Cardiometabolic Multimorbidity and Activity Limitation in Canada: A Cross-Sectional Study of Adults Using the Canadian Longitudinal Study of Aging (CLSA) Data
Bibliographic record
Abstract
Abstract Background: Cardiometabolic multimorbidity (CM) is the diagnosis of at least two of: diabetes, stroke, or heart disease. CM is a common pattern of multimorbidity, however, the association between CM and activity limitation remains unknown. The objectives of this study were to 1) estimate the prevalence of activity limitations among Canadians with CM; and 2) quantify the association between CM and activity limitations.Methods: Using data from the Canadian Longitudinal Study on Aging (CLSA), we estimated the prevalence of CM in Canadians aged 45 to 85 (n=51,022). Multinomial logistic regression was used to quantify the association between CM and activity limitation, evaluated using the Older American Resources and Services (OARS) scale.Results: The prevalence of people living with CM and reporting any activity limitation was 27.4%, with the greatest proportion (47.9%) observed in participants living with all three cardiometabolic conditions. The multinomial odds ratio (or relative risk ratio (RRR)) of activity limitation was greatest amongst participants with all three CM conditions (any limitation: RRR = 11.229, 95% CI = 5.803 to 21.726). Of the two disease combinations, those that included stroke had the greatest odds of activity limitation (stroke and diabetes: RRR = 6.546, 95% CI = 4.436 – 9.661; stroke and myocardial infarction: RRR = 7.029, 95% CI = 4.168 – 11.853). Conclusion: Activity limitation is common amongst Canadians living with CM, and those with CM have an increased odds of reporting activity limitation relative to those with no CM conditions. The odds increase in dose-response relationship as one accumulates more CM conditions.
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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 | 0.001 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".