DEMOGRAPHIC

AND

HEALTH

SURVEYS

DHS WORKING PAPERS

2015 No. 121

Simona J. Simona

Mazuba Muchindu

Harriet Ntalasha

September 2015

This document was produced for review by the United States Agency for 

International Development.

Intimate Partner Violence (IPV) in Zambia: 

Sociodemographic Determinants 

and Association with Use of 

Maternal Health Care 

Intimate Partner Violence (IPV) in Zambia: 

Sociodemographic Determinants and Association 

with Use of Maternal Health Care 

Simona J. Simona1

Mazuba Muchindu1

Harriet Ntalasha1

ICF International 

Rockville, Maryland, USA 

September 2015 

1

Department of Social Development Studies, University of Zambia 

Corresponding author: Simona J. Simona, Department of Social Development Studies, University of 

Zambia; Email: jssimona@yahoo.com; simona.simona@unza.zm 
Acknowledgments 

The authors wish to convey their gratitude to the United States Agency for International Development 

(USAID) for funding the research project through the DHS Fellows Program implemented by ICF 

International. We are grateful to Dr. Wenjuan Wang and Dr. Sarah Staveteig who facilitated the two 

workshops that led to the creation of this paper and who provided technical support throughout the project. 

We want to acknowledge the co-facilitators: Adinan Juma, Henock Yebyo, and Ann Mwangi for their 

tireless effort in guiding this study. We also thank Rebecca Winter, the reviewer of our paper, for providing 

us with constructive comments. Finally, we are indebted to the University of Zambia’s management for 

allowing us to attend the two workshops in Kampala, Uganda, and Livingstone, Zambia. 

Editor: Bryant Robey 

Document Production: Natalie La Roche 

The DHS Working Papers series is a prepublication series of papers reporting on research in progress that 

is based on Demographic and Health Surveys (DHS) data. This research is carried out with support provided 

by the United States Agency for International Development (USAID) through The DHS Program (#AIDOAA-C-13-00095). The views expressed are those of the authors and do not necessarily reflect the views 

of USAID or the United States Government. 

The DHS Program assists countries worldwide in the collection and use of data to monitor and evaluate 

population, health, and nutrition programs. For additional information about the DHS Program, 

contact DHS Program, ICF International, 530 Gaither Road, Suite 500, Rockville, MD 20850, USA. Phone: 

+1 301-407-6500; Fax: +1 301-407-6501; Email: reports@dhsprogram.com; Internet: www. 

dhsprogram.com. 

Recommended citation: 

Simona, Simona J., Mazuba Muchindu, and Harriet Ntalasha. 2015. Intimate Partner Violence (IPV) in 

Zambia: Sociodemographic Determinants and Association with Use of Maternal Health Care. DHS 

Working Papers No. 121. Rockville, Maryland, USA: ICF International. 
iii 

ABSTRACT 

This study used the 2013-2014 Zambia Demographic and Health Survey (ZDHS) dataset 

to examine, on one hand, the sociodemographic characteristics associated with intimate partner 

violence (IPV) and, on the other hand, the relationship between IPV and use of maternal health 

care (place of delivery and ANC visits). The study was based on 6,087 women, age 15-49, who 

were interviewed as part of the domestic violence module of the ZDHS. They reported having 

been in an intimate relationship previously and giving birth in the five years preceding the survey. 

Data were analysed using STATA 13. 

The study found that women’s characteristics, including marital status, household wealth, 

witnessing parental violence, and attitudes justifying wife beating, were significantly associated 

with reporting experience of IPV, after adjusting for educational attainment, occupation, alcohol 

consumption, area of residence, and other socio-economic factors. Partner characteristics 

significantly associated with IPV were alcohol consumption and controlling behaviour. 

IPV is only significantly associated with maternal delivery in a health facility at the 

bivariate level of analysis. It is not significantly associated with use of maternal health care after 

adjusting for area of residence, mother’s age for the most recent birth, birth order, educational 

attainment, and wealth. 

The study indicates that gender inequality and problematic cultural norms that privilege 

men with power over women still exist in Zambia, and thus IPV preventive strategies should 

incorporate a way to adjustsuch cultural norms, not only to increase the use of maternal health 

services but also to enhance the welfare of women. 

Keywords: Zambia, intimate partner violence (IPV), maternal health care, sociodemographic 

characteristics 

1 

1. INTRODUCTION 

Intimate partner violence (IPV), defined as lifetime experience of violence by an intimate 

partner, is a global social and public health problem, perpetrated mostly by men against women 

(Krug et al. 2002; Chiume 2006; and Tuldhar et al. 2013). Globally, the lifetime prevalence of IPV 

among ever-partnered women ranges from 15% to 71%, and studies indicate that nearly one in 

every three women has experienced physical aggression, sexual coercion, or emotional abuse in 

an intimate relationship (Olayanju et al. 2013). According to a World Health Organization (WHO) 

multi-country study on women’s health and domestic violence against women, 6%-49% of women 

age 15-49 reported sexual violence by a partner at some point in life (WHO 2010). In Zambia, 

evidence shows that 43% of women age 15-49 have experienced physical violence and that 37% 

experienced physical violence in the 12 months preceding the 2013-2014 Zambia Demographic 

and Health Survey (ZDHS) (CSO 2014). 

