Sage Journals: Discover world-class research

Abstract

Intimate partner violence (IPV) is a widespread issue, particularly affecting married women in low- and middle-income countries (LMICs), where cultural norms often lead to its acceptance. Using data from national demographic and health surveys and a two-level hierarchical model, this study examines factors affecting IPV acceptance among married women in 20 LMICs. Studies show that higher education, greater wealth, decision-making power, urban residency, and older age at marriage all reduce IPV acceptance. Furthermore, surveys from 2019 to 2022 indicate a decline in acceptance of IPV. In LMICs, targeted interventions need to be implemented to reduce IPV and increase gender equality.

Keywords

attitudes toward IPV multilevel modeling (MLM)individual-level factors country-level factors married women low-and middle-income countries

Introduction

Intimate partner violence (IPV) refers to any act or behavior that leads to physical, sexual, or psychological harm by an intimate partner (Krug et al., 2002). It remains a widespread public health issue, significantly affecting one in every three women worldwide and significantly impacting their well-being and safety (World Health Organization, 2021). The high prevalence of IPV leads to both severe short-term and long-term detrimental effects on women's health and well-being, including depression, anxiety, posttraumatic stress disorder, suicidal ideation, severe injuries, reproductive health issues, sexually transmitted infections, and even death (Gunarathne et al., 2023; Ibrahim et al., 2015; Miller et al., 2022; Sardinha et al., 2022). These consequences pose significant barriers to achieving gender equality and fulfilling Sustainable Development Goal (SDG) 5.2, which aims to eradicate all forms of violence against women and girls (Bhowmik & Biswas, 2022; Gunarathne et al., 2024a).

The prevalence of IPV against women is particularly high in low- and middle-income countries (LMICs), particularly in South Asia, East Asia and the Pacific, and Sub-Saharan Africa (SSA), where the prevalence rate varies from 13.7% in Cambodia to 75% in Bangladesh (Bhowmik & Biswas, 2022; Coll et al., 2020; Gunarathne et al., 2024a). Moreover, married women are among the most vulnerable victims as evidenced by a multicountry study that revealed that approximately 35% of ever-married women have been victims of severe physical and/or sexual violence by their husbands or partners during their lifetimes (Sardinha et al., 2022). The high prevalence of IPV among married women is associated with various maladaptive factors including lower educational attainment, lower socioeconomic status, early marriage, exposure to childhood abuse, norms accepting violence, women's decision-making power, and income levels (Coll et al., 2020; Gunarathne et al., 2023; Sanni et al., 2021). Among these factors, the acceptance of IPV is particularly common among women in LMICs, compared to developed countries as many view it as acceptable and normal (Bhowmik & Biswas, 2022; Ma et al., 2023; Rani & Bonu, 2009; Tran et al., 2016). This acceptance perpetuates the cycle of violence by reinforming patriarchal norms and social acceptability of IPV, keeping IPV at a persistently high level (Gunarathne et al., 2024b; Waltermaurer, 2012). The cycle of violence may be influenced by neighborhood conditions, especially factors such as socioeconomic disadvantage and prevailing cultural norms (Wright & Fagan, 2013).

Cultural norms and traditions significantly influence the acceptance of IPV among women in LMICs (Gunarathne et al., 2023, 2024a; Tran et al., 2016). Addressing the sociodemographic and cultural factors that reinforce these attitudes is essential for reducing IPV rates. The literature indicates that factors at different hierarchical levels, including individual, household, and community, shape attitudes toward IPV among women. Individual-level factors such as education, age, and exposure to media, as well as household-level factors such as socioeconomic status and decision-making power, play significant roles in shaping these attitudes (Bhowmik & Biswas, 2022; Gunarathne et al., 2024a; Serrano-Montilla et al., 2020). Additionally, country-level factors such as gender norms, legal frameworks, and economic conditions significantly impact the acceptance of IPV (Gunarathne et al., 2024a; Hayes & Boyd, 2017).

While several studies have examined the predictors of IPV acceptance in specific regions or countries, there is a lack of multicountry studies that consider both individual and country-level factors in a comprehensive manner using a multilevel analysis approach. Therefore, this study aims to address this gap by investigating the multilevel determinants of attitudes toward IPV among married women in 20 LMICs using a two-level hierarchical modeling approach. By identifying the most vulnerable groups of married women and understanding the factors influencing their acceptance of IPV, this research can inform policy measures aimed at reducing IPV in line with United Nations (UN) SDG 5.2. This study not only contributes to the existing body of knowledge but also provides actionable insights for policymakers to implement effective interventions to combat IPV and promote women's rights and safety globally by considering both individual-level and country-level factors.

Materials and Methods

Study Design

Data from the latest national representative cross-sectional Demographic and Health Surveys (DHSs) of 20 low- and middle-income countries (LMICs) across South Asia, East Asia and the Pacific, and Sub-Saharan Africa were used for this study. These regions were selected as they encompass the majority of LMICs globally. The DHSs are standardized surveys conducted in over 90 countries, allowing cross-country comparability due to consistent methodologies and harmonized variable definitions (Gamage et al., 2022). The DHS employs a two-stage stratified cluster sampling design. As a first step, a sample of enumerated areas (EAs) is selected from the sampling frame using the probability proportional to size (PPS) method. The second stage involves the selection of a predetermined number of households from each EA with equal probability. Data is then collected through face-to-face interviews with eligible household members (Gunarathne et al., 2024a; United Nations, 2005; Short Fabic et al., 2012).

