Multidimensional Sleep and Cardiometabolic Risk Factors for Type 2 Diabetes: Examining Self-Report and Objective Dimensions of Sleep
Bibliographic record
Abstract
PURPOSE: The purpose of the study was to determine the association between objective and self-report measures of sleep and cardiometabolic risk factors for type 2 diabetes. METHODS: This study examines data on Australian adults, collected as part of the Child Health CheckPoint study. Sleep was examined in terms of actigraphy-derived sleep duration, timing, efficiency and variability; and self-report trouble sleeping. Cardiometabolic risk factors for type 2 diabetes were examined in terms of body mass index and biomarkers of inflammation and dyslipidemia. Generalized estimating equations, adjusted for geographic clustering, were used to determine the association between measures of sleep and cardiometabolic risk factors. RESULTS: Complete case analysis was conducted for 1017 parents (87% mothers). Both objective and self-report measures of sleep were significantly but weakly associated with cardiometabolic risk factors. CONCLUSION: Both objective and self-report measures of sleep are significantly associated with cardiometabolic risk factors for type 2 diabetes. Self-report troubled sleep is associated with poorer cardiometabolic health, independent of actigraphy-derived sleep parameters.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".