Prevalence and Social-Ecological Correlates of Intimate Partner Violence in a Conflict Zone—Evidence From the 2015 Afghanistan Demographic and Health Survey

Abstract

This study examined the prevalence and social-ecological correlates of male-to-female intimate partner violence (IPV) in Afghanistan. Using data from the 2015 Afghanistan Demographic and Health Survey, which included 20,793 currently married women, we found that the past-year prevalence of physical IPV was highest (46%), followed by emotional (34%) and sexual forms (6%). Results also showed that the risk of IPV in general was associated with an array of community and societal-, family and relationship-, and person-level factors. Our findings point to potential intervention targets for women in this conflict zone where IPV is a highly pervasive and complex societal challenge.

Keywords

Afghanistan domestic partner violence women

Introduction

Intimate Partner Violence (IPV): Background and Magnitude of Problem

IPV is a pervasive public health challenge that happens in every country and culture, and at all levels of society (World Health Organization [WHO], 2002). Often perpetrated by a husband or male intimate partner, IPV is one of the most common forms of violence against women (VAW) and includes physical aggression, psychological abuse, sexual coercion, and controlling behaviors (WHO, 2012), resulting in severe consequences for women’s physical, mental, sexual, and reproductive health (Garcia-Moreno et al., 2006). IPV can indeed be life-threatening, and in some cases, life-terminating as one-third of female murder victims have been killed by intimate partners (Campbell et al., 2007). Moreover, for many, it can unleash a long chain of ill consequences such as chronic pain, frequent headaches, sleep problems (Black et al., 2011), posttraumatic stress disorder (PTSD), depression, and suicidal ideation (Zlotnick et al., 2006).

On a global scale, 1 in 3 women aged 15 and older will have experienced either physical and/or sexual IPV in their lifetime with rates of initial occurrence, severity, and frequency varying by geo-cultural context (Devries et al., 2013). The United States (U.S.) does not fare better than the rest of the world. In a 2010 national survey commissioned by the U.S. Centers for Disease Control and Prevention (CDC), over one-third of women in the U.S. report having been physically assaulted, sexually assaulted, and/or stalked by an intimate partner (Black et al., 2011). IPV, however, does vary by region, which is explained by the fact that it is a product of social context. According to Jewkes (2002), while complex, two factors seem to be necessary for it to occur: (1) the unequal position of women in either a particular relationship or in society, and (2) the normative use of violence in dealing with conflicts that arise in relationships. Relatedly, predominant theoretical perspectives in the IPV literature contend that higher regional rates of male-to-female IPV can be a result of patriarchal power structures that encourage male dominance and female subordination (Birkley & Eckhardt, 2015; Dixon & Graham-Kevan, 2011).

IPV in the Context of Political Violence

For men who choose to engage in IPV, political violence can give rise to a climate of impunity by disrupting judicial systems designed to assure order (Horn et al., 2014; Jewkes, 2002) and by impeding legal progress on laws protecting women against violence (Haglund & Richards, 2018). Political violence may intensify these patriarchal power structures as it exacerbates pre-existing gender inequalities and challenges traditional gender roles, in turn, making women more vulnerable to IPV in conflict-affected settings (Clark et al., 2010). For example, in Nigeria, women’s autonomy (household decision-making) has been found to place them at higher risk of physical, sexual, and emotional violence, a relationship that was found to be moderated by husband’s controlling and domineering attitudes (Sunmola et al., 2019). Men evidently use violence as a means of re-exerting control and power to maintain gender roles consistent with social norms as revealed in qualitative interviews with working Sri Lankan women who had experienced IPV (Guruge et al., 2017). In Sri Lanka, a country emerging from decades of civil war, Guruge et al.’s (2015) scoping review shows that 20%–60% of Sri Lankan women experience IPV in their lifetime and that younger age, low socio-economic status (SES), and childhood experiences of violence increase the risk of IPV victimization.

Similarly, in a representative sample of Ugandan men and women from the country’s 2006 Demographic and Health Survey (DHS), Speizer (2010) demonstrates that both the perpetration (among men) and victimization (among women) of IPV (physical and/or sexual forms) is significantly higher among those witnessing their fathers beating their mothers. Men and women who witnessed such violence at a young age also held more supportive attitudes toward wife-beating, which in turn increased the odds of perpetration for men and victimization for women. It is noteworthy to mention that older age and higher education reduced the odds of IPV victimization among women, whereas rural residence increased the odds. Additionally, in a more recent study of rural dwellers in tribal regions of Uganda, IPV (physical, emotional, sexual) prevalence rates for both men and women exceeded 43% and higher education was found to be independently associated with lower IPV victimization among women, whereas alcohol consumption and prior war-related traumatic experiences increased the odds of IPV victimization (Kinyanda et al., 2016). The authors also observed a bi-directional relationship between IPV and a broad range of mental disorders for women including problems with alcohol drinking, suicidality, and depression. The psychological sequelae of IPV has also been reported ini the Côte d'Ivoire where women reporting past-year physical and sexual IPV (23% prevalence rate) were three times more likely to report PTSD compared to women who did not report any IPV (Gupta et al., 2014). Strikingly, IPV was a more robust prediictor of mental health than the impacts of war-related violence.

Furthermore, political violence operates to increase women’s risk of IPV by fracturing kinship support systems due to displacement and increasing financial stress brought about by poverty. The weakening of social support structures, along with crises in family roles and responsibilities, the societal habituation to conflict, and the disruption of peaceful conflict resolution practices are what Kelly et al. (2018) point to in explaining why IPV prevalence was 90% higher among Liberian women residing in districts experiencing four to five cumulative years of conflict compared to districts with no conflict. Though conflict and human rights violations apparently have a direct impact on men and their propensity to perpetrate violence on their partners, as observed among displaced Iraqi couples (Goessman et al., 2019) and among South African men whose collective experiences of human rights violations and racial discrimination increased their violent behavior against their female partners (Gupta et al., 2012). Additionally, in Timor-Leste, mental disturbance resulting from torture led to IPV perpetration in men, with low SES adding to the risk (Rees et al., 2018). Impoverished men are more likely to be prevented from achieving the social expectations of providing for their families during and in the aftermath of political violence, leading to frustrations that manifest themselves through violence for men to reassert positions of power in their families.

Finally, a study by Clark et al. (2010) conducted in the occupied Palestinian territories also demonstrates a robust relationship between ongoing political violence and male-to-female IPV prevalence. Women with husbands directly exposed to political violence reported statistically significant higher odds of both physical and sexual violence compared to women whose husbands were not exposed. Regardless of their husband’s exposure, women reporting IPV were more likely to be younger, less educated, and residing in the West Bank than those reporting no IPV. A more recent study conducted in the same region testing Heise’s social-ecological framework (Heise, 1998) shows that many factors central to this model, namely, husband’s education and unemployment, along with controlling behaviors, influenced the prevalence of different forms of IPV among Palestinian women (Haj-Yahia & Clark, 2013). While the authors account for regional differences (Gaza vs. West Bank) as markers of poverty and deprivation, they do not account for regional or district-level degrees of conflict severity regarding IPV prevalence. Instead, they call for further research that uses more direct measurements of regional poverty and that explores potential regional differences in reporting and other regional variables that might impact the risk of IPV.

