Modeling Growth Patterns for the First Two Years of Age in a Cohort of Bangladesh Children

• Activity Number: 678
• Type: Topic Contributed
• Date/Time: Thursday, August 13, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Jennie Z. Ma* and Yin Zhang and Jianhui Zhou and William A. Petri Jr.
• Companies: University of Virginia and University of Virginia and University of Virginia and University of Virginia
• Keywords: growth modeling ; functional principal component analysis ; catch-down growth

Abstract

Children in developing countries suffer greatly from malnutrition, which is a common cause for impaired physical and cognitive development. Better understanding of growth patterns in early life is critical for developing effective interventions. In this study, we aim to model growth curves of height with functional data analysis approaches and identify risk factors for children with catch-down growth trend. The study cohort consists of 626 Bangladesh children followed for 24 months after birth. The functional principal component analysis (fPCA) is performed, and children with different growth patterns are identified based on their fPCA scores. Significant risk factors associated with catch-down growth are selected in a logistic regression model. Similar approaches will be applied to another Bangladesh cohort to identify informative biomarkers of growth for early diagnostic test and targeted intervention development.