P2‐268: Association between dietary patterns and cognitive impairment in the elderly
Bibliographic record
Abstract
Previous studies on western diet and cognitive impairment were inconsistent. Significant differences were observed between the eastern and western diets, this study aimed to assess the relationship between dietary patterns and cognitive impairment in the elderly. This is a cross-sectional study. A total of 566 elders (age≥65) were recruited from a teaching hospital in Taipei, Taiwan from 2011 to 2013. Cognitive impairment was assessed by the Montreal Cognitive Assessment with a score <24 indicates cognitive impairment. Dietary information in the past year was collected based on a semi-quantitative food frequency questionnaire. Principal component analysis and logistic regression model were performed to identify dietary patterns and their association with cognitive impairment. Higher tertiles of the “traditional Chinese” dietary pattern (fermented foods and pickled vegetables) protected against cognitive impairment [T2: adjusted odds ratio (AOR)=0.30–0.34; T3: AOR=0.33–0.39] as compared to the lowest tertile. After stratification by age groups (age<75 and ≥75) or sex, similar protective effects were observed (AOR=0.25–0.40). In addition, higher tertiles of “traditional Chinese” dietary pattern protected against cognitive impairment among APOE e4 non-carriers (T2: AOR=0.36, T3: AOR = 0.38), APOE e4 carriers (T2: AOR=0.05), and supplement users (AOR=0.31 and 0.33). “Traditional Chinese” dietary pattern protected against cognitive impairment 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 | 0.000 | 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 | 0.000 |
| 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".