IPV in Afghanistan: Cultural Norms, Risk Factors, Legal Recourse for Women

The political situation in Afghanistan exemplifies how a decades-long protracted conflict, spanning from the Soviet invasion in 1979 to the US/NATO-led intervention has contributed to the prevalence of IPV. These serial conflicts have indirectly led to IPV by pushing many into poverty, which is at the root of social suffering and a central driver of family conflicts due to overcrowded housing along with domestic violence (DV) enacted by economically frustrated husbands (Eggerman & Panter-Brick, 2010). The UN Population Fund further describes gender-based violence in Afghanistan as a phenomenon that is deeply rooted in cultural norms and complex inequalities that when aligned with poverty and lack of awareness, greatly increase the risk of subordinating women to men (UNFPA, 2016). The UN agency also estimates that a staggering 87% of Afghan women in Afghanistan experience at least one form of IPV (physical, sexual, or psychological violence) in their lifetime, and that 62% experience multiple forms. In more recent estimates based on the country’s 2015 DHS, Coll et al. (2020) estimated a 45.8% prevalence rate for past-12 month physical IPV and 46% for past-12 month emotional and/or sexual IPV. Both values rank highest in comparison to 45 other low- and middle-income countries (LMICs) included in their analysis.

Although limited, recent studies examining Afghan women’s vulnerability to physical and emotional IPV find that individual-level factors, such as having a husband with more than one wife and childhood traumas (women witnessing DV between parents) along with inequitable gender norms, place women at higher risk (Gibbs et al., 2018). In a more recent paper, the same authors find that physical violence is perpetrated not only by husbands, but also by (cruel) mothers-in-law and sibling in-laws/siblings as well (Jewkes et al., 2019). Additionally, the authors cite that IPV was more likely to occur in circumstances of impoverishment or food insecurity (Jewkes et al., 2019). Relatedly, national surveys show that women’s poverty, low education, and early marriage place Afghan women at higher risk of IPV, as do accepting attitudes toward IPV (Nijhowne & Oates, 2008; UNFPA, 2016).

Tran et al. (2016) recently examined “attitudes toward IPV” among men and women across 39 LMICs and found that the rate of acceptance among women (justifying wife-beating under at least 1 of 5 conditions) was highest in Afghanistan (90.2%) and lowest in Argentina (2%). Their analysis shows that countries with low human development indices, high rates of gender inequality, and low country-level education were more accepting of IPV. Tran and colleagues contend that countering acceptance of VAW should become a priority for the achievement of gender equality. The authors suggest reducing IPV prevalence by using the formal education sector to teach young people about respect toward women and equity in relationships.

Interventions that aim to transform social and cultural norms around VAW may hold much promise for preventing IPV (WHO, 2009), especially among young Afghans whose accepting attitudes toward wife-beating seem to be formed at a young age (Li et al., 2018). Although preventing IPV may be a challenge in what Ahmad and Anctil Avoine (2018) refer to as a “culture of misogyny” in Afghanistan, which has been structurally legitimized by tradition, laws, the international community, and the current political situation. While Islam is not inherently misogynist, the fact that religious concepts can be interpreted at will within a patriarchal power structure permits them to work against women (Toor, 2014). Women in parliament defending the Elimination of VAW (EVAW) law couch their arguments in Shari’a in deference to influence of Islamic jurisprudence. Under pressure from foreign aid donors, President Karzai decreed EVAW in 2009 without the stamp of parliament, indicating the tenuousness and reliance on transnational pressure on political elites of efforts to implement the legal strictures of EVAW, which included defining rape (“tajavoz-e jinsi”) as a crime separate from adultery.

The patriarchal bias of the Afghan Penal Code is evident in its treatment of rape as the crime of extramarital sex, known as “zina” (Human Rights Watch, 2016). In a dismal example of legalized and institutionalized secondary victimization, Afghan women are charged with zina even in cases of their own rape and many Afghan women have been forced to marry their rapists (UN Assistance Mission in Afghanistan [UNAMA] & UN High Commissioner for Human Rights [UNHCHR], 2013). Not surprisingly, legal recourse for victimized Afghan women is lacking, given the inconsistent involvement of police in what they deem private family disputes, and the contradictory approach to handling such cases in local courts where laws criminalizing VAW are challenged with laws that defend the use of such acts of violence (Stokes et al., 2016). Following the passage of EVAW, with the support of the International Development Law Organization, special VAW units were formed with prosecutors specializing in complaints of domestic abuse. By 2015, 20 of 34 Afghan provincial capitals had VAW units, but their enforcement of the law appears uneven at best. Wimpelmann (2017) concludes that VAW units provide Afghan women valuable leverage in many cases, but they generally reinforce the view that VAW is a private family problem.

While only 1 in 5 Afghan women seeks help for IPV, most tap into their social supports such as family and friends, whereas a small minority seeks help from health professionals (Metheny & Stephenson, 2019), although it is questionable whether health professionals possess the interpersonal skills needed for addressing such sensitive domestic issues (Samar et al., 2014). For these reasons, along with cultural factors that might stigmatize women who seek a divorce, Afghan women essentially have nowhere to turn. Consequently, IPV may be a continued stressor among victimized Afghan women.

More research examining IPV risk factors and direct causes are needed in order to design effective prevention programs that point to common characteristics of victims and their perpetrators (Abramsky et al., 2011). Additionally, in impoverished countries like Afghanistan, preventing IPV may help fulfill women’s human rights and lead to the achievement of the Sustainable Development Goals (Coll et al., 2020). To this end, the purpose of this study is to examine the prevalence of and factors associated with recent or past-12 month IPV (physical, emotional, and sexual violence) among a nationally representative sample of currently married Afghan women. Here, we use data from Afghanistan’s most recent (2015) DHS—henceforth referred to as “AfDHS.” We take a similar approach used in Haj-Yahia and Clark’s (2013) study of Palestinian women by employing Heise’s social-ecological framework to aid in the selection of variables consistent with this framework from the AfDHS that we expect will contribute to better understanding of male-to-female IPV victimization in Afghanistan.

Method

Participants and Procedures

For this study, we used data from 20,793 currently married women completing the DV module of the most recent (2015) AfDHS. This meant eliminating women who self-reported being widowed (n = 495) and divorced or separated (n = 36). The AfDHS is a nationally representative cross-sectional household survey that provides up-to-date estimates of basic demographic and health indicators from samples stratified by geographic region and by urban and rural areas within each region (Croft et al., 2018). Questionnaires are administered by local staff in various languages spoken in Afghanistan (e.g., Dari, Pashto). Procedures and questionnaires for DHS survey protocols are reviewed by ICF International’s (consulting firm contracted by USAID) Institutional Review Board (IRB) and also by a local (in-country) IRB. This IRB oversight ensures that before each interview, an informed consent statement is read to the respondent, who may accept or decline to participate. Further details about survey administration procedures, consent process, and data management can be found elsewhere (www.dhsprogram.com).

Measures

Past Year Experience of Physical, Emotional, and Sexual Violence

The DV module in the DHS, which is a modified version of the Conflict Tactics Scale (CTS) (Straus, 1979), was used for measuring experience with physical, emotional, and sexual violence within the last 12 months. Seven items were used to assess the frequency of physical violence perpetrated by the respondents’ husband (e.g., ever been pushed, shook, or had something thrown by husband; ever been slapped by husband). Three items were used to assess the frequency of emotional violence (e.g., ever been humiliated by husband), and three for sexual violence (e.g., ever been physically forced into unwanted sex by husband). Items were coded as “1” if at least one of the questions in each of the relevant violence indicators were answered with an “often” or “sometimes” response, and coded as “0” if all items within each indicator were answered with a “never” and/or “yes, but not in the past 12 months” response.

