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. Author manuscript; available in PMC: 2023 Dec 1.
Published in final edited form as: J Interpers Violence. 2022 Feb 15;37(23-24):NP22501–NP22527. doi: 10.1177/08862605211072167

Psychosocial and Culturally Specific Factors Related to IPV Victimization Among a Sample of Latino Sexual Minority Men in the U.S.

Gabriel Robles 1, Stephen C Bosco 2,3, Iris Cardenas 1, Joletta Hostetter 1, Tyrel J Starks 3
PMCID: PMC9376202  NIHMSID: NIHMS1801478  PMID: 35166599

Abstract

A growing body of research illustrates that sexual minority men (SMM) experience elevated rates of intimate partner violence (IPV) compared to heterosexual samples. Researchers have examined the relationship between minority stress and IPV victimization among sexual minority men. A majority of the IPV research identifying risk factors associated with IPV victimization among SMM have sampled predominately non-Hispanic White SMM, while Latino SMM are consistently under-represented in IPV research. This study examines the associations between (1) co-occurring psychosocial factors (e.g., depression, anxiety, childhood sexual abuse, drug use, and problematic drinking) and (2) Latino-specific minority stress factors (e.g., U.S.-born, language, racial and ethnic identities, and discrimination) on IPV victimization in a nationwide sample of Latino SMM. Data were collected from Latino SMM aged 18 or older, identified as cis-male, and in a romantic relationship with a cis-male partner (N=530). The participants were recruited through social media and geo-location-based dating mobile applications. A majority (72%) of the sample reported IPV victimization in their lifetime. Specific to forms of IPV, more than half (51.9%) of the sample reported monitoring behaviors, while 49.6% reported emotional IPV, 45.1% reported physical IPV, 31.5% reported controlling behaviors, and 22.3% reported HIV-related IPV. In multivariable models, psychosocial and Latino-specific factors were associated with the increased likelihood of IPV victimization. Regarding Latino-specific factors, being born in the U.S. and race-based discrimination predicted IPV victimization. These findings highlight the extent to which minority stress elevates the risk of IPV for Latino SMM and point to the need to address social factors in IPV prevention services. Further, work on SMM IPV victimization tends to focus on the potential role of sexual orientation-related discrimination, whereas the current study points to the importance of race-based discrimination.

Keywords: sexual minority men, intimate partner violence, Latino, Hispanic, relationships

INTRODUCTION

More than two decades of research have demonstrated that sexual minority men (SMM) experience rates of intimate partner violence (IPV) that are significantly higher than heterosexual men (Chen et al., 2020) and comparable to heterosexual women (Blosnich & Bossarte, 2009; Stephenson & Finneran, 2013; Tjaden et al., 1999). IPV represents one of the most common forms of interpersonal violence experienced among SMM compared to hate crimes, childhood abuse, and non-partner physical abuse (Brown & Herman, 2015; Roberts et al., 2010). Research on IPV among SMM has grown; however, most of these findings are driven by predominately non-Hispanic White SMM samples. To date, understanding factors associated with IPV in Latino SMM remains understudied.

IPV Prevalence and Measurement Issues

The prevalence of IPV in Latino SMM is difficult to quantify due to the limited research on IPV in Latino SMM compared to non-Hispanic White SMM (Edwards et al., 2015; Kim & Schmuhl, 2019). The few studies focused exclusively on Latino SMM have shown elevated IPV rates compared to the broader population of SMM (Feldman et al., 2007; Nieves-Rosa et al., 2000; Stephenson et al., 2013). This emerging work has featured several studies with sufficient representation of Latino SMM to illustrate that IPV is a salient challenge for this group (De Santis et al., 2014; Nieves-Rosa et al., 2000; Santaya & Walters, 2011). Estimated prevalence rates of any IPV reported by Latino SMM range widely (Feldman et al., 2007; Santaya & Walters, 2011), 3.1 – 25.7% for sexual IPV (Gonzalez-Guarda et al., 2013; Santaya & Walters, 2011), 5.6 – 48.6% for physical IPV (Gonzalez-Guarda et al., 2013; Santaya & Walters, 2011), and 40 – 48% for emotional IPV (Madera & Toro-Alfonso, 2005; Toro-Alfonso & Rodríguez-Madera, 2004b).