Many studies have examined factors or predictors of intimate partner violence in different 

parts of the world. The documented factors of IPV operate on different levels, ranging from 

individual sociodemographic characteristics to culturally related factors, particularly in the African 

context. Commonly reported sociodemographic factors that are positively associated with IPV 

include the woman’s age (Romans et al. 2007; Olayangu et al. 2013), childhood experience of 

domestic violence (Yount and Carrera 2006), having a low level of education, being unemployed, 

financial dependence on the partner (Dutton 1988; Gartner 1999; Smith 1990), using drugs or 

drinking alcohol (Koenig et al. 2006; Kwagala 2013), and having more surviving children (Hindin 

et al. 2008). 

Lower levels of education and unemployment are both seen as contributing to women’s 

frequent dependence on their husbands and partners, thereby making it difficult for them to leave 

situations of domestic violence. These factors also make women more tolerant of spousal abuse 

(Kalmus 1982), hence putting them in a vicious cycle of violence and abuse. Similarly, women 

with more children have been reported to be more likely to tolerate violence (Young and Carrera 

2006). However, there have been contradictory findings on the association between education and 

IPV. Some studies have found that some women with lower educational status compared with their 

partners are at a higher risk of violence (Garcia-Moreno et al. 2005), but other studies have found 
2 

that women with higher educational status than their partners are at higher risk of violence (Jewkes 

et al. 2002; Taillieu and Brownridge 2010). 

Other factors associated with women’s likelihood of being victims of IPV include marrying 

at a young age, lack of contact with natal kin, witnessing abuse of one’s mother, (Felson et al. 

2000), coming from a poorer household than the partner (Resko 2010), and being more than 10 

years younger than one’s partner (Lawoko et al. 2007) 

Cultural factors associated with IPV include justification that a husband can beat his wife 

for various reasons, including disobedience or refusal of sex (Shezongo-Macmillan 2007), male 

controlling behaviour, and control over family resources and the means of production (Jewkes et 

al. 2002; Taillieu and Brownridge 2010). However, some studies also show that women who have 

control over these resources are not protected from IPV (Vyas and Watts 2009). 

Cultural factors in Africa can be explained by institutionalised gender inequalities that 

privilege men with power over women in decision-making (Ofei-Aboagye 1994; Hinden 2003; 

Suffitz 2010). This cultural inequality relegates women to subordinate positions, thereby 

exacerbating their vulnerability to domestic violence. In Zambia the IPV discourse is not different 

from the general African pattern (OMCT 2002; Dover 2005; Simpson 2005). 

Women’s experience of IPV has been associated with poor sexual and reproductive health 

outcomes, such as sexually transmitted infections (STIs), including HIV (Campbell 2002), 

pregnancy complications and abortion (Emenike et al. 2008), urinary tract infections (Campbell 

2002), and sexual dysfunction (UNICEF 2000). The experience of IPV also has an indirect effect 

on maternal health by making it difficult for women to access a variety of maternal health care 

services (Fischbach and Herbert 1997; WHO 2012; Rahman et al. 2012). 

Women who have ever experienced partner violence are less likely to use maternal health 

services such as antenatal care (ANC) during pregnancy. This finding has been established by a 

number of studies in different parts of the world. In a study exploring the relationship between 

maternal experiences of physical and sexual IPV and the use of reproductive health care services 

in Bangladesh, Rahman et al. (2012) found an association between maternal IPV experiences and 

the low use of ANC. Women who had been sexually abused were significantly less likely to have 

visited a skilled ANC and delivery care provider. The more severe the violence, the more profound 
3 

were the consequences. In Nigeria Ononokpono and Azfredrick (2014) also found significant 

associations between IPV and the use of maternal health care services. They found that women 

who had ever experienced physical or emotional IPV were significantly less likely to use adequate 

ANC and delivery assistance by a skilled health care provider. 

The main argument given to explain the relationship between IPV and maternal health care 

indicators is that violence can affect a woman’s emotional and physical health, and this in turn 

may lead to lack of incentive to pursue appropriate maternal health care (Rahman et al. 2012, in 

Ononokpono and Azfredrick, 2014). This seems to be common in countries with value systems 

that emphasize male dominance and subordination of women. In a study on use of maternal health 

care services in Nicaragua, for example, Lubbock and Stephenson (2008) found that men had the 

authority both in the workplace and in the home to dictate women’s mobility and autonomy in 

accessing maternal health care services. They could deny women permission to seek care if, for 

example, they were examined by a male health practitioner, due to jealousy. Therefore, in many 

instances women would choose not to go for health care, in order to avoid potential violence or 

conflict with their partners. 

Similarly, Amina et al. (2009) have argued that women in abusive relationships are more 

likely to have challenges in negotiating use of male-controlled contraception (e.g., condoms) 

compared with women who are not in such relationships. Such women also might fear using other 

forms of contraception (e.g., hormonal pills) without the knowledge of their partners, as this could 

make them appear to be cheating on the partner and thus result in violence. 

However, other studies on IPV and use of maternal health services have reported 

conflicting results. In a recent study in New Zealand, researchers found increased use of 

contraception among women who had experienced IPV (Amina et al. 2009). Similarly, in Nigeria 

Ononokpono and Azfredrick (2014) found no significant relationship between sexual IPV and use 

of maternal health care services. In Zambia, Stewart et al. (2010) also found that women’s 

experience of physical/sexual violence from partners was not associated with use of antenatal care, 

skilled delivery, and delivery in a facility (Stewart et al. 2010). 

