Healthy eating and reduced risk of cognitive decline
Bibliographic record
Abstract
OBJECTIVE: We sought to determine the association of dietary factors and risk of cognitive decline in a population at high risk of cardiovascular disease. METHODS: Baseline dietary intake and measures of the Mini-Mental State Examination were recorded in 27,860 men and women who were enrolled in 2 international parallel trials of the ONTARGET (Ongoing Telmisartan Alone and in Combination with Ramipril Global Endpoint Trial) and TRANSCEND (Telmisartan Randomised Assessment Study in ACE Intolerant Subjects with Cardiovascular Disease) studies. We measured diet quality using the modified Alternative Healthy Eating Index. Cox proportional hazards regression was used to determine the association between diet quality and risk of ≥3-point decline in Mini-Mental State Examination score, and reported as hazard ratio with 95% confidence intervals with adjustment for covariates. RESULTS: During 56 months of follow-up, 4,699 cases of cognitive decline occurred. We observed lower risk of cognitive decline among those in the healthiest dietary quintile of modified Alternative Healthy Eating Index compared with lowest quintile (hazard ratio 0.76, 95% confidence interval 0.66-0.86, Q5 vs Q1). Lower risk of cognitive decline was consistent regardless of baseline cognitive level. CONCLUSION: We found that higher diet quality was associated with a reduced risk of cognitive decline. Improved diet quality represents an important potential target for reducing the global burden of cognitive decline.
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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 | 0.001 |
| 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".