Despite the emergence of research on IPV in SMM, the existing studies have relied upon measures of IPV that are hetero-centric and often do not assess minority stress-related fears relevant to this population (Finneran & Stephenson, 2013; Stephenson & Finneran, 2013). The heterosexist assumption rejects the unique social, structural, and individual differences between same-gender couples and perhaps contribute to the wide range of prevalence estimates found in the literature. As a result, the Intimate Partner Violence among Gay and Bisexual Men (IPV-GBM) scale was developed to assess IPV within the context of same-sex couples in addition to those of racially and ethnically diverse backgrounds (Stephenson & Finneran, 2013). The IPV-GBM includes subscales to measure different forms of IPV such as physical/sexual, emotional, and HIV-related violence and controlling and monitoring behaviors. The IPV-GBM scale is one of the only scales to address the unique forms of IPV in SMM; this measure was normed on a sample of predominately non-Hispanic White and Black SMM (Stephenson & Finneran, 2013). The current study is one of the first to utilize this scale on a sample of Latino SMM.

Minority Stress and IPV Risk in SMM

Minority Stress Theory has been widely applied to understand adverse health outcomes in minority populations. The theory suggests that having or espousing a stigmatized identity exposes an individual to a number of stressors not experienced by majority group members (Meyer, 1995, 2003). Meyer (2003) posited that proximal (e.g., internalized homonegativity) and distal (e.g., discrimination) sources of stress lead to adverse health outcomes. Minority Stress Theory has largely guided the research on IPV in SMM and how IPV is conceptualized in this population (Kim & Schmuhl, 2019). Previous work has demonstrated a positive association between minority stress and IPV victimization in SMM (Badenes-Ribera et al., 2017; De Santis et al., 2014; Longobardi & Badenes-Ribera, 2017; Stephenson & Finneran, 2017b).

While research on IPV guided by Minority Stress Theory has generally elucidated unique risk factors increasing the risk of IPV in SMM (Carvalho et al., 2011; Decker et al., 2018; Edwards et al., 2015; Stephenson & Finneran, 2017a), there is a critical concern in overgeneralizing these findings across all SMM. The link between minority stress and IPV has been studied much less in Latino SMM than non-Hispanic White SMM (Kim & Schmuhl, 2019; Longobardi & Badenes-Ribera, 2017), leading to the unitary understanding of IPV victimization across SMM. Latino SMM experience elevated rates of minority stress based on their multiple social identities (race, ethnic background, and sexual orientation) compared to non-Hispanic White SMM (De Santis et al., 2014; Feldman et al., 2007). It is of critical importance to acknowledge the varied experiences of Latino SMM, such as histories, cultures, and societal experiences, as important differences across social groups. Identifying the association between discrimination and IPV victimization is imperative to develop a more comprehensive conceptualization of IPV victimization among Latino SMM.

Psychosocial Factors Associated with IPV

Research has shown that certain individual-level factors increase the likelihood of IPV victimization in SMM, such as substance use, mental health, and family history of violence (Badenes-Ribera et al., 2017; Dickerson-Amaya & Coston, 2019; Edwards et al., 2015; Finneran et al., 2012; Goldberg & Meyer, 2013; Miller & Irvin, 2017). The association between substance use and IPV in SMM (Buller et al., 2014; Duncan et al., 2018) has been well established in the larger body of research. Fewer studies have replicated the association in Latino SMM (De Santis et al., 2014; De Santis et al., 2012; Lee et al., 2020). Latino SMM report greater rates of substance use and substance-use disorders compared to heterosexual Latino men (Cochran et al., 2007) and non-Latino SMM (Irwin & Morgenstern, 2005; Slater et al., 2017). Researchers have interpreted the positive association between substance use and IPV among SMM as a way to self-medicate and cope with relationship distress and being dissatisfied with a relationship (McKenry et al., 2006). However, researchers tend to conflate drug and alcohol use (Buller et al., 2014; McKenry et al., 2006), therefore reducing the ability to determine which substance is a greater predictor (or consequence) of IPV. Alcohol use has also been shown to increase IPV risk among non-Latino SMM (Davis et al., 2016; Finneran & Stephenson, 2014; Stults et al., 2016) and Latino SMM (Santaya & Walters, 2011). The association between substance use and IPV in Latino SMM has been identified; the bulk of these findings do not account for the potential role of Latino-specific factors contributing to observed correlation.

An essential component in examining minority stress is the impact of the social environment across the lifespan, such as discrimination and childhood sexual abuse (CSA) on proximal stressors and health outcomes (Pachankis, 2015). Prior research has identified that childhood sexual abuse (CSA) increases the risk of IPV among SMM (e.g., Balsam et al., 2011; Bosco et al., 2020; Koeppel & Bouffard, 2014; McKenry et al., 2006); specifically IPV victimization (Godbout et al., 2017; Koeppel & Bouffard, 2014). However, the examination of the relationship between CSA and IPV victimization in Latino SMM is comparatively understudied. The small body of work has produced mixed findings with some studies indicating CSA is associated with increased the risk of IPV (Toro-Alfonso & Rodríguez-Madera, 2004a, 2004b; Welles et al., 2011), while other studies found that CSA was not associated with IPV among Latino SMM (Feldman et al., 2007; Lee et al., 2020). Given that Latino SMM are more likely to experience CSA (Arreola et al., 2005; Parsons et al., 2017; Phillips et al., 2014) and IPV (Feldman et al., 2007; Nieves-Rosa et al., 2000; Stephenson et al., 2013) compared to non-Hispanic White SMM additional research is required to understand the relationship between these two factors.

