Childhood Gender Nonconformity and Intimate Partner Violence in Adolescence and Young Adulthood

Abstract

Childhood gender nonconformity has been associated with numerous adverse experiences, including peer bullying and homophobic violence. However, little is known about gender nonconformity in the context of intimate relationships, independent of sexual orientation. This study aimed to examine associations between childhood gender nonconformity and intimate partner violence (IPV) in adolescence and early adulthood. Using data from the 2007 wave of the U.S. Growing Up Today Study (N = 7,641, mean age = 22.8 years), we estimated risk ratios (RRs) for the association of gender nonconformity up to age 11 years and lifetime IPV victimization and perpetration. Models were adjusted for demographic characteristics, including sexual orientation identity. We assessed effect modification by gender and examined whether childhood abuse mediated the association between nonconformity and IPV. Males in the top decile of nonconformity were at elevated risk of IPV victimization (RR = 1.40, 95% confidence interval [CI] = [1.15, 1.71]) and IPV perpetration (RR = 2.34, 95% CI = 1.54, 3.56) compared with those below median nonconformity, adjusting for sexual orientation and demographic characteristics. There was no evidence of a similar association for females in the top decile of gender nonconformity. Childhood abuse did not mediate IPV disparities by gender nonconformity. We identify gender nonconformity as an important risk indicator for IPV victimization and perpetration among young adult males, independent of sexual orientation. Findings highlight the vulnerability of boys and men who do not conform to societal gender norms and the importance of studying gender expression as a determinant of violence. IPV prevention efforts may be improved with more explicit focus on socially constructed gender norms and support for diverse gender expressions. Further research into the pathways between nonconformity and IPV and in more diverse populations is needed to build a more comprehensive understanding of the unique experiences gender nonconforming youth face.

Keywords

dating violence domestic violence gender nonconformity masculinity femininity predicting domestic violence

Introduction

Intimate partner violence (IPV) is a widespread, but preventable, public health problem. Adolescence and early adulthood are particularly vulnerable times characterized by the exploration of romantic relationships, sexuality, identity, and values. Indeed, 71% of female and 58% of male IPV victims first experience IPV before age 25 years (Breiding et al., 2014). Consequences of IPV victimization and perpetration can be severe and long-lasting and include depression, substance abuse, antisocial behavior, disordered eating, and suicidal ideation (Banyard & Cross, 2008; Bonomi, Anderson, Nemeth, Rivara, & Buettner, 2013; Exner-Cortens, Eckenrode, & Rothman, 2013; Foshee et al., 2016; Foshee, Reyes, Gottfredson, Chang, & Ennett, 2013; Johnson, Giordano, Longmore, & Manning, 2014; Nahapetyan, Orpinas, Song, & Holland, 2014; Roberts, Klein, & Fisher, 2003; Smith, White, & Holland, 2003). Given the substantial health consequences, identifying factors that put individuals at risk for involvement in IPV is essential to creating effective prevention strategies.

Gender nonconformity (GNC)—that is, behaving or appearing in ways that do not follow conventional gender norms or are considered atypical for one’s perceived gender (Zucker & Wood, 2011)—may be one such risk factor. GNC has been associated with increased risk of depressive symptoms, posttraumatic stress disorder, and suicidality as well as decreased well-being and overall health-related quality of life (Friedman, Koeske, Silvestre, Korr, & Sites, 2006; Gordon et al., 2017; Remafedi, Farrow, & Deisher, 1991; Rieger & Savin-Williams, 2012; Roberts, Rosario, Corliss, Koenen, & Austin, 2012b; Roberts, Rosario, Slopen, Calzo, & Austin, 2013; Rosario et al., 2014). Gender differences are important since stigmatization of GNC differs for males and females, in that femininity in males is, in some contexts, less socially accepted than masculinity in females (D’Haese, Dewaele, & Van Houtte, 2016; Kane, 2006; Skidmore, Linsenmeier, & Bailey, 2006). Research on GNC has been conducted largely among samples who identify as lesbian, gay, or bisexual (LGB) and has focused primarily on bullying victimization and perpetration of aggression in peer relationships (D’Augelli, Grossman, & Starks, 2006; Toomey, Card, & Casper, 2014; Toomey, Ryan, Diaz, Card, & Russell, 2010). Little empirical evidence has been generated on GNC in the context of intimate relationships. Sexual orientation disparities in IPV have been well documented, indicating that LGB youth are at higher risk for IPV compared with their heterosexual counterparts (Dank, Lachman, Zweig, & Yahner, 2014; Reuter, Newcomb, Whitton, & Mustanski, 2017; Rothman, Exner, & Baughman, 2011). However, whether gender expression is associated with IPV independent of sexual orientation is not well understood.

One pathway linking GNC and IPV may be childhood abuse. Childhood GNC has been associated with physical, sexual, and psychological abuse victimization in childhood (Roberts, Rosario, Corliss, Koenen, & Austin, 2012a). Furthermore, child abuse is a known risk factor for IPV perpetration and victimization (Capaldi, Knoble, Shortt, & Kim, 2012; Vagi et al., 2013). Thus, if gender nonconforming children are at higher risk of childhood abuse, they may also be at greater risk of being involved in IPV compared with gender conforming children.

The present study investigates whether disparities exist in IPV involvement by childhood GNC in a community sample of U.S. young adults, independent of sexual orientation. We hypothesized that participants who reported higher levels of GNC in childhood would have higher rates of IPV victimization and perpetration compared with participants reporting lower levels of GNC in childhood, and there would be a higher magnitude association for males compared with females. We also hypothesized that childhood abuse would partially mediate the association between GNC and IPV victimization and perpetration.

Method

Participants

We use data from the Growing Up Today Study (GUTS), a national longitudinal cohort of children of participants of the Nurses’ Health Study II (NHSII), a cohort of female registered nurses across the United States (Field et al., 1999). Baseline GUTS questionnaires were mailed in 1996, and more than 16,000 youth enrolled (7,843 boys and 9,039 girls). Since then, participants completed self-administered questionnaires, annually until 2001 and biennially thereafter.

