Motor function and incident dementia: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: cognitive and mobility decline are interrelated processes, whereby mobility decline coincides or precedes the onset of cognitive decline. Objective: to assess whether there is an association between performance on motor function tests and incident dementia. Methods: electronic database, grey literature and hand searching identified studies testing for associations between baseline motor function and incident dementia in older adults. Results: of 2,540 potentially relevant documents, 37 met the final inclusion criteria and were reviewed qualitatively. Three meta-analyses were conducted using data from 10 studies. Three main motor domains-upper limb motor function, parkinsonism and lower limb motor function-emerged as associated with increased risk of incident dementia. Studies including older adults without neurological overt disease found a higher risk of incident dementia associated with poorer performance on composite motor function scores, balance and gait velocity (meta-analysis pooled HR = 1.94, 95% CI: 1.41, 2.65). Mixed results were found across different study samples for upper limb motor function, overall parkinsonism (meta-analysis pooled OR = 3.05, 95% CI: 1.31, 7.08), bradykinesia and rigidity. Studies restricted to older adults with Parkinson's Disease found weak or no association with incident dementia even for motor domains highly associated in less restrictive samples. Tremor was not associated with an increased risk of dementia in any population (meta-analysis pooled HR = 0.80, 95% CI 0.31, 2.03). Conclusion: lower limb motor function was associated with increased risk of developing dementia, while tremor and hand grip strength were not. Our results support future research investigating the inclusion of quantitative motor assessment, specifically gait velocity tests, for clinical dementia risk evaluation.
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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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.040 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".