Document Detail

Identifying predictors of the reasons women give for choosing to breastfeed.
MedLine Citation:
PMID:  17991799     Owner:  NLM     Status:  MEDLINE    
The aims of this article are to outline the reasons Australian women give for initiating breastfeeding, identify unique predictors for these reasons, and use principal components factor analysis to determine factors that influence a woman's decision to breastfeed. Data were collected as part of a large longitudinal study investigating the breastfeeding behaviors and supports of women in Southern Queensland, Australia. The most common reason women (N = 562) gave for deciding to breastfeed was breast milk is better for my baby (95.5%). Reasons related to the mother such as breastfeeding is more convenient (84.3%) were also popular. Four significant components-mother-related reasons, health effects for the infant, moral and family influences, and advice from others-were determined after principal components factor analysis. As well as health benefits for the infant, convenience and other reasons related to the mother appear to be important factors in an Australian woman's decision to breastfeed.
Wendy Brodribb; Anthony Bruce Fallon; Desley Hegney; Maxine O'Brien
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of human lactation : official journal of International Lactation Consultant Association     Volume:  23     ISSN:  0890-3344     ISO Abbreviation:  J Hum Lact     Publication Date:  2007 Nov 
Date Detail:
Created Date:  2007-11-09     Completed Date:  2007-12-17     Revised Date:  2008-11-21    
Medline Journal Info:
Nlm Unique ID:  8709498     Medline TA:  J Hum Lact     Country:  United States    
Other Details:
Languages:  eng     Pagination:  338-44     Citation Subset:  N    
University of Queensland, Brisbane, Australia.
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MeSH Terms
Breast Feeding / epidemiology,  psychology*
Decision Making
Infant Nutritional Physiological Phenomena*
Infant, Newborn
Longitudinal Studies
Maternal Behavior
Mothers / psychology*
Principal Component Analysis

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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