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Assessing fetal growth impairments based on family data as a tool for identifying high-risk babies. An example with neonatal mortality

BACKGROUND: Low birth weight is associated with an increased risk of neonatal and infant mortality and morbidity, as well as with other adverse conditions later in life. Since the birth weight-specific mortality of a second child depends on the birth weight of an older sibling, a failure to achieve...

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Autores principales: Pedersen, Carsten B, Sun, Yuelian, Vestergaard, Mogens, Olsen, Jørn, Basso, Olga
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2233632/
https://www.ncbi.nlm.nih.gov/pubmed/18045458
http://dx.doi.org/10.1186/1471-2393-7-28
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author Pedersen, Carsten B
Sun, Yuelian
Vestergaard, Mogens
Olsen, Jørn
Basso, Olga
author_facet Pedersen, Carsten B
Sun, Yuelian
Vestergaard, Mogens
Olsen, Jørn
Basso, Olga
author_sort Pedersen, Carsten B
collection PubMed
description BACKGROUND: Low birth weight is associated with an increased risk of neonatal and infant mortality and morbidity, as well as with other adverse conditions later in life. Since the birth weight-specific mortality of a second child depends on the birth weight of an older sibling, a failure to achieve the biologically intended size appears to increase the risk of adverse outcome even in babies who are not classified as small for gestation. In this study, we aimed at quantifying the risk of neonatal death as a function of a baby's failure to fulfil its biologic growth potential across the whole distribution of birth weight. METHODS: We predicted the birth weight of 411,957 second babies born in Denmark (1979–2002), given the birth weight of the first, and examined how the ratio of achieved birth weight to predicted birth weight performed in predicting neonatal mortality. RESULTS: For any achieved birth weight category, the risk of neonatal death increased with decreasing birth weight ratio. However, the risk of neonatal death increased with decreasing birth weight, even among babies who achieved their predicted birth weight. CONCLUSION: While a low achieved birth weight was a stronger predictor of mortality, a failure to achieve the predicted birth weight was associated with increased mortality at virtually all birth weights. Use of family data may allow identification of children at risk of adverse health outcomes, especially among babies with apparently "normal" growth.
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spelling pubmed-22336322008-02-07 Assessing fetal growth impairments based on family data as a tool for identifying high-risk babies. An example with neonatal mortality Pedersen, Carsten B Sun, Yuelian Vestergaard, Mogens Olsen, Jørn Basso, Olga BMC Pregnancy Childbirth Research Article BACKGROUND: Low birth weight is associated with an increased risk of neonatal and infant mortality and morbidity, as well as with other adverse conditions later in life. Since the birth weight-specific mortality of a second child depends on the birth weight of an older sibling, a failure to achieve the biologically intended size appears to increase the risk of adverse outcome even in babies who are not classified as small for gestation. In this study, we aimed at quantifying the risk of neonatal death as a function of a baby's failure to fulfil its biologic growth potential across the whole distribution of birth weight. METHODS: We predicted the birth weight of 411,957 second babies born in Denmark (1979–2002), given the birth weight of the first, and examined how the ratio of achieved birth weight to predicted birth weight performed in predicting neonatal mortality. RESULTS: For any achieved birth weight category, the risk of neonatal death increased with decreasing birth weight ratio. However, the risk of neonatal death increased with decreasing birth weight, even among babies who achieved their predicted birth weight. CONCLUSION: While a low achieved birth weight was a stronger predictor of mortality, a failure to achieve the predicted birth weight was associated with increased mortality at virtually all birth weights. Use of family data may allow identification of children at risk of adverse health outcomes, especially among babies with apparently "normal" growth. BioMed Central 2007-11-28 /pmc/articles/PMC2233632/ /pubmed/18045458 http://dx.doi.org/10.1186/1471-2393-7-28 Text en Copyright © 2007 Pedersen et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Pedersen, Carsten B
Sun, Yuelian
Vestergaard, Mogens
Olsen, Jørn
Basso, Olga
Assessing fetal growth impairments based on family data as a tool for identifying high-risk babies. An example with neonatal mortality
title Assessing fetal growth impairments based on family data as a tool for identifying high-risk babies. An example with neonatal mortality
title_full Assessing fetal growth impairments based on family data as a tool for identifying high-risk babies. An example with neonatal mortality
title_fullStr Assessing fetal growth impairments based on family data as a tool for identifying high-risk babies. An example with neonatal mortality
title_full_unstemmed Assessing fetal growth impairments based on family data as a tool for identifying high-risk babies. An example with neonatal mortality
title_short Assessing fetal growth impairments based on family data as a tool for identifying high-risk babies. An example with neonatal mortality
title_sort assessing fetal growth impairments based on family data as a tool for identifying high-risk babies. an example with neonatal mortality
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2233632/
https://www.ncbi.nlm.nih.gov/pubmed/18045458
http://dx.doi.org/10.1186/1471-2393-7-28
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