Income,Gender,and Forms of Intimate Partner Violence

Abstract

Poverty and socioeconomic disadvantage place demands on intimate relationships and provide fertile ground for disagreements and conflicts. It is not known whether poverty also leads to intimate partner violence (IPV). This study investigates the association between income and forms of IPV victimization for both males and females. We also examine whether income inequalities are related to IPV and whether the gender balance of household income contributes to IPV victimization. Data are from a cohort of 2,401 young offspring (60.3% females) who participated at the 30-year follow-up of the Mater-University of Queensland Study of Pregnancy in Brisbane, Australia. Participants completed questionnaires including their income details and the Composite Abuse Scale. Within low-income families, both partners experience higher levels of IPV. Females’ income is not independently related to experiencing IPV either for females or males. Females and males experience a higher rate of IPV when the husband earns a low income. When considering partners’ relative income, families in which both partners earned a low income experienced higher levels of almost all forms of IPV. Income (im)balance in which females earn more or partners both have higher income was less often associated with the experience OF IPV IPV appears to be mutually experienced in the setting of the poverty. Objective economic hardship and scarcity create a context which facilitates IPV for both partners in a relationship.

Keywords

income intimate partner violence victimization gender a birth cohort study

Introduction

While intimate partner violence (IPV) is a globally widespread public health concern (Campbell et al., 2002; Devries et al., 2013; Garcia-Moreno, Jansen, Ellsberg, Heise, & Watts, 2006; Krug, Mercy, Dahlberg, & Zwi, 2002), there is relatively little research about its characteristics or causes. Understanding the context in which IPV is experienced, should contribute to more informed policy responses (Jewkes, 2002). IPV cannot be understood in isolation; it is associated with a wide range of biological and psychological characteristics as well as social, environmental, and economic factors (Abramsky et al., 2011; Capaldi, Knoble, Shortt, & Kim, 2012; Djikanovic, Jansen, & Otasevic, 2010; Jewkes, 2002; Walton-Moss, Manganello, Frye, & Campbell, 2005). Contrary to popular belief that IPV may occur in all socioeconomic settings, a body of research has established a robust link between the poverty, low socioeconomic status (SES), disadvantage circumstances, and IPV perpetration and victimization (Fox, Benson, DeMaris, & Van Wyk, 2002; Goodman, Smyth, Borges, & Singer, 2009; Kishor & Johnson, 2006; Sutherland, Sullivan, & Bybee, 2001).

Poverty, as argued by Family Stress Theory (Conger, Ge, Elder, Lorenz, & Simons, 1994), causes IPV because it involves socioeconomic strains and financial insecurity which contributes to frustration and powerlessness and encourages men to display violent behaviors against women (Cano & Vivian, 2001; Fox et al., 2002; Jewkes, 2002). It is also possible that poverty-related IPV may affect both partners in a marital relationship. Within a dysfunctional family system, affected by economic distress, poverty might be both a cause and consequence of IPV (Goodman et al., 2009).

While there is some evidence that low-income families are more likely to engage in IPV, relatively little has been written about the separate role of husband’s and wife’s income as these might be related to IPV (Kaukinen, 2004). Existing theoretical models and the findings related to these models, which link gender, economic issues, and domestic violence, are not consistent (Vyas & Watts, 2009). Feminist scholars (Dobash & Dobash, 1979; Hester, Kelly, & Radford, 1996; Yodanis, 2004) emphasize IPV as a “gendered problem” emerging from the domination and control of women by men. They propose women’s status empowerment and gender equality as solutions to IPV (Corvo & Johnson, 2003). Dependency theory highlights females’ dependency reflecting lower resources or the competition for resources as the root of violence against women. Women who are economically independent and have higher status in their relations may be able to negotiate more effectively and not stay in abusive relationships (Golden, Perreira, & Durrance, 2013; Hornung, McCullough, & Sugimoto, 1981; Kalmuss & Straus, 1982; Tauchen & Witte, 1995). Conversely, from the Social Exchange and Resource Theory perspective, partners use resources, like violence or income, to achieve more power in their relationships. In a situation where there is a lack of socioeconomic resources, violence can be used and exchanged. As a result, it might be that higher economic resources place women at greater risk of IPV (Allen & Straus, 1980; Goode, 1971). In the context of societies which are largely patriarchal, Relative Resource Theory suggests that women with higher relative status constitute a challenge to established male dominance and are more vulnerable to abuse (Macmillan & Gartner, 1999; McCloskey, 1996).

Gendered Resources Theory, in contrast, argues that Relative Resource Theory ignores the cultural context under which masculinity is constructed and assumes that all males desire to be the main provider, whereas females’ higher resource increases the risk of IPV only if the male partner holds less egalitarian gender views (Atkinson, Greenstein, & Lang, 2005). Despite Australia historically having been characterized as a predominantly male-breadwinner culture (Baxter & Hewitt, 2013; van Egmond, Baxter, Buchler, & Western, 2010), over the most recent decades, women’s labor force participation rates and the proportion of women with a bachelor’s degree have increased to 58% and 25%, respectively. Egalitarian gender beliefs about work and family roles have become more common, and couples with similar SES or dual-earner families have emerged to be increasingly common (de Vaus, 2004). Perhaps as a consequence of these social and economic changes, IPV in Australia may have particular characteristics. For instance, recent evidence suggests a growing rate of males’ IPV victimization (Australian Bureau of Statistics, 2012; People, 2005).

