Changes in Serum Concentrations of Maternal Poly- and Perfluoroalkyl Substances over the Course of Pregnancy and Predictors of Exposure in a Multiethnic Cohort of Cincinnati, Ohio Pregnant Women during 2003–2006
Bibliographic record
Abstract
Data on predictors of gestational exposure to poly- and perfluoroalkyl substances (PFASs) in the United States are limited. To fill in this gap, in a multiethnic cohort of Ohio pregnant women recruited in 2003-2006, we measured perfluorooctanesulfonate (PFOS), perfluorooctanoate (PFOA), and six additional PFASs in maternal serum at ∼16 weeks gestation (N = 182) and delivery (N = 78), and in umbilical cord serum (N = 202). We used linear regression to examine associations between maternal serum PFASs concentrations and demographic, perinatal, and lifestyle factors. PFASs concentrations in maternal sera and in their infants' cord sera were highly correlated (Spearman rank correlation coefficients = 0.73-0.95). In 71 maternal-infant dyads, unadjusted geometric mean (GM) concentrations (95% confidence interval) (in μg/L) in maternal serum at delivery of PFOS [8.50 (7.01-9.58)] and PFOA [3.43 (3.01-3.90)] were significantly lower than at 16 weeks gestation [11.57 (9.90-13.53], 4.91 (4.32-5.59), respectively], but higher than in infants' cord serum [3.32 (2.84-3.89), 2.85 (2.51-3.24), respectively] (P < 0.001). Women who were parous, with a history of previous breastfeeding, black, or in the lowest income category had significantly lower PFOS and PFOA GM concentrations than other women. These data suggest transplacental transfer of PFASs during pregnancy and nursing for the first time in a U.S. birth cohort.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".