Exploring the Nexus between Physical and Cognitive Status in Older Adults in South Brazil
Bibliographic record
Abstract
Abstract Background Low‐middle income countries in Latin America, including Brazil, face a higher prevalence of cognitive decline compared to high‐income countries, leading to social‐economic and healthcare implications. Several studies have showed an association between reduced physical function and cognitive decline. However, there remains a gap in the understanding of this relationship within the older Brazilian population. The main objective of this study is to evaluate the physical function of older adults in South Brazil across different cognitive states. Method A cross‐sectional analysis was conducted using baseline data from the “CREM ‐ Center for Aging and Movement Reference: a Controlled Clinical Trial” developed in the Brazilian South Region. A total of 336 community‐dwelling older adults over 60 years of age were categorized into three cognitive states based on established cutoffs points of the Montreal Cognitive Assessment (MoCA): No Cognitive Impairment (NCI), Mild Cognitive Impairment (MCI), and Cognitive Impairment (CI). Timed up and go was used to assess functional mobility; Single‐leg Stance Test to assess static balance; 10‐meter walk test to assess gait; Arm‐curl and 30‐second chair‐stand test, Back Scratch Test and Chair it‐and‐Reach Test, to assess upper and lower‐limb flexibility. The ANOVA was used to determine the main effects of the cognitive level groups (NCI, MCI and CI). A Tukey correction for multiple comparisons was used for the comparisons between groups. Result NCI group exhibited superior functional mobility (p<0.001), balance (p<0.001), gait speed (p = 0.002), muscular endurance (p = 0.002), and flexibility (p = 0.007) compared to those with MCI and CI. All physical assessments modalities were able to differentiate the three groups: NCI was the group with better results and the MCI group showed better results than the CI group. Conclusion This study strengthens the evidence that cognitive status influences physical function in Brazilian older adults. Identifying specific physical indicators associated with cognitive decline may enhance screening efforts in clinical trials. Longitudinal studies are recommended to elucidate the causal relationship between physical function and cognitive abilities.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| 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".