Does the timing of sample collection confound the association between prenatal serum PFAS concentrations and birthweight: results from two prospective cohort studies
Bibliographic record
Abstract
BACKGROUND: Maternal serum concentrations of per- and polyfluoroalkyl substances (PFAS) during pregnancy have been consistently associated with reduced birthweight. However, these associations may be confounded by the timing of sample collection due to pregnancy-related changes in pharmacokinetics that impact both serum PFAS concentrations and birthweight. METHODS: We measured nine serum PFAS concentrations in each trimester among 728 women in the MABC Study (Ma'anshan, China, enrolled 2013-2014). We estimated covariate-adjusted differences in birthweight for individual PFAS and their mixture, as well as percent change in PFAS by infant birthweight. We repeated our analyses in 70 women-infant dyads from the HOME Study (Cincinnati, Ohio, enrolled 2003-2006) with repeated PFAS measures in 2nd trimester and at delivery. RESULTS: -transformed 1st and 3rd trimester PFOA was associated with a 6-gram (95 % CI:-35, 22) and 26-gram (95 % CI:-54, 3) decrease in birthweight, respectively. Concentrations of six PFAS declined more steeply among women who gave birth to larger vs. smaller infants. PFOA declined by 11.3 % (95 % CI:-12.7, -9.9) vs. 8.9 % (95 % CI:-10.3, -7.5) per 13 weeks among women who gave birth to infants born at the 90th vs. 10th birthweight percentiles, respectively. We observed similar findings in the HOME Study. CONCLUSIONS: These findings suggest that physiological changes in pregnancy may confound associations between serum PFAS and birthweight. Studies with PFAS measures later in pregnancy may overestimate the true effect of PFAS on fetal growth.
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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 | 0.024 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".