While feminist theory focuses more on female victimization (Corvo & Johnson, 2003; Dobash & Dobash, 1979; Hester et al., 1996; Yodanis, 2004), a family violence perspective suggests that both men and women engage in domestic violence (Capaldi, Kim, & Shortt, 2007; Dutton, Nicholls, & Spidel, 2005; Fergusson, Horwood, & Ridder, 2005; Langhinrichsen-Rohling, 2010; Ross & Babcock, 2010; Straus, 2008; Straus & Ramirez, 2007). Based on the typology of Johnson (1995), IPV encompasses both severe and unidirectional forms of violence (as feminist scholars indicate) and minor and/or reciprocal violent behaviors (as family violence theory suggests). However, few studies have included different types of IPV (Hegarty & Valpied, 2007; Krebs, Breiding, Browne, & Warner, 2011; Salom, Williams, Najman, & Alati, 2015). Economic factors might have different effects on different types of IPV. In one study, for instance, a clear association was found between husband’s low SES and female’s higher risk of physical abuse, but not psychological abuse (Vung, Ostergren, & Krantz, 2008).

Furthermore, previous measurements of IPV have been criticized because they have provided inconsistent, biased, and limited information. For example, the Conflict Tactics Scale (Straus, 1979) is the most widely used measure of IPV; however, it has been suggested that it lacks cultural validity, concentrates mostly on physical abuse, and does not comprise a comprehensive assessment of emotional, economic, and sexual abuse (DeKeseredy, 2000; Kimmel, 2002). Hence, there is a need to use a validated and multidimensional measure that reflects the full range of types of IPV.

Another concern is that the most influential studies in the field have involved clinical and selective samples (Dutton, Hamel, & Aaronson, 2010; Langhinrichsen-Rohling, 2010). Controversies about rates of IPV highlight the importance of the type of sample from which the data are gathered. For example, rates of male violence tend to be much higher when the findings come from a nonrepresentative population like physically abused women (Langhinrichsen-Rohling, 2010). Using a large population-based sample comprising men and women can bridge the existing gap in our comprehension of IPV.

Current Study

Different and inconsistent theoretical perspectives in the field make it hard to anticipate how partners’ income matters in a relation to IPV. It is simply not known whether wife’s income affects the risk of IPV, not only for females but also for the male partner. In addition, income may range from low to high; it is unclear whether equality or inequality at all income levels might be related to risk of IPV. This study involves the analysis of survey data, which examines the association between income (personal income, family income, and balance in contribution to family income) and IPV for both males and females. It investigates the relationship between family income and different types of IPV, namely, whether wife’s income influences IPV for both partners and whether income (im)balance between wife and husband might be important in relation to IPV.

Method

Participants

Data for the current study were taken from the Mater-University of Queensland Study of Pregnancy (MUSP). Baseline data were collected at the first antenatal visit to the Mater Public Hospital in Brisbane between 1981 and 1983 from 7,223 consecutive women, and additional assessments were conducted when the study children were 6 months, 5 years, 14 years, 21 years, and 30 years. The Mater Hospital and the University of Queensland Ethics committees approved this study, and written informed consent was obtained from the young adults. The study design and sampling method have been previously discussed (Keeping et al., 1989; Najman et al., 2005). The present analysis used data from the 30-year follow-up surveys with 40% of the cohort participating in that phase of the study. While recruitment to the study included some 99% of those invited to participate, losses to follow up (i.e., the 30-year follow-up), are disproportionately of young, single, separated/divorced, economically disadvantaged and more emotionally distressed participants (Najman et al., 2015). In practice and based on several previously published papers, results of weighted analyses and multiple imputation suggest that loss to follow up rarely has an impact on findings (Najman et al., 2015; Ware, Williams, & Aird, 2006). The participants at the 30-year follow-up were a subsample of 2,401 heterosexual persons (952 males and 1,449 females) who completed self-report questionnaires about IPV and economic factors.