The specific DHSs included in this study were conducted in Sri Lanka (2006, n = 9391), Bangladesh (2017, n = 18789), India (2019, n = 76141), Nepal (2022, n = 10392), Pakistan (2017, n = 14090), Swaziland (2006, n = 1474), Ghana (2014, n = 4168), Kenya (2022, n = 15649), Lesotho (2014, n = 3476), Nigeria (2018, n = 27273), Senegal (2019, n = 5352), Tanzania (2022, n = 6231), Zambia (2018, n = 7213), Zimbabwe (2015, n = 5587), Cambodia (2021, n = 12681), Indonesia (2017, n = 33229), Myanmar (2015, n = 7299), Papua New Guinea (2016, n = 7300), Philippines (2022, n = 10360), and Timor-Leste (2016, n = 6442). Despite the availability of a more recent survey, the 2006 DHS of Sri Lanka was included due to the lack of specific variables of interest (women's attitudes toward intimate partner violence) in the 2016 survey. There were 282,537 married women aged 15–49 years from 20 LMICs in the total sample.

Variables

Outcome Variable. The outcome variable was married women's attitude toward IPV, categorized as accepting or not accepting IPV. Based on five questions asking women whether they consider a husband to be justified in hitting or beating his wife in the following situations, this binary variable was derived: (1) she goes out without telling him, (2) she neglects the children, (3) she argues with the husband, (4) she refuses to have sex with the husband, and (5) she burns the food. Consistent with previous studies (Bhowmik & Biswas, 2022; Biswas et al., 2017; Gunarathne et al., 2024a), the attitude toward IPV variable was coded as “Yes” if the woman accepted husband's beating in any of the mentioned situations, and “No” if she did not accept husband's beating in all situations.

Predictor Variables. Predictor variables were classified into individual-level (level-one) and country-level (level-two) factors. The selection of individual-level factors was based on past literature (Bhowmik & Biswas, 2022; Biswas et al., 2017; Gunarathne et al., 2024a; Mulatu et al., 2024; Seidu et al., 2022) to understand the impact of individual-level characteristics on attitudes toward IPV, and these level-one predictors refer to individual married women, including area of residence (urban, rural); education of both respondent and her partner (none, primary, secondary, higher); respondent's current employment status (not working, working); wealth index (poorest, poorer, middle, richer, richest); respondent's involvement in decision-making (recoded binary variable: not able to make decisions, able to make decisions about own health care, a large household purchase, and/or visits to family or relatives); sex of household head (male, female); respondent's exposure to media (not exposed or exposed to newspapers, radio, and/or TV); the age of respondents (≤25 years old, >25 years old); and respondent's age at marriage (all binary, split by median age (19 years)). At the country level, predictor variables included survey period (before 2019, 2019–2022), gross domestic product (GDP) per capita of the country (in USD), and region of the country (South Asia, East Asia and the Pacific, Sub-Saharan Africa), based on information availability (Utaile et al., 2023). Detailed descriptions of the level-one and level-two factors as well as the outcome variable are provided in Table 1.

Table 1.

Description of Level-One, Level-Two Predictors, and Outcome Variable.

Variable	Description
Level-one predictors (individuals)
Sociodemographic factors
Area of residence	Residence of the women (urban = 1 and rural = 2)
Respondent's education level	Highest educational level of the women (no education = 0, primary = 1, secondary = 2, higher = 3)
Current working status	Current working status of the women (not working = 0, working = 1)
Wealth index	Wealth index of the women (poorest = 1, poorer = 2, middle = 3, richer = 4, richest = 5)
Husband/partner's education	Highest education level of the husband/ partner (no education = 0, primary = 1, secondary = 2, higher = 3)
Decision-making	Women's involvement in decision-making (not able to make decision = 0, able to make decision = 1)
Gender of household head	Gender of household head (male = 1, female = 2)
Media exposure	Women's exposure to media (not exposed = 0, exposed = 1)
Respondent's age	Age of the women (less than or equal 25 years = 1, greater than 25 years = 2)
Age at marriage	Women's age at marriage (less than or equal 19 years = 1, greater than 19 years = 2)
Number of children	Number of children (less than 3 children = 1, 3 or more children = 2)
Level-two predictors (countries)
Survey period	Survey period of the country (before 2019 = 1, 2019 to 2022 = 2)
Gross domestic product (GDP) per capita	GDP per capita of the country in (current USD)
Region	Regions of the country located (South Asia = 1, East Asia and Pacific = 2, Sub-Saharan Africa = 3)
Outcome variable
Attitudes toward intimate partner violence (IPV)	Attitudes toward married women's acceptance of IPV (no = 0, yes = 1)

Statistical Analysis

Given the large-scale survey data, listwise deletion was applied to missing values under the assumption that the missing values were completely random (Gunarathne et al., 2024a). In the final model, only factors showing a significant relationship with the outcome indicators were considered. A hierarchical data structure was used in the analysis, in which women (level one) are nested within countries (level two), allowing the simultaneous examination of factors at the individual and country levels. Multilevel models with two levels were fitted with the first level representing individual-level variables and the second level representing country-level variables. Categorical predictors were uncentered, while the numerical level-two predictor (GDP per capita) was centered on the grand mean to enhance model interpretation and reduce potential multicollinearity issues. For the outcome variable, attitude toward intimate partner violence (IPV), three sequential models were constructed: Model 1 was based on a random effect, Model 2 included a random effect and individual-level variables, and Model 3 added country-level variables to Model 2. This three-model approach quantified the variation in outcomes between countries (Model 1) and assessed how much of that variation was explained by individual-level variables (Model 2) and country-level variables (Model 3). This approach aligns with our research questions and allows for a clear interpretation of the fixed effects at both individual and country levels. The proportional change in variance from Model 1 to Model 3 was computed for this purpose (Dias et al., 2020). To examine the relationship between married women's attitude toward IPV and the various variables measured at both an individual and a national level, odds ratios and their respective 95% confidence intervals (CI) were calculated. The fit of the models was assessed using the Bayesian information criterion (BIC) and Akaike information criterion (AIC). The goodness of fit of the multilevel model was tested by the log-likelihood ratio (LR) test. Multicollinearity between independent variables was assessed using the variance inflation factor (VIF). All analyses were conducted in R (version 4.2.0) using the “lme4” package, and a significance level of 0.05 was used for all tests.