The current analysis includes 7,641 individuals who responded to the 2007 survey wave, when participants were ages 20 to 27 years old (M = 22.8 years) and provided information on the primary predictor, childhood GNC, and on the key outcomes, IPV victimization and IPV perpetration. We used multiple imputation to account for missingness in household income (18% missing). All other covariates had <0.5% missing data, so participants missing data on those covariates were excluded from the analysis. The Brigham and Women’s Hospital Institutional Review Board approved this study.

Measures

Primary predictor: GNC

Childhood GNC was measured in 2005 and 2007 with four questions from the Recalled Childhood Gender Identity/Gender Role Questionnaire (Zucker et al., 2006). The questions assessed gendered behaviors up to age 11 years, including media characters imitated or admired, roles in pretend play, preferences for toys and games, and feelings of femininity or masculinity. Responses were on a 5-point scale from always girls or women/very “feminine” to always boys or men/very “masculine,” which was reversed for males so that higher scores indicate greater GNC. A GNC score was created by taking the mean of the four responses (Cronbach’s α = .83). The score was coded into three categories separately by gender: (a) below median (most gender conforming), (b) median to below top decile, and (c) top decile (most gender nonconforming; Figure 1).

Figure 1.

Childhood gender nonconformity, range of mean response scores by gender among young adults (ages 20-27 years) in the U.S. growing up today study (N = 7,641).

Prior GUTS studies have used similar coding because the relationship between GNC and health outcomes appears to be nonlinear, with the strongest associations found in the top 10% of nonconforming youth (Calzo et al., 2014; Roberts et al., 2012a, 2013). The 2005 assessment of GNC was used as it is most proximal to childhood. For participants missing data in 2005 (n = 1,257, 16% of participants), we used the 2007 GNC report. There was moderate agreement between the 2005 and 2007 GNC assessments—as a continuous measure, correlation = .74, and as an ordinal measure, weighted κ = 0.49, agreement = 64.6%. Participants missing all GNC responses in both 2005 and 2007 were excluded (n = 36, 0.5% of participants).

Primary outcome: IPV

IPV was measured in 2007 with questions adapted from the Abuse Assessment Screen (McFarlane, Parker, Soeken, & Bullock, 1992). Participants were first asked if they had ever been involved in an intimate relationship that lasted 3+ months. If yes, they were asked about IPV. Of all 9,863 participants in the 2007 survey, 7,768 (79%) responded yes to ever having been in a relationship for 3+ months. Excluded participants (n = 2,095, 21%) were slightly younger, more likely to be male, identify as completely heterosexual and as a race other than White but did not differ on GNC compared with included participants.

We examined two binary lifetime IPV outcomes: (a) IPV victimization (physical, sexual, or emotional/psychological) and (b) IPV perpetration (physical or sexual). Four victimization questions asked if participants had ever been made to feel afraid, ever been “emotionally abused (e.g., threatened, insulted, yelled at, degraded),” ever been “hit, slapped, kicked, or otherwise physically hurt by,” or if their partner had ever used “threats, force, or verbal pressure to do something sexual” when they did not want to. Participants were considered to have experienced IPV victimization if they responded “yes, this happened once” or “yes, this happened more than once” to any of these four questions. Two perpetration questions asked participants if they had ever “hit, slapped, kicked, or otherwise physically hurt” their partner(s) or ever used “threats, force, or verbal pressure to make your partner(s) do something sexual when she or he did not want to?” Participants were considered to have perpetrated IPV if they responded “yes, this happened once” or “yes, this happened more than once” to either of these two questions. Participants missing information on IPV were excluded (n = 63, 0.8% of participants).

Mediator: Childhood abuse

History of abuse during childhood before age 11 years was assessed in 2007 and included violence directly experienced by the participant as well as violence witnessed by the participant in the household. The questionnaire assessed emotional, physical and sexual abuse with four items from the Childhood Trauma Questionnaire (Bernstein et al., 1994), two items from the Conflict Tactics Scale (Straus, Hamby, Boney-McCoy, & Sugarman, 1996), and two items from the Sexual Maltreatment Scale of the Parent–Child Conflict Tactics Scales (Straus, Hamby, Finkelhor, Moore, & Runyan, 1998). Emotional and physical abuse were coded as never or rarely versus sometimes or more. Sexual abuse was coded as never versus ever.

Witnessing violence before age 11 years was also assessed in 2007 with six items on hearing or seeing an adult use physical force with (e.g., shove, punch) or verbally abuse (e.g., threaten, degrade) his or her mother, another adult, or a child in the household. These items were coded as two variables to indicate witnessing physical abuse and witnessing emotional abuse and dichotomized as never versus ever.

Covariates

Gender (male or female) was assessed by maternal report at baseline in 1996. Age (in years) at questionnaire return was assessed in 2007. Race was self-reported at baseline in 1996 (coded as White or all other races, given that 95% of the baseline GUTS cohort identified as White). Sexual orientation identity was self-reported in 2007 with a question adapted from the Minnesota Adolescent Health Survey about feelings of attraction (Remafedi, Resnick, Blum, & Harris, 1992) and coded as completely heterosexual versus sexual minority (includes mostly heterosexual, lesbian/gay, mostly homosexual, and bisexual). For participants who were unsure or missing data in 2007 (n = 67, 0.9%), we used the 2005 report of sexual orientation identity. Socioeconomic position (SEP) was operationalized as annual household income in 2001, as this was the only available indicator of SEP. Household income was reported by mothers in the NHSII (coded categorically: <US$50,000, US$50,000-US$74,000, US$75,000-US$99,000, US$100,000-US$149,000, ≥US$150,000). Family structure was reported in 1996 (coded categorically as living with both parents, one parent, or one parent and a stepparent/other).

Analysis

We first examined prevalence of IPV victimization and perpetration by nonconformity separately for females and males. χ²-tests were used to test for significant differences. After fitting bivariate models to assess crude associations with nonconformity, we used multivariable loglinear regression accounting for covariates including age at questionnaire return, race, household income, family structure, and sexual orientation identity. The below median nonconformity (i.e., most gender conforming) group served as the reference category. To assess whether childhood abuse mediates the association between nonconformity and IPV, we examined the fully adjusted models adding childhood abuse as independent variables. Given that there was no attenuation of the GNC associations, we did no further mediation analysis.

