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Prevalence and Correlates of Intimate Partner Violence by Type and Severity: Population-Based Studies in Azerbaijan, Moldova, and Ukraine

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The article estimates the prevalence and sociodemographic correlates of intimate partner violence (IPV) by type and severity in population-based samples from three countries of the former Soviet Union (fSU). The article utilized nationally representative data from the Demographic and Health Surveys (DHS) conducted in Azerbaijan (2006), Moldova (2005), and Ukraine (2007). Respondents were selected using stratified multistage cluster sampling. The sample included ever-married (or cohabitating) females of reproductive age (15-49 years old); weighted sample n = 3,847 in Azerbaijan, n = 4,321 in Moldova, and n = 2,355 in Ukraine. The analysis used multinomial survey logistic regression adjusting for the sampling design and sampling weights. Ten percent of ever-partnered women in Azerbaijan and Ukraine and 20% in Moldova ever experienced physical IPV (without sexual) from their most recent husband or cohabitating partner; 3% of women in Azerbaijan and Ukraine and 5% in Moldova experienced sexual IPV (with or without physical), and 2% of women in Azerbaijan, 3% in Ukraine, and 6% in Moldova experienced violence resulting in severe physical injuries from their most recent partner. In all three countries physical, sexual, and injurious IPV was higher among formerly married women. Compared to women with above secondary education, women with secondary education or below demonstrated higher risk for physical IPV (in Moldova and Ukraine), sexual IPV in Moldova, and injurious IPV in all three countries. Poor socioeconomic status-as indicated by low household wealth status in Azerbaijan and partner's unemployment in Moldova and Ukraine-was significantly associated with higher risk for physical and injurious IPV. In Moldova and Ukraine partners' low level of education was associated with higher risk for sexual IPV. The article demonstrates that experiences and factors associated with IPV are diverse and context specific. The findings may be helpful in targeting interventions to sociodemographic groups disproportionately affected by IPV in these three transitional countries.
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DOI: 10.1177/0886260513479026
2013 28: 2521 originally published online 18 March 2013J Interpers Violence
Leyla Ismayilova and Nabila El-Bassel
Ukraine
Severity: Population-Based Studies in Azerbaijan, Moldova, and
Prevalence and Correlates of Intimate Partner Violence by Type and
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DOI: 10.1177/0886260513479026
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Article
Prevalence and
Correlates of Intimate
Partner Violence by
Type and Severity:
Population-Based Studies
in Azerbaijan, Moldova,
and Ukraine
Leyla Ismayilova1 and Nabila El-Bassel2
Abstract
The article estimates the prevalence and sociodemographic correlates of
intimate partner violence (IPV) by type and severity in population-based
samples from three countries of the former Soviet Union (fSU). The
article utilized nationally representative data from the Demographic and
Health Surveys (DHS) conducted in Azerbaijan (2006), Moldova (2005),
and Ukraine (2007). Respondents were selected using stratified multistage
cluster sampling. The sample included ever-married (or cohabitating)
females of reproductive age (15-49 years old); weighted sample n = 3,847 in
Azerbaijan, n = 4,321 in Moldova, and n = 2,355 in Ukraine. The analysis used
multinomial survey logistic regression adjusting for the sampling design and
sampling weights. Ten percent of ever-partnered women in Azerbaijan and
Ukraine and 20% in Moldova ever experienced physical IPV (without sexual)
from their most recent husband or cohabitating partner; 3% of women in
Azerbaijan and Ukraine and 5% in Moldova experienced sexual IPV (with or
without physical), and 2% of women in Azerbaijan, 3% in Ukraine, and 6% in
1School of Social Service Administration, University of Chicago, IL, USA
2Columbia University School of Social Work (CUSSW), New York, NY
Corresponding Author:
Leyla Ismayilova, School of Social Service Administration, University of Chicago, 969 East 60th
Street, Chicago, IL 60637, USA.
Email: leyla@uchicago.edu
479026JIV281210.1177/0886260513479026Journal of Interpersonal ViolenceIsmayilova and El-Bassel
research-article2013
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2522 Journal of Interpersonal Violence 28(12)
Moldova experienced violence resulting in severe physical injuries from their
most recent partner. In all three countries physical, sexual, and injurious IPV
was higher among formerly married women. Compared to women with
above secondary education, women with secondary education or below
demonstrated higher risk for physical IPV (in Moldova and Ukraine), sexual
IPV in Moldova, and injurious IPV in all three countries. Poor socioeconomic
status—as indicated by low household wealth status in Azerbaijan and
partner’s unemployment in Moldova and Ukraine—was significantly
associated with higher risk for physical and injurious IPV. In Moldova and
Ukraine partners’ low level of education was associated with higher risk for
sexual IPV. The article demonstrates that experiences and factors associated
with IPV are diverse and context specific. The findings may be helpful in
targeting interventions to sociodemographic groups disproportionately
affected by IPV in these three transitional countries.
Keywords
intimate partner violence, domestic violence, spousal violence, the former
Soviet Union, transitional countries, Newly Independent States (NIS),
physical and sexual violence, severity of violence.
Introduction
Intimate partner violence (IPV)—defined as a “behavior within an intimate
relationship that causes physical, sexual or psychological harm” (World
Health Organization [WHO], 2002, p. 89)—is a global social issue that
infringes on a woman’s rights, endangers her safety, and affects her overall
well-being. The majority of data on IPV come from Western industrialized
countries or developing countries of Africa, Latin America, and Asia (García-
Moreno, Jansen, Ellsberg, Heise, & Watts, 2005; Kishor & Johnson, 2004;
Koenig, Ahmed, Hossain, & Khorshed Alam Mozumder, 2003; Koenig,
Stephenson, Ahmed, Jejeebhoy, & Campbell, 2006; Lawoko, 2006; Xu et al.,
2005; Naved & Persson, 2005). According to the Demographic and Health
Survey (DHS; Kishor & Johnson, 2004), the prevalence of physical violence
committed by most recent or current husband or cohabitating partner varies
substantially across developing nations from 48% in Zambia, 40% in
Colombia, and 34% in Egypt to lower rates in Cambodia (16%), Haiti (17%),
and the Dominican Republic (18%). Sexual violence by most recent or cur-
rent partner ranges from 17% in Haiti, 11% in Colombia to 6% in the
Dominican Republic and 4% in Cambodia (Kishor & Johnson, 2004). A sig-
nificant portion of reported IPV in these countries results in minor (e.g.,
bruises) or more serious injuries (e.g., broken bones) or requires medical
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Ismayilova and El-Bassel 2523
attention (54% in Colombia, 38% in Cambodia, and 19% both in Egypt and
Haiti; Kishor & Johnson, 2004). The WHO multicountry study on Women’s
Health and Domestic Violence conducted in 10 developing and developed
countries measured violence committed by current or former partners, and
the lifetime prevalence of physical IPV ranged from 13% in Japan to 61% in
Peru, with the rest of countries falling between 23% and 49% (García-Moreno
et al., 2005; Garcia-Moreno, Jansen, Ellsberg, Heise, & Watts, 2006). The
lifetime prevalence of sexual violence by an intimate partner at any point in
life was between 6% (Japan and Serbia and Montenegro) and 59% (Ethiopia),
with the rest of study sites reporting between 10% and 50% (Garcia-Moreno
et al., 2006).
However, a scarce body of scientific knowledge is available on IPV in the
transitional countries of the former Soviet Union (fSU), also known as Newly
Independent States (NIS; Institute of Medicine [IOM], 2008). The available
research on IPV in the fSU countries is primarily limited to descriptive stud-
ies (Centers for Disease Control and Prevention [CDC], 2003; International
Rescue Committee [IRC], 2004; National Scientific and Applied Center for
Preventive Medicine of the Ministry of Health and Social Protection [NCPM]
& ORC Macro, 2006; United Nations Development Programme [UNDP],
2005), often with small or nonrandom samples (Winrock International,
2001). Thus, the magnitude and sociodemographic characteristics signifi-
cantly associated with increased rates of IPV remain unknown in the fSU
region (CDC, 2003). Low socioeconomic status commonly manifested
through household poverty, unemployment, and lower educational attain-
ment were found to be associated with a greater risk for physical and/or sex-
ual IPV across many countries, including Chile, Egypt, India, and the
Philippines (Bangdiwala et al., 2004), Australia (Dal Grande, Hickling,
Taylor, & Woollacott, 2003), South Africa (Jewkes, Levin, & Penn-Kekana,
2002), Mexico (Rivera-Rivera et al., 2004), and in the United States (Ionita,
2012). The associations between IPV and other sociodemographic correlates
such as age, rural versus urban residence, and marital status demonstrate
mixed findings and vary across countries (Ionita, 2012; Jewkes et al., 2002).
Without country-specific data about how IPV is distributed across various
sociodemographic groups by type and severity, it is difficult to create a com-
prehensive picture of IPV in each country and develop appropriate services
specific to the fSU countries (United Nations Economic Commission for
Europe [UNECE], 2004).
Only in recent years two multicountry population-based studies—DHS
and Reproductive Health Survey (RHS)—provided the first nationally repre-
sentative data on IPV in the fSU region. The RHS study (CDC, 2003) was
conducted between 1997 and 2000. The DHS surveys were conducted
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between 2005 and 2007 and represent the most recent data on IPV in the
region. Both RHS and DHS surveys utilized similar multistage sampling
strategies, interviewed one woman per household, and collected information
about IPV committed by married or cohabiting partners among ever-partnered
women of reproductive age (ages 15-49). Although the RHS study provides
data about lifetime IPV committed by current or former partners and the DHS
focuses only on most recent partners, the DHS data capture more recent
developments in the fSU countries and will be used in this article. The article
focuses on Azerbaijan, Moldova, and Ukraine, the only three fSU counties
that included a Domestic Violence (DV) module, in addition to the standard
DHS questionnaire. Prior to the DHS survey, data collected on IPV and asso-
ciated factors in women in the fSU region did not utilize a unified methodol-
ogy and, therefore, were not readily comparable. The multicountry World
Mental Health (WMH) survey conducted in Ukraine in 2002 provides nation-
ally representative data on lifetime and current physical IPV both from
women and men (N = 1,116) but includes only one country from the fSU
region and does not include measures of sexual IPV and IPV resulting in
physical injuries (O’Leary, Tintle, Bromet, & Gluzman, 2008). The DHS
data, for the first time, present an opportunity for cross-country comparison
in this region.
Politically, geographically, and socially the fSU region represents a com-
mon area that deserves special consideration. Given the regional similarities,
the results from analyses of these three countries may potentially be appli-
cable to other fSU countries.
Regional Context
After the collapse of Soviet Union in 1991, Azerbaijan, Moldova, and Ukraine
gained independence and since then have been in the transition stage from
socialist political and economic systems to independent democratic states
with market economies. As a part of the Soviet Union for 70 years, the coun-
tries shared similar socioeconomic, judicial, and political contexts (Suhrcke,
Rocco, & McKee, 2007). The transitional countries of fSU have a legacy of
strong infrastructure and well-established systems of social, educational, and
health care services dating back to the Soviet era (Heller & Keller, 2001). The
transition from a socialist to market economy, however, brought on the eco-
nomic crisis of the 1990s, along with massive political and social changes,
resulting in high unemployment, deterioration of services, financial instabil-
ity, ethnic wars, and growth in poverty and inequality (Scott, 2000). Economic
and social challenges of the transitional period had a devastating effect
on family functioning, level of stress, and emotional well-being of the
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Ismayilova and El-Bassel 2525
population, including increased alcohol consumption, homicide and suicide
rates, especially among adult males (Brainerd, 2001; Brainerd & Cutler,
2004; Pridemore & Chamlin, 2006). The fSU states lacked sufficient finan-
cial and technical resources to address social needs, including combating
IPV, which exacerbated the family crisis. Over the past decade all three coun-
tries have experienced economic growth (to varying degrees) and are in the
process of reforming their social and health care systems, including develop-
ing a national response to IPV (United States International Development
Agency [USAID], 2007). Study findings about sociodemographic groups
disproportionately affected by IPV would be valuable in making program and
policy decisions to allocate the resources efficiently.
