Application of multilevel linear spline models for analysis of growth trajectories in a cohort with repeat antenatal and postnatal measures of growth: a prospective cohort study

Abstract

ObjectivesTo model trajectories of antenatal and postnatal growth using linear spline multilevel models.DesignProspective cohort study.SettingMaternity hospital in Dublin, Ireland.Participants720–759 mother–child pairs from the ROLO study (initially a randomised control trial of a low glycaemic index diet in pregnancy to prevent recurrence of macrosomia [birth weight >4 kg]).Primary outcomesTrajectories of growth from 20 weeks gestation (abdominal circumference [AC], head circumference [HC] and weight) or birth (length/height) to 5 years.ResultsOver 50% of women had third-level education and 90% were of white ethnicity. Women were a mean (SD) age of 32 years (4.2) at recruitment. The best fitting model for AC, HC and weight included a model with 5 linear spline periods. The best fitting models for length/height included a model with 3 linear spline periods from birth to 6 months, 6 months to 2 years and 2 years to 5 years. Comparison of observed and predicted values for each model demonstrated good model fit. For all growth measures, growth rates were generally fastest in pregnancy or immediately post partum (for length/height), with rates of growth slowing after birth and becoming slower still as infancy and childhood progressed.ConclusionWe demonstrate the application of multilevel linear spline models for examining growth trajectories when both antenatal and postnatal measures of growth are available. The approach may be useful for cohort studies or randomised control trials with repeat prospective assessments of growth.