Frailty, Nutrition, and Quality of Life in Urban-Dwelling Older Adults Facing Vulnerability: Observational Study in Primary Heath Care
Bibliographic record
Abstract
Objective: To analyze the association between vulnerability, nutritional aspects, frailty, and quality of life (QoL) in older adults receiving care from Primary Health Care (PHC) services in an urban area. Methods: This was a cross-sectional study conducted with community-dwelling older adults. The following instruments were used to assess the variables of interest: the Vulnerable Elders Survey (VES-13), Mini Nutritional Assessment (MNA), Edmonton Frailty Scale (EFS), and the Medical Outcomes Study Short Form-36 (SF-36). Statistical procedures included association analyses, Spearman’s correlation, and binary logistic regression to identify predictors of the outcome. Results: A total of 323 individuals participated in the study, of whom 148 (45.8%) were classified as vulnerable according to the VES-13. Vulnerability showed a moderate negative correlation with nutritional status (r = -0.38; p < 0.001). Frailty (EFS) and quality of life (SF-36) showed strong correlations, especially in domains related to physical and functional aspects (r > 0.49; p < 0.050). Binary logistic regression revealed frailty (EFS) as the main predictor of vulnerability (R² = 0.20; p < 0.001; OR = 1.35 [95% CI: 1.24–1.48]), with functional independence (R² = 0.25; p < 0.001; OR = 3.96 [95% CI: 2.74–5.73]) and functional performance (R² = 0.17; p < 0.001; OR = 3.21 [95% CI: 2.21–4.67]) being the domains that most strongly increased the odds of vulnerability. Conclusion: There was a significant association between vulnerability, nutritional status, frailty, and quality of life. More refined analyses highlighted frailty, particularly in its functional domains, as a key predictor of vulnerability among older adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".