The Association Between Vitamin D and Premenstrual Syndrome: A Systematic Review and Meta-Analysis of Current Literature
Bibliographic record
Abstract
A number of studies have assessed the association between vitamin D and premenstrual syndrome (PMS) in different populations, but the findings have been inconclusive. Herein, we systematically reviewed available observational and interventional evidence to elucidate the overall relationship between vitamin D and PMS. PubMed, Cochrane Library, ScienceDirect, Scopus, Google Scholar, and ISI Web of Science databases were searched for all available articles until September 2018. The Newcastle-Ottawa quality assessment scale and Jadad scale were used to assess the quality of the observational and interventional studies, respectively. A total of 16 studies out of 196 met our inclusion criteria and were included in the final analysis. Although no significant association between serum 25(OH)D and PMS (weighted mean difference (WMD) = 3.35; 95% confidence interval, −7.80 to 1.11; p = 0.14) was indicated in observational studies, vitamin D supplementation was effective in ameliorating PMS symptoms based upon findings from interventional studies. These results add to the existing literature supporting the fact that nutrition, especially vitamin D, plays an important role in women’s health. Additional well-designed clinical trials should be considered in future research to develop firm conclusions on the efficacy of vitamin D on PMS. KEY TEACHING POINTS5–8% of women experience severe PMS.Nutrition especially vitamin D plays an important role in the women's health.Vitamin D could exert significant clinical effects on PMS symptoms.This is a systematic review and meta-analysis in this regard.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".