Functional principal component analysis for identifying the child growth pattern using longitudinal birth cohort data.

ABSTRACT:

Background

Longitudinal studies are important to understand patterns of growth in children and limited in India. It is important to identify an approach for characterising growth trajectories to distinguish between children who have healthy growth and those growth is poor. Many statistical approaches are available to assess the longitudinal growth data and which are difficult to recognize the pattern. In this research study, we employed functional principal component analysis (FPCA) as a statistical method to find the pattern of growth data. The purpose of this study is to describe the longitudinal child growth trajectory pattern under 3 years of age using functional principal component method.

Methods

Children born between March 2002 and August 2003 (n = 290) were followed

SUBMITTER: Karuppusami R 

PROVIDER: S-EPMC8935724 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature