Association between physical activity and cognitive function in a multi-ethnic Asian older adult population
Bibliographic record
Abstract
Physical activity (PA) is regarded as a non-pharmacological preventive strategy against cognitive decline. This study aimed to examine the relationship between PA and cognitive function in cognitively normal older Malaysian adults from a multi-ethnic, urban-dwelling community. Participants completed a questionnaire with questions on demographic details, socioeconomic status, health conditions, and short form of the International Physical Activity Questionnaire (IPAQ). Bivariate analyses and hierarchical linear regression were conducted to examine the relationship between IPAQ and Montreal Cognitive Assessment (MoCA) scores. Among the 382 participants (median age = 66 years), 51.6% were female. Median MoCA score was 24; and IPAQ levels were 28%, 39% and 33% 'Low', 'Moderate' and 'High' respectively. Bivariate analysis showed MoCA scores significantly differed across IPAQ levels (p-value < 0.001). Pairwise comparisons showed significant differences between MoCA scores and 'High' and 'Low' (p-value < 0.001) and 'Moderate' and 'Low' (p-value = 0.001) IPAQ levels. Hierarchical regression of potential confounding factors showed that while lower PA, being older, being Malay and hypertension were initially associated with lower MoCA scores, the association was explained by the greater influence of education and savings. Additional research is required to gain a more comprehensive understanding of these relationships.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".