SITAR--a useful instrument for growth curve analysis

Area of Science:

• Epidemiology
• Biostatistics
• Human Growth and Development

Background:

• Growth curve analysis is crucial in life course epidemiology for understanding individual variations in pubertal growth spurts.
• Traditional methods like Preece-Baines (PB) curves require fitting numerous individual curves, posing a computational challenge.
• Individual differences in the timing and intensity of growth spurts necessitate robust analytical tools.

Purpose of the Study:

• To introduce and evaluate the SuperImposition by Translation And Rotation (SITAR) model as an alternative to traditional growth curve analysis.
• To demonstrate the SITAR model's ability to summarize individual growth patterns using a single fitted curve and three key parameters.
• To assess the utility of the SITAR model in epidemiological research using datasets of adolescent boys and girls with Turner syndrome.

Main Methods:

• The SITAR model fits a single mean growth curve, aligning individual curves through adjustments for size, tempo, and velocity (random effects).
• Data from Christ's Hospital School (CHS) boys (N=3245) and girls with Turner syndrome (TS) (N=105) were analyzed using the SITAR model.
• The model's performance was compared to individually-fitted PB curves in terms of variance explained and residual standard deviation.

Main Results:

• The SITAR model achieved a high goodness-of-fit, explaining 99% of the variance in both datasets with a residual standard deviation of 6-7 mm, comparable to PB curves.
• In CHS boys, growth tempo analyzed by SITAR was significantly associated with insulin-like growth factor-1 levels measured 50 years later.
• Girls with Turner syndrome treated with oxandrolone showed a significantly increased growth velocity compared to placebo, as determined by the SITAR model.

Conclusions:

• The SITAR growth curve model is a powerful and efficient epidemiological instrument for analyzing height trajectories during puberty.
• The model effectively captures individual growth variations (size, tempo, velocity) and facilitates associations with long-term outcomes.
• SITAR provides a valuable alternative for analyzing complex growth data in large-scale epidemiological studies.