Is Shift Work Sleep Disorder a Risk Factor for Metabolic Syndrome and Its Components? A Systematic Review of Cross-Sectional Studies
Bibliographic record
Abstract
Shift work sleep disorder is prevalent in night shift workers due to prolonged misalignment of the circadian rhythm. Night shift workers comprise a significant portion of the workforce and it is important to study the potential implications on their health. Studies have shown the association of metabolic syndrome (MetS) and the components, that is, obesity, dyslipidemia, hypertension, and insulin resistance, with shift workers. Nocturnal exposure to bright light can affect various physiological processes including melatonin secretion, which is a regulator in insulin synthesis. A systematic review was conducted to identify studies showing the association between shift work and MetS and/or its components, as well as to review the pathophysiology for further investigations. This review follows the guidelines as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist 2009. One thousand nine hundred ten records were identified from the PubMed database using both keywords and medical subject headings terms. After applying the inclusion/exclusion and eligibility criteria, 18 observational studies were included in the qualitative synthesis. Quality appraisal was conducted by two investigators independently using the Newcastle/Ottawa Scale, and 11 articles were finalized for the review after scoring 60% and above. Each study measured the different components of MetS and/or the presence of MetS. Statistically significant results were reported for the association between shift work and MetS, shift work and obesity, shift work and dyslipidemia, shift work and hypertension, and shift work and insulin resistance. This review identifies a need to emphasize treatment plans for shift workers to manage not only sleep disorders but other chronic diseases such as MetS, obesity, hypertension, dyslipidemia, and insulin resistance.
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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 | 0.055 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".