Sex differences in functioning and disability among adults with cardiometabolic multimorbidity using Canadian longitudinal study on aging data: A cross-sectional study
Bibliographic record
Abstract
Background: Cardiometabolic multimorbidity (CM), two or more of stroke, diabetes, and heart disease is increasing in prevalence and associated with a multiplicative mortality risk. Sex differences exist in disability outcomes for those with stroke, diabetes, and heart disease, and thus are likely for those with CM. Objectives: To assess 1) sex differences in the prevalence of CM, 2) sex differences in disability variables amongst those with CM, and 3) the predicted probabilities of disability among people with and without CM by sex. Methods: A secondary analysis using data from the Canadian Longitudinal Study on Aging (CLSA). The CLSA included a stratified, random sample of approximately 51,000 participants aged 45 to 85 at recruitment. Independent variables include depressive symptoms, pain, high blood pressure, eyesight, limitations with activities of daily living (ADL), and social participation. Results: A weighted population of 13,204,82 participants were included, 659,621 had CM. Males had a higher prevalence of CM than females, accounting for 62% of those with CM. Females with CM had a higher probability than males of reporting high depressive symptoms (females: 29% [95%CI:27%-31%], males: 21% [95%CI:19%-23%]), pain (females: 49% [95%CI:47%-52%], males: 41% [95%CI:39%-43%]), and limitations with ADL (females: 27% [95%CI:25%-29%], males: 11% [95%CI:10%-13%]) Males with CM had a higher probability than females of reporting infrequent social participation (females: 18% [95%CI:16%-20%], males: 23% [95%CI:21%-25%]). Conclusion: This study provides evidence on sex differences in the likelihood of reporting disability variables in individuals with CM. These insights into sex differences can inform targeted interventions and improve patient 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 | 0.004 |
| Science and technology studies | 0.002 | 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".