Despite a number of similarities, the fSU region is not a homogeneous
entity. Due to differences in ethnicity and religion, family relationships and
cultural norms, especially in regards to women, vary across these countries
(CDC, 2003). Ukraine and Moldova, with predominantly Christian popula-
tions, share relatively more egalitarian gender beliefs, while Azerbaijan, a
secular Muslim nation, is characterized by more traditional values and con-
servative norms in respect to women (Asian Development Bank, 2006;
Heyat, 2006; Manijeh, 1999; Tohidi, 1996). Women in Moldova and
Ukraine enjoy more freedoms in respect to advanced education and employ-
ment outside of home, whereas women in Azerbaijan, particularly outside
of urban areas, are often expected to stay home and take care of their fami-
lies. The nationally representative data demonstrate that only 13% of
women in Azerbaijan pursue higher education compared to 21% of women
in Moldova and 33% in Ukraine, and only 20% of women in Azerbaijan are
currently employed compared to 51.4% in Moldova and 74% in Ukraine
(NCPM & ORC Macro, 2006; SSC & Macro International, Inc., 2008;
Ukrainian Center for Social Reforms [USCR], State Statistical Committee
[SSC], Ministry of Health [MOH], & Macro International, Inc., 2008). The
total fertility rate is also the highest in Azerbaijan among the three countries
(on average, 2.0 children per woman compared 1.7 in Moldova and 1.2 in
Ukraine).
Views on dating and sexual relationships are also more liberal in Moldova
and Ukraine, and premarital sexual relationships among women are more
acceptable by the society than in Azerbaijan. The median age at first inter-
course is higher in Azerbaijan (22 years) compared to Moldova (20 years)
and Ukraine (19.6 years) and is almost identical to the age at first marriage
(NCPM & ORC Macro, 2006; SSC & Macro International Inc, 2008; UCSR
et al., 2008). Although traditional values are changing in Azerbaijan, particu-
larly in the capital city Baku, living-together unmarried young couples are
relatively uncommon in the rest of the country. Only 0.2% of women in
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Azerbaijan report living together with their intimate partner, compared to 5%
in Moldova and 4.9% in Ukraine (NCPM & ORC Macro, 2006; SSC &
Macro International Inc, 2008; UCSR et al., 2008). At the same time,
Azerbaijan differs from countries with traditional Muslim cultures due to a
long history of socialistic ideology and suppression of religion. Nearly all
women in Azerbaijan have attended secondary school, and the female liter-
acy rate is 99% compared to 85% in Turkey, 81% in Iran, 58% in Egypt, and
44% in Morocco (World Bank, 2012). Furthermore, while Azerbaijan and
Ukraine exhibit significant economic growth, Moldova remains the poorest
country in Eastern Europe (Hensel & Gudim, 2004). Therefore, an examina-
tion of cross-country similarities and differences in relation to IPV in
Azerbaijan, Moldova, and Ukraine may contribute to the understanding of
IPV in a unique sociocultural context.
In the fSU countries, accurate official data regarding the magnitude of IPV
are scarce (CDC, 2003). Until recently IPV has not been defined as a separate
criminal offence, and crimes against women (e.g., assault, murder, rape) were
punishable irrespective of the relationship to perpetrator (Amnesty
International, 2006; Minnesota Advocates for Human Rights, 2000).
Therefore, the official criminal statistics on IPV were unclear, and data on
crimes committed by current or former partners were not readily available.
Although in recent years a number of fSU countries, including Ukraine,
Moldova, and latest Azerbaijan (in 2010), have adopted laws on prevention
and combating of domestic violence distinguishing IPV from assaults com-
mitted by other perpetrators, the challenges in reporting, recording, and pros-
ecution of IPV cases still remain (Fedkovych, Trokhym, & Chumalo, 2007;
Gureyeva, 2011; Ionita, 2012). With IPV being surrounded by the culture of
silence and ineffective legal mechanisms for resolving IPV-related issues,
crimes against women are still rarely reported to the police (Amnesty
International, 2006; UNDP, 2005), especially if committed by close relatives
(Yunus, Tahirova, & Alakbarova, 2004). However, health records indicate
that IPV is a serious issue in the region. For example, in Ukraine an emer-
gency doctor estimated that out of all injuries reported by women to his
trauma center between one third and one half were inflicted by their husbands
(Minnesota Advocates for Human Rights, 2000). The number of actual inci-
dents of IPV in these countries, however, is likely much higher. In a popula-
tion-based study, among ever-married women currently experiencing physical
abuse only 1% in Azerbaijan, 12% in Moldova, and 16% in Ukraine reported
violence to the police, or 1% in Azerbaijan, 16% in Moldova, and 9% in
Ukraine shared incidents of violence with their health providers (CDC, 2003).
Thus, usually only severe incidents of IPV are reported in the official health
and police records. Globally, nationally representative studies are useful in
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Ismayilova and El-Bassel 2527
providing information about the prevalence of IPV, but they are particularly
essential in countries where official data regarding IPV are scarce and/or
inaccurate.
Using population-based samples from Azerbaijan, Moldova, and Ukraine,
this article estimates the prevalence and severity of physical and sexual IPV
among ever-married women and examines the associations between physi-
cal and sexual IPV and key sociodemographic characteristics (woman’s age,
urban vs. rural area of residence, marital status, number of children, educa-
tion, employment status, household wealth, and partner’s education and
occupation).
Methods
Data Source
The study is an analysis of secondary data collected through the DHS in
Azerbaijan (2006), Moldova (2005), and Ukraine (2007) that provided
most recent nationally representative data on IPV. The DHS employs a uni-
fied methodology that allows for cross-country comparisons. The standard
DHS women’s questionnaire was administered in eight fSU countries and
included data on key sociodemographic, household, women’s status, and
maternal and reproductive health variables. The standard DHS question-
naire was conducted in Armenia (2000, 2005, 2010), Kazakhstan (1995,
1999), Kyrgyz Republic (1997), Turkmenistan (2000), and Uzbekistan
(1996, 2002). Except for Armenia, the DHS surveys in these fSU countries
were conducted before 2005 and used an earlier version of the DHS ques-
tionnaire (DHS-III and DHS-IV). In addition to the standard DHS question-
naire, three fSU countries—Azerbaijan (2006), Moldova (2005), and
Ukraine (2007)—administered the DV module. Therefore, the analysis is
limited to these three countries. The DHS questionnaire was administered
by trained local interviewers.
Sampling Scheme
DHS are nationally representative household surveys that use a stratified
multistage sampling strategy. Using the most recent national census, regional
clusters (or primary sampling units [PSUs]) are selected using a probability-
proportionate-to-size sampling procedure within each strata, meaning that
more populated clusters had a higher probability of being selected. The origi-
nal data sets (without applying sampling weights) include 381 regional clus-
ters in Azerbaijan, 400 in Moldova, and 500 in Ukraine. Households are then
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2528 Journal of Interpersonal Violence 28(12)
randomly selected within each selected cluster. The DV module is adminis-
tered to one randomly selected woman of reproductive age (15-49 years old)
within each selected household.1 Household and individual sampling weights
calculated by the DHS team are included in the data sets and are utilized to
account for the sampling design. The detailed sampling methodology is pre-
sented in the DHS sampling manual (Macro International, Inc., 1996) and
DHS country reports (NCPM & ORC Macro, 2006; SSC & Macro
International, Inc., 2008; UCSR et al., 2008).
In the Moldova DHS, the clusters were drawn separately for urban and
rural areas (strata). In Azerbaijan and Ukraine, the stratification was achieved
by separating economic regions (8 in Azerbaijan and 27 in Ukraine) into rural
and urban areas. Due to administrative difficulties and a blockade, no respon-
dents were included from the following areas: Transnistria (a disputed region
of Moldova), Nakhichevan (an autonomous republic in Azerbaijan), Kalbajar-
Lachin region and the four districts of Yukhari Garabakh (occupied territories
in Azerbaijan), and a region in Ukraine uninhabited since the Chernobyl
nuclear disaster.
The original samples (N = 8,444 in Azerbaijan, N = 7,440 in Moldova,
and N = 6,841 in Ukraine) were reduced to include ever-married2 (currently
or formerly married or cohabitating) women of reproductive age (15-49) who
were eligible and completed the DV module. Eligible ever-married women
who did not complete the DV module or who could not be interviewed
because privacy could not be achieved during their interviews (about 1% in
all three countries) were excluded from the analysis. The reduced sample
used in this study included 4,301 women in Azerbaijan, 4,593 women in
Moldova, and 2,453 women in Ukraine. To obtain nationally representative
estimates, weights from the DV module were used as sampling weights (final
weighted samples n = 3,847 in Azerbaijan, n = 4,321 in Moldova, and n =
2,355 in Ukraine).
Measures
Dependent variables: The DHS measures violence committed by most recent
husband/partner and covers four types of IPV—physical, sexual, psychologi-
cal, and partner’s controlling behaviors. This article focuses on physical and
sexual IPV and severity of these two types of IPV. A history of IPV by most
recent partner is defined as having occurred if a woman reported any abusive
acts ever committed by her current or most recent husband or cohabitating
partner. The DHS questionnaire included seven items measuring physical
violence: (a) husband/partner ever threw something at her, pushed, shoved;
(b) slapped the respondent; (c) twisted her arm, or pull her hair; (d) ever
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Ismayilova and El-Bassel 2529
punched with his fist or with something that could hurt her; (e) kicked,
dragged, or beat her up; (f) tried to choke or burn on purpose; or (g) threat-
ened or attacked with a knife, gun, or other type of weapon) and three items
measuring sexual violence (a) husband/partner ever physically forced respon-
dent to have sexual intercourse, (b) forced her to perform any other sexual
acts, and (c) respondent reported forced first sexual intercourse with this part-
ner. Almost all women who have reported ever experiencing sexual IPV also
reported ever experiencing physical IPV (see Table 2). Therefore, physical
and sexual IPV variables were recoded into a combined measure with three
categories: 0 = no reported history of physical or sexual IPV by most recent
partner, 1 = reported only physical IPV by most recent partner, 2 = reported
any sexual IPV (with or without physical IPV) by most recent partner.
Violence ever resulting in a physical injury is one of the approaches used
in the literature to measure the severity of physical or sexual IPV (United
Nations Statistics Division [UNSD], 2009). In the DHS study women who
reported ever experiencing physical or sexual IPV were asked whether the
following ever happened to them as a result of what their current or most
recent husband/partner did to them: (a) cuts, bruises, or aches; (b) eye inju-
ries, sprains, dislocations, burns; or (c) deep wounds, broken bones, broken
teeth, or other serious injuries. While classification of physical injuries is a
complex issue and consequences of violence may range from minor to life-
threatening injuries, less severe injuries (e.g., small cuts, bruises, or sprains)
occur more frequently compared to more severe and less frequent injuries
(e.g., broken bones, head injuries, broken teeth, knife wounds; El-Bassel et al.,
2007; Tjaden & Thoennes, 2000). The recoded measure of injurious IPV
included three categories reflecting the severity of physical injuries (0 = no
injuries, 1 = less severe injuries only (cuts, bruises, or aches), and 2 = more
severe injuries (eye injuries, sprains, dislocations, burns, or deep wounds,
broken bones, broken teeth, or other serious injuries).
