Magnitude and determinants of intimate partner violence against women in Somalia: evidence from the SDHS survey 2020 dataset

Abstract

Background

Intimate partner violence (IPV) is a pervasive issue across Sub-Saharan Africa and other developing countries, including Somalia. Understanding the prevalence and drivers of IPV against women is crucial for effective prevention and intervention efforts. However, limited research has focused on identifying these determinants specifically in the Somali context.

Purpose

This study aims to identify the prevalence and key determinants of IPV in Somalia, including age groups, administrative regions, place of residence, educational level, household size, husband/partner’s education and work, respondent’s work, and total children ever born.

Methods

Data from the Somali Demographic and Health Survey (SDHS) 2020 were analyzed. Univariate analysis, bivariate analysis and multivariable logistic regression models were used to assess the associations between the identified determinants and IPV.

Results

The study found significant associations between several factors and IPV. Age, region of residence, type of residence, educational level, husband/partner’s education and work, respondent’s work, and total children ever born were identified as significant determinants of IPV in Somalia. Younger age groups, rural residence, lower educational attainment, unemployment of the husband/partner and respondent, and larger household size were associated with an increased risk of IPV.

Conclusion and recommendations

The findings highlight the importance of addressing socio-demographic factors to effectively combat IPV in Somalia. Based on the results, recommendations include implementing comprehensive educational programs promoting gender equality and challenging traditional norms, enhancing economic opportunities for women and men, tailoring interventions to address regional disparities, strengthening the legal framework, and improving support services for IPV survivors. Future research should focus on longitudinal studies, qualitative research, intervention evaluation, multi-sectoral collaboration, and the impact of IPV on children. By addressing these recommendations and conducting further research, stakeholders can work towards preventing and reducing IPV in Somalia and other similar contexts.

Background

Intimate partner violence (IPV) is a significant public health concern that affects individuals and communities worldwide. It encompasses various forms of physical, sexual, and psychological abuse perpetrated by a current or former intimate partner [1]. The consequences of IPV are far-reaching, leading to physical injuries, mental health issues, and long-term social and economic burdens [2]. Understanding the determinants of IPV is crucial for developing effective prevention strategies and interventions.

Conceptually, IPV is influenced by a complex interplay of individual, relational, and societal factors [3, 4]. Several theoretical frameworks, such as the ecological model, social learning theory, and feminist theory, have been utilized to understand the multifaceted nature of IPV [5]. The ecological model posits that IPV is influenced by multiple levels of factors, including individual characteristics, relationship dynamics, community influences, and societal norms [4]. Social learning theory highlights the role of observational learning and socialization processes in perpetuating violent behaviors. Feminist theory emphasizes the power imbalances and gender inequalities that contribute to violence against women.

Globally, efforts to address IPV have gained momentum over the past few decades. In 1993, the United Nations Declaration on the Elimination of Violence against Women recognized IPV as a violation of women’s human rights. Regionally, Sub-Saharan Africa has faced significant challenges in addressing IPV due to socio-cultural norms, economic disparities, and weak legal systems. Within East Africa, countries like Kenya, Uganda, and Tanzania have made strides in recognizing and responding to IPV through legislation, awareness campaigns, and support services [2, 3, 7,8,9,10,11].

In Somalia, a country located in the Horn of Africa, the historical context has influenced the prevalence and response to IPV. Decades of conflict and political instability have disrupted social structures and exacerbated gender inequalities. Traditional gender norms, such as male dominance and female subordination, have persisted, contributing to the perpetuation of IPV. Limited research has been conducted specifically on the determinants of IPV in Somalia, highlighting the need for context-specific studies in this area. To the best of our knowledge, this study represents the first comprehensive investigation into the determinants of IPV in Somalia. Prior to this study, existing research had primarily focused on documenting the prevalence and consequences of IPV rather than identifying the underlying factors. By examining the determinants of IPV in Somalia, this research aims to fill an important knowledge gap and provide insights into the specific contextual factors that contribute to IPV in the country.

