Characterising the relationship between mobility, cognition and brain structure in healthy older adults
Bibliographic record
Abstract
With a rapidly growing older population, understanding factors that contribute to healthy ageing is a public health priority – and one such factor is mobility. Using cognitive assessments and magnetic resonance imaging (MRI), this thesis aimed to characterise the associations between mobility and the ageing brain. First, a systematic review and meta-analysis of the literature was conducted to examine the relationship between different domains of cognition (memory, executive function and processing speed) and mobility (gait, balance and lower-extremity function). The reviewed evidence suggested that reduced mobility was correlated with lower cognitive function in older adults, although notable variability was observed between studies. To address the gaps identified by the review, I examined mobility-cognition associations in the Canadian Longitudinal Study on Ageing. Findings supported the hypothesis that poor mobility is associated with poor cognition, and indicated that this relationship is not domain-specific. In addition, I found that controlling for a variety of age-related confounders did not nullify the mobility-cognition association. Less is known about the neural correlates of poor mobility. To examine which brain structures are associated with mobility, voxel-based-morphometry and diffusion tensor imaging outcomes were correlated with mobility measures in a sample of older adults from the Whitehall II cohort. Our findings indicated that older adults with poor mobility tend to have lower grey matter volume and reduced white matter microstructure. Since mobility relates to brain structure and function, it is plausible that improving mobility may lead to cognitive and structural benefits. To test this, I examined the effects of a physical activity intervention in a sub-sample recruited from the Retirement in Action study. In a between-group comparison of change over 6-months, we did not find evidence that physical activity modified cognitive or MRI outcomes. The evidence presented in this thesis supports the hypothesis that mobility is positively associated with cognition and brain structure in healthy older adults. Contrary to predictions, however, we did not observe exercise-induced effects in brain structure or function.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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".