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Patterns and Determinants of Physical Violence
Against Women in Malawi
Thokozani Mzumara
Mzimba North District Hospital https://orcid.org/0000-0002-0011-269X
Philip Maunda
Mzimba North District Hospital
Mary Mbotwa
Mzimba North District Hospital
Cecilia Nambala
Mzimba North District Hospital
Byenala Kaonga
Clinical research education and management services, Lilongwe, Malawi
Adriano Focus Lubanga
Kamuzu Central Hospital
Akim Nelson Bwanali
Clinical research education and management services, Lilongwe, Malawi
George N. C. Munthali
Yangtze school of management and economics
Lazarus Obed Livingstone Banda
Nalikule college of education
Mary Kumwanje Sibande
University of Livingstonia
Research Article
Keywords: Violence, Trauma, Injury, physical Physical Attack, Women Empowerment, Malawi
Posted Date: November 28th, 2024
DOI: https://doi.org/10.21203/rs.3.rs-5527694/v1
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
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Additional Declarations: The authors declare no competing interests.
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Abstract
Background
Physical assault remains a major contributing factor to the burden of trauma globally. The burden is
mainly shouldered by countries in the lower and middle-income economies compared to high-income
countries.
Aim
The study aimed to ascertain the pattern of physical attack (PA) and its associated factors among
Malawian women.
Method
The study employed secondary data from a multiple indicator cluster survey conducted by UNICEF and
the National Statistical Oce, Malawi, which is publicly available. The data was analyzed using SPSS
version 27, and R version 4.3.3 was used to create graphs and tables. The Chi-square test was used in
bivariate analysis, and the independent t-test was used to assess mean differences between variables.
The binary logistic regression analysis was conducted to determine the effect of independent variables
on the likelihood of the dependent variable. A p-value p < 0.05 was considered statistically signicant.
Results
The study found that about 4.5% of women in Malawi have been physically attacked. According to
bivariate analysis, PA was associated with marital status (p < 0.001), region (p < 0.001), school
attendance (p = 0.002), use of contraceptives (p = 0.021), and use of the internet (p < 0.001). The logistic
regression model was statistically signicantχ2(8) = 393.272.402, p < .0001. The model explained 5%
(Nagelkerke R2) of the variance in physical attack. The model correctly identies 95.5% of the cases.
Used internet (p = 0.02), region (p < 0.001), ever-drunk alcohol (p < 0.001), marital status (p = 0.007), and
functional diculties (p < 0.001) were signicant predictors of physical attack in the model
Conclusion
The physical attack has a widespread disparity inuenced by marital status and the ever-drunk alcohol
region, highlighting geographical, cultural, and socioeconomic differences and calling for a multisectoral
approach to curb violence against women of reproductive age in Malawi.
INTRODUCTION
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The WHO estimates that about 35% of women worldwide have experienced some form of violence in
their lifetime (Chikhungu et al., 2021). Furthermore, the United Nations estimates that 20–50% of women
have been physically attacked (Dovonou et al., 2024). Globally, physical violence against women is a
serious human rights issue and affects many societies (Tesfaye et al., 2024). The proportion of females
experiencing physical violence varies based on geographical variations (Tetikcok et al., 2016).
Sustainable Development Goal Number 5 emphasizes empowering women and girls, including
eliminating violence in public and private spheres (Chikhungu et al., 2021). Besides empowerment, other
efforts to curb violence among women (VAW) include advocacy and home visitation, which have proven
to reduce violence; however, VAW remains a challenge in many parts of the world (Garcia-Moreno et al.,
2015). VAW is an unprecedented act that remains the most underrecognized human rights violation
(Albofotouh and Almuneef, 2020).
Over one-third of women globally are impacted by violence against them, affecting their physical, sexual,
emotional, and social welfare (Chernet & Cherie, 2020). A recent study conducted in Malawi using a
hospital-based registry found that men were the most affected by interpersonal violence; however,
domestic violence among women could be higher because most cases were self-reported and many are
reluctant to admit the cause of violence (Maine et al., 2018).
Violence against females has a signicant negative impact on their families, communities, and general
well-being. Its direct and indirect consequences greatly strain households and economies (Ellsberg et al.,
2015). At the individual level, violence against women may lead to medical costs to treat injuries, mental
health costs, and legal costs for those who seek additional services and protection (Vyas et al., 2023).