Independent variables: Sociodemographic characteristics included respon-
dent’s age (in categories), marital status (currently vs. formerly married or
cohabitating), number of children (0, 1-2, and 3), rural/urban residence,
household wealth status, respondent’s and partner’s level of education,
respondent’s employment status and partner’s occupation. Marital status is a
binary variable representing (0) currently married (or cohabitating) women
or (1) formerly married (or formerly cohabitating) women, which includes
divorced, widowed, or separated women. To measure wealth status, the DHS
uses a wealth index that is computed using principal component analysis and
includes five quintiles (from 1 = lowest wealth to 5 = highest) based on own-
ership of durable assets (e.g., TV, mobile phone, washing machine, photo and
video cameras, computer, air conditioner, etc.), means of transpiration (e.g.,
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2530 Journal of Interpersonal Violence 28(12)
car), and ownership of land and farm animals. The index has been tested in
many countries and demonstrated to be an accurate measure of household
economic status in countries with irregular income data (Westoff, 2005). To
include a measure of household wealth status, the wealth index was dichoto-
mized into two categories: the lowest two quintiles (poor and poorest quin-
tiles) were coded as 1 to indicate poor wealth status, and the middle and two
highest quintiles (rich and richest quintiles) were coded as 0 and indicated
middle or high wealth status. Continuous variables measuring woman’s and
her partner’s total years of schooling were skewed. Recoded education vari-
ables included two categories “secondary education or below” (coded as 1)
and “above secondary education” (coded as 0). Due to the policy of manda-
tory secondary education in the fSU (10-11 years, an equivalent of high
school), the number of individuals who have no education or primary (ele-
mentary) education only was minimal (<0.5 in Ukraine, <1% in Moldova,
and <2% in Azerbaijan). “Secondary education or below” category also
included primary professional (vocational) education (e.g., professional-
technical institutions [PTU] for acquiring manual or basic skills occupa-
tions). “Above secondary education” category included institutions of higher
education (university-level undergraduate or graduate education) and sec-
ondary specialized education (tekhnicums) providing technical training for
midlevel professionals (nurses, midwives, musicians, technicians).
Respondent’s current employment status is a binary variable and mea-
sured whether respondent was employed at the time of the survey. Being
currently employed was defined as having done work in the past 7 days,
including those on leave or vacation. Given the difficulty of measuring wom-
en’s employment in developing countries and to avoid underestimating wom-
en’s employment in the informal sector, respondents were asked about any
work they may have done for family, others, or self, including any jobs for
which they are paid in cash, in kind, or not at all (e.g., having a small busi-
ness, working on the family farm, or in the family business). The DHS wom-
en’s questionnaire did not include a variable on partner’s current employment
status. Instead, we included partner’s occupation variable with five catego-
ries (professional, technical, or managerial; sales and services; skilled and
unskilled manual labor; agriculture; and did not work/no occupation).
Data Analysis
The statistical analysis was performed in STATA 12 for complex surveys.
Descriptive statistics and regression models included survey command
(-svy-) to account for DHS’s stratified multistage cluster sampling design.
Regional clusters were specified as PSUs, and weights from the DV module
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Ismayilova and El-Bassel 2531
were used as sampling weights. In Moldova urban/rural area was specified as
strata. In Azerbaijan and Ukraine strata variable included rural and urban
areas within each economic region. Without specifying sampling design, by
default STATA assumes that the observations are drawn using simple random
sampling (Hamilton, 2009). Ignoring the nested structure of the data set may
underestimate the standard errors and produce more statistically significant
results, increasing the risk of Type 1 error (Chambers & Skinner, 2003).
Univariate statistics combined with Stata’s survey and subpopulation
(-subpop-) commands were used to obtain nationally representative estimates
of IPV prevalence by type and severity. Ever-married or cohabitating women
were specified as the subpopulation. Tables 1 and 2 include weighted per-
centages and means along with corresponding 95% confidence intervals that
take into account variability in country-level means and percentages across
regional clusters and strata.
We then used multinomial (or polytomous) survey logistic regression
adjusted for the sampling design to estimate associations between IPV and
sociodemographic characteristics. First, we calculated unadjusted relative
risks (RR) with corresponding 95% confidence intervals (CI) for each
sociodemographic measure and then we calculated adjusted RRs simultane-
ously controlling for other sociodemographic characteristics. The IPV and
most predictor variables had less than 0.1% missing data. Variables measur-
ing partner’s years of education and partner’s occupation had between 0.63%
and 1.39% missing values. Missing data less than 5% should not pose any
significant problems during the analysis (Graham, 2009). The models were
tested for multicollinearity, and variance inflation factors (VIFs) did not
exceed 1.74, which was below the cutoff value of 10, indicating high collin-
earity (Tabachnick & Fidell, 2006). The statistical analysis was conducted
individually for each country, and the results were compared.
Results
Participant Characteristics
Table 1 contains information about sociodemographic characteristics of the
sample. The mean age of respondents was 35 to 36 years across all three
countries. However, there were fewer 15- to 24-year-old ever-married
women in the Ukrainian data set, compared to the two other countries. The
percentage of formerly married women was lowest in Azerbaijan (10%),
followed by Moldova (12%) and Ukraine (22%). In Ukraine, respondents
predominantly lived in urban areas (70%), and in Moldova in rural areas
(60%), with Azerbaijan having a relatively equal proportion of respondents
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2532 Journal of Interpersonal Violence 28(12)
Table 1. Sociodemographic Characteristics of the Sample (15- to 49-Year-Old
Ever-Married or Cohabitating Women From Demographic and Health Survey
(DHS) Azerbaijan 2006, DHS Moldova 2005, and DHS Ukraine 2007).
Azerbaijan Moldova Ukraine
Sociodemographic
characteristics %
95% Confidence
Intervals %
95% Confidence
Intervals %
95% Confidence
Intervals
Age (in categories)
15-24 14.54 [12.98, 16.25] 14.91 [13.76, 16.15] 10.23 [8.61, 12.1]
25-34 31.28 [29.33, 33.29] 31.95 [30.48, 33.45] 30.37 [28.26, 32.57]
35-44 38.87 [36.81, 40.96] 32.68 [30.96, 34.43] 38.64 [36.32, 41.02]
45-49 15.32 [13.78, 16.99] 20.46 [19.04, 21.96] 20.76 [18.74, 22.94]
Residence
Urban 56.17 [52.94, 59.35] 40.05 [38.27, 41.86] 69.77 [67.77, 71.71]
Rural 43.83 [40.65, 47.06] 59.95 [58.14, 61.73] 30.23 [28.29, 32.23]
Marital status
Currently married or
living together
89.74 [88.08, 91.19] 88.04 [86.78, 89.2] 77.73 [75.65, 79.68]
Formerly married
or living together
(divorced, widowed,
or separated)
10.26 [8.81, 11.92] 11.96 [10.8, 13.22] 22.27 [20.32, 24.35]
Living children
0 10.11 [9.1, 11.23] 10.95 [9.86, 12.15] 10.87 [9.45, 12.48]
1-2 56.25 [54.2, 58.28] 68.83 [66.76, 70.83] 81.51 [79.61, 83.27]
3 and more 33.63 [31.53, 35.81] 20.22 [18.35, 22.22] 7.62 [6.43, 9.01]
Socioeconomic status
Wealth status
Middle or high (ref.) 61.79 [58.67, 64.82] 65.00 [62.11, 67.79] 66.71 [63.4, 69.86]
Low/poor 38.21 [35.18, 41.33] 35.00 [32.21, 37.89] 33.29 [30.14, 36.6]
Respondent’s education
Above secondary
(>11 years)
27.28 [25.05, 29.63] 43.37 [41.27, 45.49] 68.23 [65.68, 70.68]
Secondary or below 72.72 [70.37, 74.95] 56.63 [54.51, 58.73] 31.77 [29.32, 34.32]
Respondent’s employment
Employed 21.74 [19.64, 23.98] 60.42 [58.31, 62.49] 79.83 [77.68, 81.82]
Unemployed 78.26 [76.02, 80.36] 39.58 [37.51, 41.69] 20.17 [18.18, 22.32]
Partner’s characteristics
Partner’s education
Above secondary
(>11 years)
36.47 [34.16, 38.83] 41.10 [39.19, 43.04] 63.60 [61.15, 65.99]
Secondary or below 63.53 [61.17, 65.84] 58.90 [56.96, 60.81] 36.40 [34.01, 38.85]
Partner’s occupation
Professional, technical,
or managerial
22.11 [19.97, 24.41] 11.29 [10.18, 12.5] 22.43 [20.31, 24.69]
Sales and services 15.11 [13.27, 17.16] 9.07 [8.10, 10.14] 29.94 [27.7, 32.28]
Skilled and unskilled
manual
46.92 [44.01, 49.85] 49.98 [47.89, 52.06] 44.6 [42.14, 47.09]
Agriculture 11.65 [9.89, 13.67] 18.5 [16.58, 20.57] 1.31 [.86, 2]
Did not work/no
occupation
4.21 [3.49, 5.07] 11.17 [10.83, 13.37] 1.72 [1.2, 2.44]
(continued)
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Ismayilova and El-Bassel 2533
Azerbaijan Moldova Ukraine
Sociodemographic
characteristics %
95% Confidence
Intervals %
95% Confidence
Intervals %
95% Confidence
Intervals
Number of regional
clusters (primary
sampling units [PSUs])
318 400 494
Number of strata 17 2 53
Number of observations
(unweighted sample)
4,301 4,593 2,453
Population size (weighted
sample)
3,847 4,321 2,355
Note: Percentages in columns are based on weighted data.
in urban and rural areas (56% vs. 44%, respectively). The level of education
was higher in Ukraine, where 68% of female participants went beyond sec-
ondary education compared to 43% female participants in Moldova and
27% in Azerbaijan. The majority of women in Ukraine (80%) and Moldova
(60%) were currently employed, whereas the majority of respondents in
Azerbaijan (78%) were not employed at the time of the survey. More women
in Azerbaijan (34%) reported having three or more children, compared to
20% of women in Moldova and 8% in Ukraine. Approximately a third of
participants in all three countries were from poor households (the two lowest
wealth quintiles). In Ukraine and Moldova, a slightly higher percentage of
women reported having above secondary education compared to their male
partners. However, in Azerbaijan, the relationship was reversed; 36% of
male partners reported having above secondary education compared to 27%
of female respondents. In all three countries almost half of respondents had
partners involved in skilled or unskilled manual labor; Ukraine has the low-
est percentage of partners involved in agriculture (1.3%) and Moldova had
the highest (18.5%).
Prevalence of IPV
Table 2 presents nationally representative estimates of the prevalence of phys-
ical, sexual, and injurious IPV committed by most recent partner among ever-
married (or cohabitating) women of reproductive age in Azerbaijan, Moldova,
and Ukraine. Twenty-four percent of respondents in Moldova and 13% both in
Azerbaijan and in Ukraine reported ever experiencing any acts of physical
IPV from their most recent or current partner. About 5% of respondents in
Table 1. (continued)
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Table 2. Physical, Sexual, and Injurious Violence Committed by Current or
Most Recent Husband or Cohabitating Partner Among 15- to 49-Year-Old Ever-
Partnered Women From Azerbaijan, Moldova, and Ukraine.
Azerbaijan Moldova Ukraine
Intimate Partner Violence
by Current or Most
Recent Partner %
95% Confidence
Intervals %
95% Confidence
Intervals %
95% Confidence
Intervals
Ever experienced any physical IPV from current or most recent partner
No 87.2 [85.68, 88.57] 75.87 [74.04, 77.61] 87.35 [85.44, 89.04]
Yes 12.80 [11.43, 14.32] 24.13 [22.39, 25.96] 12.65 [10.96, 14.56]
Ever experienced any sexual IPV from current or most recent partner
No 97.09 [96.28, 97.73] 95.01 [94.18, 95.73] 96.72 [95.54, 97.59]
Yes 2.91 [2.27, 3.72] 4.99 [4.27, 5.82] 3.28 [2.41, 4.46]
Ever experienced both physical and sexual IPV from current or most recent partner
No 97.78 [97.08, 98.31] 95.87 [95.11, 96.51] 97.25 [96.14, 98.05]
Yes 2.22 [1.69, 2.92] 4.13 [3.49, 4.89] 2.75 [1.95, 3.86]
A history of IPV from current or most recent partner (combined measure)
No physical IPV 86.51 [85, 87.88] 75.02 [73.18, 76.77] 86.81 [84.82, 88.58]
Any physical IPV only 10.58 [9.4, 11.91] 19.99 [18.36, 21.73] 9.91 [8.48, 11.54]
Any sexual IPV with or
without physical IPV
2.91 [2.27, 3.72] 4.99 [4.27, 5.82] 3.28 [2.41, 4.46]
Ever experienced injurious IPV (physical or sexual IPV resulting in any physical injuries)
No injuries 94.7 [93.73, 95.53] 85.25 [83.81, 86.58] 90.91 [89.3, 92.3]
Less severe injuries only
(e.g., bruises, aches)
3.01 [2.37, 3.82] 8.36 [7.36, 9.48] 6.35 [5.22, 7.72]
More severe injuries
(e.g., dislocations,
sprains, eye injuries,
broken bones, teeth)
2.29 [1.75, 2.98] 6.39 [5.46, 7.47] 2.73 [1.98, 3.77]
Physical or sexual IPV
ever resulted in any
physical injuries (among
women who reported
a history of physical or
sexual IPV from current
or most recent partner)
(n = 511)a(n = 1,061)a(n = 302)a
No injuries 60.1 [54.44, 65.51] 39.94 [36.34, 43.66] 29.27 [23.14, 36.26]
Less severe injuries only 22.69 [18.13, 28.01] 34.04 [30.44, 37.84] 49.45 [42.61, 56.32]
More severe injuries 17.21 [13.32, 21.95] 26.01 [22.67, 29.66] 21.28 [15.59, 28.35]
Note: Percentages in columns are based on weighted data.
aWeighted sample of women who reported ever experiencing physical or sexual IPV from current or most
recent partner.
