The Relationship between Cardiorespiratory Fitness and Montreal Cognitive Assessment Scores in Older Adults
Bibliographic record
Abstract
BACKGROUND: Relatively little is known regarding the association between objective measures of physical function such as cardiorespiratory fitness (CRF) and cognitive function tests in healthy older adults. OBJECTIVE: To evaluate the relationship between CRF and cognitive function in adults aged 55 and older. METHODS: Between 2008 and 2017, 4,931 men and women underwent a comprehensive preventive physical exam at the Cooper Clinic in Dallas, Texas. CRF was determined by duration of a maximal treadmill exercise test. Cognitive function was evaluated with the Montreal Cognitive Assessment (MoCA). In a multivariate model, adjusted odds ratios with 95% confidence intervals for MoCA scores < 26 (i.e., cognitive impairment) were determined by using CRF as both a continuous and a categorical variable. RESULTS: The mean age of the sample was 61.0 ± 6.0 years; mean maximal MET values were 10.0 ± 2.2. Mean MoCA scores were 26.9 ± 2.2; 23.4% of the sample had MoCA scores indicative of cognitive impairment. The odds ratio for cognitive impairment was 0.93 (0.88-0.97) per 1-MET increment in CRF. When examined as a categorical variable, and using the lowest CRF quintile as the referent, there was a significantly reduced likelihood for cognitive impairment across the remaining ordered CRF categories (p trend = 0.004). CONCLUSION: The association between CRF and MoCA score in older adults suggests that meeting or exceeding public health guidelines for physical activity is likely to increase CRF in low fit individuals, maintain CRF in those with a moderate to high level of CRF, and thereby help to maintain cognitive function in healthy older adults.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".