Impact of maternal Bisphenol A exposure on thyroid hormones and birth anthropometric outcomes: A repeated measures study
Bibliographic record
Abstract
We investigated the effects of prenatal bisphenol A (BPA) exposure on maternal thyroid hormones and fetal growth outcomes within a cohort from Saudi Arabia. In this prospective study, 672 pregnant women provided 1957 urine samples, which were analyzed for BPA concentrations using UPLC-MS/MS throughout three trimesters. We recorded BPA detection rates and median concentrations, using mixed-effects models to examine the influence on maternal thyroid hormones, specifically free thyroxine (FT4) and thyroid-stimulating hormone (TSH). Additionally, we explored the impact on fetal growth markers such as head circumference (HC) and placental weight (PWT) through multivariable regression, adjusting for confounders. Findings indicated that BPA was present in over 95 % of samples, with a notable decrease in median concentrations from the 1st to the 3rd trimester. Higher BPA exposure correlated with a 2.96 % increase in FT4 levels and a 14.58 % reduction in TSH in the top exposure quartile. Fetal growth analysis showed a decrease of 3.8 % in HC and 15.3 % in PWT associated with high first-trimester BPA levels. Furthermore, FT4 levels in the first and 2nd trimesters mediated the relationship between BPA exposure and fetal growth outcomes by 21.1 % for PWT and 19.1 % for HC, while gestational age mediated 12.1 % of the change in HC. The study highlights significant disruptions in thyroid function and detrimental effects on fetal development due to high BPA exposure, underscoring the need for rigorous monitoring and preventive measures during pregnancy. • BPA was detected in 95 % of women across three trimesters. • High BPA was linked to decreased FT4 and TSH levels. • BPA exposure correlated with lower head circumference. • Elevated BPA affected placental weight significantly. • FT4 mediated BPA's impact on birth outcomes by up to 21.1 %.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".