Western dietary pattern increases risk of cardiovascular disease in Iranian adults: a prospective population-based study
Bibliographic record
Abstract
Limited data are available regarding the association of major dietary patterns and risk of cardiovascular disease (CVD) in Middle Eastern countries. We aimed to evaluate the association of major dietary patterns, using factor analysis, with the risk of CVD. Participants without CVD (n = 2284) were recruited from the Tehran Lipid and Glucose Study and were followed for a mean of 4.7 years. Dietary intake of participants was assessed at baseline (2006-2008); biochemical variables were evaluated at baseline and follow-up examination. Multivariate Cox proportional hazard regression models, adjusted for potential confounders, were used to estimate risk of CVD across tertiles of dietary pattern scores. Linear regression models were used to indicate association of dietary pattern scores with changes of CVD risk factors over the study period. Two major dietary patterns, Western and traditional, were identified. During a mean 4.7 ± 1.4 years of follow-up, 57 participants experienced CVD-related events. In the fully adjusted model, we observed an increased risk of CVD-related events in the highest compared to the lowest tertile category of Western dietary pattern score (HR = 2.07, 95% CI = 1.03-4.18, P for trend = 0.01). Traditional dietary pattern was not associated with incidence of CVD or CVD risk factors. A significant association was observed between the Western dietary pattern and changes in serum insulin (β = 5.88, 95% CI = 0.34-11.4). Our findings confirm that the Western dietary pattern, characterized by higher loads of processed meats, salty snacks, sweets, and soft drinks, is a dietary risk factor for CVD 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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".