Dietary Intake of DHA and EPA in a Group of Pregnant Women in the Moncton Area
Bibliographic record
Abstract
PURPOSE: To compare docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and fish intake of pregnant women at 30 weeks of gestation to current recommendations and to determine the factors associated with omega-3 (ω-3) intake. METHODS: A food frequency questionnaire was completed by 54 women (54/131 = 41%) at 30 ± 0.8 weeks gestation. Supplement intake, sociodemographic characteristics, and ω-3 food habits were evaluated. RESULTS: Among this high socioeconomic status (SES) group, 66.7% and 64.8% met the Food and Agriculture Organization of the United Nations (FAO)/World Health Organization (WHO) recommendation of 200 mg/d DHA and 300 mg/d DHA + EPA, respectively, and only 48.1% met the Academy of Nutrition and Dietetics (Academy) recommendation of 500 mg/d DHA + EPA. Eighteen of the 54 women took a ω-3 supplement during the third trimester. This significantly improved their total intake to meet the FAO/WHO (88.9% ≥200 mg/d DHA and 94.4% ≥300 mg/d DHA + EPA) and the Academy (77.8% ≥500 mg/d DHA + EPA) recommendations. Among nonsupplement users (36/54), 50% met the FAO/WHO recommendations and only 33.3% met the Academy recommendations. CONCLUSIONS: Results suggest that the majority of high SES women did not meet ω-3 recommendations from food alone. Continued prenatal education on the importance of fish intake and on the addition of ω-3 prenatal supplement is essential.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".