Adolescent Relationship Aggression Perpetration and Victimization in the Context of Neighborhood Gender Equality

Abstract

Adolescent relationship aggression (ARA) is a serious and common public health problem with many associated adverse health outcomes. Research on risk factors for ARA and resulting programmatic efforts to address the issue have focused primarily on individual-level characteristics, and less so on broader macro-level factors. The present study investigates the longitudinal relationship between one macro-level factor—neighborhood gender equality—and the prevalence of ARA perpetration and victimization among 723 participants (351 males and 372 females) of the Survey on Teen Relationships and Intimate Violence across two waves (2013 and 2016). Controlling for individual demographic characteristics and residential stability, the authors found that male participants living in neighborhoods with higher gender equality were less likely to report perpetrating ARA (β = −0.56; p < 0.05). The authors did not detect associations between neighborhood gender equality and perpetration for female participants nor did the authors detect associations between neighborhood gender equality and victimization for either male or female participants. Their findings suggest that ARA perpetration by males is among the myriad of negative impacts of gender inequality and that efforts to address structural gender inequality may also lead to healthier, violence-free intimate relationships among adolescents. The authors discuss suggestions for further research.

Introduction

Adolescent relationship aggression (ARA), encompassing psychological, physical, and/or sexual abuse (Offenhauer and Buchalter 2011) between current or past dating partners (Centers for Disease Control and Prevention, 2018), is a common public health problem with many associated adverse outcomes (Barter and Stanley 2016; Exner-Cortens et al. 2013; Orpinas et al. 2017; Temple et al. 2016), including future experiences with intimate partner violence victimization (IPV) (Exner-Cortens et al. 2017). ARA has been reported by adolescents as young as age 10 (Taylor and Mumford 2016) and extends into emerging adulthood (Arnett 2000; Halpern et al. 2009; Zhang et al. 2016). Other terms used to describe ARA in the literature are teen dating violence and intimate partner violence, neither of which apply to fixed age ranges, but tend to refer to teenage and adult populations, respectively. Much research has focused on individual-level risk factors for ARA victimization and perpetration (e.g., Foshee et al. 2011; Garthe et al. 2016; Vagi et al. 2013), but prevention efforts to address these risks have had varying results. For instance, evaluations of a few middle and high school based prevention programs show limited impact (De La Rue et al. 2014). Overall, programmatic efforts tend to focus on adolescent attitudes, intentions, and skills, rather than community norms and structural factors, consistent with the research focus to date. Some of the programs address gender inequities, but there are others who question whether gender inequities are relevant for ARA (Langhinrichsen-Rohling 2010). This study was conducted to investigate the longitudinal relationship between neighborhood-level gender equality and the prevalence of ARA perpetration and victimization.

Bronfenbrenner's ecological model (1977) suggests that macrosystem factors are determinants of individual behaviors and outcomes. According to some feminist theoretical approaches, structural gender inequality is one such macro factor underlying violence against females (Yodanis 2004). Structural gender equality, as defined in terms of development goals around the world, reflects equal access for both men and women to resources, education, and rewards for work (World Bank 2001). The United Nations has created a set of indicators for gender equality that further extends the measure to public life and decision making, health and health service access, and human rights inclusive of measures of gender-based violence (United Nations 2017). According to theory, gender inequality underpins systemic patterns of rewards and punishment to maintain male power over females (Glick and Fiske 2001). These structural patterns may play out at many levels: in families, workplaces, and the community. However, this theory fails to explain violence perpetrated against males. Hunnicut and Broidy (2004) address the limits of feminist theoretical approaches, noting that past applications assume that males represent a monolithic group with invariable cultural systems, fail to address the durability of patriarchy in times and places exhibiting gains in gender equality, and inadequately theorize the complexity of gendered power dynamics in relationships.

