Relationship Between Frailty And Executive Function By Age And Sex In The Canadian Longitudinal Study Of Aging
Bibliographic record
Abstract
Frailty reflects age-related damage to multiple physiological systems. Executive dysfunction is often a presenting symptom of diseases characterized by cognitive impairment. Worsened cardiovascular health is also associated with worsened executive function. PURPOSE: To test the hypothesis that higher frailty would be associated with executive dysfunction and that cardiovascular function would mediate this relationship. METHODS: Middle-aged and older-aged adults at baseline (n = 29,591 [ 51% female]) and 3-year follow-up (n = 25,488 [12911 females]) from the Canadian Longitudinal Study of Aging were included. Frailty at baseline was determined from a 61-item index, a cumulative cardiovascular score was calculated from 30 cardiovascular health variables (ratio), and participants completed a word-colour Stroop task as a measure of executive function. Multiple linear regressions and mediation analyses (mediator: cardiovascular score) were conducted between frailty, Stroop reaction time and cardiovascular function in groups stratified by both age and sex (middle-aged males [MM], middle-aged females [MF], older-aged males [OM], older-aged females [OF]). RESULTS: Frailty (MM:0.15 ± 0.05, MF:0.16 ± 0.06, OM:0.21 ± 0.06, OF:0.23 ± 0.06) was associated with both cardiovascular health (MM:0.12 ± 0.1, MF:0.11 ± 0.1, OM:0.20 ± 0.1, OF:0.18 ± 0.1; β > 0.037, p < 0.001) and Interference condition reaction time (MM:23.7 ± 7.9 s, MF:23.1 ± 7.3 s, OM:32.9 ± 13.1 s, OF:30.9 ± 12.0 s; β > 2.57, p < 0.001) across all groups when adjusted for covariates. Cardiovascular health was a partial (~10%) mediator between frailty and reaction time across all groups, aside from middle-aged females. CONCLUSIONS: Higher frailty levels are associated with executive dysfunction, which are partially mediated by worse cardiovascular health. Strategies to improve frailty and better cardiovascular health may be useful for combatting the age-related decline in executive function.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".