- Open Access
Understanding the factors associated with married women’s attitudes towards wife-beating in sub-Saharan Africa
BMC Women's Health volume 22, Article number: 242 (2022)
Intimate partner violence remains a major public health problem, especially in countries in sub-Saharan Africa. We examined the factors associated with married women’s attitudes towards wife-beating in sub-Saharan Africa.
We used Demographic and Health Survey data of 28 sub-Saharan African countries that had surveys conducted between 2010 and 2019. A sample of 253,782 married women was considered for the analysis. Bivariate and multivariate logistic regression analyses were carried out, and the results were presented using crude odds ratio (cOR) and adjusted odds ratio (aOR) at 95% confidence interval.
The pooled result showed about 71.4% of married women in the 28 countries in this study did not justify wife-beating. However, the prevalence of non-justification of wife-beating varied from 83.4% in Malawi to 17.7% in Mali. Women’s age (40–44 years-aOR = 1.61, 95% CI 1.16–2.24), women’s educational level (secondary school-aOR = 1.47, 95% CI 1.13–1.91), husband’s educational level (higher-aOR = 0.55, 95% CI 0.31–0.95), women’s occupation type (professional, technical or managerial-aOR = 1.66, 95% CI 1.06–2.62), wealth index (richest-aOR = 5.52, 95% CI 3.46–8.80) and women’s decision-making power (yes-aOR = 1.39, 95% CI 1.19–1.62) were significantly associated with attitude towards wife-beating.
Overall, less than three-fourth of married women in the 28 sub-Saharan African countries disagreed with wife-beating but marked differences were observed across socio-economic, decision making and women empowerment factors. Enhancing women’s socioeconomic status, decision making power, and creating employment opportunities for women should be considered to increase women’s intolerance of wife-beating practices, especially among countries with low prevalence rates such as Mali.
Violence against women remains a major public health problem [1,2,3,4]. The United Nations defines violence against women as “any act of gender-based violence that results in, or is likely to result in, physical, sexual, or mental harm or suffering to women, including threats of such acts, coercion or arbitrary deprivations of liberty, whether occurring in public or private life” [1, 2].
Intimate partner violence (IPV) is one of the most common forms of domestic violence and is manifested in physical, emotional, and sexual forms as defined by the World Health Organization (WHO) . IPV has negative physical (e.g., back pain, limited mobility, injury), sexual (e.g., victims of sexual violence, risky sexual behavior, sexually transmitted infections, including HIV), reproductive (miscarriage, stillbirth, preterm delivery, infant mortality), and mental health (depression, post-traumatic stress, and other anxiety disorders such as sleep difficulties and suicidal attempts) consequences for women and children [2, 4,5,6]. It is also associated with socioeconomic problems such as isolation, inability to work, loss of wages and lack of participation in regular activities [2, 4,5,6].
IPV, including wife-beating, is prevalent in all societies across the globe [7, 8]. However, the magnitude and degree to which it is accepted by societies vary across regions; sub-Saharan African countries have higher prevalence of IPV [7, 8]. Out of 15 countries with the highest prevalence of justifying wife-beating in the world, 14 of them are in sub-Saharan Africa (SSA) . About 24% of women in Africa reported that wife-beating is sometimes or always justified . A recent meta-analysis and systematic review study shows that 25.9% of women experienced physical violence or beating by their husbands . Another report in 34 African countries shows that justifying wife-beating varied based on educational level, which is from 41% among individuals with no formal education, to 23% and 25% among individuals who attended primary school and secondary or higher levels of education, respectively . Additionally, justifying wife-beating varied between 25 and 29% among individuals aged 66+ years and 18–25 years, respectively .
The attitude of accepting wife-beating as a cultural norm within communities is linked to increased probability of continuation of a low response to wife-beating in societies [11,12,13,14,15]. People who consider wife-beating as a normal phenomenon are less likely to respond timely and support the victims, and the delayed response is less empathetic [16, 17]. Women who justify any form of violence by a husband, including wife-beating usually blame themselves for the violence, are less likely to report the problem to legal authorities, and are more likely to experience long-term psychological problems [15, 18].
