in <43% of pools. We observed fair (ICC = 0.40–0.59) to good (0.60–0.74) between-day reliability of the pools of two samples in children for all chemicals. Reliability was poor (<0.40) to fair between trimesters in pregnant women and between seasons in children. For most chemicals, three daily pools of two urines each (for weekly exposure windows) and four weekly pools of 15–20 urines each would be necessary to obtain an ICC above 0.80. Conclusions: This quantification of the variability of biomarker measurements of many non-persistent chemicals during several time windows shows that for many of these compounds a few dozen samples are required to accurately assess exposure over periods encompassing several trimesters or months. The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement no 308333 – the HELIX project. Dr. Maribel Casas received funding from Instituto de Salud Carlos III (Ministry of Economy and Competitiveness) (MS16/00128). Dr. Regina Grazuleviciene received the grant of the Lithuanian Agency for Science Innovation and Technology (No. 31V-66). Dr. Juan R Gonzalez is supported by Ministerio de Economía y Competitividad y Fondo Europeo de Desarrollo (MTM2015-68140-R). The pregnant women recruited in Grenoble are part of SEPAGES mother-child cohort, which has been partly funded by a grant from the European Research Council (ERC, consolidator grant #311765-EDOHaD, PI, R. Slama). Background: Exposome studies are challenged by exposure misclassification for non-persistent chemicals, whose temporal variability contributes to bias in dose-response functions. Objectives: We evaluated the variability of urinary concentrations of 24 non-persistent chemicals: 10 phthalate metabolites, 7 phenols, 6 organophosphate (OP) pesticide metabolites, and cotinine, between weeks from different pregnancy trimesters in pregnant women, and between days and between seasons in children. Methods: 154 pregnant women and 152 children from six European countries were enrolled in 2014–2015. Pregnant women provided three urine samples over a day (morning, midday, and night), for one week in the 2nd and 3rd pregnancy trimesters. Children provided two urines a day (morning and night), over two one-week periods, six months apart. We pooled all samples for a given subject that were collected within a week. In children, we also made four daily pools (combining morning and night voids) during the last four days of the first follow-up week. Pools were analyzed for all 24 metabolites of interest. We calculated intraclass-correlation coefficients (ICC) and estimated the number of pools needed to obtain an ICC above 0.80. Results: All phthalate metabolites and phenols were detected in >90% of pools whereas certain OP pesticide metabolites and cotinine were detected in <43% of pools. We observed fair (ICC = 0.40–0.59) to good (0.60–0.74) between-day reliability of the pools of two samples in children for all chemicals. Reliability was poor (<0.40) to fair between trimesters in pregnant women and between seasons in children. For most chemicals, three daily pools of two urines each (for weekly exposure windows) and four weekly pools of 15–20 urines each would be necessary to obtain an ICC above 0.80. Conclusions: This quantification of the variability of biomarker measurements of many non-persistent chemicals during several time windows shows that for many of these compounds a few dozen samples are required to accurately assess exposure over periods encompassing several trimesters or months. Keywords: Phthalate metabolites, Phenols, Organophosphate pesticide metabolites, Pregnancy, Childhood, Intraclass-correlation coefficient Exposome studies are challenged by exposure misclassification for non-persistent chemicals, whose temporal variability contributes to bias in dose-response functions.BACKGROUNDExposome studies are challenged by exposure misclassification for non-persistent chemicals, whose temporal variability contributes to bias in dose-response functions.We evaluated the variability of urinary concentrations of 24 non-persistent chemicals: 10 phthalate metabolites, 7 phenols, 6 organophosphate (OP) pesticide metabolites, and cotinine, between weeks from different pregnancy trimesters in pregnant women, and between days and between seasons in children.OBJECTIVESWe evaluated the variability of urinary concentrations of 24 non-persistent chemicals: 10 phthalate metabolites, 7 phenols, 6 organophosphate (OP) pesticide metabolites, and cotinine, between weeks from different pregnancy trimesters in pregnant women, and between days