Defining longitudinal trajectory of body mass index percentile and predicting childhood obesity: methodologies and findings in the Boston Birth Cohort

Abstract

Background: Overweight or obesity (OWO) in school-age childhood tends to persist into adulthood. This study aims to address a critical need for early identification of children at high risk of developing OWO by defining and analyzing longitudinal trajectories of body mass index percentile (BMIPCT) during early developmental windows.

Methods: We included 3029 children from the Boston Birth Cohort (BBC) with repeated BMI measurements from birth to age 18 years. We applied locally weighted scatterplot smoothing with a time-limit scheme and predefined rules for imputation of missing data. We then used time-series K-means cluster analysis and latent class growth analysis to define longitudinal trajectories of BMIPCT from infancy up to age 18 years. Then, we investigated early life determinants of the BMI trajectories. Finally, we compared whether using early BMIPCT trajectories performs better than BMIPCT at a given age for predicting future risk of OWO.

Results: After imputation, the percentage of missing data ratio decreased from 36.0% to 10.1%. We identified four BMIPCT longitudinal trajectories: early onset OWO; late onset OWO; normal stable; and low stable. Maternal OWO, smoking, and preterm birth were identified as important determinants of the two OWO trajectories. Our predictive models showed that BMIPCT trajectories in early childhood (birth to age 1 or 2 years) were more predictive of childhood OWO (age 5-10 years) than a single BMIPCT at age 1 or 2 years.

Conclusions: Using longitudinal BMIPCT data from birth to age 18 years, this study identified distinct BMIPCT trajectories, examined early life determinants of these trajectories, and demonstrated their advantages in predicting childhood risk of OWO over BMIPCT at a single time point.

Keywords: Body mass index; Child health; Children BMI trajectory; Data imputation; Longitudinal birth cohort; Multinomial logistic regression; Overweight or obesity.

Figure 1:

Data availability before imputation (top panel) and after imputation* (bottom panel) for all samples. X-axis is the time (monthly data from birth to age 1 year, quarterly data from age 1 to 2 years, and annual data from age 2 to 18 years), and each row of the Y-axis represents one child. In each column, green indicates BMIPCT data is available, purple means BMIPCT data is missing, and yellow represents administratively censored data, which are the points beyond participants’ ages. *Time-limit aware scheme in data imputation as illustrated in Supplementary Figure S2, http://links.lww.com/PN9/A24: for missing monthly data from birth to age 1 year, imputation was allowed using data no more than 4 months earlier/later; for missing quarterly data between age 1 and 2 years, collected data no more than 1 year apart could be used; for subsequent missing annual data, imputation could be carried out using data no more than 2 years apart. BMIPCT, body mass index percentile.

Figure 2:

Summary of four BMI trajectory groups from birth to age 10 years. Thick black lines indicate the mean trajectories identified for early onset OWO (solid); late onset OWO (dashed); normal stable (dash-dotted); and low stable group (dotted). Actual trajectories for participants in each defined trajectory group are shown by the thin gray line in (B) to (E). BMI, body mass index; OWO, overweight or obesity.