Results

Table 2 presents descriptive statistics for both individual and country-level variables. In the sample of 282,537 married women, the majority (66%), resided in rural areas. Among the married women surveyed, 39.2% had secondary education, while only 12.2% had higher education. Approximately 46.4% were employed. Wealth distribution was fairly even, with 21.8% in the poorest quintile and 18.7% in the richest. Most partners had secondary education (43.3%), and 85.7% of women were involved in household decision-making. Female-headed households made up 14%, and over half of the women had some media exposure. Acceptance of IPV was at 37.1%, indicating varying degrees of justification for IPV among participants based on specific scenarios. Among the five specific scenarios used to assess attitudes toward IPV, the most commonly accepted justification was neglecting the children, with 27.8% of participants agreeing. This was followed by going out without telling the husband (22.5%), arguing with the husband (21.3%), refusing to have sex with the husband (15.1%), and burning the food (11.8%). Surveys were mostly conducted between 2019 and 2022, covering three major regions. South Asia represented 25.0% of the sample, including Sri Lanka, Bangladesh, India, Nepal, and Pakistan. East Asia and the Pacific accounted for 30.0%, with data from Cambodia, Indonesia, Philippines, Myanmar, Papua New Guinea, and Timor-Leste. Sub-Saharan Africa comprised the largest proportion (45.0%), with countries including Swaziland, Ghana, Kenya, Lesotho, Nigeria, Senegal, Tanzania, Zambia, and Zimbabwe. The average GDP per capita was 2271.35 USD, ranging from 969.9 USD in Lesotho to 4788.0 USD in Indonesia.

Table 2.

Descriptive Statistics of Outcome Variable, As Well As Level-One and Level-Two Predictors (Individual Level, N = 282,537; Country Level, N = 20).

	N	M	SD	Min	Max
Level-one (individual level) descriptive statistics
Area of residence	282,537	0.66	0.475	1	2
Respondent's education level	282,537	1.41	0.973	0	3
Wealth index	282,537	2.93	1.418	1	5
Current working status	282,537	0.46	0.499	0	1
Partner's education	282,537	1.57	0.942	0	3
Decision-making	282,537	0.86	0.350	0	1
Media exposure	282,537	0.61	0.488	0	1
Respondent's age	282,537	0.79	0.408	0	1
Age at marriage	282,537	0.42	0.493	0	1
Gender of household head	282,537	0.14	0.347	0	1
Attitudes toward intimate partner violence	282,537	0.37	0.483	0	1
Number of children	282,537	1.48	0.499	1	2
Level-two (country level) descriptive statistics
Survey period	20	0.48	0.500	0	1
Region	20	1.84	0.850	1	3
Gross domestic product per capita (in USD)^a	20	2271.35	1028.77	969.9	4788.0

Area of residence (urban = 1 and rural = 2); Respondent's education level (no education = 0, primary = 1, secondary = 2, higher = 3); Wealth index (poorest = 1, poorer = 2, middle = 3, richer = 4, richest = 5); Current working status (not working = 0, working = 1); Partner's education (no education = 0, primary = 1, secondary = 2, higher = 3); Decision-making (not able to make decision = 0, able to make decision = 1); Media exposure (not exposed = 0, exposed = 1); Respondent's age (less than or equal 25 years = 1, greater than 25 years = 2); Age at marriage (less than or equal 19 years = 1, greater than 19 years = 2); Gender of household head (male = 1, female = 2); Attitudes toward intimate partner violence (no = 0, yes = 1); Number of children (less than 3 children = 1, 3 or more children = 2); Survey period (before 2019 = 1, 2019 to 2022 = 2); Region (South Asia = 1, East Asia and the Pacific = 2, and Sub-Saharan Africa = 3).

Metric variable.

Table 3 shows the associations between attitudes toward IPV and various individual and country-level covariates using multilevel modeling. The analysis revealed that women from rural areas had 17% higher odds of accepting IPV (AOR = 1.17, 95% CI: [1.15–1.20]) than those from urban areas. Higher levels of education were associated with lower odds of accepting IPV, women with primary, secondary, and higher education were 14% (AOR = 0.86, 95% CI: [0.83–0.88]), 25% (AOR = 0.75, 95% CI: [0.72–0.77]), and 46% (AOR = 0.54, 95% CI: [0.52–0.57]) less likely to accept IPV, respectively, compared to women with no education. Working women had slightly higher odds of accepting IPV (AOR = 1.07, 95% CI: [1.04–1.09]) compared to those who were not working. Wealthier women were less likely to accept IPV with those in the poorer, middle, richer, and richest wealth quintiles receiving 7% (AOR = 0.93, 95% CI: [0.91–0.96]), 13% (AOR = 0.87, 95% CI: [0.85–0.90]), 20% (AOR = 0.80, 95% CI: [0.77–0.82]), and 39% (AOR = 0.61, 95% CI: [0.59–0.63]), respectively, less likely to accept IPV compared to those in the poorest quintiles.

Table 3.

Associations (Odds Ratio and 95% Confidence Intervals) Between Attitudes Toward IPV and Individual, and Country-Level Covariates (Attitudes Toward IPV among Married Women in 20 LMICs Located in South Asia, East Asia and the Pacific, and Sub-Saharan Africa).

