Dataset Information

Mental health of pregnant and postpartum women during the third wave of the COVID-19 pandemic: a European cross-sectional study.

ABSTRACT:

Objective

To describe the mental health of perinatal women in five European countries during the third pandemic wave and identify risk factors related to depressive and anxiety symptoms.

Design

A cross-sectional, online survey-based study.

Setting

Belgium, Norway, Switzerland, the Netherlands and the UK, 10 June 2021-22 August 2021.

Participants

Pregnant and up to 3 months postpartum women, older than 18 years of age.

Primary outcome measure

The Edinburgh Depression Scale (EDS) and the Generalised Anxiety Disorder scale (GAD-7) were used to assess mental health status. Univariate and multivariate generalised linear models were performed to identify factors associated with poor mental health.

Results

5210 women participated (including 3411 pregnant and 1799 postpartum women). The prevalence of major depressive symptoms (EDS ≥13) was 16.1% in the pregnancy group and 17.0% in the postpartum . Moderate to severe generalised anxiety symptoms (GAD ≥10) were found among 17.3% of the pregnant and 17.7% of the postpartum women. Risk factors associated with poor mental health included having a pre-existing mental illness, a chronic somatic illness, having had COVID-19 or its symptoms, smoking, unplanned pregnancy and country of residence. Among COVID-19 restrictive measures specific to perinatal care, pregnant and postpartum women were most anxious about not having their partner present at the time of delivery, that their partner had to leave the hospital early and to be separated from their newborn after the delivery.

Conclusion

Approximately one in six pregnant or postpartum women reported major depression or anxiety symptoms during the third wave of the pandemic. These findings suggest a continued need to monitor depression and anxiety in pregnancy and postpartum populations throughout and in the wake of the pandemic. Tailored support and counselling are essential to reduce the burden of the pandemic on perinatal and infant mental health.

SUBMITTER: Tauqeer F

PROVIDER: S-EPMC9835449 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Mental health of pregnant and postpartum women during the third wave of the COVID-19 pandemic: a European cross-sectional study.

Tauqeer Fatima F Ceulemans Michael M Gerbier Eva E Passier Anneke A Oliver Alison A Foulon Veerle V Panchaud Alice A Lupattelli Angela A Nordeng Hedvig H

BMJ open 20230111 1

<h4>Objective</h4>To describe the mental health of perinatal women in five European countries during the third pandemic wave and identify risk factors related to depressive and anxiety symptoms.<h4>Design</h4>A cross-sectional, online survey-based study.<h4>Setting</h4>Belgium, Norway, Switzerland, the Netherlands and the UK, 10 June 2021-22 August 2021.<h4>Participants</h4>Pregnant and up to 3 months postpartum women, older than 18 years of age.<h4>Primary outcome measure</h4>The Edinburgh Depr ...[more]

PMID: 36631239

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Project description:IntroductionEvidence on perinatal mental health during the coronavirus disease 2019 (COVID-19) pandemic and its potential determinants is limited. Therefore, this multinational study aimed to assess the mental health status of pregnant and breastfeeding women during the pandemic, and to explore potential associations between depressive symptoms, anxiety, and stress and women's sociodemographic, health, and reproductive characteristics.Material and methodsA cross-sectional, web-based study was performed in Ireland, Norway, Switzerland, the Netherlands, and the UK between 16 June and 14 July 2020. Pregnant and breastfeeding women up to 3 months postpartum who were older than 18 years of age were eligible. The online, anonymous survey was promoted through social media and hospital websites. The Edinburgh Depression Scale (EDS), the Generalized Anxiety Disorder seven-item scale (GAD-7), and the Perceived Stress Scale (PSS) were used to assess mental health status. Regression model analysis was used to identify factors associated with poor mental health status.ResultsIn total, 9041 women participated (including 3907 pregnant and 5134 breastfeeding women). The prevalence of major depressive symptoms (EDS ≥ 13) was 15% in the pregnancy cohort and and 13% the breastfeeding cohort. Moderate to severe generalized anxiety symptoms (GAD ≥ 10) were found among 11% and 10% of the pregnant and breastfeeding women. The mean (±SD) PSS scores for pregnant and breastfeeding women were 14.1 ± 6.6 and 13.7 ± 6.6, respectively. Risk factors associated with poor mental health included having a chronic mental illness, a chronic somatic illness in the postpartum period, smoking, having an unplanned pregnancy, professional status, and living in the UK or Ireland.ConclusionsThis multinational study found high levels of depressive symptoms and generalized anxiety among pregnant and breastfeeding women during the COVID-19 outbreak. The study findings underline the importance of monitoring perinatal mental health during pandemics and other societal crises to safeguard maternal and infant mental health.