Measures

Dependent Variable: IPV

Based on criteria used by the World Health Organization (WHO), IPV is defined as “behaviour by an intimate partner or ex-partner that causes physical, sexual or psychological harm, including physical aggression, sexual coercion, psychological abuse and controlling behaviours” (WHO, 2012, p. 1. We measured IPV at 30 years using the Composite Abuse Scale (CAS; Hegarty, Bush, & Sheehan, 2005; Hegarty & Valpied, 2007). The CAS is a validated and widely used scale (Loxton, P1owers, Fitzgerald, Forder, Anderson et al., 2013; Lokhmatkina, Kuznetsova, & Feder, 2010; Rietveld, Lagro-Janssen, Vierhout, & Wong, 2010) to assess frequency of violence in intimate relationships (current or previous relationships) in a 12-month period. The scale comprises 30 items (α = .95) and four subscales: Severe Combined Abuse (α = .79; comprises eight items which include rape, keep from obtaining medical care, locked in the bedroom), Emotional Abuse (α = .90; comprises 11 items which include insults, verbal, psychological, dominance, and separation from friends and family), Physical Abuse (α = .89; comprises seven items which include slapping, throwing, hitting, shaking), and Harassment (α = .72; comprises four items which include actual harassment like following, harassing over the telephone and at work). Response options ranged from never, only once, several times, once a month, once a week, and daily, which were scored from 0 (never) to 5 (daily). Total scores for each of the four subscales were calculated by summing the response to the relevant items. Then the recommended cutoff scores for the individual subscales—Severe Combined Abuse (≥1), Physical Abuse (≥1), Emotional Abuse (≥3), and Harassment (≥2) and Total Scale (≥3)—were applied. Participants with equal or higher scores than the cutoff score were considered to have experienced abuse (Hegarty & Valpied, 2007).

Independent Variables

Absolute personal income

All the 30-year follow-up respondents were asked to choose their own and their partners’ income from 11 categories (no income to Aus$3,000 or more per week) separately. Income was defined as gross income before tax and other deductions; including wages, pensions, government payments and income from other sources such as investments. Own and partner absolute income were separately categorized into three categories: low (income under $600 per week), middle ($600-$1,300 per week), and high (more than $1,300). Respondents who had no partner were excluded from further analysis.

Family income

Using the midrange of own and partner’s income categories and adding them, we created a weekly family income variable with five categories: $0 to $999; $1,000 to $1,499; $1,500 to $1,999; $2,000 to $2,499; and $2,500 and more.

Gender (im)balance in income

We combined respondents’ income with their partners’. Calculated variable comprised nine states (three own states × three partner states). Then we categorized them into three main groups of “husband (male) earns more,” “wife (female) earns more,” and “balanced.” Balance earning itself was classified into three groups of “both [partners] earn low,” “both earn middle,” and “both earn high.” This category is different from Kaukinen’s (2004) income incompatibility measurement, which ignores different levels of income parity. Husband’s higher income is the reference group for analysis.

Demographic Variables and Covariates

We adjusted for a number of demographic variables that may be related to both income and IPV. Evidence shows that both income and IPV are related to covariates like age, marital status, length of relationship, or education level. For example, partners with a lesser education level, those who are cohabitating, and couples with children are more likely to report financial problems as well as violence in their intimate relationships (Capaldi et al., 2012; McDonald, Jouriles, Ramisetty-Mikler, Caetano, & Green, 2006; Peisch et al., 2016).

All respondents are around 30 years of age, so there is no adjustment for age variation in the sample. We control for respondents’ and their partners’ education level categorized into high school completion or less (primary, started secondary, completed secondary), diploma and college, and university (reference category). Having had children was dichotomized into no and yes. Marital status was created from three questions of “What is your present marital status?” “Have you ever been divorced?” and “Do you live with your partner?” Removing single ever and single now, before in relation respondents, this variable comprised two categories, living together and married. The married group was considered as the references group. Length of relationship was asked with a question, “For how long has your current live-in relationship lasted (in years)?”

Data Analysis

The prevalence of each type of IPV was determined across the gender groups. For describing demographic characteristics, descriptive statistics, chi-square, and t test were used. IPV forms (Physical Abuse, Emotional abuse, Severe Combined, and Harassment) were not mutually exclusive. For each form of IPV, the bivariate relationship with own, partner, and family income and gender income differences was modeled using logistic regression. Each of these models was then adjusted for respondent’s education, marital status, duration of relation, and having children. Unadjusted and adjusted odds ratios (ORs) with 95% confidence intervals (95% CIs) are reported. We also assessed interactions between family income and gender differences in income. Statistical analyses were conducted using STATA-13 and SPSS-24 softwares.

Results

Although this cohort of males and females are that the same average age (male = 30.39; female = 30.25), the sociodemographic characteristics of respondents are different in a number of important respects (Table 1). At 30 years of age, women are more likely to be married (men are more often single), and to report they have had a child and a university degree (even men more often reported their partners had higher degrees). Female are more likely to have low income, but males and females understandably report a similar family income. Level of IPV appeared similar for male and female respondents, with one exception. Males reported experiencing physical abuse more often than females. Bivariate associations between covariates and different forms of IPV are presented in Appendices A and B.

Table 1.

Gender Differences in Study Variables at 30-Year Follow-Up.

