AI Insight
Researchers analyzed growth patterns in over 14,000 Vietnamese urban children from 2018-2025, identifying 10 distinct growth phenotypes in boys and 12 in girls using advanced statistical clustering methods. The study found that these growth patterns were associated with prepubertal body mass index categories, with one tall, accelerated growth phenotype in boys showing particularly high obesity rates (53.5%). Growth phenotype classification improved prediction of late adolescent height beyond standard baseline measurements, especially in boys.
Why it matters
This research suggests that children follow distinct growth trajectories rather than a single average pattern, which could help clinicians identify children at risk for abnormal growth or obesity earlier. The identification of specific growth phenotypes linked to weight status may enable more personalized monitoring and intervention strategies in pediatric healthcare.
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⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
Background Child growth is usually summarized by an average trajectory, an approach that can hide clinically meaningful heterogeneity between children. This study aims to identify various growth phenotypes in Vietnamese children. Methods This study analyzed retrospective longitudinal anthropometric data from annual school health check of children in Hanoi, Hochiminh, and Haiphong, Vietnam from 2018 to 2025. Children with at least 4 visits spanning at least 3 years were included (8,612 boys and 6,107 girls). Height for age trajectory was summarized with functional principal component scores and combined with SITAR derived random effects for growth size, pubertal timing, and tempo, then clustered with sex specific Gaussian mixture models. We evaluated phenotype associations with prepubertal BMI category, cluster stability, and whether phenotype improved prediction of late adolescent height beyond baseline prepubertal variables. Results Ten growth phenotypes in boys and twelve in girls were identified. Phenotype membership was associated with prepubertal BMI category in both sexes. A tall, accelerated growth phenotype in boys (4.2% of boys) had the highest prepubertal obesity prevalence (53.5%) and strongest obesity association in external validation. The girls’ phenotype solution was more sensitive to visit based eligibility criteria than the boys’ solution. Adding phenotype to a baseline model improved prediction of late adolescent height in both sexes, more strongly in boys. Conclusions Combining functional and SITAR based clustering identified clinically distinguishable growth phenotypes in Vietnamese children linked to prepubertal BMI and late adolescent height. Sex specific validation is needed before these phenotypes inform clinical application.