Impact of cognitive decline on the physical functioning of older adults in Southern Brazil: a cross-sectional study
Bibliographic record
Abstract
Introduction Reduced physical function has been linked to cognitive decline, yet this relationship remains understudied in the older Brazilian population. This study evaluates the impact of cognitive decline on physical functioning in older adults in Southern Brazil. Methods A cross-sectional analysis was conducted with community-dwelling older adults (n = 336), categorized as cognitively unimpaired (CU, n = 181), mild cognitive impairment range (MCI-range, n = 105), or dementia-range (n = 50) based on Montreal Cognitive Assessment cutoff points adapted for the Brazilian population. Physical function was assessed using tests for balance, strength, flexibility, and aerobic endurance. Statistical analyses included one-way ANOVA with post hoc Bonferroni tests. Results Most physical function variables worsened as cognitive impairment increased. The CU group performed significantly better than the MCI- and dementia-range groups in dynamic and static balance, upper-body strength (η2 = 0.09), upper- and lower-body flexibility (η2 = 0.07, η2 = 0.08), and aerobic endurance (η2 = 0.11) (p < 0.05). Conclusion Cognitive status influences physical function in older adults. Identifying physical indicators linked to cognitive decline may improve screening efforts in clinical trials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".