Associations of the MIND Diet with Cardiometabolic Diseases and Their Risk Factors: A Systematic Review
Bibliographic record
Abstract
Purpose: Recent studies have expanded the scope of research on the Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet beyond its impact on cognitive performance. These investigations have specifically explored its potential to provide protection against cardiometabolic diseases and associated risk factors, including obesity and dyslipidemia. Methods: We systematically summarized and evaluated all existing observational and trial evidence for the MIND diet in relation to cardiometabolic diseases and their risk factors in adults. PubMed, Embase, CINAHL and Cochrane Library databases were systematically searched to extract original studies on humans published until September 2023, without date restrictions. A total of 491 studies were initially retrieved, out of which 23 met the eligibility criteria and were included in the final review. Duplicated and irrelevant studies were screened out by five independent reviewers using the Rayyan platform. Quality assessment was ascertained using the Newcastle-Ottawa scale for observational studies and the Cochrane risk-of-bias tool (RoB 2) for randomized trials. Results: Across the different study designs, the MIND diet was generally associated with an improvement in anthropometric measures and other cardiometabolic outcomes, such as blood pressure, glycemic control, lipid profile, inflammation and stroke. The effects of the MIND eating pattern on some cardiovascular diseases are less conclusive. Conclusion: The findings of this systematic review support the recommendation of the MIND diet as a strategy to reduce cardiometabolic risk in adults. Further well-designed and long-term studies are warranted.
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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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".