Abstract P179: Abdominal Skin-fold Thickness Improves Anthropometric Prediction of Insulin Resistance in Prepubescent Colombian Children
Bibliographic record
Abstract
Introduction: Body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR), have been considered poor measures of cardiometabolic risk in children, in whom increases in these measures may reflect increases in lean mass more so than fat mass. Hypothesis: We examined the hypothesis that abdominal skinfolds (ASF) have better predictive value than BMI and other anthropometric measures for identifying insulin resistance (IR) in prepubescent Colombian children. Methods: We used data from a population-based cross-sectional study of 1,262 children, aged 6-10 y, in Bucaramanga, Colombia. Logistic regression stepwise variable selection (P<0.05 for entry and retention) was performed to identify anthropometric predictors of IR, as determined by homeostatic model assessment (HOMA). Receiver operating characteristic (ROC) curves were used to compare area under the curve (AUC). Results: There were 57 boys and 70 girls classified as IR (HOMA >90th percentile). Among anthropometric measures compared - including WC, WHtR, and four skinfolds - only age- and sex-specific ASF and BMI z-scores were retained as independent anthropometric predictors of IR. Prediction of IR was marginally better using ASF z-scores than BMI z-scores (P for contrast= 0.13). However, the final Model, which included both ASF and BMI, significantly increased the AUC from 0.80 (95% CI: 0.75-0.84) to 0.82 (95% CI: 0.78-0.86) - an improvement of 0.02 (95% CI: 0.004-0.04; P for contrast= 0.01)(see table ). In the final Model, after adjusting for BMI z, a 1-SD increment in ASF z was associated with 2.38 (95% CI: 1.74-3.26) greater odds of IR; whereas a 1-SD increment in BMI z, after adjustment for ASF z, was associated with 1.46 (95% CI: 1.11-1.91) greater odds of IR. Conclusions: ASF was independent from and marginally better than BMI in predicting IR in Colombian children. Furthermore, integration of ASF with BMI improved IR risk stratification compared to BMI alone, opening new perspectives in the prediction of cardiometabolic risk in children. ROC Curve Contrast Estimation and Testing Results for Anthropometric Measures of Insulin Resistance ROC Curve Contrasts Difference in AUC 95% CI P for Contrast WCz - BMIz 0.006 (-0.016, 0.028) 0.622 WHtRz - BMIz −0.045 (-0.074, -0.016) 0.002 ASFz - BMIz 0.018 (-0.005, 0.040) 0.126 Model (ASFz + BMIz) - BMIz 0.021 (0.004, 0.038) 0.014 BMI z-score (BMIz) was used as reference in all contrast estimates and tests against waist circumference z-score (WCz), waist-to-height z-score (WHtRz), abdominal skinfolds z-score (ASFz), and the best stepwise-selection Model (includes ASFz + BMIz)
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".