Variables	Male (%)	Female (%)	χ²
Marital status	n = 975	n = 1,463	27.75**
Married	41.1	48.3
Living together	26.4	26.5
Single now, before in relation	12.5	12.7
Single ever	20.0	12.5
Having children	n = 968	n = 1,454	53.55**
No	59.6	44.4
Yes	40.4	55.6
Own’s education	n = 986	n = 1,472	20.91**
University	22.9	31.1
Diploma and college	41.3	38.7
High School and less	35.8	30.2
Partner’s education	n = 743	n = 1,193	52.24**
University	39.0	24.9
Diploma and college	27.5	40.5
Under diploma	33.5	36.6
Own absolute income (per week)	n = 985	n = 1,461	269.47**
Low (>$600)	12.3	39.4
Middle (between $600 and $1,300)	43.5	39.0
High (<$1,300)	44.3	21.6
Partner’s absolute income (per week)	n = 708	n = 1,168	259.85**
Low (>$600)	41.0	11.0
Middle (between $600 and $1,300)	39.7	44.3
High (<$1,300)	19.4	44.6
Family income (per week)	n = 955	n = 1,449	2.10
$0-$999	18.6	20.2
$1,000-$1,499	22.5	21.5
$1,500-$1,999	18.0	17.2
$2,000-$2,499	15.3	14.3
$2,500+	25.5	26.8
Gender (im)balance in income	n = 708	n = 1,161	22.61**
Both earn low	3.7	6.6
Both earn middle	19.5	20.4
Both earn high	15.5	14.8
Wife earns more	6.2	10.8
Husband earns more	55.1	47.4
IPV victimization	n = 952	n = 1,449
Severe combined (≥1)	3.0	4.5	3.17
Physical abuse (≥1)	12.6	9.7	4.90*
Emotional abuse (≥3)	17.4	16.3	0.54
Harassment (≥2)	8.2	7.0	1.10
Total (≥3)	10.1	10.3	0.03
	M (SD)		t test
Length of relationship (range = 0-17years)	4.67 (4.2)	5.85 (4.5)	6.33**

Note. IPV = intimate partner violence.

p < .01. **p < .001.

Table 2 presents the association between total family income and gender differences in experiences of IPV. Lower family income is associated with severe combined IPV as well as physical and emotional abuse for females and severe combined victimization and harassment for males. While the specific details may vary, IPV tends to be experienced by both partners in low-income families.

Table 2.

Gender Differences in Association Between Family Income and IPV Victimization (OR With 95% CI; Ref. = $2,500+).

	SC		PA		EA		H
Family income	Female	Male	Female	Male	Female	Male	Female	Male
$0-$999	16.62 [2.06, 134.36] ^a	10.74 [1.11, 103.58] ^a	2.74 [1.16, 6.48]	1.02 [0.37, 2.82]	2.13 [1.09, 4.14]	1.30 [0.55, 3.02]	1.08 [0.32, 3.68]	5.38 [1.50, 19.19]
$1,000-$1,499			1.94 [0.90, 4.19]	0.74 [0.34, 1.62]	2.0 [1.15, 3.46]	1.18 [0.63, 2.20]	0.72 [0.23, 2.22]	3.47 [1.14, 10.53]
$1,500-$1,999	3.77 [0.33, 42.84]	3.76 [0.32, 44.38]	0.93 [0.38, 2.25]	0.89 [0.44, 1.82]	1.29 [0.72, 2.30]	0.61 [0.31, 1.19]	0.34 [0.09, 1.36]	0.78 [0.18, 3.36]
$2,000-$2,499	2.13 [0.13, 34.60]	1.87 [0.11, 31.16]	1.63 [0.72, 3.73]	0.60 [0.27, 1.33]	1.59 [0.89, 2.84]	0.53 [0.27, 1.05]	0.60 [0.15, 2.36]	1.82 [0.58, 5.75]
$2,500+	1	1	1	1	1	1	1	1

Note. Each form of IPV is modeled separately for males and females who currently are in relationship. ORs in bold are significantly different to those of the reference category (p < .05). Model includes ORs (95% CI) adjusted for own and partner education, marital status, length of relationship, and having child. IPV = intimate partner violence; OR = odds ratio; CI = confidence interval; SC = severe combined; PA = physical abuse; EA = emotional abuse; H = harassment.

Due to insufficient sample size, only for SC, two first categories were merged.

Table 3 presents the association between husband’s and wife’s income and IPV after adjusting for sociodemographic variables. Females whose partners (husbands) earn a low income are at greater risk of most forms of IPV with the exception of harassment. Males whose income is low are more likely to report IPV victimization except physical abuse. The income level of women (wives) in contrast to their partners’ income appears unrelated to the level of IPV experienced by women or men in this study. These associations are presented graphically in Appendices C and D. Table 3 also shows that couples who earn equally low income (compared with higher husband’s income) are at greater risk of IPV. Both male and female respondents in families in which both partners have a low income are at substantially increased risk of almost all forms of IPV.

Table 3.

Summary of Logistic Regression Analysis for Wife and Husband’s Absolute and Gender (Im)Balance Income Predicting IPV Victimization (OR With 95% CI).

