Prevalence and predictors of depression, anxiety and stress symptoms among pregnant women during COVID-19-related lockdown in Abakaliki, Nigeria

  1. Johnbosco I. Nwafor
  2. Ijeoma N. Okedo-Alex
  3. Arinze C. Ikeotuonye

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Abstract

Introduction

Several studies on COVID-19 and pregnancy have been published recently, but few studies have evaluated the impact of this pandemic on maternal mental health particularly in low-resource setting.

Aim

To determine the prevalence and predictors of COVID-19-related depression, anxiety and stress symptoms among pregnant women.

Materials and methods

This was a questionnaire-based cross-sectional study conducted among 456 pregnant women attending prenatal care at Abakaliki, Nigeria during COVID-19-related lockdown. They were screened for psychological morbidities using DASS 21 (Depression, Anxiety and Stress Scale).

Results

Severe and extremely severe depression were reported in 33 (7.2%) and 29 (6.4%) participants respectively. 15 (3.3%) and 35 (7.7%) women had severe and extremely severe anxiety respectively. 105 (23%) had severe anxiety whereas 76 (16.7%) reported extremely severe stress. Multiparity (2 - 4) and occupations such as trading and farming were predictors of depression whereas grandmultiparity, urban residence and trading were identified as predictors of anxiety and stress.

Conclusion

Depression, anxiety and stress symptoms were relatively common among pregnant women during COVID-19-related lockdown in Abakaliki, Nigeria. There is a need to integrate screening for depression, anxiety and stress in existing antenatal care programs so as to identify and prevent long term adverse psychological outcome related to COVID-19 pandemic.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.30.20184697: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: Women who gave consent to participate in the study were included.
    IRB: Ethical considerations: This study was approved by the Research and Ethics Committee of the Alex Ekwueme Federal University Teaching Hospital, Abakaliki.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variable10 Study participants and criteria: The study participants were pregnant women attending prenatal care at the study facility during the study period.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The collected data were entered and analyzed using SPSS version 22 (IBM Corp.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    This study has a limitation. It is a single centre study that cannot be considered representative of the population of pregnant women in Nigeria during the lockdown period. A multicentre study would have improved the generalization of the study findings. Despite this limitation, this is a timely study and reflects the psychological distress of pregnant women in the face of the spread of COVID-19. In conclusion, a significant proportion of pregnant women had psychological symptoms of depression, anxiety and stress during COVID-19-related lockdown in Nigeria. There is a need to pay special attention to vulnerable populations, such as pregnant women, so as to prevent long term adverse psychological outcome that may result from COVID-19 pandemic.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.08.30.20184697v1 on medRxiv