Furthermore, injuries are the leading cause of death and disability-adjusted life years, with an estimated
400million deaths and 211,000 years lost annually (Maine et al., 2018). Interpersonal violence (IPV)
accounts for about 8% of the trauma burden. Originally, IPV could be grouped into family or intimate
violence and community violence. Accordingly, IPV is dened as the use of physical power that can
result in injury, harm, death, psychological trauma, or deprivation. In particular, physical violence is
dened by the United Nations as an act attempting to cause or result in pain or physical injury. It includes
beating, biting, burning, kicking, punching, and use of weapons, or tearing out hair. Again, the use of
physical force against another person via pushing, biting, pinching, kicking, slapping, stabbing, shooting,
and/or beating is referred to as physical violence (Albofotouh and Almuneef, 2020). Additionally, any act
that uses physical force or any other kind of weapon to cause harm that is not unintentional and has the
potential to cause either internal or external injury, or possibly both, is considered physical violence
(Donovou et al., 2024). Moreover, violence is dened by the World Health Organization (WHO) as any real
or threatened use of physical force by one person against another, a group, or a community that causes
death, psychological harm, deprivation, or stunted development (Tetikcok et al., 2016).
According to feminist theory, violence among women originates from traditional social structures and is
a reection of unbalanced social relationships in society (Chikhungu et al., 2021). Gender-based violence
(GBV) is a major public health concern, and though GBV applies to both males and females, females are
mostly victimized (Dovonou et al., 2024). GBV may be nancial, emotional, psychological, physical, or
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sexual (Donovan et al., 2024). The consequences of GBV are multiple and include murder, suicide, HIV
infection, alcohol, drug dependency, unwanted pregnancies, unwanted abortion, anxiety, fear, self-hatred,
and self-denial (Donovou et al., 2024). These negative outcomes may also lead to the inability to be a
good partner and parent after childbirth (Dhar et al., 2018). Violence affects women's health, happiness,
and social mobility signicantly; thus, scholars, decision-makers, and practitioners must move quickly to
address this issue. Effective intervention techniques and the advancement of gender equality in Africa
depend on an understanding of the frequency and causes of physical violence against women (Tesfaye
et al., 2024).
Nevertheless, previous studies elsewhere have reported an increase in the prevalence of violence
against women, especially in low and middle-income countries, owing to the socioeconomic landscape
(Sen et al., 2017). Domestic violence remains a critical issue in Malawi and Sub-Saharan Africa, with 42%
of Malawian women and up to 44% regionally experiencing intimate partner violence (Chikhungu et al.,
2019; Ssentongo et al., 2020). The situation is also linked to demographic factors featured in every
country. For instance, in Zambia and Mozambique, non-poor women face higher violence rates. At the
same time, in Zimbabwe and Kenya, it’s more prevalent among poor women, highlighting the diverse
socio-economic dynamics across countries (Bamiwuye & Odimegwu, 2014). Factors contributing to high
IPV rates include excessive alcohol use, socio-economic disparities, lifestyle behaviors, and cultural
norms such as polygamy, which correlate with increased violence (Chikhungu et al., 2019; Alkhatib et al.,
2021). Banda et al. (2024a) report similar violence among and by homeless street dwellers.
Recommended strategies include reducing alcohol misuse, empowering women through education and
workforce participation, and challenging harmful social norms that justify abuse. This multi-faceted
approach, involving prudent policy enforcement and community education (Banda et al., 2024b; 2024c),
is vital to curb IPV in Malawi and Sub-Saharan Africa more broadly (Ssentongo et al., 2020; Bamiwuye &
Odimegwu, 2014; Tsawe & Mhele, 2022). Despite the extant vast scholarship on physical violence, to the
best of our knowledge, there is a dearth of literature on the magnitude and features of physical violence
experienced by women of reproductive age in Malawi. Hence, this study aims to ascertain the pattern of
physical attack and its associated factors among Malawian women. The ndings of the study can help
inform further research on the risk factors of domestic violence in general. This would, in turn, inform
policies on the protection of women and girls against acts of violence and promote well-being and
productivity.
METHODOLOGY
Study design
The analysis relied on data from the Malawi Multiple Indicator Cluster Survey (MICS) 2019–2020, a
nationally representative household survey available at https://mics.unicef.org/surveys. MICS is a
nationally representative household survey that offers current data on HIV, maternal health, childbearing,
sexual behavior, child health indicators, fertility, sanitation, and hygiene. MICS is carried out every four to
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ve years by the Ministry of Health and Malawi's National Statistics Oce (NSO), with technical
assistance from UNICEF. The MICS's methodology and sampling approach have been thoroughly
explained elsewhere (NSO, 2021). We used a subset of data that contains data on women (aged 15–49
years) (UNICEF, 2019). The survey sought to assess women's and children's well-being in rural and urban
locations across Malawi's 28 districts. It also reported progress towards the Sustainable Development
Goals and Malawi's Growth and Development Strategy. The National Statistical Oce conducted the
survey funded by UNICEF and other international development organizations (Mandiwa Namondwe,
2024).
Independent variable
The independent variables included the age of the woman in years, her use of contraceptives (1 = Yes/ 2
= No), her use of the internet (1 = Yes/ 2 = No), her marital status (1 = currently married/2 = formely
married/3 = never married), her functional diculties, the region (1 = North/2 = Central/3 = South),
whether she has ever attended school (1 = Yes/ 2 = No), whether she has ever drank alcohol (1 = Yes/ 2 =
No), and whether she has ever smoked cigarettes (1 = Yes/2 = No) and the area (rural/urban).
