The association between Vitamin D serum level and sleep quality among pregnant women in Asia
Bibliographic record
Abstract
Background and purpose: Studies have investigated that Vitamin D serum level is associated with sleep quality and circadian rhythms in pregnant women in Asia, but the results remained controversial. This systematic review is conducted to explore the association between Vitamin D serum level and sleep quality among pregnant women population in Asia. Methods: We conducted systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Relevant studies that discussed the association between Vitamin D serum level and sleep quality was retrieved from Pubmed, EBSCO, and Proquest. The outcome variable was sleep-quality which measured with Pittsburg Sleep Quality Index (PSQI) questionnaires and the independent variable was the serum 25(OH)D levels. A total 2,285 articles were excluded, leaving 3 final articles to be analyzed. The risk of bias was assessed with the New-Castle Ottawa Quality Assessment Scale (NOS). Results: Three studies included in this review with a total of 1,359 pregnant women in Asia, ranging from 18 to 68 years old. All three studies were controlled for covariates. Out of three studies, two studies showed a significant result of the association between Vitamin D serum level with sleep quality with a p-value <0,05. Causal reasons remained unexplained considering the studies were completed in cross-sectional and cohort design. Conclusion: This study gives an overview of the role of Vitamin D in the sleep quality of pregnant women in Asia. Future research should focus on conducting more comprehensive studies with stringent criteria to further explore this association in diverse Asian populations
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".