		Attitudes toward IPV
		Model 1	Model 2	Model 3
Fixed effects
Individual level
Area of residence (Ref. Urban)	Rural		1.17(1.15–1.20)	1.17(1.15–1.20)
Respondent’s education (Ref. No education)	Primary		0.86(0.83–0.88)	0.86(0.83–0.88)
	Secondary		0.75(0.72–0.77)	0.75(0.73–0.77)
	Higher		0.54(0.52–0.57)	0.55(0.53–0.57)
Wealth index (Ref. Poorest)	Poorer		0.93(0.91–0.96)	0.93(0.91–0.96)
	Middle		0.87(0.85–0.90)	0.87(0.85–0.90)
	Richer		0.80(0.77–0.82)	0.80(0.78–0.82)
	Richest		0.61(0.59–0.63)	0.61(0.59–0.63)
Working status (Ref. Not working)	Working		1.07(1.04–1.09)	1.07(1.05–1.09)
Partner's education (Ref. No Education)	Primary		0.86(0.84–0.89)	0.86(0.84–0.89)
	Secondary		0.84(0.81–0.86)	0.84(0.81–0.86)
	Higher		0.76(0.73–0.79)	0.76(0.73–0.79)
Decision-making (Ref. Not able to make decision)	Able to make decision		0.76(0.74–0.78)	0.76(0.74–0.78)
Sex of household head (Ref. Male)	Female		0.97(0.95–0.99)	0.97(0.95–0.99)
Media exposure (Ref. Not exposed)	Exposed		1.05(1.03–1.07)	1.05(1.03–1.07)
Respondent's age (Ref. ≤25 years)	>25 years		0.91(0.88–0.93)	0.90(0.88–0.93)
Age at marriage (Ref. ≤19 years)	>19 years		0.85(0.84–0.87)	0.85(0.84–0.87)
Number of children (Ref. Less than 3 children)	3 or more children		0.97(0.95–0.99)	0.97(0.95–0.99)
Country level
Survey period (Ref. Before 2019)	2019–2022			0.53(0.30–0.94)
Region (Ref. South Asia)	East Asia and Pacific			1.57(0.81–3.07)
Region (Ref. South Asia)	Sub-Saharan Africa			1.17(0.69–1.99)
GDP per capita				0.99(0.98–1.01)
Random effects
Between-country variance		0.61	0.64	0.56
ICC		0.156	0.163	0.138
Proportional change in variance^a		Ref	5.15%	−13.71%
BIC		352753.5	343189.5	343235.7
AIC		352732.4	342978.4	342982.5

Note. Model 1 = null model (only random effects). Model 2 = Model 1 + individual-level variables. Model 3 = Model 2 + country-level variables. Bold values indicate statistically significant results.

IPV = intimate partner violence; LMICs = low- and middle-income countries; GDP = gross domestic product; ICC = intraclass correlation coefficient; BIC = Bayesian information criterion; AIC = Akaike information criterion.

In relation to Model 1.

Women whose partners had higher education levels were also less likely to accept IPV. Specifically, partners with primary, secondary, and higher education were associated with 14% (AOR = 0.86, 95% CI: [0.84–0.89]), 16% (AOR = 0.84, 95% CI: [0.81–0.86]), and 24% (AOR = 0.76, 95% CI: [0.73–0.79]) lower odds of accepting IPV compared to those whose partners had no education. Women who had decision-making power were 24% (AOR = 0.76, 95% CI: [0.74–0.78]) less likely to accept IPV than those who did not have decision-making power. Additionally, female-headed households had slightly lower odds of justifying IPV (AOR = 0.97, 95% CI: [0.95–0.99]) compared to male-headed households. Women exposed to media had slightly higher odds of accepting IPV (AOR = 1.05, 95% CI: [1.03–1.07]) compared to those not exposed to media.

Age also plays a role in attitudes toward IPV. Women over 25 years old were 9% (AOR = 0.91, 95% CI: [0.88–0.93]) less likely to accept IPV compared to younger women. Similarly, women who married after age 19 had 15% (AOR = 0.85, 95% CI: [0.84–0.87]) lower odds of accepting IPV than those who married at 19 or younger. Additionally, women with three or more children had slightly lower odds of justifying IPV (AOR = 0.97, 95% CI: [0.95–0.99]) compared to those with fewer than three children.

At the country level, surveys conducted between 2019 and 2022 were associated with significantly lower odds of justifying IPV (AOR = 0.53, 95% CI: [0.30–0.94]) compared to those conducted before 2019. Model 2, which incorporated individual-level variables, had the lowest BIC and AIC values, indicating the best fit among the models. These lower values indicate that individual-level factors play a significant role shaping attitudes toward IPV across these countries. The intraclass correlation coefficient (ICC) revealed that only 16% of the variance in attitudes toward IPV was due to differences between countries, highlighting that most of the variation is driven by individual-level factors. The proportional change in the variance from the null model (Model 1) to Model 2 was 5.15%, while from Model 1 to Model 3, it was −13.71%. The increase in between-country variance from Model 1 to Model 2 suggests that individual-level factors may be amplifying the differences in IPV attitudes between countries.

Discussion

Attitudes toward IPV acceptance are a significant underlying cause of its high prevalence in LMICs (Bhowmik & Biswas, 2022; Gunarathne et al., 2023; Tran et al., 2016), and this study examined the individual and country-level factors that influence these attitudes among married women in 20 LMICs across South Asia, Sub-Saharan Africa, and East Asia and the Pacific. Using a two-level hierarchical modeling approach, our findings highlight several key determinants. Higher education levels in the women and their partners, greater household wealth, decision-making autonomy, female-headed households, older age, and older age at marriage were associated with lower odds of justifying IPV. In contrast, residing in rural areas, media exposure, and employment were linked to higher odds of justification. Additionally, surveys conducted more recently (2019–2022) indicated significantly lower justification for IPV, suggesting a potential shift in social norms or increased awareness over time.