	SC		PA		EA–		H
	Female	Male	Female	Male	Female	Male	Female	Male
Model 1: Absolute income^a
Husband’s income
Low	7.60 [1.37, 42.11]	4.68 [1.07, 20.44]	2.77 [1.32, 5.82]	1.67 [0.66, 4.26]	2.12 [1.22, 3.68]	2.60 [1.17, 5.81]	2.17 [0.72, 6.57]	8.25 [2.50, 27.25]
Middle	5.23 [1.12, 24.41]	0.71 [0.19, 2.65]	1.42 [0.78, 2.60]	0.77 [0.43, 1.35]	1.13 [0.74, 1.71]	1.13 [0.71, 1.82]	1.04 [0.41, 2.61]	3.22 [1.29, 7.99]
High	1	1	1	1	1	1	1	1
Wife’s income
Low	2.0 [0.38, 10.54]	1.36 [0.39, 2.65]	1.71 [0.72, 4.10]	0.79 [0.35, 1.78]	1.70 [0.94, 3.05]	0.77 [0.38, 1.56]	0.63 [0.18, 2.21]	0.65 [0.20, 2.15]
Middle	1.06 [0.19, 5.83]	1^b	1.47 [0.62, 3.48]	0.69 [0.32, 1.47]	1.39 [0.79, 2.46]	0.81 [0.43, 1.54]	0.95 [0.27, 3.29]	0.37 [0.12, 1.71]
High	1	1^b	1	1	1	1	1	1
Model 2: Gender (im)balance in income
Both earn low	3.46 [1.0, 12.51]	5.59 [1.08, 28.93]	3.20 [1.52, 6.80]	2.36 [0.80, 6.99]	2.32 [1.26, 4.29]	3.26 [1.24, 8.58]	2.52 [0.83, 7.60]	6.77 [1.98, 23.14]
Both earn middle	1.38 [0.39, 4.89]	0.46 [0.5, 3.93]	1.37 [0.69, 2.72]	0.89 [0.43, 1.87]	1.16 [0.71, 1.90]	1.24 [0.69, 2.25]	0.96 [0.30, 3.08]	1.90 [0.72, 4.98]
Both earn high	1.03 [0.19, 5.47]	—	0.90 [0.35, 2.33]	1.24 [0.54, 2.86]	0.84 [0.45, 1.58]	1.12 [0.55, 2.28]	1.69 [0.55, 6.47]	1.79 [0.45, 6.60]
Wife earns more	0.69 [0.08, 5.98]	1.02 [0.11, 9.64)	0.95 [0.34, 2.61]	1.24 [0.44, 3.49]	0.80 [0.40, 1.61]	1.98 [0.87, 4.50]	1.20 [0.25, 5.72]	3.25 [0.92, 11.40]
Husband earns more	1	1	1	1	1	1	1	1

Note. Each form of IPV is modeled separately for males and females. ORs in bold are significantly different to those of the reference category (p < .05). Models include ORs (95% CI) adjusted for own and partner education, marital status, length of relationship, and having child. IPV = intimate partner violence; OR = odds ratio; CI = confidence interval; SC = severe combined; PA = physical abuse; EA = emotional abuse; H = harassment.

In Model 1, husband’s and wife’s income were adjusted for each other.

Due to insufficient sample size, high income and middle income were merged and considered as the reference group.

Discussion

Previous studies have suggested that females are disproportionally the victims of IPV, that family poverty may predict and be a cause of IPV, and that income disparities between partners may contribute to IPV. First, we find that levels of IPV as reported by male and female respondents are similar. This raises the possibility that IPV is characteristic of a relationship and that IPV may be bidirectional. Surprisingly, males report experiencing physical abuse more often than females. Second, we find that low household income is associated with an increased risk of IPV for both females and males. Females in low-income families are at higher risk of physical abuse, emotional abuse, and severe combined abuse. Within a low SES family, males are disproportionally likely to experience severe combined abuse and harassment. Third, against expectations, females’ absolute income is not related to the experience of IPV either for females or males. Females and males experience a higher rate of IPV when the husband (usually the primary income earner) earns a low income. Last, when considering partners’ relative income, families in which both partners earned a low income are at greater risk of almost all forms of IPV. Surprisingly, income (im)balance in which females earn more, or partners both have higher income, is less often associated with the experience of IPV.

In the current study, although the prevalence of physical abuse generally was higher for males, it was not associated with family or personal income in men. Further studies are needed to investigate predictors of males’ victimization within the family. When total family income is low, females are substantially more likely than men to experience physical abuse. These associations are independent of a variety of potential confounding factors, including partners’ education level, marital status, duration of relationship, and having children. In line with our finding, we could only find one study in England which reported an association between low social class and physical abuse victimization among women but not among men (Khalifeh, Hargreaves, Howard, & Birdthistle, 2013). It remains the case in contemporary Western societies that gender role expectations of men to be the main income earner may make them vulnerable to multiple economic stressors. Our finding supports a Relative Resource Theory explanation which suggests that when there is a lack of economic resources, men might exchange force and physical violence in their intimate relationships. Another possibility is that there may be circumstance where incomes are nominally pooled, but in practice, one partner controls the household money (Vogler & Pahl, 1994). Due to the lower share of money in the household pool, women may be more vulnerable to the consequences of financial deprivation or engage in conflict to improve their access to resources.