For all regression models, generalized estimating equations (GEE) were used to account for the nonindependence of sibling clusters in the GUTS cohort (Zeger & Liang, 1986). We estimated risk ratios (RRs) and 95% confidence intervals (CIs) using log-binomial models (Spiegelman & Hertzmark, 2005). When the log-binomial models failed to converge, we used log-Poisson models with robust error variance (standard errors), which provide valid but not fully efficient estimates of the RRs and 95% CIs (Spiegelman & Hertzmark, 2005; Zou, 2004). To test whether the associations differed by gender, we tested gender-by-GNC interaction terms. Gender modified the associations between GNC and IPV (p < .05 for gender-by-nonconformity interaction terms), so all results are presented stratified by gender.

Multiple imputation methods were implemented to account for missing data on household income and to allow for the uncertainty of the imputed values using SAS PROC MI and PROC MIANALYZE to pool results from multiple imputed data sets (Horton & Kleinman, 2007; Yuan, 2011). We checked the sensitivity of our findings by comparing the results with multiply imputed data to the results with complete data and found no substantive differences. All analyses were conducted using SAS 9.4 (SAS Institute, Cary, North Carolina).

Results

The analytic sample included 4,997 females and 2,644 males. Participants were 20 to 27 years of age at the 2007 wave of data collection (M = 22.8 years) and were 97% White. In the sample, 16% of females and 11% of males reported GNC in the top decile, while 23% of females and 12% of males identified as a sexual orientation minority (Table 1). Although childhood GNC was strongly associated with sexual orientation identity (p < .001), most participants (61%) in the top decile of nonconformity identified as completely heterosexual (compared with 87% and 82% in the < median and ≥ median but below top decile groups, respectively). Among females, 44% reported IPV victimization and 18% reported IPV perpetration. Among males, 26% reported IPV victimization and 7% reported IPV perpetration.

Table 1.

Distribution of Participant Characteristics and Violence Exposure by Gender Among Young Adults (Ages 20-27 Years) in the U.S. Growing Up Today Study (N = 7,641).

	Females (n = 4,997)	Males (n = 2,644)
	% (n)
Gender nonconformity scores
<Median	49.2 (2,460)	37.8 (998)
≥Median, below top decile	34.6 (1,731)	50.9 (1,346)
Top decile (most nonconforming)^a	16.1 (806)	11.3 (300)
Intimate partner violence victimization
Any	43.8 (2,187)	26.2 (693)
None	56.2 (2,810)	73.8 (1,951)
Intimate partner violence perpetration
Any	18.0 (900)	7.1 (189)
None	82.0 (4,097)	92.9 (2,455)
Age (years)
20-22	45.0 (2,249)	47.1 (1,245)
23-27	55.0 (2,748)	52.9 (1,399)
Race
White	96.6 (4,828)	96.7 (2,557)
All other races	3.4 (169)	3.3 (87)
Sexual orientation identity
Heterosexual	77.5 (3,871)	87.7 (2,320)
Sexual minority	22.5 (1,126)	12.3 (324)
Household income (annual)^b
<US$50,000	12.4 (508)	11.1 (243)
US$50,000-US$74,000	23.1 (945)	21.9 (482)
US$75,000-US$99,000	21.9 (894)	23.2 (511)
US$100,000-US$149,000	27.1 (1,108)	26.6 (584)
≥US$150,000	15.5 (633)	17.2 (378)
Family structure during childhood
Both parents	88.3 (4,411)	89.4 (2,365)
One parent	8.2 (411)	7.2 (191)
One parent + stepparent/other	3.5 (175)	3.3 (88)
Childhood physical abuse
Sometimes or more	11.1 (554)	10.6 (281)
Never or rarely	88.9 (4,443)	89.4 (2,363)
Childhood emotional abuse
Sometimes or more	41.7 (2,082)	39.7 (1,049)
Never or rarely	58.3 (2,915)	60.3 (1,595)
Childhood sexual abuse
Once or more	8.9 (445)	3.8 (101)
Never	91.1 (4,552)	96.2 (2,543)
Witness physical abuse
A few times or more	10.1 (507)	6.5 (171)
Never or once	89.9 (4,490)	93.5 (2,473)
Witness emotional abuse
A few times or more	21.9 (1,096)	16.0 (422)
Never or once	78.1 (3,901)	84.0 (2,222)

Note. Percentages may not sum to 100% due to rounding.

Due to the discreteness of the gender nonconformity scores, the top decile group contains slightly greater than 10% of the participants.

Household income is presented with no imputation for missingness (909 females and 446 males missing income).

Participants reporting higher levels of GNC in childhood had higher rates of IPV victimization and perpetration (Table 2). Among females in the top decile of GNC, 48% reported victimization and 19% reported perpetration compared with 41% and 17% for those below median nonconformity. Among males in the top decile, 38% reported victimization and 15% reported perpetration compared with 23% and 6% for those below median nonconformity. At all levels, females reported higher rates of IPV compared with males.

Table 2.

Prevalence of IPV Victimization and Perpetration by Childhood Gender Nonconformity Among Young Adults (Ages 20-27 Years) in the U.S. Growing Up Today Study (N = 7,641).

	Childhood Gender Nonconformity Score, % (n)			p Value^a
	< Median	≥ Median, Below Top Decile	Top Decile (Most Nonconforming)	p Value^a
IPV victimization
Females	40.8 (1,003)	46.3 (801)	47.5 (383)	<.001
Males	23.4 (234)	25.6 (345)	38.0 (114)	<.001
IPV perpetration
Females	17.4 (427)	18.4 (318)	19.2 (155)	.43
Males	5.6 (56)	6.5 (87)	15.3 (46)	<.001

Note. IPV = intimate partner violence.

p values based on χ²-tests.

In unadjusted models (Table 3, column 1), females in the top decile of nonconformity were at elevated risk of IPV victimization (RR = 1.16, 95% CI = [1.06, 1.27]). There was no association between nonconformity and IPV perpetration for females. Males in the top decile of nonconformity were at elevated risk of both IPV victimization (RR = 1.62, 95% CI = [1.35, 1.95]) and perpetration (RR = 2.74, 95% CI = [1.89, 3.98]). After adjustment for covariates, the associations between nonconformity and IPV were attenuated (Table 3, column 2). For females, being in the top decile of nonconformity was not associated with elevated risk of experiencing or perpetrating IPV. However, males in the top decile of nonconformity had 1.4 times greater risk of experiencing IPV victimization (RR = 1.40, 95% CI = [1.15, 1.71]) and 2.3 times greater risk of perpetrating IPV (RR = 2.34, 95% CI = [1.54, 3.56]) compared with those below median nonconformity, adjusting for covariates.