The link between IPV and mental health has been well-documented among cisgender heterosexual (Bacchus et al., 2018; Devries et al., 2013) and SMM samples (Buller et al., 2014; Williams et al., 2015). The current body of research has yet to provide sufficient empirical support for a similar association in Latino SMM, despite the disproportionate risk of mental health problems reported by Latino SMM (Díaz et al., 2001; Meyer et al., 2008). Mental health risks among Latino SMM are compounded by the co-occurrence of factors including immigration, acculturative stress (Rhodes et al., 2013), stigmatization (Guarnero & Flaskerud, 2008), and racial and sexual orientation-based discrimination (Kim & Fredriksen-Goldsen, 2017). Mental health issues among Latino SMM are associated with increased risk of drug abuse (De Santis et al., 2014), and alcohol use (English et al., 2018), and IPV (Charak et al., 2019; Gonzalez-Guarda et al., 2013). Substance use among Latino SMM has been shown to decrease the impact of negative emotions associated with their sexual orientation, violence, and social stigma (De Santis et al., 2014).

A wealth of research is devoted to understanding the factors contributing to HIV risk, substance use, and mental health among Latino SMM; limited attention has been directed to the examination of IPV predictors across multiple Latino SMM identified ethnic groups. The current exploratory study has one primary aim: to examine associations between co-occurring psychosocial constructs (i.e., substance use, mental health, CSA, and discrimination) as well as culture-specific stressors such as immigration (i.e., U.S.-born vs. non-U.S. born and time spent in the U.S.) and IPV victimization. We hypothesize that the discrimination would be associated with experiences of IPV, in addition to the well establish correlates of HIV such as mental health, substance use, and CSA among this diverse sample of Latino SMM.

METHODS

Participants and Procedures

As part of a national study on Latino cultural values and their impact on sexual health and intimate relationships, we recruited Latino SMM using English and Spanish advertisements on social media platforms and a geo-location-based dating application. To be eligible, participants needed to be 18-years of age or older, reside in the United States – the 50 states, D.C., and Puerto Rico, identify as a cis-male, be in a romantic relationship with another cis-male who was at least 18-years old, identify as Hispanic or Latino, and able to read in either English or Spanish.

Eligible participants were asked to complete an online consent form in either English or Spanish. After completing the informed consent, participants were directed to the online survey designed to facilitate completion in English or Spanish. Participants indicated their language of preference upon clicking the advertisement. Participants were also able to confirm their preferred language before and after consent. Participants, who entered the survey and wanted to switch languages, were able to select a menu option on the screen that allowed them to toggle language preference. At the end of the survey, participants were asked to recruit their main partners. Participants were also asked to provide an email address to receive compensation. All procedures were approved by the CUNY University Institutional Review Board (CUNY-UI IRB).

The larger study yielded a total sample of 720, which included two subsamples (1) partnered Latino SMM who did not successfully recruit their partner and (2) participants who successfully recruited their partner. For the current study, we analyzed the data from the subsample of Latino SMM who did not successfully recruit their partner (n=530).

The measures in the current study were forward and backward translated (Chen & Boore, 2010) by two investigators who are fluent in both English and Spanish. One researcher translated a measure into Spanish; then, the other researcher would translate the identical measure back into English. After, the research team discussed observed differences in the original English, Spanish, and newly back-translated English measure. The team focused on lexicon and grammar to ensure greater readability across ethnic Latino subgroups. We observed no missing data given that the survey was programmed in which all responses were required.

Measures

Demographics.

Participants reported their age, racial and ethnic background, sexual orientation, education, income, HIV status, and relationship length.

Regarding Latino-specific factors, the participants were asked to indicate their Latino race and ethnicity, whether they were born in the mainland U.S (i.e., 50 states and District of Columbia). For the study, we classified Latino SMM born in Puerto Rico as being born outside the mainland U.S. Language preference (English vs. Spanish) was measured using the autogenerated Qualtrics variable that recorded the participants’ language to complete the survey.

Intimate Partner Violence.

