title: Pubertal growth assessment.
abstract: Almost all available sets of height growth reference values are constructed in a cross-sectional manner, except for a few studies in which longitudinal sampling was used. Such reference values are, however, flawed because of considerable individual variation in the timing of puberty, especially among children with early or late pubertal maturation. An additional complicating factor is that the magnitude of the total pubertal growth spurt is significantly larger among those individuals with early pubertal maturation, compared with late maturation. Based on the growth records of 145 healthy Swedish children followed longitudinally, this study introduces a pre-pubertal standard for the assessment of pre-pubertal height for children with late onset of puberty. By plotting the height values of a child in a chart containing pre-pubertal reference values, the onset of the pubertal growth spurt can be identified by a change in the pre-pubertal height standard deviation score values of 0.3 standard deviations or more over a period of 1 year. Once the pubertal onset is established, a highly accurate final height prediction method can be applied to the data, as described in this article, in which height and age at pubertal onset are the only two measures required. The r(2) value of the prediction model was over 0.80 for both sexes. Finally, a method for assessing total pubertal height gain is presented. The method adjusts for the timing of puberty and is based on the height and age at pubertal onset, plus the observed final height.
authors.affiliation: Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China. jpekarl@hkucc.hku.hk
authors.forename: Johan
authors.initials: J
authors.lastname: Karlberg
authors.forename: Chi-Wai
authors.initials: CW
authors.lastname: Kwan
authors.forename: Lars
authors.initials: L
authors.lastname: Gelander
authors.forename: Kerstin
authors.initials: K
authors.lastname: Albertsson-Wikland
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D002648:Child; D002675:Child, Preschool; D016208:Databases, Factual; D005260:Female; D005544:Forecasting; D006128:Growth / Q000502:physiology*; D006801:Humans; D008297:Male; D008954:Models, Biological; D011627:Puberty / Q000502:physiology*