P3‐393: Development of a Brain Health Food Guide for Use in Middle‐Aged and Older Adults
Bibliographic record
Abstract
The Alzheimer’s Association, USA, recently argued that ‘there is sufficiently strong evidence to conclude that a healthy diet and lifelong learning/cognitive training may also reduce the risk of cognitive decline’. While results from most epidemiologic studies support diets which emphasize plant-based foods to maintain cognitive function; there is not consensus on best characteristics across all food groups, especially dietary fats. Consequently there remains a need to derive evidence-based recommendations to describe an optimal diet pattern to support cognitive health. As such, we developed a Brain Health Food Guide (BHFG), which could ultimately be used to support dietary change in middle aged and older adults. A primary consideration in developing the BHFG was to harmonize diet patterns across two RCTs, PREDIMED (Mediterranean-style diet) and ENCORE (DASH diet), which differ markedly in their fat recommendations; both of which demonstrated improved cognitive performance associated with diet change. Relevant data from observational prospective studies exploring a diet-cognition relationship were collated. Conversion factors were developed to enable comparison across studies with different serving size definitions or studies that that expressed serving size as volumes versus those expressed in units of mass. In terms of dietary fat, studies generally supported an intervention that simultaneously targets reductions in SFA consumption while promoting greater contribution of PUFA and MUFA to total fat intake—particularly from plant sources. The evidence supporting targets to increase or decrease total fat intake was equivocal. Translating across all food groups, the BHFG emphasizes vegetables (raw leafy greens, cruciferous vegetables), fruits (berries), nuts, fish, legumes, and low-fat dairy products. It includes whole grains, poultry, and moderate alcohol consumption. It is reduced in red and processed meats, refined grains, commercial sweets, pre-packaged foods, sugared drinks, and high-fat dairy products. A brain healthy eating pattern, based on observational and intervention studies, can be derived from existing literature.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.035 | 0.028 |
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".