Women’s attitude towards wife-beating is a proxy for insight or perception of their status [19, 20] and one indicator of women’s empowerment [21,22,23]. Evidence shows that women who believe wife-beating is a non-justifiable practice usually are more likely to be aware of their rights, have better self-image and status, and greater sense of empowerment [20, 24, 25]. On the other hand, women who believe wife-beating as justifiable usually believe that a husband has the responsibility of correcting his wife’s behavior even through violent behavior, and those women have less awareness of their rights and less self-image [19, 20, 24, 25]. Hence, refusing or not justifying physical violence against women, including beating by their husbands, is an indicator of empowerment [26, 27].
In May 2016, at the WHO Assembly, several sub-Saharan African countries endorsed a global plan of action to strengthen the role of the health system within a national multispectral response to address interpersonal violence, including wife-beating, against women and girls, and against children . In line with this, some studies in African countries have shown that socioeconomic and demographic factors are associated with wife-beating attitude among women and men [5, 15, 29,30,31,32]. However, most of these studies do not reflect recent data (used relatively old data) from (1999–2001) , (2003–2007) , (2010–2012) , and focused only on prevalence , or a single country, and among all women of reproductive age [5, 29,30,31]. To fill these gaps, we aimed to examine the factors associated with married women’s attitude towards wife-beating attitude using nationally representative data from 28 sub-Saharan African countries.
We extracted nationally representative Demographic and Health Survey (DHS) data conducted between 2010 and 2019 from 28 countries in SSA. DHS is carried out with the financial and technical support of the United States Aid for International Development (USAID) and Inner City Fund (ICF) International . The survey is conducted across several low- and middle-income countries to gather data for monitoring demographic and health indicators, including wife-beating attitude .
In DHS, a two-stage stratified cluster sampling technique is applied. In the first stage, enumeration areas (EAs) are selected using probability proportional to size (PPS), and in the second stage, fixed numbers of households (usually 25–30 households) are sampled from the selected EAs using systematic sampling technique . We included 28 countries in SSA based on the inclusion criteria; country with DHS conducted between 2010 and 2019, availability of outcome variable and key explanatory variables (Table 1). We used the individual recode (IR) files for this study. A total of 253,782 married women were included in the analysis. The DHS datasets are freely available for download at https://dhsprogram.com/data/available-datasets.cfm. This manuscript was prepared based on the guidelines for strengthening of observational studies in epidemiology (STROBE) .
The outcome variable for this study was attitude towards wife-beating. In the DHS, women aged 15–49 are asked five questions to measure their attitude towards wife-beating. The questions focus on whether a husband is justified in hitting or beating his wife for at least one of the following five reasons: burning food, arguing with him, going out without telling him, neglecting the children and refusing to have sexual intercourse with him. According to the DHS guideline, a woman is said to disagree to wife-beating if she disagrees with all of these five reasons. Based on this, an overall binary variable was created with a value 1 and 0, where 1 indicated disagreement with all of these reasons, and 0 indicated agreement with at least one of the reasons for wife-beating [38, 39].
By referring to several studies [5, 15, 29,30,31,32] on women’s attitude towards wife-beating, we included the following independent variables: age in years [15–19, 20–24, 25–29, 30–34, 35–39, 40–44, 45–49]; women’s educational level (no formal education, primary school, secondary school, higher); and husband’s educational level (no formal education, primary school, secondary school, higher). Other explanatory variables included were women’s occupation (no occupation, professional or technical or managerial, agricultural, manual, others); household wealth quintile (poorest, poorer, middle, richer, richest), reading newspaper (no, yes), listening to radio (no, yes), watching television (no, yes), parity (0, 1–2, 3–4, 5+), religion (Christian, Muslim, others), and place of residence (urban, rural).
Other variables were barriers to accessing healthcare services and decision making capacity. Barriers to healthcare services were coded as “no” if the women had no big problems with any of the following four barriers; money needed for treatment, permission of husband to go to health facility, distance to health facility and not wanting to go alone to health facility and coded as “yes” if the women had a big problem with at least one of four barriers. Regarding decision making capacity, we coded as “no” if the women were not involved (either alone or together with their husbands) in all three of the following decision-making parameters: their own health, large household purchases, and to visit families or relatives, and we coded as “yes” if the women were involved in decision making in all three of the above-mentioned decision-making parameters.