Outcome variable
The study's main outcome variable was a physical attack, coded as yes = 1 or no = 2, don't know = 8, and
no response = 9. To achieve the study's objective, those who experienced an attack were coded as 1;
otherwise, they were coded as 2, indicating no physical attack.
Data management
All missing variables were replaced with the mode and the median. Furthermore, we recorded all
responses coded as 9 = did not say to 2 = no, and we recorded don't know = 8 to no = 2.
Data analysis
The data was entered into SPSS version 27. It utilized descriptive statistics such as mean and standard
deviation, percentages, and frequencies. To illustrate the data graphically, we employed graphs and
tables created using R version 4.3.3 programming software. For inferential statistics, we employed the
chi-square test and independent t-test as part of the bivariate analysis. Logistic regression techniques
were used where only variables signicant on the bivariate analysis were entered into the logistic
regression model to understand the effect of the independent variables on the likelihood of the
dependent variable. The value of p < 0.05 was considered statistically signicant.
Ethics
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The study did not require ethical approval due to the nature of the study design since we use publicly
available, identied data. The original study was ethically approved, and they obtained informed consent
from study participants. Approved. However, data management in this study followed standard practices
stipulated in the Helsinki Code.
RESULTS
Characteristics of study variables
The study retrieved data from 25626 women. The age range was 15 to 49 years. The mean age was
28.17 (SD = 9.377), and the median was 27. About 15584 (60.8%) were married or in a union, while 6075
(23.7%) were single. About 1163 (4.5%) of the participants had functional diculties. The majority of
participants were from the southern region, 11641 (45.4%) and the least number of participants were
from the north, 5619 (21.9%)
The majority of participants ever attending school was 23625 (92.2%) (Table1)
Out of 23625 who ever attended school, the majority, 16745 (70.9%), went as far as primary education,
with only 505 (2.1%) going to higher education institutions (Table2).
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Table 1
Demographic Characteristics of Participants
Characteristics Frequency (n = 25626) Percentage (%)
Attended School
Yes 23625 92.2
No 2001 7.8
Region
North 5619 21.9
Central 8366 45.4
South 11641 45.4
Marital/Union Status
Currently married/in union 15584 60.8
Formerly married/in union 3967 15.5
Never married/in a union 6075 23.7
Internet Usage
Yes 1586 6.2
No 24040 93.8
Area of Residence
Urban 4231 16.5
Rural 21395 83.5
Cigarette Smoking
Yes 224 0.9
No 25402 99.1
Ever Drunk Alcohol
Yes 1720 6.7
No 23906 93.3
Health Insurance
Yes 145 0.6
No 25481 99.4
Physically Attacked
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Characteristics Frequency (n = 25626) Percentage (%)
Yes 1144 45.0
No
Has Functional Diculties
Yes
No
24482
1163
24463
95.5
4.5
95.5
Table 2
The highest level of school attained by women in the study
Highest Level of School Attended Frequency (n = 25626) Percentage (%)
ECE 13 0.1
Primary 16745 70.9
Lower Secondary 3061 13.0
Upper Secondary 3245 13.7
Higher 505 2.1
Vocational Training 56 0.2
Prevalence and features of physical attack
The proportion of women physically attacked
About 1144 (4.5%) of Malawian women have been physically attacked. Out of these women attacked,
777 (67.9%) of attacks happened within the last 12 months. The majority of women, 794 (69.4%), were
offended by one person who committed the offence. Out of 1144 women who were attacked, 262
(22.9%) of women were attacked by a person or persons who had a weapon.
Factors Associated with Physical Attack
According to the results of a bivariate analysis, married women (596 (52.1%) were more likely than single
women (272 (23.3%) to experience physical attacks. A statistically signicant difference was observed
(p < 0.001). Furthermore, the northern region 483 (42.2%) had a higher rate of physical attacks among
women than the southern region 333 (29.1%), and the difference was statistically signicant (p < 0.001).
Comparing people with physical attacks to those without, 1045 (91.3%) had no functional handicap while
only 99 (8.7%) had a handicap (p < 0.001). In terms of school attendance, 62 (5.4%) of those who never
went to school and the majority of those who were physically attacked had attended before 1082
(94.6%) (p = 0.002) ( See Table3). According to the independent t-test, the mean age of women who
were physically attacked was 28.13 (SD = 9.407), which was the same as those who were not attacked,
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28.18 (SD = 9.375), and there was no statistically signicant difference (p = 0.441). Based on the area of
residence, the study found that there was no signicant association between rural and urban residents
(p = 0.140). The majority of people who were physically attacked had used contraceptives before, and the
association is statistically signicant (p = 0.021). In addition, the majority of women who were physically
attacked: 1043 (91.2%) have never used the internet compared to 101 (8.8%) who have used the internet
(p < 0.001). The majority of women who were physically attacked had no health insurance, 1141 (99.7%),
compared to 3 (0.3%) who were covered by health insurance, but it was not statistically signicant (p =
0.161). Ever-drunk alcohol was statistically signicant (p < 0.001), whereas cigarette smoking and PA
were (p = 0.001).
