Exploring Multiple Forms of Intimate Partner Violence in a Gender and Racially/Ethnically Diverse Sample of Transgender Adults

Abstract

Intimate partner violence (IPV) is highly prevalent in transgender (trans) populations in the United States; however, details about its manifestations and correlates have not been well captured. Using data from the 2015 U.S. Transgender Survey, we analyzed weighted data from 23,999 adult transgender participants to estimate the prevalence and explore correlates of five IPV subtypes: psychological IPV, physical IPV, trans-related IPV, stalking, and forced sex committed by an intimate partner. Regression models examined race/ethnicity, gender identity, past-year incarceration, past-year sex work, and lifetime homelessness, and adjusted for annual household income, highest level of education, age, birthplace, Census region, and relationship status. The sample was racially/ethnically diverse (62.6% White, 0.7% Alaskan Native/American Indian, 4.7% Asian/Native Hawaiian/Pacific Islander, 12.7% Black/African American, 16.5% Latinx/Hispanic, 0.4% Middle Eastern/North African, 2.5% Multiracial/Not Listed), and comprised of 31.2% transgender men, 34.2% transgender women, 27.5% assigned-female-at-birth nonbinary participants, and 7.1% assigned-male-at-birth nonbinary participants. Rates of IPV were high, with variability by IPV subtype: 42.0% endorsed psychological IPV, 39.9% endorsed physical IPV, 30.4% endorsed trans-related IPV, 18.0% endorsed stalking, and 21.5% endorsed forced sex by an intimate partner. We observed disparities in IPV subtypes by race/ethnicity, gender identity, and experiences of social marginalization. Results highlight the need for targeted, trans-inclusive IPV screening practices and interventions. Future studies should examine the syndemic effects of IPV, social marginalization, and health outcomes related to HIV, substance use, and mental health in trans populations.

Keywords

transgender nonbinary intimate partner violence gender-based violence disparities

Introduction

The emerging literature on IPV in transgender populations demonstrates that across the lifespan, trans populations are significantly more likely to experience IPV when compared with general cisgender samples and sexual minority cisgender people (Dank, Lachman, Zweig, & Yahner, 2014; Langenderfer-Magruder, Whitfield, Walls, Kattari, & Ramos, 2016; Sterzing, Ratliff, Gartner, McGeough, & Johnson, 2017; Valentine et al., 2017). Within trans populations, the 2015 U.S. Transgender Survey (USTS) provides arguably the most accurate estimates of intimate partner violence (IPV) prevalence. Among the 27,715 participants in this survey, 54% reported experiencing some form of IPV throughout their lives. The report highlighted the need for policies to address violence in trans populations and for further work to understand disparities in IPV for trans people of color, sex workers, and those with a history of sex work, and people with a history of homelessness (James et al., 2016).

Previous studies of IPV in trans populations have not consistently differentiated between IPV subtypes or captured forms of IPV unique to trans people. The Center for Disease Control and Prevention’s (CDC) National Intimate Partner and Sexual Violence Survey (NISVS) categorizes IPV into five subtypes: physical violence, psychological aggression, sexual violence, stalking, and control of reproductive or sexual health; none of the identified studies on IPV in trans populations acknowledged or measured all five types (Black et al., 2011; Smith et al., 2018). Legal and social science research has documented forms of IPV specific to trans people’s gender identity or presentation, which include emotional abuse that seeks to exacerbate gender dysphoria, controlling access to transition-related medical care, and threatening to out a trans partner (Cook-Daniels, 2015; Goodmark, 2013; Mizock & Lewis, 2008; Yerke & DeFeo, 2016). However, to our knowledge, just one known published study has measured trans-specific IPV within the United States by asking participants whether their partner belittled them because of their gender identity and whether their partner made them do something that did not agree with their gender identification (Garthe et al., 2018). This study did not include measures of physical or sexual IPV specific to trans people, and, thus, was unable to differentiate between different types of IPV experiences or capture the full spectrum of trans-related IPV.

The primary goal of this study is to identify and describe patterns of IPV subtypes among trans respondents in the USTS. The USTS includes general items about physical violence, psychological violence, sexual violence, and stalking by an intimate partner as well as items about IPV specific to trans people, which permits examination and differentiation of specific IPV subtypes in accordance with previous CDC research (Black et al., 2011; Smith et al., 2018).

Second, this study seeks to examine patterns of IPV exposure regarding race/ethnicity, gender identity, and social marginalization indicators among trans respondents. While the USTS report provides data on some of these potential correlates, the study did not test for statistical significance, examine multiple types of IPV, or conduct multivariate analyses controlling for potentially confounding variables underlying prevalence differences.

Previous research, including analysis of the USTS, has explored associations between race/ethnicity and experience of IPV in U.S. trans adults. In the USTS, the prevalence of IPV among American Indian (73%), Black (56%), Latinx (54%), Middle Eastern (62%), and multiracial (62%) USTS participants was higher than that among White participants (54%; James et al., 2016). A study of trans women with a history of sex work found that race/ethnicity was associated with physical assault by a primary partner in bivariable analyses (Nemoto, Bodeker, & Iwamoto, 2011). However, studies of sexual minority cisgender men and heterosexual cisgender women have not found consistent significant differences between participants of color and White participants when controlling for income and education (Bent-Goodley, 2007; Finneran & Stephenson, 2013; Rennison & Planty, 2003). In two studies of trans youth, race/ethnicity was not associated with IPV when adjusting for socioeconomic variables (Garthe et al., 2018; Goldenberg, Jadwin-Cakmak, & Harper, 2018). Therefore, multivariable analyses are needed to determine if the racial/ethnic disparities in IPV reported in the USTS are explained by socioeconomic variables.