Table 3.

Childhood Gender Nonconformity as a Predictor of IPV Victimization and Perpetration Among Young Adults (Ages 20-27 Years) in the U.S. Growing Up Today Study (N = 7,641).

	Unadjusted	Adjusted ^a
	Risk Ratio (95% CI)
IPV victimization
Females
< Median	1.00	1.00
≥ Median, below top decile	1.13 [1.06, 1.22]***	1.09 [1.02, 1.17]*
Top decile (most nonconforming)	1.16 [1.06, 1.27]***	1.07 [0.98, 1.16]
Males
< Median	1.00	1.00
≥ Median, below top decile	1.10 [0.95, 1.26]	1.07 [0.93, 1.23]
Top decile (most nonconforming)	1.62 [1.35, 1.95]***	1.40 [1.15, 1.71]***
IPV perpetration
Females
< Median	1.00	1.00
≥ Median, below top decile	1.06 [0.93, 1.21]	0.98 [0.86, 1.12]
Top decile (most nonconforming)	1.11 [0.94, 1.31]	0.95 [0.80, 1.12]
Males
< Median	1.00	1.00
≥ Median, below top decile	1.15 [0.82, 1.60]	1.12 [0.80, 1.56]
Top decile (most nonconforming)	2.74 [1.89, 3.98]***	2.34 [1.54, 3.56]***

Note. Multiple imputation implemented to address missingness in household income. IPV = intimate partner violence; CI = confidence interval.

Models adjusted for age at questionnaire return, race, household income, family structure, and sexual orientation identity.

p < .05. **p < .01. ***p < .001.

We did not find support for our hypothesis of partial mediation by childhood abuse in these analyses. All five childhood abuse variables were significantly associated with GNC (p < .001). Although several of the child abuse variables were significantly associated with IPV victimization and perpetration in the adjusted models, there was no significant attenuation of the GNC effect estimates for females or males (Table 4).

Table 4.

Childhood Gender Nonconformity as a Predictor of IPV With Hypothesized Mediation by Childhood Abuse Among Young Adults (Ages 20-27 Years) in the U.S. Growing Up Today Study (N = 7,641).

	IPV Victimization		IPV Perpetration
	Gender Nonconformity	Gender Nonconformity and Childhood Abuse	Gender Nonconformity	Gender Nonconformity and Childhood Abuse
	Risk ratio (95% CI)
Females
Gender nonconformity
< Median	1.00	1.00 (Reference)	1.00	1.00 (Reference)
≥ Median, below top decile	1.09 [1.02, 1.17]*	1.09 [1.02, 1.17]*	0.98 [0.86, 1.12]	0.99 [0.87, 1.12]
Top decile (most nonconforming)	1.07 [0.98, 1.16]	1.04 [0.95, 1.14]	0.95 [0.80, 1.12]	0.89 [0.75, 1.05]
Child abuse before age 11 years
Physical abuse		1.12 [1.02, 1.24]*		1.22 [1.04, 1.44]*
Emotional abuse		1.14 [1.06, 1.23]***		1.46 [1.27, 1.67]***
Sexual abuse		1.26 [1.15, 1.37]***		1.50 [1.29, 1.75]***
Witnessing physical abuse		0.93 [0.83, 1.04]		1.15 [0.95, 1.40]
Witnessing emotional abuse		1.13 [1.04, 1.24]**		1.10 [0.93, 1.30]
Males
Gender nonconformity
< Median	1.00	1.00 (Reference)	1.00	1.00 (Reference)
≥ Median, below top decile	1.07 [0.93, 1.23]	1.08 [0.93, 1.24]	1.12 [0.80, 1.56]	1.13 [0.82, 1.58]
Top decile (most nonconforming)	1.40 [1.15, 1.71]***	1.40 [1.15, 1.71]***	2.34 [1.54, 3.56]***	2.37 [1.57, 3.58]***
Child abuse before age 11 years
Physical abuse		1.27 [1.05, 1.54]*		1.47 [1.00, 2.17]
Emotional abuse		1.30 [1.13, 1.50]***		1.52 [1.10, 2.10]*
Sexual abuse		1.01 [0.75, 1.36]		1.03 [0.54, 1.98]
Witnessing physical abuse		1.06 [0.83, 1.36]		1.47 [0.88, 2.46]
Witnessing emotional abuse		1.17 [0.98, 1.41]		1.07 [0.69, 1.65]

Note. All models adjusted for age at questionnaire return, race, household income, family structure, and sexual orientation identity. IPV = intimate partner violence; CI = confidence interval.

p < .05. **p < .01. ***p < .001.

Discussion

The findings from a large-scale national cohort provide evidence of a relationship between childhood GNC and involvement in IPV in adolescence and early adulthood among males. As hypothesized, young adult males in this study who reported having gender nonconforming (i.e., more feminine) behaviors in childhood were at higher risk of experiencing and perpetrating IPV compared with those below median nonconformity, independent of sexual orientation identity. Although females had substantially higher risk of IPV than males in each category of nonconformity, we found no evidence of a similar association for females in the top decile of GNC. Although most of the prior work on GNC has been conducted among LGB populations (D’Augelli et al., 2006; Ploderl & Fartacek, 2009; Skidmore et al., 2006), this study highlights the unique, independent effect of GNC in patterning IPV among heterosexual and sexual minority male young adults.

The findings of this study are consistent with prior research that individuals who transgress gender norms are vulnerable to discrimination, prejudice, and involvement in violence and aggression in a society with rigid constraints on gender expression (Gordon & Meyer, 2007; Toomey et al., 2014). The minority stress model, which suggests that individuals from stigmatized social categories experience excess stress from a range of stressors (e.g., discrimination, rejection, internalized homophobia, identity concealment) as a result of their minority social position, has been commonly applied to explain sexual orientation disparities in health outcomes and behaviors (Meyer, 2003). The concept of minority stress can apply to gender nonconforming individuals living in a society with narrow gender norms. Such individuals may be subjected to chronic stress related to stigmatization from living outside the norm. The resulting psychological disruption from the stress can lead to anxiety, depression, substance abuse, emotional dysregulation, social isolation, and poor relationship quality, which may contribute to both IPV victimization and perpetration (Hatzenbuehler, 2009). It is important to consider that IPV is often mutual and bidirectional (Langhinrichsen-Rohling, 2010), so risk factors are commonly shared, and minority stress variables have been linked to both victimization and perpetration (Capaldi et al., 2012).