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Table 3
Associated Factors with Physical Attack among Study Participants
Factors Physical Attack P-Value
Yes (n, %) No (n, %)
Attended School
Yes 1082 (94.6%) 22543
(92.1%)
p = 0.002*
No 62 (5.4% 1939
(7.9%)
Region
North 483 (42.2%) 5136
(21.0%)
p < 0.001*
Central 328 (28.7%) 8038
(32.8%)
South 333 (29.1%) 11308
(46.2%)
Marital/Union Status
Currently married/in
union
1596 (52.1%) 14988
(61.2%)
p < 0.001*
Formerly married/in
union
276 (24.1%) 3691
(15.1%)
Never married/in a union 272 (23.8%) 5803
(23.7%)
Disability
Has functional
diculty
99 (8.7%) 1064
(4.3%)
p < 0.001*
Has no functional diculty 1045 (91.3%) 23418
(95.7%)
Health Insurance
n = Sample size; % = Percentage, *P-value signicant at 0.05.
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Factors Physical Attack P-Value
Yes (n, %) No (n, %)
Yes 3 (0.3%) 142 (0.6%) p = 0.161
No 1141 (99.7%) 24340 (99.4%)
Internet Usage
Yes 101 (8.8%) 1485 (6.1%) p < 0.001*
No 1043 (91.2%) 22997 (93.9%)
Contraceptive Usage
Yes 620 (54.2%) 14113 (57.6%) p = 0.021*
No 524 (45.8%) 10369 (42.4%)
Area of Residence
Urban 207 (18.1%) 4024 (16.4%) p = 0.140
Rural 937 (81.9%) 20458 (83.6)
Cigarette Smoking
Yes 20
(1.7%)
204
(0.8%)
p < 0.001*
No 1124
(98.3%)
24278
(99.2%)
Ever Drunk Alcohol
Yes 176
(15.4%)
1544
(6.3%)
p < 0.001*
No 968
(84.6%)
22938
(93.7%)
n = Sample size; % = Percentage, *P-value signicant at 0.05.
Predictors of physical attack
Binary logistic regression was run to ascertain the effects of the use of contraceptives, use of the
internet, marital status, functional diculties, region, and ever-attended school on the likelihood of
physical attack among women. The logistic regression model was statistically signicantχ2(8) =
393.272.402, p < .0001. The model explained 5% (Nagelkerke R2) of the variance in physical attack. The
model correctly identies 95.5% of the cases. Used internet (p = 0.02), region (p < 0.001), ever-drunk
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alcohol (p < 0.001), marital status (p = 0.007), and functional diculties (p < 0.001) were signicant
predictors of physical attack in the model. Females who were formerly married were 0.5 times more
likely to experience physical attacks compared to those who were never married. Those who ever drunk
alcohol were 2.2 times more likely to get physically attacked compared to those who had never drunk
alcohol.
Table 4
Predictors of Physical Attack among Study Participants
Predictors of Physical Attack AOR (95% CI) P-Values
Used Internet 0.773 (0.623–0.960) p = 0.020*
Ever Attended School 0.798 (0.611–1.042) p = 0.098
Region
North 0.321 (0.278–0.372) p < 0.001*
Central 0.732 (0.626–0.856) p < 0.001*
Cigarette Smoking 0.794 (0.487–1.295) p = 0.356
Ever Drunk Alcohol 2.295 (1.921–2. 743) p < 0.001*
Marital/Union Status
Currently married/in union 1.110 (0.936–1.317) p = 0.228
Formerly married/in union 0.590 (0.491–0.709) p < 0.001*
Has Functional Diculties (18–49 years) 0.590 (0.419–0.652) p < 0.001*
Used contraceptive 1.041 (0.907–1.195) p = 0.568
AOR: Adjusted Odds Ratios, CI: Condence Intervals, *P-value signicant at 0.05.
DISCUSSION
The prevalence of physical attacks in this study was lower than that of violence in higher-income
countries (Sardinha et al., 2022). Furthermore, it was lower than the ndings of a study conducted in
Ethiopia, which found a prevalence of 24%. In addition, the prevalence of PA in this study is lower than
what was reported in a multinational study, which showed that about half of women had experienced
physical violence in their lifetime (Garcia-Moreno et al., 2005). The results of our study are surprising
considering that in the majority of low-income countries, women are less empowered, unlike in high-
income countries where women's empowerment soars higher (Albofotouh and Almuneef, 2020).