Using Stata version-14 software, analysis was done as follows. First, descriptive analysis such as frequency distribution and percentages of the sampled women’s characteristics, and the prevalence of wife-beating attitude were computed. Pearson’s Chi-Square test (χ2) was used to test for proportional difference between explanatory variables and prevalence of wife-beating attitude and, using bivariate logistic regression analysis, we examined the crude odds of each explanatory variable with the prevalence of wife-beating attitude (disagreement with wife-beating). Then, multicollinearity test was conducted to assess the presence of collinearity among the explanatory variables using the Variance Inflation Factor (VIF); we found no significant evidence of collinearity (VIF Mean = 1.87, VIF Min = 1.09, Max VIF = 3.43). Finally, all statistically significant explanatory variables in the bivariate regression test were entered into a multivariable logistic regression model. DHS data has weight variables in each country’s data, and we took these variables into account in the pooled statistical analysis. We first generated weight in each of the country’s dataset, using the weight variables, before we pooled the data together. Thereafter, we executed the “svyset” command in the pooled dataset including the unique codes for each country's population sample unit (PSU) and strata. The adequacy of the final model was checked by Hosmer–Lemeshow Test, and it showed that the model was a good fit (p value = 0.5947). The results were presented using crude odds ratio (cOR) and adjusted odds ratio (aOR), at a 95% Confidence Interval (CI). Any P-value less than or equal to 0.05 (p ≤ 0.05) was considered statistically significant.
The data used for the analysis of this study was secondary data that are publicly available (https://dhsprogram.com/data/available-datasets.cfm). Since ethical procedures were the responsibility of the institutions that funded, commissioned, and managed the surveys, further ethical clearance was not required. ICF international ensures that all the DHS surveys follow the U.S. Department of Health and Human Services rules for respecting of human subjects’ rights. For more details related to ethical issues, readers can visit http://goo.gl/ny8T6X.
Socio-demographic characteristics of respondents
As shown in Table 2, a total of 253,782 married women were included in the analysis for this study. Among the study participants, about 7.9% were adolescents (15–19 years) and 35.3% lived in rural areas. About 27.5% and 21.1% of the participants and their husbands, respectively, had no formal education, and 25.3% of participants were not working. Approximately 69.5% of participants encountered barriers to accessing healthcare services, and 34.6% of participants did not decide, either alone or together with their husband, on any of the three decision making parameters—their own health, purchasing large household expenses and visiting families/relatives.
Prevalence of wife-beating attitude
The pooled result shows that about 71.4% of married women in the 28 countries in SSA disagreed with wife-beating for all the five reasons; going out without telling husband, arguing with husband, neglecting the children; refusing to have sex with husband, and burning food. As shown in Fig. 1, large proportions of married women (88.5%) disagreed with wife-beating when the wife burns food, when the wife refuse to have sex with husband (86.3%), goes out without telling husband (83%), arguing with husband (82.3%) and neglecting children (82%) (Fig. 1).
Prevalence of wife-beating across studied countries
As shown in Fig. 2, the highest prevalence of disagreement with wife-beating was seen in Malawi (83.4%), Angola (71.4), Ghana (70%), Cameroon (68.9%), Togo (68.1%) and Benin (65.4%) respectively. On the other hand, the lowest prevalence of disagreement with beating was reported in Mali (17.7%), Chad (21.2%), Congo Democratic Republic (23%), Guinea (28%) and Ethiopia (33.1%) respectively (Fig. 2).
Prevalence of wife-beating attitude across explanatory variables
Table 2 shows variations in the prevalence of wife-beating attitude (disagreed/not justified for wife-beating) across the explanatory variables’ subgroups. For instance, about 58.4% of married women who were within the age groups 15–19 years disagreed with wife-beating; while 74.3% of married women who were within the age groups of 30–34 years disagreed with wife-beating. The prevalence varied from 62.3 to 92.2% between not educated and those married women who attended higher education respectively. Similarly, there were 61.5–90.8% variations in prevalence of wife-beating attitude (disagreed with wife-beating) between married women with professional/technical/managerial and agricultural occupation types respectively (Table 2).