Thus, theoretical approaches to gender-based violence have begun to take into account female aggression against males. Gender convergence theory (Steffensmeier and Allan 1996), for instance, suggests the potential for individual levels of violence to change due to macro shifts in gender equality. Specifically, this theoretical approach posits that a society functioning through greater gender equality would result in increased female offending. Conversely, according to the ameliorative hypothesis (Lei et al. 2014; Whaley and Messner 2002), greater structural gender equality would likely lead to reduced male violence against females and, in theory, less gendered violence overall. Attempts to explain why greater structural gender equality might not lead to reduced male violence against females include theory centered on the potential backlash resulting from the deterioration of male power (Martin et al. 2006; Whaley and Messner 2002). Moreover, potential countervailing increases in female aggression resulting from expanded liberation would also lead to increases in violence (Hunnicutt and Broidy 2004; Lei et al. 2014). In sum, theory suggests that neighborhood-level gender equality may play a role in male and female involvement in ARA. Understanding whether neighborhood-level gender equality is associated with ARA can help inform prevention strategies. If gender equality at the neighborhood level is associated with ARA, this would lend support to the idea that social norm changes at the community level may reduce violence.

Importantly, whether community-level gender equality makes a difference in individual violence may change over time (Elder et al. 2003). Not only might levels of gender equality change over time, but how much it influences behavior might also change. Moreover, adolescents' residential stability over time affects the impact of a given socioecological context (Bronfenbrenner 1977). Exposure may vary as a result of individuals making a residential move from one neighborhood to another. Youth might experience more or less gender inequality depending on the structural and cultural characteristics of their new neighborhood.

Moving from theory to evidence, few studies have attempted to capture the impact of macro-level gender equality. Research assessing the impact of macro-level gender equality tends to focus on adult violence. For example, focusing on macro-level gender equality, urban studies have indicated ongoing backlash in some regions, with higher rates of male violent offending against females associated with greater macro-level gender equality (Martin et al. 2006; Whaley and Messner 2002). Adolescent studies, investigating violence more broadly, have examined a range of community-level structural and social measures such as collective efficacy, social organization, and neighborhood disadvantage, with mixed results (e.g., Fagan and Wright 2012; Jain et al. 2010; Karriker-Jaffe et al. 2009). Moreover, qualitative research has shown that adolescent males and females have different risk perceptions and coping strategies informed by neighborhood environments (Cobbina et al. 2008). Yet, to their knowledge, Lei and colleagues have conducted the only study of adolescent violence (including physical assault and threats, bulling, fighting with weapons, and so on) examining the role of structural gender equality (Lei et al. 2014). Lei et al. (2014) found that neighborhood gender equality suppressed male violence (consistent with the ameliorative hypothesis), whereas female violence was less affected by greater gender equality.

In this study, the authors assessed the longitudinal impact of neighborhood gender equality on ARA perpetration and victimization. The liberation hypothesis associated with gender convergence theory suggests the possibility that greater gender equality would be associated with more ARA perpetrated by females and thus more ARA victimization of males. However, given the unique interpersonal context of dating relationships—and the extent of mutual aggression in adolescent dating relationships (Gray and Foshee 1997; Malik et al. 1997; Taylor and Mumford 2016)—gender equality in the broader community may not affect male and female ARA in the same way that Lei et al. found that it correlated with violent behavior. Rather, in line with the ameliorative hypothesis, the authors hypothesized that greater structural gender equality would be associated with reduced perpetration reported by male youth and thus reduced female victimization. Because the ameliorative hypothesis posits reduced gendered violence overall, the authors might expect structural gender equality also to be associated with reduced perpetration reported by females and, thus, reduced male victimization. Accordingly, the authors hypothesized that in neighborhoods with greater gender equality, male ARA victimization and female perpetration would also be lower. In other words, the authors expected that both male and female ARA involvement would be less for adolescents from neighborhoods marked by higher gender equality.

Materials and Methods

Sample

This study uses data from the annual Survey on Teen Relationships and Intimate Violence (STRiV), an ongoing cohort study sponsored by the National Institute of Justice. Participants are youth, ages 10 to 18 at baseline (collected between October 2013 and January 2014), recruited from households in the GfK/Knowledge Panel, an address-based, national household probability sample. The survey was repeated on an annual basis, including Wave 4, which was collected between October 2016 and July 2017. STRiV sampling and recruiting methods are discussed in detail elsewhere (Taylor and Mumford 2016).