Empowerment could most likely lead to economic and social dependence and a resulting reduced risk of
physical violence. Nevertheless, the lower rate of PA in our study could be attributed to women's
reluctance to declare violence since the victims are always blamed for their misfortune (Giammarioli et
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al., 2023). In addition, the ndings of this study could be attributed to a lack of knowledge about what
constitutes physical violence (reference). Furthermore, according to research, violence against women
remains underreported due to impunity, stigma, shame, and silence (Sapkota et al., 2024). The ndings
of the study highlight the great need for necessary gender-based physical violence awareness
campaigns in Malawi to empower women to understand their rights and how to report incidents if they
occur.
In the current review, it was found that marriage status was associated with physical attacks, similar to a
previous study conducted in Malawi and Uganda (Tesfaye et al., 2024). The ndings of this paper may
suggest that the majority of PA among women could be gender-based violence perpetrated by intimate
partners. According to research, women are at greater risk of violence at home than in the streets,
highlighting the magnitude of intimate partner violence (Chernet & Cherie, 2020). Of the many forms of
violence against women, the majority are perpetrated by intimate partners (Vyas et al., 2023). Although
the study did not assess the proportion of intimate partner violence, the majority of the violence endured
by women was perpetrated by one person, suggesting high rates of intimate partner violence (IPV)
among Malawian women. Therefore, future studies should conduct a thorough investigation of IPV and
associated factors to elucidate this phenomenon further.
The current study found that physical attack is highest in the northern region of Malawi, similar to a
study by Feseha et al. (2012). The high prevalence of PA in the Northern region could be attributed to the
predominant existence of polygamous family structures in the region coupled with a patrilineal system
(Chikhungu, 2021). According to research, there are marked differences in the prevalence of PA in
different geographical regions that could be driven by variations in cultural traditions among study
populations (Do et al., 2013). The study did not address the association between the number of wives by
husband and PA, but studies have shown that women in polygamous families are mostly victimized
(Abolfotouh and Almuneef, 2020). Hence, the study suggests that the majority of PA cases emanate
from cultural practices and emphasizes the need to question unacceptable cultural behaviors to curb
gender-based violence.
Surprisingly, this paper found that there is a strong association between attending school and
experiencing physical violence. Other studies have reported that physical violence among women is
associated with lower levels of education (Bones, 2016; Kreager et al., 2013; Sanz-barbero et al., 2019).
The ndings of our study can be attributed to a large number of participants who had primary school
education compared to those who reached higher levels of education. The ndings of this study highlight
the need to incorporate women's empowerment in the primary education curriculum to raise awareness
and prevent gender-based violence. Studies have shown that signicant correlations are found between
a decreased probability of violence and more women's empowerment on an individual basis (Ma et al.,
2023).
Alcohol consumption has been reported in numerous studies as a cause of gender-based violence
worldwide, including physical violence (McKinney et al., 2009), as it reduces cognitive function and self-
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control, making individuals less capable of resolving conicts nonviolently (Bernardin, 2014). However, in
our study, a signicantly higher proportion of women who experienced physical attacks had never
consumed alcohol, with this difference being highly signicant (p < 0.001), suggesting that factors other
than alcohol consumption may play a more prominent role in violence against women in this context
In this study, there was no association between age and physical violence, dissimilar to other studies; for
instance, a study conducted in Morocco found that violence was more common among younger women
compared to older women (Boughima et al., 2018). We attribute the ndings of this study to the narrow
age range used since this study only focused on women of reproductive age. Accordingly, age could be
interplayed with other factors, such as economic status, social support, economic dependence, and
functional dependency (Sanz Barbero et al., 2019).
The study found no signicant association between PA and area of residence. This is in disagreement
with a study conducted in Turkey (Sen and Bolsoy, 2017), which found that some people who lived in
shatter settlements suffered more violence than others. The ndings of our study can be attributed to
growing shatter populations in urban communities, which are generally characterized by informal
employment and may face peculiar challenges similar to the rural setting.
In this study, the majority of people who were physically attacked had used contraceptives before, and
the association is statistically signicant (p = 0.021). In contrast, a study conducted in India to assess
the relationship between physical violence and the use of contraceptives found that women who were
physically abused were less likely to use contraceptives (Stephenson et al., 2013). The differences could
be due to cultural traditions in the two settings as well as health policies in the two countries. The
ndings of our study could be due to the integrated health service delivery of family planning with other
services.
In addition, this study found that not using the internet was associated with facing physical attacks
among women compared to those who have used the internet, similar to a recent study by Sakpokta et
al. (2024). The ndings of our study are unexpected since there is a clear link between cyberbullying and
physical violence (Backe et al., 2018). The ndings of our study can be explained by the ability of the
internet to provide information that may lead to women's empowerment. The study highlights the need to
leverage the digital solutions and interventions provided by the internet mainly as a source of
information to raise awareness and increase the adoption of contraceptive methods.
