Supplementation practices among pregnant women and those trying to conceive: a population-representative survey in Vancouver, Canada
Bibliographic record
Abstract
Dietary supplements including vitamins, minerals, and natural health products are commonly consumed by those aiming to optimize fertility and pregnancy outcomes. The aim of this survey was to describe supplementation practices among individuals who were pregnant or trying to conceive in Vancouver, Canada. An online survey was conducted among 500 individuals who were pregnant ( n = 250) or trying to conceive ( n = 250). Participants met a substantial proportion of vitamin and mineral recommendations through supplements alone. Exceptions included calcium, magnesium, and choline, with median (interquartile range (IQR)) supplementation doses reported by those who were pregnant and trying to conceive, respectively, of: 250 (200 and 250 mg) and 250 (200 and 250 mg), 50 (50 and 75 mg) and 50 (50 and 90 mg), and 53 (10 and 150 mg) and 55 (10 and 100 mg), as compared to perinatal recommendations of 1000 mg/day (calcium), 350 mg/day (magnesium), and 450 mg/day (choline). Conversely, median (IQR) doses of folate reported by those who were pregnant and trying to conceive, respectively, were: 1000 (780 and 1000 µg) and 1000 (800 and 1000 µg), with ∼70% overall (337/471) reporting doses ≥1000 µg (the tolerable upper intake level). Most participants (451/500; 90%) reported supplementation with a prenatal multivitamin; of these, 83% reported that supplementation occurred daily. Overall, as diet was not considered, we cannot ascertain whether recommendations for calcium, magnesium, and choline were met through the combination of supplements and foods; however, we believe that additional supplementation with choline may be required to meet recommendations in pregnancy. Excessive folate supplementation has been previously identified as a concern throughout North America; here, we provide further evidence for excessively high doses consumed via supplements.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".