Moldova and 3% of respondents both in Azerbaijan and Ukraine reported a
history of sexual violence from their most recent or current partner. Almost all
women who reported experiencing sexual IPV also reported experiencing
physical IPV. Twenty percent of respondents in Moldova, 11% in Azerbaijan,
and 10% in Ukraine reported experiencing only physical IPV (without sexual
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Ismayilova and El-Bassel 2535
IPV) at some points in their lives. Among women with a history of physical or
sexual IPV, 40% of women in Azerbaijan, 60% in Moldova, and 70% in
Ukraine have experienced violence that resulted in physical injuries (e.g.,
bruises, aches, dislocations, wounds, broken bones or teeth).
Correlates of Physical and Sexual IPV
The unadjusted models demonstrated that formerly married women, women
with only secondary education or below, and women whose partners have
only secondary education or below or involved in manual labor show higher
prevalence of physical IPV across all three countries (Table 3). Low house-
hold wealth in Azerbaijan and Moldova and partner’s unemployed status in
Ukraine and Moldova were associated with higher prevalence of physical
IPV. In Moldova the risk of physical IPV was higher among women from
rural areas and women with children.
Formerly married women in all three countries also reported higher prev-
alence of sexual IPV (with or physical IPV) compared to currently married
women. In Ukraine and Moldova physical IPV was higher among older cat-
egories of women, and in Moldova sexual IPV was also higher among
women above 35 years of age, when compared to 15- to 24-year-old ever-
partnered women.
After simultaneously adjusting for all sociodemographic covariates (wom-
an’s age, urban vs. rural area of residence, marital status, number of children,
education, employment status, household wealth, and partner’s education and
partner’s occupation), in all three countries marital status remained the stron-
gest sociodemographic factor associated with physical and sexual IPV (Table 4).
Formerly married women reported significantly higher rates of physical and
sexual IPV from most recent partner. In Ukraine, compared to ever-married
women below the age of 25, the risk of experiencing physical IPV was higher
for women of all other age groups (RR = 3.26-4.39), while the risk of sexual
IPV was lower among 25- to 44-year-old ever-married women. In Azerbaijan
the prevalence of IPV did not differ significantly by age groups.
After adjusting for other sociodemographic factors, there were no longer
statistically significant associations between age, rural residence, poor wealth
status, and physical IPV in Moldova. However, women with low levels of
educational attainment (secondary education or below), women who have
partners with low education, and women whose partners are unemployed or
involved in nonprofessional jobs (e.g., manual labor, agriculture) demon-
strated higher risk for physical and sexual IPV in Moldova. The risk for phys-
ical IPV was significantly higher among Moldovan women with children,
compared to women with no children.
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Table 3. Unadjusted Relative Risk Ratios for a History of Physical and Sexual Intimate Partner Violence (IPV) From Current or
Most Recent Husband or Cohabitating Partner Among 15- to 49-Year-Old Ever-Partnered Women in Azerbaijan, Moldova, and
Ukraine.
Azerbaijan Moldova UKRAINE
N = 3,847aN = 4,321aN = 2,355a
A History of IPV From Current or Most Recent
PartnerbA History of IPV From Current or Most Recent Partnerb
A History of IPV From Current or Most Recent
Partnerb
Physical IPV Only
Sexual IPV With or w/o
Physical IPV Physical IPV Only
Sexual IPV With or w/o
Physical IPV Physical IPV Only
Sexual IPV With or w/o
Physical IPV
Variables
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Demographic characteristics
Age (in categories)
15-24 (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
25-34 1.19 [0.76, 1.86] 1.60 [0.77, 3.34] 1.22 [0.92, 1.62] 1.7 [0.76, 3.14] 4.82*** [2.11, 10.97] 0.42 [0.15, 1.14]
35-44 1.22 [0.77, 1.94] 1.35 [0.66, 2.78] 1.62 [1.21, 2.17]*** 2.45** [1.35, 4.45] 6.42*** [2.87, 14.32] 0.48 [0.18, 1.30]
45-49 1.03 [0.61, 1.74] 0.67 [0.23, 1.98] 1.69 [1.25, 2.27]*** 2.35** [1.25, 4.42] 7.79*** [3.42, 17.74] 0.76 [0.25, 2.29]
Residence
Urban (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
Rural 1.17 [0.9, 1.52] 0.88 [0.52, 1.5] 1.75 [1.44, 2.13]*** 1.31 [0.95, 1.8] 1.4 [0.99, 1.97] 0.7 [0.38, 1.28]
Marital status
Currently
married or
living together
(ref)
1.0 1.0 1.0 1.0 1.0 1.0
Formerly
married or
living together
3.62*** [2.41, 5.42] 7.04*** [3.85, 12.86] 3.37*** [2.66, 4.27] 6.08*** [4.27, 8.67] 4.13*** [2.98, 5.71] 7.95*** [4.07, 15.53]
Number of living children
0 1.0 1.0 1.0 1.0 1.0 1.0
(continued)
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2537
Azerbaijan Moldova UKRAINE
N = 3,847aN = 4,321aN = 2,355a
A History of IPV From Current or Most Recent
PartnerbA History of IPV From Current or Most Recent Partnerb
A History of IPV From Current or Most Recent
Partnerb
Physical IPV Only
Sexual IPV With or w/o
Physical IPV Physical IPV Only
Sexual IPV With or w/o
Physical IPV Physical IPV Only
Sexual IPV With or w/o
Physical IPV
Variables
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
1-2 1.2 [0.75, 1.93] 1.31 [0.60, 2.86] 1.57** [1.07, 2.16] 1.99* [1.15, 3.47] 1.73 [0.95, 3.13] 0.43 [0.16, 1.11]
3 and more 1.28 [0.81, 2.01] 0.87 [0.35, 2.14] 2.62*** [1.29, 3.03] 2.96*** [1.62, 5.4] 2.62* [1.25, 5.5] 0.76 [0.24, 2.4]
Socioeconomic status
Wealth status
Middle or high
(ref.)
1.0 1.0 1.0 1.0 1.0 1.0
Low/poor 1.61* [1.2, 2.17] 0.94 [0.58, 1.52] 1.99*** [1.63, 2.42] 1.83*** [1.36, 2. 47] 1.29 [0.87, 1.93] 1.06 [0.53, 2.12]
Respondent’s education
Above
Secondary
(ref.)
1.0 1.0 1.0 1.0 1.0 1.0
Secondary or
Below (11
years)
1.66** [1.19, 2.31] 0.71 [0.4, 1.27] 1.81*** [1.48, 2.2] 2.18*** [1.56, 3.06] 1.77*** [1.28, 2.45] 1.73 [0.9, 3.32]
Respondent’s employment
Employed (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
Unemployed 0.87 [0.61, 1.25] 0.64 [0.35, 1.16] 0.92 [0.77, 1.1] 0.82 [0.6, 1.14] 0.72 [0.46, 1.13] 0.9 [0.38, 2.14]
Partner’s characteristics
Partner’s education
Above
secondary
(ref.)
1.0 1.0 1.0 1.0 1.0 1.0
(continued)
Table 3. (continued)
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2538
Azerbaijan Moldova UKRAINE
N = 3,847aN = 4,321aN = 2,355a
A History of IPV From Current or Most Recent
PartnerbA History of IPV From Current or Most Recent Partnerb
A History of IPV From Current or Most Recent
Partnerb
Physical IPV Only
Sexual IPV With or w/o
Physical IPV Physical IPV Only
Sexual IPV With or w/o
Physical IPV Physical IPV Only
Sexual IPV With or w/o
Physical IPV
Variables
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Secondary or
below (11
years)
1.45* [1.07, 1.96] 1.34 [0.76, 2.39] 2.05*** [1.69, 2.49] 2.42** [1.72, 3.4] 1.82*** [1.31, 2.51] 2.51** [1.3, 4.86]
Partner’s occupation
Professional,
technical, or
managerial
(ref.)
1.0 1.0 1.0 1.0 1.0 1.0
Sales and
services
1.37 [0.8, 2.35] 1.36 [0.57, 3.23] 1.93** [1.28, 2.93] 1.51 [0.91, 2.30] .99 [0.58, 1.67] 1.84 [0.56, 6.03]
Skilled and
unskilled
manual
2.05** [1.3, 3.23] 1.09 [0.52, 2.3] 2.37*** [1.74, 3.24] 3.5*** [0.91, 2.30] 1.7* [1.12, 2.58] 2.08 [0.66, 6.54]
Agriculture 1.21 [0.69, 2.12] 0.85 [0.28, 2.6] 4.0*** [2.76, 5.79] 5.91*** [0.91, 2.30] b b
Did not work/
no occupation
1.78 [0.83, 3.79] 0.58 [0.16, 2.13] 3.42*** [2.35, 4.97] 4.35*** [0.91, 2.30] 3.48** [1.43, 8.44] 1.92 [0.31, 12.0]
Note: Exponentiated coefficients; 95% confidence intervals in brackets.
aTotal weighted sample size.
bReference category: no lifetime physical or sexual IPV.
cCombined with “skilled and unskilled manual” category due to small number of individuals involved in agriculture in Ukraine.
*p < .05. **p < .01. ***p < .001.
Table 3. (continued)
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2539
Table 4. Adjusted Relative Risk Ratios for a History of Physical and Sexual Intimate Partner Violence (IPV) From Current or Most
Recent Husband or Cohabitating Partner Among 15- to 49-Year-Old Ever-Partnered Women in Azerbaijan, Moldova, and Ukraine.
Azerbaijan Moldova Ukraine
A History of IPV From Current or Most Recent
PartneraA History of IPV From Current or Most Recent Partnera
A History of IPV From Current or Most Recent
Partnera
Physical IPV Only
Sexual IPV With or w/o
Physical IPV Physical IPV Only
Sexual IPV With or w/o
Physical IPV Physical IPV Only
Sexual IPV With or w/o
Physical IPV
Variables
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Demographic characteristics
Age (in categories)
15-24 (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
25-34 1.1 [0.66, 1.84] 1.16 [0.59, 2.31] 1.13 [0.84, 1.54] 1.48 [0.72, 3.02] 3.26** [1.37, 7.76] 0.33* [0.12, 0.90]
35-44 0.99 [0.58, 1.67] 0.82 [0.42, 1.60] 1.34 [0.96, 1.85] 1.8 [0.87, 3.74] 3.65** [1.55, 8.60] 0.31* [0.10, 0.91]
45-49 0.72 [0.37, 1.38] 0.31 [0.10, 0.99] 1.26 [0.88, 1.80] 1.47 [0.66, 3.30] 4.39** [1.77, 10.89] 0.47 [0.14, 1.54]
Residence
Urban (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
Rural 0.92 [0.63, 1.35] 1.00 [0.45, 2.21] 1.21 [0.90, 1.63] 0.82 [0.53, 1.26] 1.09 [0.71, 1.67] 0.54 [0.23, 1.27]
Marital status
Currently
married or
living together
(ref.)
