The association between serum vitamin D, fertility and semen quality: A systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: A number of studies have examined the association between vitamin D, fertility and semen quality, however, findings have been inconclusive. Herein, we systematically reviewed available observational studies to elucidate the overall relationship between vitamin D, fertility and semen quality in adult population. METHODS: PubMed, Cochrane's Library, Science Direct, Scopus, Google Scholar and ISI Web of Science databases were searched until December 2018 for all available studies evaluating the association between vitamin D, fertility and semen quality. The Newcastle-Ottawa Quality Assessment Scale was used to examine the quality of each study. RESULTS: A total of 18 studies out of 1843 met our inclusion criteria and were included in our systematic review and meta-analysis. Serum 25(OH)D3 was significantly higher in fertile subjects compared to infertile ones (WMD -0.63; 95% CI, -1.06 to -0.21; P = 0.003). Furthermore, there was a significant association between serum 25(OH)D, sperm motility (WMD -5.84; 95% CI, -10.29 to -1.39; P = 0.01) and sperm progressive motility (WMD -5.24; 95% CI, -8.71 to -1.76; P = 0.003). CONCLUSION: Our findings add to the existing literature supporting the concept that nutrition, especially vitamin D, plays an important role in men's sexual health. It should be noted that because of significant heterogeneity among the included studies, caution is warranted when interpreting the results. Further well-designed prospective cohort studies and clinical trials are needed for better understanding of the relationship between vitamin D and fertility and its components.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.030 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".