When family income is disaggregated into the husband’s income, the wife’s income, and the gender (im)balance in income, there are some important differences in the gendered basis of IPV. When the husband’s income is low, he is much more frequently likely to report experiencing most forms of IPV with the exception of physical abuse. This finding again suggests that despite men reporting physical abuse more often, there is no association between family or personal income and males’ physical victimization. Female partners of low-income males also more often experience most types of IPV, with the exception of harassment. In broad terms, a low-income earning male is substantially more likely to live in a household in which both partners report higher rates of various forms of IPV; by contrast, where the wife’s income is low, this appears to be unrelated to experiences of IPV.

The finding that wife’s income is unrelated to IPV experience for females may challenge explanations associated with Dependency Theory, which suggests wives’ economic dependency is a protective factor against IPV victimization (Golden et al., 2013; Hornung et al., 1981; Kalmuss & Straus, 1982; Tauchen & Witte, 1995). Although wife’s income can increase family well-being (Rogers & DeBoer, 2001), in the current study female income made a smaller contribution to the family income than male’s (34.1% vs. 65.9%, p < .0001). It is not surprising that regardless of the male partner’s income, wife’s income is unrelated to the level of IPV for both females and males. Feminist theory and intersectionality perspective argue that women’s status is complex and multidimensional, including political, legal, social, and economic dimensions. Income is only one marker of a broader range of interdependent characteristics associated with gender inequality (Crenshaw, 1991; Dobash & Dobash, 1979; Hester et al., 1996; Yodanis, 2004).

When we consider the gender balance of income, relative experiences of almost all forms of IPV (with the exception of physical abuse in males and harassment in females) are highest when both partners report receiving low income. Disagreements over the allocations of limited resources may contribute to the experience of IPV. Money has been reported to be the most critical and pervasive source of interpersonal conflicts (Oggins, 2003; Papp, Cummings, & Goeke-Morey, 2009). Families with inadequate funds have to struggle with recurrent and unsolvable issues, including making decision about who, when, why, and how limited funds are to be allocated. Money is also related to power and to the sense of self-worth. Partners in a low-income family may engage in more aggressive pattern of behaviors, which is consistent with the view that partners in such relationships become simultaneously both victims and perpetrators. It may also be the case that the division of household labor in a low-income family may be a source of conflict and violence (Killewald & Gough, 2010). Our findings challenge the significance of subjective dimensions of financial issues (e.g., symbolic meanings) in interpersonal relationships. The data suggest that objective economic hardships and resource scarcity create a context for competition, conflict, and abuse. We also find that in such circumstances, females are at increased risk of physical abuse and males disproportionately experience harassment. The pattern raises the possibility that males and females may use different strategies in response to constraints of living in a poor family. This finding is consistent with some previous studies suggesting that females tend to display verbal and indirect forms of aggression, whereas distressed males may show direct and more physical forms of violence (see, for example, Björkqvist, 1994).

The current study has several strengths. We have used a relatively large, population-based sample, including both men and women, which enabled us to examine different types of IPV as well as to adjust for a range of demographic factors associated with IPV. We also used a validated and comprehensive measurement of IPV which was reliable for both genders. Testing the reliability of the IPV subscales separately for females and males, we found that the Cronbach’s alpha of all subscales was higher than .80 (except harassment in men = .63). We asked about recent experience of IPV to reduce the probability of memory bias (Ruiz-Pérez, Plazaola-Castaño, & Vives-Cases, 2007).

However, our results should be interpreted with regard to some limitations: The cross-sectional nature of our study does not allow us to make a causal inference about the relationship between income and IPV (Khalifeh et al., 2013). Small sample size, especially in the severe combined victimization group, widened the CIs and decreased the precision of the estimate. We modeled each form of IPV separately but recognize that they may overlap and co-occur (Krebs et al., 2011). In an abusive relationship, each partner may be both victim and perpetrator. Our findings relied on only one partner’s report of victimization, which might be subject to self-serving bias or less accurate reports of IPV (Perry & Fromuth, 2005). For instance, there is a possibility that men might have overreported their experiences of physical abuse in the current study, because IPV is a more salient event for males. However, in an abusive relationship, men may be less inclined to disclose their victimization, due to social shame and denial (Brown, 2004; Dutton, Nicholls, & Spidel (2005). There is also a need to differentiate between the frequency and degree of physical violence. It is possible that although men report they experience physical violence more frequently, due to the lesser females’ physical power, men might less be seriously injured. Regardless of the frequency of violence acts, men may do more physical harm when they are violent (Catalano, 2013).

Our findings suggest the need to consider the couple as the unit of interest. Public health initiatives should be targeted not only at women’s victimization but also at men’s vulnerability to IPV in the context of relationships. Lack of knowledge about women’s violence hinders identification of potential intervention targets. The vast majority of IPV victimization does not appear in crime data or clinical settings. This study was based on cross-sectional reports of common couple violence, which is relatively dyadic, minor, and possibly consistent over time. It is not clear when and how this form of family violence may become severe and under what circumstances this may occur. Further studies need to investigate whether IPV varies over life-course stages. Looking for possible patterns of IPV over time may offer direction for policy and intervention.

Footnotes

Appendix C

Appendix D

Appendix A

Univariate Logistic Regression Analysis for Variables Predicting IPV Victimization in Females.

	SC		PA		EA		H
Variables	Yesn (%)	OR (95% CI)	Yesn (%)	OR (95% CI)	Yesn (%)	OR (95% CI)	Yesn (%)	OR (95% CI)
Marital status
Single now, before in relation	29 (16.1)	16.44 [7.37, 36.68]	49 (27.2)	7.25 [4.50, 11.67]	65 (36.1)	4.73 [3.21, 6.97]	47 (26.1)	17.14 [9.17, 32.02]
Living together	11 (2.9)	2.53 [1.01, 6.34]	29 (7.6)	1.59 [0.95, 2.64]	58 (15.1)	1.49 [1.03, 2.16]	13 (3.4)	1.70 [.79, 3.66]
Married	8 (1.2)	1	34 (4.9)	1	74 (10.7)	1	14 (2.0)	1
Having children
Yes	41 (5.1)	1.38 [0.83, 2.31]	95 (11.8)	1.73 [1.20, 2.50]	147 (18.3)	1.39 [1.04, 1.85]	70 (8.7)	1.81 [1.18, 2.79]
No	24 (3.7)	1	46 (7.2)	1	89 (13.9)	1	32 (5.0)	1
Own education
Under diploma	24 (5.6)	2.19 [1.08, 4.43]	53 (12.4)	2.0 [1.25, 3.19]	83 (19.4)	1.68 [1.16, 2.42]	46 (10.7)	2.76 [1.59, 4.79]
Diploma and college	29 (5.2)	2.02 [1.02, 4.0]	57 (10.2)	1.61 [1.01, 2.54]	94 (16.8)	1.41 [0.99, 2.01]	37 (6.6)	1.62 [0.92, 2.86]
University	12 (2.6)	1	30 (6.6)	1	57 (12.6)	1	19 (4.2)	1
Partner’s education
Under diploma	13 (3.2)	1.60 [0.60, 4.26]	31 (7.7)	2.64 [1.24, 5.64]	59 (14.6)	1.77 [1.09, 2.88]	19 (4.7)	3.59 [1.21, 10.67]
Diploma and college	5 (1.1)	0.51 [0.16, 1.69]	30 (6.3)	2.14 [1.0-4.57]	59 (12.4)	1.46 [0.90, 2.39]	10 (2.1)	1.56 [0.49, 5.02]
University	6 (2.0)	1	9 (3.1)	1	26 (8.8)	1	4 (1.4)	1
Own income^a
Low	12 (2.8)	6.79 [0.88, 52.56]	33 (7.6)	2.39 [1.08, 5.25]	66 (15.1)	1.87 [1.11, 3.14]	13 (3.0)	1.45 [0.51, 4.12]
Middle	5 (1.3)	3.13 [0.36, 26.91]	21 (5.4)	1.66 [0.72, 3.81]	45 (11.6)	1.37 [0.80, 2.36]	9 (2.3)	1.12 [0.37, 3.38]
High	1 (0.4)	1	8 (3.3)	1	21 (8.7)	1	5 (2.1)	1
Partner’s income^a
Low	5 (4.2)	21.06 [2.44, 182.05]	14 (11.9)	3.25 [1.58, 6.68]	25 (21.2)	2.35 [1.38, 3.99]	6 (5.1)	2.50 [0.89, 7.03]
Middle	11 (2.4)	11.48 [1.48, 89.30]	29 (6.2)	1.60 [0.88, 2.89]	57 (12.2)	0.35 [0.81, 1.82]	10 (2.1)	1.02 [0.42, 2.48]
High	1 (0.2)	1	19 (4.0)	1	49 (10.3)	1	10 (2.1)	1
Length of relationship M (SD)	2.29 (3.62)	0.78 [0.72, 0.85]	4.17 (4.92)	0.90 [0.87, 0.95]	5.19 (4.76)	0.96 [0.93, 0.99]	2.81 (4.40)	0.82 [0.77, 0.87]

Note. ORs in bold are significantly different to those of the reference category (p < .05). IPV = intimate partner violence; SC = severe combined; PA = physical abuse; EA = emotional abuse; H = harassment; OR = odds ratio; CI = confidence interval.

Singles were omitted from the analysis, because we ask them about current income which might be different from when they were in the relation.

Appendix B

Univariate Logistic Regression Analysis for Variables Predicting IPV Victimization in Males.