1.0 1.0 1.0 1.0 1.0 1.0
Formerly
married or
living together
4.2*** [2.73, 6.46] 8.42*** [4.07, 17.41] 3.9*** [3.04, 5.01] 6.95*** [4.76, 10.15] 4.12*** [3.11, 6.27] 8.86*** [3.94, 19.95]
Number of living children
0 1.0 1.0 1.0 1.0 1.0 1.0
1-2 1.43 [0.83, 2.46] 1.71 [0.70, 4.15] 1.46* [1.02, 2.08] 1.79 [0.89, 3.59] 1.39 [0.70, 2.77] 0.48 [0.17, 1.38]
3 and more 1.68 [0.98, 2.89] 1.88 [0.65, 5.39] 1.86** [1.22, 2.85] 2.08 [0.90, 4.80] 1.99 [0.89, 4.46] 1.02 [0.27, 3.87]
(continued)
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2540
Azerbaijan Moldova Ukraine
A History of IPV From Current or Most Recent
PartneraA History of IPV From Current or Most Recent Partnera
A History of IPV From Current or Most Recent
Partnera
Physical IPV Only
Sexual IPV With or w/o
Physical IPV Physical IPV Only
Sexual IPV With or w/o
Physical IPV Physical IPV Only
Sexual IPV With or w/o
Physical IPV
Variables
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Socioeconomic status
Wealth status
Middle or high
(ref.)
1.0 1.0 1.0 1.0 1.0 1.0
Low/poor 1.59* [1.04, 2.43] 1.04 [0.57, 1.90] 1.29 [0.98, 1.68] 1.29 [0.83, 2.01] 1.35 [0.90, 2.03] 1.03 [0.52, 2.07]
Respondent’s education
Above
secondary (ref.)
1.0 1.0 1.0 1.0 1.0 1.0
Secondary or
below (11
years)
1.34 [0.95, 1.88] 0.61 [0.30, 1.24] 1.27* [1.01, 1.59] 1.59* [1.10, 2.29] 1.61** [1.13, 2.29] 1.49 [0.68, 3.29]
Respondent’s employment
Employed (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
Unemployed 0.94 [0.66, 1.35] 0.97 [0.47, 2.01] 0.83 [0.68, 1.01] 0.73 [0.52, 1.04] 0.62* [0.40, 0.97] 0.84 [0.37, 1.87]
Partner’s characteristics
Partner’s education
Above
secondary
(ref.)
1.0 1.0 1.0 1.0 1.0 1.0
Secondary or
below (11
years)
0.96 [0.65, 1.43] 1.34 [0.70, 2.56] 1.46*** [1.15, 1.85] 1.54** [1.05, 2.27] 1.21 [0.84, 1.74] 2.41* [1.01, 5.83]
(continued)
Table 4. (continued)
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2541
Azerbaijan Moldova Ukraine
A History of IPV From Current or Most Recent
PartneraA History of IPV From Current or Most Recent Partnera
A History of IPV From Current or Most Recent
Partnera
Physical IPV Only
Sexual IPV With or w/o
Physical IPV Physical IPV Only
Sexual IPV With or w/o
Physical IPV Physical IPV Only
Sexual IPV With or w/o
Physical IPV
Variables
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Relative
Risk
95% Confidence
Intervals
Partner’s occupation
Professional,
technical, or
managerial
(ref.)
1.0 1.0 1.0 1.0 1.0 1.0
Sales and
services
1.34 [0.75, 2.41] 1.2 [0.53, 2.74] 1.72* [1.13, 2.62] 1.31 [0.52, 3.31] 0.76 [0.44, 1.29] 1.3 [0.42, 4.01]
Skilled and
unskilled
manual
1.95* [1.16, 3.30] 1.16 [0.58, 2.35] 1.63** [1.14, 2.32] 2.51* [1.21, 5.19] 1.22 [0.76, 1.94] 1.39 [0.46, 4.21]
Agriculture 1.1 [0.60, 2.02] 1.07 [0.30, 3.82] 2.06** [1.32, 3.20] 3.7** [1.62, 8.45] b b
Did not work/
no occupation
1.78 [0.79, 4.04] 0.72 [0.20, 2.61] 2.52*** [1.71, 3.72] 3.88** [1.65, 9.13] 3.35** [1.41, 7.97] 1.39 [0.23, 8.29]
Coefficient
F5.56 10.89 62.99
Design df 301 398 444
Number of
observations
(unweighted
sample)
4,233 4,549 2,416
Population size
(weighted
sample)
3,800 4,278 2,311
Note: Exponentiated coefficients; 95% confidence intervals in brackets.
aReference category: no lifetime physical or sexual IPV.
bCombined with “skilled and unskilled manual” category due to a small number of individuals involved in agriculture in Ukraine.
*p < .05. **p < .01. ***p < .001.
Table 4. (continued)
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2542 Journal of Interpersonal Violence 28(12)
In Azerbaijan, after adjusting for other sociodemographic factors, the risk
for physical IPV was higher among women from poor households (RR =
1.59, 95% CI = 1.04, 2.43) and among women whose partner were involved
in manual labor (RR = 1.95, 95% CI = 1.16, 3.3).
In Ukraine, the risk of physical IPV was higher among women with sec-
ondary education or below (RR = 1.61, 95% CI = 1.13, 2.29) compared to
women who went beyond secondary education. Partner’s low level of educa-
tion was associated with increased risk for sexual IPV (RR = 2.41, 95% CI =
1.01-5.83), whereas partner’s unemployment was associated in higher physi-
cal IPV in Ukraine (RR = 3.35, 95% CI = 1.41-7.97).
Correlates of IPV Resulting in Physical Injuries
Table 5 presents the results of unadjusted regression models for injurious IPV
and each sociodemographic measure. Both less severe and more severe inju-
ries were more likely to be reported by formerly married women in all three
countries. The relationships were maintained after adjusting for other
sociodemographic characteristics (Table 6). Women’s lower level of educa-
tion was associated with higher prevalence of injurious IPV in Azerbaijan
and Moldova.
As shown in Table 6, the adjusted analysis demonstrated that women
from poor households were significantly at higher risk for IPV resulting in
severe physical injuries in Azerbaijan (RR = 2.11, 95% CI = 1.19-3.73) and
in Ukraine (RR = 2.38, 95% CI = 1.12-5.06). Women with secondary edu-
cation or below reported higher prevalence of IPV resulting in less severe
physical injuries in Azerbaijan (RR = 2.38, 95% CI = 1.31-4.31) and
Ukraine (RR = 1.73, 95% CI = 1.11-2.70) and severe physical injuries in
Moldova (RR = 1.78, 95% CI = 1.24-2.56). In Moldova, after adjusting for
other variables, women above 25 years of age were more like to report IPV
resulting in physical injuries and the risk increased with age. Partner’s
involvement in manual labor was associated with higher risk for injurious
IPV in all three countries (IPV resulting in less severe injuries in Azerbaijan
and more severe injuries in Moldova and Ukraine). In addition, in Moldova,
partner’s lower level of education, rural residence, and having a partner
who is unemployed or involved in agriculture was associated with higher
likelihood of injurious IPV.
After adjusting for other covariates, in Azerbaijan the probability of IPV
resulting in severe physical injuries was lower in rural areas (RR = 0.4, 95%
CI = 0.21-0.76). In Ukraine the likelihood of IPV resulting in severe injuries
was lower in families with 1 to 2 children (RR = 0.32, 95% CI = 0.11-0.92)
compared to families with no children.
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2543
Table 5. Unadjusted Relative Risk Ratios for Ever Experiencing Injurious Intimate Partner Violence (IPV; Physical or Sexual IPV
Resulting in Physical Injuries) Most Recent Husband or Cohabitating Partner Among 15- to 49-Year-Old Ever-Partnered Women in
Azerbaijan, Moldova, and Ukraine.
Azerbaijan Moldova Ukraine
N = 511aN = 1,061aN = 303a
Physical or Sexual IPV Resulting in Physical InjuriesbPhysical or Sexual IPV Resulting in Physical InjuriesbPhysical or Sexual IPV Resulting in Physical Injuriesb
Less Severe Injuries More Severe Injuries Less Severe Injuries More Severe Injuries Less Severe Injuries More Severe Injuries
Variables
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Demographic characteristics
Age (in categories)
15-24 (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
25-34 1.76 [0.64, 4.79] 0.89 [0.35, 2.27] 1.75 [0.97, 3.15] 4.3*** [2.16, 8.56] 0.45 [0.10, 2.01] 0.3 [0.04, 2.34]
35-44 2.44 [0.93, 6.39] 0.94 [0.38, 2.28] 1.79* [1.03, 3.08] 4.83*** [2.36, 9.86] 0.47 [0.10, 2.16] 0.63 [0.08, 4.72]
45-49 2.51 [0.76, 8.29] 1.32 [0.42, 4.11] 2.38** [1.24, 4.55] 6.79*** [3.15, 14.66] 0.43 [0.09, 2.07] 0.6 [0.08, 4.49]
Residence
Urban (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
Rural 0.9 [0.5, 1.59] 0.53* [0.28, 0.98] 1.25 [0.90, 1.75] 1.01 [0.69, 1.47] 1.09 [0.59, 2.03] 1.12 [0.49, 2.56]
Marital status
Currently married or
living together (ref.)
1.0 1.0 1.0 1.0 1.0 1.0
Formerly married or
living together
3.29** [1.45, 7.46] 8.19*** [3.61, 18.59] 1.54* [1.02, 2.33] 2.54*** [1.68, 3.82] 2.55** [1.40, 4.63] 3.53** [1.50, 8.28]
Number of living children
0 1.0 1.0 1.0 1.0 1.0 1.0
1-2 1.19 [0.48, 2.92] 1.09 [0.39, 3.10] 0.68 [0.36, 1.29] 1.32 [0.64, 2.69] 0.4 [0.15, 1.05] 0.19* [0.05, 0.72]
3 and more 1.29 [0.51, 3.21] 0.75 [0.25, 2.29] 0.75 [0.38, 1.48] 1.58 [0.74, 3.37] 0.42 [0.11, 1.51] 0.3 [0.06, 1.52]
Socioeconomic status
Wealth status
Middle or high (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
Low/poor 1.62 [0.93, 2.82] 1.17 [0.64, 2.14] 1.01 [0.72, 1.42] 1.26 [0.87, 1.83] 1.22 [0.66, 2.26] 1.99 [0.85, 4.68]
(continued)
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2544
Azerbaijan Moldova Ukraine
N = 511aN = 1,061aN = 303a
Physical or Sexual IPV Resulting in Physical InjuriesbPhysical or Sexual IPV Resulting in Physical InjuriesbPhysical or Sexual IPV Resulting in Physical Injuriesb
Less Severe Injuries More Severe Injuries Less Severe Injuries More Severe Injuries Less Severe Injuries More Severe Injuries
Variables
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Respondent’s education
Above secondary (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
Secondary or below
(11 years)
2.57** [1.35, 4.89] 1.45 [0.70, 2.98] 0.93 [0.66, 1.29] 1.55* [1.04, 2.29] 1.19 [0.59, 2.42] 1.05 [0.47, 2.32]
Respondent’s employment
Employed (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
Unemployed 0.72 [0.35, 1.50] 0.63 [0.32, 1.27] 1.26 [0.89, 1.77] 0.89 [0.61, 1.30] 1.44 [0.52, 3.98] 1.48 [0.49, 4.46]
Partner’s characteristics
Partner’s education
Above secondary (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
Secondary or below
(11 years)
1.61 [0.85, 3.07] 1.75 [0.76, 4.05] 1.06 [0.73, 1.56] 1.5 [0.99, 2.28] 1.28 [0.70, 2.34] 1.31 [0.57, 3.04]
Partner’s occupation
Professional, technical,
or managerial (ref.)