Participants completed the 22-item Intimate Partner Violence among Gay and Bisexual Men (IPV-GBM) scale (Stephenson & Finneran, 2013), which was specifically developed to measure IPV among gay and bisexual men (Kuder-Richardson 20 (kr20) =.97). The IPV-GBM scale measures IPV occurrence throughout the participant’s lifetime using five subscales: physical and sexual, monitoring, controlling, HIV-related, and emotional. Physical and sexual violence subscale consisted of 8-items (kr20 =.95), monitoring subscale consisted of 5-items (kr20 =.89), controlling subscale consisted of 4-items (kr20 =.91), the emotional subscale consisted of 3-items (kr20 =.78), and the HIV-related subscale consisted of 3-items (kr20 =.93). Participants were asked whether they have ever experienced these forms of violence with a yes/no response format. Any form of IPV variable was derived by assigning participants a score of “1” for having experienced at least one form of violence and “0” if participants have not experienced any form of IPV.

Childhood Sexual Abuse (CSA).

CSA was assessed with a single item from the Adverse Childhood Experiences (Felitti et al., 1998) inventory. Participants were asked, “During your first 18 years of life, did an adult or person at least 5 years older than you ever: Touch or fondle you or have you touch their body in a sexual way [or] attempt or actually have oral, anal, or vaginal intercourse with you?” Responses were dichotomous; participants either reported Yes or No.

Depression.

Depression was assessed using the Center for Epidemiological Studies – Depression (CESD-10; Radloff, 1977), a 10-item self-report measure of how a participant may have felt or behaved over the past 3-months. All items were scored on a Likert-type scale from 0 (rarely or none of the time) to 3 (most or all of the time). Scores were summed. The possible range of scores is 0 to 30; the higher scores indicated the presence of more depressive symptomology. Internal consistency for the scale was good (α =.83).

Anxiety.

Anxiety was assessed using the General Anxiety Disorder-7 (GAD-7; Spitzer et al., 2006), a 7-item self-report measure assessing anxiety-related psychosocial problems in the past 2 weeks. Responses were recorded using a 4-point Likert-type scale with responses ranging from 0 (not at all) to 3 (nearly every day). Scores were summed with a possible range of scores is 0 to 21, with higher scores indicating the presence of more anxious symptomology. Internal consistency for the scale was good (α =.94).

Drug use severity.

Drug use severity was assessed using the 10-item Drug Abuse Screening Test (DAST-10; Skinner, 1982). Participants who reported drug use in the past 30-days were asked to indicate the presence or absence of negative psychosocial symptoms associated with drug use. Responses were summed to produce a count variable representing the number of problems. Those participants who did not indicate the use of any drugs were given a score of zero.

Problematic drinking.

Alcohol Use Disorders Identification Test (AUDIT) was used to assess problematic drinking (Bohn et al., 1995). The AUDIT is a 10-item self-report scale to measure the quantity of consumption and physical and psychosocial problems related to alcohol consumption. All responses were reported on a 5-point Likert-type scale to assess drinking frequency from 0 (Never) to 4 (Four or more times per week), amount of consumption on a drinking day from 0 (1–2 drinks) to 4 (10 or more), and problems relates to consumption 0 (Never) to 4 (Daily/Almost Daily). A 3-point Likert-type scale was used to assess physical injury to self or others as a result of drinking from 0 (No) to 2 (Yes, during the last six months) and concern from others from 0 (No) to 4 (Yes, during the last 6 months). All 10-items were summed to create a total scale score with higher scores indicating greater problematic drinking. Internal consistency was strong (α =.91).

Everyday Discrimination Scale (EDS)

Sexual Orientation. was used to measure sexual orientation-related discrimination, participants completed a modified version of the Everyday Discrimination Scale (EDS; Williams et al., 1997), a 9-item measure that assessed unfair treatment based on the participant’s sexual orientation. Response items range from 1 (never) to 6 (experience discrimination almost every day), with higher scores indicating greater perceived discrimination. Internal consistency was strong (α =.94).

Everyday Discrimination Scale (EDS)

Race and Ethnicity. was used to measure Race/ethnic-related discrimination, participants completed a modified version of the Everyday Discrimination Scale (EDS; Williams et al., 1997), a 9-item measure that assessed unfair treatment based on the participant’s race/ethnic background. Response categories range from 1 (never) to 6 (experience discrimination almost every day), with higher scores indicating greater perceived discrimination. Internal consistency was strong (α =.96).

Analytic Plan

The analyses for the current study were calculated in SPSS (v. 25; SPSS, 2017). Chi-squared tests of independence and Analyses of variance (ANOVA) were utilized to examine the associations between lifetime reports of any IPV and all variables of interest, including demographic characteristics. We subsequently sought to disaggregate the specific forms of victimization from any form of IPV. We then conducted a frequency analysis. To identify factors associated with forms of IPV victimization, we used multivariable logistic regression analyses between co-occurring psychosocial and Latino-specific factors as the independent variables and the forms of IPV as the dependent variables. All models were adjusted for demographic characteristics.