 
4 

Given such conflicting results, there is need for further examination of the relationship 

between IPV and use of maternal health services. Few studies of this subject have been conducted 

in Zambia and other developing countries (Fischbach and Herbet 1997; Jewkes, Levin, and PennKekana 2002; Usdin et al. 2005; Diop-Sidibe, Campbell, and Becker 2006). In addition, the little 

available literature on IPV and maternal health care in Zambia is based on old data. 
5 

2. CONCEPTUAL FRAMEWORK 

There are a number of theoretical models that analyze both the factors associated with IPV 

and its consequences. Those that examine factors related to IPV include biological, psychological, 

cultural, phenomenological, ecological, and gender equality models. The ecological model 

provides a broad picture of factors related to both victims and perpetrators of IPV. This model 

focuses on the social environment and its influence on the possibility of being either a victim or 

perpetrator of intimate partner violence. Such an approach is considered useful when coming up 

with measures to reduce intimate partner violence and to strengthen protective factors and avoid 

the likelihood of becoming a victim and/or perpetrator of IPV (CDC 2004, in WH, 2010).

The ecological model proposes that IPV is a result of factors operating at four levels—

individual, relationship, community, and societal. This study only looks at individual and 

relationship factors. Individual factors include sociodemographic characteristics that may increase 

the likelihood of an individual becoming a victim or perpetrator of violence, while relationship 

factors point to increased risk of violence as a result of relationships with peers, intimate partners, 

and family members, who are a person’s closest social circle and can shape their behavior and 

range of experiences (WHO 2010; WHO 2012). At the individual level, among the factors 

consistently associated with a woman’s increased likelihood of experiencing violence by her 

partner(s) are low level of education, exposure to violence between parents,sexual abuse during 

childhood, acceptance of violence, and exposure to other forms of prior abuse. Also, at the 

individual level some of the most consistent factors associated with a man’s increased likelihood 

of committing violence against his partner(s) are young age, low level of education, witnessing or 

experiencing violence as a child, harmful use of alcohol and drugs, personality disorders, 

acceptance of violence (e.g., feeling it is acceptable for a man to beat his partner), and past history 

of abusing partners (WHO 2012). 

One of the few models on the consequences of IPV is the IPV contextual framework 

proposed by Bell and Naugle in 2008. According to this model, consequences of IPV include 

increasing the partner’s compliant behaviour, thus escaping or avoiding arguments, termination of 

the relationship, and physical injury (Bell and Naugle, 2014). A woman may therefore opt not to 

go for an ANC visit or other maternal care in order to avoid violence from her partner. 

Based on the above formulation, we derived a conceptual framework, shown in Figure 1. 

This model highlights common individual factors and partner/relationship factors that lead to IPV. 

The model then looks at how IPV in turn leads to low use of maternal health services. The 

sociodemographic factors examined in the study are those covered by DHS data. For women, these 
6 

are area of residence, age, marital status, number of living children, education, employment, and 

wealth. For their husbands/partners they are education, alcohol consumption, education difference 

with wife/partner, age difference with wife/partner, and controlling behavior. It is acknowledged 

that while some of these may have a strong relationship, others may not. 

The maternal health care services studied are also those with available DHS data— 

antenatal care and place of delivery. As indicated already, the argument here is that IPV could 

affect a woman’s emotional and physical health and this in turn could lead to lack of incentive to 

pursue appropriate maternal health care (Rahman et al., 2012, in Ononokpono and Azfredrick, 

2014).

Research Questions

This study addresses the following research questions: 

1. What sociodemographic factors are associated with intimate partner violence (IPV) among 

women age 15-49 in Zambia? 

2. Among these women, what is the relationship between IPV and their use of maternal health 

services? 

Figure 1. Conceptual framework for intimate partner violence and use of maternal health care 

services 

Women’s characteristics 

Area of residence 

Age 

Child’s birth order 

Educational attainment 

Marital status 

Wealth 

Occupation 

Wife-beating attitudes 

Witnessing violence

Partner’s characteristics

Educational attainment 

Occupation 

Alcohol consumption 

Controlling behavior

IPV 

Physical or sexual violence

Use of maternal 

health care 

4 or more ANC visits 

Place of delivery
7 

3. DATA AND METHODS 

3.1. Data Source 

Data for this study were derived from the 2013-2014 Zambia Demographic and Health 

Survey (ZDHS). The survey is nationally representative and was organized under the auspices of 

the Central Statistical Office (CSO), Ministry of Health, and ICF International in partnership with 

other governmental and nongovernmental organizations in Zambia. The data collected through the 

survey include background characteristics, marriage and sexual activity, fertility, family planning, 

maternal health, nutrition, HIV/AIDS, and domestic violence. The study made use of the individual 

women’s recode, from the survey module on domestic violence. 

3.2. Sample Size and Sampling Procedure 

The 2013-2014 ZDHS used a two-stage sampling design with a sampling frame from the 

Zambia 2010 Census of Population and Housing (CPH 2010). Because the country has 10 

provinces, 20 strata were created representing urban and rural areas in each province. The survey 

selected 722 standard enumeration areas (SEAs) from the strata in the first-stage of the selection 

process, from which 18,050 households were selected. The total number of women age 15-49 

interviewed was 16,411. 

