Characterizing early child growth patterns of height-for-age in an urban slum cohort of Bangladesh with functional principal component analysis.
Early childhood is a critical stage of physical and cognitive growth that forms the foundation of future wellbeing. Stunted growth is presented in one of every 4 children worldwide and contributes to developmental impairment and under-five mortality. Better understanding of early growth patterns should allow for early detection and intervention in malnutrition. We aimed to characterize early child growth patterns and quantify the change of growth curves from the World Health Organization (WHO) Child Growth Standards.



In a cohort of 626 Bangladesh children, longitudinal height-for-age z-scores (HAZ) were modelled over the first 24 months of life using functional principal component analysis (FPCA). Deviation of individual growth from the WHO standards was quantified based on the leading functional principal components (FPCs), and growth faltering was detected as it occurred. The risk factors associated with growth faltering were identified in a linear regression.



Ninety-eight percent of temporal variation in growth trajectories over the first 24 months of life was captured by two leading FPCs (FPC1 for overall growth and FPC2 for change in growth trajectory). A derived index, adj-FPC2, quantified the change in growth trajectory (i.e., growth faltering) relative to the WHO standards. In addition to HAZ at birth, significant risk factors associated with growth faltering in boys included duration of breastfeeding, family size and income and in girls maternal weight and water source.



The underlying growth patterns of HAZ in the first 2 years of life were delineated with FPCA, and the deviations from the WHO standards were quantified from the two leading FPCs. The adj-FPC2 score provided a meaningful measure of growth faltering in the first 2 years of life, which enabled us to identify the risk factors associated with poor growth that would have otherwise been missed. Understanding faltering patterns and associated risk factors are important in the development of effective intervention strategies to improve childhood growth globally.



ClinicalTrials.gov Identifier: NCT02734264 , registered 22 March, 2016.
Department of Statistics, University of Virginia, Charlottesville, VA, USA.
Yin
Y
Zhang
Department of Statistics, University of Virginia, Charlottesville, VA, USA.
Jianhui
J
Zhou
Department of Statistics, University of Virginia, Charlottesville, VA, USA.
Feiyang
F
Niu
Division of Pediatric Infectious Diseases, Children's Hospital of Richmond at Virginia Commonwealth University, Richmond, VA, USA.
Jeffrey R
JR
Donowitz
International Centre for Diarrhoeal Disease Research, Bangladesh (ICDDR, B), Dhaka, Bangladesh.
Rashidul
R
Haque
Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia, Charlottesville, VA, USA.
William A
WA
Petri
Department of Public Health Sciences, University of Virginia, P.O. Box 800717, Charlottesville, 22908, VA, USA. jzm4h@virginia.edu.
Jennie Z
JZ
Ma
D001459:Bangladesh; D001827:Body Height; D002675:Child, Preschool; D005260:Female; D057238:Growth Charts; D006130:Growth Disorders / Q000175:diagnosis* / Q000209:etiology; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D016014:Linear Models; D008137:Longitudinal Studies; D008297:Male; D025341:Principal Component Analysis; D011446:Prospective Studies; D012307:Risk Factors; D014944:World Health Organization
Anthropometry; Functional data analysis; Growth faltering; Longitudinal growth; Stunting