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. Author manuscript; available in PMC: 2022 Jan 1.
Published in final edited form as: Psychol Sex. 2020 Mar 10;12(1-2):141–161. doi: 10.1080/19419899.2020.1729848

Intersections between Young Women’s Racial/Ethnic Identities and Sexual Orientation on Rates of Sexual Violence and Substance Use

Alyssa Norris a,b, Carla Rich a, Clair Kaplan c,d, Naomi Krieger a, Kate B Carey e,f, Michael P Carey a,b,e
PMCID: PMC7962142  NIHMSID: NIHMS1567500  PMID: 33738042

Abstract

Background:

Little is known about whether there are differences in rates of sexual violence and its association with substance use based on women’s identities, specifically the intersection of their race/ethnicity and sexual orientation.

Method:

Women (N = 546; 18 to 29 years of age) recruited from a reproductive healthcare clinic reported their race, ethnicity, sexual orientation, sexual violence history and substance use. Five logistic regressions examined (a) rates of sexual violence, and (b) the strength of the associations between sexual violence and four substance use outcomes (heavy alcohol use, marijuana use, cigarette use, number of cigarettes used) based on sexual orientation. Subsequent logistic regressions examined race/ethnicity as a moderator of the associations between sexual orientation and (a) rates of sexual violence and (b) substance use.

Results:

Most women surveyed were heterosexual (64%), and 35% of all women reported unwanted sex. Sexual minority women (SMW) reported higher rates of sexual violence and substance use than heterosexual women. Sexual violence was more strongly associated with heavy alcohol use, but not with marijuana or cigarette use, for SMW than heterosexual women. Rates of sexual violence varied based on the intersection of sexual orientation and race/ethnicity. Although SMW were more likely to report sexual violence than heterosexual women, this association was weaker for Black/Latinx women than for non-Hispanic White women (aOR = 0.39, 95%CI [0.18, 0.82]). Race/ethnicity did not moderate the strength of associations between sexual violence and substance use.

Conclusions:

SMW exhibit increased risk for sexual violence and substance use, and victimization was associated with heavy alcohol use. Few racial/ethnic differences emerged as a function of sexual orientation, so SMW are a group with unique needs around sexual violence experiences and substance use, regardless of race/ethnicity. Healthcare providers should be aware of the link between substance use and prior victimization when treating SMW.

Sexual violence is prevalent among young women (Black et al., 2011). Sexual violence has enduring adverse effects on young women, including heavy alcohol use among female survivors (Norris, Carey, Walsh, Shepardson, & Carey, 2019). In fact, substance use and sexual violence are often co-occurring public health concerns among young women (Lorenz & Ullman, 2016). A large body of research highlights that experiencing childhood sexual abuse and adulthood sexual violence are associated with increased odds of cigarette, marijuana, and alcohol use (Bryan et al., 2016; Kilpatrick, Acierno, Resnick, Saunders, & Best, 1997; Long & Ullman, 2016; Sartor et al., 2015; Sartor et al., 2016). Given that substance use harms young women’s health (e.g., cardiovascular health: Piano, Burke, Kang, & Philips, 2018) and also increases women’s re-victimization risk (Testa, Hoffman, & Livingston, 2010), it is important to identify women at-risk for sexual violence and substance use.

Sexual Violence among Sexual Minority Women

One group of women disproportionately impacted by sexual violence is sexual minority women (SMW; women who report same-sex sexual activity, sexual attraction to women, and/or women who endorse an identity such as bisexual, lesbian, or queer). Compared to heterosexual women, SMW are more likely to experience childhood sexual abuse and sexual violence in adulthood (Balsam, Rothblum, & Beauchaine, 2005; Rothman, Exner, & Baughman, 2011). SMW’s risk of victimization has been contextualized within the minority stress paradigm (cf. McCauley, Coulter, Bogen, & Rothman, 2018) reflecting their marginalized position in the social and structural systems of our culture.

The perpetration of sexual violence and the impact this violence has on survivors is determined by a complex range of factors across social-ecological levels (Campbell, Dworkin, & Cabral, 2009), including relationship factors, social support, and community-level factors. People experience these factors differently because they are viewed and treated differently based on how they are perceived in society; therefore, people might have different experiences with sexual violence as a function of their multiple identities. First, SMW face pervasive discrimination and victimization which, in turn, results in social isolation and marginalization (Meyer, 1995, 2003; Roberts, Austin, Corliss, Vandermorris, & Koenen, 2010). These forces increase their vulnerability to sexual violence (Díaz, Ayala, & Bein, 2004) and also contribute to greater engagement in alcohol, tobacco, and marijuana use (Coulter, Kinsky, Herrick, Stall, & Bauermeister, 2015; Lewis, Mason, Winstead, Gaskins, & Irons, 2016; McCabe, Hughes, West, Veliz, & Boyd, 2019). For example, SMW report higher levels of traumatic childhood events (Merrick, Ford, Ports, & Guinn, 2018), including physical, sexual, and psychological abuse as well as poorer quality attachments with primary caregivers (Balsam et al., 2005; Merrick et al., 2018; Sterzing et al., 2017). Early childhood trauma is associated with poorer mental health (Maercker et al., 2004), sexual risk behavior (Merrick, Litrownik, Everson, & Cox, 2008), and substance use, known risk factors for later victimization (e.g., Miron & Orcutt, 2014; Testa, Hoffman, & Livingston, 2010). Second, the marginalization of same-sex sexuality may mean that sexual minority youth turn to older partners or outlets that increase their exposure to predatory persons (Balsam et al., 2005). Finally, attitudes toward sexual minorities might also contribute to this increased risk. Johnson and Grove (2010) highlight how the sexualization of bisexual women, particularly women of color, contributes to their increased risk of being targeted for assault. Further, bisexual women report pressure to engage in same-sex behavior to “prove” their sexuality or for others’ enjoyment (e.g., Fahs, 2009). These authors highlight how the sexualization of SMW can contribute to assault risk due to implicit perceptual biases (e.g., perpetrators misperceive these women as being sexually interested), or in the form of “corrective rape” meant to teach SMW heterosexuality.

