Longitudinal association of dietary habits and the risk of cardiovascular disease among Iranian population between 2001 and 2013: the Isfahan Cohort Study
Bibliographic record
Abstract
There has been a steady rise in the incidence of cardiovascular disease (CVD) in the Iranian population. The aim of this study is to investigate the association between Global Dietary Index (GDI) and CVD risk among the Iranian adult population. This study was conducted based on Isfahan Cohort Study, a longitudinal study that collected data between 2001 and 2013 on 6405 adults. Dietary intakes were assessed by a validated food frequency questionnaire to calculate GDI. All participants were followed every two years by phone call to ask about death, any hospitalization, or cardiovascular events to examine CVD events. The Average age of participants was 50.70 ± 11.63 and the median of GDI score was 1 (IQR: 0.29). A total of 751 CVD events (1.4 incidence rate, per 100 person-year) occurred during 52,704 person-years of follow-up. One-unit GDI increase was associated with a higher risk of MI by 72% (HR: 1.72; 95% CI 1.04-2.84), stroke by 76% (HR: 1.76; 95% CI 1.09-2.85) and CVD by 30% (HR: 1.48; 95% CI 1.02-2.65). In addition, a one-unit GDI increase was associated with a higher risk of coronary heart disease more than 2 times (HR: 2.32; 95% CI 1.50-3.60) and CVD mortality and all-cause mortality over than 3 times [(HR: 3.65; 95% CI 1.90-7.01) and (HR: 3.10; 95% CI 1.90-5.06), respectively]. Higher GDI had a significant relationship with the increased risk of CVD events and all-cause mortality. Further epidemiological studies in other populations are suggested to confirm our findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 | 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".