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A novel shape-based approach to identify gestational age-adjusted growth patterns from birth to 11 years of age
A novel shape-based approach to identify gestational age-adjusted growth patterns from birth to 11 years of age
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A novel shape-based approach to identify gestational age-adjusted growth patterns from birth to 11 years of age
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A novel shape-based approach to identify gestational age-adjusted growth patterns from birth to 11 years of age
A novel shape-based approach to identify gestational age-adjusted growth patterns from birth to 11 years of age

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A novel shape-based approach to identify gestational age-adjusted growth patterns from birth to 11 years of age
A novel shape-based approach to identify gestational age-adjusted growth patterns from birth to 11 years of age
Journal Article

A novel shape-based approach to identify gestational age-adjusted growth patterns from birth to 11 years of age

2023
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Overview
Child growth patterns assessment is critical to design public health interventions. However, current analytical approaches may overlook population heterogeneity. To overcome this limitation, we developed a growth trajectories clustering pipeline that incorporates a shape-respecting distance, baseline centering (i.e., birth-size normalized trajectories) and Gestational Age (GA)-correction to characterize shape-based child growth patterns. We used data from 3945 children (461 preterm) in the 2004 Pelotas Birth Cohort with at least 3 measurements between birth (included) and 11 years of age. Sex-adjusted weight-, length/height- and body mass index-for-age z-scores were derived at birth, 3 months, and at 1, 2, 4, 6 and 11 years of age (INTERGROWTH-21st and WHO growth standards). Growth trajectories clustering was conducted for each anthropometric index using k-means and a shape-respecting distance, accounting or not for birth size and/or GA-correction. We identified 3 trajectory patterns for each anthropometric index: increasing ( High ), stable ( Middle ) and decreasing ( Low ). Baseline centering resulted in pattern classification that considered early life growth traits. GA-correction increased the intercepts of preterm-born children trajectories, impacting their pattern classification. Incorporating shape-based clustering, baseline centering and GA-correction in growth patterns analysis improves the identification of subgroups meaningful for public health interventions.