	SC		PA		EA		H
Variables	Yesn (%)	OR (95% CI)	Yesn (%)	OR (95% CI)	Yesn (%)	OR (95% CI)	Yesn (%)	OR (95% CI)
Marital status
Single now, before in relation	13 (11.3)	6.15 [2.48, 15.24]	26 (22.6)	2.32 [1.35, 3.97]	33 (28.7)	2.43 [1.48, 3.98]	23 (20.0)	7.95 [3.82, 16.58]
Living together	4 (1.6)	0.79 [0.24, 2.65]	33 (13.3)	1.22 [0.75, 1.98]	49 (19.8)	1.49 [0.98, 2.26]	22 (8.9)	3.10 [1.50, 6.38]
Married	8 (2.0)	1	44 (11.2)	1	56 (14.2)	1	12 (3.0)	1
Having children
Yes	20 (5.2)	3.39 [1.53, 7.52]	65 (16.9)	1.88 [1.28, 2.76]	84 (21.8)	1.64 [1.17, 2.30]	31 (8.1)	0.97 [0.60, 1.55]
No	9 (1.6)	1	55 (9.7)	1	82 (14.5)	1	47 (8.3)	1
Own education
Under diploma	15 (4.5)	5.07 [1.15, 22.36]	58 (17.2)	2.64 [1.48, 4.73]	67 (19.9)	1.59 [1.0, 2.55]	40 (11.9)	3.15 [1.50, 6.63]
Diploma and college	12 (3.1)	3.49 [0.77, 15.73]	45 (11.6)	1.68 [0.92, 3.05]	68 (17.6)	1.35 [0.85, 2.15]	28 (7.2)	1.83 [0.85, 3.95]
University	2 (0.9)	1	16 (7.3)	1	30 (13.6)	1	9 (4.1)	1
Partner’s education
Under diploma	8 (3.3)	1.92 [0.62, 5.94]	35 (14.5)	1.49 [0.88, 2.53]	4 (18.7)	1.32 [0.83, 2.10]	21 (8.7)	2.16 [1.04, 4.50]
Diploma and college	4 (2.0)	1.16 [0.31, 4.39]	26 (13.3)	1.35 [0.77, 2.37]	38 (19.4)	1.39 [0.86, 2.45]	12 (6.1)	1.48 [0.65, 3.36]
University	5 (1.8)	1	29 (10.2)	1	42 (14.8)	1	12 (4.2)	1
Own income^a
Low	3 (8.8)	6.27 [1.43, 27.49]	7 (20.6)	1.93 [0.78, 4.72]	9 (26.5)	2.11 [0.93, 4.79]	6 (17.6)	8.60 [2.79, 26.53]
Middle	4 (1.4)	0.95 [0.25, 3.57]	31 (11.2)	0.94 [0.57, 1.55]	48 (17.3)	1.23 [0.79, 1.90]	20 (7.2)	3.12 [1.35, 7.21]
High	5 (1.5)	1	39 (11.9)	1	48 (14.6)	1	8 (2.4)	1
Partner’s income^a
Low	7 (2.7)	—	33 (12.5)	0.93 [0.49, 1.76]	44 (16.7)	1.13 [0.62, 2.05]	18 (6.8)	1.39 [0.53, 3.60]
Middle	4 (1.6)		25 (10.3)	0.75 [0.38, 1.46]	40 (16.5)	1.12 [0.61, 2.05]	10 (4.1)	0.82 [0.30, 2.30]
High	0		16 (13.3)	1	18 (15.0)	1	6 (5.0)	1
Length of relationshipM (SD)	4.14 (0.92)	0.96 [0.88, 1.06]	4.71 (4.16)	1.0 [0.95, 1.05]	4.97 (4.11)	1.02 [0.98, 1.06]	3.60 (4.16)	0.93 [0.87, 0.99]

Singles were omitted from the analysis, because we ask them about current income which might be different from when they were in the relation.

Acknowledgements

The authors would like to thank the Mater-University of Queensland Study of Pregnancy (MUSP) research team, the Schools of Public Health and Social sciences (The University of Queensland), and also the Research Training Program of the Australian Government and the University of Queensland for sponsoring the principal author of the research.

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: This study was funded by the National Health and Medical Research Council and Australian Research Council (NHMRC Grant 1009460). The principal author is in receipt of “the Australian Government Research Training Program Scholarship” and “the University of Queensland Centennial Scholarship.”

Author Biographies

Zohre Ahmadabadi is a PhD candidate at the School of Public Health of the University of Queensland. She received her master’s degree in sociology in 2005 from Shahid Beheshti University (National University of Iran), Tehran, Iran. Her research interests are predictors and consequences of intimate partner violence.

Jackob M. Najman is a professor of medical sociology and director of Queensland Alcohol & Drug Research and Education Centre (QUADREC) at the University of Queensland. He received his doctorate in 1978 from the University of New South Wales. He has authored and/or coauthored over 500 publications. His major research commitment has been a large-scale prebirth cohort study which recruited over 8,000 pregnant women over the period 1981-1983.

Gail M. Williams is a professor at the University of Queensland. She received her doctorate from the University of Queensland. She is head of the Epidemiology and Biostatistics Division.

Alexandra M. Clavarino is an associate professor at the University of Queensland. She received her doctorate in medical sociology from the University of Queensland. Her main interests are in life-course studies of women’s mental and physical health outcomes.

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