Efficacy of Mediterranean diet for the prevention of neurological diseases: A systematic review and meta-analysis featured in the Italian National Guidelines “La Dieta Mediterranea”
Bibliographic record
Abstract
BACKGROUND: Neurological diseases, including Alzheimer's disease, depression, and Parkinson's disease, pose a growing public health challenge. Dietary patterns, particularly the Mediterranean diet (MD), have been proposed as modifiable factors for prevention. The aim of this systematic review and meta-analysis was to evaluate the association between adherence to the MD and the risk or progression of neurological conditions. METHODS: This review was conducted in accordance with PRISMA 2020 and MOOSE guidelines. A comprehensive search of PubMed/MEDLINE, Scopus, Embase, and Cochrane Library was performed up to February 28, 2024. Study quality was assessed using the Newcastle-Ottawa Scale, and the certainty of evidence was evaluated with the NUTRIGRADE approach. Pooled effect sizes were computed using a random-effects model and expressed as risk ratios (RR), hazard ratios, or odds ratios, as appropriate. RESULTS: Forty-five studies involving over 730 000 participants were included. Higher MD adherence was associated with reduced risk or prevalence of Alzheimer's disease (odds ratios = 0.92), mild cognitive impairment (RR = 0.93), depression (RR = 0.96), and Parkinson's disease (RR = 0.90), with moderate certainty of evidence. Limited evidence suggested reduced anxiety and lower mortality among patients with Alzheimer's disease. No significant associations were observed for dementia prevalence or progression from mild cognitive impairment to dementia. CONCLUSIONS: Greater adherence to the MD is consistently associated with a lower risk of several neurological and mental health conditions. These findings support the promotion of MD-based dietary patterns in clinical and public health strategies to prevent cognitive decline and enhance healthy aging.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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".