Mediterranean diet and prime diet quality score are associated with reduced risk of premature coronary artery disease in Iran: a multi-centric case-control study
Bibliographic record
Abstract
The Mediterranean diet (Med-Diet) is widely recognized for its protective effect in cardiovascular diseases (CVDs), less is known about the associations between health and adherence to the Prime Diet Quality Score (PDQS). This study investigates the relationship between adherence to the Med-Diet and PDQS with the risk of premature coronary artery disease (PCAD) in an Iranian population. A total of 3287 participants were included in this multicenter case-control study across various ethnic groups in Iran, categorized into PCAD cases (n = 2106) and controls (n = 1181). PCAD cases were defined as individuals with at least one coronary artery exhibiting ≥ 75% stenosis or a left main coronary artery with ≥ 50% stenosis, while controls had normal coronary arteries. Dietary intake was assessed using a semi-quantitative food frequency questionnaire (FFQ), previously validated for accuracy in the Iranian population Adherence to the Med-Diet was assessed using a standardized scoring system, awarding one point for higher consumption of beneficial food groups (such as vegetables, whole grains, legumes, fish, nuts, and a high monounsaturated-to-saturated fat ratio) and one point for lower consumption of less favorable foods (such as red and processed meats). The total score ranged from 0 to 9, with higher scores indicating greater adherence to the Med-Diet. The PDQS, a dietary quality index, evaluated adherence across 14 healthy and 7 unhealthy food groups, with higher scores reflecting better diet quality. Logistic regression models were employed to examine the association between dietary scores and PCAD risk. Participants with higher adherence to both the Med-Diet and PDQS had significantly lower odds of PCAD (OR = 0.30, 95% CI: 0.22, 0.40; P for trend < 0.001 for PDQS), with a stronger association observed for the Med-Diet (OR = 0.08, 95% CI: 0.06, 0.10; P for trend < 0.001). Additionally, higher adherence to the Med-Diet (OR = 0.04, 95% CI 0.03, 0.05) and PDQS (OR = 0.21, 95% CI: 0.17, 0.26) was inversely associated with PCAD severity in the fully adjusted model. This study showed a protective association of the Med-Diet and PDQS with reduced risk of PCAD in the Iranian population.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".