The USTS report did not disaggregate IPV data by assigned sex at birth or gender identity, which might obscure important differences in IPV experiences in this large survey. Previous studies found higher rates of IPV in trans women compared with trans men using data gathered from electronic medical records and face-to-face interviews (Brown & Herman, 2015; Valentine et al., 2017). However, a study of trans youth found that there were no significant differences in odds of IPV among trans feminine, trans masculine, and gender nonconforming participants (Goldenberg et al., 2018). The USTS dataset includes adults across the trans spectrum, which provides an opportunity to examine the prevalence of IPV by gender identity.

In addition to the roles of race/ethnicity and gender identity as key demographics associated with IPV, there are indications that IPV might be associated with different forms of social marginalization such as incarceration, sex work, and homelessness among trans populations. Among participants in the USTS, 77% of those with a history of sex work and 72% of those with a history of homelessness reported having experienced IPV, though the prevalence of IPV among those with a history of incarceration was not reported (James et al., 2016). Research with trans youth suggests that a history of incarceration, sex work, and homelessness are associated with IPV experience (Brennan et al., 2012; Goldenberg et al., 2018). Furthermore, an analysis of syndemics among trans populations suggests that, conceptually, IPV and indicators of social marginalization are mutually reinforcing (Poteat, Scheim, Xavier, Reisner, & Baral, 2016). However, quantitative analyses have not yet shown whether these experiences of social marginalization are associated with IPV among trans adults.

In sum, the overarching goal of this study is to depict how IPV affects trans people in the United States through exploratory analysis of the IPV data collected by the USTS. Aside from providing more detail on the findings from this large dataset, our results can inform the development of targeted interventions related to IPV and common co-occurring health concerns in trans populations.

Method

Data

This is a secondary analysis of the 2015 USTS. The USTS used purposive sampling techniques to recruit adult trans people (ages 18 and older) living in the United States to take a one-time online survey. Participant selection, procedures, and measures are described in full detail elsewhere (James et al., 2016). Briefly, outreach efforts were conducted through a network of community-based organizations serving trans individuals to recruit people of color, older adults, people living in rural areas, and low-income individuals who may otherwise be underrepresented in an online sample. Recruitment efforts achieved a sample of 27,715 participants, which is the largest known survey sample of trans adults within the United States.

Measures

We analyzed IPV patterns by a wide array of demographic characteristics including race/ethnicity, gender identity, household income, education, age, birthplace, Census region, and relationship status.

Participants could report their race as White, Alaskan Native/American Indian, Asian/Pacific Islander, Black/African American, Latinx/Hispanic, or Middle Eastern/North African. We grouped participants reporting more than one race or some other race into a “Multiracial/Race Not Listed” category.

USTS participants answered questions about their assigned sex at birth and specific gender identity. Based on these responses, participants were categorized into four gender identity groups: trans men, trans women, assigned female at birth (AFAB) nonbinary people, and assigned male at birth (AMAB) nonbinary people. “Nonbinary” is an umbrella term describing those whose gender is not exclusively male or female, including those who identify with more than one gender, as no gender, or with a gender other than male or female (James et al., 2016).

The USTS combined participants’ answers to questions about their individual income and the income of other people living in their home into a measure of annual household income that we categorized into five levels. Education was categorized into four groups: college graduate, some college or associate degree, high school graduate, or general educational development (GED) recipient, and not a high school graduate. Age was categorized to capture older youth (18-24), younger adults (25-44), middle-aged adults (45-64), and older adults (65+).

Participants reported their citizenship status based on the following survey options: natural-born U.S. citizen, naturalized citizen, documented immigrant, or undocumented immigrant. We dichotomized these responses to distinguish participants born outside or inside the United States. Participants reported their current state of residence, and we subsequently categorized participants into one of the four U.S. Census regions. Finally, based on self-reported marital/relationship status, we created a dichotomous variable according to whether participants were in a relationship at the time of the survey. Participants “not in a relationship” included those who reported their marital status as single, a romantic/not active/platonic, divorced, or widowed. Participants “in a relationship” reported their status as partnered (living or not living together), open relationship, or poly.

In addition to these demographic characteristics, we analyzed IPV by three indicators of social marginalization: incarceration, sex work, and homelessness (Brennan et al., 2012). All three variables were dichotomous. Participants were considered to have experienced incarceration in the past year if they reported being held in a jail, prison, or juvenile detention during that time. Participants were considered to have had a past-year experience with sex work if they reported working in the sex industry or engaging in sex or sexual activity for money, food, shelter, drugs, safety/protection, a job/employment, transportation, or another good/service in the past year. Finally, participants were considered to have experienced lifetime homelessness if they reported ever being homeless, including staying in a shelter, living on the street, living in a car, or living somewhere temporarily because of an inability to afford housing.

