Nutrition Status, Muscle Mass, and Frailty in Older People: A Cross-Sectional Study Conducted in Cyprus
Bibliographic record
Abstract
Objective Aging is a worldwide serious public health problem. Frailty is also becoming an alarming geriatric syndrome. This study was conducted to analyze the relationship of frailty with nutritional and muscle status in individuals aged 65 and older.Method The study was carried out between July 2018 and September 2019 among 347 people aged 65 and older residing in Cyprus. All the data were collected and measured with face-to-face interview method by the researcher which includes demographic information, a retrospective 1-day food consumption record, Edmonton Frailty Scale (EFS), anthropometric measurements, hand grip strength, muscle mass, and walking speed.Results The average age of individuals was 73.12 ± 6.78 years. When sex, education levels, and drug usage were compared with EFS levels, severity of frailty was found to be significantly higher in females, non-educated individuals, and in individuals using 3 or more drugs everyday (p < 0.05). Body mass index (BMI) values of non-frail participants were found significantly higher than mildly, moderately, and severely frail participants (p < 0.05). It was observed that there was a statistically significant and negative correlation between the participants’ EFS scores and muscle mass (p < 0.05). A negative correlation between hand grip strength and EFS scores was also observed. Energy and protein intake was not found to be significantly different in EFS level groups, while calcium intake of participants with mild, moderate, and severe frailty was found to be significantly lower than in those who were not frail or apparently vulnerable (p < 0.05).Conclusions Being female, having low education levels, using more than 3 drugs per day, and having lower muscle mass increases frailty levels. As a consequence, higher education, decreasing the number of drugs used per day, and preserving muscle mass with adequate activity are important cornerstones of decreasing frailty risk.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".