Association between mid upper arm and calf circumferences and cognitive function in elderly
Bibliographic record
Abstract
Background: Nutritional status has been associated with cognitive function in elderly. Several anthropometric measurement, including mid upper arm circumference and calf circumference are recognized as effective means to assess nutritional status, as they have good correlation with body mass index. This study aimed to identify the association between MUAC, CC and cognitive function in elderly population.Methods: This cross sectional study involved 71 elderly subjects aged more than 60 years old. We recruited subjects from Medan Helvetia district because it has the largest aging population in Medan, North Sumatera, Indonesia. The Cognitif function was assessed using montreal cognitive assessment test Indonesian version (MoCA-INA) and visual cognitive assessment test. To examine the association between MUAC, CC and cognitive function using Kruskal Wallis test and Fisher Exact.Results: There were 42 females and 29 males. The mean age was 68.68±6.35 years. The mean MUAC was 24.3±3.25 cm and CC was 31.5±2.45 cm. There was no association between MUAC and MoCA-INA (p=0.215) and VCAT (p=0.062). There was an association between CC and MoCA-INA (p=0.040) and VCAT (p=0.019).Conclusions: There was an association between calf circumference and cognitive function while mid upper arm circumference was not. Compared to BMI, calf circumference can predict sarcopenia in the elderly. Elderly with functional impairment and impaired mobility may show a decrease in calf circumference. Sarcopenia is often associated with brain atrophy in the elderly.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".