Our outcome of interest was IPV. The USTS asked participants who reported having ever been in a romantic or sexual relationship 24 questions about specific forms of IPV throughout their lives. In keeping with the subtypes of IPV defined by the NISVS, we categorized these items into dichotomous lifetime measures of physical IPV (9 items, α = .79), psychological IPV (10 items, α = .88), stalking (one item), and forced sex (one item; Table 1). The USTS also included three items about IPV specific to trans people (e.g., “Have any of your romantic or sexual partners told you you weren’t a real man/woman?”), which we collapsed into a single dichotomous variable indicating any trans-related IPV.

Table 1.

Categorization of IPV Items, 2015 USTS.

Physical IPV: Have any of your romantic or sexual partners ever . . .?

• Slapped you?
• Pushed or shoved you?
• Hit you with a fist/something hard?
• Kicked you?
• Hurt you by pulling your hair?
• Slammed you against something?
• Tried to choke/suffocate you?
• Beaten you?
• Burned you on purpose?
• Used a knife or gun on you?

Psychological IPV: Have any of your romantic or sexual partners ever . . .?

• Tried to keep you from seeing family/friends?
• Kept you from having your own money?
• Kept you from leaving the house?
• Hurt someone you love?
• Threatened to hurt/take away pet?
• Wouldn’t let you have other meds?
• Threatened to call the police on you?
• Threatened to use your immigration status?
• Made threats to physically harm you?

Trans-Related IPV: Have any of your romantic or sexual partners ever . . .?

• Wouldn’t let you have your hormones?
• Threatened to out you?
• Told you you weren’t a real woman/man?

Stalking: Have any of your romantic or sexual partners ever . . .?

• Stalked you?

Forced Sex: Have any of your romantic or sexual partners ever . . .?

• Forced sexual activity?

Note. USTS = U.S. Transgender Survey; IPV = intimate partner violence.

Analysis

We analyzed the univariable distribution of the sample across all exposure variables. Reported results show weighted proportions that account for the complex survey design, which included U.S. population-based weightings regarding race/ethnicity, age, and education. We restricted the analysis to participants who completed any of the 24 items about IPV, which were asked of participants who reported ever having had a romantic or sexual partner in their lifetime. We also restricted our sample to only participants who reported living in the 50 U.S. states and who identified with one of the four gender identity groups: trans men, trans women, AFAB nonbinary people, and AMAB nonbinary people.

We analyzed the bivariable distribution of all exposure variables across each IPV outcome and reported this information by weighted proportion. Finally, we developed multivariable logistic regression models to determine the relationship between the exposures and each of the five IPV outcomes. The exposures entered in each model were race/ethnicity, gender identity, past-year incarceration, past-year sex work, lifetime homelessness, household income, education, age, birthplace, Census region, and relationship status. By including all exposures of interest, analyses were able to delineate the unique statistical contribution of each variable to the model (e.g., whether associations between race/ethnicity and IPV persisted once controlling for confounders). Participants who were missing data on any of these variables were not included in the regression models. Results reported in text focus on associations between IPV and the primary exposures of interest: race/ethnicity, gender identity, and social marginalization indictors.

Regressions accounted for complex survey design. Results describe weighted proportions for each variable as well as odds ratios (ORs) and 95% confidence intervals (CI). Groups with the lowest IPV prevalence were selected as reference groups for multivariable analyses.

Results

Sample

The final sample included 23,999 participants. In the weighted sample, most participants identified as White (62.6), followed by Latinx/Hispanic (16.5%), Black/African American (12.7%), Asian/Pacific Islander (4.7%), and Multiracial/Race Not Listed (2.5%). Less than 1% of the sample identified as Alaskan Native/American Indian or Middle Eastern/North African (Table 2).

Table 2.

Sample Characteristics, 2015 U.S. Transgender Survey, N = 23,999.

	Weighted % (Unweighted N)
Race/Ethnicity
White	62.6 (19,666)
Alaskan Native/American Indian	0.7 (297)
Asian/Native Hawaiian/Pacific Islander	4.7 (620)
Black/African American	12.7 (684)
Latinx/Hispanic	16.5 (1,257)
Middle Eastern/North African	0.4 (118)
Multiracial/Race Not Listed	2.5 (1,357)
Gender Identity
Trans man	31.2 (7,258)
Trans woman	34.2 (8,264)
AFAB nonbinary	27.5 (6,731)
AMAB nonbinary	7.1 (1,746)
Annual Household Income^a
>$100,000	14.3 (3,604)
$50,000-$99,999	21.7 (5,440)
$25,000-$49,999	21.2 (4,998)
$10,000-$24,999	18.8 (4,460)
<$9,999	16.3 (3,533)
Highest Level of Education
College graduate	39.0 (9,474)
Some college or associate degree	48.8 (11,042)
HS graduate/GED	10.0 (2,776)
Not a HS graduate	2.2 (707)
Age
65+	2.1 (580)
45-64	13.8 (3,561)
25-44	44.2 (10,100)
18-24	40.0 (9,758)
Birthplace
United States	94.2 (23,131)
Outside United States	5.8 (868)
Census Region
Northeast	20.7 (4,978)
Midwest	18.7 (4,937)
South	29.2 (6,575)
West	31.4 (7,509)
Relationship Status^a
Not in a relationship	44.3 (10,365)
In a relationship	54.1 (13,262)
Past-Year Incarceration^a
No	98.1 (23,624)
Yes	1.7 (333)
Past-Year Sex Work^a
No	91.7 (22,329)
Yes	6.3 (1,253)
Lifetime Homelessness^a
No	67.5 (16,577)
Yes	32.3 (7,377)
Intimate Partner Violence
Psychological	42.0 (9,937)
Physical	39.9 (9,329)
Trans-Related	30.4 (7,195)
Stalking	18.0 (4,257)
Forced Sex	21.5 (5,266)

