Global cognition predicts the incidence of poor physical performance among older adults: A cross‐national study
Bibliographic record
Abstract
AIM: The relationship between physical performance and cognition is well established. However, findings on the relationship between global cognition and the incidence of functional disability has been inconsistent. Using data from the International Mobility in Aging Study, we investigated the relationship between baseline cognitive function and the incidence of poor physical performance 2 years later. METHODS: A total of 1071 community-dwelling participants (aged 64-75 years) from four sites in Canada and Latin America, with a Short Physical Performance Battery score ≥9 at baseline (good performance) were included. We carried out two sets of analyses, measuring cognition with either the Leganés Cognitive Test or the Montreal Cognitive Assessment. We used three logistic regression models, controlling for either no confounders, sociodemographic confounders or sociodemographic and health confounders. The full model was also stratified by site. A score <9 on the Short Physical Performance Battery indicated poor physical performance. RESULTS: In the fully adjusted model, each 1-point increase in the baseline Leganés Cognitive Test score (range 0-32) was associated with a 10% decrease in the odds of incidence of poor physical performance at the 2-year follow-up (P = 0.019). Likewise, each 1-point increase in the baseline Montreal Cognitive Assessment score (range 0-30) was associated with a 16% decrease in the odds of developing poor physical performance (P = 0.005). When stratified by site, the results were significant at the Latin American sites (P = 0.02), but not at the Canadian sites (P = 0.08). CONCLUSIONS: Poor baseline cognition is associated with the incidence of poor physical performance in community-dwelling older adults. To prevent physical disability, interventions addressing both cognitive and physical performance are required. Geriatr Gerontol Int 2020; ••: ••-••.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".