Project description:BackgroundThe COVID-19 pandemic has contributed to unprecedented worries and challenges for pregnant women due to social restrictions and changes in maternity care provision. We aimed to investigate the mental health impact of COVID-19 pandemic on pregnant women in Sweden and explore factors associated with poor perinatal mental health in this specific context.MethodThis was a nation-wide cross-sectional survey of pregnant women living in Sweden. Validated questionnaires were distributed through non-profit organizations´ websites and social media channels from May 2020 to February 2021. Perinatal depression, anxiety, and acute stress reaction were assessed using the Edinburgh Postnatal Depression Scale (EPDS), Generalized Anxiety Disorder-7 (GAD-7) and Impact Event Scale (Revised) (IES-R), respectively. Sociodemographic characteristics and self-perceived mental well-being were also obtained. Factors associated with mental health outcomes were analyzed using multivariate logistic regression model.ResultsAmong a total of 470 participants, 43.2% (n = 203) reported depression (EPDS ≥13), 25.7% (n = 121) moderate to severe anxiety (GAD-7 score ≥ 10), and 23.7% (n = 110) moderate to severe acute stress reaction (IES-R ≥ 33). 27.4% participants (n = 129) expressed concerns regarding their mental well-being during the pandemic. Pregnant mothers who had sick family members reported poorer mental health outcomes than those who did not (median [Interquartile range (IQR)] EPDS scores: 14.0 [8.75-18.0] vs 11.0 [6.25-15.0], p < .001; median (IQR) GAD7 scores: 7.0 [4.0-12.25] vs 6.0 [3.0-9.0], p = .003); median (IQR) IES-R scores: 20.0 [9.0-38.0] vs 15.0 [7.0-30.0], p = .048). Logistic regression analyses revealed that risk factors for poor mental health outcomes were having a sick family member with any illness, unemployment, and experiencing a substantially stressful life event. Having a higher educational level and a younger age during the pandemic were protective.ConclusionDepression and anxiety were highly prevalent among pregnant women in Sweden during the COVID-19 pandemic, indicating a need for professional mental health support for this vulnerable group of population. Unemployment was an associated risk factor whereas younger age and higher educational level were protective suggesting an important role of socio-economic factors in modulating the impact of COVID-19 pandemic on perinatal mental health.

Project description:Background: Maternal depression and anxiety are significant public health concerns that play an important role in the health and well-being of mothers and children. The COVID-19 pandemic, the consequential lockdowns and related safety restrictions worldwide negatively affected the mental health of pregnant and postpartum women. Methods: This regional study aimed to develop a machine learning (ML) model for the prediction of maternal depression and anxiety. The study used a dataset collected from five Arab countries during the COVID-19 pandemic between July to December 2020. The population sample included 3569 women (1939 pregnant and 1630 postpartum) from five countries (Jordan, Palestine, Lebanon, Saudi Arabia, and Bahrain). The performance of seven machine learning algorithms was assessed for the prediction of depression and anxiety symptoms. Results: The Gradient Boosting (GB) and Random Forest (RF) models outperformed other studied ML algorithms with accuracy values of 83.3% and 83.2% for depression, respectively, and values of 82.9% and 81.3% for anxiety, respectively. The Mathew's Correlation Coefficient was evaluated for the ML models; the Naïve Bayes (NB) and GB models presented the highest performance measures (0.63 and 0.59) for depression and (0.74 and 0.73) for anxiety, respectively. The features' importance ranking was evaluated, the results showed that stress during pregnancy, family support, financial issues, income, and social support were the most significant values in predicting anxiety and depression. Conclusion: Overall, the study evidenced the power of ML models in predicting maternal depression and anxiety and proved to be an efficient tool for identifying and predicting the associated risk factors that influence maternal mental health. The deployment of machine learning models for screening and early detection of depression and anxiety among pregnant and postpartum women might facilitate the development of health prevention and intervention programs that will enhance maternal and child health in low- and middle-income countries.

Dataset Information

Mental health of pregnant and postpartum women during the third wave of the COVID-19 pandemic: a European cross-sectional study.

Objective

Design

Setting

Participants

Primary outcome measure

Results

Conclusion

Publications

Mental health of pregnant and postpartum women during the third wave of the COVID-19 pandemic: a European cross-sectional study.

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