Association between exercise habits in adolescence and old age and the risk of mild cognitive impairment: the Bunkyo health study
Bibliographic record
Abstract
Background: Exercise in adolescence and old age improves cognitive function in older adults, but the combined effect of exercise habits in both periods is controversial. This study aimed to clarify the relationship between exercise habits in adolescence and old age and mild cognitive impairment (MCI) and to compare regional brain volumes and blood biochemical markers associated with cognitive function in older adults. Methods: Baseline data of 1615 participants aged 65-84 years from the Bunkyo Health Study were analyzed. MCI was diagnosed using the Japanese version of the Montreal Cognitive Assessment. Participants were divided into four groups based on their exercise habits in adolescence (13-18 years) and old age: no exercise in either period (None-None), exercise in adolescence only (Active-None), exercise in old age only (None-Active), and exercise in both periods (Active-Active). Logistic regression models estimated the odds ratios (ORs) of MCI prevalence. Regional brain volumes, such as the prefrontal cortex, temporal lobe, parietal cortex, and hippocampus, and blood biochemical markers, such as BDNF, IGF-1, and homocysteine, were compared between groups. Results: The OR for MCI was significantly lower in the Active-Active group than in the None-None group (OR, 0.62; 95% CI, 0.41-0.94). However, there were no significant differences in regional brain volumes and blood biochemical markers between the Active-Active and None-None groups. Conclusions: Older adults with exercise habits in both adolescence and old age have a lower risk of MCI. However, specific regional brain volumes and biochemical markers may not be associated with differences in cognitive function in 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 | 0.001 |
| 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 | 0.001 |
| 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".