At the individual level, higher education levels in both women and their partners were consistently associated with lower odds of justifying IPV. This aligns with the existing literature (Bhowmik & Biswas, 2022; Gunarathne et al., 2024a; Seidu et al., 2022; Serrano-Montilla et al., 2020; Wang, 2016), suggesting that education empowers individuals with the knowledge and skills to challenge traditional norms and gender roles that perpetuate IPV (Gunarathne et al., 2024a; Wang, 2016). Educated women are more likely to be aware of their rights, which help them develop a positive self-image and abilities, resulting in a lower acceptance of such violence (Gunarathne et al., 2024a). Furthermore, educated husbands report lower rates of violence against their wives, and there is a trend for highly educated men to marry educated partners, which may influence the reduction or absence of IPV and subsequently decrease its acceptance (Weitzman, 2018). Regardless of gender, higher education levels are associated with greater understanding of women's rights, ultimately contributing to the reduction of attitudes that justify IPV.

The results of this study are consistent with the findings of previous research, which have indicated that higher household wealth may result in lower IPV justification (Adu, 2022; Bhowmik & Biswas, 2022; Gunarathne et al., 2024a). Economic stability may reduce stress and conflict within households, decreasing IPV likelihood (Lucero et al., 2016; Neppl et al., 2016; Stöckl et al., 2021). As a result, a less stressful and friendly family environment can mitigate factors contributing to IPV acceptance. Moreover, wealthier households may have access to more resources and support systems that discourage IPV acceptance (Gunarathne et al., 2023). Hence, economic stability is an important factor in reducing the acceptance of IPV. To reduce IPV acceptance and support victims, policies focused on improving household economic conditions are essential.

Similar to previous findings, it has been found that women with the ability to make household decisions are less likely to justify IPV (Biswas et al., 2017; Gunarathne et al., 2024a; Merdassa et al., 2021; Seidu et al., 2022). Women's autonomy in decision-making enhances their empowerment, allowing them greater control over their lives and creating environments in which IPV is less accepted (Gunarathne et al., 2023; Tenkorang, 2018). Often, empowered women are better educated and more economically independent, which reinforces their ability to resist and challenge IPV norms (Gunarathne et al., 2024a; Osorio, 2023; Weitzman, 2018). Interestingly, female-headed households were associated with lower justification of IPV in this study, aligning with previous studies (Bhowmik & Biswas, 2022; Gunarathne et al., 2024a). There is a possibility that the female leadership role in such households leads to the formation of attitudes that reject violence as a result of their enhanced autonomy and decision-making power (Gunarathne et al., 2024a; Seidu et al., 2022). Therefore, empowering women in their social and domestic environments is crucial for reducing their acceptance of IPV.

In line with previous studies, this research also found that older ages and older ages at marriage are associated with lower acceptance of IPV (Bhowmik & Biswas, 2022; Gunarathne et al., 2024a; Merdassa et al., 2021; Seidu et al., 2022). Older women possess greater life experience and have greater access to information about women's rights, employment opportunities, and support services, which may make them less likely to tolerate IPV (Bhowmik & Biswas, 2022; Gunarathne et al., 2024a; Merdassa et al., 2021). Marriage at a later age is often associated with the ability to make more informed decisions as a result of higher education and maturity, which can significantly reduce their justification and vulnerability to IPV by allowing them to be more independent from their spouses (Chen & Zhao, 2022; Gunarathne et al., 2024a; Weitzman, 2018). Consequently, education and awareness about women's rights and support services, especially among younger women, can contribute to attitudes that reject IPV.

Rural residency was found to be associated with greater odds of justifying IPV, consistent with prior research (Gunarathne et al., 2024a; Merdassa et al., 2021; Sayem et al., 2012; Seidu et al., 2022). It may be due to the fact that rural regions, particularly those in LMIC regions, often adopt more traditional and patriarchal norms, which can perpetuate IPV acceptance (Oyediran, 2016; Seidu et al., 2022). Moreover, the limited availability of services, such as legal protection and support in rural areas, influences violence acceptance (Gunarathne et al., 2024a; Heron & Eisma, 2021). A targeted intervention that challenges traditional norms and improves access to essential services can assist rural women in becoming aware of IPV, thus reducing its acceptance.

Clearly, the media plays a crucial role in raising awareness and providing social support for women, acting as a protective factor against IPV justification (Bhowmik & Biswas, 2022; Jesmin, 2015; Oyediran, 2016). However, this study revealed that media exposure was associated with an increased likelihood of justifying IPV, which is also supported by some other studies (Forsyth & Ward, 2022; Seidu et al., 2022). While the media can provide valuable information, it also has the potential to spread harmful ideas and norms that lead to the promotion of violence, particularly when the content is not critically analyzed or reinforces damaging gender roles (Forsyth & Ward, 2022; Gunarathne et al., 2024a; Seidu et al., 2022). Therefore, media consumers need to engage critically with media content to minimize the possibility of reinforcing harmful ideas.

In accordance with previous research, married women's employment was also related to higher IPV justification (Cools & Kotsadam, 2017; Gunarathne et al., 2024a). While this may seem surprising, women's employment can result in tension and conflict in some contexts, particularly in LMICs. The cause of this problem is often a combination of factors, such as gender-based discrimination at the workplace, limited access to social protection, and the instability and low wages of many available jobs (Biswas & Thampi, 2021; Gage & Thomas, 2017; Uthman et al., 2011). Furthermore, employment can impact traditional gender norms, leading to resistance and increased pressures both at home and at work, resulting in married women's vulnerability and acceptance of IPV (Gunarathne et al., 2024a; Owoo, 2020; Zafar et al., 2022). This unexpected outcome highlights the need for further investigation, including qualitative research.

At the country level, surveys conducted more recently (2019–2022) showed significantly lower justifications for IPV, indicating a potential shift in social norms or increased awareness over time, in accordance with past research (Pierotti, 2013). This may be due to various global and regional initiatives aimed at reducing IPV and promoting gender equality. However, in the final model, region and GDP per capita did not show significant effects, indicating that individual-level factors might be more critical in shaping attitudes toward IPV in these LMICs.