Note. AFAB = assigned female at birth; AMAB = assigned male at birth; HS = high school; GED = general educational equivalent.

Percentages do not add to 100 to reflect missing data.

The sample included diverse gender identities: 31.2% identified as trans men, 34.2% as trans women, 27.5% as AFAB nonbinary, and 7.1% as AMAB nonbinary (Table 2). Participants were evenly distributed by annual household income, though 7.85% had missing data on income (Table 2). Post hoc analysis showed that participants missing income data were significantly less likely to have experienced physical IPV, trans-related IPV, and stalking than other participants (χ² p < .05). The sample was well educated with most participants reporting their highest level of education as “some college or associate degree” (48.8%), and 39.0% reporting being college graduates (Table 2). The sample skewed young with 40.0% of participants ages 18 to 24 and 44.2% of participants ages 25 to 44. Only 2.1% of the sample was older than 65 (Table 2).

The majority of participants reported being born in the United States (94.2%). There was an unequal distribution of participants by Census region with 31.4% living in the West, 29.2% in the South, 20.7% in the North, and 18.7% in the Midwest (Table 2).

A small majority of participants reported being in a relationship at the time of the survey (54.1%). Few reported past-year incarceration (1.7%) or engaging in sex work in the past year (6.3%). Nearly a third of participants reported being homeless at some point in their lives (32.3%). Less than 2% of participants had missing data on each of these variables (Table 2).

IPV

Psychological IPV was the most frequently endorsed subtype with 42.0% of the sample reporting experiencing this form of IPV in their lifetime. This was followed by physical IPV (39.9%) and trans-related IPV (30.4%). The prevalence of stalking (18.0%) and forced sex (21.5%) was comparatively lower in this sample (Table 2).

In the following sections, we present information about relationship between IPV outcomes and our three primary exposures: race/ethnicity, gender identity, and social marginalization. Information about the distribution of IPV by additional covariates included in the adjusted models (annual household income, highest level of education, age, birthplace, Census region, and relationship status) can be found in Table 3, and associations between additional covariates and each subtype of IPV can be found in Table 4.

Table 3.

Weighted Prevalence of Five IPV Subtypes by Demographic Characteristics, 2015 USTS, N = 23,999.

	Psychological IPV (Weighted %)	Physical IPV (Weighted %)	Stalking (Weighted %)	Forced Sex (Weighted %)	Trans-Related IPV (Weighted %)
Race/Ethnicity	χ² p < .001	χ² p < .001	χ² p = .006	χ² p = .001	χ² p = .003
White	41.1	38.3	17.3	21.3	29.7
Alaskan Native/American Indian	64.0	58.3	33.4	37.0	49.9
Asian/Native Hawaiian/Pacific Islander	34.7	29.9	18.3	19.6	25.5
Black/African American	42.5	42.9	17.7	17.8	31.9
Latinx/Hispanic	42.4	40.8	19.3	22.1	30.2
Middle Eastern/North African	54.5	43.2	29.3	32.1	37.0
Multiracial/Race Not Listed	49.6	50.3	22.0	33.2	35.1
Gender Identity	χ² p < .001	χ² p < .001	χ² p < .001	χ² p < .001	χ² p < .001
Trans man	44.7	44.3	19.2	21.3	32.5
Trans woman	38.7	38.8	15.6	15.2	38.1
AFAB nonbinary	43.3	35.6	21.0	30.2	19.4
AMAB nonbinary	35.5	35.5	12.5	16.7	23.8
Past-Year Incarceration	χ² p < .001	χ² p < .001	χ² p < .001	χ² p < .001	χ² p < .001
No	41.3	39.0	17.7	21.1	29.8
Yes	61.2	60.7	34.7	33.0	51.1
Past-Year Sex Work	χ² p < .001	χ² p < .001	χ² p < .001	χ² p < .001	χ² p < .001
No	39.7	37.7	16.6	19.8	28.8
Yes	62.3	56.0	31.7	40.1	44.8
Lifetime Homelessness	χ² p < .001	χ² p < .001	χ² p < .001	χ² p < .001	χ² p < .001
No	33.5	31.2	13.3	16.4	24.2
Yes	58.7	56.5	27.7	31.6	42.6
Annual Household Income	χ² p < .001	χ² p < .001	χ² p < .001	χ² p < .001	χ² p < .001
>$100,000	35.5	35.1	13.0	14.2	28.9
$50,000-$99,999	38.7	38.0	16.4	17.8	29.4
$25,000-$49,999	44.0	43.1	19.3	22.0	31.9
$10,000-$24,999	48.0	43.5	21.1	25.7	33.1
<$9,999	41.2	37.2	19.7	26.1	28.4
Highest Level of Education	χ² p < .001	χ² p = .019	χ² p < .001	χ² p < .001	χ² p < .0358
College graduate	38.3	38.1	15.2	18.3	29.8
Some college or associate degree	43.0	40.0	19.5	23.2	29.8
HS graduate/GED	45.1	40.4	18.8	22.0	31.6
Not a HS graduate	53.0	45.3	29.1	30.0	38.9
Age	χ² p < .001	χ² p < .001	χ² p < .001	χ² p < .001	χ² p < .001
65+	25.7	30.4	8.5	6.2	33.7
45-64	42.7	43.7	16.7	11.3	40.9
25-44	45.6	45.4	19.6	21.7	33.2
18-24	37.6	31.6	17.1	25.2	23.0
Birthplace	χ² p = .751	χ² p = .863	χ² p = .001	χ² p = .267	χ² p = .022
United States	41.6	39.4	17.7	21.4	30.1
Outside United States	41.0	38.5	22.7	21.1	30.6
Census Region	χ² p = .139	χ² p = .078	χ² p = .217	χ² p < .101	χ² p < .001
Northeast	41.4	38.3	16.8	20.1	27.5
Midwest	41.4	38.2	18.3	23.0	31.5
South	43.1	41.0	18.8	21.3	32.7
West	40.5	39.3	17.8	21.3	28.8
Relationship Status	χ² p < .001	χ² p < .001	χ² p = .009	χ² p = .004	χ² p = .068
Not in a relationship	38.2	34.6	16.9	19.6	30.0
In a relationship	44.2	43.1	18.7	22.8	30.1

