Evidence map›Paper›PMID 37525163›Full record

ArticleBMC women's health2023

An analysis of changes in the prevalence and patterns of intimate partner violence against women in seven Asian countries.

Seema Vyas, Henrica A F M Jansen, Jessica Gardner, Sujata Tuladhar, Kate Hammond, Kristin Diemer

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Article in BMC women's health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Seema VyasIndependent researcher, London, United Kingdom.ORCID 0000-0003-3066-664X
Henrica A F M JansenIndependent researcher, Bangkok, Thailand.ORCID 0009-0005-3691-049X
Jessica GardnerUNFPA Asia-Pacific Region, Bangkok, Thailand.ORCID 0009-0000-4749-6021
Sujata TuladharUNFPA Asia-Pacific Region, Bangkok, Thailand.
Kate HammondUniversity of Melbourne, Melbourne, Australia.ORCID 0000-0002-9688-4220
Kristin DiemerUniversity of Melbourne, Melbourne, Australia. k.diemer@unimelb.edu.au.ORCID 0000-0002-5150-5362

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAssessments of changes in prevalence and patterns of violence against women are critical to inform prevention and response approaches and to monitor progress towards elimination. Most countries in the Asia Region have data on violence and several have completed second and third waves of surveys. This study sought to assess and compare the prevalence and patterns of physical and/or sexual partner violence in seven Asian countries with at least two rounds of comparable national-level data.

methodsWe conducted primary descriptive analyses using Demographic and Health data from India, Nepal, and Pakistan (South Asia), and from Cambodia, the Philippines, Timor-Leste, and extracted data from reports from Vietnam (Southeast Asia). We examined differences in partner violence by type of violence, reference periods, severity of violence, and age group. Pearson chi-square tests and Mantel-Haenszel test for trend were used to assess whether differences between time points were significant (p < 0.05).

resultsPrevalence and patterns of violence vary across countries and sub-regions. In Southeast Asia, women in Cambodia and Vietnam experienced increasing and relatively high levels of sexual violence alongside declining physical violence. Reported levels of violence were lowest in the Philippines and prevalence showed consistent declines. Timor-Leste stands out as having the highest prevalence of physical partner violence, and there were consistently significant increases in estimates. Women in South Asia experienced predominantly physical violence and there were consistent declines in all three countries, though physical violence increased among older women in India.

conclusionsData from Asian countries where more than one prevalence survey had been done provided a unique opportunity to analyse differences in estimates of violence against women at two time points. Deeper analyses into types and severity of violence revealed that overall prevalence estimates hid more complex patterns. There are clear limitations in using survey data to understand the nuances which highlighted the need for depth analysis identifying contextual factors of violence to inform situation specific policies and interventions for the greatest impact. It is also clear that more than two data points are necessary to identify change over time, and interventions driving or preventing that change.

Indexed as

Intimate Partner ViolenceAgedFemaleHumansPakistanPrevalenceRisk FactorsSurveys and QuestionnairesViolenceDomestic violenceIntimate partner violenceSouth AsiaSoutheast Asia

Identifiers

PMID37525163
PMCPMC10391984

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LicenceCC BY
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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.