STRiV baseline data represent 2354 youth respondents, of whom 1499 (63.7%) completed the Wave 4 survey. The average age of respondents at baseline was 14.7; the average age at Wave 4 was 17.7 years. Wave 4 respondents were slightly younger than respondents lost to follow-up (the age difference was less than one-fifth of the standard deviation), but there were no significant differences with regards to gender or dating status.

Participants

Respondents to the dating questions were provided with the following introductory text: “The next questions are about dating relationships. By dating, we mean a relationship with a boy or a girl who you are “going with,” “dating,” “going steady with,” or have had that kind of relationship with. This includes anyone who is or was your boyfriend or girlfriend, where you liked someone and they liked you back.” The study sample includes Wave 4 respondents meeting the following criteria: (1) respondent reported a past-year or current dating relationship (henceforth referred to as “daters”); and (2) respondent answered questions regarding ARA perpetration and victimization (posed only to daters). Among Wave 4 participants, 728 were daters, 723 (351 males and 372 females) of whom provided ARA outcome responses, constituting the sample used in their analysis. The sample description is presented in Table 1; 85% had not moved outside of their Wave 1 tract over the four waves.

Table 1.

Descriptives of Participant Sociodemographics, Residence Stability, Neighborhood Gender Equality, and Adolescent Relationship Aggression Experience (N = 723)

	Males and femalesn (%)	Males onlyn (%)	Females onlyn (%)
Age (years)
Mean (SD)	17.7 (2.8)	17.6 (3.0)	17.7 (2.7)
Race/ethnicity^a
White non-Hispanic	487 (60.7)	243 (63.0)	244 (58.5)
Black non-Hispanic	75 (16.0)	33 (15.2)	42 (16.8)
Hispanic	127 (17.5)	61 (17.8)	66 (17.3)
Other non-Hispanic	34 (5.7)	14 (4.0)	20 (7.4)
Household income^a
Mean range	$50,000 to $74,999	$50,000 to $74,999	$40,000 to $59,999
Residence stability
Moved	118 (15.4)	55 (15.7)	63 (15.6)
Did not move	605 (84.6)	296 (84.9)	309 (84.4)
Gender equality index
Mean (SD)	−0.047 (0.853)	−0.002 (0.992)	−0.092 (0.694)
Range	−1.537 to 4.372	−1.537 to 4.372	−1.479 to 4.067
ARA perpetration
Perpetrator	119 (18.9)	37 (11.3)	82 (26.2)
Nonperpetrator	604 (81.1)	314 (88.7)	290 (73.8)
ARA victimization
Victim	136 (17.8)	63 (17.0)	73 (18.5)
Nonvictim	587 (82.2)	288 (83.0)	299 (81.5)

Means and proportions are based on weighted proportions. Frequencies are unweighted.

Assessed in W1.

ARA, adolescent relationship aggression.

Measures

ARA perpetration and victimization

ARA was assessed using a modified version of the Conflict in Adolescent Dating Relationships Inventory (CADRI) (Wolfe et al. 2001). Youth were prompted to report on ARA that occurred in one specific current or past year dating relationship. The self-report scale assesses various forms of ARA perpetration (instances when the respondent did something to the partner) and victimization (experiences of the partner doing something to the respondent). The authors limited the current analysis to measures assessing sexual and physical perpetration (13 items; Cronbach's α = 0.9) and victimization (13 items; Cronbach's α = 0.9). Participants were classified in two binary variables as an ARA perpetrator or victim at Wave 4 if they reported experience with any form of sexual or physical ARA.

Gender equality index

Drawing on prior studies using a similar index (Martin et al. 2006; Lei et al. 2014), the authors constructed a gender equality index (GEI) using publicly available data (2009–2013) from the American Community Survey (ACS). The authors extracted these data at the tract level, the smallest analytic level possible for their measures of interest. The ACS only releases 5-year aggregate data at the tract level; therefore, the measures on which the GEI is based are an approximation of the true Wave 1 measures. The GEI is based on the female-to-male ratio of three tract-level measures: (1) income levels; (2) adults 25 years and older with 4 or more years of college education; and (3) individuals 16 years and older employed in management, professional, and related occupations. The authors used principal component analysis to create an index from these ratios. The measures were loaded on to a single component, with all loadings exceeding 0.5.