This study provides valuable insights into the main effects of individual and country-level factors on attitudes toward IPV but also has several limitations that need to be acknowledged. First, the cross-sectional design limits our ability to draw causal inferences about the relationship between various factors and IPV justifications. Second, due to data limitations in the DHS, the study included only married women aged 15–49 and focused solely on attitudes toward physical abuse. Third, the DHS data did not include qualitative information, such as respondents' opinions regarding patriarchal norms. Qualitative data could be valuable in understanding the root causes of attitudes toward IPV acceptance as well as validating the quantitative findings. Fourth, the reliance on self-reported data may introduce bias, since respondents may underreport or overreport their attitudes and experiences because of social desirability or recall biases. Finally, interaction terms were not considered in these multilevel models to maintain model simplicity and interpretability, as adding numerous interaction terms in the presence of many predictors can result in increased complexity and the risk of overfitting. The results of this study should be interpreted with caution considering these limitations.

Conclusions

Utilizing two-level hierarchical modeling, this study provides a comprehensive overview of individual and country-level factors influencing attitudes toward IPV among married women in 20 LMICs. Based on the results of the study, married women from rural areas, those with lower levels of education, those who marry at a young age, those living in households dominated by males, those working, who are not involved in household decision-making, and those belonging to the poorest households are more likely to justify IPV. In addition, recent surveys (2019–2022) show a significant decline in IPV acceptance, suggesting that awareness and social norms have changed during the period for the better. Our findings highlight the importance of targeted interventions aimed at educating and empowering women to reduce their acceptance of IPV. Policymakers and stakeholders should focus on strategies that improve women's educational and economic opportunities, promote gender equality, and enhance decision-making autonomy. Additionally, efforts should be concentrated in rural areas where traditional and patriarchal norms are more prevalent. Effective interventions will contribute to achieving Sustainable Development Goal 5.2 by 2023, which aims to eliminate all forms of violence against women and girls.

Footnotes

Acknowledgments

We conducted this study as part of a PhD program at Swinburne University of Technology in Australia, and we would like to thank the University for awarding a tuition fee scholarship (TFS). It is our pleasure to acknowledge the Department of Census and Statistics in Sri Lanka for providing data of DHS 2006 in Sri Lanka.

Data Availability

The secondary data sets analyzed in the current study are freely available upon request from the DHS website ().

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical Approval and Consent to Participate

De-identified secondary datasets are provided upon request by the DHS program authority. The authors obtained permission from DHS to use the above-mentioned surveys. Furthermore, this study was approved by the Swinburne University of Technology Human Research Ethics Committee (approval number: 20226572-10707).

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Lakma Gunarathne

Pragalathan Apputhurai

Maja Nedeljkovic

Jahar Bhowmik

Author Biographies

Lakma Gunarathne, BSc Honours (ORCID: 0000-0002-0602-8683), is a graduate of the University of Sri Jayewardenepura, Sri Lanka and is currently enrolled in the Doctor of Philosophy at Swinburne University of Technology, Australia. Her research interests center on intimate partner violence (IPV), women's well-being, factors that contribute to the spread of IPV, impacts of IPV, and interventions.

Pragalathan Apputhurai, PhD (ORCID: 0000-0003-1667-6315), is a lecturer and director of statistics short courses at the Department of Health Science and Biostatistics at Swinburne University of Technology. His research interests are statistical inference, data modeling (environmental events), Bayesian statistics, and statistical computing. In addition, Prahan teaches in the undergraduate and postgraduate programs in the field of Applied Statistics.

Maja Nedeljkovic, PhD (ORCID: 0000-0003-0963-0335), is a professor at the Centre for Mental Health and Department of Psychological Sciences at Swinburne University of Technology. Her research interests are clinical psychology, health psychology, psychopathology, psychological assessment, health economics, psychotherapy, neuropsychology, and cognitive neuropsychology. Dr Nedeljkovic has extensive experience in mental health among victims of family violence, anxiety, and mental health disorders among the victims of intimate partner violence.

Jahar Bhowmik PhD (ORCID: 0000-0001-9697-1968), is an associate professor and postgraduate applied statistics course director at the Department of Health Science and Biostatistics at Swinburne University of Technology. His research programs are focused on public health and well-being, applied epidemiology, and health-related data modeling. Dr Bhowmik has been investigating violence against women in low- and middle-income countries in his projects and evaluating the progress toward United Nations Sustainable Development Goal 5.2. His primary research focus is to investigate the factors associated with intimate partner violence and its impact on the mental health of survivors and develop recommendation for effective interventions.

References

Adu

(2022). Socio-economic inequalities in intimate partner violence justification among women in Ghana: Analysis of the 2014 Ghana demographic and health survey data. International Health, 15(2), 182–188. https://doi.org/10.1093/inthealth/ihac032

Bhowmik

Biswas

R. K.

(2022). Married women’s attitude toward intimate partner violence is influenced by exposure to media: A population-based spatial study in Bangladesh. International Journal of Environmental Research and Public Health, 19(6), 3447. https://doi.org/10.3390/ijerph19063447

Biswas

R. K.

Rahman

Kabir

Raihan

(2017). Women’s opinion on the justification of physical spousal violence: A quantitative approach to model the most vulnerable households in Bangladesh. PLOS ONE, 12(11), Article e0187884. https://doi.org/10.1371/journal.pone.0187884

Biswas

Thampi

(2021). Women’s workforce participation and spousal violence: Insights from India (Working Paper No. 2021-17). Department of Economics, University of Massachusetts.