The domestic violence module was administered to one randomly selected woman in each 

selected household. The total number of women who answered the domestic violence module in 

the ZDHS was 11,778. These women were asked about their experiences of violence. Since our 

focus is on intimate partner violence and maternal health use, we restricted the analysis to evermarried women who had a live birth in the five years preceding the survey. The total number of 

women included in the study is 7,005 (weighted = 6,087). Figure 2 shows our sampling derivation. 

 
8 

Figure 2. Sample derivation 

3.3. Definition of Variables 

3.3.1. Dependent Variables 

There are three dependent variables for this study: intimate partner violence (IPV), place 

of delivery, and number of antenatal care (ANC) visits. IPV is defined as ever experiencing 

physical or sexual violence. Ever experiencing physical violence was determined by the 

respondent answering “yes” to any of a string of questions about whether her spouse ever did the 

following:(1) slapped her; (2) twisted her arm or pulled her hair; (3) pushed, shook, or threw 

something at her; (4) punched her with his fist or something that could hurt her; (5) kicked her, 

dragged her, or beat her up; (6) tried to choke her or burned her on purpose; or (7) threatened her 

All women (n=16, 411) 

Never married (n=583) 

Not given birth in the last 5 years 

(n=7,058) 

Not interviewed for DV (n=1,765) 

Final sample (n=7,005) (weighted=6,087) 
9 

or attacked her with a knife, gun, or any other weapon. Experiencing sexual violence was 

determined by the respondent answering “yes” to any of the two questions that asked whether the 

woman’s spouse had ever forced her to have sexual intercourse or to perform any sexual activity 

without her will. 

Data on place of delivery were collected for all births in the five years preceding the survey, 

but the analysis focused on the care that women received for their most recent birth. It was 

measured by the survey question that asked women where they delivered their more recent birth. 

If a woman answered home or other home, it was recoded as “home,” and all kinds of conventional 

health facilities were recoded as “facility delivery.” 

ANC visits were measured using the question that asked women how many times they 

received antenatal care during the pregnancy for the most recent birth. If they received no ANC 

care or made one to three ANC visits, this was recoded as “0”, and if they made four or more 

antenatal care visits, this was recoded as “1”. 

3.3.2. Independent Variables 

There are three sets of independent variables in this study. The variables were chosen on 

account of their theoretical relevance, dominance in the literature, and presence in the DHS dataset. 

The first set considers IPV as the dependent variable and has sociodemographic characteristics as 

independent variables. The first set includes women’s characteristics (current age, marital status, 

wealth index, educational attainment, employment, area of residence, alcohol consumption, 

experience of violence, and attitudes toward wife beating) and partners’ characteristics 

(educational attainment, alcohol consumption, and occupation). The second set, which considers 

place of delivery as the dependent variable, has IPV and ANC visits as independent variables in 

addition to some sociodemographic characteristics that have been found to be associated with place 

of delivery in the literature. The third set considers receiving ANC (number of visits) as the 

dependent variable, with IPV as the independent variable, while controlling for the effects of the 

sociodemographic characteristics. Table 1 shows how the variables used in the study were defined 

and recoded for the purposes of this analysis. 
10 

Table 1. Operational definition of variables 

Variable Operational definition 

Dependent variables 

IPV 0=no experience of physical or sexual spousal violence, 1=any lifetime 

experience of physical or sexual spousal violence 

ANC 0=0-3 ANC visits, 1=4 and more ANC visits 

Place of delivery 0=home, 1=facility delivery 

Independent variables 

Area of residence 1=urban, 2=rural 

Current age 1=15–24, 2=25–34, 3=35–49 

Age at most recent birth <20, 20-34, 35 or older

Child’s birth order 1, 2, 3, 4 or higher 

Educational attainment 0=none (no education), 1=primary (1-7 years), 2=higher (8+ years) 

Marital status 1=married or in union, 2=widowed, 3=divorced 4=not living together 

Household wealth 1=poorest, 2=poor, 3=middle, 4=rich, 5=richest 

Religion 1=Catholic, 2=Protestant, 3=Muslim/other 

Occupation in the past 12 months 0=not employed, 1=employed for cash, 2=self-employed agriculture 

Alcohol consumption Does respondent drink alcohol: 0=no, 1=yes 

Wife beating justifiable A positive response to any of the following wife-beating justifications: 

goes out without telling him, neglects children, argues with him, refuses 

to have sex with him, burns food (0=no, 1=yes) 

Witnessed parental violence 0=no, 1=yes 

Husband’s educational attainment 0=none (no education), 1=primary (1-7 years), 2=higher (8+ years) 

Husband jealous Whether or not husband is jealous when respondent talks to other men: 

0=no, 1=yes, 2=don’t know 

Husband’s occupation in past 12 months 0=Not employed, 1=employed for cash, 2=self-employed agriculture 

Husband’s alcohol consumption Does partner drink alcohol: 0=no, 1=yes 

3.4. Statistical Analysis 

We used STATA 13 to conduct our analysis. The analysis began with a univariate analysis, 

where descriptive statistics of sociodemographic characteristics of the respondents were obtained. 

Frequency distributions and proportions of each independent variable against the dependent 

variables were determined, followed by ascertaining associations between each independent 

variable against dependent variables, using chi-square. To obtain and ascertain the strength of 

associations, logistic regression models with 95% odds ratio confidence intervals were used. Three 

regression models were run. The first had IPV as the dependent variable and sociodemographic 

and partner characteristics as independent variables. The second model had ANC visits as the 

dependent variable and IPV as the independent variable, along with other women’s characteristics. 