The majority of women who were physically attacked had no health insurance, 1141 (99.7%), compared
to 3 (0.3%) who were covered by health insurance, but it was not statistically signicant (p = 0.161).
Nevertheless, a recent study hypothesized that expanding family health insurance was linked to the
prevention of violence (Letourneau et al., 2022). This study's results could be explained by the low
proportion of women who are covered by insurance in our study. In Malawi, the coverage of women with
health insurance is poor (Chauluka et al., 2022). Ideally, health insurance coverage could help increase
women's access to health services and other support services where they can learn about physical
violence and reduce the prevalence of attacks.
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Limitations
The study has limitations. First, the study could not make comparisons based on gender as it only
focused on women. Secondly, the subjective nature of the study is prone to recall bias, especially
considering the sensitivity of the issues in the setting leading to the underreported occurrence of
physical violence. Thirdly, the study did not assess other forms of violence, such as sexual and
psychological violence, as it was beyond the scope of the study. The study does not indicate access to
care services such as police, health, and other victim support systems. The study did not categorize the
type of injuries sustained and also the time of injury, including husbands' characteristics such as age,
alcohol or tobacco use, and history of childhood abuse.
Conclusion
In conclusion, the study found that physical violence among Malawian women of reproductive age is
lower than elsewhere. Our study also found that physical violence is signicantly higher among
Malawian women from the northern region and those who have attended school. These ndings
highlight the need for increased advocacy for women’s rights and sexual autonomy, especially in
northern Malawi. Women across the country are encouraged to join social groups that promote
education and empowerment, helping them recognize and report any form of abuse.
Future Study Areas
Further research on the prevalence, patterns, and causes of intimate partner violence (IPV) against
Malawian women is crucial, as IPV remains a serious public health issue affecting women, families, and
societies globally. In addition, further studies can look at the negative impacts of physical violence,
including other forms of violence such as emotional, psychological, and economic violence, on well-
being and livelihood.
References
1. Abolfotouh MA, Almuneef M (2020) Prevalence, pattern and factors of intimate partner violence
against Saudi women. J Public Health 42(3):e206–e214. https://doi.org/10.1093/pubmed/fdz092
2. Alkhatib A, Ibingira C, Mujuni B, Amanya G, Nnyanzi LA (2021) Preventing multimorbidity with
lifestyle interventions in Sub-Saharan Africa: A new challenge for public health in low and middle-
income countries. Int J Environ Res Public Health 18(23):12449.
https://doi.org/10.3390/ijerph182312449
3. Backe EL, Lilleston P, McCleary-Sills J (2018) Networked individuals, gendered violence: A literature
review of cyberviolence. Violence Gend 5(3):135–146
4. Bamiwuye SO, Odimegwu C (2014) Spousal violence in sub-Saharan Africa: Does household poverty-
wealth matter? Reproductive Health 11(1). https://doi.org/10.1186/1742-4755-11-45
Page 17/21
5. Banda LOL, Banda CV, Banda JT, Hlaing TT, Mwaene E (2024) Assessing farmers’ knowledge of
environmental policy along the Ayeyarwady River: Strides towards the Indian Ocean marine life
safety. Heliyon 10(16). https://doi.org/10.1016/j.heliyon.2024.e35503
. Banda LOL, Banda CV, Banda JT, Mwaene E, Munthali GNC, Hlaing TT, Chiwosi B (2024) Unraveling
agricultural water pollution despite an ecological policy in the Ayeyarwady Basin. BMC Public Health
24(1). https://doi.org/10.1186/s12889-024-19084-7
7. Banda LOL, Banda JT, Banda CV, Mwaene E, Msiska CH (2024) Unraveling substance abuse among
Malawian street children: A qualitative exploration. PLoS ONE 19(5):e0304353.
https://doi.org/10.1371/journal.pone.0304353
. Bazargan-Hejazi S, Medeiros S, Mohammadi R, Lin J, Dalal K (2013) Patterns of intimate partner
violence: A study of female victims in Malawi. J Injury Violence Res 5(1):38–50.
https://doi.org/10.5249/jivr.v5i1.139
9. Bernardin F, Bosser M, A., Paille F (2014) Cognitive Impairments in Alcohol -Dependent Subjects.
Front Psychiatry 5(78). http://doi.org/10.3389/fpsyt.2014.00078
10. Bernardin F, Bosser M, A., Paille F (2014) Cognitive impairments in alcohol-dependent subjects.
Front Psychiatry 5:78. https://doi.org/10.3389/fpsyt.2014.00078
11. Bones S (2016) Education and Income Imbalances Among Married Couples in Malawi as Predictors
for Likelihood of Physical and Emotional Intimate Partner Violence. Violence Vict 31(1):51–70.
