Growth curve models for weight among infants: a scoping review protocol.

Abstract

Objective: This scoping review aims to provide a systematic overview of the literature on statistical models to estimate weight growth curves among infants, examining key features such as study design, sample size, and statistical approaches.

Introduction: Growth models were first developed to estimate individuals' growth curves by modeling each individual separately. Later, with the aim of estimating mean trajectories, approaches using mixed effects regression models were proposed. More flexible models were also applied in this context, enabling the estimation of more parameters (eg, Generalized Additive Models for Location, Scale, and Shape; SuperImposition by Translation and Rotation models).

Inclusion criteria: Studies of statistical/mathematical methodologies for estimating weight growth curves of infants under 24 months of age, based on prospective/retrospective cohorts, or cross-sectional studies will be included. Only studies published in English, Portuguese, or Spanish will be considered. Case series reports, reviews, short letter publications, books, and abstract-only papers, such as conference proceedings, will be excluded.

Methods: This review will be conducted in accordance with the JBI methodology for scoping reviews. PubMed, Scopus, Web of Science Core Collection, SciELO, and LILACS will be searched for published studies, while ProQuest and RCAAP will be searched for unpublished studies. Search results will be imported into Rayyan to remove duplicates. Two reviewers will independently screen titles, abstracts, and full-text articles. Any disagreements will be resolved through discussion or with a third reviewer. The resulting data, namely mathematical/statistical approaches and models, will be summarized in tabular format, accompanied by a narrative summary.

Review registration: Open Science Framework https://osf.io/95udq.