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Psychosocial stratification of antenatal indicators to guide population-based programs in perinatal depression

BACKGROUND: There is increasing awareness that perinatal psychosocial adversity experienced by mothers, children, and their families, may influence health and well-being across the life course. To maximise the impact of population-based interventions for optimising perinatal wellbeing, health servic...

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Autores principales: John Eastwood, E. D., Wang, Andy, Khanlari, Sarah, Montgomery, Alicia, Yang, Jean Yee Hwa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8025384/
https://www.ncbi.nlm.nih.gov/pubmed/33823838
http://dx.doi.org/10.1186/s12884-021-03722-8
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author John Eastwood, E. D.
Wang, Andy
Khanlari, Sarah
Montgomery, Alicia
Yang, Jean Yee Hwa
author_facet John Eastwood, E. D.
Wang, Andy
Khanlari, Sarah
Montgomery, Alicia
Yang, Jean Yee Hwa
author_sort John Eastwood, E. D.
collection PubMed
description BACKGROUND: There is increasing awareness that perinatal psychosocial adversity experienced by mothers, children, and their families, may influence health and well-being across the life course. To maximise the impact of population-based interventions for optimising perinatal wellbeing, health services can utilise empirical methods to identify subgroups at highest risk of poor outcomes relative to the overall population. METHODS: This study sought to identify sub-groups using latent class analysis within a population of mothers in Sydney, Australia, based on their differing experience of self-reported indicators of psychosocial adversity. This study sought to identify sub-groups using latent class analysis within a population of mothers in Sydney, Australia, based on their differing experience of self-reported indicators of psychosocial adversity. Subgroup differences in antenatal and postnatal depressive symptoms were assessed using the Edinburgh Postnatal Depression Scale. RESULTS: Latent class analysis identified four distinct subgroups within the cohort, who were distinguished empirically on the basis of their native language, current smoking status, previous involvement with Family-and-Community Services (FaCS), history of child abuse, presence of a supportive partner, and a history of intimate partner psychological violence. One group consisted of socially supported ‘local’ women who speak English as their primary language (Group L), another of socially supported ‘migrant’ women who speak a language other than English as their primary language (Group M), another of socially stressed ‘local’ women who speak English as their primary language (Group Ls), and socially stressed ‘migrant’ women who speak a language other than English as their primary language (Group Ms.). Compared to local and not socially stressed residents (L group), the odds of antenatal depression were nearly three times higher for the socially stressed groups (Ls OR: 2.87 95%CI 2.10–3.94) and nearly nine times more in the Ms. group (Ms OR: 8.78, 95%CI 5.13–15.03). Antenatal symptoms of depression were also higher in the not socially stressed migrant group (M OR: 1.70 95%CI 1.47–1.97) compared to non-migrants. In the postnatal period, Group M was 1.5 times more likely, while the Ms. group was over five times more likely to experience suboptimal mental health compared to Group L (OR 1.50, 95%CI 1.22–1.84; and OR 5.28, 95%CI 2.63–10.63, for M and Ms. respectively). CONCLUSIONS: The application of empirical subgrouping analysis permits an informed approach to targeted interventions and resource allocation for optimising perinatal maternal wellbeing.
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spelling pubmed-80253842021-04-07 Psychosocial stratification of antenatal indicators to guide population-based programs in perinatal depression John Eastwood, E. D. Wang, Andy Khanlari, Sarah Montgomery, Alicia Yang, Jean Yee Hwa BMC Pregnancy Childbirth Research Article BACKGROUND: There is increasing awareness that perinatal psychosocial adversity experienced by mothers, children, and their families, may influence health and well-being across the life course. To maximise the impact of population-based interventions for optimising perinatal wellbeing, health services can utilise empirical methods to identify subgroups at highest risk of poor outcomes relative to the overall population. METHODS: This study sought to identify sub-groups using latent class analysis within a population of mothers in Sydney, Australia, based on their differing experience of self-reported indicators of psychosocial adversity. This study sought to identify sub-groups using latent class analysis within a population of mothers in Sydney, Australia, based on their differing experience of self-reported indicators of psychosocial adversity. Subgroup differences in antenatal and postnatal depressive symptoms were assessed using the Edinburgh Postnatal Depression Scale. RESULTS: Latent class analysis identified four distinct subgroups within the cohort, who were distinguished empirically on the basis of their native language, current smoking status, previous involvement with Family-and-Community Services (FaCS), history of child abuse, presence of a supportive partner, and a history of intimate partner psychological violence. One group consisted of socially supported ‘local’ women who speak English as their primary language (Group L), another of socially supported ‘migrant’ women who speak a language other than English as their primary language (Group M), another of socially stressed ‘local’ women who speak English as their primary language (Group Ls), and socially stressed ‘migrant’ women who speak a language other than English as their primary language (Group Ms.). Compared to local and not socially stressed residents (L group), the odds of antenatal depression were nearly three times higher for the socially stressed groups (Ls OR: 2.87 95%CI 2.10–3.94) and nearly nine times more in the Ms. group (Ms OR: 8.78, 95%CI 5.13–15.03). Antenatal symptoms of depression were also higher in the not socially stressed migrant group (M OR: 1.70 95%CI 1.47–1.97) compared to non-migrants. In the postnatal period, Group M was 1.5 times more likely, while the Ms. group was over five times more likely to experience suboptimal mental health compared to Group L (OR 1.50, 95%CI 1.22–1.84; and OR 5.28, 95%CI 2.63–10.63, for M and Ms. respectively). CONCLUSIONS: The application of empirical subgrouping analysis permits an informed approach to targeted interventions and resource allocation for optimising perinatal maternal wellbeing. BioMed Central 2021-04-06 /pmc/articles/PMC8025384/ /pubmed/33823838 http://dx.doi.org/10.1186/s12884-021-03722-8 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
John Eastwood, E. D.
Wang, Andy
Khanlari, Sarah
Montgomery, Alicia
Yang, Jean Yee Hwa
Psychosocial stratification of antenatal indicators to guide population-based programs in perinatal depression
title Psychosocial stratification of antenatal indicators to guide population-based programs in perinatal depression
title_full Psychosocial stratification of antenatal indicators to guide population-based programs in perinatal depression
title_fullStr Psychosocial stratification of antenatal indicators to guide population-based programs in perinatal depression
title_full_unstemmed Psychosocial stratification of antenatal indicators to guide population-based programs in perinatal depression
title_short Psychosocial stratification of antenatal indicators to guide population-based programs in perinatal depression
title_sort psychosocial stratification of antenatal indicators to guide population-based programs in perinatal depression
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8025384/
https://www.ncbi.nlm.nih.gov/pubmed/33823838
http://dx.doi.org/10.1186/s12884-021-03722-8
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