10.1891/0886–6708.VV-D-14-00016
12. Bones S (2016) Education and income imbalances among married couples in Malawi as predictors
for likelihood of physical and emotional intimate partner violence. Violence Vict 31(1):51–70.
https://doi.org/10.1891/0886-6708.VV-D-14-00016
13. Boughima F, Razine R, Benyaich H, Mrabet M (2018) The prole of women victims of domestic
violence in Morocco. La Revue de Médecine Légale 9(3):96–102.
https://doi.org/10.1016/j.medleg.2018.05.002
14. Boughima F, Razine R, Benyaich H, Mrabet M (2018) The prole of women victims of domestic
violence in Morocco. La Revue de MéDecine LéGale 9(3):96–102.
https://doi.org/10.1016/j.medleg.2018.05.002
15. Chauluka M, Uzochukwu BS, Chinkhumba J (2022) Factors associated with coverage of health
insurance among women in Malawi. Front Health Serv 2:780550
1. Chernet AG, Cherie KT (2020) Prevalence of intimate partner violence against women and
associated factors in Ethiopia. BMC Womens Health 20:22
17. Chikhungu LC, Amos M, Kandala N, Palikadavath S (2021) Married women’s experience of domestic
violence in Malawi: New evidence from a cluster and multinomial logistic regression analysis. J
interpers Violence 36(17–18):8693–8714
1. Chilanga E, Collin-Vezina D, Khan MN, Riley L (2020) Prevalence and determinants of intimate
partner violence against mothers of children under ve years in Central Malawi. BMC Public Health
20:1–14
Page 18/21
19. Dhakal L, Berg-Beckhoff G, Aro AR (2014) Intimate partner violence (physical and sexual) and
sexually transmitted infection: Results from Nepal Demographic Health Survey 2011. Int J Women's
Health, 75–82
20. Dhar D, McDougal L, Hay K, Atmavilas Y, Silverman J, Triplett D, Raj A (2018) Associations between
intimate partner violence and reproductive and maternal health outcomes in Bihar, India: A cross-
sectional study. Reproductive Health 15:1–14
21. Do KN, Weiss B, Pollack A (2013) Cultural Beliefs, Intimate Partner Violence and Mental Health
Functioning among Vietnamese Women. Int Perspect Psychol 2(3). 10.1037/ipp0000004
22. Do KN, Weiss B, Pollack A (2013) Cultural beliefs, intimate partner violence and mental health
functioning among Vietnamese women. Int Perspect Psychol 2(3).
https://doi.org/10.1037/ipp0000004
23. Dovonou CA, Alassani CA, Alassan KS, Tamou S, Attinsounon CA, Ahoui S, Wanvoegbe FA (2024)
Frequency and factors associated with gender-based violence in the Northern Region of Benin from
2016 to 2022. Open J Intern Med 14:287–298. https://doi.org/10.4236/ojim.2024.143026
24. Ellsberg M, Arango DJ, Morton M, Gennari F, Kiplesund S, Contreras M, Watts C (2015) Prevention of
violence against women and girls: What does the evidence say? Lancet 385(9977):1555–1566
25. Feseha G, Gerbaba M (2012) Intimate partner physical violence among women in Shimelba refugee
camp, northern Ethiopia. BMC Public Health Feb 13:12:125. 10.1186/1471-2458-12-125
2. Feseha G, mariam G, A., Gerbaba M (2012) Intimate partner physical violence among women in
Shimelba refugee camp, northern Ethiopia. BMC Public Health 12:125.
https://doi.org/10.1186/1471-2458-12-125
27. Forty J (2021) Do women with autonomy in the household experience less intimate partner violence
in Malawi? Evidence from the 2015-16 Demographic and Health Survey. J Biosoc Sci 54(6):939–
958. https://doi.org/10.1017/s0021932021000559
2. Garcia-Moreno C, Jansen HA, Ellsberg M, Heise L, Watts C (2005) WHO Multicountry Study on
Women’s Health and Domestic Violence Against Women: Initial Results on Prevalence, Health
Outcomes and Women’s Responses. World Health Organization, Geneva
29. García-Moreno C, Zimmerman C, Morris-Gehring A, Heise L, Amin A, Abrahams N, Watts C (2015)
Addressing violence against women: a call to action. Lancet 385(9978):1685–1695
30. Giammarioli AM, Longo E, Bucciardini R (2023) Gender-Based Violence is a Never to be Forgotten
Social Determinant of Health: A Narrative Literature Review. Women's Health Problems-A Global
Perspective
31. Kiser M, Escamilla V, Samuel J, Eichelberger K, Mkwaila J, Cairns B, Charles A (2013) Sex
differences in interpersonal violence in Malawi: Analysis of a hospital-based trauma registry. World J
Surg 37(12):2972–2978
32. Kreager DA, Felson RB, Warner C, Menger MR (2013) Women's Education, Marital Violence, and
Divorce: A Social Exchange Perspective. J Marriage Family 75(3):565–581.