Note. IPV = Intimate Partner Violence; USTS = U.S. Transgender Survey; AFAB = assigned female at birth; AMAB = assigned male at birth; HS = high school; GED = general educational development.

Table 4.

Adjusted Multivariable Regressions to Identify Correlates of Five IPV Subtypes Among U.S. Transgender Adults, 2015 USTS, N = 23,999.

	Psychological IPV aOR (95% CI)	Physical IPV aOR (95% CI)	Trans-Related IPV aOR (95% CI)	Stalking aOR (95% CI)	Forced Sex aOR (95% CI)
Race/Ethnicity
Asian/Pacific Islander	(ref)	(ref)	(ref)	(ref)	(ref)
White	1.2 [1.0, 1.4]	1.2 [1.0, 1.5]	1.0 [0.8, 1.3]	1.0 [0.7, 1.2]	1.1 [0.9, 1.5]
Alaskan Native/American Indian	2.2 [1.5, 3.1]	1.8 [1.3, 2.6]	1.7 [1.2, 2.4]	1.6 [1.1, 2.4]	1.9 [1.3, 2.8]
Black/African American	1.0 [0.7, 1.3]	1.2 [0.9, 1.6]	1.0 [0.7, 1.3]	0.7 [0.5, 1.0]	0.7 [0.5, 1.0]
Latinx/Hispanic	1.2 [0.9, 1.5]	1.3 [1.1, 1.7]	1.1 [0.9, 1.5]	1.3 [0.7, 1.9]	1.1 [0.8, 1.4]
Middle Eastern/North African	2.0 [1.3, 3.1]	1.5 [1.0, 2.3]	1.7 [1.0, 2.7]	1.8 [1.1, 3.0]	1.8 [1.1, 2.9]
Multiracial/Race Not Listed	1.4 [1.1, 1.7]	1.7 [1.4, 2.2]	1.3 [1.0, 1.7]	1.0 [0.8, 1.4]	1.7 [1.3, 2.2]
Gender Identity
AMAB nonbinary	(ref)	(ref)	(ref)	(ref)	(ref)
Trans woman	1.0 [0.8, 1.2]	1.0 [0.8, 1.2]	1.7 [1.4, 2.0]	1.1 [0.9, 1.3]	0.9 [0.7, 1.1]
Trans man	1.5 [1.3, 1.8]	1.5 [1.2, 1.7]	1.5 [1.3, 1.8]	1.6 [1.3, 2.0]	1.4 [1.1, 1.7]
AFAB nonbinary	1.6 [1.3, 1.9]	1.2 [1.0, 1.4]	0.8 [0.7, 1.0]	2.0 [1.6, 2.5]	2.2 [1.8, 2.7]
Past-Year Incarceration
No	(ref)	(ref)	(ref)	(ref)	(ref)
Yes	1.4 [1.0, 2.0]	1.6 [1.1, 2.3]	1.5 [1.1, 2.1]	1.8 [1.3, 2.6]	1.2 [0.8, 1.8]
Past-Year Sex Work
No	(ref)	(ref)	(ref)	(ref)	(ref)
Yes	2.3 [1.9, 2.8]	1.9 [1.6, 2.2]	1.7 [1.4, 2.0]	2.1 [1.7, 2.5]	2.6 [2.2, 3.1]
Lifetime Homelessness
No	(ref)	(ref)	(ref)	(ref)	(ref)
Yes	2.4 [2.2, 2.6]	2.5 [2.3, 2.7]	2.1 [1.9, 2.3]	2.2 [1.9, 2.4]	2.3 [2.1, 2.6]
Annual Household Income
>$100,000	(ref)	(ref)	(ref)	(ref)	(ref)
$50,000-$99,999	1.0 [0.9, 1.1]	1.0 [0.9, 1.1]	1.0 [0.8, 1.1]	1.2 [1.0, 1.4]	1.1 [1.0, 1.3]
$25,000-$49,999	1.1 [1.0, 1.3]	1.1 [1.0, 1.3]	1.0 [0.9, 1.2]	1.3 [1.1, 1.5]	1.3 [1.1, 1.5]
$10,000-$24,999	1.2 [1.1, 1.4]	1.1 [1.0, 1.3]	1.0 [0.9, 1.2]	1.3 [1.1, 1.5]	1.4 [1.2, 1.6]
