Association between physical functioning with cognition among community-dwelling older adults: a cross-sectional study
Bibliographic record
Abstract
Objective: Declines in physical and cognitive functioning often co-exist through aging. Gait-related parameters have been related to cognitive function, although it is unclear whether other measures of physical functioning are similarly related to cognition. Here, we analyzed the relationship between physical functioning with cognition in older adults. Methods: In total, 116 participants were included (M age = 69 years, SD = 6; 71% women). We quantified cognitive functioning using the Montreal Cognitive Assessment (MoCA) and executive functioning tasks (Digit Span Forward minus Backward and verbal fluency tests). Physical function measures included gait speed, Short-physical Performance Battery (SPPB), five-times Sit-to-Stand Test, the Timed Up and Go (TUG) test, the Six-minute Walk Test (6MWT), and lower extremity muscle strength. We used multiple linear regression analyses to explore the association between cognitive measures and each measure of physical functioning, adjusting for age, sex, education, and RCT. Results: We observed a positive association between muscle strength and the MoCA (b = 0.84, SE = 0.40, 95%CI 0.05–1.64) after controlling for covariates. Significant associations were also found between the five-times-sit-to-stand test (b = -0.63, SE = 0.26, 95%CI -1.15–-0.12), TUG (b = -1.13, SE = 0.57, 95%CI -2.26–-0.01), 6MWT (b = 0.04, SE = 0.02, 95%CI 0.01–0.07), and lower extremity muscle strength (b = 1.92, SE = 0.93, 95%CI 0.09–3.77) with the FAS verbal fluency test, and between the TUG (b = -0.62, SE = 0.24, 95%CI -1.11–-0.14) with animal naming. Conclusion: In community-dwelling older adults, higher levels of muscle strength, dynamic balance and cardiorespiratory fitness were positively related with global cognition and executive control measures.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".