Factors associated with wife-beating attitude
As shown in Table 3, higher odds of disagreement with wife-beating was seen among married women who were within the age groups of 45–49 years (aOR = 1.50, 95% CI 1.07–2.11), 40–44 (aOR = 1.61, 95% CI 1.16–2.23), 30–34 years (aOR = 1.48, 95% CI 1.12–1.96), 25–29 years (aOR = 1.41, 95% CI 1.09–1.82) and 20–24 years (aOR = 1.34, 95% CI 1.04–1.73) as compared to (15–19 years) married adolescents. Similarly, the results showed higher odds of disagreement with wife-beating among married women who attended secondary school (aOR = 1.54, 95% CI 1.20–1.97) and higher (aOR = 2.50, 95% CI 1.17–5.33) as compared to those who had no formal education. Moreover, higher odds of disagreement with wife-beating was seen among married women who were from richest (aOR = 5.65, 95% CI 3.65–8.77), richer (aOR = 3.18, 95% CI 2.17–4.66) and middle (aOR = 1.51, 95% CI 1.12–2.04) households as compared to married women who were from poorest households. In addition, higher odds of disagreement with wife-beating was seen among married women who had decision making capacity (aOR = 1.38, 95% CI 1.19–1.61) as compared to those married women who had no decision making capacity. On the contrary, we found lower odds of disagreement with wife-beating among married women whose husbands attended primary (aOR = 0.78, 95% CI 0.65–0.94) and secondary school (aOR = 0.75, 95% CI 0.62–0.92) as compared to married women whose husbands did not have formal education.
In this study, we examined the prevalence of disagreement with wife-beating and its associated factors among married women in 28 sub-Saharan African countries. The findings show that about 71.4% of married women in the studied countries disagreed with all the five wife-beating reasons. The prevalence varied across countries, from 83.4% in Malawi to 17.7% in Mali. Our findings are supported by previous literature in SSA . The variation in the prevalence of disagreement with wife-beating across countries could be linked to disparities in women’s educational achievements and cultural norms [15, 40]. Moreover, contextual factors , including socioeconomic disparities across countries [10, 42,43,44] may explain variations in the prevalence of disagreement with wife-beating.
The study shows that woman’s age, women’s educational level, husband’s educational level, women’s occupation type, economic status and decision-making power were significantly associated with disagreement with wife-beating among married women. More specifically, we found higher odds of disagreement with wife-beating among older married women as compared to younger women. These findings are comparable with previous studies in 39 LMIC , Jordan , Nigeria , and Bangladesh . The acceptance of wife-beating may be linked with cultural beliefs [5, 45, 46]. Higher odds of disagreement with wife-beating among older women might be due to the long duration of living within the communities long relationship between women and their husbands, which allow women to understand their important role within the union and have better awareness about societal culture and norms .
In this study, higher odds of disagreement/not justifying wife-beating were seen among married women who attended secondary school compared to married women who had no formal education. Consistent findings were documented in Ethiopia [29, 31], Nigeria , SSA  and 39 LMIC . This could be partly explained by the associations of women’s education with employment opportunities and income-gaining capacities . Women’s education shapes community discourse and affects women’s perception within the society . In the African context, women’s education is also linked with political knowledge, participation, and decision-making capacities [8, 47]. Education is known to positively affect women’s behavior and disagreeing attitude toward wife-beating because they learn about and have greater differentiation capacities between the actual societal norms and the global context regarding women violence [8, 48], and education increases their exposure to global discourse that again raise their capacity in rejecting partner violence [8, 48]. Previous study in Kenya on scholarship programs targeted to increase girls’ secondary schooling  and another study in Sierra Leone focused on policy reform to expand primary school coverage confirmed that girls’ or women’s education reduces acceptance for wife-beating . However, some scholars argue that women with higher educational attainment may face higher risk of beating by their husbands because educated women are more likely to challenge norms and cultures that support male dominance [8, 41].
