Non-high-density-lipoprotein cholesterol and cardiovascular risk factors among adolescents with and without impaired fasting glucose
Bibliographic record
Abstract
To evaluate how non-high-density-lipoprotein (non-HDL) is associated with impaired fasting glucose (IFG) and clustered metabolic risk (MR) factors among adolescents, we pooled 2764 adolescents, aged 12-19 years, from the National Health and Nutrition Examination Survey from 3 time periods (1999-2000, 2001-2002, and 2003-2004) who were free of diabetes and had fasted overnight for this analysis. IFG was defined as 100 <or= glucose <or= 125 mg.dL-1. Age- and sex-specific cut-offs were used for 4 MR factors: higher levels of triglycerides, waist circumference, blood pressure, and lower levels of HDL. Clustered MR was defined as having any 2 of the 4 factors. Overall, approximately 11% of adolescents had IFG. The mean level of non-HDL cholesterol was much higher in those with IFG than in those without IFG, with adjustment for certain confounding variables (121.4 vs. 110.1 mg.dL-1; p < 0.05). This difference could still be observed in adolescents with one or more clustered MR factors. However, there were no statistical differences in low-density-lipoprotein (LDL) level. Compared with those who were without IFG and not at high levels of non-HDL - after adjustment for age, sex, race, current smoking, and body mass index - the odds of having clustered MR factors were 1.08 (95% CI, 0.65-1.82) for those with IFG and low non-HDL cholesterol, 3.55 (2.29-5.48) for those without IFG but with high non-HDL cholesterol, and 10.10 (3.67-27.80) for those with both IFG and high non-HDL cholesterol. Moreover, those with IFG and at increased risk of obesity were more likely to have higher levels of non-HDL cholesterol (odds ratio (95% CI): 4.41 (2.28-8.50)), compared with those without IFG and not at increased risk of obesity. In summary, prediabetic adolescents with IFG and high levels of non-HDL cholesterol are more likely to have clustered MR factors. Thus, the levels of non-HDL cholesterol may be an important indicator in monitoring cardiovascular disease risk among adolescents with IFG.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".