Association Between Sleep Duration and Related Risk Factors with Metabolic Syndrome: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Background: Metabolic syndrome (MetS) is a global health problem that increases the risk of cardiovascular disease, stroke, and all-cause mortality. We aimed to investigate the association between sleep duration and related risk factors with the development of MetS: A systematic review and Meta-analysis of Observational Studies. Methods: We systematically searched PubMed/MEDLINE, Web of Science, EMBASE, Scopus, and ProQuest for observational studies that enrolled adults without MetS at baseline. We investigated the association between sleep duration or insomnia and MetS through adjusted analysis. We pooled association estimates for all independent variables and presented both proportion and absolute risks for MetS. Results: After screening records, 26 observational studies with a total population of 279,571 met our criteria. Our meta-analyses showed male sex (absolute risk increase (ARI): 144 more, 95% CI: 116 to 173 more in 1000 participants), short sleep duration of ≤ 6 hours (ARI: 62 more, 95% CI: 38 to 88 more in 1000 participants), insomnia (ARI: 57 more, 95% CI: 12 to 112 more in 1000 participants), and difficulty maintaining sleep (ARI: 30 more, 95% CI: 1 to 63 more in 1000 participants) may be associated with an increased likelihood of MetS. Regular exercise (absolute risk decrease (ARD): 20 fewer, 95% CI: 3 to 36 fewer in 1000 participants) and vegetable intake (ARD: 57 fewer, 95% CI: 25 to 81 fewer in 1000) may be associated with decreased likelihood of MetS. Conclusions: Adequate sleep, improved sleep patterns, regular exercise, and increased vegetable intake have a substantial impact on MetS prevention.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.037 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".