RESULTS

The rates of IPV victimization by form is presented in Figure 1. A majority (72.1%) of the sample reported experiencing at least one form of IPV in their lifetime. Monitoring IPV was the most commonly reported form of IPV (51.9%), followed by emotional IPV (49.6%) and physical IPV (45.1%). Almost one-third (31.5%) of the participants reported experiencing controlling IPV, and less than one-fourth (22.3%) of the sample reported experiencing HIV-related IPV.

Figure 1:

Figure 1:

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Percentages of IPV by form

Table 1 contains a detailed summary of the demographic characteristics and bivariate associations between demographic characteristics and IPV victimization. Participants primarily identified as White Latino (63.2%), identified as Gay (87.5%). Most were HIV-negative (76.2%), born in the U.S. (57.9%), completed the survey in Spanish (80.8%). The average age was 31.3 (SD = 6.9), and over half (52.8%) reported current relationship length as 3 years or less. In terms of associations between demographic characteristics and IPV victimization, educational level, income, relationship length, and HIV status were associated with reporting IPV victimization. The associations between sexual orientation, age, and Latino-specific factors (i.e., U.S.-born, survey language, and race/ethnicity) and IPV experiences were not statistically significant.

Table 1.

Demographics and Experiences of IPV by Sample Characteristics

Experiences of IPV
Total Any Test Statistic
n (%) n (%) n (%)
Yes No
530 (100) 382 (72.1) 148 (27.9)
Sexual Identity χ2(2) = 4.6
 Gay 464 (87.5) 337 (88.2) 127 (85.8)
 Bisexual 48 (9.1) 36 (9.4) 12 (8.1)
 Queer/Otder 18 (3.4) 9 (6.1) 9 (2.4)
U.S. Born χ2(1) = 1.3
 Yes 307 (57.9) 227 (59.4) 80 (54.1)
 No 223 (42.1) 155 (40.6) 68 (45.9)
Survey Language χ2(1) = 1.2
 English 102 (19.2) 304 (79.6) 124 (83.8)
 Spanish 428 (80.8) 78 (20.4) 24 (16.2)
Race/Etdnicity χ2(4) = 5.5
 Black/Afro-Latino 43 (8.1) 34 (8.9) 9 (6.1)
 White Latino 335 (63.2) 239 (62.6) 96 (64.9)
 Native American or Indigenous 19 (3.6) 10 (2.6) 9 (6.1)
 Multiracial 92 (17.4) 70 (18.3) 22 (14.9)
 Otder 41 (7.7) 29 (7.6) 12 (8.1)
Education χ2(1) = 3.9*
 Less tdan 4-year college degree 336 (63.4) 252 (66.0)a 84 (56.8)b
 4-year college degree or more 194 (36.6) 130 (34.0)a 64 (43.2)b
Income χ2(1) = 5.5*
 30K or less 332 (62.6) 251 (65.7)a 81 (54.7)b
 More tdan 30K 198 (37.4) 131 (34.3)a 67 (45.3)b
HIV Status χ2(1) = 7.7**
 Negative/Unknown 404 (76.2) 279 (73.0)a 125 (84.5)b
 Positive 126 (23.8) 103 (27.0)a 23 (15.5)b
Childhood Sexual Abuse χ2(1) = 14.1**
 Yes 208 (39.2) 169 (44.2)a 39 (26.4)b
 No 322 (60.8) 213 (55.8)a 109 (73.6)b
Relationship Lengtd χ2(1) = 5.2*
 3 years or less 280 (52.8) 190 (49.7)a 90 (60.8)b
 More tdan 3 years 250 (47.2) 192 (50.3)a 58 (39.2)b
M (SD) M (SD) M (SD)
Age 31.3 (6.9) 31.1 (6.4) 31.6 (8.2) t(528) = −0.80
Depression 11.0 (6.4) 12.0 (6.4) 8.4 (5.8) t(528) = 5.96**
Anxiety 7.4 (5.7) 8.1 (5.6) 5.4 (5.4) t(528) = 5.02**
AUDIT 7.4 (8.0) 8.4 (8.5) 4.8 (5.6) t(528) = 4.71**
DAST 1.3 (2.1) 1.4 (2.3) 0.9 (1.5) t(528) = 2.75**
EDS SO 2.2 (1.1) 2.4 (1.1) 1.9 (1.0) t(528) = 4.09**
EDS Race 2.4 (1.2) 2.5 (1.2) 2.0 (1.0) t(528) = 4.84**
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*

p <.05

**

p < .01

AUDIT = Alcohol Use Disorders Identification Test; DAST = Drug Abuse Screening Test; EDS = Everyday Discrimination Scale; SO = Sexual Orientation

