Correlation Between Body Mass Index and Frailty on Activities of Daily Living among Elderly in The Nursing Home
Bibliographic record
Abstract
Introduction: High Body Mass Index (BMI) is associated with mortality and morbidity in the elderly. High BMI is also associated with limited physical function. Another issue faced by the elderly is frailty, frailty is associated with decreased exercise capacity, reduced muscle strength, and decreased bone mass leading to adverse health outcomes such as disability, falls, hospitalization and death. Physical frailty is highly prevalent for the elderly who is living in nursing homes. The aim of this study is to determine the association between body mass index and frailty to Activities of Daily Living (ADL) among the elderly in the nursing home. Methods: This study was conducted in 3 nursing homes in South Sulawesi. BMI and frailty were measured. Frailty was assessed by Edmonton Frail Scale (EFS), while activities of daily living was examined by Barthel Index (BI) Results: There were 30 participants, consisting of males 10 (33.3%), and females 20 (66.7%) with a median age of 72 years old, included in this study. The median BMI result was 20.4 (13.3-29.2). The median result of EFS was 5.5 (2-12). The median BI result was 92.5 (45-100). BMI have insignificant correlation with ADL (r = 0.196; p = 0.298), frailty have negative strong correlation with ADL (r = -0.738; p=0.000). Conclusion: There was no significant correlation between BMI and ADL. Otherwise, frailty and ADL have a strong correlation among the elderly in the nursing home.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".