ArticleBMC public health2021
Postpartum depression symptoms in survey-based research: a structural equation analysis.
Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 4 of them syntheses that pooled it.
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Who cites it
29 citing papers in PubMed, 4 syntheses or guidelines pooled it, 57 citations in OpenAlex.
- Parental Postnatal Depression in the Time of the COVID-19 Pandemic: A Systematic Review of Its Effects on the Parent-Child Relationship and the Child's Developmental Outcomes.International journal of environmental research and public health · 2023Pooled it
- Nutritional factors and cross-national postpartum depression prevalence: an updated meta-analysis and meta-regression of 412 studies from 46 countries.Frontiers in psychiatry · 2023Pooled it
- Association between depressive symptoms in the postpartum period and COVID-19: A meta-analysis.Journal of affective disorders · 2023Pooled it
- Prevalence and Risk Factors Associated with Postpartum Depression during the COVID-19 Pandemic: A Literature Review and Meta-Analysis.International journal of environmental research and public health · 2022Pooled it
- A group psychological intervention for postnatal depression in British mothers of South Asian origin - the ROSHNI-2 RCT.Health technology assessment (Winchester, England) · 2025Trial
- Effect of esketamine on postpartum depression after labor analgesia and potential mechanisms: a randomized, double-blinded controlled trial.BMC anesthesiology · 2024Trial
- Exploratory RCT of a group psychological intervention for postnatal depression in British mothers of South Asian origin - ROSHNI-D.Acta psychologica · 2023Trial
- The effectiveness of an internet-based support program on maternal self-efficacy, postpartum depression and social support for primiparous women during the COVID-19 pandemic: Randomized controlled trial.Frontiers in public health · 2023Trial
- Review
- Understanding mothers' lived experiences of postpartum depression: a qualitative phenomenological study.BMC pregnancy and childbirth · 2025Article
- Frequency and Correlates of Depressive Symptoms Among Postpartum Mothers: A Cross-sectional, Community-based Study.Indian journal of psychological medicine · 2025Article
- Empowering postpartum women: the role of mHealth apps in promoting mental health and obesity prevention.BMC women's health · 2025Article
- Comparative Effectiveness of Non-Pharmacological Interventions for Postpartum Depression and Anxiety: A Network Meta-Analysis.Neuropsychiatric disease and treatment · 2025Review
- Associations among mental well-being, marital quality, and maternal depressive symptoms in China: a cross - sectional study and mediated analysis.Frontiers in psychiatry · 2025Article
- Using YouTube Comments Data to Explore Postpartum Depression in Social Media: An Infodemiology Study.International journal of environmental research and public health · 2024Article
- The prevalence and related factors of post-partum anxiety and depression among mothers during COVID-19 pandemic in 2021.BMC public health · 2024Article
- The Impact of the COVID-19 Pandemic on Depressive Disorder with Postpartum Onset: A Cross-Sectional Study.Healthcare (Basel, Switzerland) · 2023Article
- Excessive gestational weight gain and emotional eating are positively associated with postpartum depressive symptoms among taiwanese women.BMC women's health · 2023Article
- Dairy products intake and the risk of postpartum depression among mothers: A pilot study.SAGE open medicine · 2023Article
- Coffee and caffeine intake and depression in postpartum women: A cross-sectional study from the National Health and Nutrition Examination Survey 2007-2018.Frontiers in psychology · 2023Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundSince the last decade, postpartum depression (PPD) has been recognized as a significant public health problem, and several factors have been linked to PPD. Mothers at risk are rarely undetected and underdiagnosed. Our study aims to determine the factors leading to symptoms of depression using Structural Equation Modeling (SEM) analysis. In this research, we introduced a new framework for postpartum depression modeling for women.
methodsWe structured the model of this research to take into consideration the Malaysian culture in particular. A total of 387 postpartum women have completed the questionnaire. The symptoms of postpartum depression were examined using the Edinburgh Postnatal Depression Scale (EPDS), and they act as a dependent variable in this research model.
resultsFour hundred fifty mothers were invited to participate in this research. 86% of the total distributed questionnaire received feedback. The majority of 79.6% of respondents were having depression symptoms. The highest coefficients of factor loading analysis obtained in every latent variable indicator were income (β = 0.77), screen time (β = 0.83), chips (β = 0.85), and anxiety (β = 0.88). Lifestyle, unhealthy food, and BMI variables were directly affected by the dependent variable. Based on the output, respondents with a high level of depression symptoms tended to consume more unhealthy food and had a high level of body mass indexes (BMI). The highest significant impact on depression level among postpartum women was unhealthy food consumption. Based on our model, the findings indicated that 76% of the variances stemmed from a variety of factors: socio-demographics, lifestyle, healthy food, unhealthy food, and BMI. The strength of the exogenous and endogenous variables in this research framework is strong.
conclusionThe prevalence of postpartum women with depression symptoms in this study is considerably high. It is, therefore, imperative that postpartum women seek medical help to prevent postpartum depressive symptoms from worsening.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.