Metrics of early childhood growth in recent human growth research: a scoping review

There is no consensus on the operational definition of child growth, leading to substantial variability in statistical strategies to summarize growth or categorize children with respect to the slope or shape of their trajectories. We conducted a scoping review to systematically summarize the variability in early childhood growth metrics in recent human growth research. We searched MEDLINE and Embase for studies on child growth as an exposure or outcome, in which each child had ≥2 serial measures of length/height, weight or body mass index (BMI) spanning an age interval. From eligible articles, we extracted details of the statistical method used to quantify child growth from a 10% random sample of studies published between Jan 2010–June 2016 and all studies from the most recent 9 months (Oct 2015 – June 2016). Each metric was deconstructed into two components: label and content. The label is the word or phrase used by the study authors to identify a particular growth metric (e.g., “growth trajectory”). The content was the conceptual and statistical properties of the metric, which we summarized as a ‘content signature’, a 9‐digit sequence of numeric codes that specified the derivation/estimation, application and interpretation of the growth parameter. Heterogeneity among growth metrics was represented by the number of unique content signatures overall and by anthropometric parameter. Of the 149 eligible articles, 19 (13%) only described cross‐sectional metrics of size (despite reportedly measuring children at ≥2 encounters), while 130 (87%) calculated, estimated, predicted or categorized growth based on ≥2 data points. From the latter, we found 76 unique metrics of early childhood growth. Among studies investigating child growth as an exposure using ≥2 data points (n=30), there were 30 unique content signatures: 9, 11, 10 for length, weight and BMI, respectively. For studies of child growth as an outcome using ≥2 data points (n=109), there were 66 unique content signatures: 23, 25, 18 for length, weight and BMI, respectively. Overall, the most common approach to quantifying growth was a simple calculation of each child's incremental change (i.e., arithmetic difference) in the anthropometric parameter between two time points (45%, 46%, 37% of metrics for length, weight and BMI, respectively) ( Figure 1). Label‐to‐content discordance was common due to distinct signatures carrying the same label, and also because of instances in which the same content signature was assigned multiple different labels. Variations in the definitions of growth may complicate comparisons of findings across studies. Discordance between metric labels and their statistical formulations further challenges integration of data and inferences. We conclude that child growth metric heterogeneity should be considered when aggregating or designing studies of the causes of relatively slow or fast growth or studies of the associations between early growth and later health outcomes. Support or Funding Information This work was supported by the Bill and Melinda Gates Foundation. 1A Sankey diagram to show the relative prevalence of estimating growth by calculating the arithmetic difference between two time points for each child by anthropometric parameter. Each band represents a unique content signature, where the width of the band is proportional to the frequency of the approach.