https://onlinelibrary.wiley.com/doi/abs/ 10.1111/jomf.12018
Page 19/21
33. Kreager DA, Felson RB, Warner C, Menger MR (2013) Women's education, marital violence, and
divorce: A social exchange perspective. J Marriage Family 75(3):565–581.
https://doi.org/10.1111/jomf.12018
34. Letourneau EJ, Assini-Meytin LC, Nair R, Stuart EA, Decker MR, McGinty EB (2022) Health insurance
expansion and family violence prevention: A conceptual framework. Child Abuse Negl 129:105664
35. Ma N, Chen S, Kong Y, Chen Z, Geldsetzer P, Zeng H, Li Z (2023) Prevalence and changes of intimate
partner violence against women aged 15 to 49 years in 53 low-income and middle-income countries
from 2000 to 2021: a secondary analysis of population-based surveys. Lancet Global Health
11(12):e1863–e1873
3. Magombo PW, Nkoka O, Ntenda PAM (2021) Association between intimate partner violence and the
use of maternal health care services among married Malawian women. BMC Women’s Health 21(1).
https://doi.org/10.1186/s12905-021-01312-6
37. Maine RG, Williams B, Kincaid JA, Mulima G, Varela C, Gallaher JR, Charles AG (2018) Interpersonal
violence in peacetime Malawi. Trauma Surg Acute Care Open, 3(1), e000252
3. McKinney CM, Caetano R, Harris TR, Ebama MS (2009) Alcohol availability and intimate partner
violence among US couples. Alcoholism: Clin Experimental Res 33(1):169–176.
https://doi.org/10.1111/j.1530-0277.2008.00825.x
39. Mukanangana F, Moyo S, Zvoushe A, Rusinga O (2014) Gender-based violence and it's Effects on
women's Reproductive Health: The Case of Hatcliffe, Harare, Zimbabwe. Afr J Reprod Health
18(1):110–122
40. Mukanangana F, Moyo S, Zvoushe A, Rusinga O (2014) Gender-based violence and its effects on
women's reproductive health: The case of Hatcliffe, Harare, Zimbabwe. African. J Reproductive
Health 18(1):110–122
41. NSO-Malawi,DHS-Program (2017) Malawi Demographic and Health Survey Report 2015–2016.
Zomba, Malawi and Rockville, Maryland USA. NSO and ICF
42. NSO (2021) Malawi Multiple Indicator Cluster Survey 2019-20, survey ndings report. Zomba,
Malawi Natl Stat Off.
43. Sanz-Barbero B, Barón N, Vives-Cases C (2019) Prevalence, associated factors and health impact of
intimate partner violence against women in different life stages. PLoS ONE 14(10):e0221049.
https://doi.org/10.1371/journal.pone.0221049
44. Sapkota PM, Pandey AR, Adhikari B, Shrestha G, Piya R, Lamichhane B, Garu S, Joshi D, Baral SC
(2024) Intimate partner violence in Nepal: Analysis of Nepal Demographic and Health Survey 2022.
PLoS ONE 19(8):e0308107. https://doi.org/10.1371/journal.pone.0308107
45. Sardinha L, Maheu-Giroux M, Stöckl H, Meyer SR, García-Moreno C (2022) Global, regional, and
national prevalence estimates of physical or sexual, or both, intimate partner violence against
women in 2018. Lancet 399(10327):803–813
4. Sen S, Bolsoy N (2017) Violence against women: prevalence and risk factors in Turkish sample.
BMC Womens Health 17:1–9
Page 20/21
47. Stephenson R, Jadhav A, Hindin M (2013) Physical domestic violence and subsequent contraceptive
adoption among women in rural India. J interpers Violence 28(5):1020–1039
4. Tesfaye M, Ndlovu AV, Thompson E, Sofo S (2024) Prevalence and Predictors of Physical Abuse of
Women in Uganda and Malawi. Can J Educational Social Stud 4(1):11–24
49. Tetikcok R, Ozer E, Cakir L, Enginyurt O, İscanli MD, Cankaya S, Ozer F (2016) Violence towards
women is a public health problem. J Forensic Leg Med 44:150–157
50. Vyas S, Meinhart M, Troy K, Brumbaum H, Poulton C, Stark L (2023) The economic cost of violence
against women and girls in low-and middle-income countries: a systematic review of the evidence.
Trauma Violence Abuse 24(1):44–55
51. WHO (2017) WHO Fact Sheet: Violence against women.2018, from http://www.who.int/news-
room/fact-sheets/details/Violence -against-women
Figures
Figure 1
Distribution of physical attack according to duration
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Figure 2
Distribution of physical attack according to number of perpetrators