INTERRELATIONSHIPS AMONG SEDENTARY BEHAVIOUR, SHORT SLEEP, AND THE MEBAOLIC SYNDROME IN ADULTS
Bibliographic record
Abstract
Introduction Sedentary behaviour is gaining attention as an important cardiometabolic risk factor. Studies of sedentary behavior and cardiometabolic risk have not considered sleep duration, although there is evidence that sleep duration may be related to both sedentary behaviour and cardiometabolic risk. Objective The purpose of this study is to determine if sedentary behaviour is related to the metabolic syndrome (MetS) while controlling for sleep duration. Methods This cross-sectional study is based on the 2003–2006 National Health and Nutrition Examination Survey. A sample of 1371 adults over the age of 20 were studied. Average daily sedentary time and sleep duration were determined via 7-day accelerometry. Screen time was determined via questionnaire. The MetS was determined using standard criteria. Analysis of variance was used to examine relationships among sedentary time and screen time with sleep duration. Multiple logistic regression was used to examine associations between total sedentary time, screen time, and sleep duration with the MetS after controlling for several covariates. Results Sedentary time and screen time did not vary across the sleep quartiles (p=0.08 and p=0.87, respectively). Participants in the highest quartile of sedentary time were significantly more likely to have the MetS than participants in the lowest quartile (odds ratio=1.60, 95% CI:1.05–2.45). The odds of the MetS was higher in participants in the highest screen time tertile as compared to the lowest tertile (odds ratio=1.67, 95% CI:1.13–2.48). Sleep duration was not independently related to the MetS. Conclusion Highly sedentary individuals and individuals with a high screen time are more likely to have the MetS.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".