Residential stability

To determine the independent effect of Wave 1 neighborhood gender equality on Wave 4 ARA, the authors assessed the movement of participants to different census tracts across the four annual waves of data to account for possible confounding that may arise as a result of living in multiple neighborhoods. Because participants who moved at some point during follow-up differed on family income from those who stayed within the same tract, it was important to keep the former in the sample. Thus, the authors include an indicator of respondents who stayed within the same tract across the four waves vs. those who moved.

Sociodemographics

Age was assessed as a continuous variable. GfK panel member data provided measures of household race/ethnicity; categories included in their analysis are white non-Hispanic (reference category); black non-Hispanic; Hispanic; and other non-Hispanic. Household income was assessed using 19 categories, which were entered into their analysis as a continuous variable.

Analytic strategy

The authors conducted descriptive statistics to examine distributions and associations of the covariates and the outcome variables. Using logistic regressions, stratified by participant sex, the authors examined the association between gender equality and ARA outcomes, controlling for all covariates. While their sample consisted of 723 participants nested within 718 census tracts, hierarchical models were not an appropriate approach, given that the overwhelming majority of census tracts represented in their sample were associated with just one participant. For all analyses, alpha was set at the .05 level.

Results

Descriptive findings

As shown in Table 1, nearly one in five (18.9%) daters in their sample reported perpetrating ARA. The prevalence of ARA perpetration differs by sex—11.3% of males reported perpetrating ARA compared to 26.2% of females (p < 0.001). Overall, 17.8% of participants reported being a victim of ARA, with prevalence being comparable for males (17.0%) and females (18.5%).

Table 2 shows the prevalence of ARA perpetration and victimization among male and female participants by the primary predictor and covariates. The prevalence of male ARA perpetration is comparable across age, residential stability, and neighborhood gender equality, although there is significant variation by race/ethnicity and household income. The prevalence of male ARA victimization did not vary by age, residential stability, or neighborhood gender equality, but did vary by race/ethnicity and household income.

Table 2.

Prevalence of Adolescent Relationship Aggression Perpetration and Victimization, by Sociodemographic Characteristics

	Males
	ARA perpetration		ARA victimization
	Nonperpetrator %	Perpetrator %	Nonvictim %	Victim %
	Age (years)
<15	90.4	9.6	91.0	9.0
15–17	87.3	12.8	80.3	19.7
18–22	88.7	11.3	80.9	19.1
Race/ethnicity^*^,†
White non-Hispanic	92.9	7.1	88.4	11.6
Black non-Hispanic	92.3	7.7	88.8	11.2
Hispanic	71.2	28.8	56.1	44.0
Other non-Hispanic	87.8	12.2	95.2	4.78
Household income^*^,†
≤$59,999	79.2	20.9	75.9	24.1
≥$60,000	96.2	3.8	88.5	11.5
Residence stability
Moved	93.0	7.1	85.6	14.4
Did not move	88.0	12.0	82.5	17.5
Gender equality index
Below median	89.4	10.6	83.4	16.6
Above median	88.1	11.9	82.6	17.4

Females
Age (years)^†
<15	75.4	24.6	92.2	7.9
15–17	78.7	21.3	84.1	15.9
18–22	71.0	29.0	77.1	22.9
Race/ethnicity^†
White non-Hispanic	73.4	26.6	84.0	16.0
Black non-Hispanic	72.5	27.5	85.9	14.1
Hispanic	74.7	25.3	67.8	39.3
Other non-Hispanic	77.1	22.9	83.5	16.5
Household income^†
≤$59,999	70.2	29.8	77.0	23.0
≥$60,000	77.3	22.7	86.0	14.0
Residence stability^*
Moved	53.9	46.2	73.4	26.6
Did not move	77.5	22.5	83.0	17.0
Gender equality index^*
Below median	80.2	19.8	82.8	17.2
Above median	67.4	32.6	80.3	18.5

p < 0.05 for ARA perpetration.

