Dietary Supplements During Pregnancy: Need, Efficacy and Safety
Bibliographic record
Abstract
SummaryNational surveys indicate that as many as 97% of women living in the United States are advised by their health care providers to take multivitamin, multimineral (MVMM) supplements during pregnancy, and 7–36% of pregnant women use botanical supplements during this time. Although there is evidence of benefit from some of these preparations, efficacy has not been established for most of them. This chapter reviews some of the most commonly used prenatal supplements in terms of the evidence for their need, efficacy, and safety. Specifically, MVMM, folate, vitamin B6, vitamin A, vitamin D, iron, zinc, magnesium, and iodine are discussed, as are several botanicals. Data indicate that, in general, evidence for benefit gained from taking prenatal MVMM supplements is not well established except for women who smoke, abuse alcohol or drugs, are anemic, or have poor quality diets. Because of folate’s well-established effect on decreasing risk for neural tube defects, it is recommended that all women of childbearing age consume supplemental folic acid daily (0.4mg/day) or obtain that amount from fortified foods. Similarly, it is recommended that all pregnant women be provided with iron supplementation (30–60 mg/day), and a recent policy statement by the American Thyroid Association suggests that all pregnant women living in the United States or Canada consume 150 mcg/day supplemental iodine to prevent iodine deficiency disorders. Currently, there is insufficient evidence to advise population-wide use of other dietary supplements, although zinc may be warranted for women consuming a vegan diet. Use of all botanical products should be carefully monitored and evaluated during pregnancy, especially those (e.g., chamomile and blue cohosh) that are contraindicated during this time. Clinicians are advised to periodically review current recommendations concerning these products, as research in this area is ongoing.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".