Screening and subtype identification of overweight and obesity in preschool children based on bioelectrical impedance analysis and decision tree modeling

MA Rui; SHEN Zhangyifei; LU Le; TANG Jinyang

doi:10.11852/zgetbjzz2025-0336

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Chinese Journal of Child Health Care ›› 2025, Vol. 33 ›› Issue (10) : 1114-1120. DOI: 10.11852/zgetbjzz2025-0336

Screening and subtype identification of overweight and obesity in preschool children based on bioelectrical impedance analysis and decision tree modeling

MA Rui, SHEN Zhangyifei, LU Le, TANG Jinyang

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Abstract

Objective To develop a classification framework for overweight/obesity subtypes based on bioelectrical impedance analysis (BIA) and decision tree modeling, with the goal of identifying sensitive indicators and characteristic features of overweight/obesity subtypes among preschool children, so as to provide a basis for targeted interventions. Methods A convenience sample of 550 preschool children aged 3 - 6 years was recruited in Shanghai from March to December 2024.Body composition was measured using the INBODY J30 device.Differences in obesity detection between body mass index (BMI) and percent body fat (PBF) were compared.Key variables were selected through collinearity analysis.A classification and regression tree (CRT) algorithm was applied to construct subtype classification rules.Feature importance was evaluated using XGBoost, and model robustness was assessed via 10-fold cross-validation. Results The detection rate of overweight/obesity was 26.5% based on BMI criteria and 21.78% based on PBF criteria.Body composition analysis revealed 29 indicators that significantly differed between overweight/obese and normal-weight children.Stepwise regression was used to address multicollinearity, resulting in 10 variables being included in the decision tree model.The CRT-generated tree contained 17 nodes (9 terminal nodes) and classified obesity into three subtypes: lower-body fat-dominant (Node 10), low skeletal muscle mass (Node 16), and high muscle mass (Node 11).The overall accuracy of the model reached 97.5%. Conclusions A multidimensional screening model integrating BIA and decision tree analysis can accurately identify overweight/obesity subtypes in preschool children.The proposed subtype classification framework offers valuable insights for developing differentiated intervention strategies and has practical significance for optimizing early prevention and control measures for childhood obesity.

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decision tree / preschool children / overweight / obesity / prediction model

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MA Rui, SHEN Zhangyifei, LU Le, TANG Jinyang. Screening and subtype identification of overweight and obesity in preschool children based on bioelectrical impedance analysis and decision tree modeling[J]. Chinese Journal of Child Health Care. 2025, 33(10): 1114-1120 https://doi.org/10.11852/zgetbjzz2025-0336

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