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A Novel method for the identification and quantification of weight faltering
Daniel J Naumenko1,2, James Dykes2, G Kesler O'Connor3
1Growth and Development Lab, Department of Anthropology, University of Colorado Boulder, Boulder, Colorado, USA.
Insights
A new method accurately quantifies infant weight faltering episodes. More frequent data collection reveals more episodes, crucial for understanding long-term growth outcomes in infants.
Area of Science:
- Pediatric Growth Monitoring
- Nutritional Epidemiology
- Infant Health Surveillance
Background:
- Short-term weight faltering episodes are common in infants but difficult to quantify.
- Understanding these episodes is crucial for assessing long-term growth outcomes.
- Existing methods may not capture the frequency and magnitude of transient weight loss.
Purpose of the Study:
- To introduce a novel method for identifying and quantifying short-term infant weight faltering.
- To assess the relationship between weight faltering episodes and overall growth.
- To evaluate the impact of data collection frequency on quantifying weight faltering.
Main Methods:
- Applied a new method to longitudinal growth data from 124 Gambian infants over the first year.
- Identified weight faltering episodes using velocity peaks and troughs.
- Simulated different data collection intervals to assess their impact on episode quantification.
Main Results:
- Identified 300 weight faltering episodes in 119 infants.
- The number and magnitude of episodes negatively correlated with 1-year growth outcomes.
- Increased data collection intervals led to missed episodes, overestimated duration, and underestimated rates of weight loss/regain.
Conclusions:
- The developed method effectively identifies and quantifies short-term weight faltering episodes.
- These episodes are negatively associated with infant growth outcomes.
- This approach provides a valuable tool for researchers studying infant growth and 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.