and between seasons in children.154 pregnant women and 152 children from six European countries were enrolled in 2014-2015. Pregnant women provided three urine samples over a day (morning, midday, and night), for one week in the 2nd and 3rd pregnancy trimesters. Children provided two urines a day (morning and night), over two one-week periods, six months apart. We pooled all samples for a given subject that were collected within a week. In children, we also made four daily pools (combining morning and night voids) during the last four days of the first follow-up week. Pools were analyzed for all 24 metabolites of interest. We calculated intraclass-correlation coefficients (ICC) and estimated the number of pools needed to obtain an ICC above 0.80.METHODS154 pregnant women and 152 children from six European countries were enrolled in 2014-2015. Pregnant women provided three urine samples over a day (morning, midday, and night), for one week in the 2nd and 3rd pregnancy trimesters. Children provided two urines a day (morning and night), over two one-week periods, six months apart. We pooled all samples for a given subject that were collected within a week. In children, we also made four daily pools (combining morning and night voids) during the last four days of the first follow-up week. Pools were analyzed for all 24 metabolites of interest. We calculated intraclass-correlation coefficients (ICC) and estimated the number of pools needed to obtain an ICC above 0.80.All phthalate metabolites and phenols were detected in >90% of pools whereas certain OP pesticide metabolites and cotinine were detected in <43% of pools. We observed fair (ICC = 0.40-0.59) to good (0.60-0.74) between-day reliability of the pools of two samples in children for all chemicals. Reliability was poor (<0.40) to fair between trimesters in pregnant women and between seasons in children. For most chemicals, three daily pools of two urines each (for weekly exposure windows) and four weekly pools of 15-20 urines each would be necessary to obtain an ICC above 0.80.RESULTSAll phthalate metabolites and phenols were detected in >90% of pools whereas certain OP pesticide metabolites and cotinine were detected in <43% of pools. We observed fair (ICC = 0.40-0.59) to good (0.60-0.74) between-day reliability of the pools of two samples in children for all chemicals. Reliability was poor (<0.40) to fair between trimesters in pregnant women and between seasons in children. For most chemicals, three daily pools of two urines each (for weekly exposure windows) and four weekly pools of 15-20 urines each would be necessary to obtain an ICC above 0.80.This quantification of the variability of biomarker measurements of many non-persistent chemicals during several time windows shows that for many of these compounds a few dozen samples are required to accurately assess exposure over periods encompassing several trimesters or months.CONCLUSIONSThis quantification of the variability of biomarker measurements of many non-persistent chemicals during several time windows shows that for many of these compounds a few dozen samples are required to accurately assess exposure over periods encompassing several trimesters or months. Background : Exposome studies are challenged by exposure misclassification for non-persistent chemicals, whose temporal variability contributes to bias in dose-response functions. Objectives : We evaluated the variability of urinary concentrations of 24 non-persistent chemicals: 10 phthalate metabolites, 7 phenols, 6 organophosphate (OP) pesticide metabolites, and cotinine, between weeks from different pregnancy trimesters in pregnant women, and between days and between seasons in children. Methods : 154 pregnant women and 152 children from six European countries were enrolled in 2014–2015. Pregnant women provided three urine samples over a day (morning, midday, and night), for one week in the 2nd and 3rd pregnancy trimesters. Children provided two urines a day (morning and night), over two one-week periods, six months apart. We pooled all samples for a given subject that were collected within a week. In children, we also made four daily pools (combining morning and night voids) during the last four days of the first follow-up week. Pools were analyzed for all 24 metabolites of interest. We calculated intraclass-correlation coefficients (ICC) and estimated the number of pools needed to obtain an ICC above 0.80. Results : All phthalate metabolites and phenols were detected in >90% of pools whereas certain OP pesticide metabolites and cotinine