<$9,999	1.0 [0.8, 1.1]	0.9 [0.8, 1.1]	0.9 [0.7, 1.1]	1.1 [1.0, 1.4]	1.3 [1.1, 1.6]
Highest Level of Education
College graduate	(ref)	(ref)	(ref)	(ref)	(ref)
Some college/associate degree	1.3 [1.2, 1.4]	1.2 [1.1, 1.3]	1.0 [1.0, 1.1]	1.3 [1.1, 1.4]	1.1 [1.0, 1.2]
HS graduate/GED	1.4 [1.2, 1.6]	1.2 [1.0, 1.4]	1.1 [0.9, 1.3]	1.2 [1.0, 1.5]	0.9 [0.8, 1.1]
Not a HS graduate	1.4 [1.1, 1.9]	1.0 [0.8, 1.3]	1.1 [0.8, 1.5]	1.6 [1.1, 2.2]	1.1 [0.8, 1.5]
Age
65+	(ref)	(ref)	(ref)	(ref)	(ref)
45-64	1.5 [1.1, 1.9]	1.3 [1.0, 1.7]	1.2 [0.9, 1.5]	1.5 [1.00, 2.4]	1.4 [0.8, 2.3]
25-44	1.3 [1.0, 1.7]	1.2 [0.9, 1.5]	0.9 [0.7, 1.1]	1.4 [0.9, 2.2]	2.4 [1.4, 3.9]
18-24	0.9 [0.7, 1.2]	0.7 [0.5, 0.9]	0.7 [0.5, 0.8]	1.1 [0.7, 1.8]	2.8 [1.7, 4.6]
Birthplace
United States	(ref)	(ref)	(ref)	(ref)	(ref)
Outside United States	1.0 [0.8, 1.2]	0.9 [0.8, 1.1]	1.0 [0.8, 1.2]	1.4 [1.1, 1.8]	1.1 [0.8, 1.4]
Census Region
Northeast	(ref)	(ref)	(ref)	(ref)	(ref)
Midwest	1.0 [0.8, 1.1]	0.9 [0.8, 1.0]	1.2 [1.1, 1.4]	1.1 [0.9, 1.3]	1.1 [1.0, 1.3]
South	1.0 [0.9, 1.2]	1.0 [1.0, 1.2]	1.3 [1.1, 1.4]	1.1 [1.0, 1.3]	1.1 [0.9, 1.2]
West	0.9 [0.8, 1.0]	0.9 [0.8, 1.0]	1.0 [0.9, 1.1]	1.0 [0.9, 1.1]	1.1 [0.9, 1.2]
Relationship Status
Not in a relationship	(ref)	(ref)	(ref)	(ref)	(ref)
In a relationship	1.3 [1.2, 1.4]	1.4 [1.3, 1.5]	1.1 [1.0, 1.2]	1.1 [1.0, 1.2]	1.2 [1.1, 1.3]

Note. Bold results indicate statistical significance (p < .05). IPV = intimate partner violence; USTS = U.S. Transgender Survey; aOR = adjusted odds ratio; CI = confidence interval; AFAB = assigned female at birth; AMAB = assigned male at birth; GED = general educational development.

Race/ethnicity

The distribution of all five subtypes of IPV differed significantly by race/ethnicity (χ² p < .01 for all), and the prevalence of all subtypes was highest among Alaskan Native/American Indian participants. The prevalence of psychological IPV, physical IPV, and trans-related IPV was lowest among Asian/Native Hawaiian/Pacific Islander participants while the prevalence of stalking was lowest among White participants and forced sex lowest among Black/African American participants (Table 3).

