Impaired Sleep, Multimorbidity, and Self-Rated Health among Canadians: Findings from a Nationally representative survey
Bibliographic record
Abstract
Background: Self-rated health (SRH) is a globally recognized measure of health status. Both impaired sleep (IS) and the presence of multimorbidity are related to poorer SRH, but the precise nature of these associations remains unclear. This study explored the association between IS, multimorbidity, and SRH among Canadian adults. Method: We used 2017-18 Canadian Community Health Survey (CCHS) data for this study. The main variable of interest, self-rated health (SRH), measured participants’ health on a 5-point Likert scale, later categorized as good/very good/excellent or fair/poor. The primary predictor, IS, was derived from two variables and categorized into four groups: no sleep issues; fewer sleeping hours (<7 hours) only; trouble sleeping only; and fewer hours & trouble sleeping. Multimorbidity was present (yes/no) if a participant indicated being diagnosed with two or more chronic conditions. Results: Just over one in ten Canadians reported fair/poor SRH and approximately one-quarter had multimorbidity or experienced few sleep hours in combination with trouble sleeping. The adjusted model indicated greater odds of fair/poor SRH associated with the 40-64years age group, male sex, and lower SES. It also suggested the presence of multimorbidity (AOR: 4.63, 95% CI: 4.06-5.28) and a combination of fewer sleep hours and troubled sleep (AOR: 4.05, 95% CI: 2.86-5.74) is responsible for poor SRH. Forty-four percent of the total effect of IS on SRH was mediated by multimorbidity. Conclusion: This unique finding highlights the mediating role of multimorbidity, emphasizing the importance of addressing it alongside sleep issues for optimal health outcomes.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".