Maribel Casas1, Xavier Basagaña2, Amrit K Sakhi3, Line S Haug3, Claire Philippat4, Berit Granum3, Cyntia B Manzano-Salgado2, Céline Brochot5, Florence Zeman5, Jeroen de Bont2, Sandra Andrusaityte6, Leda Chatzi7, David Donaire-Gonzalez2, Lise Giorgis-Allemand4, Juan R Gonzalez2, Esther Gracia-Lavedan2, Regina Grazuleviciene6, Mariza Kampouri8, Sarah Lyon-Caen4, Pau Pañella2, Inga Petraviciene6, Oliver Robinson9, Jose Urquiza2, Marina Vafeiadi8, Céline Vernet4, Dagmar Waiblinger10, John Wright10, Cathrine Thomsen3, Rémy Slama4, Martine Vrijheid2. 1. ISGlobal, Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain; Universitat Pompeu Fabra, Barcelona, Spain. Electronic address: maribel.casas@isglobal.org. 2. ISGlobal, Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain; Universitat Pompeu Fabra, Barcelona, Spain. 3. Norwegian Institute of Public Health (NIPH), Oslo, Norway. 4. 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. 5. 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. 6. Vytauto Didziojo Universitetas (VDU), Kaunus, Lithuania. 7. Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, USA; Department of Genetics & Cell Biology, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands. 8. Department of Social Medicine, University of Crete (UOC), Heraklion, Crete, Greece. 9. ISGlobal, Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain; Universitat Pompeu Fabra, Barcelona, Spain; MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, United Kingdom. 10. Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust (BTHFT), Bradford, United Kingdom.
Abstract
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.
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.
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