These ecological systems, and how they differentially impact women based on their sexual identities, may interact in distinct ways to influence the strength of associations between sexual violence and its correlates, such as mental health and substance use. Some research suggests that substance use, such as heavy alcohol use and cigarette use, is more strongly associated with the sexual violence histories of SMW than heterosexual women (e.g., Hequembourg et al., 2013; Hughes et al., 2010; Matthews et al., 2018). Minority stress factors, such as poorer quality of social resources, appears to contribute to these disparities. Among sexual violence survivors, SMW report lower levels of social support and more negative reactions to disclosures of their sexual violence experiences (Seabrook, McMahon, Duquaine, Johnson, & DeSilva, 2018; Sigurvinsdottir & Ullman, 2016a) as well as higher levels of depression, posttraumatic stress (PTSD) symptoms, and substance use compared to heterosexual women (López & Yeater, 2018; Sigurvinsdottir & Ullman, 2015, 2016b, 2016a). Negative social reactions to their disclosures are more strongly associated with alcohol and drug misuse among SMW than heterosexual women (Sigurvinsdottir & Ullman, 2015).

Intersectionality: Sexual Orientation, Race/Ethnicity, and Sexual Violence

However, it is important to acknowledge that sexual orientation is but one component of a woman’s identity, and racial/ethnic differences among SMW are understudied. Within an intersectionality framework, multiple historically marginalized identities (e.g., being a female as well as a sexual and racial/ethnic minority) contribute simultaneously to the health and lived experiences of an individual. The impact of minority stress and oppression cannot be confined to a single identity axis. Specific to the experience of violence, structural inequalities impact women as a function of both their sexual orientation and race/ethnicity. However, as highlighted by Crenshaw (1989; 1991), much of our research on sexual violence has focused on the singly-burdened and relatively privileged (e.g., White sexual minorities) rather than what Crenshaw denotes as the “multiply-burdened” (e.g., sexual minority women of color), resulting in frameworks that might not reflect the experiences of, and therefore that further marginalize, racial/ethnic minority SMW. For example, compared to heterosexual women, SMW face a wide array of structural barriers that impact their experiences with violence, including financial barriers to accessing and engaging in healthcare and support systems. Yet, Black and Latinx SMW experience these burdens compounded across their intersecting identities rather than simply in one domain because this is how systems of power and oppression function (Crenshaw, 1991).

As outlined by Crenshaw (1989; 1993) and reiterated by Cole (2009), identities can intersect in three overarching ways. First, experiences in a particular domain may be more similar to members of specific groups depending on the outcome of interest. For example, gender may be more salient to the experience of sexual violence, such that Black women’s experiences may be more similar to White women’s experiences than to Black men’s experiences. Second, the impact of multiply marginalized identities might contribute additively, such that being a woman, a sexual minority, and Black all might contribute additively to victimization experiences given that all are minority status positions. However, many scholars highlight the limitations of this additive perspective. For example, some theorists argue it is not possible to simply “add” minority experiences, as the same structures bind and shape our experiences based on gender, race/ethnicity, sexual orientation, and so forth (e.g., Bowleg, 2008; Crenshaw, 1991; Stewart & McDermott, 2004; Yette & Ahern, 2018). To exemplify this, Stewart and McDermott (2004) use the example of a Latina lesbian mother, who likely shares some approaches to motherhood as lesbians more broadly (e.g., co-mothering) but likely faces unique ways of interacting with society compared to a White lesbian mother. Therefore, in the third approach, the lived experience of a Black or Latinx lesbian is viewed as unique, existing only at the intersection of those identities, unable to be delineated by each identity or viewed simply as a sum of its parts.

Although it is not fully known how race/ethnicity intersects with sexual orientation to increase the risk of experiencing sexual violence, co-occurring marginalized identities are associated with higher rates of victimization more broadly for SMW of color (Bostwick et al., 2019), which might also extend to sexual violence. In addition to higher rates of discrimination due to both their race/ethnicity and their sexual orientation (Balsam, Molina, Beadnell, Simoni, & Walters, 2011), Black and Latinx SMW also report poorer mental health and less social support than both heterosexual women and White SMW (Calabrese, Meyer, Overstreet, Haile, & Hansen, 2015; Kim & Fredriksen-Goldsen, 2012). Importantly, poorer social support and mental health are risk factors for sexual victimization (Krahe & Berger, 2017; Mason et al., 2009). Finally, the sexualization of particular women, such as SMW (Johnson & Grove, 2010) and Black women (Anderson et al., 2018), contributes to more negative attitudes toward these women, such as victim blame (Dupuis & Clay, 2013), and could increase risk of perpetrators targeting them.