†

p < 0.05 for ARA victimization.

Female ARA perpetration did not vary by age, race/ethnicity, or household income. The prevalence of ARA perpetration, however, differed by residential stability and by neighborhood gender equality. The prevalence of ARA victimization among female daters varied by age and race/ethnicity.

Multivariable models of male and female ARA involvement

For males, the authors did not detect associations between neighborhood gender equality and ARA perpetration when controlling for residential stability only or both residential stability and age (Table 3). However, when the authors accounted for household income and race/ethnicity, males living in neighborhoods with higher gender equality were less likely to report perpetration (β = −0.56; p < 0.05). The authors did not find statistically significant associations between neighborhood gender equality and male victimization in any of the models. There also were no statistically significant associations between neighborhood gender equality and ARA perpetration or victimization reported by females.

Table 3.

Logistic Regression of Gender Equality, Residence Stability, Age, Household Income, and Race Ethnicity on Adolescent Relationship Aggression Perpetration and Victimization by Sex

Males
ARA perpetration
	Model 1	Model 2	Model 3
	B	β	β
	Gender equality	−0.301	−0.293	−0.559^*
Residence stability	0.607	0.579	0.953
Age		0.024	−0.035
Household income			−0.107^*
Race/ethnicity (ref: White)
Black			−0.055
Hispanic			1.597
Other			0.864

ARA victimization
Gender equality	−0.203	−0.155	−0.324
Residence stability	0.249	0.112	0.325
Age		0.123	0.093
Household income			−0.066
Race/ethnicity (ref: White)
Black			−0.271
Hispanic			1.681^*
Other			−0.854

Females
ARA perpetration
Gender equality	0.320	0.335	0.348
Residence stability	−1.010^*	−1.137^*	−1.102^*
Age		0.092	0.100
Household income			−0.022
Race/ethnicity (ref: White)
Black			−0.335
Hispanic			−0.126
Other			−0.357

ARA victimization
Gender equality	0.336	0.357	0.352
Residence stability	−0.619	−0.800^*	−0.783
Age		0.134^*	0.155^*
Household income			−0.015
Race/ethnicity (ref: White)
Black			−0.262
Hispanic			0.849
Other			−0.066

p < 0.05.

Discussion

Violence prevention interventions targeting males often include components geared toward addressing gender inequality (Flood 2015), highlighting the important role that this macro-level factor plays in patterns of gender-based violence. However, efforts to understand the role of gender equality as it relates to violence against women in the United States have focused primarily on adult rape and homicide (Martin et al. 2006; Whaley and Messner 2002). For more than two decades, researchers have been expanding the body of knowledge on ARA, recognizing the risks posed in adolescence, as well as the increased risk for adult IPV involvement and related sequelae. However, in the United States, social structures that may influence ARA perpetration have been understudied (see Reed et al. 2011 for example study). Using nationally representative data, this study found evidence, consistent with the ameliorative hypothesis, that male ARA perpetration was lower in neighborhoods where there was more gender equality.

Moreover, the authors did not find greater neighborhood gender equality to be associated with increased female perpetration or male victimization, as would be expected under gender convergence theory (Steffensmeier and Allan 1996). Their findings also do not support evidence of backlash in the form of higher male perpetration rates due to lessened economic power over females, as suggested by some theoretical perspectives (Martin et al. 2006; Whaley and Messner 2002). Although their findings suggest an inverse relationship between neighborhood gender equality and male perpetration, the authors did not detect the expected parallel association–that is a lower prevalence of female victimization in neighborhoods with greater gender equality. This discrepancy may be due to several factors. Perhaps females living in more gender egalitarian neighborhoods are more likely to identify or recall a broader range of actions as “acts of ARA.” Or it may be that males in these same neighborhoods are less willing to report perpetration. However, their results are consistent with previous evidence suggesting the favorable impact of neighborhood gender equality on male offending (Lei et al. 2014). Overall, the primary takeaway from their results is that, adjusting for residential stability and sociodemographics, improvements in neighborhood gender equality may lead to less ARA perpetrated by boys and young men and overall safer relationships for their partners.