In contradiction with a previous study in Ethiopia , we found lower odds of disagreement with wife-beating among married women with educated husband as compared to married women whose husbands had no formal education. Further qualitative studies would be beneficial in investigating the reasons for lower odds among married women with educated husbands as compared to non-educated husbands.
Moreover, we found that higher odds of disagreeing/not justifying wife-beating among married women with professional, technical or managerial occupation types as compared to married women who were not working. Comparable findings were reported in SSA  and in a study conducted by WHO . Beyond its positive effect on income and wealth, employment is also protective against abuse [8, 51].
The study also shows higher odds of disagreement with wife-beating among married women in higher economic status as compared to married women in lower economic status. This finding is consistent with previous studies conducted in Ghana , Ethiopia , Nigeria  and LMICs . A plausible explanation could be women in wealthier households are more likely to be educated and have exposure to media that allow them to prefer discussion and democratic ways to any conflicting issues instead of reacting and arguing with their husbands . Again, they might not have shortage of finance and related conflict causing situation . Unlike wealthier women, poorer women may interpret wife-beating as normal life or accept it due to their economic dependence on their husbands [52, 53]. It is not surprising that justifying or tolerating physical violence (including beating) is linked with independence, as poor women who may be independent may justify wife beating due to their dependence on their husband . Studies in SSA also confirmed associations between economic status and wife-beating [52, 55, 56].
Decision-making power of married women was associated with wife-beating attitude . We found higher odds of disagreeing/not justifying wife-beating among married women with decision making power compared to married women who were not involved in decision-making. Previous studies in Ethiopia  and Nigeria  reported similar findings. It is possible that women who had decision-making power would have opportunities to move and access information through their social networks [57,58,59]. Decision making power is an important concept for the woman herself and the society because the combination of access capabilities and actions shape whether women have influence over the decisions about their private lives, their health, and the health of their children and family .
Strengths and limitations of the study
Investigating wide-ranging socioeconomic, demographic, and women’s empowerment factors using a large sample of nationally representative data across several countries in SSA is a major strength of the paper. However, the findings should be interpreted in the context of the following limitations. First, we used data from DHSs that were conducted within nine years; comparison of findings might not be always possible due to the time effect. Second, though we included most countries, still there are few countries in SSA that were excluded from the analysis because of the exclusion criteria; as a result, generalizing the findings to all countries in SSA may not be possible. Third, due to the cross-sectional nature of DHS data, establishing a cause-effect relationship may not be possible. Finally, the survey participant’s self-reported data may be affected by recall bias.
Conclusions and policy implications
Overall, less than three-fourths of married women in the 28 sub-Saharan African countries disagreed with wife-beating but marked differences were observed across socio-economic, decision making and women empowerment factors. Women’s age, women’s educational level, husband’s educational level, women’s occupation, wealth index and women’s decision-making power were significantly associated with wife-beating attitude.
Changing societies’ (including women’s) attitude toward wife-beating required political commitment and integrated implementations of policies and programs among different sectors such as Ministries of Health and Justice, and Ministries of Child and Women or Gender and Social Affairs. Policy makers need to design policies and strategies that enhance women’s socioeconomic status including creating employment opportunities and their decision-making capacity to increase women’s intolerance of wife-beating practices, especially among countries with low prevalence rates such as Mali.
Though further studies on husband education and married women’s attitude towards wife-beating may be needed, these findings highlight that awareness creation for general population and involvement of educational courses about wife-beating practice’s negative consequences to reduce challenges from their husband and the general community.
Moreover, policy and regulation transformation into actions through the development of service delivery protocols or guidelines are required for better achievement in the reduction of wife-beating practices and societal acceptance attitude.
Availability of data and materials
Data for this study were sourced from Demographic and Health surveys (DHS) and available here: http://dhsprogram.com/data/available-datasets.cfm.
Adjusted odd ratio
Crude odds ratio
Demographic and health surveys
Intimate partner violence
Variance inflation factor
United Nations. Declaration on the elimination of violence against women. New York: UN; 1993.
WHO. Violence against women. 2021. https://www.who.int/news-room/fact-sheets/detail/violence-against-women. Accessed 13 March 2021.
World Health Organization. Understanding and addressing violence against women: Intimate partner violence (WHO/RHR/12.36), Geneva. 2012.