Building on the existing theoretical frameworks, this study aims to derive explanatory variables from the first-ever Somali Demographic and Health Survey (SDHS) 2020 data. The SDHS provides a rich dataset that allows for the exploration of various socio-demographic factors associated with IPV. By utilizing this dataset, we can examine the associations between age groups, region of residence, type of residence, educational level, household size, husband/partner’s education and work, respondent’s work, and total children ever born, as well as the risk of experiencing IPV. The purpose of this study is to identify the key determinants of IPV in Somalia. By examining the associations between socio-demographic factors and IPV, one aim is to provide evidence-based insights that can inform targeted interventions and policies. The novelty of this study lies in its focus on Somalia, a country with unique socio-cultural and contextual factors, and the utilization of the first-ever SDHS data for this purpose. The main contributions of this research include enhancing the understanding of IPV in Somalia, highlighting the specific determinants that influence its occurrence, and providing recommendations for prevention and intervention efforts.

Review of literature

IPV against women is a significant problem globally, causing physical, sexual, and psychological harm [12]. It is the most prevalent form of violence against women, leading to various negative outcomes such as depression, HIV, injuries, and low-birth-weight babies [13]. Understanding the prevalence and drivers of IPV is crucial for developing effective interventions and support services to address the mental health needs of survivors [14, 15]. This literature review below examines existing studies on IPV in Africa, with a focus on Sub-Saharan Africa and Somalia, to provide context for assessing the prevalence and drivers of IPV against women in Somalia.

Studies conducted in Sub-Saharan Africa have consistently shown a high prevalence of IPV among women, ranging from 20% to over 75% [16, 17]. Emotional and physical violence are the most commonly reported forms of IPV in this region [17]. Risk factors contributing to IPV in Sub-Saharan Africa include low educational attainment of both partners, partner’s alcohol use, exposure to domestic violence during childhood, and various household and community/cultural factors [17]. IPV rates are particularly high among pregnant women in Africa, with key risk factors including HIV infection, a history of violence, and substance use by the partner [18]. These findings highlight the urgent need for targeted interventions to address IPV in Sub-Saharan Africa.

Research conducted in East Africa, including Somalia, indicates a high prevalence of IPV in this region [17,18,19,20]. Factors such as poverty, alcohol abuse, and adherence to traditional gender roles have been identified as drivers of IPV in East Africa [17, 19]. The intersection of IPV with the HIV pandemic further exacerbates the issue, underscoring the importance of prevention efforts [19]. In East Africa, IPV rates among pregnant women remain unacceptably high. Various risk factors contribute to this issue [5, 6, 20, 21]. Additionally, rural and less educated women in the Middle East and North Africa face a higher risk of IPV [22]. These results emphasize the need for comprehensive interventions to address the determinants and prevalence of IPV in East Africa, including Somalia.

Although research specific to IPV in Somalia is limited, studies conducted in other African countries offer valuable insights. For example, in war-torn Somalia, violence associated with conflict has created fear and limited access to reproductive health services [21]. In Ethiopia, a neighboring country, there is a high prevalence of IPV, with factors such as abduction, polygamy, and spousal hostility contributing to the likelihood of violence [23]. The intersection of IPV with the HIV pandemic is also recognized in Sub-Saharan Africa, emphasizing the importance of community-based prevention programs [19]. Scholars have highlighted the need for interdisciplinary collaboration and further research on IPV in the Ethiopian context [24]. These studies suggest that similar factors may contribute to IPV in Somalia, but more research is needed to understand the specific determinants and prevalence in this context.

The literature review thus provides an overview of existing studies on IPV against women in Africa, with a focus on Sub-Saharan Africa and Somalia. The prevalence of IPV in Sub-Saharan Africa, including East Africa, is alarmingly high, with risk factors such as poverty, alcohol abuse, and adherence to traditional gender roles. The intersection of IPV with the HIV pandemic further exacerbates the issue. While research specific to Somalia is limited, insights from other African countries suggest the presence of similar drivers of IPV. The findings underscore the importance of using the SDHS 2020 dataset to assess the prevalence and drivers of IPV against women in Somalia, enabling the development of targeted interventions to address this pressing issue.