Chen

Zhao

(2022). The timing of first marriage and subsequent life outcomes: Evidence from a natural experiment. Journal of Comparative Economics, 50(3), 713–731. https://doi.org/10.1016/j.jce.2022.04.005

Coll

C. V. N.

Ewerling

García-Moreno

Hellwig

Barros

A. J. D.

(2020). Intimate partner violence in 46 low-income and middle-income countries: An appraisal of the most vulnerable groups of women using national health surveys. BMJ Global Health, 5(1), Article e002208. https://doi.org/10.1136/bmjgh-2019-002208

Cools

Kotsadam

(2017). Resources and intimate partner violence in sub-Saharan Africa. World Development, 95(C), 211–230. https://doi.org/10.1016/j.worlddev.2017.02.027

Dias

N. G.

Fraga

Soares

Hatzidimitriadou

Ioannidi-Kapolou

Lindert

Sundin

Toth

Barros

Ribeiro

A. I.

(2020). Contextual determinants of intimate partner violence: A multi-level analysis in six European cities. International Journal of Public Health, 65(9), 1669–1679. https://doi.org/10.1007/s00038-020-01516-x

Forsyth

Ward

K. P.

(2022). Media use and men’s approval of intimate partner violence in Honduras. Journal of Interpersonal Violence, 37(13–14), 11541–11556. https://doi.org/10.1177/0886260521993926

10.

Gage

A. J.

Thomas

N. J.

(2017). Women’s work, gender roles, and intimate partner violence in Nigeria. Archives of Sexual Behavior, 46(7), 1923–1938. https://doi.org/10.1007/s10508-017-1023-4

11.

Gamage

Biswas

R. K.

Bhowmik

(2022). Health awareness and skilled birth attendance: An assessment of sustainable development goal 3.1 in South and South-East Asia. Midwifery, 115, Article 103480. https://doi.org/10.1016/j.midw.2022.103480

12.

Gunarathne

Apputhurai

Nedeljkovic

Bhowmik

(2024a). Factors associated with married women’s attitude toward intimate partner violence: A study on 20 low-and middle-income countries. Health Care for Women International, 46(5), 1–21. https://doi.org/10.1080/07399332.2024.2319214

13.

Gunarathne

Apputhurai

Nedeljkovic

Bhowmik

(2024b). Investigating pathways linking of women’s education Status and empowerment to intimate partner violence among married women in Sri Lanka: A structural equation modeling approach. Journal of Interpersonal Violence, 0(0), Article 08862605241279980. https://doi.org/10.1177/08862605241279980

14.

Gunarathne

Bhowmik

Apputhurai

Nedeljkovic

(2023). Factors and consequences associated with intimate partner violence against women in low- and middle-income countries: A systematic review. PLOS ONE, 18(11), Article e0293295. https://doi.org/10.1371/journal.pone.0293295

15.

Hayes

B. E.

Boyd

K. A.

(2017). Influence of individual- and national-level factors on attitudes toward intimate partner violence. Sociological Perspectives, 60(4), 685–701. https://doi.org/10.1177/0731121416662028

16.

Heron

R. L.

Eisma

M. C.

(2021). Barriers and facilitators of disclosing domestic violence to the healthcare service: A systematic review of qualitative research. Health & Social Care in the Community, 29(3), 612–630. https://doi.org/10.1111/hsc.13282

17.

Ibrahim

Ahmed

W. S.

El-Hamid

Hagras

(2015). Intimate partner violence among Egyptian pregnant women: Incidence, risk factors, and adverse maternal and fetal outcomes. Clinical and Experimental Obstetrics & Gynecology, 42(2), 212–219. https://doi.org/10.12891/ceog1829.2015

18.

Jesmin

S. S.

(2015). Social determinants of married women’s attitudinal acceptance of intimate partner violence. Journal of Interpersonal Violence, 32(21), 3226–3244. https://doi.org/10.1177/0886260515597436

19.

Krug

E. G.

Mercy

J. A.

Dahlberg

L. L.

Zwi

A. B.

(2002). The world report on violence and health. Lancet, 360(9339), 1083–1088. https://doi.org/10.1016/s0140-6736(02)11133-0

20.

Lucero

J. L.

Lim

Santiago

A. M.

(2016). Changes in economic hardship and intimate partner violence: A family stress framework. Journal of Family and Economic Issues, 37(3), 395–406. https://doi.org/10.1007/s10834-016-9488-1

21.

Chen

Kong

Chen

Geldsetzer

Zeng

Wehrmeister

F. C.

Subramanian

S. V.

Song

(2023). Prevalence and changes of intimate partner violence against women aged 15 to 49 years in 53 low-income and middle-income countries from 2000 to 2021: A secondary analysis of population-based surveys. The Lancet Global Health, 11(12), e1863–e1873. https://doi.org/10.1016/S2214-109X(23)00417-5

22.

Merdassa

Medhanyie

Fisseha

(2021). Individual and community-level risk factors of women’s acceptance of intimate partner violence in Ethiopia: multilevel analysis of 2011 Ethiopian Demographic Health Survey. BMC Women’s Health, 21(1), 283. https://doi.org/10.1186/s12905-021-01427-w

23.

Miller

Okoth

Prigmore

H. L.

Ressler

D. J.

Mbeya

Rogers

Moon

T. D.

Audet

C. M.

(2022). The prevalence of interpersonal violence (IPV) against women and its associated variables: An exploratory study in the Rongo sub-county of Migori County, Kenya. Journal of Interpersonal Violence, 37(5–6), 2083–2101. https://doi.org/10.1177/0886260520935484

24.

Mulatu

Dessie

Abera

(2024). Multi-level analysis of intimate partner violence and its determinants among reproductive age group women in Ethiopia: Evidence from Ethiopian demographic health survey, 2016. BMC Public Health, 24(1), Article 1391. https://doi.org/10.1186/s12889-024-18781-7

25.

Neppl

T. K.

Senia

J. M.

Donnellan

M. B.

(2016). Effects of economic hardship: Testing the family stress model over time. Journal of Family Psychology, 30(1), 12–21. https://doi.org/10.1037/fam0000168

26.

Osorio

(2023). The effect of education on intimate partner violence: Evidence from an education reform in Tanzania. https://ssrn.com/abstract=4526328

27.