The third model had place of delivery as the dependent variable and IPV as an independent 

variable, while adjusting for the influence of selected socio-demographic variables. 

To address the issue of disproportionate sampling and nonresponse, the domestic violence 

sample weight was applied in the analysis. The svy commands were applied to adjust for the effects 
11 

of a complex sampling design (two-stage sampling design) that was used in the 2013-14 ZDHS. 

Ignoring the sampling design has the effect of underestimating the sampling errors, which 

consequently obscures the decision on whether or not to reject the null hypothesis. The Variance 

inflator factor (VIF) was used to diagnose multicollinearity among the covariates in each model. 

3.5. Ethical Consideration 

Permission to use the 2013-14 dataset was obtained from the DHS Program website with 

the assistance of ICF International. There was no need to obtain any ethical clearance for the 

secondary analysis. All ethical protocols were fulfilled by ICF International and CSO during the 

initial stages of primary data collections (Central Statistical Office, Ministry of Health, and ICF 

International,2013-2014). 

13 

4. RESULTS 

4.1. Background Characteristics of the Participants 

Table 2 reports the background characteristics of the sample population for this study. 

Nearly two-thirds of the women (63%) resided in urban areas and almost half (47%) were age 25-

34. Mother’s age at the most recent birth was mostly 20-34 (69%), and for about one-third of the 

respondents (34%) their most recent birth was their second or third, while for only 14% of 

respondents the most recent birth was their first. 

Most of the women had attained primary education (57%), were married (89%), and were 

Protestants (82%). About two-thirds (65%) were in the lowest three categories of the wealth index, 

while about half (49%) were employed for cash and 42% were not employed. Most of respondent’s 

husbands were employed for cash (75%), and most had attained at least eight years of education 

(52%). 

Table 2. Background characteristics of the participants 

Background characteristics Number of women % 

Woman’s characteristics 

Area of residence 

Urban 2251 37.0 

Rural 3836 63.0 

Current age 

15–24 1677 27.6 

25–34 2879 47.3 

35–49 1531 25.1 

Mother’s age for most recent birth 

<20 807 13.3 

20–34 4180 68.7 

35+ 1100 18.0 

Birth order 

1s 876 14.4 

2 or 3 2088 34.3 

4 or 5 1525 25.1 

6th or more 1598 26.3 

Educational attainment 

No education 662 10.9 

Primary 3450 56.7 

Higher 1975 32.4 

Marital status 

Married 5386 88.5 

Widowed 124 2.0 

Divorced 388 6.4 

Separated 189 3.1 

(Continued...) 
14 

Table 2. − Continued

Background characteristics Number of women % 

Woman’s characteristics 

Household wealth index 

Poorest 1398 23.0 

Poor 1316 21.6 

Middle 1236 20.3 

Rich 1165 19.1 

Richest 972 16.0 

Religion 

Catholic 1012 16.6 

Protestant 4984 81.9 

Muslim/other 91 1.5 

Occupation in the past 12 months 

Not employed 2537 41.7 

Employed for cash 2956 48.6 

Self-employed agriculture 594 9.8 

Alcohol consumption 

No 5524 90.8 

Yes 563 9.2 

Wife beating justifiable 

No 2994 49.2 

Yes 3090 50.8 

Witnessed parental violence 

No 3293 54.1 

Yes 2218 36.4 

Do not know 576 9.5 

Husband’s characteristics

Husband’s educational attainment 

No education 565 9.3 

Primary 2380 39.1 

Higher 3142 51.6 

Husband jealous 

No 2139 35.2 

Yes 3889 63.9 

Don’t know 59 1.0 

Husband’s occupation 

Not employed 428 7.0 

Employed for cash 4556 74.8 

Self-employed agriculture 1103 18.1 

Husband’s alcohol consumption 

No 3318 54.5 

Yes 2769 45.5 

4.2. Prevalence of Intimate Partner Violence among Ever-married Women Who Had a 

Birth in the Five Years Preceding the Survey 

Figure 3 indicates that, among ever-married women with a recent birth, 40% reported ever 

experiencing physical violence by their intimate partners, and 17% reported experiencing sexual 

violence. More than four women in every ten (43%) reported ever experiencing physical or sexual 

violence. 
15 

Figure 3. Prevalence of physical and sexual violence among ever-married women who had a birth 

in the five years preceding the survey 

4.3. Use of Maternal Health Care: Facility Delivery and Four or More ANC Visits 

among Ever-married Women Who Had a Birth in the Five Years Preceding the 

Survey 

Nearly three-quarters (70%) of ever-married women who gave birth in the five years before 

the survey delivered in a health facility, and more than half (55%) made four or more antenatal 

care visits to a health facility. 

Figure 4. Percentage of ever-married women who used maternal health care services in the five 

years preceding the survey 

40.3

17.3

43.2

0

10

20

30

40

50

60

70

80

90

100

Ever experiencing physical

violence

Ever experiencing sexual

violence

Ever experiencing physical or

sexual violence

Percentage

54.6

69.8

0

10

20

30

40

50

60

70

80

90

100

4 or more ANC visits Facility delivery

Percentage
16 

4.4. Intimate Partner Violence and Women’s Sociodemographic Characteristics 

The bivariate analysis revealed a number of significant relationships between women’s 

sociodemographic characteristics and their experience of IPV. Table 3 shows that women’s 

educational attainment, marital status, and occupation in the 12 months preceding the survey were 

strongly associated with experiencing IPV. Levels of IPV were higher among women with less 

than eight years of education, among women who were divorced or separated compared with 

currently married women, and among women who were employed in the last 12 months, whether 

for cash or self-employed, compared with women who were not employed. 

