Evidence map›Paper›PMID 42246375›Full record

SynthesisJournal of global health2026

Correlates of hysterectomy in low- and middle-income countries: a systematic review.

Jesty Saira Varghese, Sapna Desai, Sisir Debnath, Sourabh Bikas Paul, Gita D Mishra

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of global health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing 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

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Jesty Saira VargheseUniversity of Queensland - Indian Institute of Technology Delhi (UQ-IITD) Research Academy, Hauz Khas, New Delhi, India.
Sapna DesaiPopulation Council Institute, New Delhi, India.
Sisir DebnathDepartment of Humanities and Social Sciences, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India.
Sourabh Bikas PaulDepartment of Humanities and Social Sciences, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India.
Gita D MishraAustralian Women and Girls' Health Research Centre, School of Public Health, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Brisbane, Queensland, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hysterectomies for benign conditions have declined in recent decades in most high-income countries (HICs); however, it remains a common surgical procedure among women of reproductive age in low- and middle-income countries (LMICs). Although an expanding body of evidence has examined the factors associated with hysterectomy in HICs, evidence remains limited in LMICs. Therefore, we systematically reviewed and synthesised the existing evidence on correlates of hysterectomy in LMICs. Methods: We comprehensively searched PubMed, Embase, CINAHL, Scopus, and Web of Science for eligible studies published up to 28 April 2025. We included quantitative studies with population-based samples that examined the correlates of hysterectomy in LMICs. Findings were synthesised using a narrative synthesis approach. Results: We included 22 studies in this review. All studies were published from 2016 onwards, and three-quarters were conducted in India. Evidence from multiple LMICs, including India, suggests that older age at survey (in reproductive ages), having health insurance at the time of survey, being currently married or having a partner, and belonging to higher wealth quintiles are associated with an increased likelihood of having had a hysterectomy. Studies from India consistently indicate that women with lower levels of education, those who are employed, residing in rural areas, classified as overweight or obese at the time of survey, and having a higher number of children were more likely to have undergone a hysterectomy. Evidence regarding adolescent age at first birth was limited and inconclusive, while evidence on tubal ligation was mixed across studies from India. Conclusions: We identified several sociodemographic and reproductive correlates of hysterectomy in LMICs. Prospective and mixed-methods studies, as well as studies examining health system factors, including provider incentives and facility-level variation, are needed to inform targeted interventions in LMIC settings. Registration: PROSPERO: CRD42022335706.

Indexed as

Developing CountriesHysterectomyFemaleHumansSocioeconomic Factors

Identifiers

PMID42246375
PMCPMC13237810

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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.