Methods

Data source

This study was based on secondary data from the household questionnaire of the 2020 Somalia Demographic and Health Survey (SDHS). The SDHS was a national survey conducted from January 2018 to February 2019. The associated data were collected using four types of questionnaires (a maternal mortality questionnaire, a household questionnaire, and two individual questionnaires—an ever-married woman’s questionnaire and a never-married woman’s questionnaire). The collected data were recoded for easier access and analysis [25,26,27,28].

Study design and setting

The study uses data that were extracted from the SDHS 2020 dataset. We recall that the SDHS 2020 was a national survey conducted by Somalia National Bureau of Statistics from January 2018 to February 2019, Somalia.

Somalia is positioned in the Horn of Africa, encompassing an estimated area of 637,657 square kilometers. The country’s topography primarily consists of plateaus, plains, and highlands [27]. Renowned for its extensive coastline, Somalia boasts the longest shoreline in Africa, stretching over 3,333 km along the Gulf of Aden to the north and the Indian Ocean to the east and south. It shares borders with Djibouti in the northwest, Ethiopia in the west, and Kenya in the southwest [26,27,28].

Sample size and sampling technique

The SHDS 2020 used a three-stage stratified cluster sample design in urban, rural, and nomadic strata. The sampling process involved the selection of Primary Sampling Units (PSUs) and Secondary Sampling Units (SSUs) with probability proportional to size, followed by systematic sampling of households. In urban and rural areas, 35 Enumeration Areas (EAs) were independently selected in the first stage, with a total of 1,433 EAs allocated across different regions. Subsequently, 10 EAs were sampled in the second stage, and 30 households were selected from each EA for the survey. This process resulted in a total of 16,360 households from 538 EAs covered in urban, rural, and nomadic areas.

In the nomadic stratum, a two-stage stratified cluster sample design was applied with a probability proportional to size for the selection of PSUs and systematic sampling of households. A sample of 10 EAs was chosen from each nomadic stratum, where a complete listing of households was conducted, and 30 households were selected for the main survey interview. Eligible women aged 12 to 49 and never-married women aged 15 to 49 were interviewed in the selected households, along with the administration of household questionnaires [26,27,28].

Study participants

Of the households selected for individual interviews, 25,625 ever married women were eligible for the IPV Sect. [25]. This resulted in a sample size of all 25,625 interviewed women being used for analysis of prevalence and associated risk factors of the IPV against women after sampling weight was applied.

Measurement and study variables

Outcome variable

The outcome variable was IPV, defined as any act of physical, sexual, or emotional violence perpetrated by an intimate partner. Following the SDHS 2020 data collection instrument, “intimate partner” in this study is operationalized as any current or former spouse or partner. While the World Health Organization (WHO) definition of intimate partner encompasses a broader range of relationships [13], the available SDHS data primarily focused on relationships with current or former husbands/partners [30,31,32]. This operational definition, therefore, reflects the limitations of the available data. IPV was assessed using questions from the SDHS, asking respondents whether they had experienced any of the following acts perpetrated by their current or former husband/partner in the 12 months preceding the survey:

• “Physical violence: pushed you, shake you, or throw something at you; kick you, drag you, or beat you up; try to choke you or burn you on purpose; or threaten or attack you with a knife, gun, or any other weapon.

• Sexual violence: physically force you to have sexual intercourse with him even when you did not want to, physically force you to perform any other sexual acts you did not want to, force you with threats or in any other way to perform sexual acts you did not want to, in the last 12 months preceding the survey, or physically force you to have sexual intercourse.

• Emotional violence: say or do something to humiliate you in front of others, threaten to hurt or harm you or someone close to you, or insult you or make you feel bad about yourself.” [13].

Explanatory variables

Data were collected on a number of individual, family, and community character variables that were expected to be associated with IPV against women. However, based on the literature, independent variables included in the analysis are described in the coming tables [1, 5, 12, 21].

