The purpose of this study is to evaluate the feasibility and validity of 3D avatar-based anthropometry for assessing anthropometric indicators of overweight and obesity in children based on artificial intelligence–derived 3D body reconstruction. This cross-sectional study included 171 children aged 8–10 years from five primary schools in southern Spain. Due to technical constraints of the reconstruction software, 75 children meeting predefined image quality and body weight requirements (≥ 30 kg) were eligible for 3D avatar analysis. Manual anthropometric measurements were obtained following International Society for the Advancement of Kinanthropometry (ISAK) standards and compared with avatar-derived circumferences. Agreement was assessed by using Wilcoxon tests, Spearman correlations, Bland–Altman analyses, and false discovery rate-adjusted comparisons. Avatar-derived circumferences were consistently greater than manual measurements, although waist-to-hip and waist-to-stature ratios demonstrated no significant differences. Avatar and manual circumferences were moderately to strongly correlated (Spearman’s ρ = 0.62–0.72; adjusted p < 0.05). However, the mean absolute errors ranged from 6.21 to 7.11 cm, and Bland–Altman analysis revealed systematic overestimation with wide limits of agreement, particularly for waist and hip circumferences. Despite these discrepancies, both methods similarly discriminated between weight status categories. Conclusion: Image-based 3D avatar anthropometry is a feasible, noninvasive approach for population-level screening and research in pediatric settings. Although the system reliably captures relative differences and body proportions, its current accuracy is insufficient for individual-level clinical assessment. Further algorithmic refinement and validation in lighter and more diverse pediatric populations are needed before clinical implementation.<Table Float="No" ID="Taba"> <tgroup cols="2"> <colspec align="left" colname="c1" colnum="1" /> <colspec align="left" colname="c2" colnum="2" /> <tbody> <row> <entry align="left" nameend="c2" namest="c1"> What is Known: • Childhood obesity remains a major public health challenge requiring accurate monitoring. • Anthropometric assessment still relies mainly on manual measurements, while AI-based 3D body modeling offers a promising non-invasive alternative. </entry> </row> <row> <entry align="left" nameend="c2" namest="c1"> What is New: • Image-based 3D avatar anthropometry is feasible in school settings but is constrained by technical requirements. • Avatar measurements are correlated with manual anthropometry and preserve weight status discrimination but demonstrate systematic overestimation and limited agreement. </entry> </row> </tbody> </tgroup> </Table>

Feasibility of image-based 3D avatar anthropometry assessment of pediatric obesity: a pilot study

期刊论文
发表日期：

2026年6月27日

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María del Mar Uclés-Torrente,
Gema Esperanza Ruiz-Gamarra,
José Manuel Alcalde-Llergo,
Manuel Vaquero-Álvarez,
Isabel María Blancas-Sánchez,
Pilar Aparicio-Martínez,
Manuel Vaquero-Abellán

摘要

The purpose of this study is to evaluate the feasibility and validity of 3D avatar-based anthropometry for assessing anthropometric indicators of overweight and obesity in children based on artificial intelligence–derived 3D body reconstruction. This cross-sectional study included 171 children aged 8–10 years from five primary schools in southern Spain. Due to technical constraints of the reconstruction software, 75 children meeting predefined image quality and body weight requirements (≥ 30 kg) were eligible for 3D avatar analysis. Manual anthropometric measurements were obtained following International Society for the Advancement of Kinanthropometry (ISAK) standards and compared with avatar-derived circumferences. Agreement was assessed by using Wilcoxon tests, Spearman correlations, Bland–Altman analyses, and false discovery rate-adjusted comparisons. Avatar-derived circumferences were consistently greater than manual measurements, although waist-to-hip and waist-to-stature ratios demonstrated no significant differences. Avatar and manual circumferences were moderately to strongly correlated (Spearman’s ρ = 0.62–0.72; adjusted p < 0.05). However, the mean absolute errors ranged from 6.21 to 7.11 cm, and Bland–Altman analysis revealed systematic overestimation with wide limits of agreement, particularly for waist and hip circumferences. Despite these discrepancies, both methods similarly discriminated between weight status categories. Conclusion: Image-based 3D avatar anthropometry is a feasible, noninvasive approach for population-level screening and research in pediatric settings. Although the system reliably captures relative differences and body proportions, its current accuracy is insufficient for individual-level clinical assessment. Further algorithmic refinement and validation in lighter and more diverse pediatric populations are needed before clinical implementation.

What is Known:

• Childhood obesity remains a major public health challenge requiring accurate monitoring.

• Anthropometric assessment still relies mainly on manual measurements, while AI-based 3D body modeling offers a promising non-invasive alternative.

What is New:

• Image-based 3D avatar anthropometry is feasible in school settings but is constrained by technical requirements.

• Avatar measurements are correlated with manual anthropometry and preserve weight status discrimination but demonstrate systematic overestimation and limited agreement.