Evidence map›Paper›PMID 38662750›Full record

Observational studyPloS one2024

Prevalence and predictors of prenatal depression during the COVID-19 pandemic: A multistage observational study in Beijing, China.

Jin Wang, Libin Hu, Tianyi Zhang, Jiajia Liu, Chuan Yu, Ningxin Zhao, Jianlin Qi, Lihua Liu

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 91% of its field
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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Jin WangInstitution of Hospital Management, Medical Innovation Research Division of Chinese PLA General Hospital, Beijing, China.
Libin HuInstitution of Hospital Management, Medical Innovation Research Division of Chinese PLA General Hospital, Beijing, China.
Tianyi ZhangInstitution of Hospital Management, Medical Innovation Research Division of Chinese PLA General Hospital, Beijing, China.
Jiajia LiuDepartment of Aviation Psychology, Air Force Medical Center, Air Force Medical University, Beijing, China.
Chuan YuDepartment of Aviation Psychology, Air Force Medical Center, Air Force Medical University, Beijing, China.
Ningxin ZhaoFaculty of Psychology, Beijing Normal University, Beijing, China.
Jianlin QiDepartment of Aviation Psychology, Air Force Medical Center, Air Force Medical University, Beijing, China.
Lihua LiuInstitution of Hospital Management, Medical Innovation Research Division of Chinese PLA General Hospital, Beijing, China.ORCID 0000-0002-3527-4859
Chinese PLA General Hospital · CNAir Force Institute of Aviation Medicine Affiliated Hospital · CNBeijing Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveWhile growing psychological health issues among pregnant women during the COVID-19 pandemic have been clearly validated, most research was conducted in countries with relatively lax quarantine measures. This study aimed to compare the prevalence of prenatal depression among pre-, peak-, and post-COVID-19 in Beijing, the region with a stringent response policy in China. We also explore predictors of prenatal depression throughout the outbreak.

methodsWe investigated prenatal depression among 742 pregnant women who received antenatal checkups in Beijing from March 28, 2019 to May 07, 2021 using the Edinburgh Postnatal Depression Scale and associative demographic, pregnancy-related, and psychosocial characteristics were measured. The phase was divided into pre-, peak-, and post-COVID-19 in light of the trajectory of COVID-19. Pearson's Chi-square test was used after the examination of confounders homogeneity. The bivariable and multivariable logistic regression was conducted to explore predictors.

resultsThe pooled prevalence of prenatal depression was 11.9% throughout the COVID-19 pandemic. Rates at different phases were 10.6%, 15.2%, and 11.1% respectively and no significant difference was observed. Multivariable logistic regression revealed that history of mental illness, number of boy-preference from both pregnant women and husband's family, social support, occupation, and living space were independent predictors of prenatal depression in Beijing.

conclusionOur data suggested that the impact of this pandemic on prenatal depression in Beijing appears to be not significant, which will strengthen confidence in adhering to current policy for decision-makers and provide important guidance for the development of major outbreak control and management policies in the future. Our findings may also provide a more efficient measure to identify high-risk pregnant women for professionals and help raise gender equity awareness of pregnant women and their husbands' families. Future studies should focus on the value of targeted care and family relations on the mental health of pregnant women.

Indexed as

COVID-19DepressionAdultBeijingChinaFemaleHumansPandemicsPregnancyPregnancy ComplicationsPregnant PeoplePrevalenceSARS-CoV-2Young Adult

Identifiers

PMID38662750
PMCPMC11045078
OpenAlexW4395479000

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.