Sexual violence at the intersection of race/ethnicity and sexual orientation.

Synthesizing across the limited research work on sexual violence is difficult due to inconsistent findings and method variance, including survey strategies (e.g., national versus community sampling) and demographic differences (e.g., age) known to impact assault risk. SMW of color report higher rates of childhood sexual abuse than White SMW in national surveys (Balsam, Lehavot, Beadnell, & Circo, 2010; Morris & Balsam, 2003). Given that adverse childhood experiences, particularly childhood sexual abuse, are associated with sexual violence in adulthood (Ports, Ford, & Merrick, 2016), these higher rates of childhood abuse might then translate to higher sexual violence rates overall among SMW of color. In contrast to national survey results, researchers in Chicago found that White, Black, and Latinx SMW reported rates of childhood sexual abuse and adult sexual violence that did not differ (Bostwick et al., 2019).

Even if exposure to victimization differs as a function of race/ethnicity and sexual orientation, it is unclear whether correlates of sexual violence, specifically substance use, also differ. This lack of clarity is due largely to there being a dearth of work in this area from intersectional perspective. To our knowledge, only one series of studies using a single sample has examined sexual violence and substance use based on the intersection of women’s sexual orientation and race/ethnicity. In a sample of sexual violence survivors, bisexual women evinced more PTSD symptoms (Sigurvinsdottir & Ullman, 2016b) and “alcohol-related problems” (Sigurvinsdottir & Ullman, 2015) than heterosexual women, but these effects were more pronounced for Black bisexual women compared to White bisexual women. In other words, race moderated the impact of sexual orientation on alcohol-related problems among sexual violence survivors. More research is needed given that these studies relied on a single sample of sexual violence survivors in the Chicago metro area across a wide age range (ages 18 to 71). Nevertheless, given robust associations between distress and substance use, particularly alcohol use (Miranda et al., 2002; Rhew et al., 2017; Stappenbeck et al., 2015), it is possible that racial/ethnic minority SMW with histories of sexual violence might be more likely to engage in substance use than White SMW.

Current Study

SMW are not a monolithic group, and yet much research has treated them as such. Research examining women’s health as a function of intersecting identities has produced a complicated pattern of findings. Some researchers have found that Black and Latinx SMW report greater substance use than both White SMW and heterosexual women (e.g., Sigurvinsdottir & Ullman, 2015), with the most pronounced discrepancy occurring between White heterosexual women and racial/ethnic minority SMW (e.g., Yette & Ahern, 2018). In contrast, other researchers have found that health differences are concentrated as a function of sexual orientation but not the intersection with race/ethnicity (Hsieh & Ruther, 2017).

The present study sought to further our knowledge by examining (a) the rates of sexual violence and (b) the associations between violence and substance use among a sample of young women (ages 18–29). To investigate these aims, we will examine the contribution of sexual orientation and the intersection of race/ethnicity with sexual orientation (i.e., interaction) to (a) women’s risk of experiencing sexual violence and (b) the associations between violence and substance use. We sought to test the following hypotheses:

Hypothesis 1: Sexual Violence Rates and Correlates by Sexual Orientation

  • Hypothesis 1a: SMW will be more likely than heterosexual women to experience sexual violence. This prediction is consistent with prior research (e.g., Rothman et al., 2011),

  • Hypothesis 1b: Sexual violence will be more strongly associated with substance use among SMW than among heterosexual women [also consistent with prior work (López & Yeater, 2018; Sigurvinsdottir & Ullman, 2015)].

Hypothesis 2: Race/Ethnicity Moderates the Effects of Sexual Orientation on (a) Sexual Violence Rates and (b) the Violence-Substance Use Association

After evaluating sexual orientation-based differences, Hypothesis 2 explores race/ethnicity as a moderator of sexual orientation to determine whether there are differences as a function of women’s sexual orientation and race/ethnicity.

  • Hypothesis 2a: No prediction is made about whether sexual orientation-based differences in rates of sexual violence will vary as a function of women’s intersecting sexual and racial/ethnic identities due to inconsistent findings across a small number of studies (e.g., Balsam et al., 2010; Bostwick et al., 2019). This question is exploratory.

  • Hypothesis 2b: Based on the limited work on associations between sexual violence and substance use at the intersection of women’s sexual and racial/ethnic identities (e.g., Sigurvinsdottir & Ullman, 2015), we hypothesized that sexual violence and substance use will be more strongly associated among Black/Latinx SMW than non-Hispanic White SMW. This prediction is tentative given the limited research.