were detected in <43% of pools. We observed fair (ICC = 0.40–0.59) to good (0.60–0.74) between-day reliability of the pools of two samples in children for all chemicals. Reliability was poor (<0.40) to fair between trimesters in pregnant women and between seasons in children. For most chemicals, three daily pools of two urines each (for weekly exposure windows) and four weekly pools of 15–20 urines each would be necessary to obtain an ICC above 0.80. Conclusions : This quantification of the variability of biomarker measurements of many non-persistent chemicals during several time windows shows that for many of these compounds a few dozen samples are required to accurately assess exposure over periods encompassing several trimesters or months. Exposome studies are challenged by exposure misclassification for non-persistent chemicals, whose temporal variability contributes to bias in dose-response functions. We evaluated the variability of urinary concentrations of 24 non-persistent chemicals: 10 phthalate metabolites, 7 phenols, 6 organophosphate (OP) pesticide metabolites, and cotinine, between weeks from different pregnancy trimesters in pregnant women, and between days and between seasons in children. 154 pregnant women and 152 children from six European countries were enrolled in 2014-2015. Pregnant women provided three urine samples over a day (morning, midday, and night), for one week in the 2nd and 3rd pregnancy trimesters. Children provided two urines a day (morning and night), over two one-week periods, six months apart. We pooled all samples for a given subject that were collected within a week. In children, we also made four daily pools (combining morning and night voids) during the last four days of the first follow-up week. Pools were analyzed for all 24 metabolites of interest. We calculated intraclass-correlation coefficients (ICC) and estimated the number of pools needed to obtain an ICC above 0.80. All phthalate metabolites and phenols were detected in >90% of pools whereas certain OP pesticide metabolites and cotinine were detected in <43% of pools. We observed fair (ICC = 0.40-0.59) to good (0.60-0.74) between-day reliability of the pools of two samples in children for all chemicals. Reliability was poor (<0.40) to fair between trimesters in pregnant women and between seasons in children. For most chemicals, three daily pools of two urines each (for weekly exposure windows) and four weekly pools of 15-20 urines each would be necessary to obtain an ICC above 0.80. This quantification of the variability of biomarker measurements of many non-persistent chemicals during several time windows shows that for many of these compounds a few dozen samples are required to accurately assess exposure over periods encompassing several trimesters or months. |
| Author | de Bont, Jeroen Urquiza, Jose Pañella, Pau Brochot, Céline Chatzi, Leda Casas, Maribel Vernet, Céline Vrijheid, Martine Gracia-Lavedan, Esther Basagaña, Xavier Granum, Berit Petraviciene, Inga Vafeiadi, Marina Donaire-Gonzalez, David Kampouri, Mariza Wright, John Waiblinger, Dagmar Philippat, Claire Andrusaityte, Sandra Giorgis-Allemand, Lise Sakhi, Amrit K. Robinson, Oliver Haug, Line S. Gonzalez, Juan R. Manzano-Salgado, Cyntia B. Zeman, Florence Grazuleviciene, Regina Slama, Rémy Lyon-Caen, Sarah Thomsen, Cathrine |
| Author_xml | – sequence: 1 givenname: Maribel surname: Casas fullname: Casas, Maribel email: maribel.casas@isglobal.org organization: ISGlobal, Barcelona, Spain – sequence: 2 givenname: Xavier orcidid: 0000-0002-8457-1489 surname: Basagaña fullname: Basagaña, Xavier organization: ISGlobal, Barcelona, Spain – sequence: 3 givenname: Amrit K. surname: Sakhi fullname: Sakhi, Amrit K. organization: Norwegian Institute of Public Health (NIPH), Oslo, Norway – sequence: 4 givenname: Line S. surname: Haug fullname: Haug, Line S. organization: Norwegian Institute of Public Health (NIPH), Oslo, Norway – sequence: 5 givenname: Claire surname: Philippat fullname: Philippat, Claire organization: Institut National de la Santé et de la Recherche Médicale (Inserm), CNRS, Univ. Grenoble Alpes, Institute for Advanced Biosciences (IAB), U1209, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Grenoble, France – sequence: 6 givenname: Berit surname: Granum fullname: Granum, Berit organization: Norwegian Institute of Public Health (NIPH), Oslo, Norway – sequence: 7 givenname: Cyntia B. orcidid: 0000-0003-1242-2318 surname: Manzano-Salgado fullname: Manzano-Salgado, Cyntia B. organization: ISGlobal, Barcelona, Spain – sequence: 8 givenname: