A Novel method for the identification and quantification of weight faltering
Dados Bibliográficos
| AUTOR(ES) | |
|---|---|
| AFILIAÇÃO(ÕES) | Department of Women and Children's Health King's College London London UK, MRC Unit The Gambia at London School of Hygiene and Tropical Medicine Banjul Gambia, Growth and Development Lab, Department of Anthropology University of Colorado Boulder Boulder Colorado USA, Department of Paediatrics University of Cambridge School of Clinical Medicine Cambridge UK, Health and Society Program, Institute of Behavioral Science University of Colorado Boulder Boulder Colorado USA, Department of Applied Mathematics University of Colorado Boulder Boulder Colorado USA, Department of Pathology University of Cambridge Cambridge UK |
| ANO | 2021 |
| TIPO | Artigo |
| PERIÓDICO | American Journal of Physical Anthropology |
| ISSN | 0002-9483 |
| E-ISSN | 1096-8644 |
| EDITORA | John Wiley and Sons Inc |
| DOI | 10.1002/ajpa.24217 |
| ADICIONADO EM | 2025-08-18 |
Resumo
ObjectiveWe 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 methodsWe 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.ResultsThree 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.ConclusionsThis 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.