Data analysis

Statistical analyses were performed using Stata 17.0. The analysis involved univariate analysis (frequency and percentage), bivariate analysis (Chi-square test), prevalence rate calculation with 95% confidence interval (CI), and multivariable logistic regression (adjusted odds ratio (AOR) with 95% CI and p-values). Sample weights from SDHS 2020 were applied to ensure representativeness [33, 34].

Results

Descriptive statistics

Table 1 Univariate analysis of numerical variables of IPV in SDHS 2020 data

Table 1 shows that the average household size in Somalia is approximately five, which indicates that there are typically five people living in these women’s homes. The household size does, however, vary somewhat, as shown by the standard deviation of 2.332, with a minimum of zero and a maximum of 9 peoples living with women under the study. Additionally, the findings of this study indicate that, on average, 6.1 children are born to the questioned women in Somalia, with a standard deviation of 2.773. The distribution of births shows that women with larger families as well as those who have never given birth fall within the range of 0 to 16.

For a better understanding of the context of IPV against women in Somalia, the results in Table 2 shed light on the respondents’ demographic and socioeconomic characteristics. Foremost, the age distribution of the respondents shows that the majority of women under study are between the ages of 25 and 39. This age range appears to be particularly crucial in terms of IPV, since it may correspond to a time when women are more prone to violence or more likely to report such instances. In addition, the table shows the regional distribution of the respondents where Sanaag, Togdheer, and Sool, account for about 30% of the population. Bay, Middle Shabelle and Hiraan were the regions with the fewest respondents. Regional distribution is important for policymakers to shape efforts towards diminishing IPV against women in order to direct interventions and support services to individuals in greatest need. In addition, the above table shows the place of residence of respondents, where urban and nomad settings were equal in percentage, at about 36% each, and the rest were rural residents. Also, the table includes details regarding the educational backgrounds of the respondents and their partners. It shows that the majority of women did not attend school, with a percentage of 86.3%, while around 10% have a primary school-level education and barely 0.5% reported having a higher education. On the other hand, 82.43% of respondents reported their partners attended school, while around 13.78% said their partners did not attend school. The wealth quantile classified households into five groups based on their economic standing. Of the respondents, 23.80% and 22.20% belonged to the lowest and second lowest wealth index classes, respectively. 19.8%, 17.95%, and 4.7% of the population were categorized as middle class and fourth class, respectively, and 16.87% as the highest wealth index category. In terms of respondents’ and partners’ employment status, women were disproportionately unemployed, with almost 98.67 of them saying they had not worked in the previous 12 months. In contrast, 53.33% of the study’s female participants said their spouses had a job during the previous 12 months, while 45.95% said the opposite. Finally, the magnitude of domestic violence against women is about 4% in Somalia.

Table 2 Univariate analysis of categorical variables of IPV in SDHS 2020 data

Prevalence of IPV against wowen in Somalia

The study found that the prevalence of IPV against women in Somalia was 4.859% (95%CI: 3.850 − 5.4335) in this particular investigation.

Bivariate analysis of association between IPV and predictors

Table 3 shows the bivariate analysis using Chi-square tests, with a particular focus on the corresponding p-values (p). Significant associations (p < 0.05) were found between IPV and age, region, residence type, education level, household size, partner’s education and work, respondent’s work, and total children ever born.

In terms of age groups, there is a statistically significant association between age and IPV (χ² = 57.1166, df = 6, p < 0.001). The highest rate of IPV is found in the 35–39 age group (5.41%), while the lowest is in the 45–49 age group (2.49%). Examining the region variable, there is a significant association between region and IPV (χ² = 212.4546, df = 15, p < 0.001). The regions with the highest rates of IPV include Hiraan (6.07%), Middle Shabelle (6.02%), and Gedo (7.75%), while Sool (0.75%) has the lowest rate. Regarding the type of residence, there is a significant association between residence and IPV (χ² = 14.5493, df = 2, p = 0.001). The rural population has the highest rate of IPV (4.48%), followed by urban residents (4.41%), while the nomadic population has the lowest rate (3.47%). The highest educational level achieved by respondents also shows a significant association with IPV (χ² = 31.9454, df = 3, p < 0.001). Those with no education have the highest rate of IPV (4.35%), while those with higher education reported no incidents of IPV.