Results of bivariate analysis highlighted multiple associations between psychosocial factors and odds of IPV victimization. There was a significant difference in scores for depression, participants who reported experiencing any lifetime IPV had higher CESD scores (M = 12.0, SD = 6.4) compared to those who did not (M = 8.4, SD = 5.8; t(528) = 5.96, p <.01). Similar to previous findings, participants with any lifetime IPV victimization also scored higher on anxiety (t(528) = 5.02, p <.01), problematic drinking (t(528) = 4.71, p <0.01), and drug use severity (t(528) = 2.75, p <0.01). Participants reporting any lifetime IPV were more likely to report a history of childhood sexual abuse (χ2(1) = 14.1, p<0.01). In addition, they scored higher on race/ethnic-related discrimination (t(528) = 4.84, p<0.05). Discrimination based on sexual orientation was not associated with lifetime IPV victimization.

Table 2 presents the results of the multivariable logistic regressions by form of IPV. In terms of demographic factors associated with forms of IPV victimization, age was the only demographic factor not associated with IPV. Those who identified as bisexual were more likely to report experiencing physical IPV compared to gay-identified SMM. Those with higher levels of education were at reduced risk of reporting physical IPV but were at an increased likelihood of reporting emotional IPV. Participants living with HIV were associated with increased odds of experiencing any IPV and physical IPV. Relationship length was associated with increased odds of reporting all forms of IPV, suggesting that participants in relationships of 3 years or more were more likely to report experiencing IPV than those of less than 3 years.

Table 2.

Summary of Logistic Regression Results

Any IPV Physical Monitoring Controlling Emotional
AOR 95% CI AOR 95% CI AOR 95% CI AOR 95% CI AOR 95% CI
Age 0.97 (0.94, 1.00) 0.99 (0.96, 1.03) 0.98 (0.95, 1.01) 1.02 (1.00, 1.06) 0.99 (0.96, 1.02)
Sexual Orientation (ref=gay)
 Bisexual 1.37 (0.65, 2.87) 2.38* (1.18, 4.79) 1.11 (0.59, 2.10) 1.47 (0.68, 3.15) 1.64 (0.79, 3.40)
 Queer/Other 0.45 (0.15, 1.39) 1.45 (0.41, 5.19) 0.56 (0.19, 1.61) 0.55 (0.07, 4.23) 0.59 (0.17, 2.01)
Race/Ethnicity (ref=White LSMM)
 Black/Afro-Latino 1.28 (0.54, 3.06) 1.35 (0.64, 2.83) 0.76 (0.38, 1.54) 0.70 (0.30, 1.64) 0.68 (0.33, 1.41)
 Native American/Indigenous 0.44 (0.17, 1.16) 0.36 (0.12, 1.10) 0.39 (0.13, 1.15) 0.48 (0.11, 2.12) 0.29** (0.12, 0.73)
 Multiracial 1.54 (0.85, 2.82) 1.20 (0.70, 2.05) 1.03 (0.61, 1.75) 0.75 (0.40, 1.43) 1.17 (0.68, 2.04)
 Other 0.91 (0.41, 2.01) 1.19 (0.54, 2.62) 1.15 (0.52, 2.54) 0.94 (0.38, 2.32) 1.01 (0.46, 2.22)
Survey Language 0.64 (0.35, 1.17) 1.10 (0.61, 2.00) 0.76 (0.44, 1.31) 0.72 (0.37, 1.43) 0.68 (0.39, 1.18)
U.S. Born 1.14 (0.72, 1.80) 1.35 (0.85, 2.15) 1.56* (1.02, 2.39) 2.25** (1.28, 3.97) 1.55* (1.00, 2.40)
Education 1.06 (0.67, 1.68) 0.56* (0.35, 0.92) 0.87 (0.56, 1.35) 0.58 (0.33, 1.03) 1.75* (1.10, 2.78)
Income 0.95 (0.59, 1.55) 0.73 (0.46, 1.16) 0.79 (0.51, 1.23) 0.45** (0.25, 0.80) 0.78 (0.49, 1.24)
HIV-status 1.81* (1.03, 3.20) 1.87* (1.15, 3.10) 1.56 (0.96, 2.52) 1.56 (0.90, 2.68) 1.39 (0.85, 2.27)
Childhood Sexual Abuse 1.88** (1.28, 3.00) 1.36 (0.90, 2.06) 1.22 (0.82, 1.82) 0.97 (0.62, 1.52) 2.24** (1.48, 3.41)
Relationship Length 1.94** (1.22, 3.09) 2.10** (1.37, 3.20) 2.86** (1.90, 4.29) 1.80* (1.14, 2.83) 1.67* (1.13, 2.55)
Depression 1.06* (1.00, 1.11) 1.12** (1.06, 1.17) 1.02 (0.98, 1.07) 1.10** (1.04, 1.16) 1.08** (1.03, 1.13)
Anxiety 1.01 (0.96, 1.07) 0.94* (0.89, 0.99) 1.02 (0.97, 1.08) 0.99 (0.93, 1.05) 1.02 (0.97, 1.07)
AUDIT 1.06** (1.02, 1.09) 1.06** (1.04, 1.09) 1.05** (1.02, 1.08) 1.07** (1.04, 1.10) 1.06** (1.03, 1.09)
DAST 1.06 (0.94, 1.20) 1.01 (0.91, 1.11) 1.02 (0.92, 1.13) 1.04 (0.94, 1.16) 0.95 (0.86, 1.05)
EDD Sexual Orientation 0.93 (0.67, 1.28) 0.99 (0.74, 1.33) 0.95 (0.72, 1.25) 1.07 (0.77, 1.50) 0.90 (0.68, 1.21)
EDD Race 1.37* (1.01, 1.85) 1.33* (1.02, 1, 74) 1.37* (1.06, 1.76) 1.24 (0.93, 1.66) 1.37* (1.05, 1.79)
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*

