High Physical Fitness Is Associated With Better Cognitive Function in Older Adults With Dementia: A Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Aging decreases cognitive and physical fitness (PF). Though evidence links PF to cognitive function, few studies focus on this association in older adults with dementia. The aim of this study is to investigate the association between cognitive function and PF in institutionalized older adults with cognitive impairment. METHODS: This is a cross-sectional study encompassing 75 older adults with suggestive major neurocognitive disorder (76% women, 78.00 ± 8.13 years) residing in nursing homes. Cognition was assessed with Montreal Cognitive Assessment (MoCA), and the eligible participants (MoCA < 17 points) were categorized as having high or low cognition function according to the 50th percentile of the MoCA score. PF was measured with the Senior Fitness Test, and a global physical fitness score (GPF), computed as the average obtained from the six tests of the Senior Fitness Test, was thereafter classified based on the 25th percentile. Linear regression and binary logistic regression were applied. RESULTS: GPF was significantly associated with MoCA (B = 0.078; 95% confidence interval [0.016, 0.139]; R2 = .300). GPF > 25th percentile (odds ratio = 7.8; 95% confidence interval [2.1, 30.4]; p = .003) and years of education (odds ratio = 1.5; 95% confidence interval [1.0, 2.1]; p = .016) were associated with a higher likelihood of having high MoCA, independently of age, medication use, and clinical conditions. CONCLUSION: A higher GPF was associated with better cognitive function in institutionalized older adults with dementia. Significance/Implications: It is crucial to understand the relationships between cognitive decline and PF in older adults with dementia. Once both are correlated, we might suggest that improving fitness may help slow cognitive decline and vice versa, which must be ascertained through longitudinal and experimental studies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".