Study limitations include the potential social desirability bias associated with self-reported ARA. However, this bias may be minimized due to use of a multi-item measure—that is, the construct was based on experience with at least one of several indicators of physical or sexual ARA. Furthermore, their operationalization of gender inequality is based on a small set of economic measures. It could be that defining gender inequality differently (e.g., expanding the age range referenced in the measures or including additional socioeconomic measures, as has been done in other studies, e.g., Whaley and Messner 2002) may yield different results.

Their findings represent a valuable starting point for understanding how macro-level gender equality manifests in the intimate relationships of teenagers and young adults and, in turn, lay the foundation for additional research on the topic. Specifically, future research focused on understanding whether and/or how the impact of gender equality on ARA varies by sexual orientation¹ and gender identity and expression might be particularly valuable for targeting interventions to youth occupying various positions on the sexuality and gender spectra. Moreover, to the extent that a reduction in gender-based violence is itself an indicator of gender equality (United Nations 2017), research attending to a broader set of indicators may yield insights about programmatic approaches and interventions that have multiplicative effects. In addition, the development of effective interventions may hinge partly on understanding the factors that mediate or moderate the association of neighborhood gender equality and ARA. Examinations focused on the family contexts within which youth are raised may be particularly valuable. Some research, for example, suggests that there are gender differences in young adult risk-taking behaviors based on the extent to which their households were patriarchal (Grasmick et al. 1996). These differences may manifest as differing approaches to intimate partner conflicts. Future research should consider unobserved correlates of gender equality and ARA such as family systems and world views associated with patriarchy.

Conclusions

Overall, our findings suggest that efforts to address macro-level structural gender equality may have positive implications for relationship violence among adolescents. Given that the overwhelming majority of research conducted on risk and protective factors associated with ARA has focused on individual-level influences, most ARA interventions have also focused on addressing these factors. These interventions have not proven to be consistently effective (De La Rue et al. 2017; Fellmeth et al. 2013; Foshee and Reyes 2009; Ting 2009). Our findings provide justification for expanding ARA prevention efforts to encompass higher level systems of influence.

Economic insecurity among women, measured at the individual level, is both a risk factor and consequence of IPV among adults (Breiding et al. 2017; Loya 2014; Ricks et al. 2015). The International Labor Union reports that gaps remain for gender equality in the United States in terms of wages, employment, and corporate leadership (International Labour Organization 2018). What our findings suggest is that an environment characterized by gendered patterns of economic inequality adversely affects the health of and safety within adolescent dating relationships and that this might be the case regardless of the level of the individual economic insecurity of the female partner. Therefore, interventions focusing on addressing gender inequality on a structural level may have favorable implications for healthy adolescent dating relationships. Structural gender equality is an important topic in internationally funded efforts to curtail IPV and gender-based violence (Flood 2015). Domestic policies and programs over the past few decades—for example, the Violence Against Women Act, the Justice for Victims of Trafficking Act of 2015, and state violence prevention efforts—reflect a common understanding that effectively curtailing gender-based violence will entail more than targeting individual behaviors through small-scale programs. There are numerous domestic programs, both government and nonprofit funded, aimed at closing the economic gap across genders. They range from targeted opportunities for women-owned businesses to Science, Technology, Engineering, and Mathematics (STEM) education for girls and women. This study suggests that the impact of these large-scale policy and programmatic efforts may extend to the intimate relationships of youth and young adults and that expanding and enforcing these efforts may lay a crucial foundation to improve the success rate of already existing school- and community-based efforts to address ARA.

Footnotes

Acknowledgments

The authors thank research assistants Maria Bohri and Tori Nadel. The authors also thank the GfK team for their continued efforts managing data collection with the STRiV cohort. The authors extend a special thanks to the study respondents for their continued participation in their study and the trust they maintain in their research team. All aspects of the study on which this article is based received approval from the IRB at NORC at the University of Chicago.

Author Disclosure Statement

No competing financial interests exist.

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