Longitudinal Associations between Cardiorespiratory Fitness and Cognition in Older Adults: A 10-Year Follow-Up from the Generation 100 Study
Bibliographic record
Abstract
INTRODUCTION: Cardiorespiratory fitness (CRF) is associated with better cognition in older adults. However, the long-term associations between CRF levels and cognitive outcomes remain unclear. This study aimed to investigate the association between baseline CRF, changes in CRF (from baseline to year 1 and year 3) and cognition in older adults. METHODS: We included 770 cognitively healthy older adults (367 females; mean age: 72.0 ± 2 years at baseline) from the Generation 100 Study. All participants had complete data on CRF and important confounding factors (age, sex, educational attainment, and self-rated memory at baseline). CRF was measured directly as peak oxygen uptake using ergospirometry. Cognition was assessed using the Montreal Cognitive Assessment (MoCA) 3-, 5-, and 10 years after baseline. Linear mixed models were used to assess the relationship between CRF at baseline, changes in CRF, and MoCA score over time. RESULTS: The mean MoCA score at 3-, 5-, 10-year follow up was 25.3, 25.0, and 24.8, respectively. Higher baseline CRF predicted 0.06 higher MoCA score at year 3 (95% CI: 0.02-0.09) and 0.07 at year 5 (95% CI: 0.03-0.11) but was not associated with MoCA score at year 10 (β: 0.02, 95% CI: -0.02 to 0.06). Neither 1-year nor 3-year changes in CRF were associated with MoCA scores at any later time points. CONCLUSIONS: Changes in CRF over 1 and 3 years were not associated with cognition in healthy older adults. However, higher baseline CRF was linked to better cognition up to 5 years later, suggesting that achieving and maintaining an age-relative high CRF before entering the 8th decade of life might benefit cognitive aging.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".