A second stress pathway may link gender nonconformity to IPV perpetration specifically among men. Masculine discrepancy stress suggests men who fail to conform to conventional masculine roles (e.g., strength and self-reliance, emotional control, and pursuit of status and power) may also be at increased risk of IPV perpetration (Berke, Reidy, Gentile, & Zeichner, 2018; Fleming, Gruskin, Rojo, & Dworkin, 2015; Mahalik et al., 2003; Pleck, 1995). When males perceive themselves to be insufficiently masculine, they may experience high levels of discrepancy stress or consider actions of their intimate partners to be threatening to their masculinity, which may cause them to overconform or act out in ways that are stereotypically masculine (e.g., engaging in high-risk sexual behavior or perpetrating IPV) to prove their masculinity (Reidy, Berke, Gentile, & Zeichner, 2014; Reidy, Brookmeyer, Gentile, Berke, & Zeichner, 2016; Vandello & Bosson, 2012). This distress may also confer risk of perpetrating IPV by causing difficulties regulating emotional states, increasing pressure to suppress emotions not considered masculine and instead express emotions through anger (Berke et al., 2019).

Although the null finding for females in the top decile of GNC is consistent with literature that masculinity in females is less negatively perceived than femininity in males (Kane, 2006; Martin, 1990), we expected that nonconformity would still impact female IPV involvement through the minority stress pathway. Furthermore, a prior study found that hypermasculine men were more violent when they perceived that a woman’s behavior violated traditional feminine gender role norms, highlighting the vulnerability of women transgressing norms (Reidy, Shirk, Sloan, & Zeichner, 2009). In addition, nonconformity among females may be related to adherence to masculine norms, which has been linked to bullying behavior, anger and aggression (Gini & Pozzoli, 2006; Kinney, Smith, & Donzella, 2001). It would follow that the nonconforming females would have higher rates of IPV perpetration, but our results are not consistent with this hypothesis.

We also did not find support for our hypothesis that childhood abuse mediates the association between GNC and IPV. Nonconformity in childhood was associated with childhood abuse, as expected, as GNC may be seen as an indicator of homosexuality by family members, regardless of if and how the child identifies their sexual orientation (Kane, 2006). Parents who are uncomfortable with nonconformity or homosexuality in their children may be more likely to be abusive (Roberts et al., 2012a). However, the elevated risk of abuse for nonconforming children did not explain the relationship between GNC and IPV. In addition to the stress pathways, there may be other pathways that future research should explore as mediators, including increased substance abuse for nonconforming youth, increased peer bullying, decreased self-esteem, or decreased relationship quality due to social stigma.

Although this is the largest study to examine the contributions of GNC to IPV, the findings must be considered in light of several limitations. First, the study relied on retrospective reporting of childhood GNC, IPV, and child abuse, which may be susceptible to recall bias. The measure of GNC focused only on expression up to age 11 years, so there was no information on changes over time or expression at the time of IPV; however, at least one prior study found a positive correlation between self-reported nonconformity in childhood and adulthood, suggesting that nonconformity can be a stable trait (Rieger, Linsenmeier, Gygax, & Bailey, 2008). Importantly, gender identity was not collected by 2007 when IPV was assessed so we were not able to identify transgender participants or examine their experiences of violence.

For reporting of IPV, social desirability bias may be present. Still, research suggests that while high social desirability bias may lead to a small decrease in reports of IPV, the distortion is likely minimal (Bell & Naugle, 2007; Visschers, Jaspaert, & Vervaeke, 2015). Response bias may also be at play—individuals willing to describe their childhood behaviors as gender nonconforming may also be more willing to report IPV compared with individuals not willing to describe their behaviors as nonconforming. This may be especially true for males reporting victimization, since conformity to masculinity is a barrier to disclosing and help-seeking (Simmons, Bruggemann, & Swahnberg, 2016). In addition, sample size precluded us from stratifying by type of IPV (e.g., physical, sexual, or emotional/psychological), severity of IPV, and overlap of IPV victimization and perpetration (e.g., whether individuals were at risk of being only a victim or perpetrator of IPV or both). Although we were able to stratify by gender, we were unable to additionally stratify results by sexual orientation, a critical intersection for future studies to address. Finally, generalizability may be limited as the sample is not nationally representative as it comprises children of nurses who are predominantly White.

Conclusion

These findings from a large-scale national study highlight both the vulnerability of young adult males who do not conform to societal gender norms and the importance of studying gender expression as a determinant of violence. Independent of sexual orientation, GNC is an important risk indicator for IPV among young adult males. Building support for diverse gender expression in childhood (e.g., through the establishment of inclusive policies in institutions such as schools) and changing socially constructed gender norms may improve health outcomes. Furthermore, while the visibility of GNC places individuals at risk of IPV, these behaviors may present opportunities for pediatricians, teachers, and parents to identify children at risk, providing an avenue for prevention. Efficacy of existing IPV prevention programs should be tested among nonconforming youth, and may be improved with more explicit focus on gender expression and masculine socialization. Further research which examines pathways between GNC and IPV separately for males and females, and whether health consequences of IPV differ by conformity, in addition to research in more demographically diverse populations, is needed to build a more comprehensive understanding of the unique experiences of gender nonconforming youth.

Footnotes

Acknowledgements

We acknowledge the Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital, and Harvard Medical School for the management of Growing Up Today Study (GUTS). We would also like to express gratitude and appreciation to the team of GUTS investigators and the thousands of GUTS participants across the country.

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 in part by grants R01 HD057368 and R01 HD066963 from the National Institutes of Health (NIH). S. B. Austin is supported by the Leadership Education in Adolescent Health project, Maternal and Child Health Bureau, Health Resources and Services Administration grants T71-MC00009 and T76-MC00001. A. R. Gordon is supported by NIH grant F32 DA042505.