Study Setting

From a methodological perspective, reaching SMW with appropriate preventive services can be challenging (e.g., Guillory et al., 2018). Although not yet explored in research, community reproductive healthcare clinics might be an ideal venue – among health care settings – to reach SMW given their higher rates of STIs (Charlton et al., 2011; Tao, 2008) but lower rates of insurance (Charlton et al., 2018). Given that these clinics are devoted to providing care to low-income and underinsured women regardless of demographic factors, and do not require patients to be connected to regular medical care, they may provide much-needed support to SMW. Further, most young women (defined in this study as 18 to 29 years of age) have seen a reproductive health specialist in the last year (Henderson & Weisman, 2005; Kaiser Family Foundation, 2018) whereas many do not have an ongoing relationship with a traditional primary care practice. Importantly, women presenting for care at reproductive healthcare clinics report higher rates of heavy alcohol use than women in the general population, with 30–40% engaging in heavy drinking in the last month (Cook et al., 2006; Hutton, McCaul, Santora, & Erbelding, 2008). Further, their substance use is associated with their sexual health, such that female patients of these clinics who engage in heavier drinking also report a greater number of sexual partners (Carey, Senn, Walsh, Scott-Sheldon, & Carey, 2016; Hutton et al., 2008). Heavy alcohol use and number of partners are associated with college women’s risk of sexual assault (Messman-Moore et al., 2010; Testa et al., 2010), but it is important to understand these associations among young women outside of college settings as well. Yet, even in reproductive healthcare clinics, women report that their providers seldom discussed sexual violence or substance use with them (Hettema et al., 2015; Kaiser Family Foundation, 2018), despite current recommendations that they do so (Committee on Health Care for Underserved Women Sexual Assault, 2019). Therefore, a goal of this project is to understand the scope of sexual violence among young women presenting for care at a community reproductive healthcare clinic.

Methods

Participants

Young women presenting for care at a reproductive health and family planning clinic in the northeastern U.S. were approached for the study (N = 715 women; aged 18 to 29 years). We limited participation to women ages 18–29 given that this cohort demonstrates the highest rates of substance misuse (Grant et al., 2017; Kanny, Naimi, Liu, Lu, & Brewer, 2018) and sexual violence risk (Planty et al., 2013; Sinozich & Langton, 2014). Women were excluded from the study if they did not read English (n = 15), could not be engaged privately (e.g., had children/family present and could not meet alone; n = 34), or were discharged from care prior to being approached (n = 23). Fifty-one declined to be screened. Therefore, 591 women (M = 23 years old, SD = 3.2) were eligible and consented to completing the screener. One-third (38%) were full-time students, 78% were employed part- or full-time, and they reported an average monthly household income of $1500–2001. The current study presents data on the 546 women who self-identified as non-Hispanic White, Latinx, or Black.

Procedures

These data were collected as part of the screening procedures to identify eligible women for an intervention trial targeting heavy alcohol use and risky sexual behavior (Carey et al., 2019). Research staff approached women presenting for routine care (e.g., any non-surgical visit) and explained the purpose of the study (i.e., to understand women’s health needs), and the role of the screener (i.e., to determine their eligibility for a future study). After consenting to be screened, women completed the survey on a tablet computer in a private room; they were given the chance to ask questions before and after the survey. If a woman reported significant distress, as indicated by an item on suicidal ideation, research staff were trained to immediately notify the healthcare provider, who would have followed the clinic protocol for such circumstances; however, none of the patients reported or demonstrated such distress. The survey took fewer than 5 minutes to complete in order to not disrupt clinic flow. Women were not compensated. Procedures were approved by The Miriam Hospital IRB.

Measures

Sexual Orientation.

Women reported their sexual attraction as follows: Only attracted to males; mostly attracted to males; equally attracted to females and males; mostly attracted to females; only attracted to females; not sure. This assessment item was chosen in line with recommendations to measure attraction rather than categorial identity or behavioral items (Pega, Gray, Veale, Binson, & Sell, 2013; Savin-Williams, 2016). Most women reported exclusively heterosexual sexual attraction (64%), followed by mostly heterosexual (25%) and bisexual (11%). Although 11 women in the full sample endorsed attraction mostly or only to women, they did not report on their race/ethnicity or did not identify as White, Black, or Latinx. Given the small number of women in each cell, this variable was dichotomized to reflect an exclusively heterosexual orientation (n = 340; 64%) or a sexual minority orientation (n = 191; 36%).

Race.

Women were asked, “Which of the following best describes your background?” Women were encouraged to select all options that applied from the following six options: American Indian or Alaska Native (n = 22), Asian (n = 39), Native Hawaiian or Pacific Islander (n = 4), African American or Black (n = 121), White or Caucasian (n = 351), “Unknown or don’t want to answer” (n = 72). Almost all of the women who did not select a racial identity (n = 69; 96%) identified as Hispanic/Latinx.

Ethnicity.

Women were asked if they considered themselves to be Hispanic/Latinx. Women who endorsed “yes” in response to this question were considered to be Latinx regardless of other racial identities. Women were considered to be non-Hispanic White if they endorsed no to this question, identified as White or Caucasian in response to the racial identity questions, and did not endorse any other racial identities. Ethnicity was dummy coded to reflect women who identified as non-Hispanic White only (n = 268) and women who identified as Latinx (n = 182; 34% of sample).

