Arterial stiffness and age moderate the association between physical activity and global cognition in older adults
Bibliographic record
Abstract
BACKGROUND: Evidence supports that time spent on physical activity has beneficial effects on cognition in older adults. Nevertheless, whether these beneficial effects are still present at the intersection of different levels of arterial stiffness and age is uncertain. METHODS: One hundred and ten healthy older adults aged 60-75 years were examined for arterial stiffness [carotid-femoral pulse wave velocity (cf-PWV)], global cognition (composite score of Montreal Cognitive Assessment, and Mini-Mental State Examination), and self-reported physical activity (PACED diary). Using PROCESS macro for SPSS, we evaluated if cf-PWV (moderator 1), and age (moderator 2) moderate the relationship between physical activity (X) and global cognition (Y). The threshold for high stiffness was set at 8.5 m/s based on previous studies that reported this cut-off as more appropriate for classifying cerebrovascular risk groups. RESULTS: Physical activity had a positive effect on cognition in young-elderly adults (<68.5 years) with a cf-PWV of at least 8.5 m/s (β = 0.48, SE = 0.193, P = 0.014, 95% CI = 0.100--0.868) and in elderly adults (≥68.5 years) with a cf-PWV of less than 8.5 m/s (β = 0.56, SE = 0.230, P = 0.017, 95% CI = 0.104-1.018). This was not the case in elderly adults with a cf-PWV of at least 8.5 m/s (β = 0.00, SE = 0.193, P = 0.998, 95% CI = -0.362 to 361), or in young-elderly adults with a cf-PWV of less than 8.5 m/s (β = 0.16, SE = 0.247, P = 0.501, 95% CI = -0.326 to 656). CONCLUSION: The interaction between arterial stiffness and age moderated the effect of physical activity on global cognition. Time spent on physical activity alone might not be sufficient to achieve cognitive benefit over a specific threshold of arterial stiffness and age.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".