Abstract P201: Cardiovascular Risk Factor Patterns And Their Associations With Total And Abdominal Obesity In Children Referred To A Cardiology Clinic
Bibliographic record
Abstract
Background: Excess adipose tissue is associated with abnormal lipids, glucose, blood pressure, and inflammatory factors. In children, body mass index percentiles (BMI%) are commonly used to define adiposity. Although waist circumference percentiles (WC%) have not been universally accepted, they may better reflect visceral fat. The objective of this study was to determine the relationship between BMI% and WC% in identifying risk factor patterns in children at risk for developing cardiovascular disease. Methods: Children (8-19y free of major disorders and medications) with obesity, hypertension, lipid disorders, and/or a family history of premature cardiovascular disease (< 55 years in male and <65 years in female first-degree relatives) were recruited from the Preventive Cardiology clinic at Boston Children’s Hospital (n=150). Lifestyle (physical activity, screen time, tobacco exposure), anthropomorphic (height, weight, WC) and blood pressure (SBP, DBP) measures were made, as well as fasting lipids (total cholesterol, HDL, triglycerides (TG), LDL, VLDL) and inflammatory markers (hs-CRP, ICAM-1, P-selectin, and TNFαR2) from a serum sample. Principal component analysis (PCA) with varimax rotation was used to identify independent patterns explaining risk factor variance. Quintiles of pattern scores were associated with BMI% and WC% using multiple linear regression. Results: PCA identified 4 patterns: lipid (low HDL, high TG and LDL), inflammatory (high ICAM and TNFαR2), blood pressure (high SBP and DBP) and Lp(a) [high Lp(a)]. BMI% was significantly associated with higher levels of the lipid and blood pressure patterns (p<0.03), explaining 15.8% and 4.7% of variance (partial r2) respectively. A higher WC% was associated with significantly higher levels of the lipid pattern (p<0.001), explaining 16.2% of variance. When both BMI% and WC% were used together, neither BMI% nor WC% remained associated with the lipid pattern;, however, BMI% was inversely associated (p=0.02) and WC% positively associated (p=0.01) with the inflammatory pattern. The combined use of BMI and WC explained 12.2% of variance in the inflammatory pattern. Conclusion: In a sample of high-risk children, BMI% or WC% explained similar variance in lipid levels; however, the combined use of BMI% (representing lean body mass) and WC% (representing abdominal fat) together explained greater variance in elevated inflammatory factors than either alone. This suggests that using WC% along with BMI% may contribute to cardiovascular risk assessments of high-risk children.
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 | 0.000 | 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) | 0.005 | 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".