Social-Ecological Factors

Here we make slight adaptations to Heise’s framework; for example, we combine societal- and community-level factors because all of the variables within these two domains are measured at the province-level. Societal- and community-level factors included a measure assessing “accepting attitudes toward wife beating,” a value that we assigned to each province based on an aggregation of this factor measured at the person-level (see below). We also generated and assigned to each province an aggregation of the “household wealth status” variable (measured at the family- and relationship-level) in order to assess province-level wealth. We also created a variable labeled “province-level IPV rate” indicating the overall percent of ever-married women aged 15–49 ever experiencing physical, sexual, or emotional IPV. This was done by using the subnational unit map depicted in the AfDHS main findings report (The World Bank, 2021) illustrating rates of IPV within each province. We assigned each province a prevalence rate based on this map, coded accordingly: 1 = 6%–15%, 2 = 16%–30%, 3 = 31%–50%, 4 = 51%–75%, and 5 = 76%–92%.

To assess political violence, we generated a province-level variable labeled “conflict severity” based on a humanitarian report showing weighted indices of conflict in each province around the time DHS data were collected (UN Office for the Coordination of Human Affairs [OCHA], 2015). Conflict severity according to this chart is operationalized using indicators of civilian casualties resulting directly from: conflict, land mines/unexploded ordnance, and conflict-induced displacement of populations. The conflict severity profile for each province ranges from 1 = “very low” to 5 = “very high.” Lastly, we also included a variable assessing rural/urban residence (0 = “rural,” 1 = “urban”).

Family and relationship-level factors included a scale assessing control issues where respondents were asked to indicate whether their husbands ever demonstrated the following controlling behaviors: (a) jealous or angry if she talks to other men; (b) frequently accuses her of being unfaithful; (c) does not permit her to meet her female friends; (d) tries to limit her contact with her family; and, (e) insists on knowing where she is at all times. Control issues were categorized as 0 = “none,” 1 = “1–2 control issues,” 2 = “3–4 control issues,” and 3 = “5 control issues.” Respondents were also asked to rate the extent to which they were “afraid of their husbands” on a 3-point scale: 0 = “never afraid,” 1 = “sometimes afraid,” and 2 = “afraid most of the time.” We also included variables measuring respondents’ participation in three types of household decisions: the respondent’s healthcare, major household purchases, and visits to family or relatives. Decision making was categorized as 0 = “husband alone or other,” 1 = “jointly with husband,” and 2 = “respondent alone.” Household wealth status quintiles ranged from 1 = “poorest” to 5 = “richest,” which is based on dwelling and household characteristics and access to a variety of consumer goods and services and assets (e.g., a television, car, drinking water, toilet facilities). Respondents also indicated whether or not their husbands were in polygynous marriages: 0 = “no other wives,” 1 = “more than 1 wife”; their husbands’ educational attainment (four categories ranging from 0 = “none” to 3 = “higher education”); the gap in education between the respondent and her husband (0 = “equally educated,” 1 = “husband more educated,” and 2 = “respondent more educated”); whether the respondent was ever beaten by their in-laws (0 = “no,” 1 = “yes”); and the number of people who reside in the respondent’s household.

Another way we adapted Heise’s framework was by applying the term “person” instead of “individual” given that the term “individual” is culturally and historically based on Western frameworks. Person-level factors included variables such as age (provided in 5-year categories ranging from 15 to 49 years), ethnicity (dummy coded as 1 = Pashtun, 2 = Tajik, 3 = Hazara, 4 = Uzbek, 5 = all other ethnicities), educational attainment (four dummy coded categories ranging from 0 = “none” to 3 = “higher education”), current pregnancy status (0 = “no or unsure,” 1 = “yes”), number of children under 5 years of age, and whether respondent’s father ever beat her mother (0 = “no,” 1 = “yes”). Lastly, we included a variable assessing “accepting attitudes toward wife-beating,” that is, whether respondents believed a husband is justified in hitting or beating his wife for specific reasons including: (1) burning food, (2) going out without telling him, (3) refusing to have sexual intercourse, (4) arguing with him, and (5) neglecting the children. Responses ranged from 0 = “does not accept any reason,” 1 = “accepts 1–2 reasons,” 2 = “accepts 3–4 reasons,” and 3 = “accepts all five reasons.”

Data Analysis

SPSS, version 25.0 (IBM Corp., 2017) was used to run descriptive and multivariate statistics. We generated absolute values and percentages for categorical variables, whereas means and standard deviations were generated for continuous variables. Additionally, we estimated the prevalence rate for past-year physical, emotional, and sexual IPV in aggregate, and for each item within each measure. Moreover, binary logistic regression was used to assess relationships at the bivariate level between the three forms of IPV and social-ecological factors. Then, multivariate binary logistic regression modeling was used to examine factors associated with IPV prevalence by entering variables in regression models in three steps, starting with societal- and community-level factors, followed by family- and relationship-level factors, and person-level factors. Hence, we present a total of three multivariate models and report adjusted odds ratios (aOR), 95% confidence intervals (CI), and p-values (statistical significance considered at p < .05). A pseudo measure of the proportion of variance, Nagelkerke R², was calculated for each model. Additionally, we screened for multicollinearity by examining inter-correlations between variables, all of which fell below 0.80, and examined VIF values for each factor by running multiple regressions, all of which were within range. All tests were weighted according to the DHS Guide to Statistics for weighting individual cases (Croft et al., 2018).

Results

Descriptive Analyses

Table 1 indicates that respondents were young (under 35 years of age) with limited education, residing in rural regions, and living in a household consisting of nine people on average. Over half of the respondents resided in a province where half or more women had experienced IPV, and 43% live in a province with high levels of conflict. A small percentage of respondents reported being beaten by their in-laws, having a husband with more than one wife, and making household decisions on their own. Most respondents indicated having a husband with 1–2 control issues, and less than one-fifth did not accept any reason for wife-beating.

Table 1.

Respondent Characteristics (n = 20,793 Weighted).

