Differences in long-term impact of traditional risk factors for atherosclerosis on different arterial territories: insights from over 20 years of follow-up in the EPIC-Norfolk prospective population study
Bibliographic record
Abstract
BACKGROUND AND AIM: The relative impact of risk factors for atherosclerosis on cardiovascular disease (CVD) events differs among arterial territories. Most studies investigating these associations comprised CVD patients, had short follow-up or lacked sex- and territory specific analyses. We therefore investigated associations between risk factors for atherosclerosis and territory-specific CVD in a large cohort with ≥20 years follow-up. METHODS: EPIC Norfolk participants without CVD were analysed for the association between first CVD event and three dichotomized risk factors: low-density lipoprotein cholesterol (LDL-C) >3 mmol/L, systolic blood pressure (SBP) >140 mmHg, and smoking, assessed individually and in clusters, with multivariable adjustment. Events included hospitalisation or death due to ischemic heart disease (IHD), ischemic stroke, haemorrhagic stroke, peripheral arterial disease (PAD) or aortic aneurysm (AA). Sex-specific estimates were obtained from interaction terms. RESULTS: In 23,581 participants (56% women, median age 58 (IQR 51-66)) with median follow-up 21.3 years, 26.4% experienced ≥1 CVD event. First CVD event incidence was 1.7 times higher in men. Total CVD was associated with LDL-C (aHR 1.35, 95%CI1.24-1.46), SBP (1.29, 1.22-1.37), and smoking (1.69, 1.56-1.82), with overlapping impact across territories. IHD risk increased with each additional factor (all three: aHR 2.86, 2.36-3.48). SBP was the most important risk factor for ischemic and haemorrhagic stroke (aHR 1.45, 1.29-1.64; 1.34, 1.10-1.64). Smoking was most strongly associated with AA (aHR 3.56, 2.93-4.34), exceeding the impact of LDL-C and SBP combined (aHR 1.78, 1.16-2.71). Associations of LDL-C with total CVD were stronger in men than in women (aHR 1.47, 1.19-1.80 vs 1.20, 1.06-1.35; p=0.018), while SBP showed stronger associations in women than in men for IHD (1.36, 1.24-1.50 vs 1.20, 1.02-1.40; p=0.037) and PAD (1.49, 1.26-1.76 vs 1.12, 0.86-1.47; p=0.008). CONCLUSIONS: Risk factor impact was consistent across arterial territories, but variation in magnitude and sex differences suggest underlying pathophysiological distinctions.
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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 | 0.003 | 0.005 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".