No Cover Image

Journal article 325 views 55 downloads

Identifying Prenatal and Postnatal Determinants of Infant Growth: A Structural Equation Modelling Based Cohort Analysis

Kelly Morgan, Shang-Ming Zhou, Rebecca Hill, Ronan Lyons Orcid Logo, Shantini Paranjothy, Sinead Brophy Orcid Logo

International Journal of Environmental Research and Public Health, Volume: 18, Issue: 19, Start page: 10265

Swansea University Authors: Ronan Lyons Orcid Logo, Sinead Brophy Orcid Logo

  • 58483.pdf

    PDF | Version of Record

    © 2021 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license

    Download (677.52KB)

Abstract

The growth and maturation of infants reflect their overall health and nutritional status. The purpose of this study is to examine the associations of prenatal and early postnatal factors with infant growth (IG). A data-driven model was constructed by structural equation modelling to examine the rela...

Full description

Published in: International Journal of Environmental Research and Public Health
ISSN: 1660-4601
Published: MDPI AG 2021
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa58483
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2021-10-27T16:04:00Z
last_indexed 2023-01-11T14:39:06Z
id cronfa58483
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2022-08-16T15:53:45.1875932</datestamp><bib-version>v2</bib-version><id>58483</id><entry>2021-10-27</entry><title>Identifying Prenatal and Postnatal Determinants of Infant Growth: A Structural Equation Modelling Based Cohort Analysis</title><swanseaauthors><author><sid>83efcf2a9dfcf8b55586999d3d152ac6</sid><ORCID>0000-0001-5225-000X</ORCID><firstname>Ronan</firstname><surname>Lyons</surname><name>Ronan Lyons</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>84f5661b35a729f55047f9e793d8798b</sid><ORCID>0000-0001-7417-2858</ORCID><firstname>Sinead</firstname><surname>Brophy</surname><name>Sinead Brophy</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2021-10-27</date><deptcode>HDAT</deptcode><abstract>The growth and maturation of infants reflect their overall health and nutritional status. The purpose of this study is to examine the associations of prenatal and early postnatal factors with infant growth (IG). A data-driven model was constructed by structural equation modelling to examine the relationships between pre- and early postnatal environmental factors and IG at age 12 months. The IG was a latent variable created from infant weight and waist circumference. Data were obtained on 274 mother-child pairs during pregnancy and the postnatal periods. Maternal pre-pregnancy BMI emerged as an important predictor of IG with both direct and indirect (mediated through infant birth weight) effects. Infants who gained more weight from birth to 6 months and consumed starchy foods daily at age 12 months, were more likely to be larger by age 12 months. Infant physical activity (PA) levels also emerged as a determinant. The constructed model provided a reasonable fit ( (11) = 21.5, &lt; 0.05; RMSEA = 0.07; CFI = 0.94; SRMR = 0.05) to the data with significant pathways for all examined variables. Promoting healthy weight amongst women of child bearing age is important in preventing childhood obesity, and increasing daily infant PA is as important as a healthy infant diet.</abstract><type>Journal Article</type><journal>International Journal of Environmental Research and Public Health</journal><volume>18</volume><journalNumber>19</journalNumber><paginationStart>10265</paginationStart><paginationEnd/><publisher>MDPI AG</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>1660-4601</issnElectronic><keywords>infant growth; structural equation modelling; pregnancy; public health; physical activity; paediatrics; obesity; postnatal development</keywords><publishedDay>29</publishedDay><publishedMonth>9</publishedMonth><publishedYear>2021</publishedYear><publishedDate>2021-09-29</publishedDate><doi>10.3390/ijerph181910265</doi><url/><notes/><college>COLLEGE NANME</college><department>Health Data Science</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>HDAT</DepartmentCode><institution>Swansea University</institution><apcterm/><funders>This work was supported by Swansea University, Public Health Wales NHS Trust, and Health and Care Research Wales; National Centre for Population Health and Wellbeing Research (NCPHWR) via Health and Care Research Wales (grant ref. CA02). This research was also supported by the Centre for the Development and Evaluation of Complex Interventions for Public Health Improvement (DECIPHer), a UKCRC Public Health Research Centre of Excellence via joint funding (MR/KO232331/1) from the British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, the Welsh Government and the Wellcome Trust.</funders><projectreference/><lastEdited>2022-08-16T15:53:45.1875932</lastEdited><Created>2021-10-27T16:59:16.6422128</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Medicine</level></path><authors><author><firstname>Kelly</firstname><surname>Morgan</surname><order>1</order></author><author><firstname>Shang-Ming</firstname><surname>Zhou</surname><order>2</order></author><author><firstname>Rebecca</firstname><surname>Hill</surname><order>3</order></author><author><firstname>Ronan</firstname><surname>Lyons</surname><orcid>0000-0001-5225-000X</orcid><order>4</order></author><author><firstname>Shantini</firstname><surname>Paranjothy</surname><order>5</order></author><author><firstname>Sinead</firstname><surname>Brophy</surname><orcid>0000-0001-7417-2858</orcid><order>6</order></author></authors><documents><document><filename>58483__21329__f92d5350fa3d4081af4621ee9d689dbc.pdf</filename><originalFilename>58483.pdf</originalFilename><uploaded>2021-10-27T17:04:45.6516525</uploaded><type>Output</type><contentLength>693776</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>&#xA9; 2021 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>https://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling 2022-08-16T15:53:45.1875932 v2 58483 2021-10-27 Identifying Prenatal and