	n (%) or M (SD)		n (%) or M (SD)
Societal- and community-level factors		Family- and relationship-level factors (cont’d)
Provincial level of accepting attitudes toward wife-beating	1.34 (.32)	Husband–wife education gap
Aggregated wealth	2.95 (.82)	Equally Educated^a	12,440 (59.8)
Provincial levels of IPV (any form)		Respondent more educated	1,265 (6.1)
6%–15%	1,577 (7.7)	Husband more educated	7,088 (34.1)
16%–30%	2,991 (14.5)	Beat by in-laws
31%–50%	4,812 (23.4)	No	18,780 (96.6)
51%–75%	5,504 (26.7)	Yes	661 (3.4)
76%–92%	5,710 (27.7)	Number of people in household	9.31 (4.60)
Residence		Person-level factors
Urban	4,607 (22.2)	Age
Rural	16,186 (77.8)	15–19 years	1,273 (6.1)
Conflict-severity		20–24 years	4,385 (21.1)
Very low	2,124 (10.2)	25–29 years	4,462 (21.5)
Low	3,494 (16.8)	30–34 years	3,114 (15.0)
Medium	6,191 (29.8)	35–39 years	3,161 (15.2)
High	8,984 (43.2)	40–44 years	2,075 (10.0)
Family and relationship factors		45–49 years	2,324 (11.2)
Husband’s control issues		Ethnicity
None	6,462 (31.1)	Pashtun	8,249 (39.7)
1–2 control issues	9,591 (46.1)	Tajik	6,754 (32.5)
3–4 control issues	3,818 (18.4)	Hazara	1,927 (9.3)
5 control issues	923 (4.4)	Uzbek	2,372 (11.4)
Afraid of Husband		All other ethnicities^b	1,474 (7.1)
Never afraid	2,317 (11.2)	Respondent’s education level
Sometimes afraid	10,728 (51.8)	None	17,349 (83.4)
Afraid most of the time	7,674 (37)	Primary	1,625 (7.8)
Household decision-making	Secondary	1,428 (6.9)
Healthcare		Higher	391 (1.9)
Husband alone or other	10,668 (51.3)	Respondent currently pregnant
Jointly with husband	9,174 (44.1)	No or unsure	16,141 (77.6)
Respondent alone	951 (4.6)	Yes	4,652 (22.4)
Purchases	Number of children under 5	1.86 (1.57)
Husband alone or other	11,905 (57.3)	Respondent’s father ever beat mother
Jointly with husband	8,442 (40.6)	No	12,837 (61.7)
Respondent alone	446 (2.1)	Yes	7,956 (38.3)
Visiting family and relatives		Accepting attitudes toward wife-beating
Husband alone or other	9,487 (45.6)	Does not accept any reason	4,018 (19.3)
Jointly with husband	10,121 (48.7)	Accepts 1–2 reasons	7,214 (34.7)
Respondent alone	1,185 (5.7)	Accepts 3–4 reasons	7,065 (34.0)
Wealth (household)		Accepts all 5 reasons	2,497 (12.0)
Poorest	4,239 (20.4)
Poorer	4,365 (21.0)
Middle	4,236 (20.4)
Richer	4,124 (19.8)
Richest	3,829 (18.4)
Husband in polygynous relationship
No	19,390 (93.2)
Yes	1,404 (6.8)
Husband’s education level
None	12,074 (58.6)
Primary	2,979 (14.5)
Secondary	4,257 (20.7)
Higher	1,298 (6.3)

Note. Valid percentages reported.

^aMajority of both men and women reporting no education.

^bIncludes Turkmen, Nuristani, Baloch, Pashai, other.

Table 2 shows that the (weighted) prevalence of physical violence is highest (46%). The experience of being slapped was most frequent, followed by being pushed, shook, or having something thrown at them by their husband. Furthermore, over one-third (34%) of respondents experienced emotional violence, mainly in the form of being humiliated by their husbands. Lastly, only a small proportion (6%) experienced any sexual violence with little variation between the different acts.

Table 2.

Prevalence of Past-Year Experience With Intimate Partner Violence (Weighted).

Violence type and items	N (%)^a
Physical violence	9,540 (46)
1. Ever been pushed, shook, or had something thrown by husband/partner	7,332 (35.3)
2. Ever been slapped by husband/partner	8,295 (39.9)
3. Ever been punched with a fist or hit by something harmful by husband/partner	3,600 (17.3)
4. Ever been kicked or dragged by husband/partner	2,783 (13.4)
5. Ever been strangled or burnt by husband/partner	504 (2.4)
6. Ever been threatened with a knife/gun or other weapons by husband/partner	441 (2.1)
7. Ever had arm-twisted or hair pulled by husband/partner	4,498 (21.7)
Emotional violence	7,152 (34)
1. Ever been humiliated by husband/partner	6,332 (30.5)
2. Ever been threatened with harm by husband/partner	2,781 (13.3)
3. Ever been insulted or made to feel bad by husband/partner	4,111 (19.8)
Sexual violence	1,278 (6)
1. Ever been physically forced into unwanted sex by husband/partner	926 (4.5)
2. Ever been forced into other unwanted sexual acts by husband/partner	583 (2.8)
3. Ever been physically forced to perform sexual acts respondent didn’t want to	761 (3.7)

Note. ^aValid percentages reported combining “sometimes” and “often” response categories.

Bivariate Analyses

In the first column of Tables 3 to 5 we depict the bivariate results of each variable with the respective outcome variable. These bivariate analyses show that participants reporting IPV in general were more likely to be rural, possessed more accepting attitudes toward wife-beating, and lived in provinces with higher IPV rates and conflict levels. Higher level of husband’s education along with their own education seemed to be protective as was greater household wealth. Moreover, respondents reporting different forms of IPV were more likely to have controlling husbands, were afraid of their husbands, and reported being beaten by their in-laws.

Table 3.

Social-Ecological Determinants of Physical Intimate Partner Violence (N = 18,536 Weighted Cases).

