Challenging the relationship of grip strength with cognitive status in older adults
Bibliographic record
Abstract
OBJECTIVE: Grip strength is a widely used motor assessment in ageing research and has repeatedly been shown to be associated with cognition. It has been proposed that grip strength could enhance cognitive screening in experimental or clinical research, but this study uses multiple data-driven approaches to caution against this interpretation. Furthermore, we introduce an alternative motor assessment, comparable to grip dynamometry, but has a more robust relationship with cognition among older adults. DESIGN: Associations between grip strength and cognition (measured with the Montreal Cognitive Assessment) were analysed cross sectionally using multivariate regression in two datasets: (1) The Irish LongituDinal Study on Ageing (TILDA; N = 5,980, community-dwelling adults ages 49-80) and (2) an experimental dataset (N = 250, community-dwelling adults aged 39-98). Additional statistical simulations on TILDA tested how ceiling effects or skewness in these variables influenced these associations for quality control. RESULTS: Grip strength was significantly but weakly associated with cognition, consistent with previous studies. Simulations revealed this was not due to skewness/ceiling effects. Conversely, a new alternative motor assessment (functional reaching [FR]) had a stronger, more robust and more sensitive relationship with cognition compared to grip strength. CONCLUSIONS: Grip strength should be cautiously interpreted as being associated with cognition. However, FR may have a stronger and clinically useful relationship with cognition.
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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 | 0.021 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".