Sexual violence.

Given the nature of the survey (i.e., to quickly assess women’s needs in a brief screening assessment), women responded to two questions about sexual violence assessing verbal coercion and forced sex (“Have you ever been pressured or forced to have sex?” No; Yes) and unwanted sex due to incapacitation (“Have you ever had sex when you did not want to because you were drunk or high?”). Women reported whether or not this occurred in their lifetime. Responses on these two questions were combined to create a composite variable that reflected lifetime sexual violence (No, Yes).

Substance use.

Women reported their weekly alcohol use over the last 3 months as follows: “During the last 3 months, how many drinks did you consume in a typical week?” This variable was recoded to reflect heavy alcohol use in line with the definitions of low-risk and excessive drinking by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and the Department of Health and Human Services (U. S. Department of Agriculture, 2015) (i.e., >7 drinks per week; dichotomous). We used weekly drinking because women’s weekly alcohol use patterns (especially exceeding 7 drinks per week for women) is associated with increased risk for all causes of death (Wood et al., 2018).

Women also reported their use of cigarettes and marijuana in the last 30 days as follows: 0 = never used; 1 = have used, but not in the last 30 days; 2 = 1–9 days; 3 = 10–19 days; 4 = 20–29 days; 5 = used every day, consistent with existing national survey instruments (e.g., National College Health Assessment). These two variables were dichotomized to represent last-month marijuana use and last-month cigarette use consistent with existing research using these items (Jones & Cunningham-Williams, 2016). If women reported current cigarette smoking, they were also asked the following open-ended question: “When you smoke cigarettes, about how many cigarettes do you smoke in a day?” (count variable).

Data Analytic Plan

Our initial goal was to compare health outcomes of non-Hispanic White women to those of women who identified only as (a) non-Hispanic Black, or (b) Latinx in separate contrasts. However, this was not feasible given the (a) substantial overlap between these racial/ethnic identities as well as (b) small cell sizes in crosstabs of racial/ethnic identities, sexual orientation, and sexual victimization (<10 women). One-third (31%) of Black women in our sample identified as Latinx, which was higher than the 5–12% anticipated from Providence census data (U.S. Census Bureau, 2018a, 2018b) or national data (e.g., Vaquera & Kao, 2006). However, among individuals in Providence identifying as Latino/a, 46% identify as Dominican (19% of all Providence residents) (U.S. Census Bureau, 2018c). In the Dominican Republic, a majority of residents identify as “mixed race” or Black and many identify as Afro-Latino (López & Gonzalez-Barrera, 2016). Therefore, this sample might reflect a larger proportion of women from these areas with intersecting Black and Latinx identities.

Due to our inability to compute specific contrasts by race/ethnicity, we conducted an analysis of study outcomes by racial/ethnic identification to support the decision to consider these women within one collapsed group. To do so, we compared non-Hispanic White women to Black women and to Latinx women, all-inclusive (i.e., women in the Black category included women who identified as Black Latinx women) (Table 1). These analyses demonstrated that Black and Latinx women evinced similar rates of sexual violence and substance use, and also had the same pattern of results when compared to non-Hispanic White women. Further, the decision not to prioritize one minority identity over another is consistent with prior research on the inadequacy of existing racial categories among Latinx populations. For example, the majority of Latinx respondents in research choose “other” as their racial category or do not select a race (Vaquera & Kao, 2006). Therefore, in line with evidence of the (a) substantial overlap in the inclusive categories of Black and Latinx women; (b) non-significant differences in the outcomes of interest (i.e., sexual violence and substance use); and (c) prior research on the difficulty of selecting racial identities using these existing Census-based instruments within Latinx populations (e.g., Vaquera & Kao, 2006), we chose to examine Black and/or Latinx women’s experiences collectively. Therefore, subsequent analyses compared non-Hispanic White women (n = 276) to Black and/or Latinx women in a single contrast (n = 270).

Table 1.

Rates of sexual minority status, sexual violence history, and substance use by racial/ethnic identity.

Non-Hispanic White
n = 276
n (%)		 Latinx
n = 185a
n (%)		 χ2 Black
n = 121a
n (%)		 χ2
Sexual Minority 108 (40%) 58 (32%) 3.31 38 (33%) 1.95
Sexual Violence 119 (43%) 51 (28%) 11.50*** 31 (26%) 10.95***
Heavy Alcohol Use 47 (17%) 22 (12%) 2.28 17 (14%) 0.57
Marijuana User 125 (45%) 80 (44%) 0.15 57 (47%) 0.11
Cigarette User 72 (26%) 24 (13%) 11.46*** 18 (15%) 6.02*
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Note.

***

p < .001.

**

p < .01.

*

p < .05.

a

Sample sizes are non-exclusive (e.g., includes all women who self-identified as Black, regardless of whether they also identified as other identity categories). Heavy alcohol use refers to exceeding the weekly drinking limit for moderate drinking as defined by NIAAA. Chi-square significance reflects non-Hispanic White women as the contrast group for Latinx and Black women.