	Bi-variate results			Step 1Nagelkerke R² = .29			Step 2Nagelkerke R² = .47			Step 3Nagelkerke R² = .49
	OR	95% CI		aOR	95% CI		aOR	95% CI		aOR	95% CI
Societal- and community-level factors
Provincial level of accepting attitudes toward wife-beating	1.98***	1.82	2.17	1.49***	1.30	1.71	.82*	.70	.95	.58***	.49	.69
Aggregated wealth	.99	.96	1.02	.76***	.71	.81	.68***	.63	.74	.65***	.59	.70
Provincial levels of IPV (any form)
6%–15%	1.00			1.00			1.00			1.00
16%–30%	3.81***	3.05	4.75	6.88***	5.31	8.90	4.37***	3.33	5.74	4.80***	3.63	6.33
31%–50%	9.04***	7.32	11.17	20.01***	15.38	26.04	14.47***	10.94	19.13	12.49***	9.44	16.51
51%–75%	12.95***	10.50	15.98	16.99***	13.39	21.55	10.87***	8.47	13.96	11.25***	8.72	14.53
76%–92%	51.23***	41.43	63.35	70.82***	55.34	90.62	39.30***	30.29	50.99	34.87***	26.82	45.34
Residence
Urban	1.00			1.00			1.00			1.00
Rural	1.64***	1.53	1.75	1.79***	1.64	1.96	1.23**	1.07	1.41	1.25**	1.09	1.44
Conflict severity
Very low	1.00			1.00			1.00			1.00
Low	2.22***	1.98	2.51	2.11***	1.85	2.41	1.84***	1.59	2.14	1.96***	1.67	2.29
Medium	2.37***	2.12	2.65	1.43***	1.25	1.64	.96	.82	1.12	1.06	.90	1.24
High	3.52***	3.16	3.91	2.54***	2.20	2.94	1.87***	1.59	2.20	2.33***	1.95	2.79
Family- and relationship-level factors
Husband’s control issues
None	1.00						1.00			1.00
1–2 control issues	3.85***	3.58	4.14	−			3.00***	2.74	3.28	2.83***	2.58	3.11
3–4 control issues	13.45***	12.21	14.82	−			6.15***	5.45	6.94	5.59***	4.93	6.33
5 control issues	10.97***	9.37	12.84	−			6.56***	5.33	8.07	6.84***	5.48	8.54
Afraid of husband
Never afraid	1.00						1.00			1.00
Sometimes afraid	3.53***	3.12	4.00	−			3.17***	2.74	3.67	3.01***	2.59	3.50
Afraid most of the time	14.44***	12.70	16.41	−			9.85***	8.45	11.48	8.75***	7.48	10.24
Household decision-making
HC/healthcare
Husband alone or other	1.00						1.00			1.00
Jointly	.66	.62	.70	−			1.13*	1.02	1.25	1.12*	1.01	1.24
Respondent alone	.68	.60	.78	−			.98	.81	1.20	.94	.76	1.15
Purchases
Husband alone or other	1.00						1.00			1.00
Jointly	.59***	.56	.63	−			.95	.86	1.06	.96	.86	1.07
Respondent alone	.91	.75	1.09	−			2.18***	1.64	2.91	2.11***	1.58	2.82
Family visits
Husband alone or other	1.00						1.00			1.00
Jointly	.67***	.64	.71	−			.89*	.81	.99	.86**	.77	.95
Respondent alone	.74***	.65	.83				1.02	.86	1.22	1.03	.86	1.23
Household wealth status
Poorest	1.00						1.00			1.00
Poorer	.93	.86	1.01	−			.82**	.73	.92	.87***	.77	.99
Middle	1.18***	1.08	1.28	−			.98	.87	1.11	1.00	.88	1.14
Richer	.93	.85	1.01	−			.79***	.70	.90	.81**	.71	.92
Richest	.58***	.53	.63	−			.58***	.48	.70	.61***	.51	.74
Husband in polygynous relationship
No							1.00			1.00
Yes	1.31***	1.18	1.47	−			1.23**	1.06	1.42	1.15	.99	1.33
Husband’s education level
None	1.00									1.00
Primary	.73***	.68	.80	−			.86**	.78	.96	.87*.	.78	97
Secondary	.72***	.68	.78	−			.85**	.77	.94	.97	.87	1.07
Higher	.54***	.47	.60	−			.86	.73	1.00	1.05	.88	1.24
Husband-wife education gap
Equally educated	1.00						−			−
Husband more educated	.55***	.48	.62	−			−			−
Wife/respondent more Educated	.77***	.73	.82	−			−			−
Beat by in-laws
No	1.00						1.00			1.00
Yes	14.52***	10.92	19.30	−			6.89***	4.94	9.62	5.64***	4.04	7.87
Number of people in household	.99**	.99	1.00				1.00	.99	1.01	.98***	.96	.99
Person-level factors
Age
15–19 years	1.00									1.00
20–24 years	.69***	.65	.73	−			−			1.77***	1.48	2.11
25–29 years	.93*	.87	.98	−			−			2.20***	1.84	2.63
30–34 years	.97	.90	1.04	−			−			2.67***	2.21	3.22
35–39 years	.96	.90	1.03	−			−			2.88***	2.39	3.47
40–44 years	.85***	.78	.93	−			−			2.52***	2.06	3.09
45–49 years	1.09*	1.01	1.18	−			−			3.10***	2.54	3.77
Ethnicity
Pashtun	1.03	.99	1.08	−			−			1.19*	1.01	1.39
Tajik	.85***	.81	.89	−			−			1.34***	1.14	1.57
Hazara	.73***	.67	.80	−			−			1.55***	1.27	1.88
Uzbek	.58***	.54	.63	−			−			.80*	.67	.95
Respondent's education level
None	1.00									1.00
Primary	.61***	.55	.67	−			−			.85*	.74	.98
Secondary	.42***	.37	.47	−			−			.88	.75	1.04
Higher	.34***	.27	.42	−			−			.79	.58	1.08
Respondent currently pregnant
No	1.00									1.00
Yes	.97	.92	1.03	−			−			1.10	1.00	1.20
Number of children under 5	.96***	.95	.97	−			−			1.11***	1.07	1.15
Respondent's father ever beat mother
No	1.00									1.00
Yes	1.84***	1.76	1.93	−			−			1.88***	1.74	2.03
Accepting attitudes toward wife-beating
Does not accept any reason	1.00									1.00
Accepts 1–2 reasons	.90***	.86	.94	−			−			1.20*	1.07	1.34
Accepts 3–4 reasons	1.11***	1.06	1.17	−			−			1.24***	1.11	1.40
Accepts all 5 reasons	.97	.90	1.05	−			−			1.13	.97	1.32

Note. 2,291 missing cases.

*p < .05; **p < .01; ***p < .001.

Table 5.

Social-Ecological Determinants of Sexual Intimate Partner Violence (N = 18,536 Weighted Cases).

	Bi-variate results			Step 1Nagelkerke R² = .11			Step 2 Nagelkerke R² = .28			Step 3 Nagelkerke R² = .30
	OR	95% CI		aOR	95% CI		aOR	95% CI		aOR	95% CI
Societal- and community-level factors
Provincial level of accepting attitudes toward wife-beating	1.56***	1.29	1.88	5.42***	4.04		2.90***	2.13	3.95	1.93***	1.38	2.70
Aggregated wealth	.65***	.60	.70	.58***	.52	.64	.62***	.54	.71	.60***	.51	.69
Provincial levels of IPV (any form)
6%–15%	1.00			1.00			1.00			1.00
16%–30%	2.73**	1.52	4.90	3.90***	2.03	7.48	2.40**	1.23	4.70	2.50**	1.27	4.95
31%–50%	10.97***	6.37	18.89	48.72***	25.64	92.56	22.52***	11.37	44.60	18.44***	9.22	36.87
51%–75%	6.53***	3.78	11.29	14.01***	7.68	25.57	5.85***	3.14	10.87	5.97***	3.19	11.20
76%–92%	10.56***	6.14	18.17	18.47***	9.99	34.15	3.59***	1.88	6.84	3.29***	1.71	6.32
Residence
Urban	1.00			1.00			1.00			1.00
Rural	1.09	.95	1.25	.67***	.57	.79	.90	.69	1.19	.89	.67	1.19
Conflict severity
Very low	1.00			1.00			1.00			1.00
Low	4.15***	2.88	5.99	4.07***	2.73	6.07	3.13***	2.07	4.72	3.29***	2.16	5.01
Medium	6.46***	4.55	9.17	4.88***	3.25	7.32	2.98***	1.95	4.57	3.23***	2.09	5.00
High	3.15***	2.21	4.48	2.46***	1.61	3.76	1.65*	1.05	2.60	2.09**	1.30	3.36
Family- and relationship-level factors
Husband’s control issues
None	1.00						1.00			1.00
1–2 control issues	2.41***	1.98	2.93	−			1.83***	1.46	2.28	1.90***	1.51	2.38
3–4 control issues	6.27***	5.14	7.65	−			4.73***	3.72	6.01	4.67***	3.66	5.96
5 control issues	18.31***	14.62	22.94	−			8.70***	6.57	11.53	8.38***	6.25	11.25
Afraid of husband
Never afraid	1.00						1.00			1.00
Sometimes afraid	1.14	.87	1.48	−			.82	.61	1.10	.82	.61	1.10
Afraid most of the time	4.29***	3.33	5.54	−			2.62***	1.97	3.50	2.53***	1.89	3.39
Household decision-making
HC/healthcare
Husband alone or other	1.00						1.00			1.00
Jointly	.49***	.43	.55	−			.77**	.64	.93	.79*	.65	.95
Respondent alone	1.04	.82	1.33	−			1.32	.92	1.90	1.40	.97	2.03
Purchases
Husband alone or other	1.00						1.00			1.00
Jointly	.59***	.52	.67	−			.92	.75	1.12	.94	.76	1.14
Respondent alone	1.35	.97	1.86	−			1.49	.96	2.32	1.53	.96	2.42
Family visits
Husband alone or other	1.00						1.00			1.00
Jointly	.83**	.74	.93	−			1.02	.85	1.22	1.01	.84	1.21
Respondent alone	1.09	.86	1.38	−			1.28	.92	1.77	1.33	.95	1.86
Household wealth status
Poorest	1.00						1.00			1.00
Poorer	.69***	.58	.821	−			.91	.74	1.11	.94	.77	1.16
Middle	.51***	.43	.61	−			.70**	.56	.87	.76*	.61	.96
Richer	.51***	.42	.60	−			.82	.64	1.05	.85	.66	1.09
Richest	.60***	.51	.72	−			1.04	.73	1.48	1.11	.77	1.60
Husband in polygynous relationship
No	1.00						1.00			1.00
Yes	1.30*	1.06	1.60	−			1.08	.84	1.39	1.16	.90	1.50
Husband’s education level
None	1.00						1.00			1.00
Primary	.75**	.62	.90	−			1.04	.84	1.29	1.03	.83	1.28
Secondary	1.04	.90	1.20	−			1.00	.83	1.19	1.03	.85	1.23
Higher	1.40**	1.14	1.73	−			1.98***	1.53	2.56	2.49***	1.89	3.28
Husband–wife education gap
Equally educated	1.00						−			−
Husband more educated	.53***	.38	.72	−			−			−
Wife/respondent more Educated	1.11	.99	1.25	−			−			−
Beat by in-laws
No	1.00						1.00			1.00
Yes	15.16***	12.81	17.93				5.23***	4.21	6.50	5.17***	4.13	6.47
Number of people in household	1.00	.98	1.01	−			1.01	1.00	1.03	1.02*	1.00	1.04
Person-level factors
Age
15–19 years	1.00									1.00
20–24 years	1.19	.89	1.59	−			−			1.17	.83	1.64
25–29 years	1.67***	1.26	2.21	−			−			1.41*	1.01	1.97
30–34 years	1.42*	1.06	1.91	−			−			.93	.65	1.32
35–39 years	1.21	.89	1.63	−			−			.97	.68	1.39
40–44 years	1.24	.90	1.70	−			−			.76	.52	1.13
45–49 years	1.16	.85	1.59	−			−			.91	.62	1.34
Ethnicity
Pashtun	.933	.73	1.19	−		.	−			.68*	.51	.91
Tajik	1.57***	1.24	2.00	−			−			.87	.65	1.17
Hazara	1.29	.98	1.71	−			−			1.03	.73	1.45
Uzbek	.30***	.21	.44	−			−			.32***	.21	.49
Respondent's education level
None	1.00									1.00
Primary	.67**	.53	.86	−			−			.88	.67	1.16
Secondary	.43***	.31	.58	−			−			.44***	.30	.64
Higher	.72	.45	1.15	−			−			.38*	.19	.79
Respondent currently pregnant
No	1.00									1.00
Yes	1.28***	1.12	1.45	−			−			1.09	.93	1.28
Number of children under 5	1.01	.97	1.04	−			−				.91	1.03
Respondent's father ever beat mother
No										1.00
Yes	1.99***	1.77	2.23	−			−			1.06	.92	1.22
Accepting attitudes toward wife-beating
Does not accept any reason	1.00									1.00
Accepts 1–2 reasons	2.00***	−	2.42	−			−			1.30*	1.03	1.63
Accepts 3–4 reasons	1.69***	−	2.06	−			−			1.07	.85	1.36
Accepts all 5 reasons	3.25***	−	4.02	−			−			1.55**	1.18	2.05