1.0 1.0 1.0 1.0 1.0 1.0
Sales and services 1.91 [0.62, 5.89] 1.56 [0.47, 5.17] 0.6 [0.26, 1.38] 1.44 [0.48, 4.27] .75 [0.25, 2.30] 2.59 [0.58, 11.56]
Skilled and unskilled
manual
1.71 [0.74, 3.98] 0.81 [0.30, 2.23] 0.81 [0.44, 1.50] 2.36 [0.91, 6.12] 0.8 [0.34, 1.90] 3.44* [1.08, 10.95]
Agriculture 1.17 [0.42, 3.27] 1.12 [0.26, 4.83] 0.88 [0.43, 1.77] 3.03* [1.10, 8.30] c c
Did not work/no
occupation
2.3 [0.49, 10.8] 0.33 [0.05, 2.24] 1.0 [0.49, 2.06] 2.1 [0.75, 5.88] c c
Note: Exponentiated coefficients; 95% confidence intervals in brackets.
aTotal weighted sample size.
bReference category: no lifetime physical or sexual IPV.
cCombined with “skilled and unskilled manual” category due to a small number of individuals involved in agriculture or without any occupation in Ukraine.
*p < .05. **p < .01. ***p < .001.
Table 5. (continued)
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2545
Table 6. Adjusted Relative Risk Ratios for Ever Experiencing Intimate Partner Violence (IPV) Resulting in Physical Injuries Among
15- to 49-Year-Old Ever-Partnered Women With a History of Physical or Sexual IPV From Most Recent Partner in Azerbaijan,
Moldova, and Ukraine.
Azerbaijan Moldova Ukraine
Physical or Sexual IPV Resulting in Physical InjuriesaPhysical or Sexual IPV Resulting in Physical InjuriesaPhysical or Sexual IPV Resulting in Physical Injuriesa
Less Severe Injuries More Severe Injuries Less Severe Injuries More Severe Injuries Less Severe Injuries More Severe Injuries
Variables Relative Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Demographic characteristics
Age (in categories)
15-24 (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
25-34 1.88 [0.79, 4.48] 0.87 [0.36, 2.11] 1.65* [1.00, 2.72] 3.52*** [1.88, 6.58] 1.11 [0.44, 2.81] 0.83 [0.14, 4.94]
35-44 1.94 [0.85, 4.40] 0.65 [0.24, 1.78] 1.96** [1.21, 3.20] 4.26*** [2.17, 8.37] 1.14 [0.43, 3.00] 1.97 [0.33, 11.68]
45-49 1.26 [0.43, 3.64] 0.56 [0.17, 1.84] 2.15** [1.25, 3.70] 4.59*** [2.31, 9.12] 1.24 [0.45, 3.46] 2.26 [0.41, 12.56]
Residence
Urban (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
Rural 0.69 [0.32, 1.19] 0.4** [0.21, 0.76] 1.48* [1.02, 2.15] 0.84 [0.54, 1.30] 0.97 [0.56, 1.68] 0.76 [0.33, 1.73]
Marital status
Currently married or
living together (ref.)
1.0 1.0 1.0 1.0 1.0 1.0
Formerly married or
living together
6.8*** [3.93, 11.76] 18.4*** [8.39, 40.34] 3.79*** [2.75, 5.22] 6.14*** [4.25, 8.87] 6.47*** [4.28, 9.78] 8.39*** [4.13, 17.07]
Number of living children
0 1.0 1.0 1.0 1.0 1.0 1.0
1-2 1.56 [0.74, 3.26] 1.77 [0.63, 5.00] 0.94 [0.56, 1.59] 1.56 [0.84, 2.89] 0.91 [0.46, 1.78] 0.32* [0.11, 0.92]
3 and more 1.89 [0.87, 4.13] 1.78 [0.52, 6.09] 1.07 [0.60, 1.89] 1.79 [0.91, 3.52] 1.33 [0.54, 3.30] 0.58 [0.17, 1.98]
(continued)
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2546
Azerbaijan Moldova Ukraine
Physical or Sexual IPV Resulting in Physical InjuriesaPhysical or Sexual IPV Resulting in Physical InjuriesaPhysical or Sexual IPV Resulting in Physical Injuriesa
Less Severe Injuries More Severe Injuries Less Severe Injuries More Severe Injuries Less Severe Injuries More Severe Injuries
Variables Relative Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Socioeconomic status
Wealth status
Middle or high (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
Low/poor 2.14* [1.19, 3.85] 2.11* [1.19, 3.73] 1.07 [0.75, 1.52] 1.44 [0.98, 2.11] 1.24 [0.74, 2.08] 2.38* [1.12, 5.06]
Respondent’s education
Above secondary (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
Secondary or below
(11 years)
2.38** [1.31, 4.31] 1.31 [0.55, 3.13] 1.08 [0.80, 1.46] 1.78** [1.24, 2.56] 1.73* [1.11, 2.70] 1.39 [0.79, 2.44]
Respondent’s employment
Employed (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
Unemployed 0.87 [0.49, 1.54] 1.02 [0.44, 2.33] 1.08 [0.82, 1.41] 0.73 [0.53, 1.02] 0.88 [0.51, 1.54] 0.96 [0.45, 2.07]
Partner’s characteristics
Partner’s education
Above secondary (ref.) 1.0 1.0 1.0 1.0 1.0 1.0
Secondary or below
(11 years)
1.01 [0.53, 1.92] 1.65 [0.71, 3.81] 1.45* [1.03, 2.05] 1.53* [1.07, 2.20] 1.70* [1.05, 2.74] 1.32 [0.70, 2.48]
Partner’s occupation
Professional, technical,
or managerial (ref.)
1.0 1.0 1.0 1.0 1.0 1.0
Sales and services 1.91 [0.76, 4.79] 1.19 [0.42, 3.41] 1.13 [0.58, 2.20] 2.66 [0.98, 7.18] 0.57 [0.28, 1.16] 1.94 [0.62, 6.07]
Skilled and unskilled
manual
2.21* [1.02, 4.81] 1.0 [0.39, 2.52] 1.29 [0.75, 2.20] 3.46** [1.45, 8.26] 0.78 [0.40, 1.51] 3.74** [1.53, 9.14]
Agriculture 1.10 [0.41, 2.99] 1.64 [0.43, 6.35] 1.58 [0.85, 2.92] 5.11*** [1.99, 13.13] b b
(continued)
Table 6. (continued)
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2547
Azerbaijan Moldova Ukraine
Physical or Sexual IPV Resulting in Physical InjuriesaPhysical or Sexual IPV Resulting in Physical InjuriesaPhysical or Sexual IPV Resulting in Physical Injuriesa
Less Severe Injuries More Severe Injuries Less Severe Injuries More Severe Injuries Less Severe Injuries More Severe Injuries
Variables Relative Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Relative
Risk
95%
Confidence
Intervals
Did not work/no
occupation
2.98 [0.69, 12.77] 0.47 [0.08, 2.79] 2.23** [1.27, 3.91] 5.07*** [1.99, 12.94] b b
F2.37 8.80 9.63
Design df 301 398 444
Number of observations
(unweighted sample)
4,233 4,549 2,416
Population size (weighted
sample)
3,800 4,278 2,312
Note: Exponentiated coefficients; 95% confidence intervals in brackets.
aReference category: physical or sexual IPV without any physical injuries.
bCombined with “skilled and unskilled manual” category due to a small number of individuals involved in agriculture or without any occupation in Ukraine.
*p < .05. **p < .01. ***p < .001.
Table 6. (continued)
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2548 Journal of Interpersonal Violence 28(12)
Discussion
This is one of the first studies proving national prevalence data and sociode-
mographic correlates of physical, sexual, and injurious IPV by most recent
husband or cohabiting partner among ever-partnered women in the three fSU
countries (Azerbaijan, Moldova, and Ukraine). The prevalence of sexual IPV
was comparable across all three countries, whereas the prevalence of physi-
cal IPV and IPV resulting in severe physical injuries was almost twice as high
in Moldova compared to Azerbaijan and Ukraine.
According to the CDC RHS, another population-based study conducted in
the fSU region between 1997 and 2001, 15% of women in Moldova, 19% in
Ukraine, and 20% in Azerbaijan reported being physically abused by their
current or former partners at some point in their lives (CDC, 2003). The DHS
instrument collects data about IPV committed by the current or most recent
partner, while the RHS study also includes IPV from former partners. This
may potentially explain the lower prevalence of IPV reported in this article
for Ukraine and Azerbaijan compared to the RHS study. In Moldova, how-
ever, the IPV prevalence numbers from the DHS survey collected in 2005 are
substantially higher than the prevalence data collected in the RHS study in
1999 (24% vs. 15%, respectively; CDC, 2003). Although the official unem-
ployment rate has dropped since the late 1990s, economic recovery has been
minimal, making Moldova among the poorest countries in Europe (Hensel &
Gudim, 2004). Dismal economic situation and male unemployment may neg-
atively affect the family stress level and contribute to the higher prevalence
of IPV in the country. Future studies investigating the increase of IPV in
Moldova are warranted.
Although the RHS study used only one item to measure sexual IPV (“if a
partner ever physically forced the respondent to have sex against her will”),
the prevalence of lifetime sexual IPV by current or former partners was 10%
in Azerbaijan (CDC, 2003), higher than that found in this study. Sexual IPV
measure was not available in the earlier versions of RHS administered in
Moldova and Ukraine.
The study also demonstrated that a significant portion of women with a
history of IPV ever experienced severe forms of violence resulting in physi-
cal injuries. High proportion of reported IPV resulting in physical injuries
may also suggest women in these countries tend to disclose primarily severe
cases of abuse from their partners. Women may feel more justified to disclose
severe abuse causing physical harm.
The study also showed that IPV differed by a number of sociodemographic
characteristics. The prevalence of physical, sexual, and injurious IPV was
disproportionally higher among formerly married women. The differences
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Ismayilova and El-Bassel 2549
between formerly and currently married women were especially drastic in
their reports of severe IPV. Divorced or separated marital status is a common
demographic factor associated with IPV (Bensley, Macdonald, Van Eenwyk,
Simmons, & Ruggles, 2000; Ionita, 2012). Alternatively, the rates might be
higher because formerly married women may feel less constrained or threat-
ened to disclose incidents of abuse in their previous marriages compared to
women who still live with their abusers. In any case, divorced or separated
status might be rather viewed as a consequence of IPV and not as a risk factor
(Janssen et al., 2003).
The study demonstrated that the estimates of physical IPV in Ukraine and
injurious IPV in Moldova were higher among older groups of women.
Although the exposure time increases with age and can explain higher likeli-
hood of ever experiencing IPV among older women, no age differences were
observed in Azerbaijan. In Ukraine and Moldova antiviolence campaigns and
programs, particularly awareness programs targeting primarily the younger
population through educational institutions, have been in existence longer
than in Azerbaijan and have achieved more significant legislative and policy
changes (Amnesty International, 2006; Yunus et al., 2004).
Women with lower levels of educational attainment were at higher risk for
physical and/or injurious IPV in all three countries, and partner’s low level of
education was a significant risk factor for sexual IPV in Ukraine and Moldova.
Both women’s and partner’s education are commonly associated with IPV in
the literature (Ackerson, Kawachi, Barbeau, & Subramanian, 2008; Bates,
Schuler, Islam, & Islam, 2004). However, the World Mental Health survey in
Ukraine did not identify significant differences in current physical IPV by
woman’s or partner’s education (O’Leary et al., 2008). The WMH data were
collected in 2002 and included an older group of respondents (the mean age
of 46 years), the majority of whom grew up and were educated during the
Soviet times. The DHS study may capture a younger generation of women
who were educated and formed in post-Soviet years, when women’s organi-
zations were more active. In Azerbaijan, however, women were equally at
risk of sexual IPV regardless of partners’ level of education. This suggests the
importance of conducting prevention work in Azerbaijan among all groups of
men regardless of their level of education.
A substantial body of literature links IPV and poverty (Dal Grande et al.,
2003; Rivera-Rivera et al., 2004; Vest, Catlin, Chen, & Brownson, 2002).