Age and income were included as covariates given evidence that lower-income women are at greater risk for sexual violence (Planty et al. 2013) and that minority women report lower incomes than White women (Fontenot, Semega, & Kollar, 2018). Age was included due to the focus on lifetime violence (e.g., older women have more time to experience violence so should report higher lifetime rates). Logistic regression analyses (controlling for age and income) modeled associations between race/ethnicity and sexual orientation on sexual violence (dichotomous) and binary substance use outcomes (heavy alcohol use; current marijuana user; current cigarette smoker). Among women who used cigarettes, Poisson regression modeled number of cigarettes smoked. The number of cigarettes smoked by current smokers was examined for outliers in line with Tabachnick and Fidell’s (2007) recommendations (z scores ≥ 3.29). None were identified.

There were few missing data. The item with the most missing data was cigarette use (n = 4; <1%). All other variables had ≤ 2 missing cases (≤ 0.4%) out of 546. Missing data were handled via listwise deletion.

The first hypothesis focused on sexual orientation-based differences. Hypothesis 1a evaluated the significance of the main effect of sexual orientation on sexual violence rates. Hypothesis 1b evaluated the four substance use outcomes, so four regression analyses were performed (i.e., one for each outcome). The first step involved presenting the findings for the main effect of sexual orientation. Subsequently, the interaction term between sexual orientation and sexual violence history was added to the model to test whether the strength of the association between sexual violence and substance use differed as a function of sexual orientation. In the presence of significant interactions, post-hoc regressions were performed separately based on women’s sexual orientation to determine whether sexual violence history was significantly associated with substance use for both heterosexual women and SMW.

Hypothesis 2 added race/ethnicity as a predictor to the models outlined above. The primary goal of these analyses was to determine whether SMW’s experiences differed as a function of their race/ethnicity (e.g., moderation). Therefore, the interaction between sexual orientation and race/ethnicity was the primary focus of Hypothesis 2a (sexual violence rates) and Hypothesis 2b (substance use). However, to aid in the interpretation of any interaction terms, we first present the main effect of race/ethnicity in each model. Subsequently, in Hypothesis 2, we evaluate the 2-way interaction term of race/ethnicity-by-sexual orientation. Finally, in Hypothesis 2b, we modeled the 3-way interaction between race/ethnicity, sexual orientation, and sexual violence history. In line with the purpose of the study to understand the impact of race/ethnicity in the context of sexual orientation and because all predictors were binary, post-hoc analyses probed any significant interactions by stratifying by race/ethnicity to determine whether any observed differences by sexual orientation were present across racial/ethnic groups. Analyses were performed in SPSS version 24.0.

Results

SMW (Mean = 23.14, SD = 3.20) were older than heterosexual women (Mean = 22.51, SD = 3.14) (t [529] = −2.19, p < .05), whereas Black/Latinx women (Mean = 22.08, SD = 2.93) were younger than non-Hispanic White women (Mean = 23.40, SD = 3.28) (t [523] = 4.97, p < .001). Household income did not differ based on sexual orientation (t [529] = −0.21, p = .83), but did differ based on race/ethnicity (t [523] = 3.43, p = .001), such that racial and/or ethnic minority women reported a lower monthly income than non-Hispanic White women. Therefore, all regression analyses controlled for age and income.

Hypothesis 1: Sexual Violence Rates and Correlates by Sexual Orientation

  • Hypothesis 1a: Rates of sexual violence. SMW were more than three times as likely to experience sexual violence as heterosexual women (53% versus 24%) (aOR = 3.31, 95%CI [2.28, 4.80]).

  • Hypothesis 1b: Associations between sexual violence and substance use. Rates of substance use as a function of sexual violence history and sexual orientation are displayed in Figure 1 and Table 2.

Figure 1.

Figure 1.

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Rates of substance use as a function of sexual violence history and sexual orientation (Hypothesis 1b).

Table 2.

Rates of substance use based on lifetime sexual violence history and sexual orientation.

Heavy Alcohol Use Marijuana User Cigarette User
No History of Sexual Violence Heterosexual 11% 31%b 12%c
Sexual Minority 14%a 60% 28%c
Survivor of Sexual Violence Heterosexual 6% 53%b 20%c
Sexual Minority 28%a 57% 33%c
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Note.

a

Significant difference in odds of heavy alcohol use among sexual minority women as a function of sexual violence history.

b

Significant difference in odds of marijuana use among heterosexual women as a function of sexual violence history.

c

Significant main effect of sexual orientation, such that SMW were more likely to be current smokers, but there was no interaction with sexual violence history (i.e., this effect did not differ as a function of sexual violence history).

Heavy alcohol use.

SMW were more likely to engage in heavy alcohol use than heterosexual women (aOR = 2.30, 95%CI [1.39, 3.82]). There was a significant interaction between sexual orientation and sexual victimization history (aOR = 4.59, 95%CI [1.36, 15.44]) in predicting heavy alcohol use. Post-hoc regression revealed that sexual violence history was not associated with heterosexual women’s odds of heavy alcohol use (aOR = 0.50, 95%CI [0.19, 1.33]) but was significantly associated with SMW’s heavy alcohol use (aOR = 2.33, 95%CI [1.15, 4.73]), Specifically, 14% of SMW without a violence history reported heavy alcohol use, whereas 28% of women who experienced sexual violence did so.