Other variables that show significant associations with IPV include the number of household members (χ² = 27.5678, df = 9, p = 0.001), husband/partner’s education (χ² = 6.7213, df = 2, p = 0.035), husband/partner’s work in the last 12 months (χ² = 26.6903, df = 2, p < 0.001), respondent’s work in the last 12 months (χ² = 4.8717, df = 2, p = 0.027), and total children ever born (χ² = 88.7376, df = 16, p < 0.001).

Table 3 Bivariate analysis of association between IPV and predictors

Multivariable logistic regression

Table 4 displays the results of the multivariable logistic regression analysis, controlling for potential confounders. Significant determinants of IPV included age (45–49 age group compared to 15–19), region (several regions showing higher risk compared to Awdal), type of residence (nomadic compared to rural), mother’s highest educational level (primary and secondary compared to no education), husband/partner’s education (no education compared to yes), husband/partner’s work (no work compared to yes), and respondent’s work (no work compared to yes).

Table 4 Results for the logistic regression analysis to identify the key determinants of the IPV in Somalia

Discussion

This study aimed to determine the prevalence and key drivers of IPV against women in Somalia using the 2020 SDHS data. The findings reveal a prevalence of 4.859% and highlight significant associations between IPV and several socio-demographic factors.

• 1. Age: The bivariate analysis showed the highest IPV rate in the 35–39 age group, a finding seemingly at odds with prior literature often highlighting younger women as more vulnerable [2, 6, 20]. However, the multivariate analysis reveals that the 45–49 age group had a significantly higher risk compared to the 15–19 group (AOR 1.694, p = 0.006). This discrepancy underscores the importance of controlling for confounders and the nuanced relationship between age and IPV risk in the Somali context. Further research is needed to explore this specific age group’s vulnerability. For example, Tiruye et al. [6] found that in Ethiopia, age was a significant predictor, but the specific age group relationship might differ due to variations in cultural norms and societal structures.

• 2. Region and Residence: The study identified significant regional variations in IPV prevalence. Regions like Hiraan, Middle Shabelle, and Gedo displayed higher rates compared to Sool, reflecting the complex interplay of social, economic, and political factors within these regions. This mirrors findings in other Sub-Saharan African countries [6] where geographical location is a strong predictor. The rural population showed higher IPV rates than urban and nomadic populations, consistent with previous studies in developing countries [5, 19] highlighting limited access to resources, reduced mobility, and the influence of traditional gender norms in rural areas.

• 3. Education and Employment: Lower educational attainment, particularly for women, was significantly associated with increased IPV risk. This aligns with existing research emphasizing education’s role in empowering women [5, 6, 25, 26] and enabling them to challenge gender-based violence. Similarly, unemployment among both respondents and their partners increased IPV risk, suggesting the importance of economic empowerment in mitigating violence. Stöckl et al. [3] highlighted the link between economic empowerment and reduced IPV risk in Sub-Saharan Africa, supporting our findings.

The logistic regression analysis confirmed the significance of age and region as determinants of IPV, even after controlling for potential confounding variables. Additionally, variables such as husband/partner’s education and work, respondent’s work, and total children ever born demonstrated significant associations with IPV. These findings underscore the complex interplay of individual, relational, and contextual factors in shaping the risk of IPV.

Therefore, the results of this study align with previous research conducted in Sub-Saharan Africa and other developing countries. Studies in similar contexts have consistently identified age, education, employment, and regional disparities as key determinants of IPV [35]. These shared findings highlight the need for comprehensive, multi-level interventions that address structural factors and promote gender equality, education, and economic empowerment [2, 3, 5, 18, 23].

In conclusion, this study contributes to our understanding of the determinants of IPV in Somalia. The findings emphasize the significance of age, region, education, and employment in shaping the risk of IPV. By addressing these determinants through targeted interventions and policies, stakeholders can work towards preventing and reducing IPV in Somalia and other similar contexts. Future research should continue to investigate the complex dynamics of IPV and explore innovative approaches to promote gender equality and create safe and supportive environments for all individuals.

