Is Neck Circumference a Marker for Cardiovascular Risk in Obese Adolescents?
Bibliographic record
Abstract
Background: Weight excess has become a public health problem worldwide, reaching about 200 million children, of whom 40 to 50 million are obese. Obesity in childhood is associated with increased blood pressure (BP), high triglycerides, low HDL-cholesterol and abnormal glucose metabolism. Visceral fat is a stronger predictor of metabolic dysfunction and cardiovascular risk than total body adiposity. Assessment of neck circumference (NC) is an easy method, which can serve as screening to identify individuals with weight excess. Our study aim was to examine associations between NC with BP values, lipid profile, blood glucose and fasting insulin in obese adolescents and verify the reproducibility of measurements of NC. Methods: 82 adolescents aged 10 to 17 years were included in the study, being 43 (22 boys and 21 girls) with obesity and 39 with normal weight (20 boys and 19 girls). Results: Significant associations were observed between NC and BMI, BP, HDL cholesterol, insulin and HOMA-IR. Disagreement between both observers for NC was observed in 5.2% of the sample, only concerning obese individuals. Conclusion: Our findings strengthen the knowledge about the potential value of NC as a tool for identifying patients at risk for hypertension, insulin resistance, and obesity. However as with the waist circumference it may be flawed in obese individuals.
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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 | 0.002 | 0.006 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".