p <.05

**

p < .01

LSMM = Latino Sexual Minority Men; AUDIT = Alcohol Use Disorders Identification Test; DAST = Drug Abuse Screening Test; EDD = Everyday Discrimination

Note: Model predicting HIV-related IPV yielded unreliable estimates due to small sample size.

In the multivariable logistic regression models, race/ethnicity and being born in the U.S. were associated with odds of lifetime IPV victimization. Participants identified as Native American/Indigenous Latino SMM were at lower odds of experiencing emotional IPV relative to White Latino SMM. Being born in the mainland U.S. was associated with increased odds of three forms of IPV: monitoring, controlling, and emotional. Results showed no significant association between survey language and odds of reporting IPV victimization.

Additional findings from the multivariable logistic regression models illustrate direct associations between psychosocial factors and reporting experiences of IPV victimization. Childhood sexual abuse was associated with increased odds of emotional and any IPV. Greater depressive symptomology was associated with increased odds of physical, emotional, controlling, and any IPV. Conversely, greater anxiety was associated with decreased odds of experiencing physical IPV. Consistent with our hypothesis, race/ethnic-related discrimination was associated with increased odds of physical, emotional, monitoring, and any IPV. Drug use severity and sexual orientation-related discrimination were not associated with reports of IPV.

DISCUSSION

The findings extend existing research by identifying potential psychosocial and Latino-specific risk factors for IPV victimization. Consistent with our hypothesis, we found that discrimination (race-based) was associated with greater odds of IPV victimization. Psychosocial factors including depression, problematic drinking, and childhood sexual abuse (CSA) increase the odds of IPV victimization. Furthermore, being born in the U.S. and racial and ethnic identity were the only Latino-specific factors related to IPV victimization in the current sample.

Race-based discrimination increased the odds of IPV victimization in the multivariable logistic regression model. Racial discrimination is a common stressor among Latino SMM, with well-documented associations with adverse physical and mental health outcomes (Choi et al., 2013; Díaz et al., 2006; Reisen et al., 2013); examination between discrimination and IPV has largely been overlooked in this population. Current findings demonstrated racial-based discrimination as a risk factor for IPV victimization, but an unexpected finding was that sexual orientation-based discrimination was not predictive of IPV victimization. This is important given that work on SMM IPV victimization tends to focus on the potential role of sexual orientation related discrimination, whereas the current study points to the importance of racial discrimination. While societal attitudes towards the LGBT community are improving, Latino SMM report less acceptance within the LGBT community (Guadalupe-Díaz, 2013), the Latino and Hispanic community (Gattamorta & Quidley-Rodriguez, 2018; Li et al., 2017; Schmitz et al., 2020), and the larger society (McConnell et al., 2018) compared to their non-Hispanic White SMM counterparts. Latino SMM face additional [minority-based] stressors related to their marginalized social identities (i.e., minority stress; Meyer, 2003) that may further elevate their risk of IPV victimization (De Santis et al., 2014; Swan et al., 2021).

The relationships between psychosocial factors and IPV are consistent with the larger body of research (Davis et al., 2016; Kimmes et al., 2019; Langenderfer-Magruder et al., 2016; Stults et al., 2021). The current study is one of the first to link co-occurring psychosocial factors to IPV victimization in a sample of partnered Latino SMM. Previous work has demonstrated a positive association between increasing numbers of psychosocial syndemic indicators and increased risk behaviors for HIV in samples of Latino SMM (e.g., Martinez et al., 2016; Martinez et al., 2020; Muñoz-Laboy et al., 2018). But there is a smaller established body of research examining the associations between syndemic indicators and IPV victimization within the sample population. Further, the application of the syndemic framework on Latino SMM has highlighted that depression, CSA, drug use, and problematic drinking represent significant influences on HIV risk within this population (Blashill et al., 2020; Lee et al., 2020; Martinez et al., 2016). More recent research on syndemic factors and health among Latino SMM has incorporated culturally relevant variables (i.e., acculturative stress and immigration) as risk factors of adverse health among this population (González-Guarda et al., 2016; Lee et al., 2020; Martinez et al., 2020).