WHO, LSHTM, SAMRC. Global and regional estimates of violence against women: prevalence and health impacts of intimate partner violence and non-partner sexual violence. WHO: Geneva, 2013.
Dickson KS, Ameyaw EK, Darteh EKM. Understanding the endorsement of wife beating in Ghana: evidence of the 2014 Ghana demographic and health survey. BMC Womens Health. 2020;20:25. https://doi.org/10.1186/s12905-020-00897-8.
Campbell J, Jones AS, Dienemann J, Schollenberger J, O’Campo P, Gielen AC, et al. Intimate partner violence and physical health consequences. Arch Intern Med. 2002;162:1157–66.
Devries KM, Mak JY, Garca-Moreno C, Petzold M, Child JC, Falder G, Rosenfeld L. The global prevalence of intimate partner violence against women. Science. 2013;340(6140):1527–8.
Cools S, Kotsadam A. Resources and intimate partner violence in Sub-Saharan Africa. World Dev. 2017;95:211–30. https://doi.org/10.1016/j.worlddev.2017.02.027.
AFRO BAROMETER. More than one in four Africans see wife-beating as justifiable, Afrobarometer survey finds. Afrobarometer Accra, Ghana, October 2019.
Muluneh MD, Stulz V, Francis L, Agho K. Gender based violence against women in Sub-Saharan Africa: a systematic review and meta-analysis of cross-sectional studies. Int J Environ Res Public Health. 2020;17:903. https://doi.org/10.3390/ijerph17030903s.
Khawaja M, Linos N, El-Roueiheb Z. Attitudes of men and women towards wife beating: findings from Palestinian refugee camps in Jordan. J Fam Violence. 2008;23(3):211–8.
McKinney CM, Caetano R, Ramisetty-Mikler S, Nelson S. Childhood family violence and perpetration and victimization of intimate partner violence: findings from a national population-based study of couples. Ann Epidemiol. 2009;19(1):25–32. https://doi.org/10.1016/j.annepidem.2008.08.008 (PMID: 18835525).
Guoping H, Yalin Z, Yuping C, Momartin S, Ming W. Relationship between recent life events, social supports, and attitudes to domestic violence: predictive roles in behaviors. J Interpers Violence. 2010;25(5):863–76. https://doi.org/10.1177/0886260509336959 (PMID: 19602674).
Flood M, Pease B. Factors influencing attitudes to violence against women. Trauma Violence Abuse. 2009;10(2):125–42.
Tran TD, Nguyen H, Fisher J. Attitudes towards Intimate PartnerViolence against Women among Women and Men in 39 Low- and Middle-Income Countries. PLoS ONE. 2016;11(11):e0167438. https://doi.org/10.1371/journal.pone.0167438.
Pavlou M, Knowles A. Domestic violence: attributions, recommended punishments and reporting behaviour related to provocation by the victim. Psychiatry Psychol Law. 2001;8(1):76–85.
West A, Wandrei ML. Intimate partner violence a model for predicting interventions by informal helpers. J Interpers Violence. 2002;17(9):972–86.
Neville HA, Heppner MJ, Oh E, Spanierman LB, Clark M. General and culturally specific factors influencing black and white rape survivors’ self—esteem. Psychol Women Q. 2004;28(1):83–94.
BDHS. Bangladesh Demographic and Health Survey, 2014. National Institute of Population Research and Training (NIPROT), Mitra and Associates & Macro International, Dhaka, Bangladesh and Calverton, Maryland, USA, 2016.
Khan MN, Islam MM. Women’s attitude towards wife-beating and its relationship with reproductive healthcare seeking behavior: a countrywide population survey in Bangladesh. PLoS ONE. 2018;13(6):e0198833. https://doi.org/10.1371/journal.pone.0198833.
Asaolu I, Alaofè H, Gunn JKL, Adu A, Monroy A, Ehiri J, Hayden MH, Ernst K. Measuring women’s empowerment in Sub-Saharan Africa: exploratory and confirmatory factor analyses of the demographic and health surveys. Front Psychol. 2018;9:994.