Note. 2,291 missing cases.

*p < .05; **p < .01; ***p < .001.

Multivariate Analyses

Tables 3 to 5 report the results of our multivariate analyses for physical, emotional, and sexual IPV, respectively.

Societal- and Community-Level Factors

Societal-community factors in the first step of each model show that provincial rates of IPV, an indicator of VAW norms, was the most influential factor in increasing the likelihood of all forms of violence. However, the effect of provincial IPV was strongest for physical IPV, as shown in Table 3, as respondents were 70 times more likely to report being physically battered by their husband in the past year. Another indicator of VAW norms, province-level “accepting attitudes toward wife-beating,” was positively associated with all forms of IPV, with the strongest effect observed in Table 5 for sexual IPV.

However, with the exception of sexual violence where women in rural regions were significantly less likely to report this outcome, rural residence increased the risk of both physical and emotional IPV. Moreover, respondents residing in provinces where the severity of conflict ranged from “low” to “high” were significantly more likely to report all forms of IPV compared to those residing in provinces with “extremely low” levels of conflict. Lastly, higher aggregated wealth, a proxy for (lower) provincial levels of generalized poverty, significantly decreased the odds of all forms of IPV as exemplified by the 42% decrease in sexual IPV shown in Table 5. Taken together, Nagelkerke R² values indicate that the combination of societal-community-level factors in Step 1 of each model explained the most variance for physical (29%) and emotional IPV (28%) IPV and the lowest for sexual IPV (11%).

Family- and Relationship-Level Factors

The effect of wealth operated differently at the household level, where it was most influential for reducing the likelihood of physical violence, as shown in Table 3, and exerting a non-significant relationship with emotional violence in Table 4. Furthermore, the effects of decision making varied depending on the type of household decision and respondents’ level of involvement in those decisions. For example, while decision making as a whole showed no significant associations with sexual violence, joint decisions regarding visiting family and relatives reduced the risk of emotional (aOR = .85) and physical IPV (aOR = .89). However, the risk of these forms of IPV increased when decisions regarding large household purchases were made alone by the respondent (emotional IPV: aOR = 1.79; physical IPV: aOR = 2.18).

Table 4.

Social-Ecological Determinants of Emotional Intimate Partner Violence (N = 18,536 Weighted Cases).

