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Estimating the population impact of hypothetical breastfeeding interventions in a low-income population in Los Angeles County: An agent-based model

BACKGROUND: Breastfeeding has clear benefits. Yet, breastfeeding practices fall short of recommendations in low-income populations including participants of the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). To promote breastfeeding, it is important to understand brea...

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Autores principales: Jiang, Linghui, Li, Xiaoyan, Wang, May C., Osgood, Nathaniel, Whaley, Shannon E., Crespi, Catherine M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145098/
https://www.ncbi.nlm.nih.gov/pubmed/32271798
http://dx.doi.org/10.1371/journal.pone.0231134
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author Jiang, Linghui
Li, Xiaoyan
Wang, May C.
Osgood, Nathaniel
Whaley, Shannon E.
Crespi, Catherine M.
author_facet Jiang, Linghui
Li, Xiaoyan
Wang, May C.
Osgood, Nathaniel
Whaley, Shannon E.
Crespi, Catherine M.
author_sort Jiang, Linghui
collection PubMed
description BACKGROUND: Breastfeeding has clear benefits. Yet, breastfeeding practices fall short of recommendations in low-income populations including participants of the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). To promote breastfeeding, it is important to understand breastfeeding-related behaviors such as initiation and maintenance within the context of a complex societal system. For individual women, making choices about infant feeding (whether to breastfeed or formula-feed a newborn, or when to stop breastfeeding) is a dynamic process involving interactions with health professionals, family, peers and workplaces. Integrating behavioral change theories with systems science tools such as agent-based modeling can help illuminate patterns of breastfeeding behaviors, identify key factors affecting breastfeeding behaviors within this complex dynamic system, and estimate the population impact of hypothetical interventions. METHODS: An agent-based model (ABM) was developed to investigate the influences of multiple levels of factors affecting breastfeeding behaviors among WIC participants. Health behavioral change theories were applied and stakeholder input obtained to improve the model, particularly during the conceptual design and model specification steps. The model was then used to identify critical points for intervention and assess the effects of five common interventions (improving knowledge through education, implementing Baby-Friendly Hospital Initiative practices, providing postpartum breastfeeding counselling, strengthening partner support, and fostering supportive workplace environments.) RESULTS: The ABM developed in this study produced outcomes (i.e., breastfeeding rates) that were concordant with empirical data. Increasing the coverage of the five selected interventions produced various levels of improvement in breastfeeding practices in the target population. Specifically, improving breastfeeding knowledge had a positive impact on women’s intent to breastfeed, while increasing the availability of the Baby-Friendly Hospital Initiative improved breastfeeding initiation rates. However, neither of these two interventions showed a significant impact on breastfeeding maintenance, which was supported by postpartum breastfeeding counseling, partner support and a supportive workplace environment. These three intervention strategies each improved breastfeeding rates at 6 months from 55.6% to 57.1%, 59.5% and 59.3%, respectively. Increasing the coverage of multiple interventions simultaneously had a synergistic effect on breastfeeding maintenance with their effects being greater than the cumulative effects of increasing the coverage of these interventions individually. CONCLUSION: The ABM we developed was helpful for understanding the dynamic process of decision-making regarding infant feeding modalities in a low-income population, and for evaluating the aggregated population-level impact of breastfeeding promotion interventions.
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spelling pubmed-71450982020-04-14 Estimating the population impact of hypothetical breastfeeding interventions in a low-income population in Los Angeles County: An agent-based model Jiang, Linghui Li, Xiaoyan Wang, May C. Osgood, Nathaniel Whaley, Shannon E. Crespi, Catherine M. PLoS One Research Article BACKGROUND: Breastfeeding has clear benefits. Yet, breastfeeding practices fall short of recommendations in low-income populations including participants of the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). To promote breastfeeding, it is important to understand breastfeeding-related behaviors such as initiation and maintenance within the context of a complex societal system. For individual women, making choices about infant feeding (whether to breastfeed or formula-feed a newborn, or when to stop breastfeeding) is a dynamic process involving interactions with health professionals, family, peers and workplaces. Integrating behavioral change theories with systems science tools such as agent-based modeling can help illuminate patterns of breastfeeding behaviors, identify key factors affecting breastfeeding behaviors within this complex dynamic system, and estimate the population impact of hypothetical interventions. METHODS: An agent-based model (ABM) was developed to investigate the influences of multiple levels of factors affecting breastfeeding behaviors among WIC participants. Health behavioral change theories were applied and stakeholder input obtained to improve the model, particularly during the conceptual design and model specification steps. The model was then used to identify critical points for intervention and assess the effects of five common interventions (improving knowledge through education, implementing Baby-Friendly Hospital Initiative practices, providing postpartum breastfeeding counselling, strengthening partner support, and fostering supportive workplace environments.) RESULTS: The ABM developed in this study produced outcomes (i.e., breastfeeding rates) that were concordant with empirical data. Increasing the coverage of the five selected interventions produced various levels of improvement in breastfeeding practices in the target population. Specifically, improving breastfeeding knowledge had a positive impact on women’s intent to breastfeed, while increasing the availability of the Baby-Friendly Hospital Initiative improved breastfeeding initiation rates. However, neither of these two interventions showed a significant impact on breastfeeding maintenance, which was supported by postpartum breastfeeding counseling, partner support and a supportive workplace environment. These three intervention strategies each improved breastfeeding rates at 6 months from 55.6% to 57.1%, 59.5% and 59.3%, respectively. Increasing the coverage of multiple interventions simultaneously had a synergistic effect on breastfeeding maintenance with their effects being greater than the cumulative effects of increasing the coverage of these interventions individually. CONCLUSION: The ABM we developed was helpful for understanding the dynamic process of decision-making regarding infant feeding modalities in a low-income population, and for evaluating the aggregated population-level impact of breastfeeding promotion interventions. Public Library of Science 2020-04-09 /pmc/articles/PMC7145098/ /pubmed/32271798 http://dx.doi.org/10.1371/journal.pone.0231134 Text en © 2020 Jiang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Jiang, Linghui
Li, Xiaoyan
Wang, May C.
Osgood, Nathaniel
Whaley, Shannon E.
Crespi, Catherine M.
Estimating the population impact of hypothetical breastfeeding interventions in a low-income population in Los Angeles County: An agent-based model
title Estimating the population impact of hypothetical breastfeeding interventions in a low-income population in Los Angeles County: An agent-based model
title_full Estimating the population impact of hypothetical breastfeeding interventions in a low-income population in Los Angeles County: An agent-based model
title_fullStr Estimating the population impact of hypothetical breastfeeding interventions in a low-income population in Los Angeles County: An agent-based model
title_full_unstemmed Estimating the population impact of hypothetical breastfeeding interventions in a low-income population in Los Angeles County: An agent-based model
title_short Estimating the population impact of hypothetical breastfeeding interventions in a low-income population in Los Angeles County: An agent-based model
title_sort estimating the population impact of hypothetical breastfeeding interventions in a low-income population in los angeles county: an agent-based model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145098/
https://www.ncbi.nlm.nih.gov/pubmed/32271798
http://dx.doi.org/10.1371/journal.pone.0231134
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