Dietary patterns during adulthood and cognitive performance in midlife
Bibliographic record
Abstract
Objective To investigate whether dietary patterns (Mediterranean diet [MedDiet], Dietary Approaches to Stop Hypertension [DASH], and A Priori Diet Quality Score [APDQS]) during adulthood are associated with midlife cognitive performance. Methods We studied 2,621 Coronary Artery Risk Development in Young Adults (CARDIA) participants; 45% were black, 57% were female, and mean age was 25 ± 3.5 years at baseline (year 0). Mean diet scores were calculated from diet history at baseline, year 7, and year 20 (mean age 25, 32, and 45 years, respectively). Cognitive function was assessed at years 25 and 30 (mean age 50 and 55 years, respectively). Linear models were used to examine association between tertiles of diet score and change in composite cognitive function and cognitive z scores (verbal memory [Rey Auditory Verbal Learning Test], processing speed [Digit Symbol Substitution Test], and executive function [Stroop Interference test]) and the Montreal Cognitive Assessment (MoCA) at year 30. Results DASH was not associated with change in cognitive performance. Higher MedDiet and APDQS scores were associated with less decline in cognitive function (MedDiet: low −0.04, middle 0.03, high 0.03, p = 0.03; APDQS: low −0.04, middle −0.00, high 0.06, p < 0.01) and Stroop Interference (MedDiet: low 0.09, middle −0.06, high −0.03; APDQS: low 0.10, middle 0.01, high −0.09, both p < 0.01). Odds ratios (95% confidence interval) for poor global cognitive function (≥1 SD below mean MoCA score) comparing extreme tertiles of diet scores were 0.54 (0.39–0.74) for MedDiet, 0.48 (0.33–0.69) for APDQS, and 0.89 (0.68–1.17) for DASH. Conclusion Greater adherence to MedDiet and APDQS dietary patterns during adulthood was associated with better midlife cognitive performance. Additional studies are needed to define the combination of foods and nutrients for optimal brain health across the life course.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".