Challenging the Wine Component in Mediterranean Diet Scores: Cognitive Outcomes in Portuguese Adults at High Risk of Dementia
Bibliographic record
Abstract
Introduction: The Mediterranean diet (MD) has been linked to better cognition, but evidence in older adults at high dementia risk is limited. Moreover, the traditional Mediterranean Diet Adherence Screener (MEDAS) counts daily wine consumption as a beneficial component, which may distort genuine diet–cognition relationships. Objective: Evaluate whether MD adherence, as measured with the original MEDAS (MEDAS-O) versus a version that reverses the wine item (MEDAS-R), is associated with cognitive function in Portuguese adults aged 55–85 years at increased dementia risk. Methodology: The sample comprised 75 participants from the NUTRIMIND randomised controlled trial (mean age 70.5 ± 7.0 years). MD adherence was evaluated using the original version of MEDAS (MEDAS-O) and an adapted version with a reverse score in the wine question (MEDAS-R). Cognitive function was assessed via the Montreal Cognitive Assessment (MoCA), Addenbrooke’s Cognitive Examination Revised (ACE-R) and Mini-Mental State Examination (MMSE). Statistical analysis was performed using Analysis of Covariance (ANCOVA) models adjusted for age, sex, BMI, education, and physical activity. Results: MEDAS-R was positively associated with better MMSE performance (p = 0.043) and showed a borderline association with the MoCA (p = 0.051), but not with the ACE-R score (p = 0.356). No association was found between MEDAS-O and cognitive function. Better cognitive scores were more frequently observed among participants with higher education (p < 0.001). Conclusions: Reversing the wine item changes how MEDAS relates to cognitive function. These findings support re-evaluating how wine is scored in MD adherence measures.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".