	Bi-variate results			Step 1 Nagelkerke R² = .28			Step 2Nagelkerke R² = .42			Step 3 Nagelkerke R² = .44
	OR	95%	CI	aOR	95%	CI	aOR	95%	CI	aOR	95%	CI
Societal- and community-level factors
Provincial level of accepting attitudes toward wife-beating	2.76***	2.50	3.04	2.17***	1.85	2.55	1.21*	1.02	1.43	1.22*	1.01	1.47
Aggregated wealth	1.14***	1.10	1.18	.85***	.79	.90	.82***	.76	.89	.84***	.77	.91
Provincial levels of IPV (any form)
6%–15%	1.00			1.00			1.00			1.00
16%–30%	1.99***	1.53	2.59	3.30***	2.44	4.45	2.43***	1.78	3.32	2.40***	1.75	3.28
31%–50%	7.19***	5.66	9.14	15.31***	11.30	20.76	10.00***	7.28	13.75	7.84***	5.71	10.77
51%–75%	9.61***	7.57	12.19	11.97***	9.10	15.74	8.96***	6.74	11.90	8.36***	6.26	11.15
76%–92%	37.23***	29.35	47.21	51.82***	39.17	68.54	28.97***	21.63	38.80	23.87***	17.81	31.99
Residence
Urban				1.00			1.00			1.00
Rural	1.04	.97	1.11	1.09	.99	1.19	.95	.82	1.09	.97	.84	1.12
Conflict severity
Very low	1.00			1.00			1.00			1.00
Low	.633***	.560	.715	.47***	.41	.54	.38***	.32	.44	.38***	.33	.45
Medium	.899	.807	1.001	.43***	.37	.49	.30***	.26	.35	.33***	.28	.39
High	1.854***	1.675	2.052	.79**	.69	.91	.58***	.49	.67	.63***	.53	.75
Family- and relationship-level factors
Husband’s control issues
None	1.00		1.00	1.00
1–2 control issues	3.15***	2.89	3.43	−			2.61***	2.37	2.89	2.65***	2.39	2.93
3–4 control issues	16.64***	15.03	18.40	−			8.62***	7.65	9.72	9.25***	8.17	10.48
5 control issues	14.61***	12.49	17.08	−			10.94***	9.01	13.30	13.62***	11.08	16.76
Afraid of husband
Never afraid	1.00				1.00	1.00
Sometimes afraid	4.41***	3.80		−			4.32***	3.63	5.13	4.27***	3.58	5.09
Afraid most of the time	9.36***	8.06		−			5.73***	4.80	6.84	5.43***	4.53	6.51
Household decision-making
HC/healthcare
Husband alone or other	1.00						1.00			1.00
Jointly	.83	.78	.88	−			1.15**	1.04	1.27	1.15**	1.04	1.27
Respondent alone	.47	.40	.55	−			.61***	.49	.76	.57***	.46	.71
Purchases
Husband alone or other	1.00						1.00			1.00
Jointly	.76	.72	.81	−			1.37***	1.24	1.52	1.33***	1.20	1.48
Respondent alone	.84	.69	1.03	−			1.79***	1.33	2.40	1.65**	1.22	2.24
Family visits
Husband alone or other	1.00						1.00			1.00
Jointly	.77***	.73	.82	−			.85**	.77	.94	.83**	.75	.92
Respondent alone	.77***	.68	.88	−			1.01	.84	1.21	1.04	.87	1.26
Household wealth status
Poorest	1.00						1.00			1.00
Poorer	1.06	.96	1.15	−			1.08	.96	1.22	1.13	1.00	1.28
Middle	1.20***	1.10	1.32	−			1.07	.95	1.21	1.06	.94	1.21
Richer	1.06	.96	1.16	−			.97	.85	1.10	.96	.84	1.10
Richest	1.04	.94	1.14	−			1.01	.84	1.22	.96	.79	1.16
Husband in polygynous relationship
No	1.00						1.00			1.00
Yes	1.44***	1.29	1.61	−			1.48***	1.28	1.71	1.44***	1.24	1.67
Husband’s education level
None	1.00						1.00			1.00
Primary	.79***	.72	.86	−			.98	.88	1.09	1.01	.91	1.13
Secondary	.80***	.74	.86	−			.93	.84	1.02	.97	.88	1.08
Higher	.74***	.65	.84	−			.94	.80	1.10	1.00	.85	1.19
Husband–wife education gap
Equally educated	1.00
Husband more educated	.57***	.50	.65	−
Wife/respondent more Educated	.80***	.75	.85	−
Beat by in-laws
No	1.00						1.00			1.00
Yes	4.56***	3.85	5.40	−			1.73***	1.40	2.13	1.57***	1.27	1.95
Number of people in household	.99***	.99	1.00	−			1.01	1.0	1.02	.98**	.97	.99
Person-level factors
Age
15–19 years	1.00		−							1.00
20–24 years	1.51***	1.30	1.75	−					−	1.29**	1.07	1.55
25–29 years	2.15***	1.86	2.49	−					−	1.96***	1.63	2.36
30–34 years	1.92***	1.65	2.23	−					−	1.73***	1.43	2.10
35–39 years	1.96***	1.68	2.27	−					−	1.91***	1.57	2.32
40–44 years	1.99***	1.69	2.33	−					−	2.09***	1.70	2.58
45–49 years	2.25***	1.92	2.63	−					−	2.12***	1.73	2.60
Ethnicity
Pashtun	2.74***	2.38	3.15	−					−	1.47***	1.23	1.77
Tajik	2.60***	2.26	2.99	−					−	1.79***	1.49	2.14
Hazara	2.03***	1.72	2.39	−					−	1.49***	1.20	1.85
Uzbek	1.46***	1.24	1.71	−					−	1.20	.98	1.46
Respondent's education level
None	1.00									1.00
Primary	.66***	.59	.74	−					−	.84*	.73	.98
Secondary	.69***	.61	.77	−					−	1.05	.90	1.24
Higher	.56***	.44	.71	−					−	.81	.59	1.10
Respondent currently pregnant
No	1.00									1.00
Yes	.93**	.86	.99	−					−	.80***	.73	.88
Number of children under 5	1.03*	1.01	1.05	−					−	1.13***	1.09	1.17
Respondent's father ever beat mother
No	1.00									1.00
Yes	2.47***	2.33	2.62	−					−	1.34***	1.24	1.44
Accepting attitudes toward wife-beating
Does not accept any reason	1.00									1.00
Accepts 1–2 reasons	1.79***	1.64	1.95	−					−	.96	.86	1.08
Accepts 3–4 reasons	1.79***	1.64	1.95	−					−	.71***	.63	.80
Accepts all 5 reasons	1.64***	1.47	1.83	−					−	.50***	.43	.59

Note. 2,291 missing cases.

*p < .05; **p < .01; ***p < .001.

However, the influence of other family- and relationship-level factors entered in Step 2 was more consistent such that the likelihood of all forms of IPV positively increased among respondents who reported having a husband with control issues (e.g., physical violence, aOR = 7.34 for husbands with ≥ 5 control issues), one they are afraid of (e.g., emotional violence, aOR = 10.94 for “afraid most of the time”), and ever having been beaten by their in-laws (e.g., sexual violence, aOR = 5.23). The addition of family-relation factors in Step 2 of each model increased variances for each model, but most notably for physical and sexual violence where R² values increased by 18% and 17%, respectively.

Person-Level Factors

Person-level factors in Step 3 of each model show that all forms of violence increase with age, but decrease with higher educational attainment. With the exception of sexual violence, the risk of physical and emotional IPV was significantly higher among respondents who reported witnessing their fathers beat their mothers. Accepting attitudes toward wife-beating unexpectedly demonstrated an inverse association with emotional violence, but was positively associated with physical and sexual IPV. The addition of person-level factors accounted for very little additional variance to each model, from 1% to 2%.

Discussion

In this article, we examined the prevalence and social-ecological determinants of IPV victimization among Afghan women. In our cross-sectional analysis of a socially diverse and nationally representative sample of currently married women from the AfDHS, we found that rates of physical, emotional, and sexual violence were relatively high when compared to those observed in neighboring DHS countries such as Pakistan (Iqbal & Fatmi, 2018). In fact, the rate of physical IPV that we report (46%) far exceeds the 30% global prevalence rate of ever-partnered women 15 years of age and older experiencing physical violence or sexual coercion (Devries et al., 2013).

With the causes of IPV being highly complex (Jewkes, 2002), especially in this cultural context, we referred to Heise’s social-ecological framework to streamline the selection of variables from the DHS in order to explain this phenomenon. Few studies have applied Heise’s framework in an active conflict zone, a notable one being Haj-Yahia and Clark’s (2013) study of Palestinian women showing statistically significant positive associations between political violence and moderate to severe forms of physical and emotional IPV.

Similarly, in our analysis, we found that conflict severity was associated with IPV, but only for physical and sexual forms. The effect of conflict severity maintained a robust positive relationship with physical and sexual violence even after controlling for all other social-ecological factors. What might explain this relationship is the possibility that aggressive masculine identities are intensified in regions where the rate of conflict is high, that violence may be viewed as a socially acceptable way to resolve conflict (Kelly et al., 2018), or that judicial systems meant to protect women are hampered in provinces where conflict is high (Clark et al., 2010; Horn et al., 2014). Alternatively, male partners endure extreme socio-economic stress due to political instability, which prevents them from meeting social expectations of manhood—frustrations that are known to manifest in perpetrating violence in Afghan men (Eggerman & Panter-Brick, 2010). Our argument is supported by a consistent relationship between higher aggregated wealth and lower prevalence of all forms of IPV.

