Evidence map›Paper›PMID 38745303›Full record

ArticleBMC public health2024

Exploring predictors and prevalence of postpartum depression among mothers: Multinational study.

Samar A Amer, Nahla A Zaitoun, Heba A Abdelsalam, Abdallah Abbas, Mohamed Sh Ramadan, Hassan M Ayal, Samaher Edhah Ahmed Ba-Gais, Nawal Mahboob Basha, Abdulrahman Allahham, Emmanuael Boateng Agyenim and 1 more

RetractedAbstract readRetracted Publication
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Leveraging Machine Learning to Uncover Ethnic-Specific Predictors of Maternal Postpartum Depression.Prevention science : the official journal of the Society for Prevention Research · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Samar A AmerDepartment of Public Health and Community Medicine, Faculty of Medicine, Zagazig University, Zagazig, Egypt. dr_samar11@yahoo.com.ORCID http://orcid.org/0000-0002-9475-6372
Nahla A ZaitounDepartment of Family Medicine, Faculty of Medicine, Zagazig University, Zagazig, Egypt.ORCID http://orcid.org/0000-0002-5274-6061
Heba A AbdelsalamDepartment of Psychiatry, Faculty of Medicine, Zagazig University, Zagazig, Egypt.
Abdallah AbbasFaculty of Medicine, Al-Azhar University, Damietta, Egypt.ORCID http://orcid.org/0000-0001-5101-5972
Mohamed Sh RamadanDepartment of Obstetrics and Gynecology, Faculty of Medicine, Zagazig University, Zagazig, Egypt.
Hassan M AyalHammurabi Medical College, University of Babylon, Al-Diwaniyah, Iraq.
Samaher Edhah Ahmed Ba-GaisHardamout University College of Medicine, Almukalla, Yemen.
Nawal Mahboob BashaDepartment of General Medicine, Shadan Institute of Medical Science, Hyderabad, India.
Abdulrahman AllahhamCollege of Medicine, Sulaiman Alrajhi University, Albukayriah, Al-Qassim, Saudi Arabia.
Emmanuael Boateng AgyenimDepartment of Virology, Noguchi Memorial Institute for Medical Research, University of Ghana Legon, Accra, Ghana.
Walid Amin Al-ShrobyDepartment of Public Health and Community Medicine, Faculty of Medicine, Beni-Suef University, Beni-Suef, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPostpartum depression (PPD) affects around 10% of women, or 1 in 7 women, after giving birth. Undiagnosed PPD was observed among 50% of mothers. PPD has an unfavorable relationship with women's functioning, marital and personal relationships, the quality of the mother-infant connection, and the social, behavioral, and cognitive development of children. We aim to determine the frequency of PPD and explore associated determinants or predictors (demographic, obstetric, infant-related, and psychosocial factors) and coping strategies from June to August 2023 in six countries.

methodsAn analytical cross-sectional study included a total of 674 mothers who visited primary health care centers (PHCs) in Egypt, Yemen, Iraq, India, Ghana, and Syria. They were asked to complete self-administered assessments using the Edinburgh Postnatal Depression Scale (EPDS). The data underwent logistic regression analysis using SPSS-IBM 27 to list potential factors that could predict PPD.

resultsThe overall frequency of PPD in the total sample was 92(13.6%). It ranged from 2.3% in Syria to 26% in Ghana. Only 42 (6.2%) were diagnosed. Multiple logistic regression analysis revealed there were significant predictors of PPD. These factors included having unhealthy baby adjusted odds ratio (aOR) of 11.685, 95% CI: 1.405-97.139, p = 0.023), having a precious baby (aOR 7.717, 95% CI: 1.822-32.689, p = 0.006), who don't receive support (aOR 9.784, 95% CI: 5.373-17.816, p = 0.001), and those who are suffering from PPD. However, being married and comfortable discussing mental health with family relatives are significant protective factors (aOR = 0.141 (95% CI: 0.04-0.494; p = 0.002) and (aOR = 0.369, 95% CI: 0.146-0.933, p = 0.035), respectively.

conclusionThe frequency of PPD among the mothers varied significantly across different countries. PPD has many protective and potential factors. We recommend further research and screenings of PPD for all mothers to promote the well-being of the mothers and create a favorable environment for the newborn and all family members.

Indexed as

Depression, PostpartumMothersAdolescentAdultCross-Sectional StudiesFemaleHumansPrevalenceRisk FactorsYoung AdultDeterminantsPostpartum depressionPsychosocialThe Edinburgh postnatal depression scale (EPDS)

Identifiers

PMID38745303
PMCPMC11092128

What OpenQuestion holds

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Registered trials

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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.