Relationship Between Maternal DHA and Iron Status And Infants' Cognitive Performance
Bibliographic record
Abstract
PURPOSE: The dietary nutrients iron and long-chain polyunsaturated fatty acids are believed to play an important role in early brain development. We investigated the relationship between pregnant women's iron and docosahexaenoic acid (DHA) status and their infants' cognitive performance at age six months. METHODS: Blood iron and DHA status were analyzed in pregnant women at 28 to 32 weeks of gestation. The women's dietary habits, sociodemographic background, and cognitive performance were assessed using questionnaires. At age six months, infants' blood hemoglobin was analyzed, feeding practices assessed, and weight, length, and head circumference recorded. Each infant's cognitive performance was assessed using the Brunet-Lézine Scale of Psychomotor Development of Early Childhood and the Bayley Scales of Infant Development. Sixty-three mother-infant dyads completed the study. RESULTS: During pregnancy, 9.5% of pregnant women were anemic, 34.9% had low iron stores, and 3.2% suffered from iron deficiency anemia. The DHA represented 4.36% and 2.15% in erythrocyte and plasma total fatty acids, respectively. These levels were considered adequate. No significant relationship was observed between gestational iron or DHA status and infants' cognitive performance. CONCLUSIONS: In this small group of infants born to mothers with relatively good feeding practices and a privileged socioeconomic background, cognitive testing with the instruments above was not associated with maternal iron and DHA levels at age six months.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".