The results also show that women who consumed alcohol, women who responded that wife 

beating is justifiable, and women who had witnessed their mothers being beaten by their fathers 

reported significantly higher levels of ever experiencing IPV. Women whose husbands were selfemployed, consumed alcohol, or were jealous reported higher lifetime experience of IPV. In 

contrast, urban or rural residence, age, wealth index status, and educational attainment were not 

associated with ever experiencing IPV. 

Table 3. Percentage of women who had experience of intimate partner violence by background 

characteristics 

 Intimate partner violence 

 % Number of women 

Woman’s characteristics 

Area of residence 

Urban 42.9 966 

Rural 43.4 1664 

Current age 

15-20 43.0 720 

25–34 44.0 1267 

35–49 42.0 644 

Educational attainment ** 

No education 42.8 283 

Primary 45.2 1560 

Higher 39.9 787 

Marital status *** 

Married 41.9 2256 

Widowed 43.6 47 

Divorced 56.7 220 

Separated 58.2 110 

Wealth 

Poorest 44.5 621 

Poor 42.4 559 

Middle 47.2 583 

Rich 42.3 492 

Richest 38.6 375 

(Continued...)
17 

Table 3. − Continued

 Intimate partner violence 

 % Number of women 

Woman’s characteristics 

Religion 

Catholic 44.2 447 

Protestant 43.2 2152 

Muslim/other 34.3 31 

Occupation the past 12 months *** 

Not employed 38.2 969 

Employed for cash 45.4 1342 

Self-employed agriculture 53.7 319 

Alcohol consumption *** 

No 42.1 2323 

Yes 54.7 308 

Wife beating justifiable *** 

No 35.6 1068 

Yes 50.5 1561 

Witnessed parental violence *** 

No 37.4 1233 

Yes 50.1 1111 

Don’t know 49.7 287 

Husband’s characteristics 

Husband’s educational attainment

No education 42.1 238 

Primary 45.2 1075 

Higher 41.9 1317 

Husband jealous *** 

No 25.8 552 

Yes 52.8 2054 

Don’t know 41.9 24 

Husband’s occupation *** 

Not employed 43.1 184 

Employed for cash 41.4 1887 

Self-employed agriculture 50.7 559 

Husband’s alcohol consumption *** 

No 35.2 1168 

Yes 52.8 1463 

*p<0.05, **p<0.01, ***p<0.001 

4.5. Logistic Regression Analysis of IPV and Sociodemographic Characteristics 

Table 4 presents the results of logistic regression analysis of IPV and sociodemographic 

characteristics. The results show that women who are divorced (p=0.001) or separated (p=0.022) 

have significantly higher odds of reporting ever experiencing IPV compared with married women. 

Lifetime experience of IPV is also significantly associated with household wealth: Women in the 

middle wealth quintile (p=0.006) have higher odds of reporting violence compared with those in 

the poorest quintile. The study shows interesting findings about women’s employment and IPV: 

Women employed for cash (p=0.01) and those who are self-employed in agriculture (p=0.002) 

have significantly higher odds of reporting ever experiencing violence than women who are not 

employed. Also, as expected, women who responded that wife beating is justifiable have higher 
18 

odds of reporting violence compared with those without this attitude, and women who reported 

that they had witnessed marital violence between their parents have higher odds compared with 

women who had not been exposed to parental violence. 

Concerning husband’s characteristics, the findings indicate that jealousy and alcohol 

consumption by the husband are each significantly associated with women’s reporting ever 

experiencing IPV. Women with jealous husbands (p=0.001) and women with partners who 

consume alcohol (p=0.001) have higher odds of reporting ever experiencing IPV. All other 

variables studied were not found to be significantly associated with IPV. 

Table 4. Logistic regression results of IPV on woman’s and husband’s characteristics 

Ever experiencing IPV

Variable Odds ratio 95% CI 

Women’s characteristics 

Area of residence 

Urban 1 

Rural 0.91 (0.74 - 1.12) 

Current age 

15–24 1 

25–34 0.98 (0.84 - 1.15) 

35–49 0.82 (0.66 - 1.03) 

Educational attainment 

No education 1 

Primary 1.03 (0.83 - 1.24) 

Higher 0.80 (0.62 - 1.04) 

Marital status 

Married 1 

Widowed 0.76 (0.47 - 1.21) 

Divorced 1.64 (1.23 - 2.19) ** 

Separated 1.71 (1.08 - 2.72) * 

Wealth 

Poorest 1 

Poor 1.08 (0.91 - 1.28) 

Middle 1.32 (1.09 - 1.62)** 

Rich 1.29 (0.99 - 1.68) 

Richest 1.11 (0.77 - 1.60) 

Religion 

Catholic 1 

Protestant 1.11 (0.94 - 1.31) 

Muslim/other 0.80 (0.42 - 1.52) 

