Modifiable risk factors for sleep apnea: evidence from meta-analysis of traditional observational studies and 2-sample mendelian randomization
Bibliographic record
Abstract
Epidemiologic studies have linked several modifiable factors to the risk of sleep apnea (SA). However, which specific factors affect the risk of SA and the strength of these effects are unclear. We conducted meta-analyses based on cross-sectional, cohort, and case-control studies found in the PubMed, Scopus, and Web of Science databases up to August 1, 2023. Studies that reported 1 of the associations of education level, physical activity, sedentary behavior, smoking status, alcohol consumption, or coffee consumption with SA were included. Two independent investigators assessed the risk of bias using the Newcastle-Ottawa Scale and the Agency for Healthcare Research and Quality scale. Two-sample Mendelian randomization (MR) studies then were conducted to clarify the causality further. A total of 49 studies were included in the meta-analysis (N = 429 809 study participants). Compared with the other categorial groups, lower level of education (odds ratio [OR] = 1.58; 95% CI, 1.28-1.96), higher level of sedentary behavior (OR = 1.22; 95% CI, 1.01-1.47), current smoking status (OR = 1.33; 95% CI, 1.17-1.51), and current alcohol consumption (OR = 1.40; 95% CI, 1.33-1.48) were associated with higher risk of SA. Higher level of physical activity (OR = 0.77; 95% CI, 0.70-0.83) was associated with lower risk of SA. In the MR study, years of educational attainment were associated with a lower risk of SA (OR = 0.83; 95% CI, 0.78-0.88), and smoking initiation was associated with a higher risk of SA (OR = 1.10; 95% CI, 1.05-1.15). Prevention strategies for SA should focus on modifying these risk factors, especially reducing education inequalities and smoking initiation. Trial registration: PROSPERO identifier: CRD42022319988.
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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 | 0.056 | 0.115 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.055 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".