Cross-sectional and prospective associations between sleep health and multimorbidity in middle to older-aged adults: Results from the Canadian Longitudinal Study on Aging (CLSA)
Bibliographic record
Abstract
OBJECTIVE: Middle-aged to older adults often exhibit the co-existence of poor sleep health and multimorbidity. We examined cross-sectional and prospective associations of pooled index of sleep health with prevalent and incident multimorbidity in the framework of an ongoing cohort study in Canada. METHODS: Data were from approximately 24,000 individuals from the Canadian Longitudinal Study on Aging (CLSA), an ongoing national study of community-dwelling adults aged 45-85 years at baseline. Multimorbidity was defined as two or more chronic conditions out of five major condition categories. Sleep variables included sleep duration, quality, initiation, maintenance, and excessive daytime sleepiness, which were combined into an index using pooled approaches. Weighted logistic regression models were computed for each index with additional age- and sex-stratified analyses. RESULTS: Higher sleep index scores, indicating poorer sleep health, were observed in females and younger age groups (ages 45-54 and 55-64). In cross-sectional analysis, the fully adjusted model showed that a 1-unit increase in pooled scores was significantly associated with 1.48 higher odds (95 % CI = 1.38, 1.58; p < 0.001) of prevalent multimorbidity at baseline. Similarly, the prospective analysis indicated significant changes in incident multimorbidity with pooled index scores in the fully adjusted model (OR = 1.33; 95 % CI = 1.20, 1.48; p < 0.001). CONCLUSION: The pooled sleep index introduced in this study may offer a novel, concise, and comprehensive approach to assessing sleep health among middle-aged and older adults. Those in these age groups experiencing poorer sleep health are at a greater risk of prevalent multimorbidity, as well as of developing multimorbidity over time.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".