Strengths and limitations

Strengths

This study is the first to comprehensively investigate IPV determinants using nationally representative data from the SDHS 2020 in Somalia, filling a crucial knowledge gap. The use of multivariable logistic regression controlled for potential confounders, improving the robustness of the findings.

Limitations

The cross-sectional nature of the SDHS data limits causal inferences. Recall bias in self-reported data on IPV is possible. The study did not include other potentially relevant variables such as alcohol consumption or exposure to childhood violence, which are known risk factors in other contexts. Additionally, another limitation of this study is the operational definition of ‘intimate partner,’ which was restricted to current or former husbands/partners due to data limitations. This may underestimate the true prevalence of IPV, as it excludes violence experienced in other intimate relationships.

Recommendations and future work

The results underscore the need for comprehensive, multi-level interventions incorporating education, economic empowerment, and legal reforms. Age-specific programs are needed to address the elevated risk in the 45–49 age group. Regional interventions must consider the unique context and challenges within each area.

Future research should include longitudinal studies to establish causal relationships, qualitative research to understand the lived experiences of survivors, evaluations of existing interventions, multi-sectoral collaborations, and investigations into the impact of IPV on children. The integration of theoretical perspectives (intersectionality and the social ecological model) enhances the understanding of the multifaceted nature of IPV and informs the design of effective interventions.

Theoretical and practical implications

The findings of this study hold important theoretical and practical implications for addressing IPV in Somalia and similar contexts.

Theoretical implications

• 1. Intersectionality of Determinants: By highlighting the interplay of various factors such as age, region, education, and employment in influencing IPV risk, this study contributes to the understanding of the complex and multifaceted nature of IPV. These findings resonate with intersectional feminist theories, emphasizing the need to consider how multiple social identities intersect to shape experiences of violence.

• 2. Social Ecological Model: The results align with the Social Ecological Model, illustrating how individual, relationship, community, and societal factors interact to influence IPV. Understanding these dynamics is crucial for developing comprehensive interventions that target multiple levels of influence to prevent and address IPV effectively.

Practical Implications:

• 1. Tailored Interventions: Policymakers and practitioners can use the identified determinants to tailor interventions that target specific age groups, regions, and educational levels. Implementing age-specific prevention strategies and regionally tailored programs can enhance the effectiveness of interventions aimed at reducing IPV.

• 2. Education and Empowerment: Investing in education, particularly for women, can serve as a protective factor against IPV. Programs that promote gender equality, provide economic opportunities, and challenge traditional gender norms can empower individuals to resist and report instances of violence.

• 3. Regional Considerations: Recognizing the regional disparities in IPV prevalence underscores the need for interventions that account for contextual differences. Strategies should be adapted to address the unique challenges faced by rural populations and specific regions with higher rates of IPV.

• 4. Policy Development: These results can inform the development of evidence-based policies and programs that prioritize the prevention of IPV. Policy initiatives focusing on education, economic empowerment, and support services can contribute to creating safer environments for women and reducing the prevalence of IPV.

Incorporating these theoretical insights and practical implications into policy and program development can significantly impact efforts to combat IPV in Somalia and advance the broader goal of promoting gender equality and preventing violence against women.

The integration of theoretical perspectives and practical considerations is essential for designing effective interventions that address the multifaceted nature of IPV and work towards creating a safer and more equitable society for all individuals.

Conclusion

The results of this study shed light on the key determinants of IPV in Somalia. The analysis revealed that age, region of residence, type of residence, educational level, husband/partner’s education and work, respondent’s work, and total children ever born are significant factors associated with IPV. These results align with previous research conducted in Sub-Saharan Africa and other developing countries, highlighting the importance of addressing socio-demographic factors to effectively combat IPV.

It is evident that IPV is a complex issue influenced by various individual, relational, and contextual factors. The study emphasized the need for tailored interventions that consider the unique characteristics of different age groups, regions, and residence types. Strategies should focus on promoting gender equality, enhancing educational opportunities, improving economic empowerment, and addressing regional disparities in resources and support services.