We also found that acceptance of wife abuse at the societal- and community- and person-levels were statistically associated with all forms of IPV. Learned social behavior (Jewkes, 2002) is a plausible reason for this finding at the person-level. Additionally, the inter-generational transmission of spousal violence is evident in our data, that is, the risk of physical and emotional IPV being significantly higher among respondents whose fathers beat their mothers. When reviewing the extremely high acceptance of IPV by the women themselves (only 19% are non-accepting), we would argue that this may be a learned behavior. Qualitative accounts from Afghan children reveal that witnessing and experiencing violence perpetuates violence itself (Li et al., 2018); ultimately, women end up accepting abuse and men feel justified in perpetrating it.

The troubling result of this finding is the likely continuation of these behaviors. For Afghan boys specifically, their exposure to interpersonal violence likely instills conceptions of violent masculinity where displays of aggression and intimidation have become socially accepted rites of passage in some parts of Afghanistan, even affecting their relationships with female relatives (Ahmadi & Stanikzai, 2018). Ill-conceived notions of masculinity may partly explain why the frequency of husbands’ controlling behaviors reported by respondents in our data is common and in effect independently associated with all forms of IPV. Alternatively, controlling behaviors can be explained by the fact that men are expected and socialized at a young age to uphold authority in the household, which means that even a young boy feels a need to assert control over the women in his household to ensure that they behave morally (Dupree, 2002). This same expectation of needing to control their household also explains why only 2% of women reported making household financial decisions on their own. It could be that the violence perpetrated in situations where women make such autonomous decisions is a way for men to regain (perceived) control, as similarly observed in Sri Lanka (Guruge et al., 2017) and Nigeria (Sunmola et al., 2019).

An important finding of this study is the very strong influence of province-level rates of IPV on all forms of IPV. Comparing odds ratios, province-level IPV is the most influential variable in all three full models. This pattern illustrates both the great influence of regional behavioral norms and the large amount of regional variation within Afghanistan. Understanding the sources of lower levels of IPV in some provinces and even in some urban centers may point to pathways for decreasing IPV in other provinces and regions. We often think of IPV as a personal or familial matter, but this finding reminds us that in Afghanistan the prevalence of IPV is very much related to broader social and cultural conditions.

While our findings and study implications are generalizable to married women in Afghanistan, our study clearly has some limitations. First, because the DHS was limited in the types of variables assessed, we could not account for critical institutional factors that future research ought to consider. These factors include the role of religion, government, and political structures as they pertains to sanctioning IPV within marriage, along with marriage laws and women’s civil rights. Second, similar to Iqbal and Fatmi’s (2018) IPV study in Pakistan, we did not include important IPV risk factors such as the husband's exposure to violence or maltreatment during childhood, and husband’s attitudes toward wife-beating and gender equality. Also, the cultural validity of the CTS in Afghanistan is questionable. Despite providing a diverse and comprehensive account of different forms of violence, it was not previously validated in this cultural context. Hence, our measures of IPV may not have provided a fully accurate picture of violent acts associated with different forms of IPV.

Nonetheless, our results support the urgent need for interventions aiming to transform attitudes and norms that condone and encourage VAW. Yet, we understand the challenges of the current social and political landscape where VAW activists and programs are often viewed as corrupt Western imperialists aiming to undermine the Afghan family and morals. Likewise, we wish to distance ourselves from narratives which frame Afghan women as victims of a hopelessly backward culture in need of saving. This said, we believe creative interventions which are culturally tailored to the region are urgently needed. Preventing and reducing IPV may be fostered in Afghanistan by targeting both boys and girls, in order to instill ideals of gender equity, tolerance, peaceful masculinity, and basic conflict resolution (Ahmadi & Stanikzai, 2018). Moreover, young males are an especially important group as they set out to establish their own families. In fact, the WHO’s guidelines on “changing cultural and social norms” for societies that are supportive of violence call for working with male peer groups, given the strong influence that young adults can have on each other’s behavior (WHO, 2009). A multisectoral response is needed (Devries et al., 2013), and the WHO suggests correcting gender-related misperceptions through mass media education campaigns, enforcing stricter laws altering norms linked to violence, and more evaluations of programs aiming to reduce gender-based violence. In conclusion, our data indicate that IPV is a pervasive societal problem in Afghanistan and that factors associated with conditions created by decades of political violence help explain this phenomenon.

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Qais Alemi

Author Biographies

Qais Alemi, PhD, MPH, MBA, is a global health researcher. His research has focused on investigating the unmet social and psychological needs of vulnerable populations, namely, those affected by political violence. His publications encompass studies of refugees resettled in the United States and in Turkey, along with various papers examining help-seeking patterns, tobacco use, and HIV stigma in Afghanistan. He is currently researching suicide stigma in Pakistan, and the development and implementation of mobile technologies for remediating stress among both Afghan and Pakistani youth.

Carl Stempel, PhD, is a cultural sociologist interested in social inequality and social transformation. His research has focused on the emergence of modern sport; how gender and discrimination influence refugee resettlement and economic integration; sport and social class distinctions; sport, masculinity, and militarism; how media use and politics influence conspiracy beliefs; and the transformation of intimate relationships. He is currently researching the influence of anti-Muslim discrimination on Muslims’ civic engagement; the race-class dynamics of white identity politics in the United States; and how public universities are supporting students’ academic performance and well-being during the COVID-19 pandemic.

Susanne Montgomery, PhD, MSN, MPH, is a social/behavioral epidemiologist with a focus on hard-to-access, underserved populations and health disparities from a behavioral health and prevention perspective. She has also conducted several collaborative studies in international settings and with immigrants to the United States. She has been the PI and Co-I of several NIH, CDC, and State-funded projects and has published over 140 peer-reviewed articles. She regularly serves as a peer reviewer for NIH, CDC, and several journals.

Patrick M. Koga, MD, MPH, FRSPH, directs refugee health research at UC Davis School of Medicine, Department of Public Health Sciences. In the past 25+ years, his work has centered on traumatized war refugees, including evaluations of new arrivals at Sacramento County Refugee Health Clinic. His transcultural psychiatry research spans wide areas from Kyrgyzstan, Afghanistan, Russia, and Iran, to Turkey, and the Arab Region. His research interests include cultural, religious, and spiritual modorators of PTSD resilience; Ulysses Syndrome; refugee domestic violence; cultural adaptations of mobile mental health apps; legal-mental health intersectionality in asylum adjudication; and the medicalization and commodification of refugee suffering.

Valerie Smith, PhD, MPH, is a refugee health studies scholar, with a focus on the migration, resettlement, and adjustment of refugees and influences of the social and structural environments on health disparities. She completed community research on The Information Needs and Associated Communicative Behaviors of Afghan Female Refugees in the San Francisco Bay Area and served as Co-PI for an Afghan refugee community health and mental health needs assessment survey. She is an award-winning instructor at California State University, East Bay.

Kelly Baek, PhD, MSW, has several years of experience in recruitment, outreach, and retention for projects and programs such as volunteer programs, community boards, and pipeline activities to diversify the behavioral health workforce. Her research interests include community-based research; sustainable, culturally sensitive mental health interventions; and program development and evaluation.

Catherine C. Fisher, MSW LCSW is a clinical social worker and doctoral student engaged in research focused on housing and homelessness and the role of faith-based organizations in public–private partnerships and policy advocacy. She has conducted several program evaluations and secured $1.5 million in grant funding for community nonprofits serving youth and families. She has presented her work through publications in social work journals and at professional conferences.

Nipher Malika, PhD, MPH, is a policy researcher with an extensive background in community-based participatory research among marginalized, minority, and immigrant populations. Her research centers on closing the gap in health inequalities through (1) understanding how various social determinants affect the health of individuals and communities; and (2) identifying solutions, in partnership with communities, to address a range of inequities.

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