Lower Physical Activity Modifies the Association between Perceived Fatigability and Executive Function but not Memory: The Study of Muscle, Mobility and Aging (SOMMA)
Bibliographic record
Abstract
ABSTRACT OBJECTIVE Emerging evidence shows that perceived fatigability—the quantification of vulnerability to fatigue in relation to specific intensity and duration of activities—may be associated with cognitive function. We sought to quantify associations with multiple domains of cognitive function and the role of physical activity (PA). METHODS SOMMA participants completed the Pittsburgh Fatigability Scale (PFS) Physical and Mental subscales (each range 0–50; higher scores=greater fatigability) and three cognitive function assessments [Digit Symbol Substitution Test (DSST), executive function; Montreal Cognitive Assessment (MoCA), general function; and California Verbal Learning Test (CVLT), memory]. Linear regression quantified associations cross-sectionally between each PFS subscale and cognitive assessment scores adjusting for covariates. Effect modification by volume and intensity of accelerometer-measured PA was assessed. RESULTS In 873 participants (59.2% women; age 76.3±5.0; 85% White), mean PFS Physical, Mental, and DSST scores were 15.8±8.7, 7.7±7.8, and 55.4±13.7. After adjustments, for each 4-point higher PFS Physical and 3-point higher PFS Mental, participants had nearly one fewer correct DSST items [β coefficient and 95% confidence interval for PFS Physical: -0.69 (-1.09, - 0.29); PFS Mental: -0.64 (-0.97, -0.30)]. Volume and intensity of PA modified the association of PFS Mental and DSST ( P interactions <0.01). All associations were strongest in those with the lowest volume and intensity of PA. PFS was not associated with MoCA or CVLT. DISCUSSION Greater perceived fatigability may be associated with poorer executive function, but not memory. Individuals with greater perceived fatigability, particularly those less active, might benefit from interventions that reduce fatigability and may beneficially influence cognitive 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".