Evidence map›Paper›PMID 41132182›Full record

SynthesisFrontiers in public health2025

The association between body image and depressive symptoms in pregnant and postpartum women: a meta-analysis.

Jingbo He, Xin Chen, Biru Luo

Abstract readMeta-Analysis
In one paragraph

Synthesis in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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

3 authors.

Jingbo HeDepartment of Nursing, West China Second University Hospital, Sichuan University/ West China School of Nursing, Sichuan University, Chengdu, Sichuan, China.
Xin ChenKey Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan, China.
Biru LuoDepartment of Nursing, West China Second University Hospital, Sichuan University/ West China School of Nursing, Sichuan University, Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Body image is an individual's internal representation of physical appearance. Perinatal depression, a psychological condition with severe implications, is influenced by body dissatisfaction. However, no studies have systematically quantified their association. Objective: To evaluate the correlation between body image and depressive symptoms in the perinatal period through meta-analysis. Methods: A systematic search was conducted in PubMed, Embase, The Cochrane Library, Medline, CNKI, Wanfang, and VIP databases, and studies assessing body image and perinatal depression were included. Two researchers independently screened, extracted, and assessed study quality. Meta-analysis used Review Manager 5.4, with the correlation coefficient (r) as the effect size, and studies assessing body image and perinatal depression were included. Results: Twenty-eight studies involving 7,241 women were included. For pregnancy, the summary r for the reverse and forward scoring groups was 0.34 (95% CI: 0.24, 0.44; Conclusion: Body dissatisfaction is consistently and moderately associated with perinatal depression. Early identification and interventions may help prevent depression and improve maternal-infant health outcomes. Systematic review registration: PROSPERO, identifier CRD42025639158, https://www.crd.york.ac.uk/PROSPERO/view/CRD42025639158.

Indexed as

Body ImageDepressionDepression, PostpartumPostpartum PeriodPregnant PeopleAdultFemaleHumansPregnancybody dissatisfactionbody imagedepressionpostpartum periodpregnancy

Identifiers

PMID41132182
PMCPMC12540066

What OpenQuestion holds

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LicenceCC BY
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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.