Frailty Severity and Cognitive Impairment Associated with Dietary Diversity in Older Adults in Taiwan
Bibliographic record
Abstract
This study aims to investigate whether frailty severity in conjunction with cognitive function, termed as” cognitive frailty”, is associated with dietary diversity in older adults. This cross-sectional study used the data from the 2014–2016 Nutrition and Health Survey in Taiwan (N = 1115; age ≥ 65 years). Dietary intake was assessed using a 24 h dietary recall and food-frequency questionnaire, and dietary diversity score (DDS; range, 0–6) and food intake frequency were calculated. The presence of frailty phenotypes was determined using the FRAIL scale, which was proposed by the International Association of Nutrition and Aging, and cognitive function was assessed using the Mini–Mental State Examination (MMSE) score. The prevalence of cognitive frailty (FRAIL scale score ≥ 3 and MMSE score ≤ 26) was 4.2%. A higher consumption frequency of dairy products, whole grains, vegetables, fruit, fish and seafood, nuts, tea, and coffee, as well as lower pickled vegetable, was inversely associated with cognitive frailty. Those with prefrailty or frailty and lower DDS demonstrated a higher cognitive impairment risk (adjust odds ratio (OR) = 2.15, 95% confidence interval = 1.21–3.83) than those without frailty and higher DDS. Older adults with cognitive prefrailty or cognitive frailty were associated with lower DDS, and frailty with lower DDS was associated with worsening cognitive function.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".