Postnatal Determinants of Infant Growth: A Structural Equation Modelling Based Cohort Analysis 83efcf2a9dfcf8b55586999d3d152ac6 0000-0001-5225-000X Ronan Lyons Ronan Lyons true false 84f5661b35a729f55047f9e793d8798b 0000-0001-7417-2858 Sinead Brophy Sinead Brophy true false 2021-10-27 HDAT The growth and maturation of infants reflect their overall health and nutritional status. The purpose of this study is to examine the associations of prenatal and early postnatal factors with infant growth (IG). A data-driven model was constructed by structural equation modelling to examine the relationships between pre- and early postnatal environmental factors and IG at age 12 months. The IG was a latent variable created from infant weight and waist circumference. Data were obtained on 274 mother-child pairs during pregnancy and the postnatal periods. Maternal pre-pregnancy BMI emerged as an important predictor of IG with both direct and indirect (mediated through infant birth weight) effects. Infants who gained more weight from birth to 6 months and consumed starchy foods daily at age 12 months, were more likely to be larger by age 12 months. Infant physical activity (PA) levels also emerged as a determinant. The constructed model provided a reasonable fit ( (11) = 21.5, < 0.05; RMSEA = 0.07; CFI = 0.94; SRMR = 0.05) to the data with significant pathways for all examined variables. Promoting healthy weight amongst women of child bearing age is important in preventing childhood obesity, and increasing daily infant PA is as important as a healthy infant diet. Journal Article International Journal of Environmental Research and Public Health 18 19 10265 MDPI AG 1660-4601 infant growth; structural equation modelling; pregnancy; public health; physical activity; paediatrics; obesity; postnatal development 29 9 2021 2021-09-29 10.3390/ijerph181910265 COLLEGE NANME Health Data Science COLLEGE CODE HDAT Swansea University This work was supported by Swansea University, Public Health Wales NHS Trust, and Health and Care Research Wales; National Centre for Population Health and Wellbeing Research (NCPHWR) via Health and Care Research Wales (grant ref. CA02). This research was also supported by the Centre for the Development and Evaluation of Complex Interventions for Public Health Improvement (DECIPHer), a UKCRC Public Health Research Centre of Excellence via joint funding (MR/KO232331/1) from the British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, the Welsh Government and the Wellcome Trust. 2022-08-16T15:53:45.1875932 2021-10-27T16:59:16.6422128 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Kelly Morgan 1 Shang-Ming Zhou 2 Rebecca Hill 3 Ronan Lyons 0000-0001-5225-000X 4 Shantini Paranjothy 5 Sinead Brophy 0000-0001-7417-2858 6 58483__21329__f92d5350fa3d4081af4621ee9d689dbc.pdf 58483.pdf 2021-10-27T17:04:45.6516525 Output 693776 application/pdf Version of Record true © 2021 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license true eng https://creativecommons.org/licenses/by/4.0/
title Identifying Prenatal and Postnatal Determinants of Infant Growth: A Structural Equation Modelling Based Cohort Analysis
spellingShingle Identifying Prenatal and Postnatal Determinants of Infant Growth: A Structural Equation Modelling Based Cohort Analysis
Ronan Lyons
Sinead Brophy
title_short Identifying Prenatal and Postnatal Determinants of Infant Growth: A Structural Equation Modelling Based Cohort Analysis
title_full Identifying Prenatal and Postnatal Determinants of Infant Growth: A Structural Equation Modelling Based Cohort Analysis
title_fullStr Identifying Prenatal and Postnatal Determinants of Infant Growth: A Structural Equation Modelling Based Cohort Analysis
title_full_unstemmed Identifying Prenatal and Postnatal Determinants of Infant Growth: A Structural Equation Modelling Based Cohort Analysis
title_sort Identifying Prenatal and Postnatal Determinants of Infant Growth: A Structural Equation Modelling Based Cohort Analysis
author_id_str_mv 83efcf2a9dfcf8b55586999d3d152ac6
84f5661b35a729f55047f9e793d8798b
author_id_fullname_str_mv 83efcf2a9dfcf8b55586999d3d152ac6_***_Ronan Lyons
84f5661b35a729f55047f9e793d8798b_***_Sinead Brophy
author Ronan Lyons
Sinead Brophy
author2 Kelly Morgan
Shang-Ming Zhou
Rebecca Hill
Ronan Lyons
Shantini Paranjothy
Sinead Brophy
format Journal article
container_title International Journal of Environmental Research and Public Health
container_volume 18
container_issue 19
container_start_page 10265
publishDate 2021
institution Swansea University
issn 1660-4601
doi_str_mv 10.3390/ijerph181910265
publisher MDPI AG
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
document_store_str 1
active_str 0
description The growth and maturation of infants reflect their overall health and nutritional status. The purpose of this study is to examine the associations of prenatal and early postnatal factors with infant growth (IG). A data-driven model was constructed by structural equation modelling to examine the relationships between pre- and early postnatal environmental factors and IG at age 12 months. The IG was a latent variable created from infant weight and waist circumference. Data were obtained on 274 mother-child pairs during pregnancy and the postnatal periods. Maternal pre-pregnancy BMI emerged as an important predictor of IG with both direct and indirect (mediated through infant birth weight) effects. Infants who gained more weight from birth to 6 months and consumed starchy foods daily at age 12 months, were more likely to be larger by age 12 months. Infant physical activity (PA) levels also emerged as a determinant. The constructed model provided a reasonable fit ( (11) = 21.5, < 0.05; RMSEA = 0.07; CFI = 0.94; SRMR = 0.05) to the data with significant pathways for all examined variables. Promoting healthy weight amongst women of child bearing age is important in preventing childhood obesity, and increasing daily infant PA is as important as a healthy infant diet.
published_date 2021-09-29T04:15:02Z
_version_ 1763754013317136384
score 10.989344