Effects of Prenatal DHA Supplementation on Child Development at age 5 years in Mexico
Bibliographic record
Abstract
Docosahexanoic acid (DHA) is an important constituent of the brain that accretes during the first 1000 days of life. Evidence of long‐term benefits of increasing DHA intakes during pregnancy is sparse. We have completed the age 5 y follow‐up of offspring of women who participated in a double‐blind randomized controlled trial of prenatal DHA supplementation in Cuernavaca, Mexico. Pregnant women (n=1094) were randomized to receive a daily supplement of 400 mg of DHA or placebo from 18–22 weeks of pregnancy until delivery. We assessed child development at age 5 y for 798 children (82% of live births) using the Spanish language version of the McCarthy Test for Global Development. Loss to follow‐up did not differ by treatment group and the groups remained balanced for maternal baseline and infant birth characteristics. Intent to treat analysis showed no significant differences by treatment group (p>;0.05) for measures of global development. We however find evidence of selective effects by quality of home environment (measured at age 12 mo; p<0.05 for interaction). Among children from poor home environments, those exposed to DHA in utero had better verbal, memory and overall scores compared to those in the placebo group. No difference was observed for children from better home environments. Children lacking an enriched learning environment may be able to “catch‐up” to their peers by DHA supplementation in pregnancy. (Support: NIH – HD043099 ).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".