Socioeconomic well-being as indicated by poor wealth status in Azerbaijan
and Ukraine and partners’ unemployment in Moldova and Ukraine were
mainly significant in relation to physical and injurious IPV. Economic hard-
ship, particularly low income and unemployment—coupled with a large
number of children, which reduces family’s limited resources—elevate stress
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2550 Journal of Interpersonal Violence 28(12)
level, diminish husband’s ability to cope, and facilitate the use of violence
(Cano & Vivian, 2001). Future studies should investigate factors that mediate
and explain the relationships between poverty, unemployment, and risk for
physical and injurious IPV in the fSU region. Income-generating programs
for men improving financial well-being of families could be useful in reduc-
ing the risk of physical IPV. Incorporating economic empowerment strategies
in violence prevention program could be particularly important in the context
of countries where men are the primary breadwinners in the family (e.g.,
Azerbaijan). Future studies should also include more partner-level variables,
especially to better understand predictors of sexual IPV.
This article utilized cross-sectional data to estimate the prevalence of IPV
and associated sociodemographic characteristics in selected fSU countries.
The findings should be interpreted with caution given the study limitations.
The data collection procedure, namely, an interviewer-administered survey,
poses constrains to honest disclosure of sensitive information, increases
social desirability bias, and may underestimate the reports of IPV, especially
sexual IPV (Ellsberg, Heise, Pena, Agurto, & Winkvist, 2001). Having inter-
views conducted in respondents’ homes could also affect the disclosure rates,
even though necessary arrangements were made to achieve privacy. Both
could be significant barriers, especially in Azerbaijan, a country with close
social networks, fear of disclosure of private information about family, and
importance of “saving the face” in the community. Underreporting of IPV
may result in weakening the relationship between IPV and other factors
(Pallitto & O’Campo, 2004). Given the difficulty of identifying and disclos-
ing family violence in this cultural environment, the prevalence numbers pro-
vided in this article should be treated as a crude underestimation of the actual
IPV in the region. Furthermore, the DHS sample is limited to women of
reproductive age, and the estimates reported in this article do not represent
the prevalence of IPV among women of all ages. The study does not allow us
to estimate the lifetime prevalence of IPV in these countries because the IPV
measure is limited to most recent husband or cohabitating partner and
excludes reports of IPV from previous marriages or dating relationships. The
measure of severity was limited to physical injuries only, and emotional harm
or impairments in other areas of functioning were not assessed. The measure
of frequency was available only for current IPV (in the past year) and, there-
fore, was not included in this article.
Regression models for sexual and injurious IPV had low frequencies for
some cells (e.g., partner’s occupation), which could reduce the power and
result in wide confidence intervals for these predictors. The DHS women’s
questionnaire included the measure of partner’s occupation but not the mea-
sure of partner’s current employment status. As reported by the DHS male
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Ismayilova and El-Bassel 2551
questionnaire, the actual percentage of current unemployment among men is
much higher in these countries (19% in Ukraine, 29% in Azerbaijan, 34% in
Moldova; NCPM & ORC Macro, 2006; SSC & Macro International, Inc.,
2008; UCSR et al., 2008). Nevertheless, the numbers in the current data set
still reflect more dismal economic situation in Moldova. Finally, the estimates
of IPV may not entirely represent national rates because respondents from
disputed regions of Azerbaijan and Moldova were not included in the DHS
survey. In a study conducted among refugees and IDPs (internationally dis-
placed persons) in Azerbaijan, 43% of married women reported experiencing
violence in their current relationships (IRC, 2004), which is considerably
higher compared to the national prevalence rate reported in this article.
Azerbaijan has about 1 million refugees and IDPs (52% of whom are women),
who for the past 20 years have been living in impoverished conditions (Council
of Europe, 2002), and their experiences may not be accounted for in this study.
The article provides empirical data that could be used by women’s organi-
zations and social service providers to raise public awareness about IPV in
the fSU region. Governments in the respective countries should be urged to
address the problem of IPV as women’s violent experiences are not isolated
incidents. The public in the fSU region predominately perceives IPV as a
private family issue and does not acknowledge it as a societal problem (ADB,
2006; UNDP, 2005). Prevalence data reported in the article illustrate the seri-
ousness of the problem and depict that women’s violent experiences affect a
significant number of women and often result in physical injuries. The find-
ings regarding sociodemographic correlates of IPV may contribute to the
body of knowledge necessary for the development of programs more appli-
cable to the context of transitional countries and targeting groups at higher
risk for IPV. Although the analysis was limited to three countries, the results
may be extrapolated to other countries in the fSU region with similar
characteristics.
A staggering difference in the reports of violence by marital status sug-
gests the importance of providing support services to women seeking divorce
due to IPV. Educational activities on prevention of IPV should begin at the
school level to capture men and women who do not go beyond secondary
education. Prevention programs should be developed at multiple levels to
target different age and socioeconomic groups at risk.
Acknowledgement
The authors would like to thank Isaac Henry Ergas’s family for supporting research in
Turkic and Central Asian studies. The Demographic and Health Surveys (DHS) have
been implemented with the join support of United States International Development
Agency (USAID), the United Nations Population Fund (UNFPA), the United Nations
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2552 Journal of Interpersonal Violence 28(12)
Children’s Fund (UNICEF), and National Ministries of Health in respective countries.
Special thanks to the women who participated in the DHS surveys.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research,
authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research,
authorship, and/or publication of this article: The article has been supported by the
Ergas Memorial Fellowship, awarded to the first author Leyla Ismayilova by the
Harriman Institute at Columbia University. It was awarded to the first author, Leyla
Ismayilova.
Notes
1. In Ukraine, women were not eligible for the Domestic Violence (DV) module
in households in which men were administered the DV module (one-half of all
selected households).
2. Hereafter married or cohabitating (living with a partner) will be used
interchangeably.
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Author Biographies
Leyla Ismayilova is an assistant professor at the University of Chicago, School of
Social Service Administration. She obtained her doctorate in clinical social work
from Columbia University in 2009. She received her master’s degree in social work
from Columbia University School of Social Work, with a concentration in advanced
clinical practice and was among the first Open Society Institute/Soros Foundation
fellows from the former Soviet Union at Columbia. She also holds master’s degree in
psychology from Baku State University, Azerbaijan. She was the founder and director
of the Center for Psychological Counseling in Azerbaijan, which provided counseling
services to women, children, and men impacted by violence and abuse.
Nabila El-Bassel is the Willma and Albert Musher professor at the Columbia
University School of Social Work (CUSSW). She is the director of the Social
Intervention Group (SIG) at CUSSW, a multidisciplinary research center that works
to develop and test effective intervention models to prevent co-occurring problems of
intimate partner violence, HIV, drug abuse, and trauma. She is also the Director of the
Columbia University Global Health Research Center of Central Asia (GHRCCA), a
multidisciplinary research center committed to advancing solutions to health and
social issues in Central Asia.
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... In our sample, older age, being married and having children were associated with less likelihood of reporting sexual violence compared to the other types of GBV. Our findings are consistent with previous reports of an inverse association between age and GBV in general, which peaks in late adolescence and early adulthood [32], and sexual violence in particular [33]. A study among ever-married women in Ukraine, found that women aged 24 and under were at the highest risk for intimate partner sexual violence and that having children was a protective factor [33]. ...
... Our findings are consistent with previous reports of an inverse association between age and GBV in general, which peaks in late adolescence and early adulthood [32], and sexual violence in particular [33]. A study among ever-married women in Ukraine, found that women aged 24 and under were at the highest risk for intimate partner sexual violence and that having children was a protective factor [33]. A novel finding from this study was that engaging in unpaid labor, such as elder and childcare, compared to being a professional, was associated with lower odds of reporting sexual violence compared to noncontact violence. ...
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... IPV is primarily the result of the patriarchal social structure that allows men to exert dominance and control over women (Dobash & Dobash, 1979). Patriarchal gender roles surrounding justification of domestic violence are most commonly associated with higher risks for IPV on an individual and community level (Ismayilova & El-Bassel, 2013). A systematic review undertaken by Vives-Cases, Gil-González, and Carrasco-Portiño (2009) reveal that male domination in the relationship is positively correlated with violence against females. ...
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... Studies conducted in Kano and Oyo States reported lower prevalences [40,51]. However, higher rates of physical violence were also reported in studies conducted in southwest Ethiopia, Tanzania, eastern Nigeria, Bangladesh, Ukraine, and Peru [45,[50][51][52][53][54]. Close to two-thirds of the study subjects opined that they received kicks on the abdomen, beating, and choking whereas a smaller proportion (17.8%) said pushing, shoving, pulling of hair, and slapping were the forms of physical violence that they experienced. ...
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... Studies conducted in Kano and Oyo States reported lower prevalences [40,51]. However, higher rates of physical violence were also reported in studies conducted in southwest Ethiopia, Tanzania, eastern Nigeria, Bangladesh, Ukraine, and Peru [45,[50][51][52][53][54]. Close to two-thirds of the study subjects opined that they received kicks on the abdomen, beating, and choking whereas a smaller proportion (17.8%) said pushing, shoving, pulling of hair, and slapping were the forms of physical violence that they experienced. ...
