Racial and Ethnic Differences in the Association Between Classical Cardiovascular Risk Factors and Common Carotid Intima‐Media Thickness: An Individual Participant Data Meta‐Analysis
Bibliographic record
Abstract
Background The major risk factors for atherosclerotic cardiovascular disease differ by race or ethnicity but have largely been defined using populations of European ancestry. Despite the rising prevalence of cardiovascular disease in Africa there are few related data from African populations. Therefore, we compared the association of established cardiovascular risk factors with carotid-intima media thickness (CIMT), a subclinical marker of atherosclerosis, between African, African American, Asian, European, and Hispanic populations. Methods and Results Cross-sectional analyses of 34 025 men and women drawn from 15 cohorts in Africa, Asia, Europe, and North America were undertaken. Classical cardiovascular risk factors were assessed and CIMT measured using B-mode ultrasound. Ethnic differences in the association of established cardiovascular risk factors with CIMT were determined using a 2-stage individual participant data meta-analysis with beta coefficients expressed as a percentage using the White population as the reference group. CIMT adjusted for risk factors was the greatest among African American populations followed by Asian, European, and Hispanic populations with African populations having the lowest mean CIMT. In all racial or ethnic groups, men had higher CIMT levels compared with women. Age, sex, body mass index, and systolic blood pressure had a significant positive association with CIMT in all races and ethnicities at varying magnitudes. When compared with European populations, the association of age, sex, and systolic blood pressure with CIMT was weaker in all races and ethnicities. Smoking (beta coefficient, 0.39; 95% CI, 0.09-0.70), body mass index (beta coefficient, 0.05; 95% CI, 0.01-0.08) and glucose (beta coefficient, 0.13; 95% CI, 0.06-0.19) had the strongest positive association with CIMT in the Asian population when compared with all other racial and ethnic groups. High-density lipoprotein-cholesterol had significant protective effects in African American (beta coefficient, -0.31; 95% CI, -0.42 to -0.21) and African (beta coefficient, -0.26; 95% CI, -0.31 to -0.19) populations only. Conclusions The strength of association between established cardiovascular risk factors and CIMT differed across the racial or ethnic groups and may be due to lifestyle risk factors and genetics. These differences have implications for race- ethnicity-specific primary prevention strategies and also give insights into the differential contribution of risk factors to the pathogenesis of cardiovascular disease. The greatest burden of subclinical atherosclerosis in African American individuals warrants further investigations.
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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 | 0.017 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.045 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".