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Child Weight Growth Chart and Its Associated Factors in Birth Cohort of Maku Using a Growth Curve Model and LMS Method

BACKGROUND: Infant growth is defined as a positive change in body size over a period of time, and is a sensitive predictor of social health. The most effective way to determine child growth is by measuring birth weight and constructing a weight growth trajectory. Many studies were conducted on the e...

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Autores principales: Ayatollahi, Seyyed Mohammad Taghi, Sharafi, Zahra, Haem, Elham
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Canadian Center of Science and Education 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4803886/
https://www.ncbi.nlm.nih.gov/pubmed/26153171
http://dx.doi.org/10.5539/gjhs.v7n6p181
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author Ayatollahi, Seyyed Mohammad Taghi
Sharafi, Zahra
Haem, Elham
author_facet Ayatollahi, Seyyed Mohammad Taghi
Sharafi, Zahra
Haem, Elham
author_sort Ayatollahi, Seyyed Mohammad Taghi
collection PubMed
description BACKGROUND: Infant growth is defined as a positive change in body size over a period of time, and is a sensitive predictor of social health. The most effective way to determine child growth is by measuring birth weight and constructing a weight growth trajectory. Many studies were conducted on the effects of different factors on birth weight, but investigations of these effects on growth trajectory are really sparse. This study analyzes longitudinal data to determine factors affecting growth trajectory and used LMS chart for comparing children. MATERIALS AND METHODS: In a cohort study, 256 neonates born in 2004 in Maku, Iran, were recruited and were followed until 2009.The weight of the neonates were measured at 12 occasions from birth, until the age of 5 years. A growth curve model was used to determine the affecting factors. The parametric LMS method was used to construct the reference centiles curve of the weight (5th, 50th, 95th percentiles). FINDINGS: The findings show that while controlling the other factors, birth region, breast feeding duration, mother’s education and infants’ gender significantly influenced the longitudinal weight rate. However, other variables did not reveal any significant association with growth. The growth charts increased rapidly from birth to 5 years of age for both sexes. It was observed that male children grew faster than females, through the first year of age up to 5 years. CONCLUSION: Although every child has a growth potential, this capacity could be influenced by various factors and can be compared with other infants through a growth chart. We used longitudinal data to obtain the risk factor of growth trajectory. LMS method was also used for description of growth. Thereafter, the weight chart of Shiraz, southern Iran’s corresponding infants, was compared.
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spelling pubmed-48038862016-04-21 Child Weight Growth Chart and Its Associated Factors in Birth Cohort of Maku Using a Growth Curve Model and LMS Method Ayatollahi, Seyyed Mohammad Taghi Sharafi, Zahra Haem, Elham Glob J Health Sci Articles BACKGROUND: Infant growth is defined as a positive change in body size over a period of time, and is a sensitive predictor of social health. The most effective way to determine child growth is by measuring birth weight and constructing a weight growth trajectory. Many studies were conducted on the effects of different factors on birth weight, but investigations of these effects on growth trajectory are really sparse. This study analyzes longitudinal data to determine factors affecting growth trajectory and used LMS chart for comparing children. MATERIALS AND METHODS: In a cohort study, 256 neonates born in 2004 in Maku, Iran, were recruited and were followed until 2009.The weight of the neonates were measured at 12 occasions from birth, until the age of 5 years. A growth curve model was used to determine the affecting factors. The parametric LMS method was used to construct the reference centiles curve of the weight (5th, 50th, 95th percentiles). FINDINGS: The findings show that while controlling the other factors, birth region, breast feeding duration, mother’s education and infants’ gender significantly influenced the longitudinal weight rate. However, other variables did not reveal any significant association with growth. The growth charts increased rapidly from birth to 5 years of age for both sexes. It was observed that male children grew faster than females, through the first year of age up to 5 years. CONCLUSION: Although every child has a growth potential, this capacity could be influenced by various factors and can be compared with other infants through a growth chart. We used longitudinal data to obtain the risk factor of growth trajectory. LMS method was also used for description of growth. Thereafter, the weight chart of Shiraz, southern Iran’s corresponding infants, was compared. Canadian Center of Science and Education 2015-11 2015-04-15 /pmc/articles/PMC4803886/ /pubmed/26153171 http://dx.doi.org/10.5539/gjhs.v7n6p181 Text en Copyright: © Canadian Center of Science and Education http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Articles
Ayatollahi, Seyyed Mohammad Taghi
Sharafi, Zahra
Haem, Elham
Child Weight Growth Chart and Its Associated Factors in Birth Cohort of Maku Using a Growth Curve Model and LMS Method
title Child Weight Growth Chart and Its Associated Factors in Birth Cohort of Maku Using a Growth Curve Model and LMS Method
title_full Child Weight Growth Chart and Its Associated Factors in Birth Cohort of Maku Using a Growth Curve Model and LMS Method
title_fullStr Child Weight Growth Chart and Its Associated Factors in Birth Cohort of Maku Using a Growth Curve Model and LMS Method
title_full_unstemmed Child Weight Growth Chart and Its Associated Factors in Birth Cohort of Maku Using a Growth Curve Model and LMS Method
title_short Child Weight Growth Chart and Its Associated Factors in Birth Cohort of Maku Using a Growth Curve Model and LMS Method
title_sort child weight growth chart and its associated factors in birth cohort of maku using a growth curve model and lms method
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4803886/
https://www.ncbi.nlm.nih.gov/pubmed/26153171
http://dx.doi.org/10.5539/gjhs.v7n6p181
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