Sleep duration and quality, physical activity and cardiometabolic multimorbidity: findings from the English Longitudinal study of Ageing
Bibliographic record
Abstract
Objectives We aimed to assess the prospective associations of sleep duration and quality with the risk of cardiometabolic multimorbidity (CMM) and the interplay with physical activity.Design: Sleep duration and quality and physical activity were self-reported using standardized questionnaires. Cardiometabolic multimorbidity was defined as the presence of at least two multiple long-term conditions (hypertension, diabetes, coronary heart disease, stroke, and other cardiovascular diseases) at follow-up. Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated using logistic regression models adjusted for cardiometabolic risk factors including physical activity.Results: We included 3,428 participants [mean (SD) age 63 (9) years, 44.8% male] free of hypertension, coronary heart disease, diabetes, and stroke at baseline. At 15 years follow-up, 206 participants developed CMM. There was an approximate U-shaped trend between sleep duration and CMM risk. Compared to sleep duration of 7-8 hrs/day, the multivariable OR (95% CI) for CMM was 1.39 (1.03-1.90) for sleep duration ≤6 hrs/day and 1.05 (0.55-2.00) for sleep duration ≥ 9 hrs/day. The odds of CMM appeared to decrease with each additional hour of sleep among participants with short sleep duration (≤6 hrs/day), although this association did not reach statistical significance (OR, 0.78, 95% CI: 0.59-1.02). Sleep quality or physical activity was not associated with CMM.Conclusions: Short sleep duration is associated with an increased CMM risk independent of physical activity. The observed trend suggests that increasing sleep duration among short sleepers may help mitigate CMM risk.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".