Ethnic Differences in Fibrinogen Levels: The Role of Environmental Factors and the beta-Fibrinogen Gene
Bibliographic record
Abstract
Fibrinogen is a cardiovascular risk factor, but little is known about levels in ethnic groups that differ in their cardiovascular risk. Fibrinogen was measured in 479 Black individuals, 459 South Asian Indians, and 453 Whites aged 40-59 years living in south London, England, from March 1994 to July 1996. Genotype was determined at two sites in the promoter of the beta-fibrinogen gene (G-455-->A and C-148-->T). Plasma fibrinogen levels were lower in Blacks than in Whites by 0.22 g/liter (95% confidence interval (CI): 0.08, 0.36) in men and 0.11 g/liter (95% CI: -0.01, 0.23) in women. These differences were not explained by measured environmental variables, including smoking, or by genotypes. The fibrinogen levels of South Asians were not consistently different from those of WHITES: The A-455 and T-148 alleles were less common in Blacks than in either Whites or South ASIANS: In Whites and South Asians, but not in Blacks, there was complete allelic association between the two variants. In Blacks, the T allele rather than the A allele was associated with higher fibrinogen levels. The average fibrinogen-raising effect of the T-148 allele across all ethnic groups was 0.14 g/liter (95% CI: 0.02, 0.26 g/liter) in women and 0.15 g/liter (95% CI: 0.03, 0.27 g/liter) in men. Low fibrinogen levels in Blacks may partly explain their lower risk of ischemic heart disease in the United KINGDOM:
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".