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Maternal socioeconomic status and infant feeding practices underlying pathways to child stunting in Cambodia: structural path analysis using cross-sectional population data

ObjectivesTo identify and investigate complex pathways to stunting among children aged 6–24 months to determine the mediating effects of dietary diversity and continued breast feeding on the association between socioeconomic factors and child stunting.Design, setting and participantsWe analysed the...

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Published in:BMJ open 2022-11, Vol.12 (11), p.e055853
Main Authors: Harvey, Chloe Mercedes, Newell, Marie-Louise, Padmadas, Sabu
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description ObjectivesTo identify and investigate complex pathways to stunting among children aged 6–24 months to determine the mediating effects of dietary diversity and continued breast feeding on the association between socioeconomic factors and child stunting.Design, setting and participantsWe analysed the most recent cross-sectional Demographic and Health Survey data from Cambodia (2014). We applied structural path analysis on a sample of 1365 children to model the complex and inter-related pathways of factors determining children’s height for age. Explanatory variables included a composite indicator of maternal employment, household wealth, maternal education, current breastfeeding status and dietary diversity score. Results are presented both in terms of non-standardised and standardised coefficients.Outcome measureThe primary outcome measure was height-for-age Z-scores as a continuous measure.ResultsFindings suggest that children’s dietary diversity and continued breast feeding mediate the association between socioeconomic status and children’s height. While there was no significant direct effect of maternal education on children’s height, results suggested significant indirect pathways through which maternal education effects children’s height; operating through household wealth, maternal employment, dietary diversity and continued breastfeeding status (p
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We applied structural path analysis on a sample of 1365 children to model the complex and inter-related pathways of factors determining children’s height for age. Explanatory variables included a composite indicator of maternal employment, household wealth, maternal education, current breastfeeding status and dietary diversity score. Results are presented both in terms of non-standardised and standardised coefficients.Outcome measureThe primary outcome measure was height-for-age Z-scores as a continuous measure.ResultsFindings suggest that children’s dietary diversity and continued breast feeding mediate the association between socioeconomic status and children’s height. While there was no significant direct effect of maternal education on children’s height, results suggested significant indirect pathways through which maternal education effects children’s height; operating through household wealth, maternal employment, dietary diversity and continued breastfeeding status (p&lt;0.001). Most notably, 41% of the effect of maternal employment on children’s height was mediated by either dietary diversity or continued breast feeding.ConclusionWe provide evidence to support targeted nutrition interventions which account for the different ways in which underlying socioeconomic factors influence infant and young child feeding practices, and the potential impact on child nutritional status.</description><identifier>ISSN: 2044-6055</identifier><identifier>EISSN: 2044-6055</identifier><identifier>DOI: 10.1136/bmjopen-2021-055853</identifier><identifier>PMID: 36328394</identifier><language>eng</language><publisher>England: British Medical Journal Publishing Group</publisher><subject>Age ; Breast Feeding ; Breastfeeding &amp; lactation ; Cambodia - epidemiology ; Child ; Children &amp; youth ; community child health ; Cross-Sectional Studies ; Employment ; Female ; Growth Disorders - epidemiology ; Growth Disorders - etiology ; Health surveys ; Households ; Humans ; Infant ; Infant Nutritional Physiological Phenomena ; nutrition ; Nutrition and Metabolism ; Nutritional Status ; Principal components analysis ; public health ; Rural areas ; Social Class ; Socioeconomic Factors ; Socioeconomic status ; Urban areas ; Variables</subject><ispartof>BMJ open, 2022-11, Vol.12 (11), p.e055853</ispartof><rights>Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.</rights><rights>2022 Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/ . Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. 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We applied structural path analysis on a sample of 1365 children to model the complex and inter-related pathways of factors determining children’s height for age. Explanatory variables included a composite indicator of maternal employment, household wealth, maternal education, current breastfeeding status and dietary diversity score. Results are presented both in terms of non-standardised and standardised coefficients.Outcome measureThe primary outcome measure was height-for-age Z-scores as a continuous measure.ResultsFindings suggest that children’s dietary diversity and continued breast feeding mediate the association between socioeconomic status and children’s height. 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We applied structural path analysis on a sample of 1365 children to model the complex and inter-related pathways of factors determining children’s height for age. Explanatory variables included a composite indicator of maternal employment, household wealth, maternal education, current breastfeeding status and dietary diversity score. Results are presented both in terms of non-standardised and standardised coefficients.Outcome measureThe primary outcome measure was height-for-age Z-scores as a continuous measure.ResultsFindings suggest that children’s dietary diversity and continued breast feeding mediate the association between socioeconomic status and children’s height. While there was no significant direct effect of maternal education on children’s height, results suggested significant indirect pathways through which maternal education effects children’s height; operating through household wealth, maternal employment, dietary diversity and continued breastfeeding status (p&lt;0.001). Most notably, 41% of the effect of maternal employment on children’s height was mediated by either dietary diversity or continued breast feeding.ConclusionWe provide evidence to support targeted nutrition interventions which account for the different ways in which underlying socioeconomic factors influence infant and young child feeding practices, and the potential impact on child nutritional status.</abstract><cop>England</cop><pub>British Medical Journal Publishing Group</pub><pmid>36328394</pmid><doi>10.1136/bmjopen-2021-055853</doi><orcidid>https://orcid.org/0000-0002-3732-2973</orcidid><orcidid>https://orcid.org/0000-0002-6538-9374</orcidid><oa>free_for_read</oa></addata></record>
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subjects Age
Breast Feeding
Breastfeeding & lactation
Cambodia - epidemiology
Child
Children & youth
community child health
Cross-Sectional Studies
Employment
Female
Growth Disorders - epidemiology
Growth Disorders - etiology
Health surveys
Households
Humans
Infant
Infant Nutritional Physiological Phenomena
nutrition
Nutrition and Metabolism
Nutritional Status
Principal components analysis
public health
Rural areas
Social Class
Socioeconomic Factors
Socioeconomic status
Urban areas
Variables
title Maternal socioeconomic status and infant feeding practices underlying pathways to child stunting in Cambodia: structural path analysis using cross-sectional population data
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