Hanmer L, Klugman J. Exploring women’s agency and empowerment in developing countries: where do we stand? Fem Econ. 2016;22(1):237–63.
Kishor S, Subaiya L. Understanding Women’s Empowerment: A Comparative Analysis of Demographic and Health Surveys (DHS) Data. DHS Comparative Reports No. 20. Calverton, Maryland, USA: Macro International Inc. 2008. https://dhsprogram.com/publications/publication-cr20-comparativereports.cfm
Wado YD. Women’s autonomy and reproductive health-care-seeking behavior in Ethiopia. Women Health. 2017:1–15.
ICDDRB. From evidence to policy: addressing gender-based violence gainst women and girls in Bangladesh. The icddr,b, Dhaka, Bangladesh, 2013.
Wencheko E, Tadesse M. Determinants of Ethiopian women’s attitudes toward wife beating. J Interpers Violence. 2020;35(1–2):510–20.
Kasturirangan A. Empowerment and programs designed to address domestic violence. Violence Against Women. 2008;14:1465–75. https://doi.org/10.1177/1077801208325188.
WHO. Global plan of action to strengthen the role of the health system within a national multisectoral response to address interpersonal violence, in particular against women and girls, and against children. 2016; p. 64. https://www.who.int/reprodusctivehealth/publications/violence/global-plan-of-action/en/.
Ebrahim NB, Atteraya MS. Women’s decision-making autonomy and their attitude towards wife-beatings: findings from the 2011 Ethiopia’s demographic and health survey. J Immigrant Minority Health. 2018;20:603–11.
Oyediran KA. Explaining trends and patterns in attitudes towards wife-beating among women in Nigeria: analysis of 2003, 2008, and 2013. Demogr Health Surv Data Genus. 2016;72:11. https://doi.org/10.1186/s41118-016-0016-9.
Mengistu AA. Socioeconomic and demographic factors influencing women’s attitude towards wife beating in Ethiopia. J Interpers Violence. 2019;34(15):3290–316.
Rani M, Bonu S, Diop-Sidibe N. An emprical investigation of attitudes towards wife-beating among men and women in seven sub-Saharan African countries. Afr J Reprod Health. 2004;8(3):116–36.
Uthman O, Gulu SL, Moradi T. Factors associated with attitudes towards intimate partner violence against women: a comparative analysis of 17 Sub-Saharan countries. BMC Int Health Hum Rights. 2009. https://doi.org/10.1186/1472-698X-9-14.
The DHS Program- Quality information to plan, monitor and improve population, health, and nutrition programs. https://dhsprogram.com/. Accessed 04 March 12, 2021.
DHS Program. Methodology: survey type. https://dhsprogram.com/methodology/survey-Types/dHs.cfm. Accessed 12 March 4, 2021.
DHS Program. Guide to DHS Statistics. Analyzing DHS data. https://dhsprogram.com/data/Guide-to-DHS-Statistics/Analyzing_DHS_Data.htm. Accessed 12 March 2021.
von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. Int J Surg. 2014;12(12):1495–9.
Croft TN, Marshal AMJ, Allen CK, et al. Guide to DHS statistics. Rockville: ICF; 2018.
Zegeye B, Shibre G, Ahinkorah BO, Keetile M, Yaya S. Urban-rural disparities in wife-beating attitude among married women: a decomposition analysis from the 2017 Senegal Continous Demographic and Health Survey. Arch Public Health. 2021;79:102.
Heise LL, Kotsadam A. Cross-national and multilevel correlates of partner violence: an analysis of data from population-based surveys. Lancet Glob Health. 2015;3(6):e332–40. https://doi.org/10.1016/S2214109X(15)00013-3 (PMID: 26001577).
True J. The political economy of violence against women. Oxford: Oxford University Press; 2012.
García-Moreno C, Pallitto C. Global and regional estimates of violence against women: prevalence and health effects of intimate partner violence and non-partner sexual violence. Geneva: WHO; 2013.
Kim JC, Watts CH, Hargreaves JR, Ndhlovu LX, Phetla G, Morison LA, et al. Understanding the impact of a microfinance-based intervention on women’s empowerment and the reduction of intimate partner violence in South Africa. Am J Public Health. 2011;97:1794–802.