When compared with Asian/Pacific Islander participants in models adjusting for gender identity, social marginalization indicators, annual household income, highest level of education, age, birthplace, Census region, and relationship status, Alaskan Native/American Indian participants had significantly higher odds of all five subtypes of IPV. Notably, odds of psychological IPV were 2.2 times greater for Alaskan Native/Native American participants than Asian/Pacific Islander participants (95% CI = [1.5, 3.1]). Multivariable regression also revealed significantly higher odds of psychological IPV (OR: 2.0, 95% CI = [1.3, 3.1]), stalking (OR: 1.8, 95% CI = [1.1, 3.0]), and forced sex (OR: 1.8, 95% CI = [1.1, 2.9]) for Middle Eastern/North African participants; and psychological IPV (OR: 1.4, 95% CI = [1.1, 1.7]), physical IPV (OR: 1.7, 95% CI = [1.4, 2.2]), and forced sex (OR: 1.7, 95% CI = [1.3, 2.2]) for Multiracial/Race Not Listed participants. Finally, Latinx/Hispanic participants had 1.3 times the odds of physical IPV compared with Asian/Pacific Islander participants (95% CI = [1.1, 1.7]; Table 4).

Gender identity

There were no consistent patterns in the prevalence of IPV subtypes across gender identity, though their distribution differed significantly (χ² p < .01). Psychological IPV was most prevalent in trans male (44.7%) participants, followed closely by AFAB nonbinary participants (43.3%). Physical IPV was also most prevalent in trans men (44.3%). Stalking and forced sex were most prevalent in AFAB nonbinary participants (21.0% and 30.2%, respectively), and trans-related IPV was most prevalent in trans women (38.1%; Table 3).

In multivariable analysis, trans men had significantly higher odds of all IPV subtypes compared with AMAB nonbinary participants. This association was strongest for stalking (OR: 1.6, 95% CI = [1.3, 2.0]). For AFAB nonbinary participants, the odds of psychological IPV (OR: 1.6, 95% CI = [1.3, 1.9]), stalking (OR: 2.0, 95% CI = [1.6, 2.5]), and forced sex (OR: 1.4, 95% CI = [1.1, 1.7]) were also significantly higher in comparison with AMAB nonbinary participants. Finally, trans women had 1.7 times the odds of trans-related IPV in comparison with AMAB nonbinary participants (95% CI = [1.4, 2.0]; Table 4).

Social marginalization

The distribution of all five subtypes of IPV differed significantly by past-year incarceration, past-year sex work, and lifetime homelessness (χ² p < .01 for all). The prevalence of psychological and physical IPV was above 50% for participants who endorsed each indicator of social marginalization, and the prevalence of trans-related IPV was also above 50% for those who had been incarcerated in the last year (Table 3).

In the adjusted models, lifetime homelessness was associated with at least twice the odds of all IPV subtypes. Participants who have ever been homeless had 2.5 times the odds of physical IPV (95% CI = [2.3, 2.7]), 2.4 times the odds of psychological IPV (95% CI = [2.2, 2.6]), 2.3 times the odds of forced sex (95% CI = [2.1, 2.6]), 2.2 times the odds of stalking (95% CI = [1.9, 2.4]), and 2.1 times the odds of trans-related IPV (95% CI = [1.9, 2.3]; Table 4).

Past-year sex work was also consistently associated with IPV in adjusted models. Compared with participants who did not report sex work in the past year, those who did had 2.6 times the odds of forced sex (95% CI = [2.2, 3.1]), 2.3 times the odds of psychological IPV (95% CI = [1.9, 2.8]), 2.1 times the odds of stalking (95% CI = [1.7, 2.5]), 1.9 times the odds of physical IPV (95% CI = [1.6, 2.2]), and 1.7 times the odds of trans-related IPV (95% CI = [1.4, 2.0]; Table 4).

Finally, past-year incarceration was associated with increased odds of three IPV subtypes. Participants who were incarcerated in the last year had 1.8 times the odds of stalking (95% CI = [1.3, 2.6]), 1.6 times the odds of physical IPV (95% CI = [1.1, 2.3]), and 1.5 times the odds of trans-related IPV (95% CI = [1.1, 2.1]; Table 4).

Discussion

Findings from this national survey of U.S. trans adults provide a comprehensive depiction of the patterns and correlates of IPV experiences among this diverse sample. The results indicate high rates of all five subtypes of IPV among trans people in the United States, with notable variability by IPV subtype. Specifically, we observed high levels of psychological IPV, physical IPV, and trans-related IPV. Although reported at comparably lower rates, nearly a fifth of participants reported being stalked by an intimate partner, and more than a fifth reported forced sex by an intimate partner. These prevalence estimates reveal the utility of disaggregating IPV subtypes in research with trans populations as each subtype warrants unique considerations for future studies, policy, and treatment.

We observed disparities in multiple IPV subtypes by race/ethnicity for participants who identified as Alaskan Native/American Indian, Middle Eastern/North African, and Multiracial/Race Not Listed. A review of cultural and societal influences on IPV among cisgender women suggests that a variety of individual, institutional, and systemic factors impacting women of color explain racial/ethnic disparities that persist when adjusting for socioeconomic co-factors as was done in this study. Particularly relevant explanations from this review worth investigating with trans populations include preference for use of informal IPV recovery providers, internalized stigma for both race and IPV, lack of culturally competent physician training on IPV, being stereotyped and labeled while seeking services, and mistrust of medical and social service systems (Bent-Goodley, 2007).