Occupation in the past 12 months 

Not employed 1 

Employed for cash 1.28 (1.11 - 1.47)** 

Self-employed agriculture 1.52 (1.17 - 1.97)** 

Alcohol consumption 

No 1 

Yes 1.21 (0.95 - 1.54)*** 

Wife beating justifiable 

No 1 

Yes 1.44 (1.24 - 1.66)*** 

(Continued...)
19 

Table 4. − Continued

Ever experiencing IPV

Variable Odds ratio 95% CI 

Women’s characteristics 

Witnessed parental violence 

No 1 

Yes 1.55 (1.35 - 1.78)*** 

Don’t know 1.49 (1.17 - 1.91)** 

Husband’s characteristics 

Husband’s educational attainment

No education 

Primary 1.22 (0.98 - 1.53) 

Higher 1.10 (0.87 - 1.39) 

Husband jealous 

No 

Yes 2.69 (2.31 - 3.14)*** 

Don’t know 1.78 (0.71 - 4.47) 

Husband’s occupation 

Not employed 1 

Employed for cash 0.97 (0.73 - 1.28) 

Self-employed agriculture 1.17 (0 .84 - 1.62) 

Husband’s alcohol consumption

No 1 

Yes 1.83 (1.59 - 2.10)*** 

*p<0.05, **p<0.01, ***p<0.001 

4.6. IPV and Use of Maternal Health Care Services 

Figure 5 indicates that there is no relationship between number of ANC visits and reporting 

ever experiencing IPV. However, there is a significant relationship between place of delivery and 

reporting ever experiencing IPV, in that women who report ever experiencing IPV are significantly 

less likely to deliver at a health facility. 
20 

Figure 5. Percentage of women who used maternal health care services by experience of IPV 

4.7. Results of Multiple Logistic Regressions of Use of Maternal Health Care and IPV 

Table 5 presents the logistic regression of IPV and use of maternal health care (place of 

delivery and ANC visits). The first model reports the relationship between IPV and place of 

delivery, while adjusting for area of residence, mother’s age for the most recent birth, birth order, 

educational attainment, wealth, and number of ANC visits. The results show that after adjusting 

for the covariates, the odds of delivering in a health facility for women who reported ever 

experiencing IPV do not significantly differ from those of women who never experienced IPV. 

The same results are observed in the second model, when ANC visits and the same 

covariates are considered. After adjusting for area of residence, mother’s age for the most recent 

birth, birth order, educational attainment, and wealth, the odds of reporting ever experiencing IPV 

are not significantly associated with having four or more ANC visits. 

68

56

71

53

0

10

20

30

40

50

60

70

80

90

100

Facility delivery 4+ANC Visits

IPV

No IPV
21 

Table 5. Multiple logistic regression results of use of maternal health care 

Maternal health care use 

Variable 

Facility delivery 

Odds ratio (95% CI) 

4 or more ANC visits 

Odds ratio (95% CI) 

IPV 

No 1 1 

Yes 0.91(0.79-1.05) 0.93(0.81-1.06) 

Area of residence 

Urban 1 

Rural 0.38(0.29-0.50)*** 1.40(1.14-1.71)** 

Mothers age at birth 

<20 1 

20–34 1.78(1.28-2.47)** 1.17(0.90-1.53) 

35+ 1.71(1.15-2.53)** 1.31(0.94-1.82) 

Birth order 

1st 1 1 

2nd or 3rd 0.48(0.33-0.62)*** 0.83(0.67-1.06) 

4th or 5th 0.42(0.30-0.41)*** 0.91(0.69-1.19) 

6th or more 0.29(0.20-0.41)*** 0.93(0.69-1.26) 

Woman’s educational attainment 

No education 1 

Primary 1.19(0.96-1.49) 1.25(1.03-1.46)* 

Higher 2.05(1.56-2.69)*** 1.26(1.00-1.58)* 

Wealth 

Poorest 1 1 

Poor 1.22(1.03-1.46)* 1.22(1.03-1.46)* 

Middle 1.18(0.96-1.45) 1.30(1.08-1.56)** 

Rich 1.81(1.35-2.42)*** 1.31(1.03-1.66)* 

Richest 3.52(2.01-6.15)*** 2.37(1.73-3.23)*** 

ANC Visits 

0-3 1 

4 or more 1.41(1.22-1.63)*** 

*p<0.05, **p<0.01, ***p<0.001 

23 

5. DISCUSSION AND CONCLUSIONS 

The study sought to establish the relationship between IPV and sociodemographic 

characteristics, on one hand, and how IPV is associated with use of maternal health care, on the 

other hand. The findings show that 43% of women who have ever been in an intimate relationship 

and who had a birth in the five years preceding the survey have ever experienced IPV. The 

prevalence of IPV reported in this study is relatively high and requires concerted efforts from 

stakeholders to address this widespread problem. 

Women’s characteristics that were significantly associated with reporting IPV in the study 

include women’s marital status, household wealth, witnessing parental violence, and attitudes 

justifying wife beating. These findings are in some respects consistent with previous studies, and 

contrasting in others. It is commonplace for previous studies in developing countries to report a 

positive relationship between household wealth and experiencing IPV (Yount and Carrea 2006; 

Luke et al. 2007; Kwagala 2013). In contrast, this study found that women in the middle wealth 

quintile had higher odds of reporting IPV. Similar results are found marginally for Zambia and 

Bolivia, in a multi-country study by Hindin et al. (2008). A backlash hypothesis within the feminist 

discourse may be appropriate for interpreting findings of a relationship between higher levels of 

wealth and increased prevalence of IPV. It asserts that men who direct violence toward empowered 

women may be threatened by the loss of authority, power, and masculinity status due to the social 

mobility of women, and use violence as a means to keep women in “their place” to maintain the 

status quo (Brownmille 1975). 

