aceBroader factors associated with current adolescent overweight/obesity status in YRBSS 2023: Survey-aware analysis and calibrated AI-assisted classification
Adolescent overweight and obesity are shaped by demographic, behavioral and psychosocial factors, but it remains unclear whether broader predictor information improves cross-sectional classification of current overweight/obesity status more consistently than changing the machine-learning algorithm. This cross-sectional secondary analysis used 2023 Youth Risk Behavior Surveillance System data from 17,814 United States adolescents aged 12-18 years. Survey-aware multivariable logistic regression was used to identif…
Extended predictor sets raised discrimination for both tree-based models on held-out data, and isotonic recalibration made predicted probabilities far more reliable for the selected Random Forest model.
Predictors and BMI status were measured in the same survey cycle, so the models classify current status rather than predict future obesity. Any screening or prevention use would require prospective and external validation.
Evidence
- Peer-reviewedPLOS One2026-10-08
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Truvace Impact Record TRV-2026-1709, v1: “Broader factors associated with current adolescent overweight/obesity status in YRBSS 2023: Survey-aware analysis and calibrated AI-assisted classification.” Truvace, 2026-10-17. /record/TRV-2026-1709 (accessed at citation time). sha256 9b34ba2fcff92841…
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