A meta-analysis of prospective studies on the role of physical activity and the prevention of Alzheimer’s disease in older adults
Bibliographic record
Abstract
BACKGROUND: The incidence of Alzheimer's disease is increasing as the global population ages. Given the limited success of pharmaceuticals in preventing this disease, a greater emphasis on non-pharmaceutical approaches is needed. The aim of this study was to quantify the association between Alzheimer's disease and physical activity in older adults over the age of 65 years. METHODS: A meta-analytic approach was used to determine if physical activity reduced the risk of Alzheimer's disease in individuals 65 years or older. Some evidence indicates that physical activity may improve cognitive function in older adults, while other evidence is inconclusive. The purpose of this study was to examine if prevention of Alzheimer's disease is possible if started at a later age. The precise brain changes that occur with the onset of Alzheimer's disease are not fully known, and therefore may still be influenced by preventative measures even in advancing age. Determining if physical activity can inhibit the onset of the disease at any age may motivate individuals to adopt an "it's never too late" mentality on preventing the onset of this debilitating disease. Longitudinal studies of participants who were 65 years or older at baseline were included. A total of 20,326 participants from nine studies were included in this analysis. RESULTS: The fixed effects risk ratio is estimated as 0.61 (95% CI 0.52-0.73) corresponding to a statistically significant overall reduction in risk of Alzheimer's disease in physically active older adults compared to their non-active counterparts. CONCLUSION: Physical activity was associated with a reduced risk of Alzheimer's disease in adults over the age of 65 years. Given the limited treatment options, greater emphasis should be paid to primary prevention through physical activity amongst individuals at high-risk of Alzheimer's disease, such as those with strong genetic and family history.
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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 | 0.026 | 0.052 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.061 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".