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Longitudinal Meta-Analysis of Peak Height Velocity in Young Female Athletes

Journal of Sports Sciences(2023)

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Abstract
Growth patterns and biological milestones in youth sports are key to interpreting the development of young athletes. However, there is no analysis of longitudinal meta-analysis describing the growth of young female athletes. This longitudinal meta-analysis estimated growth curves and age at peak height velocity (PHV) in young female athletes based on anthropometric data from longitudinal studies found in the literature. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, studies with repeated measurements in young female athletes were identified from searches of four databases (MEDLINE, Web of Science, SCOPUS, and SPORTDiscus) without date restrictions through August 2023. We adapted our bias assessment criteria using the Cochrane risk of bias tool for randomized controlled trials as a reference. Bayesian multilevel modeling was used to perform a longitudinal meta-analysis to extract stature growth curves and age at PHV. Fourteen studies met our eligibility criteria. Twenty-one independent samples could be included in the analysis. Conditional on the data and models, the predicted mean age at PHV for female athletes was 11.18 years (90% CI: 8.62; 12.94). When studies were aggregated by sport in the models, the models could not capture sport-specific growth curves for stature and estimate a corresponding age at PHV. We provide the first longitudinal meta-analytic summary of pubertal growth and derive age at PHV in young female athletes. The meta-analysis predicted that age at PHV occurs at similar ages to those in the general pediatric population. The data pool was limited in sports and geographic distribution, emphasizing the need to promote longitudinal research in females across different youth sports contexts.
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Key words
longitudinal studies,multilevel analysis,bayesian approach,adolescent development,youth sports
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