Association between physical-activity trajectories and cognitive decline in adults 50 years of age or older
Bibliographic record
Abstract
Aims: To investigate the associations of physical-activity trajectories with the level of cognitive performance and its decline in adults 50 years of age or older. Methods: We studied 38729 individuals (63 ± 9 years; 57% women) enrolled in the Survey of Health, Ageing and Retirement in Europe (SHARE). Physical activity was self-reported and cognitive performance was assessed based on immediate recall, verbal fluency, and delayed recall. Physical-activity trajectories were estimated using growth mixture modelling and linear mixed effects models were used to investigate the associations between the trajectories and cognitive performance. Results: The models identified two physical-activity trajectories of physical activity: constantly-high physical activity (N=27634: 71%) and decreasing physical activity (N=11095; 29%). Results showed that participants in the decreasing physical-activity group exhibited a lower level of cognitive performance compared to the high physical-activity group (immediate recall: ß=0.94; 95% confidence interval [CI]=0.92 to 0.95; verbal fluency: ß=0.98; 95% CI=0.97 to 0.98; delayed recall: ß=0.95; 95% CI=0.94 to 0.97). Moreover, compared with participants in the constantly-high physical-activity group, participants in the decreasing physical-activity group showed a steeper decline in all cognitive measures (immediate recall: ß=-0.04; 95% CI=-0.05 to -0.04; verbal fluency: ß=-0.22; 95% CI=-0.24 to -0.21; delayed recall: ß=-0.04; 95% CI=-0.05 to -0.04). Conclusions: Physical-activity trajectories are associated with the level and evolution of cognitive performance in adults over 50 years. Specifically, our findings suggest that a decline in physical activity over multiple years is associated with a lower level and a steeper decline in cognitive performance.
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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 | 0.003 |
| 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 | 0.001 |
| 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".