Efficacy of Mediterranean Diet for the primary prevention of autoimmune diseases: A systematic review and meta-analysis featured in the Italian National Guidelines “La Dieta Mediterranea”
Bibliographic record
Abstract
The Mediterranean Diet (MD) has been associated with reduced inflammation and improved immune regulation, suggesting a potential protective role against autoimmune diseases. 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 (HR), or odds ratios (OR), as appropriate. A total of 9 high-quality studies were included. No significant associations were found between high vs. low MD adherence and the incidence of rheumatoid arthritis (RR = 0.99, 95% CI: 0.97-1.01), lupus (HR = 0.97, 95% CI: 0.91-1.03), Crohn's disease (RR = 0.95, 95% CI: 0.84-1.07), or ulcerative colitis (RR = 1.02, 95% CI: 0.97-1.08). A significant inverse association was observed for multiple sclerosis (RR = 0.91, 95% CI: 0.85-0.98) and for Sjögren's syndrome (OR = 0.81, 95% CI: 0.66-0.99). However, the certainty of evidence for all outcomes was rated as low. Promising associations were observed for multiple sclerosis and Sjögren's syndrome, although current evidence does not support a consistent protective effect of the MD across several other autoimmune diseases. Further longitudinal research is needed to confirm these findings and explore underlying mechanisms. Meanwhile, the promotion of MD adherence remains justified within broader public health strategies for chronic disease prevention.
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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 | 0.015 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.028 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".