An assessment of maturity from anthropometric measurements

Med Sci Sports Exerc. 2002 Apr;34(4):689-94. doi: 10.1097/00005768-200204000-00020.


Purpose: The range of variability between individuals of the same chronological age (CA) in somatic and biological maturity is large and especially accentuated around the adolescent growth spurt. Maturity assessment is an important consideration when dealing with adolescents, from both a research perspective and youth sports stratification. A noninvasive, practical method predicting years from peak height velocity (a maturity offset value) by using anthropometric variables is developed in one sample and cross-validated in two different samples.

Methods: Gender specific multiple regression equations were calculated on a sample of 152 Canadian children aged 8-16 yr (79 boys; 73 girls) who were followed through adolescence from 1991 to 1997. The equations included three somatic dimensions (height, sitting height, and leg length), CA, and their interactions. The equations were cross-validated on a combined sample of Canadian (71 boys, 40 girls measured from 1964 through 1973) and Flemish children (50 boys, 48 girls measured from 1985 through 1999).

Results: The coefficient of determination (R2) for the boys' model was 0.92 and for the girls' model 0.91; the SEEs were 0.49 and 0.50, respectively. Mean difference between actual and predicted maturity offset for the verification samples was 0.24 (SD 0.65) yr in boys and 0.001 (SD 0.68) yr in girls.

Conclusion: Although the cross-validation meets statistical standards for acceptance, caution is warranted with regard to implementation. It is recommended that maturity offset be considered as a categorical rather than a continuous assessment. Nevertheless, the equations presented are a reliable, noninvasive and a practical solution for the measure of biological maturity for matching adolescent athletes

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Anthropometry / methods*
  • Child
  • Female
  • Growth / physiology*
  • Humans
  • Longitudinal Studies
  • Male
  • Predictive Value of Tests
  • Regression Analysis