Relationship Between C-Reactive Protein and Atherosclerotic Risk Factors and Oxidative Stress Markers Among Young Persons 10–18 Years Old
Bibliographic record
Abstract
BACKGROUND: This study was undertaken to determine the association of serum C-reactive protein (CRP) with generalized and abdominal obesity, body fat composition, the metabolic syndrome, and oxidative stress markers among young people. METHODS: We conducted a population-based study of 512 young people, aged 10-18 years. We obtained anthropometric and blood pressure measurements. Fasting blood sugar, total cholesterol (TC), HDL-cholesterol, triglycerides, CRP, malondialdehyde (MDA), and conjugated diene (CDE) were quantified. LDL-cholesterol (LDL-C) was calculated for samples with TG < or =4.52 mmol/L RESULTS: Mean triglycerides, waist and hip circumferences, percentage body fat, subcutaneous fat, and systolic blood pressure increased significantly with increasing body mass index (BMI). In contrast, the mean LDL and TC were higher in underweight than normal weight individuals, and then increased significantly from normal to higher BMI categories. Mean HDL cholesterol significantly decreased with increasing BMI. Overall, CRP, MDA, and CDE were significantly correlated with measures of abdominal obesity. Serum CRP, MDA, and CDE significantly increased in the upper quartiles of waist circumference. Study participants with higher CRP concentrations were more likely to have metabolic syndrome and high oxidative stress markers. CONCLUSION: We found a significant positive association between CRP and oxidative stress markers in healthy young people, as well as an increase in these markers in the upper quartiles of waist circumference, but not BMI. Oxidative stress and CRP may interact in the early inflammatory processes of atherosclerosis.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".