Associations of prenatal per- and polyfluoroalkyl substances with whole blood folate levels in pregnant women in the Health Outcomes and Measures of the Environment (HOME) Study
Bibliographic record
Abstract
Background: Folate plays a critical role during pregnancy, preventing neural tube defects and possibly adverse neurodevelopment. Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals that may decrease folate levels. Although some studies have found associations between PFAS and folate, we are unaware of studies conducted in pregnant women. To address this knowledge gap, we evaluated associations between PFAS and whole blood folate (WBF) in pregnant women. Methods: We used data from 288 pregnant women in the Health Outcomes and Measures of the Environment (HOME) Study, a pregnancy and birth cohort in the Cincinnati Ohio area. We measured eight serum PFAS and WBF concentrations at 16 weeks' gestation. We used linear regression to estimate the effect of each PFAS on WBF, and quantile-based g-computation and Bayesian kernel machine regression (BKMR) to investigate the joint effect of PFAS on WBF, adjusting for parity, prenatal vitamin intake, maternal race/ethnicity, household income, maternal age, and second trimester smoking status in all models. In addition, we investigated interactions between PFAS using BKMR. Results: We did not observe inverse associations of individual PFAS or their mixture with WBF, nor interactions between PFAS in the BKMR model in pregnant women. Conclusion: Future studies could consider WBF measures in late pregnancy to evaluate other periods of susceptibility. Furthermore, as people are exposed to multiple PFAS, future studies should continue to consider joint PFAS exposure.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".