Owoo

N. S.

(2020). Occupational prestige and women’s experience of intimate partner violence in Nigeria. Feminist Economics, 26(4), 56–88. https://doi.org/10.1080/13545701.2020.1820064

28.

Oyediran

K. A.

(2016). Explaining trends and patterns in attitudes towards wife-beating among women in Nigeria: Analysis of 2003, 2008, and 2013 demographic and health survey data. Genus, 72(1), Article 11. https://doi.org/10.1186/s41118-016-0016-9

29.

Pierotti

R. S.

(2013). Increasing rejection of intimate partner violence: Evidence of global cultural diffusion. American Sociological Review, 78(2), 240–265. https://doi.org/10.1177/0003122413480363

30.

Rani

Bonu

(2009). Attitudes toward wife beating: A cross-country study in Asia. Journal of Interpersonal Violence, 24(8), 1371–1397. https://doi.org/10.1177/0886260508322182

31.

Sanni

Hudani

Buh

Ghose

(2021). Prevalence and predictors of intimate partner violence among married women in Egypt. Journal of Interpersonal Violence, 36(21–22), 10686–10704. https://doi.org/10.1177/0886260519888196

32.

Sardinha

Maheu-Giroux

Stöckl

Meyer

S. R.

García-Moreno

(2022). Global, regional, and national prevalence estimates of physical or sexual, or both, intimate partner violence against women in 2018. Lancet, 399(10327), 803–813. https://doi.org/10.1016/s0140-6736(21)02664-7

33.

Sayem

A. M.

Begum

H. A.

Moneesha

S. S.

(2012). Attitudes towards justifying intimate partner violence among married women in Bangladesh. Journal of Biosocial Science, 44(6), 641–660. https://doi.org/10.1017/s0021932012000223

34.

Seidu

A.-A.

Awiah Dzantor

Sambah

Ahinkorah

Ameyaw

(2022). Participation in household decision making and justification of wife beating: Evidence from the 2018 Mali demographic and health survey. International Health, 14(1), 74–83. https://doi.org/10.1093/inthealth/ihab008

35.

Serrano-Montilla

Lozano

L. M.

Bender

Padilla

J. L.

(2020). Individual and societal risk factors of attitudes justifying intimate partner violence against women: A multilevel cross-sectional study. BMJ Open, 10(12), Article e037993. https://doi.org/10.1136/bmjopen-2020-037993

36.

Short Fabic

Choi

Bird

(2012). A systematic review of demographic and health surveys: Data availability and utilization for research. Bulletin of the World Health Organization, 90(8), 604–612. https://doi.org/10.2471/blt.11.095513

37.

Stöckl

Hassan

Ranganathan

Hatcher

A. M.

(2021). Economic empowerment and intimate partner violence: A secondary data analysis of the cross-sectional demographic health surveys in sub-Saharan Africa. BMC Women’s Health, 21(1), Article 241. https://doi.org/10.1186/s12905-021-01363-9

38.

Tenkorang

(2018). Women’s autonomy and intimate partner violence in Ghana. International Perspectives on Sexual and Reproductive Health, 44(2), 51–61. https://doi.org/10.1363/44e6118

39.

Tran

T. D.

Nguyen

Fisher

(2016). Attitudes towards intimate partner violence against women among women and men in 39 low- and middle-income countries. PLOS ONE, 11(11), Article e0167438. https://doi.org/10.1371/journal.pone.0167438

40.

United Nations. (2005). Household surveys in developing and transition countries (No. 96; Studies in Methods Series F). United Nations.

41.

Utaile

M. M.

Ahmed

A. A.

Yalew

A. W.

(2023). Multilevel analysis of factors for intimate partner violence during pregnancy in Gammo Gaffa zone, south Ethiopia: A community based study. Frontiers in Public Health, 11, Article 1122041. https://doi.org/10.3389/fpubh.2023.1122041

42.

Uthman

O. A.

Moradi

Lawoko

(2011). Are individual and community acceptance and witnessing of intimate partner violence related to its occurrence? Multilevel structural equation model. PLOS ONE, 6(12), Article e27738. https://doi.org/10.1371/journal.pone.0027738

43.

Waltermaurer

(2012). Public justification of intimate partner violence: A review of the literature. Trauma, Violence & Abuse, 13(3), 167–175. https://doi.org/10.1177/1524838012447699

44.

Wang

(2016). Factors influencing attitude toward intimate partner violence. Aggression and Violent Behavior, 29, 72–78. https://doi.org/10.1016/j.avb.2016.06.005

45.

Weitzman

(2018). Does increasing women’s education reduce their risk of intimate partner violence? Evidence from an education policy reform. Criminology, 56(3), 574–607. https://doi.org/10.1111/1745-9125.12181

46.

World Health Organization. (2021). Violence against women. https://www.who.int/news-room/fact-sheets/detail/violence-against-women

47.

Wright

E. M.

Fagan

A. A.

(2013). The cycle of violence in context: Exploring the moderating roles of neighborhood disadvantage and cultural norms. Criminology: An Interdisciplinary Journal, 51(2), 217–249. https://doi.org/10.1111/1745-9125.12003

48.

Zafar

Zia

Amir-Ud-Din

(2022). Troubling trade-offs between women’s work and intimate partner violence: Evidence from 19 developing countries. Journal of Interpersonal Violence, 37(17–18), 16180–16205. https://doi.org/10.1177/08862605211021961

Factors Influencing Attitudes Toward Intimate Partner Violence Among Married Women: A Multilevel Analysis Across 20 Low- and Middle-Income Countries

Abstract

Keywords

Introduction

Materials and Methods

Study Design

Variables

Statistical Analysis

Results

Discussion

Conclusions

Footnotes

Acknowledgments

Data Availability

Declaration of Conflicting Interests

Ethical Approval and Consent to Participate

Funding

ORCID iDs

Author Biographies

References