Gender identity was significantly associated with all IPV outcomes, even after adjusting for socioeconomic variables. Notably, the prevalence of psychological and physical IPV was highest among trans men. This finding contradicts two previous studies that found higher rates of IPV in trans women compared with trans men (Brown & Herman, 2015; Valentine et al., 2017). Although reasons for discrepancies across studies are unclear, in-person assessment methods may have resulted in undercounting of IPV experiences in trans men who, like cisgender men, may find identifying and disclosing IPV challenging to notions of masculinity (Chan, 2011). As such, our findings display the importance of understanding how distinct dimensions of IPV differ across gender identities within trans populations.

In addition, trans men and trans women had a higher prevalence of trans-related IPV compared with AFAB and AMAB nonbinary participants. This finding likely reflects the inclusion of an item about partners restricting hormone use, which may not be equally relevant to the experiences of all gender identity groups. Our results indicate disproportionally high rates of psychological IPV, stalking, and forced sex for AFAB nonbinary participants, and further underscore the need for additional research leading to the development of measures that capture the full range of IPV impacting nonbinary people and effective interventions for nonbinary people with IPV experience.

Past-year incarceration, past-year sex work, and lifetime homelessness were all associated with increased odds of psychological, physical, and trans-related IPV and stalking by an intimate partner. Past-year sex work and lifetime homelessness were also associated with increased odds of forced sex by an intimate partner. These findings corroborate previous research with young trans women that demonstrated that a history of sex work and incarceration are related to syndemics of IPV, polysubstance use, low self-esteem, and victimization due to trans identity (Brennan et al., 2012). Increased levels of social and economic empowerment have been shown to have protective effects against IPV in cisgender women; as homelessness, incarceration, and sex work all can result from and cause disempowerment, it logically follows that they would be risk factors for IPV (Jewkes, 2002). Future studies are needed to continue to characterize the dynamics between IPV and health outcomes also associated with social marginalization such as HIV, substance use disorders, and poor mental health (Meyer, Springer, & Altice, 2011; Poteat et al., 2016).

Limitations

There are key limitations to acknowledge. As this study was cross-sectional, we cannot draw conclusions about causal or temporal relationships between exposure variables and IPV. Survey items assessed lifetime exposure to each IPV subtype, and did not examine recency, frequency, or consequences to IPV experiences. Despite the inclusion of three survey questions on trans-specific IPV experiences, these items do not reflect the full range of trans-related IPV; future qualitative studies are needed to better describe IPV in trans populations and develop comprehensive survey measures. Self-report bias may have affected participants’ comfort to disclose experiences of IPV, incarceration, sex work, and homelessness. Use of an online nonprobability sample and recruitment through community groups engaged with trans populations affects generalizability of findings. Based on previous health surveillance of trans populations, it is likely that despite the geographic diversity and use of Census-based sampling weights, the USTS sample has higher levels of education and income than the general trans population (Crissman, Berger, Graham, & Dalton, 2017). Finally, due to items available in the USTS dataset, we were unable to analyze interpersonal or community-level correlates of IPV. For example, neighborhood-level measures of economic development, social disorganization, and community violence have previously been associated with IPV and may have a unique impact on trans populations (Beyer, Wallis, & Hamberger, 2015).

Conclusion

Studies are needed to develop interventions that identify, prevent, and address IPV among trans populations. As IPV has previously been shown to have a syndemic relationship with HIV, substance use, and poor mental health in multiple populations, understanding its relationship with these outcomes is crucial to developing multicomponent health interventions for trans populations. Previous studies focused on IPV perpetrated by cisgender men against cisgender women have suggested that IPV interventions should include both partners and act through mitigating ideologies of male superiority and cultures of violence (Jewkes, 2002). In the context of relationships in which one partner is trans, addressing power dynamics created through cissexism may be necessary to prevent IPV. In addition, interventions addressing co-occurring issues such as alcohol use and aggression within the partnership are warranted (Stover, Meadows, & Kaufman, 2009). Previous literature has suggested that current IPV screening practices in healthcare settings do not adequately detect and address IPV impacting lesbian, gay, bisexual, transgender (LGBT) individuals (Ard & Makadon, 2011; Ghandour, Campbell, & Lloyd, 2015). Tools designed to identify IPV perpetrated by cisgender men against cisgender women cannot capture the full range of IPV experiences impacting trans people. In addition to interventions designed to prevent IPV in trans individuals, efforts to develop culture- and gender-sensitive IPV screening and counseling practices for trans patients are needed.

Footnotes

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: Preparation of this manuscript was supported by the National Institutes of Health (NIH)-National Institute on Alcohol Abuse and Alcoholism (NIAAA) U24AA022000.

ORCID iD

Wesley M. King

Author Biographies

Wesley M. King, EdM, is a researcher at Brown University School of Public Health. His research focuses on syndemics impacting transgender communities, including HIV, intimate partner violence, substance use, and mental health.

Arjee Restar, MPH, is a researcher at Brown University School of Public Health. Her research seeks to promote health equity through structural- and behavioral-based interventions for marginally placed communities at high risk of sexual and mental health outcomes, particularly transgender and gender-nonconforming communities of color.

Don Operario, PhD, is a professor of Public Health in the Department of Behavior and Social Sciences at Brown University School of Public Health. He researches social and psychological determinants of HIV, sexual health, and related issues as well as lived experiences associated with social inequity with an emphasis on intervention development for high-risk groups.

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