Estimating peak height velocity in individuals: a comparison of statistical methods

Abstract

Background

Estimates pertaining to the timing of the adolescent growth spurt (e.g. peak height velocity; PHV), including age at peak height velocity (aPHV), play a critical role in the diagnosis, treatment, and management of skeletal growth and/or developmental disorders. Yet, distinct statistical methodologies often result in large estimate discrepancies.

Aim

The aim of the present study was to assess the advantages and disadvantages of three modelling methodologies for height as well as to determine how estimates derived from these methodologies may differ, particularly those that may be useful in paediatric clinical practice.

Subjects and methods

Height data from 686 individuals of the Fels Longitudinal Study were modelled using 5th order polynomials, natural cubic splines, and SuperImposition by Translation and Rotation (SITAR) to determine aPHV and PHV for all individuals together (i.e. population average) by sex and separately for each individual. Estimates within and between methodologies were calculated and compared.

Results

In general, mean aPHV was earlier, and PHV was greater for individuals when compared to estimates from population average models. Significant differences between mean aPHV and PHV for individuals were observed in all three methodologies, with SITAR exhibiting the latest aPHV and largest PHV estimates.

Conclusion

Each statistical methodology has a number of advantages when used for specific purposes. For modelling growth in individuals, as one would in paediatric clinical practice, we recommend the use of the 5th order polynomial methodology due to its parameter flexibility.

Keywords:

• Growth spurt
• growth trajectory
• polynomial
• natural cubic spline
• SITAR

Disclosure statement

The authors have nothing to disclose.

Additional information

Funding

This work was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (F31 HD091939, R01 HD012252) and the National Institute of Arthritis and Musculoskeletal and Skin Diseases (R01 AR055927).