Phthalate exposure during pregnancy and its association with thyroid hormones: A prospective cohort study
Notice bibliographique
Résumé
Phthalate esters (PAEs) possess endocrine-disrupting properties. Studies in humans have indicated that in utero phthalate exposure affects maternal thyroid hormones, which are essential for fetal growth and development. However, these studies also reported inconsistent results on the relationship between phthalates and thyroid hormones. This prospective cohort study aimed to assess phthalate exposure across the three trimesters of pregnancy and its association with thyroid hormone levels. From 2019 to 2022, we recruited 672 pregnant women, and two urine samples and one blood sample were collected from each participant during the pregnancy. We examined the urine samples from 663, 335, and 294 women in the first, second, and third trimester, respectively, for the following seven phthalate metabolites: monoethyl phthalate (MEP) from diethyl phthalate (DEP); mono-n-butyl phthalate (MnBP) and mono-iso-butyl phthalate (MiBP) from dibutyl phthalate (DBP); monobenzyl phthalate (MBzP) from butyl benzyl phthalate; and three di(2-ethylhexyl) phthalate (DEHP) metabolites, mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), and mono-(2-ethyl-5-carboxypentyl) phthalate (MECPP). Additionally, we examined the levels of free thyroxine (FT4), thyroid-stimulating hormone (TSH), and total triiodothyronine (TT3) in the serum samples of the following participants: 596, 627, and 576 in the first trimester; 292, 293, and 282 in the second trimester; and 250, 250, and 248 in the third trimester, respectively. Other than MBzP, which was detected in 25%–33% of the samples, other metabolites were detectable in >86% of urine samples, indicating widespread exposure to DEP, DBP, and DEHP. The detected phthalate exposure levels in our cohort were significantly higher than those reported in other countries. Metabolite levels varied across the trimesters, implying changes in exposure and metabolism throughout pregnancy. The observed variability in urinary concentrations of phthalate metabolites, which ranged from poor to moderate, underscores the importance of taking multiple measurements during pregnancy for precise exposure assessment. Using a linear mixed model, we analyzed the effects of repeated phthalate exposure on thyroid hormone levels while adjusting for potential confounders. We observed significant linear trends in FT4, TSH, and, to a lesser extent, TT3 across quartiles of specific phthalate metabolites. Comparing the highest to the lowest quartiles, we found a significant increase in FT4 levels, ranging from 2 to 3.7%, associated with MEP; MECPP; MEHHP; and the sum of seven metabolites (∑7PAE), three DEHP metabolites (∑3DEHP), two DBP metabolites (∑DBP), and both low molecular weight (∑LMW) and high molecular weight metabolites. Increased TSH levels (5%–16%) were observed for all phthalate metabolites (except MEHHP) and their molar sums, including ∑7PAE. For TT3, a significant increase was observed with MEP (2.2%) and a decrease was observed with ∑DBP (−2.7%). A higher TSH/FT4 ratio was observed with the highest quartiles (third or fourth) of several phthalate metabolites: MEP (8.8%), MiBP (8.7%), MnBP (22.2%), ∑7PAE (15.3%), ∑DBP (16.4%), and ∑LMW (18.6%). These hormonal alterations, most notably in the second and third trimesters, suggest that phthalate exposure may impact fetal growth and development by affecting maternal thyroid function.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».