Predicting the timing of maturational spurts in skeletal age

Am J Phys Anthropol. 2013 Jan;150(1):68-75. doi: 10.1002/ajpa.22142.

Abstract

Measures of maturity provide windows into the timing and tempo of childhood growth and maturation. Delayed maturation in a single child, or systemically in a population, can result from either genetic or environmental factors. In terms of the skeleton, delayed maturation may result in short stature or indicate another underlying issue. Thus, prediction of the timing of a maturational spurt is often desirable in order to determine the likelihood that a child will catch up to their chronological age peers. Serial data from the Fels Longitudinal Study were used to predict future skeletal age conditional on current skeletal age and to predict the timing of maturational spurts. For children who were delayed relative to their chronological age peers, the likelihood of catch-up maturation increased through the average age of onset of puberty and decreased prior to the average age of peak height velocity. For boys, the probability of an imminent maturational spurt was higher for those who were less mature. For girls aged 11 to 13 years, however, this probability was higher for those who were more mature, potentially indicating the presence of a skeletal maturation plateau between multiple spurts. The prediction model, available on the web, is most relevant to children of European ancestry living in the Midwestern US. Our model may also provide insight into the tempo of maturation for children in other populations, but must be applied with caution if those populations are known to have high burdens of environmental stressors not typical of the Midwestern US.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adolescent
  • Adolescent Development / physiology*
  • Age Determination by Skeleton*
  • Anthropology, Physical
  • Bone Development / physiology*
  • Child
  • Child Development / physiology*
  • Female
  • Humans
  • Longitudinal Studies
  • Male
  • Models, Statistical*