Sayem AM, Begum HA, Moneesha SS. Attitudes towards justifying intimate partner violence among married women in Bangladesh. J Biosoc Sci. 2012;44(6):641–60. https://doi.org/10.1017/S0021932012000223 (PMID: 22687269).
Ajayi LA, Soyinka-Airewele P. Key triggers of domestic violence in Ghana: a victim centered analysis. Afr Popul Stud. 2018;32(1):4097–108.
Adjei SB. The social intentionality of battered women’s agency in Ghana. Psychol Dev Soc. 2018;30(1):1–18.
Isaksson A-S, Kotsadam A, Nerman M. The gender gap in African political participation: testing theories of individual and contextual determinants. J Dev Stud. 2013;50(2):302–18.
Pierotti RS. Increasing rejection of intimate partner violence: Evidence of global cultural diffusion. Am Sociol Rev. 2013;78(2):240–65.
Friedman W, Kremer M, Miguel E, Thornton R. Education as liberation? Technical report. National Bureau of Economic Research. 2011.
Mocan NH, Cannonier C. Empowering women through education: Evidence from sierra leone, Working Paper 18016. National Bureau of Economic Research. 2012.
Garca-Moreno C, Jansen HAFM, Ellsberg M, Heise L, Watts C. WHO multicountry study on women’s health and domestic violence against women: Initial results on prevalence, health outcomes and women’s responses, Technical report. Geneva: World Health Organization. 2005.
Adjah ES, Agbemafle I. Determinants of domestic violence against women in Ghana. BMC Public Health. 2016;16:1–9. https://doi.org/10.1186/s12889-016-3041-x.
Vyas S, Jansen HAFM. Unequal power relations and partner violence against women in Tanzania: a cross-sectional analysis. BMC Womens Health. 2018;18:185.
Dhungel S, Dhungel P, Dhital SR, Stock C. Is economic dependence on the husband a risk factor for intimate partner violence against female factory workers in Nepal? BMC Womens Health. 2017;17(1):82.
Doku DT, Asante KO. Women’s approval of domestic physical violence against wives: analysis of the Ghana demographic and health survey. BMC Womens Health. 2015;15:120.
Ahinkorah BO, Dickson KS, Abdul-Aziz S. Women decision-making capacity and intimate partner violence among women in sub-Saharan Africa. Arch Public Health. 2018;76(5):1–10. https://doi.org/10.1186/s13690-018-0253-9.
Folayan MO, Tantawi ME, Vukovic A, Schroth R, Gaffar B, Al-Batayneh OB, et al. Women’s economic empowerment, participation in decision-making and exposure to violence as risk indicators for early childhood caries. BMC Oral Health. 2020;20:54. https://doi.org/10.1186/s12903-020-1045-5.
Furuta M, Salway S. Women’s position within the household as a determinant of maternal health care use in Nepal. Int Fam Plan Perspect. 2006;32:17–27.
Grown C, Gupta GR, Pande R. Taking action to improve women’s health through gender equality and women’s empowerment. Lancet. 2005;365(9458):541–3.
O’Neil T, Domingo P. The power to decide Women, decision-making and gender equality. Briefing. Overseas Development Institute London, UK. 2015. Licence (CC BY-NC 3.0). ISSN: 2052-7209
The authors thank the MEASURE DHS project for their support and for free access to the original data.
There was no funding for this study.
Ethics approval and consent to participate
Ethics approval was not required for this study since the data is secondary and is available in the public domain. More details regarding DHS data and ethical standards are available at: http://goo.gl/ny8T6X.
Consent for publication
No consent to publish was needed for this study as we did not use any details, images or videos related to individual participants. In addition, data used are available in the public domain.
The authors declare no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
About this article
Cite this article
Zegeye, B., Olorunsaiye, C.Z., Ahinkorah, B.O. et al. Understanding the factors associated with married women’s attitudes towards wife-beating in sub-Saharan Africa. BMC Women's Health 22, 242 (2022). https://doi.org/10.1186/s12905-022-01809-8
- Domestic violence
- Women’s empowerment
- Sub-Saharan Africa
- Global health