Scoping Review of the Effects of Dietary Supplements on Postpartum Depression
Bibliographic record
Abstract
Postpartum depression (PPD) can emerge as one of many maternal risks during the postpartum period. Though antidepressants have traditionally treated PPD, dietary supplements have been increasingly studied as a more accessible remedy, focusing on prevention. The goal of this study is to consolidate information about the effects of dietary supplements on PPD. A scoping review was conducted to identify a possible relationship between various supplements and PPD, using relevant studies on PubMed and Medline published between January 1, 2010 and February 1, 2020. Only English language literature with human subjects was included. 39 articles (from 606 articles originally retrieved) were included and summarized under headings related to: vitamins; minerals; fatty acids; antibiotics and probiotics; and, combination of supplements. The results revealed that dietary supplementation with Vitamin D, multivitamins, selenium, n-3 polyunsaturated fatty acids (PUFA), or probiotics generally lead to decreased PPD risk. Supplementation with calcium, magnesium, zinc, iodine, iron, or any B-vitamins has no effect on PPD, although there are conflicting reports regarding folate, Vitamin D, and n-3 PUFA. Furthermore, antibiotic usage and n-6 PUFA intake have correlated with increased PPD risk. Studies assessing supplement co-exposure were limited. The results of this review are mixed, with some dietary supplements having a positive effect and others having a negative or no association with PPD. This review highlights the limited knowledge regarding the effects of selenium, iodine, probiotics, and antibiotics. Further research is needed to study the combined effects of various supplements on PPD, as mothers often take multiple supplements during pregnancy.
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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 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".