Evidence map›Paper›PMID 36276386›Full record

ArticleFrontiers in public health2022

The impact of COVID-19 on the mental health of pregnant women in Shanghai, China.

Jiali Zhang, Hualong Yuan, Liping Xu, Chuntao Yi, Weiming Tang

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In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Jiali ZhangFenglin Community Health Service Center, Shanghai, China.
Hualong YuanFenglin Community Health Service Center, Shanghai, China.
Liping XuFenglin Community Health Service Center, Shanghai, China.
Chuntao YiFenglin Community Health Service Center, Shanghai, China.
Weiming TangGuangdong No. 2 Provincial People's Hospital, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: COVID-19 has dramatically impacted people's health, especially mental health. This study aimed to compare the psychological status of pregnant women before and after the COVID-19 outbreak. Methods: Participants were recruited (from September 29, 2019, to November 5, 2020) and screened by the Patient Health Questionnaire (PHQ-9) and the Generalized Anxiety Disorder Scale (GAD-7). The study participants were categorized into three groups based on two turning-points: January 23, 2020, when China initiated a locked-down strategy, and May 11, 2020, when Shanghai started to ease the COVID-19 measures. Multivariable logistic regression was used to determine the factors associated with depression and anxiety in pregnant women. We used enter method for variable selection; only variables with Results: We recruited 478 pregnant women. After the outbreak, the depression rate (PHQ-9 ≥ 5) increased by 12.3% (from 35.4 to 47.7%), and the anxiety rate (GAD-7 ≥ 5) was stable (13.3 vs. 16.2%). The multivariable logistic regression results further confirmed that the odds of depression in pregnant women increased 81% after the outbreak (aOR = 1.81, 95%CI: 1.16-2.84). However, the median depression scale score was still statistically higher after the pandemic situation was stable (5.0 vs. 4.0) compared to the outbreak period. Conclusion: The depression rate increased among pregnant women after the outbreak and was not recovered after the ease of COVID-19 measures in Shanghai. Health institutes should pay attention to the long-term influence of the pandemic.

Indexed as

COVID-19ChinaDepressionFemaleHumansMental HealthPregnancyPregnant PeopleSARS-CoV-2anxietyChinaCOVID-19depressionpregnant women

Identifiers

PMID36276386
PMCPMC9583156

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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.