Evidence map›Paper›PMID 40379816›Full record

ArticleScientific reports2025

Latent profiles and associated factors of body image in pregnant women.

Yunmei Guo, Zhonglan Tang, Qing Wang, LianHong Wang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

4 authors.

Yunmei GuoNursing Department, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China.
Zhonglan TangNursing Department, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China.
Qing WangNursing Department, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China.
LianHong WangNursing Department, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China. 2726912415@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to investigate the status of body image among pregnant women and identify associated factors using latent profile analysis (LPA). This cross-sectional study was conducted using a convenience sample of 460 pregnant women in the gynecology outpatient clinic of a tertiary hospital in Zunyi between December 2023 and April 2024. Data on body image, demographic characteristics, quality of life, and E-health literacy were collected. Then, multiple stepwise linear regression was conducted to identify risk factors associated with level of maternal body image in the study participants. Lastly, latent profile analysis was used to classify participants based on their body image status. The results of the latent profile analysis revealed that 48% of participants exhibited high level body image dissatisfaction , 44.60% suffered from moderate level body image dissatisfaction , and the remaining 7.30% of patients had low levelbody image dissatisfaction . Additionally, significant differences were observed in scale scores and dimensions among the three categories (both p < 0.001). Finally, multiple regression analysis identified QOL (B = 0.65, p < 0.001), E-health literacy (B = 0.05, p < 0.05), and gestational age (B = -0.01, p < 0.05) as significant factors associated with body image among pregnant women. Body image dissatisfaction is highly prevalent among pregnant women in China. Thus, healthcare providers are recommended to prioritize addressing body image dissatisfaction and develop effective intervention strategies to improve the quality of life and e-health literacy of pregnant women.

Indexed as

Body ImagePregnant PeopleAdultChinaCross-Sectional StudiesFemaleHealth LiteracyHumansPregnancyQuality of LifeRisk FactorsSurveys and QuestionnairesYoung AdultBody imageLatent profile analysisPregnant women

Identifiers

PMID40379816
PMCPMC12084620

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.