PFAS exposures and child growth: a longitudinal study from fetal life to early childhood
Bibliographic record
Abstract
ABSTRACT Background Prenatal exposure to poly- and perfluoroalkyl substances (PFAS) has been associated with lower birth weight or increased adiposity in adolescence. No study has investigated associations with longitudinal growth from conception to early childhood. We explored the association between maternal serum PFAS concentrations during pregnancy and child growth assessed repeatedly from the second trimester of pregnancy to 3 years of age. Methods In the SEPAGES cohort, for 450 pregnant women recruited before 19 gestational weeks in Grenoble (France), we measured 26 PFAS from non-fasting maternal serum samples (median gestational age at sampling: 19.4 weeks). Cluster-based analysis identified three PFAS exposure groups (low, moderate, high). Child growth parameters (weight, height, and head parameters) were measured at second and third trimesters (ultrasound examinations), at birth and until 3 years. Using a nonlinear mixed model, we predicted growth parameters and velocities at exactly 3 months and 3 years. Results Compared to children belonging to the low PFAS exposure group, those belonging to the high exposure group had higher head circumference during the second trimester (ß [95% CI] = 3.60 [1.49 to 5.72] mm) and at 3 years (39.85 [1.62 to 78.08] mm) as well as higher estimated fetal weight during the second trimester (15.85 [1.48 to 30.21] g) and BMI growth velocity at 3 years (9.66 [1.73 to 17.59] g/m 2 /month). PFAS concentrations were not associated with growth parameters at third trimester, birth and 3 months. Conclusions In this prospective study, maternal serum PFAS concentrations were associated with some child growth parameters, potentially associated with increased risk of obesity in later-life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".