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Full-text available
Background. Violence against women perpetrated by an intimate partner is an important public health issue. In recent years, attention has focused also on intimate partner violence (IPV) during pregnancy due to its prevalence, adverse health consequences, and intervention potentials. Aim. To determine the knowledge, experiences, and factors influencing IPV, including the controlling behaviors of male partners of pregnant women attending an antenatal clinic (ANC) of a tertiary health facility in Sokoto. Materials and method. A descriptive cross-sectional study was conducted among 260 pregnant women attending ANC in a tertiary health facility in the Sokoto metropolis. They were selected using a systematic sampling technique, and a set of pretested questionnaire items was used for data collection. Data were analysed using IBM SPSS version 20. Results. The respondents’ ages ranged from 19 to 40 years with a mean of years, and up to 83.5% of them were in a monogamous setting. Three-quarters of them were Muslims mostly from urban areas (72.1%), and 36.4% had a university or HND degree. Majority of them responded correctly to questions on IPV; overall, up to 99.2% of them had good knowledge of IPV. About 33% of the respondents have experienced IPV while pregnant and up to 61.7% of them said they did nothing because of fear. Some of the controlling behaviors of male partners included always asking for permission before seeing friends and family members and also controlling their finances. Factors associated with IPV include tribe, place of residence, and partner consuming alcohol. Conclusion. Majority of the respondents had good knowledge of IPV with about one-third of them ever experiencing it. Respondent’s partners were mostly jealous and exhibited some form of controlling behaviors. Physical violence was the most prevalent form, and most of the victims did nothing about it. Government and women’s right groups should push for the implementation of tougher punitive measures against perpetrators of IPV. 1. Introduction Violence against women is a major public health and human rights concern, with intimate partner violence and sexual violence being among the most pervasive forms of violence against women [1]. Although women can be violent in relationships with men, the most common perpetrators of violence against women are male intimate partners or ex-partners [2]. Until recently, most governments have considered violence against women (particularly “domestic” violence by a husband or other intimate partner) to be a relatively minor social problem [3]. In recent times, however, violence against women is recognized as a global concern [3, 4]. Intimate partner violence (IPV) is defined as threatened, attempted, or completed physical or sexual violence or emotional abuse by a current or former intimate partner. It describes the physical, sexual, or psychological harm by a current or former intimate partner or spouse, and this type of violence can also occur among heterosexual or same-sex couples [4]. The World Health Organization (WHO) defines intimate partner violence as an act of coercion, physical abuse, or threat of violence in an intimate relationship [5]. According to WHO, IPV is the most common form of violence against women. Violence by an intimate partner is manifested by physical, sexual, or emotional abusive acts as well as controlling behaviors; although violence occurs in different forms and settings including the workplace, school, and community, violence at home by intimate partner violence is considered as the most prevalent form [6]. The act of physical violence includes slapping, kicking, pushing, and beating, as well as forced sexual intercourse and other forms of sexual coercion. Psychological abuse involves insults, belittling, constant humiliation, threats of harm, or controlling behaviors that consist of isolating a person from friends and families; monitoring their movements; and restricting access to financial resources, employment, education, or medical care [7]. Studies conducted in sub-Saharan African and Asian countries showed an IPV rate ranging from 28% in Madagascar, 74% in Ethiopia, and 57% in India to 87% in Jordan [8]. In a multicountry study conducted in 10 different countries, a rate ranging from 18.5 to 75.8% was reported; domestic violence by an intimate partner alone had a rate of 15.5 to 70.9%, while violence by nonpartners ranged between 5.1 and 64.6% [5]. In Nigeria, a study conducted in Lagos, Southwest Nigeria, on the prevalence and predictors of intimate partner violence exposure showed a one-year prevalence of 29%, with significant proportions reporting psychological (23%), physical (9%), and sexual (8%) abuse, while in Oyo, a study showed that there was a 31.1% prevalence of wife beating among women of reproductive age [9, 10]. In Northern Nigeria, studies conducted among pregnant women in Zaria and Jos showed 28% and 63.2% of the respondents, respectively, experienced some form of abuse [11, 12]. Intimate partner violence in pregnancy has been identified among the leading causes of maternal mortality in some developed countries like the United States and the United Kingdom [13]. Pregnancy-related IPV has been reported to be associated with high perinatal and neonatal mortality risk among exposed women compared to unexposed pregnant women [14]. Neonatal complications include intrauterine growth retardation, preterm delivery, and low birth weight with extended intensive hospitalization [15–19]. Maternal consequences associated with IPV during pregnancy include abortions, miscarriages, preeclampsia, gestational diabetes, and placental abruption [20]. Although the prevalence of IPV is quite high in Nigeria, far fewer cases are reported. This is probably because of the influence of religion and culture especially in many parts of Africa, where culture may allow couples to solve their problem by the use of violence, since most cases of violence against an intimate partner are not seen as wrong. Nigeria still remains patriarchal in nature, where men are regarded as “gods” of the household, controlling every affair, including the women’s right to reproductive capabilities [21]. Incidents are therefore, underreported because doing so is viewed as causing indignity to the husband and being disrespectful of family members and elders whose roles include arbitrating in such matters. As a result of this, the true magnitude of the problem is relatively unknown and unexamined [22–24]. Despite increasing research on the prevalence and health effects of IPV during pregnancy from numerous countries around the globe, several gaps in knowledge still exist especially in low- and middle-income countries including Nigeria [25]. Though several studies have been conducted on IPV globally, in Nigeria there is still dearth of information on IPV; most of the studies conducted looked at IPV among women generally, but not much studies had been carried out among pregnant women in Sokoto State despite its effect on the health of the mothers and their babies. Systematic reviews were conducted on domestic violence, which included studies done in different parts of the world; however, studies among pregnant women were not included in the review. The findings showed that relatively few studies and publications emerged from Africa compared to North America and Europe [26]. Furthermore, there are differences in cultural and religious patterns in the different zones in the country; even in the northern part of the country, there are differences in what people regard as IPV [27]. This study, therefore, is aimed at examining the knowledge of IPV, controlling behaviors of male partners, and experiences of intimate partner violence among women attending an antenatal clinic at the Usmanu Danfodiyo University Teaching Hospital, Sokoto. 2. Materials and Method The study was conducted at the Usmanu Danfodiyo University Teaching Hospital (UDUTH), Sokoto between June and August, 2018. Being a tertiary institution, the hospital provides specialized health care service to Sokoto State, the entire northwestern region of the country, and the neighboring Niger Republic. With a bed capacity of 850, UDUTH has staff strengths of over 1705, which includes doctors, nurses, pharmacists, medical laboratory scientists, and physiotherapists spread across all departments providing curative, preventive, and rehabilitative services. Antenatal clinic service is provided on all the weekdays with an average daily attendance of 250 pregnant women. The study employed a descriptive cross-sectional study design, and all pregnant women presenting at the ANC clinic for booking or routine antenatal care and must have had a previous pregnancy (inclusion criteria) constituted the study population. Respondents were recruited into the study using the formula for estimating sample size in a population less than 10,000 [28]. After adjusting for a nonresponse rate of 10%, a total of 260 respondents were recruited into the study. A systematic sampling technique was used to select the study participants after calculating the sampling interval as follows: Based on the above sampling interval, the systematic sampling technique was carried out as follows: (i)The first participant was selected using simple random sampling carried out among the first three pregnant women that came for booking(ii)Thereafter, every third pregnant woman that came to the ANC clinic for booking was enrolled in the study until the required sample size was obtained. This was continued every day until the desired sample size was obtained A set of pretested semistructured interviewer-administered questionnaire items was administered on the respondents which sought information on respondents’ sociodemographic characteristics, their knowledge of IPV, the controlling behavior of partners during pregnancy, the experiences of respondents, and factors influencing IPV during pregnancy. Data collection using the instrument described above was done with the help of three medical students who were trained by the researchers on the objectives of the study, general principles of research ethics, interpersonal communication, and techniques of data collection. The data from the questionnaire was manually checked for completeness and entered into IBM SPSS version 20 for electronic data cleaning and analysis. Each correct response to a knowledge variable was awarded a score of one mark, and a zero mark was awarded to each incorrect response. The knowledge scores were added up, converted to percentage, and graded as either good knowledge (score of ≥50%) or poor knowledge (<50%). Continuous variables were summarized as mean and standard deviation, and categorical variables were summarized and presented as frequencies and percentages. This was followed by inferential statistics (bivariate analysis), which were used to identify the major determinants of IPV during pregnancy. The level of statistical significance was set at 5% (). Permission for the study was obtained from the ethics and research committee of UDUTH. Participants were informed of the objectives of the study and were assured of the confidentiality of the information volunteered. Informed verbal consent was also obtained from all the respondents. 3. Results The respondents’ ages ranged from 19 to 40 years with a mean age of years, and up to 83.5% of them were in a monogamous setting. Up to three-quarters of them were Muslims mostly from urban areas (190 (72.1%)), and 92 (36.4%) had a university or HND and 96 (36.9%) belonged to the upper socioeconomic class (SEC); for their partners, 170 (65.4%) were in the upper SEC (Table 1). Variables Frequency (%) Age group (years) <20 13 (5.0) 20-29 123 (47.3) 30-39 122 (46.9) 40-49 2 (0.8) Mean Marital status Married 259 (99.6) Widowed 1 (0.4) Type of marriage Monogamous 217 (83.5) Polygamous 43 (16.5) Religion Islam 198 (76.2) Christianity 61 (23.5) Others 1 (0.4) Tribe Hausa 169 (65.0) Yoruba 50 (19.2) Igbo 21 (8.1) Fulani 20 (7.7) Place of residence Urban 190 (72.1) Rural 70 (26.9) Level of education of wife University/HND graduate 92 (36.4) Diploma/NCE/SSCE 34 (13.1) Completed primary school/JSS 47 (18.1) Primary school not completed/ 13 (5.0) Qur’anic school only/none 74 (28.5) Level of education of husband or partner University/HND graduate 140 (53.8) Diploma/NCE/SSCE 55 (21.2) Completed primary school/JSS 49 (18.8) Primary school not completed/ 6 (2.3) Qur’anic school only/none 10 (3.8) Occupation of wife Senior civil servant/professional/manager/contractor/large scale business 63 (24.2) Intermediate school civil servant/secondary school teacher 14 (5.4) Junior secondary school teacher/driver/artisan 53 (20.4) Petty trader/labourer/messenger 12 (4.6) Subsistent farmer/student/full-term house wife 118 (45.4) Occupation of husband/partner Senior civil servant/professional/manager/contractor/large scale business 133 (51.5) Intermediate school civil servant/secondary school teacher 39 (15) Junior secondary school teacher/driver/artisan 42 (16.2) Petty trader/labourer/messenger 38 (14.6) Subsistent farmer/student/full-term house wife 7 (2.7) Wife’s SEC Upper class 96 (36.9) Middle class 41 (15.8) Lower class 123 (47.3) Husband/partner’s SEC Upper class 170 (65.4) Middle class 53 (20.4) Lower class 37 (14.2)
Chapter
In the former socialist countries, a painful ideological and economic transition from socialist state economies to liberal multi-party systems and a free market economy began in 1989–1991. In the course of this process, the re-emergence of religion and other conservative ideologies went hand in hand with the temporary retraditionalisation of gender relations and of femininities and masculinities. This chapter analyses some important components of retraditionalisation that have evolved over the past quarter of a century. The first part sketches patriarchal landscapes by drawing on qualitative and quantitative comparisons of gender relations within the region and on a global scale. This will be followed by the examination of dominant gender ideologies, discourses, and stereotypical femininities and masculinities in the second section. In this context, new and alarming developments have come into being, such as gender-biased abortion in some regions. Such occurrences, as well as the generally very precarious relationship between the heterosexual mainstream and lesbian, gay, and transgender members of society, can be interpreted as a consequence of vigorous patriarchal gender ideologies.
Article
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Book
This book is concerned with statistical methods for the analysis of data collected from a survey. A survey could consist of data collected from a questionnaire or from measurements, such as those taken as part of a quality control process. Concerned with the statistical methods for the analysis of sample survey data, this book will update and extend the successful book edited by Skinner, Holt and Smith on 'Analysis of Complex Surveys'. The focus will be on methodological issues, which arise when applying statistical methods to sample survey data and will discuss in detail the impact of complex sampling schemes. Further issues, such as how to deal with missing data and measurement of error will also be critically discussed. There have significant improvements in statistical software which implement complex sampling schemes (eg SUDAAN, STATA, WESVAR, PC CARP ) in the last decade and there is greater need for practical advice for those analysing survey data. To ensure a broad audience, the statistical theory will be made accessible through the use of practical examples. This book will be accessible to a broad audience of statisticians but will primarily be of interest to practitioners analysing survey data. Increased awareness by social scientists of the variety of powerful statistical methods will make this book a useful reference.
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We explore the determinants of domestic violence in two rural areas of Bangladesh. We found increased education, higher socioeconomic status, non-Muslim religion, and extended family residence to be associated with lower risks of violence. The effects of women status on violence was found to be highly context-specific. In the more culturally conservative area, higher individual-level women autonomy and short-term membership in savings and credit groups were both associated with significantly elevated risks of violence, and community-level variables were unrelated to violence. In the less culturally conservative area, in contrast, individual-level women status indicators were unrelated to the risk of violence, and community-level measures of women status were associated with significantly lower risks of violence, presumably by reinforcing nascent normative changes in gender relations.
Article
This book is concerned with statistical methods for the analysis of data collected from a survey. A survey could consist of data collected from a questionnaire or from measurements, such as those taken as part of a quality control process. Concerned with the statistical methods for the analysis of sample survey data, this book will update and extend the successful book edited by Skinner, Holt and Smith on 'Analysis of Complex Surveys'. The focus will be on methodological issues, which arise when applying statistical methods to sample survey data and will discuss in detail the impact of complex sampling schemes. Further issues, such as how to deal with missing data and measurement of error will also be critically discussed. There have significant improvements in statistical software which implement complex sampling schemes (eg SUDAAN, STATA, WESVAR, PC CARP ) in the last decade and there is greater need for practical advice for those analysing survey data. To ensure a broad audience, the statistical theory will be made accessible through the use of practical examples. This book will be accessible to a broad audience of statisticians but will primarily be of interest to practitioners analysing survey data. Increased awareness by social scientists of the variety of powerful statistical methods will make this book a useful reference.
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This paper focuses on the intersection of gender, state socialism, nationality, and religion in the newly independent republic of Azerbaijan. It demonstrates that although Muslim Azeri women have accomplished an impressive level of emancipation, their overall status remains flawed with contradictions and duality. Similar to women of several other countries in the Muslim world confronting colonial domination or semicolonial intrusion, Azeri women's liberation has been held hostage to their assigned responsibility as the primary repositories of tradition, and ethnic and national identity. At the end, the gender dynamics of recent changes and the new search for national identity in the ethnically contested and war-stricken context of post-Soviet Azerbaijan is briefly explored.
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This paper focuses on the intersection of gender, state socialism, nationality, and religion in the newly independent republic of Azerbaijan. It demonstrates that although Muslim Azeri women have accomplished an impressive level of emancipation, their overall status remains flawed with contradictions and duality. Similar to women of several other countries in the Muslim world confronting colonial domination or semicolonial intrusion, Azeri women's liberation has been held hostage to their assigned responsibility as the primary repositories of tradition, and ethnic and national identity. At the end, the gender dynamics of recent changes and the new search for national identity in the ethnically contested and war-stricken context of post-Soviet Azerbaijan is briefly explored.