In the multivariable logistic regression models, bisexual-identified Latino SMM reported greater odds of physical IPV than gay-identified Latino SMM, a finding consistent with the larger body of research on the increased risk of IPV among bisexual SMM compared to gay SMM (Edwards et al., 2015; Walters et al., 2013). Intersectionality Theory has explained this finding, which posits that individuals possess interdependent social identities that shape their experiences due to the power (or lack thereof) associated with these various identities within a particular societal context (Bowleg et al., 2017; Crenshaw, 1989). This suggests that social identities alone are not a risk factor, but the oppressive social context surrounding said identities is conducive to risk. For example, bisexual-identified Latino SMM experience stigmatization and discrimination based on their multiple identities from both the LGBTQ+ community (Friedman et al., 2014; Han & Choi, 2018; Turell et al., 2018) as well as from the larger society (Barker & Langdridge, 2008; Díaz et al., 2001; Ibañez et al., 2012). Future research should examine the relationship between multiple intersecting forms of oppression (sexual, racial, immigration, etc.) among Latino SMM and IPV victimization using intersectional research methods.

These findings must be understood in light of several limitations. The results are based on self-report cross-sectional data collected from a non-probability sample of predominately White Latino gay-identified, Latino SMM in a romantic relationship, and Latino SMM currently living in the U.S. The sample likely underrepresents and may over-represent subgroups of Latino SMM in the U.S. due to lack of geographical representativeness, and non-probability nature of the recruitment strategy. Thus, we do not attempt to characterize the results as matching the true population dynamics of Latinos in the U.S. Therefore, findings may lack generalizability to the larger population of Latino SMM, specifically among Latino SMM who are not in an intimate relationship and those living outside of the U.S. An additional limitation is that the sample is composed of partnered Latino SMM. They identify as cisman/male/masculine. These findings cannot be generalized to sexual minority women or transgender and gender-expansive communities. The cross-sectional nature of the data does not allow us to understand whether a specific factor is a predictor or a consequence of IPV. Further, the data were generated from a sample of partnered Latino SMM recruited primarily through geosocial dating applications, which reduces generalizability. Also, the current study did not examine partner effects. The exploration of cross-partner effects could result in findings that highlight potential risk factors for IPV (e.g., differences in race and/or ethnicity, “outness,” and histories of abuse) or factors that act as a buffer against IPV (e.g., social support, communication skills, and conflict management) as well as address directionality of occurrences of IPV.

Overall, the findings of this study have implications for policy and practice. IPV prevention efforts in Latino communities would be more effective if they were developed to target SMM specifically. Increasing providers’ knowledge about the potential risk factors for IPV unique to Latino SMM is likely to help prevent and address IPV. Specific efforts to address IPV in the Latino SMM community should target depression, problematic drinking, CSA, and race-based discrimination.

Additionally, practitioners working with SMM, particularly Latino SMM, should screen for the specific forms of violent behaviors in which IPV manifests in this community to identify and help those experiencing IPV effectively. Clinical interventions should address the role of intersecting identities with particular attention to the role that discrimination may play on IPV victimhood, assess mental health issues such as depression, problematic substance use, and experiences of childhood abuse among Latino SMM as they potentially contribute to IPV risk. Practitioners are encouraged to implement culturally concordant trauma-informed care with Latino SMM IPV survivors to foster the continuation of care.

The findings highlight the factors associated with the risk of IPV victimization in partnered Latino SMM. The results expand on previous research to suggest a complex interplay of psychosocial factors and Latino-specific factors on IPV victimization among partnered Latino SMM. We specifically bring attention to the role that discrimination (race-based) may play on predicting IPV victimization, and may be added to the list of well-established factors associated with IPV (e.g., CSA, mental health, substance use). Results from the current study suggest potential intervention points that can be addressed to reduce the risk of IPV victimization in this population. Future research should explore how interventions that address psychosocial and culturally relevant factors influence IPV risk in Latino SMM. For instance, future interventions should address the role of intersecting identities, mental health, alcohol abuse, and experiences of childhood abuse as they contribute to IPV risk.

Acknowledgement:

The analyses of these data were supported by a Research Supplement to Promote Diversity in Health-Related Research funded by the National Institute of Drug Abuse (R01DA045613-01S).

Footnotes

Conflict of Interest: Authors report no conflict of interest.

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