ORCID iD

Avanti Adhia

Author Biographies

Avanti Adhia is a doctoral candidate in the Department of Social and Behavioral Sciences at the Harvard T.H. Chan School of Public Health with a concentration in Women, Gender, and Health. She holds a Bachelor of Science in applied mathematics from Columbia University. Her research interests are in social epidemiology and are centered on interpersonal violence victimization and perpetration. She is specifically interested in the causes and consequences of intimate partner violence, gender-based violence (e.g., sexual assault), and child abuse.

Allegra R. Gordon is research faculty in the Division of Adolescent and Young Adult Medicine at Boston Children’s Hospital and Harvard Medical School. She earned her doctorate in Social Epidemiology with a concentration in Women, Gender, and Health at the Harvard T.H. Chan School of Public Health. She holds an MPH in sociomedical sciences, with a concentration in Sexuality and Health, from Columbia University and a BA in Education & Environmental Studies from Swarthmore College. Her research interests relate to the mental and physical health impacts of discrimination and the effects of gender norms on the health of young people.

Andrea L. Roberts is a research scientist in the Department of Environmental Health at the Harvard T.H. Chan School of Public Health. Her research focuses on mental health, including causes and consequences of autism, posttraumatic stress disorder (PTSD), and depression. She also studies the psychological, behavioral, and physical health outcomes of trauma and stress, including PTSD, depression, intimate partner violence, and health-risk behaviors. She is interested in gender nonconformity and sexual orientation as risk factors for abuse and trauma. She is also particularly interested in the effects of trauma on health across generations.

Garrett M. Fitzmaurice is a professor in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health and professor of Psychiatry (Biostatistics) at the Harvard Medical School. He is also Director of the Laboratory for Psychiatric Biostatistics at McLean Hospital. His research interests are in methods for analyzing longitudinal and repeated measures data. A major focus of his methodological research has been on developing statistical methods for analyzing repeated binary data and for handling the problems of attrition and missing data in longitudinal studies. Much of his research has concentrated on applications to mental health research.

David Hemenway is a professor in the Department of Health Policy and Management and Director of the Harvard Injury Control Research Center at the Harvard T.H. Chan School of Public Health. He has written widely on injury prevention, including on firearms, violence, suicide, child abuse, motor vehicle crashes, fires, falls, and fractures. He headed the pilot for the National Violent Death Reporting System, which provides detailed information on suicide and homicide. In 2012, he was recognized by the Centers for Disease Control & Prevention as one of the “twenty most influential injury and violence professionals over the past twenty years.”

S. Bryn Austin is a faculty member at the Harvard T.H. Chan School of Public Health and the director of Fellowship Research Training in the Division of Adolescent and Young Adult Medicine at Boston Children’s Hospital. She is also director of the Strategic Training Initiative for the Prevention of Eating Disorders: A Public Health Incubator at the Harvard Chan School and Boston Children’s Hospital. Dr. Austin’s research interests include lesbian, gay, bisexual, and transgender adolescent health and addressing social and physical environmental influences on physical activity, nutritional patterns, and eating disorders risk in school and community settings.

References

Banyard

V. L.

Cross

(2008). Consequences of teen dating violence: Understanding intervening variables in ecological context. Violence Against Women, 14, 998-1013. doi:10.1177/1077801208322058

Bell

K. M.

Naugle

A. E.

(2007). Effects of social desirability on students’ self-reporting of partner abuse perpetration and victimization. Violence and Victims, 22, 243-256.

Berke

D. S.

Reidy

D. E.

Gentile

Zeichner

(2019). Masculine discrepancy stress, emotion-regulation difficulties, and intimate partner violence. Journal of Interpersonal Violence, 34(6), 1163-1182.

Bernstein

D. P.

Fink

Handelsman

Foote

Lovejoy

Wenzel

. . . Ruggiero

(1994). Initial reliability and validity of a new retrospective measure of child abuse and neglect. The American Journal of Psychiatry, 151, 1132-1136. doi:10.1176/ajp.151.8.1132

Bonomi

A. E.

Anderson

M. L.

Nemeth

Rivara

F. P.

Buettner

(2013). History of dating violence and the association with late adolescent health. BMC Public Health, 13, Article 821. doi:10.1186/1471-2458-13-821

Breiding

M. J.

Smith

S. G.

Basile

K. C.

Walters

M. L.

Chen

Merrick

M. T.

(2014). Prevalence and characteristics of sexual violence, stalking, and intimate partner violence victimization—National intimate partner and sexual violence survey, United States, 2011. MMWR Surveillance Summaries, 63(8), 1-18.

Calzo

J. P.

Roberts

A. L.

Corliss

H. L.

Blood

E. A.

Kroshus

Austin

S. B.

(2014). Physical activity disparities in heterosexual and sexual minority youth ages 12-22 years old: Roles of childhood gender nonconformity and athletic self-esteem. Annals of Behavioral Medicine, 47, 17-27. doi:10.1007/s12160-013-9570-y

Capaldi

D. M.

Knoble

N. B.

Shortt

J. W.

Kim

H. K.

(2012). A systematic review of risk factors for intimate partner violence. Partner Abuse, 3, 231-280. doi:10.1891/1946-6560.3.2.231

Dank

Lachman

Zweig

J. M.

Yahner

(2014). Dating violence experiences of lesbian, gay, bisexual, and transgender youth. Journal of Youth and Adolescence, 43, 846-857. doi:10.1007/s10964-013-9975-8

10.

D’Augelli

A. R.

Grossman

A. H.

Starks

M. T.

(2006). Childhood gender atypicality, victimization, and PTSD among lesbian, gay, and bisexual youth. Journal of Interpersonal Violence, 21, 1462-1482. doi:10.1177/0886260506293482

11.

D’Haese

Dewaele

Van Houtte

(2016). The relationship between childhood gender nonconformity and experiencing diverse types of homophobic violence. Journal of Interpersonal Violence, 31, 1634-1660. doi:10.1177/0886260515569063

12.

Exner-Cortens

Eckenrode

Rothman

(2013). Longitudinal associations between teen dating violence victimization and adverse health outcomes. Pediatrics, 131, 71-78. doi:10.1542/peds.2012-1029

13.