Céline surname: Brochot fullname: Brochot, Céline organization: Institut National de l'Environnement Industriel et des Risques (INERIS), Unité Modèles pour l'Ecotoxicologie et la Toxicologie, Parc Alata BP2, 60550 Verneuil-en-Halatte, France – sequence: 9 givenname: Florence surname: Zeman fullname: Zeman, Florence organization: Institut National de l'Environnement Industriel et des Risques (INERIS), Unité Modèles pour l'Ecotoxicologie et la Toxicologie, Parc Alata BP2, 60550 Verneuil-en-Halatte, France – sequence: 10 givenname: Jeroen surname: de Bont fullname: de Bont, Jeroen organization: ISGlobal, Barcelona, Spain – sequence: 11 givenname: Sandra surname: Andrusaityte fullname: Andrusaityte, Sandra organization: Vytauto Didziojo Universitetas (VDU), Kaunus, Lithuania – sequence: 12 givenname: Leda surname: Chatzi fullname: Chatzi, Leda organization: Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, USA – sequence: 13 givenname: David orcidid: 0000-0003-2337-1712 surname: Donaire-Gonzalez fullname: Donaire-Gonzalez, David organization: ISGlobal, Barcelona, Spain – sequence: 14 givenname: Lise surname: Giorgis-Allemand fullname: Giorgis-Allemand, Lise organization: Institut National de la Santé et de la Recherche Médicale (Inserm), CNRS, Univ. Grenoble Alpes, Institute for Advanced Biosciences (IAB), U1209, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Grenoble, France – sequence: 15 givenname: Juan R. surname: Gonzalez fullname: Gonzalez, Juan R. organization: ISGlobal, Barcelona, Spain – sequence: 16 givenname: Esther surname: Gracia-Lavedan fullname: Gracia-Lavedan, Esther organization: ISGlobal, Barcelona, Spain – sequence: 17 givenname: Regina surname: Grazuleviciene fullname: Grazuleviciene, Regina organization: Vytauto Didziojo Universitetas (VDU), Kaunus, Lithuania – sequence: 18 givenname: Mariza surname: Kampouri fullname: Kampouri, Mariza organization: Department of Social Medicine, University of Crete (UOC), Heraklion, Crete, Greece – sequence: 19 givenname: Sarah surname: Lyon-Caen fullname: Lyon-Caen, Sarah organization: Institut National de la Santé et de la Recherche Médicale (Inserm), CNRS, Univ. Grenoble Alpes, Institute for Advanced Biosciences (IAB), U1209, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Grenoble, France – sequence: 20 givenname: Pau surname: Pañella fullname: Pañella, Pau organization: ISGlobal, Barcelona, Spain – sequence: 21 givenname: Inga surname: Petraviciene fullname: Petraviciene, Inga organization: Vytauto Didziojo Universitetas (VDU), Kaunus, Lithuania – sequence: 22 givenname: Oliver surname: Robinson fullname: Robinson, Oliver organization: ISGlobal, Barcelona, Spain – sequence: 23 givenname: Jose surname: Urquiza fullname: Urquiza, Jose organization: ISGlobal, Barcelona, Spain – sequence: 24 givenname: Marina surname: Vafeiadi fullname: Vafeiadi, Marina organization: Department of Social Medicine, University of Crete (UOC), Heraklion, Crete, Greece – sequence: 25 givenname: Céline surname: Vernet fullname: Vernet, Céline organization: Institut National de la Santé et de la Recherche Médicale (Inserm), CNRS, Univ. Grenoble Alpes, Institute for Advanced Biosciences (IAB), U1209, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Grenoble, France – sequence: 26 givenname: Dagmar surname: Waiblinger fullname: Waiblinger, Dagmar organization: Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust (BTHFT), Bradford, United Kingdom – sequence: 27 givenname: John surname: Wright fullname: Wright, John organization: Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust (BTHFT), Bradford, United Kingdom – sequence: 28 givenname: Cathrine surname: Thomsen fullname: Thomsen, Cathrine organization: Norwegian Institute of Public Health (NIPH), Oslo, Norway – sequence: 29 givenname: Rémy surname: Slama fullname: Slama, Rémy organization: Institut National de la Santé et de la Recherche Médicale (Inserm), CNRS, Univ. Grenoble Alpes, Institute for Advanced Biosciences (IAB), U1209, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Grenoble, France – sequence: 30 givenname: Martine surname: Vrijheid fullname: Vrijheid, Martine organization: ISGlobal, Barcelona, Spain |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30300814$$D View this record in MEDLINE/PubMed https://ineris.hal.science/ineris-01960310$$DView record in HAL |
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| Title | Variability of urinary concentrations of non-persistent chemicals in pregnant women and school-aged children |
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