Abstract 16843: Waist Measures are an Important Factor Further Specifying Adiposity-Related Cardiometabolic Risk for Children Classified by Body Mass Index
Bibliographic record
Abstract
Background: Body mass index (BMI) is commonly used as an indirect indicator of adiposity in children reflective of its association with cardiometabolic risk. The interaction of waist circumference percentile (WC%) and waist-to-height ratio (WHtR) with BMI may provide further risk specification in children. Methods: Data were analyzed from 5 NHANES surveys from 1999-2008. Two sets of groups were created based on categories of BMI/WC% and BMI/WHtR to assess the interaction of waist measures and BMI percentile (WHO charts) in association with cardiometabolic risk factors, including fasting lipids, glucose and insulin, C-reactive protein (CRP) and blood pressure category. Results: Data were available for 14,802 subjects (age range 5-18.9 years, 50% male, 4,542 fasting blood work). Overweight (BMI≥85%) and obesity (BMI≥95%) were noted for 13% and 27%, respectively. WC% ≥ 90% and WHtR ≥ 0.6 were noted in 16% and 10%, respectively. Both between and within BMI categories, increasing waist measures were significantly associated with increased lipid abnormalities (Figure A), higher insulin and glucose values, increased likelihoods of higher hypertension categories, and higher CRP levels (Figure B). Adjusted multivariable regression models for cardiometabolic risk factors had similar R 2 and c statistic values when waist measure categories were studied independently of or interacting with BMI categories. Interactions remained significant with continuous variables. Conclusions: Waist measures further specify cardiometabolic risk within classifications based on BMI, and should be included in the routine screening and assessment of risk in the pediatric population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".