An Evaluation of the Longitudinal, Bidirectional Associations Between Gait Speed and Cognition in Older Women and Men
Bibliographic record
Abstract
BACKGROUND: Few cohort studies have examined longitudinal associations between age-related changes in cognition and physical performance. Further, whether these associations differ for men versus women or can be attributed to differences in physical activity (PA) is unknown. METHODS: Participants were 2,876 initially well-functioning community-dwelling older adults (aged 70-79 years at baseline; 52% female; 39% black) studied over a 9-year period. Usual gait speed, self-reported PA, and two cognitive measures-Digit Symbol Substitution Test (DSST) and Mini-Modified Mental State examination (3MS)-were assessed years 0 (ie, baseline), 4, and 9. RESULTS: Early decline between years 0 and 4 in gait speed predicted later decline between years 4 and 9 in performance on the 3MS (β = 0.10, p = .004) and on the DSST (β = 0.16, p < .001). In contrast, the associations between early decline in cognition and later decline in gait speed were weaker and were non-significant after correcting for multiple comparisons (β = 0.08, p = .019 for 3MS and β = .06, p = .051 for DSST). All associations were similar for women and men and were unaltered when accounting for PA levels. CONCLUSIONS: The results indicate declining gait speed as a precursor to declining cognitive functioning, and suggest a weaker reciprocal process among older women and men.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".