Modeling the Impact of Sex on How Exercise Is Associated with Cognitive Changes and Death in Older Canadians
Bibliographic record
Abstract
BACKGROUND: Exercise improves cognition and lessens the risk of death in older adults. Cognition and mortality are each also affected by biological sex, which might modify the effect of exercise. We investigated how sex mediates the impact of exercise on mortality and 5-year changes in cognition. METHODS: In the Canadian Study of Health and Aging (n = 8,403, 60.7% women), cognitive states were defined as errors in the Modified Mini-Mental State Examination. Improvement and declines were modeled using a 4-parameter truncated Poisson distribution. RESULTS: Men and women showed similar levels of improvement or stabilization (34.1%, 95% CI = 32.1-35.9 in women and 30.2%, 95% CI = 28.2-32.4 in men). In unadjusted analysis, more men died (34%, 95% CI = 32.3-36.3) than did women (30.3%, 95% CI = 28.4-32.2). Higher education was beneficial for cognitive function in both sexes, but did not impact survival when other factors were considered. The effect of exercise differed by sex: women had a survival advantage compared with men, but men most benefited in cognitive functioning. CONCLUSIONS: Exercise is strongly associated with cognitive improvement and stabilization in men, and with better survival in women. In contrast to conventional approaches, our model allows us to analyze how different risk factors affect cognition to any degree, and simultaneously to assess their impact on survival.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".