The findings on attitudes justifying wife beating and having witnessed parental violence 

agree with other studies done in Africa (Antai 2011; Kwagala 2013; Gage and Hutchinson 2006; 

Klomegah 2008; Hindin et al. 2008). The finding that IPV victims often justify wife beating 

reflects both the persistence of cultural norms that privileged men with power hold over women 

(Simpson 2005; Fourie 2004; Dover 2005) and also the lack of progress in the fight against gender 

inequality in the Zambian society. The same explanation suffices for the link between being a 

victim of violence and having witnessed parental violence. Women who grew up witnessing 

violence between their parents may be more likely to accept it as part of everyday life. 
24 

Men’s jealousy and alcohol consumption are common predictors of intimate partner 

violence against women in Africa (Koenig et al. 2003; Kimuna and Djamba 2008). These two 

factors could be constructed as precursors to the enactment of violence against women, which in 

a male-dominated society like Zambia is plausible (OMCT, 2002). However, the causal direction 

between consuming alcohol and perpetrating IPV is confounding. It is not clear whether alcohol 

consumption causes violence against women or the desire to commit physical or sexual violence 

against women causes alcohol consumption. 

Contrary to other studies elsewhere (Antai 2011; Kwagala 2013), our study did not find 

occupation, educational attainment, and area of residence to be significantly associated with IPV 

in the adjusted model. This difference in findings should help to highlight the importance of 

analyzing factors specific to the population under study. 

The second part of our analysis, which examined the relationship between IPV and use of 

maternal health care, shows a significant relationship only between IPV and facility delivery at the 

bivariate level, which shows that women who reported ever experiencing IPV are less likely to 

deliver at a health facility compared with women who reported never experiencing IPV. But after 

adjusting for key sociodemographic factors, such as area of residence, educational attainment, birth 

order, and wealth, the analysis did not find place of delivery or number of ANC visits to be 

significantly associated with IPV. This finding means that the odds of accessing maternal health 

and antenatal care are not significantly different between women who reported ever experiencing 

IPV and those who reported never experiencing it. These findings are consistent with other studies 

done in Zambia (Hindin et al. 2008; Stewart et al. 2010) and in Nepal (Tuladhar et al. 2013). 

It is important to explore the reasons that encourage women to go for antenatal checks and 

subsequently deliver in a health facility, despite experiencing physical or sexual violence. It may 

be that women who experience spousal violence fear the health risks to the unborn baby and thus 

are motivated to ensure its safety by consistently complying with the recommended number of 

ANC visits and by delivering at a health facility. Another reason could be that male partners 

become involved in encouraging their wives to attend ANC and deliver at a health facility 

regardless of their violent behaviour, because of the symbolic meaning that is attached to 

childbearing in most Zambian societies. Some scholars in Zambia, for instance, have intimated 

that sexual prowess and its associated results such as polygamous marriages and childbearing are 
25 

symbols of masculinity (Dover 2005; Simpson 2005). This can act as a motivation for men to be 

helpful during the process of childbirth. 

The availability of health care services, community knowledge, and acceptance of maternal 

health services also influence use of maternal health care services (Lubbock and Stephenson 2008). 

Where maternal health services are easily accessible and women know the importance of accessing 

these services, there is a high likelihood that they will use such services, even when facing IPV 

victimization. This may be true for Zambia because of the strides the country has made in 

providing maternal health services in the last 5-10 years. The 2013-14 ZDHS reported that 96% 

of mothers received ANC from a skilled provider (a doctor, clinical officer, nurse, or midwife) for 

their most recent birth in the five years preceding the survey, and 68% of births took place in a 

health facility. 

This study has strengths and limitations. Firstly, it is probable that sensitive topics such as 

physical and sexual violence always suffer from underreporting due to many cultural and other 

underlying factors. Thus it is likely that it underestimates prevalence of IPV among the selected 

sample population. The second limitation is that the cross-sectional nature of the study design used 

in the DHS limits determination of causality between the variables. Also, the definition of ever 

experiencing physical or sexual violence used in this study may not reflect the current situation, 

and cannot help in deciphering whether the violence was in fact committed by the woman’s current 

partner. These limitations notwithstanding, using DHS data has important strengths. The survey 

uses probability sampling procedure to select participants from the entire country, which validates 

generalization of the findings to the whole population, and its standard form allows for 

comparability within and between countries and between repeat surveys. Data are collected 

through a carefully designed questionnaire by highly experienced interview teams with extensive 

training and supervision. 

All in all, the current study found that in Zambia the sociodemographic characteristics of 

women that are associated with experience of IPV include marital status, household wealth, 

occupational status, witnessing parental violence, and attitudes justifying wife beating. Partner 

characteristics include alcohol consumption and jealousy. The study also discovered that IPV is 

not strongly associated with use of maternal health care except at a bivariate level, where place of 

delivery is associated with IPV. These findings underscore the importance of addressing issues of 
26 

gender equality and problematic cultural norms embedded in our society that make women 

vulnerable to IPV. Although the relationship between IPV and use of maternal health care was not 

found to be statistically significant, its direction gives important insight that calls for the need to 

continue with programs aimed at increasing access to and knowledge about maternal health care 

services. 

 

 
27 

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