Associations between maternal folate status and choline intake during pregnancy and neurodevelopment at 3–4 years of age in the Alberta Pregnancy Outcomes and Nutrition (APrON) study
Bibliographic record
Abstract
Abstract Folate and choline are methyl donor nutrients that may play a role in fetal brain development. Animal studies have reported that prenatal folate and choline supplementation are associated with better cognitive outcomes in offspring and that these nutrients may interact and affect brain development. Human studies that have investigated associations between maternal prenatal folate or choline levels and neurodevelopmental outcomes have reported contradictory findings and no human studies have examined the potential interactive effect of folate and choline on children’s neurodevelopment. During the second trimester of pregnancy, maternal red blood cell folate was measured from blood samples and choline intake was estimated using a 24-h dietary recall in 309 women in the APrON cohort. At 3–5 years of age, their children’s neurodevelopment was assessed using the Wechsler Preschool and Primary Scales of Intelligence – Fourth Edition CND , NEPSY-II language and memory subtests, four behavioral executive function tasks, and the Movement Assessment Battery for Children – Second Edition. Adjusted regressions revealed no associations between maternal folate and choline levels during pregnancy and most of the child outcomes. On the Dimensional Change Card Sort, an executive function task, there was an interaction effect; at high levels of choline intake (i.e., 1 SD above the mean; 223.03 mg/day), higher maternal folate status was associated with decreased odds of receiving a passing score (β = −0.44; 95%CI −0.81, −0.06). In conclusion, maternal folate status and choline intake during the second trimester of pregnancy were not associated with children’s intelligence, language, memory, or motor outcomes at 3–4 years of age; however, their interaction may have an influence children’s executive functions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".