Field

A. E.

Camargo

C. A.

Taylor

C. B.

Jr. Berkey

C. S.

Frazier

A. L.

Gillman

M. W.

Colditz

G. A.

(1999). Overweight, weight concerns, and bulimic behaviors among girls and boys. Journal of the American Academy of Child and Adolescent Psychiatry, 38, 754-760. doi:10.1097/00004583-199906000-00024

14.

Fleming

P. J.

Gruskin

Rojo

Dworkin

S. L.

(2015). Men’s violence against women and men are inter-related: Recommendations for simultaneous intervention. Social Science & Medicine, 146, 249-256. doi:10.1016/j.socscimed.2015.10.021

15.

Foshee

V. A.

Gottfredson

N. C.

Reyes

H. L.

Chen

M. S.

David-Ferdon

Latzman

N. E.

. . . Ennett

S. T.

(2016). Developmental outcomes of using physical violence against dates and peers. The Journal of Adolescent Health, 58, 665-671. doi:10.1016/j.jadohealth.2016.03.002

16.

Foshee

V. A.

Reyes

H. L.

Gottfredson

N. C.

Chang

L. Y.

Ennett

S. T.

(2013). A longitudinal examination of psychological, behavioral, academic, and relationship consequences of dating abuse victimization among a primarily rural sample of adolescents. The Journal of Adolescent Health, 53, 723-729. doi:10.1016/j.jadohealth.2013.06.016

17.

Friedman

M. S.

Koeske

G. F.

Silvestre

A. J.

Korr

W. S.

Sites

E. W.

(2006). The impact of gender-role nonconforming behavior, bullying, and social support on suicidality among gay male youth. The Journal of Adolescent Health, 38, 621-623. doi:10.1016/j.jadohealth.2005.04.014

18.

Gini

Pozzoli

(2006). The role of masculinity in children’s bullying. Sex Roles, 54, 585-588.

19.

Gordon

A. R.

Krieger

Okechukwu

C. A.

Haneuse

Samnaliev

Charlton

B. M.

Austin

S. B.

(2017). Decrements in health-related quality of life associated with gender nonconformity among U.S. adolescents and young adults. Quality of Life Research, 26, 2129-2138. doi:10.1007/s11136-017-1545-1

20.

Gordon

A. R.

Meyer

I. H.

(2007). Gender nonconformity as a target of prejudice, discrimination, and violence against LGB individuals. Journal of LGBT Health Research, 3, 55-71.

21.

Hatzenbuehler

M. L.

(2009). How does sexual minority stigma “get under the skin”? A psychological mediation framework. Psychological Bulletin, 135, 707-730. doi:10.1037/a0016441

22.

Horton

N. J.

Kleinman

K. P.

(2007). Much ado about nothing: A comparison of missing data methods and software to fit incomplete data regression models. The American Statistician, 61, 79-90. doi:10.1198/000313007X172556

23.

Johnson

W. L.

Giordano

P. C.

Longmore

M. A.

Manning

W. D.

(2014). Intimate partner violence and depressive symptoms during adolescence and young adulthood. Journal of Health and Social Behavior, 55, 39-55. doi:10.1177/0022146513520430

24.

Kane

E. W.

(2006). “No way my boys are going to be like that!” Parents’ responses to children’s gender nonconformity. Gender & Society, 20, 149-176.

25.

Kinney

T. A.

Smith

B. A.

Donzella

(2001). The influence of sex, gender, self-discrepancies, and self-awareness on anger and verbal aggressiveness among U.S. college students. The Journal of Social Psychology, 141, 245-275. doi:10.1080/00224540109600550

26.

Langhinrichsen-Rohling

(2010). Controversies involving gender and intimate partner violence in the United States. Sex Roles, 62, 179-193.

27.

Mahalik

J. R.

Locke

B. D.

Ludlow

L. H.

Diemer

M. A.

Scott

R. P. J.

Gottfried

Freitas

(2003). Development of the conformity to Masculine Norms Inventory. Psychology of Men and Masculinity, 4, 3-25.

28.

Martin

C. L.

(1990). Attitudes and expectations about children with nontraditional and traditional gender roles. Sex Roles, 22, 151-166.

29.

McFarlane

Parker

Soeken

Bullock

(1992). Assessing for abuse during pregnancy: Severity and frequency of injuries and associated entry into prenatal care. Journal of the American Medical Association, 267, 3176-3178.

30.

Meyer

I. H.

(2003). Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: Conceptual issues and research evidence. Psychological Bulletin, 129, 674-697. doi:10.1037/0033-2909.129.5.674

31.

Nahapetyan

Orpinas

Song

Holland

(2014). Longitudinal association of suicidal ideation and physical dating violence among high school students. Journal of Youth and Adolescence, 43, 629-640. doi:10.1007/s10964-013-0006-6

32.

Pleck

J. H.

(1995). The gender role strain paradigm: An update. In Levant

R. F.

Pollack

W. S.

(Eds.), A new psychology of men (pp. 11-32). New York, NY: Basic Books.

33.

Ploderl

Fartacek

(2009). Childhood gender nonconformity and harassment as predictors of suicidality among gay, lesbian, bisexual, and heterosexual Austrians. Archives of Sexual Behavior, 38, 400-410. doi:10.1007/s10508-007-9244-6

34.

Reidy

D. E.

Berke

D. S.

Gentile

Zeichner

(2014). Man enough? Masculine discrepancy stress and intimate partner violence. Personality and Individual Differences, 68, 160-164.

35.

Reidy

D. E.

Brookmeyer

K. A.

Gentile

Berke

D. S.

Zeichner

(2016). Gender role discrepancy stress, high-risk sexual behavior, and sexually transmitted disease. Archives of Sexual Behavior, 45, 459-465. doi:10.1007/s10508-014-0413-0

36.

Reidy

D. E.

Shirk

S. D.

Sloan

C. A.

Zeichner

(2009). Men who aggress against women: Effects of feminine gender role violation on physical aggression in hypermasculine men. Psychology of Men & Masculinity, 10(1), 1-12.

37.

Remafedi

Farrow

J. A.

Deisher

R. W.

(1991). Risk factors for attempted suicide in gay and bisexual youth. Pediatrics, 87, 869-875.

38.

Remafedi

Resnick

Blum

Harris

(1992). Demography of sexual orientation in adolescents. Pediatrics, 89(Suppl. 4), 714-721.

39.

