Impaired gross motor development in infants with higher PFAS concentrations
Bibliographic record
Abstract
Industrial produced perfluoroalkyl substances (PFAS) are environmentally persistent and found in humans around the globe. PFAS is transferred from mother to child during pregnancy and lactation and PFAS concentrations are high in infants. PFAS exposure in early life has been linked to a range of negative health effects. In the present study we have investigated PFAS concentrations in mothers (pregnancy week 18, 28 and 36 and six weeks, four and six months postpartum, n = 114) and in infants at six months age (n = 94), and studied the effects of PFAS status on infant gross motor development by Alberta Infant Motor Scale (AIMS) at age six months. PFAS concentrations declined in the mothers during pregnancy and postpartum period, and the highest concentrations were seen in infants aged six months. Parity was a strong negative predictor and fish intake a strong positive predictor of maternal PFAS status, while maternal concentrations of PFAS in pregnancy week 18 and months of exclusive breastfeeding determined the PFAS concentrations in infants at six months. Infants who scored below the median on gross motor development had higher PFAS concentrations than infants with a better gross motor development. Ninety percent of the women reported having fish for dinner at least once a week, with fatty fish as the most popular choice (72%). A higher maternal fish intake in pregnancy week 18 was associated with a poorer gross motor development in the infants at six months. Infant gross motor development is a marker of later cognitive outcome and our findings indicate that higher PFAS concentrations in young infants and maternal fatty fish intake may impair neurodevelopment.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".