Marijuana use.

SMW were more likely to have used marijuana in the past 30 days than heterosexual women (aOR = 2.24, 95%CI [1.54, 3.25]). There was a significant interaction between sexual orientation and sexual violence (aOR = 0.38, 95%CI [0.18, 0.81]) on marijuana use. Post-hoc analyses revealed that sexual violence was not associated with marijuana use among SMW (aOR = 0.94, 95%CI [0.53, 1.65]), but it was among heterosexual women (aOR = 2.51, 95%CI [1.51, 4.17]). Whereas 31% of heterosexual women without a history of sexual violence used marijuana in the last month, 53% of heterosexual women who experienced sexual violence had done so. In contrast, 60% of SMW without a history of sexual violence versus 57% of SMW with a history of sexual violence used marijuana.

Cigarette use.

SMW were more likely to have used cigarettes in the past 30 days than heterosexual women (aOR = 1.60, 95%CI [1.47, 3.65]). Among current smokers (n = 118), SMW (Mean = 5.46) smoked a greater number of cigarettes per day than heterosexual women (Mean = 5.00) (IRR = 1.21, 95%CI [1.02, 1.44]). The 2-way interaction between sexual orientation and sexual violence was not significant in predicting odds of being a current smoker (aOR = 1.45, 95%CI [0.58, 3.58]) or number of cigarettes smoked among current smokers (IRR = 1.40, 95%CI [0.98, 2.01]).

Hypothesis 2: Race/Ethnicity Moderates the Effects of Sexual Orientation on (a) Sexual Violence Rates and (b) the Violence-Substance Use Association

  • Hypothesis 2a: Rates of sexual violence. Black/Latinx women were half as likely as non-Hispanic White women to report sexual violence (27% versus 43%) (aOR = 0.51, 95%CI [0.35, 0.74]). There was a significant interaction between sexual orientation and race/ethnicity in predicting odds of sexual violence (aOR = 0.39, 95%CI [0.18, 0.82]), such that the association was weaker among Black/Latinx women than White SMW. Post-hoc regression analyses by race/ethnicity revealed that SMW had a greater risk of experiencing sexual violence than heterosexual women if they were White (65% versus 26%; aOR = 5.37, 95%CI [3.15, 9.16]) or Black/Latinx (39% versus 21%; aOR = 2.00, 95%CI [1.17, 3.44]). Therefore, SMW had higher rates of sexual violence regardless of race/ethnicity. However, the sexual orientation discrepancy was more pronounced for White women (Figure 2).

  • Hypothesis 2b: Associations between sexual violence and substance use. This hypothesis was tested in four steps. First, prior to examining the interaction effects, we added the main effect of race/ethnicity to the models of marijuana, heavy alcohol, and cigarette use to guide in subsequent interpretation of any significant effects. Subsequently, we then modeled all 2-way interactions with race/ethnicity for each substance use outcome (i.e., race/ethnicity × sexual orientation; race/ethnicity × sexual violence history). Third, we analyzed the 3-way interaction between race/ethnicity, sexual orientation, and sexual violence history for each substance use outcome. Finally, any significant interactions were probed post-hoc. Given our focus on understanding racial/ethnic differences as a function of sexual orientation, we examined how sexual orientation was associated with substance use outcomes separately for non-Hispanic White women and Black/Latinx women. These post-hoc regressions are reported where relevant in that given step.

Figure 2.

Figure 2.

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Rates of sexual violence as a function of sexual orientation and race/ethnicity (Hypothesis 2a).

Step 1: Main effect of race/ethnicity.

There were no main effects of race/ethnicity on rates of heavy alcohol use (aOR = 0.83, 95%CI [0.50, 1.38]) or marijuana use (aOR = 1.01, 95%CI [0.74, 1.48]). There was a main effect of race/ethnicity in predicting cigarette use (aOR = 0.52, 95%CI [0.32, 0.83]), such that Black/Latinx women (13%) were less likely to be current smokers than non-Hispanic White women (26%). Among current smokers, there was also a main effect of race/ethnicity on cigarettes smoked (IRR = 0.74, 95%CI [0.61, 0.89]), such that Black/Latinx women (Mean = 4.51) reported smoking fewer cigarettes than did non-Hispanic White women (Mean = 5.94).

Step 2: 2-way interactions with race/ethnicity.

There were no significant interaction effects between race/ethnicity and sexual violence history in the rates of heavy alcohol use (aOR = 0.39, 95%CI [0.14, 1.13]), marijuana use (aOR = 0.95, 95%CI [0.45, 2.00]), or cigarette use (aOR = 1.08, 95%CI [0.42, 2.77]). Among current smokers, the 2-way interaction was not significant (IRR = 0.98, 95%CI [0.68, 1.43]).