Reuter

T. R.

Newcomb

M. E.

Whitton

S. W.

Mustanski

(2017). Intimate partner violence victimization in LGBT young adults: Demographic differences and associations with health behaviors. Psychology of Violence, 7, 101-109. doi:10.1037/vio0000031

40.

Rieger

Linsenmeier

J. A.

Gygax

Bailey

J. M.

(2008). Sexual orientation and childhood gender nonconformity: Evidence from home videos. Developmental Psychology, 44, 46-58. doi:10.1037/0012-1649.44.1.46

41.

Rieger

Savin-Williams

R. C.

(2012). Gender nonconformity, sexual orientation, and psychological well-being. Archives of Sexual Behavior, 41, 611-621. doi:10.1007/s10508-011-9738-0

42.

Roberts

A. L.

Rosario

Corliss

H. L.

Koenen

K. C.

Austin

S. B.

(2012a). Childhood gender nonconformity: A risk indicator for childhood abuse and posttraumatic stress in youth. Pediatrics, 129, 410-417. doi:10.1542/peds.2011-1804

43.

Roberts

A. L.

Rosario

Corliss

H. L.

Koenen

K. C.

Austin

S. B.

(2012b). Elevated risk of posttraumatic stress in sexual minority youths: Mediation by childhood abuse and gender nonconformity. American Journal of Public Health, 102, 1587-1593. doi:10.2105/AJPH.2011.300530

44.

Roberts

A. L.

Rosario

Slopen

Calzo

J. P.

Austin

S. B.

(2013). Childhood gender nonconformity, bullying victimization, and depressive symptoms across adolescence and early adulthood: An 11-year longitudinal study. Journal of the American Academy of Child and Adolescent Psychiatry, 52, 143-152. doi:10.1016/j.jaac.2012.11.006

45.

Roberts

T. A.

Klein

J. D.

Fisher

(2003). Longitudinal effect of intimate partner abuse on high-risk behavior among adolescents. Archives of Pediatrics & Adolescent Medicine, 157, 875-881. doi:10.1001/archpedi.157.9.875

46.

Rosario

Reisner

S. L.

Corliss

H. L.

Wypij

Frazier

A. L.

Austin

S. B.

(2014). Disparities in depressive distress by sexual orientation in emerging adults: The roles of attachment and stress paradigms. Archives of Sexual Behavior, 43, 901-916. doi:10.1007/s10508-013-0129-6

47.

Rothman

E. F.

Exner

Baughman

A. L.

(2011). The prevalence of sexual assault against people who identify as gay, lesbian, or bisexual in the United States: A systematic review. Trauma, Violence & Abuse, 12, 55-66. doi:10.1177/1524838010390707

48.

Simmons

Bruggemann

A. J.

Swahnberg

(2016). Disclosing victimisation to healthcare professionals in Sweden: A constructivist grounded theory study of experiences among men exposed to interpersonal violence. BMJ Open, 6(6), e010847. doi:10.1136/bmjopen-2015-010847

49.

Skidmore

W. C.

Linsenmeier

J. A.

Bailey

J. M.

(2006). Gender nonconformity and psychological distress in lesbians and gay men. Archives of Sexual Behavior, 35, 685-697. doi:10.1007/s10508-006-9108-5

50.

Smith

P. H.

White

J. W.

Holland

L. J.

(2003). A longitudinal perspective on dating violence among adolescent and college-age women. American Journal of Public Health, 93, 1104-1109.

51.

Spiegelman

Hertzmark

(2005). Easy SAS calculations for risk or prevalence ratios and differences. American Journal of Epidemiology, 162, 199-200. doi:10.1093/aje/kwi188

52.

Straus

M. A.

Hamby

S. L.

Boney-McCoy

Sugarman

D. B.

(1996). The revised Conflict Tactics Scales (CTS2). Journal of Family Issues, 17, 283-316.

53.

Straus

M. A.

Hamby

S. L.

Finkelhor

Moore

D. W.

Runyan

(1998). Identification of child maltreatment with the Parent–Child Conflict Tactics Scales: Development and psychometric data for a national sample of American parents. Child Abuse & Neglect, 22, 249-270.

54.

Toomey

R. B.

Card

N. A.

Casper

D. M.

(2014). Peers’ perceptions of gender nonconformity: Associations with overt and relational peer victimization and aggression in early adolescence. The Journal of Early Adolescence, 34, 463-485. doi:10.1177/0272431613495446

55.

Toomey

R. B.

Ryan

Diaz

R. M.

Card

N. A.

Russell

S. T.

(2010). Gender-nonconforming lesbian, gay, bisexual, and transgender youth: School victimization and young adult psychosocial adjustment. Developmental Psychology, 46, 1580-1589. doi:10.1037/a0020705

56.

Vagi

K. J.

Rothman

E. F.

Latzman

N. E.

Tharp

A. T.

Hall

D. M.

Breiding

M. J.

(2013). Beyond correlates: A review of risk and protective factors for adolescent dating violence perpetration. Journal of Youth and Adolescence, 42, 633-649. doi:10.1007/s10964-013-9907-7

57.

Vandello

J. A.

Bosson

J. K.

(2012). Hard won and easily lost: A review and synthesis of theory and research on precarious manhood. Psychology of Men & Masculinity, 14, 101-113.

58.

Visschers

Jaspaert

Vervaeke

(2015). Social desirability in intimate partner violence and relationship satisfaction reports: An exploratory analysis. Journal of Interpersonal Violence, 32, 1401-1420. doi:10.1177/0886260515588922

59.

Yuan

(2011). Multiple imputation using SAS software. Journal of Statistical Software, 45(6), 1-25.

60.

Zeger

S. L.

Liang

K. Y.

(1986). Longitudinal data analysis for discrete and continuous outcomes. Biometrics, 42, 121-130.

61.

Zou

(2004). A modified poisson regression approach to prospective studies with binary data. American Journal of Epidemiology, 159, 702-706.

62.

Zucker

K. J.

Mitchell

Bradley

Tkachuk

Cantor

Allin

(2006). The recalled childhood gender identity/gender role questionnaire: Psychometric properties. Sex Roles, 54, 469-483.

63.

Zucker

K. J.

Wood

(2011). Assessment of gender variance in children. Child and Adolescent Psychiatric Clinics of North America, 20, 665-680. doi:10.1016/j.chc.2011.07.00