Prenatal Folate and Choline Levels and Brain and Cognitive Development in Children: A Critical Narrative Review
Bibliographic record
Abstract
Women's nutritional status during pregnancy can have long-term effects on children's brains and cognitive development. Folate and choline are methyl-donor nutrients and are important for closure of the neural tube during fetal development. They have also been associated with brain and cognitive development in children. Animal studies have observed that prenatal folate and choline supplementation is associated with better cognitive outcomes in offspring and that these nutrients may have interactive effects on brain development. Although some human studies have reported associations between maternal folate and choline levels and child cognitive outcomes, results are not consistent, and no human studies have investigated the potential interactive effects of folate and choline. This lack of consistency could be due to differences in the methods used to assess folate and choline levels, the gestational trimester at which they were measured, and lack of consideration of potential confounding variables. This narrative review discusses and critically reviews current research examining the associations between maternal levels of folate and choline during pregnancy and brain and cognitive development in children. Directions for future research that will increase our understanding of the effects of these nutrients on children's neurodevelopment are discussed.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".