BACKGROUND: Body shape and size are typically described using measures such as body mass index (BMI) and waist circumference, which predict disease risks in adults. However, this approach may underestimate the true variability in childhood body shape and size. OBJECTIVE: To use a comprehensive three-dimensional photonic scan approach to describe variation in childhood body shape and size. SUBJECTS/METHODS: At age 6 years, 3350 children from the population-based 2004 Pelotas birth cohort study were assessed by three-dimensional photonic scanner, traditional anthropometry and dual X-ray absorptiometry. Principal component analysis (PCA) was performed on height and 24 photonic scan variables (circumferences, lengths/widths, volumes and surface areas). RESULTS: PCA identified four independent components of children's body shape and size, which we termed: Corpulence, Central:peripheral ratio, Height and arm lengths, and Shoulder diameter. Corpulence showed strong correlations with traditional anthropometric and body composition measures (r>0.90 with weight, BMI, waist circumference and fat mass; r>0.70 with height, lean mass and bone mass); in contrast, the other three components showed weak or moderate correlations with those measures (all r<0.45). There was no sex difference in Corpulence, but boys had higher Central:peripheral ratio, Height and arm lengths and Shoulder diameter values than girls. Furthermore, children with low birth weight had lower Corpulence and Height and arm lengths but higher Central:peripheral ratio and Shoulder diameter than other children. Children from high socio-economic position (SEP) families had higher Corpulence and Height and arm lengths than other children. Finally, white children had higher Corpulence and Central:peripheral ratio than mixed or black children. CONCLUSIONS: Comprehensive assessment by three-dimensional photonic scanning identified components of childhood body shape and size not captured by traditional anthropometry or body composition measures. Differences in these novel components by sex, birth weight, SEP and skin colour may indicate their potential relevance to disease risks.