A Novel method for the identification and quantification of weight faltering.

OBJECTIVE: We describe a new method for identifying and quantifying the magnitude and rate of short-term weight faltering episodes, and assess how (a) these episodes relate to broader growth outcomes, and (b) different data collection intervals influence the quantification of weight faltering. MATERIALS AND METHODS: We apply this method to longitudinal growth data collected every other day across the first year of life in Gambian infants (n = 124, males = 65, females = 59). Weight faltering episodes are identified from velocity peaks and troughs. Rate of weight loss and regain, maximum weight loss, and duration of each episode were calculated. We systematically reduced our dataset to mimic various potential measurement intervals, to assess how these intervals affect the ability to derive information about short-term weight faltering episodes. We fit linear models to test whether metrics associated with growth faltering were associated with growth outcomes at 1 year, and generalized additive mixed models to determine whether different collection intervals influence episode identification and metrics. RESULTS: Three hundred weight faltering episodes from 119 individuals were identified. The number and magnitude of episodes negatively impacted growth outcomes at 1 year. As data collection interval increases, weight faltering episodes are missed and the duration of episodes is overestimated, resulting in the rate of weight loss and regain being underestimated. CONCLUSIONS: This method identifies and quantifies short-term weight faltering episodes, that are in turn negatively associated with growth outcomes. This approach offers a tool for investigators interested in understanding how short-term weight faltering relates to longer-term outcomes.

Timing of the Infancy-Childhood Growth Transition in Rural Gambia.

The Karlberg model of human growth describes the infancy, childhood, and puberty (ICP) stages as continuous and overlapping, and defined by transitions driven by sequential additional effects of several endocrine factors that shape the growth trajectory and resultant adult size. Previous research has suggested that a delayed transition from the infancy to the childhood growth stage contributes to sub-optimal growth outcomes. A new method developed to analyze the structure of centile crossing in early life has emerged as a potential tool for identifying the infancy-childhood transition (ICT), through quantifying patterns of adjacent monthly weight-for-age z-score (WAZ) deviation correlations. Using this method, the infancy-childhood transition was identified as taking place at around 12 months of age in two cohorts of UK infants. Here, we apply this method to data collected as part of a longitudinal growth study in rural Gambia [the Hormonal and Epigenetic Regulators of Growth, or HERO-G study, N = 212 (F = 99, M = 113)], in order to identify the ICT and assess whether timing of this transition differs across groups based on sex or birth seasonality. We calculated Pearson correlation coefficients for adjacent monthly WAZ score deviations. Based on the patterns of change in the correlation structure over time, our results suggest that the infancy-childhood transition occurs at around 9 months of age in rural Gambian infants. This points to an accelerated ICT compared to UK infants, rather than a delayed ICT. A comparatively later transition, seen in UK infants, allows maximal extension of the high rates of growth during the infancy stage; an earlier transition as seen in Gambian infants cuts short this period of rapid growth, potentially impacting on growth outcomes in childhood while diverting energy into other processes critical to responses to acute infectious challenges. Growth in later developmental stages in this population offers an extended window for catch-up.