Evidence map›Paper›PMID 40181343›Full record

ArticleBMC public health2025

Socioeconomic inequalities in cervical cancer screening practices in Vietnam: a decomposition analysis.

Thi Bich-Van Nguyen, Kim-Duy Vu, Lam Tung Ngoc Cu, Minh Hai Nguyen Ngoc, Hoang-Dung Ho

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

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

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5 · Who and what money

Authors and funding

5 authors.

Thi Bich-Van NguyenDepartment of Obstetrics and Gynaecology, Hanoi Medical University, Hanoi, Vietnam.
Kim-Duy VuNational Institute of Hygiene and Epidemiology, No. 1 Yersin street, Hanoi, Vietnam. vukimduy99@gmail.com.ORCID http://orcid.org/0000-0003-2376-8621
Lam Tung Ngoc CuNational Institute of Hygiene and Epidemiology, No. 1 Yersin street, Hanoi, Vietnam.ORCID http://orcid.org/0000-0003-1709-8684
Minh Hai Nguyen NgocDepartment of Obstetrics and Gynaecology, Hanoi Medical University, Hanoi, Vietnam.
Hoang-Dung HoNational Institute of Hygiene and Epidemiology, No. 1 Yersin street, Hanoi, Vietnam.ORCID http://orcid.org/0000-0003-2462-5868

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn Vietnam, cervical cancer remains a critical public health issue, with disparities in screening uptake reflecting broader socioeconomic inequalities.

objectiveThis study aims to dissect socioeconomic disparities in cervical cancer screening uptake among Vietnamese women, using data from the 2020-2021 Multiple Indicator Cluster Survey 6 (MICS).

methodsEmploying a cross-sectional design, we analysed MICS Survey data for women's cervical cancer screening reports over the past three years. The study utilised decomposition analysis to unravel the contributions of various determinants to socioeconomic disparities in screening uptake, employing Poisson regression with robust variance models to explore the association between socioeconomic status, quantified through Wealth Index quintiles, and screening practices.

resultsAmong participants, 28.2% reported receiving cervical cancer screening. The positive Erreygers concentration index value (ECI) was overall 0.296, which was statistically significant at a 1% level, indicating that cervical cancer screening was predominantly concentrated among individuals with higher wealth index scores. Decomposition analysis indicated that ethnic minority status significantly contributed to this disparity, alongside factors such as education and residency.

conclusionThe use of the concentration index in this study elucidates significant socioeconomic and ethnic inequalities in cervical cancer screening in Vietnam. It underlines the necessity of tailored interventions aimed at the most disadvantaged groups, including ethnic minorities and low-income populations, to mitigate these disparities. Strategic policy reforms and targeted health initiatives are essential for promoting equitable access to cervical cancer screening and improving public health outcomes across Vietnam.

Indexed as

Early Detection of CancerHealthcare DisparitiesUterine Cervical NeoplasmsAdultCross-Sectional StudiesFemaleHumansMiddle AgedSocioeconomic FactorsSurveys and QuestionnairesVietnamCervical cancer, Screening program, Inequality, Concentration index, Erreygers index

Identifiers

PMID40181343
PMCPMC11966878

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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.