Associations between self-reported sleep duration, all-cause and cardiovascular disease mortality in employed individuals: a systematic review and meta-analysis
Bibliographic record
Abstract
Objective: Sleeping less or more than the 7-8 h has been associated with mortality in the general population, which encompasses diversity in employment status, age and community settings. Since sleep patterns of employed individuals may differ to those of their unemployed counterparts, the nature of their sleep-mortality relationship may vary. We therefore investigated the association between self-reported sleep duration and all-cause mortality (ACM) or cardiovascular disease mortality (CVDM) in employed individuals. \n \nData sources: Based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses, searches between January 1990 and May 2020 were conducted in PubMed, Web of Science and Scopus. Inclusion/exclusion criteria: Included were prospective cohort studies of 18–64-year-old disease-free employed persons with sleep duration measured at baseline, and cause of death recorded prospectively as the outcome. Gray literature, case-control or intervention design studies were excluded. \n \nData Extraction: Characteristics of the studies, participants, and study outcomes were extracted. The quality and risk of bias were assessed using the Newcastle-Ottawa Scale. \n \nData synthesis: The pooled relative risks (RR) with 95% confidence intervals (CI) were obtained with a random-effects model and results presented as forest plots. Heterogeneity and sensitivity analysis were assessed. \n \nResults: Shorter sleep duration (less than or equal to 6 h) was associated with a higher risk for (ACM) (RR: 1.16, 95% CI: 1.11 -1.22) and CVDM (RR: 1.26, 95% CI: 1.12 -1.41) compared to 7-8 h of sleep, with no significant heterogeneity. The association between longer sleep (greater than or equal to 8 h) and ACM (RR: 1.18, 95% CI:1.12 -1.23, P < 0.001) needs to be interpreted cautiously owing to high heterogeneity \n(I2 ¼ 86.0%, P < 0.001). \n \nConclusion: Interventions and education programs targeting sleep health in the workplace may be warranted, based on our findings that employed individuals who report shorter sleep appear to have a higher risk for ACM and CVDM.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.032 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".