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Potential prevention of small for gestational age in Australia: a population-based linkage study

BACKGROUND: Small for gestational age (SGA) infants are at increased risk of morbidity and mortality. We sought to identify risk factors associated with SGA and examined the potential for reducing the proportion of infants with SGA at a population level. METHODS: Birth and hospital records were link...

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Autores principales: Taylor, Lee K, Lee, Yuen Yi Cathy, Lim, Kim, Simpson, Judy M, Roberts, Christine L, Morris, Jonathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3835866/
https://www.ncbi.nlm.nih.gov/pubmed/24246011
http://dx.doi.org/10.1186/1471-2393-13-210
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author Taylor, Lee K
Lee, Yuen Yi Cathy
Lim, Kim
Simpson, Judy M
Roberts, Christine L
Morris, Jonathan
author_facet Taylor, Lee K
Lee, Yuen Yi Cathy
Lim, Kim
Simpson, Judy M
Roberts, Christine L
Morris, Jonathan
author_sort Taylor, Lee K
collection PubMed
description BACKGROUND: Small for gestational age (SGA) infants are at increased risk of morbidity and mortality. We sought to identify risk factors associated with SGA and examined the potential for reducing the proportion of infants with SGA at a population level. METHODS: Birth and hospital records were linked for births occurring in 2007–2010 in New South Wales, Australia. The analysis was stratified into three groups: preterm births, term births to non-diabetic mothers and term births to diabetic mothers. Logistic regression was used to examine the association between SGA and a range of socio-demographic and behavioural factors and health conditions, with generalised estimating equations to account for correlation among births to the same mother. Model-based population attributable fractions (PAFs) were calculated for risk factors that were considered causative and potentially modifiable. RESULTS: Of 28,126 SGA infants, the largest group was term infants of non-diabetic mothers (88.5%), followed by term infants of diabetic mothers (6.3%) and preterm infants (5.3%). The highest PAFs were for smoking: 12.4% for preterm SGA and 10.3% for term SGA infants of non-diabetic mothers. Other risk factors for SGA that were considered modifiable included: illicit drug dependency or abuse in pregnancy in all three groups, and pregnancy hypertension and late commencement of antenatal care in term infants of non-diabetic mothers, but PAFs were less than 3%. CONCLUSIONS: There are opportunities for modest reduction of the prevalence of SGA through reduction in smoking in pregnancy, and possibly earlier commencement of antenatal care and improved management of high-risk pregnancies.
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spelling pubmed-38358662013-11-21 Potential prevention of small for gestational age in Australia: a population-based linkage study Taylor, Lee K Lee, Yuen Yi Cathy Lim, Kim Simpson, Judy M Roberts, Christine L Morris, Jonathan BMC Pregnancy Childbirth Research Article BACKGROUND: Small for gestational age (SGA) infants are at increased risk of morbidity and mortality. We sought to identify risk factors associated with SGA and examined the potential for reducing the proportion of infants with SGA at a population level. METHODS: Birth and hospital records were linked for births occurring in 2007–2010 in New South Wales, Australia. The analysis was stratified into three groups: preterm births, term births to non-diabetic mothers and term births to diabetic mothers. Logistic regression was used to examine the association between SGA and a range of socio-demographic and behavioural factors and health conditions, with generalised estimating equations to account for correlation among births to the same mother. Model-based population attributable fractions (PAFs) were calculated for risk factors that were considered causative and potentially modifiable. RESULTS: Of 28,126 SGA infants, the largest group was term infants of non-diabetic mothers (88.5%), followed by term infants of diabetic mothers (6.3%) and preterm infants (5.3%). The highest PAFs were for smoking: 12.4% for preterm SGA and 10.3% for term SGA infants of non-diabetic mothers. Other risk factors for SGA that were considered modifiable included: illicit drug dependency or abuse in pregnancy in all three groups, and pregnancy hypertension and late commencement of antenatal care in term infants of non-diabetic mothers, but PAFs were less than 3%. CONCLUSIONS: There are opportunities for modest reduction of the prevalence of SGA through reduction in smoking in pregnancy, and possibly earlier commencement of antenatal care and improved management of high-risk pregnancies. BioMed Central 2013-11-19 /pmc/articles/PMC3835866/ /pubmed/24246011 http://dx.doi.org/10.1186/1471-2393-13-210 Text en Copyright © 2013 Taylor 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
Taylor, Lee K
Lee, Yuen Yi Cathy
Lim, Kim
Simpson, Judy M
Roberts, Christine L
Morris, Jonathan
Potential prevention of small for gestational age in Australia: a population-based linkage study
title Potential prevention of small for gestational age in Australia: a population-based linkage study
title_full Potential prevention of small for gestational age in Australia: a population-based linkage study
title_fullStr Potential prevention of small for gestational age in Australia: a population-based linkage study
title_full_unstemmed Potential prevention of small for gestational age in Australia: a population-based linkage study
title_short Potential prevention of small for gestational age in Australia: a population-based linkage study
title_sort potential prevention of small for gestational age in australia: a population-based linkage study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3835866/
https://www.ncbi.nlm.nih.gov/pubmed/24246011
http://dx.doi.org/10.1186/1471-2393-13-210
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