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Characterizing early child growth patterns of height-for-age in an urban slum cohort of Bangladesh with functional principal component analysis

BACKGROUND: 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...

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Autores principales: Zhang, Yin, Zhou, Jianhui, Niu, Feiyang, Donowitz, Jeffrey R., Haque, Rashidul, Petri, William A., Ma, Jennie Z.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5359797/
https://www.ncbi.nlm.nih.gov/pubmed/28327104
http://dx.doi.org/10.1186/s12887-017-0831-y
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author Zhang, Yin
Zhou, Jianhui
Niu, Feiyang
Donowitz, Jeffrey R.
Haque, Rashidul
Petri, William A.
Ma, Jennie Z.
author_facet Zhang, Yin
Zhou, Jianhui
Niu, Feiyang
Donowitz, Jeffrey R.
Haque, Rashidul
Petri, William A.
Ma, Jennie Z.
author_sort Zhang, Yin
collection PubMed
description BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02734264, registered 22 March, 2016. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12887-017-0831-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-53597972017-03-22 Characterizing early child growth patterns of height-for-age in an urban slum cohort of Bangladesh with functional principal component analysis Zhang, Yin Zhou, Jianhui Niu, Feiyang Donowitz, Jeffrey R. Haque, Rashidul Petri, William A. Ma, Jennie Z. BMC Pediatr Research Article BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02734264, registered 22 March, 2016. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12887-017-0831-y) contains supplementary material, which is available to authorized users. BioMed Central 2017-03-21 /pmc/articles/PMC5359797/ /pubmed/28327104 http://dx.doi.org/10.1186/s12887-017-0831-y Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Zhang, Yin
Zhou, Jianhui
Niu, Feiyang
Donowitz, Jeffrey R.
Haque, Rashidul
Petri, William A.
Ma, Jennie Z.
Characterizing early child growth patterns of height-for-age in an urban slum cohort of Bangladesh with functional principal component analysis
title Characterizing early child growth patterns of height-for-age in an urban slum cohort of Bangladesh with functional principal component analysis
title_full Characterizing early child growth patterns of height-for-age in an urban slum cohort of Bangladesh with functional principal component analysis
title_fullStr Characterizing early child growth patterns of height-for-age in an urban slum cohort of Bangladesh with functional principal component analysis
title_full_unstemmed Characterizing early child growth patterns of height-for-age in an urban slum cohort of Bangladesh with functional principal component analysis
title_short Characterizing early child growth patterns of height-for-age in an urban slum cohort of Bangladesh with functional principal component analysis
title_sort characterizing early child growth patterns of height-for-age in an urban slum cohort of bangladesh with functional principal component analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5359797/
https://www.ncbi.nlm.nih.gov/pubmed/28327104
http://dx.doi.org/10.1186/s12887-017-0831-y
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