Regarding 2-way interactions between race/ethnicity and sexual orientation, there were no significant 2-way interactions in predicting odds of heavy alcohol use (aOR = 0.56, 95%CI [0.19, 1.60]), marijuana (aOR = 1.42, 95%CI [0.66, 3.07]), or cigarette use (aOR = 1.25, 95%CI [0.47, 3.35]). However, among current smokers, the 2-way interaction between race/ethnicity and sexual orientation (IRR = 2.59, 95%CI [1.62, 4.15]) was significant in the number of cigarettes smoked. Post-hoc regression analyses were conducted to explore the effect of sexual orientation by race/ethnicity. Although SMW smoked a greater number of cigarettes than heterosexual women overall, this pattern differed by race/ethnicity, such that it was present only for Black/Latinx women (IRR = 2.11, 95%CI [1.43, 3.13]) but not White women (IRR = 1.00, 95%CI [0.82, 1.23]). Among non-Hispanic White women, heterosexual women smoked a similar number of cigarettes (Mean = 6.55) as SMW (Mean = 5.68). In contrast, among Black/Latinx women, SMW smoked more (Mean = 5.50) than heterosexual women (Mean = 2.62).

Step 3: 3-way interaction.

There were no significant 3-way interactions in predicting odds of heavy alcohol use (aOR = 0.56, 95%CI [0.19, 1.60]), marijuana use (aOR = 0.94, 95%CI [0.19, 4.74]) or cigarette use (aOR = 2.80, 95%CI [0.35, 22.47]). Among current smokers, the 3-way interaction was also not significant for number of cigarettes smoked per day (IRR = 2.00, 95%CI [0.54, 7.46]).

Discussion

The current study clarifies rates of sexual violence and the association between sexual violence and substance use among SMW by investigating differences by race/ethnicity. Perhaps most notably, sexual orientation-based differences were largely consistent across race/ethnicity, such that both White and Black/Latinx SMW experience higher rates of violence than their heterosexual counterparts. Similarly, there were no racial/ethnic differences in the strength of the associations between sexual violence and substance use as a function of sexual orientation. Therefore, these findings provide support for prior arguments that the discrimination and oppression related to intersecting identities cannot simply be assumed to confer harm in an additive fashion as a function of how many marginalized identities a woman holds (Bowleg, 2008; Cole, 2009). Indeed, finding that the sexual orientation-based discrepancy in rates of sexual violence was more pronounced for White SMW than for Black/Latinx SMW highlights the nuanced nature of women’s intersecting identities and the need to look “upstream” to better understand the structural and group processes that underlie these inequalities (Weber & Parra-Medina, 2003).

Sexual Violence and Alcohol Use: Higher Rates and Stronger Association among SMW

SMW were more likely to experience lifetime sexual violence, and they also display stronger associations between their sexual violence histories and current heavy alcohol use, consistent with prior research (Hughes et al., 2010; López & Yeater, 2018; Rothman et al., 2011). Therefore, despite the associations between heavy alcohol use and sexual violence in young women generally (e.g., Abbey, 2001), these are particularly notable for SMW. These findings are important for several reasons. First, it is concerning that nearly one-third of SMW with a history of sexual violence engaged in heavy alcohol use (i.e., >7 drinks per week) given that this level of drinking (a) is associated with greater all-cause mortality (Wood et al., 2018), (b) mediates the likelihood of being sexually revictimized in the future (Norris et al., 2018; Testa et al., 2010), and (c) is associated with poorer mental health (e.g., Powers, Duffy, Burns, & Loxton, 2016).

Second, the stronger association between sexual violence and alcohol use among SMW highlights the need for integrated prevention efforts that concomitantly target sexual violence risk and heavy alcohol use among SMW. Such programs have demonstrated efficacy with young women more broadly (e.g., Gilmore et al., 2014) and may be adapted for SMW. Of note, education to prevent sexual violence should be multifactorial and target multiple ecological systems, including support services for survivors, reducing perpetration rates, and improving institutional responsivity and regulations; engaging populations at-risk for being assaulted is viewed as one portion of this prevention programming. Therefore, this work should in no way be misconstrued to reflect blame on anyone but the perpetrators of these violent acts. Policy and research efforts should also seek to mitigate both the perpetration of violence against these women as well as the lack of adequate support following assault experiences.

SMW with a history of sexual violence may be more likely to engage in heavy alcohol use than heterosexual women for several potential reasons. Among women who have experienced sexual violence, SMW report higher levels of distress (Sigurvinsdottir & Ullman, 2015), less social support, more negative reactions to disclosure (Sigurvinsdottir & Ullman, 2016b), and greater reliance on substances to cope (López & Yeater, 2018). Although not assessed in this study, this confluence of factors (i.e., lack of coping resources, poorer social support, greater distress) likely contribute to SMW’s heavier drinking (Stappenbeck et al., 2015). However, as this study is not causal, it is important to note that the marginalization of SMW that increases risk of engaging in substance use also confers risk for experiencing sexual violence (cf. McCauley et al., 2018). Therefore, it is likely a confluence of factors that contributes to this stronger association between heavy alcohol use and violence.

In contrast, SMW were more likely to use marijuana and cigarettes regardless of violence history. Only heterosexual women evinced an association between sexual violence and marijuana use, and neither heterosexual nor SMW exhibited an association between cigarette use and sexual violence (Figure 1). There are several potential explanations for this different pattern of findings for alcohol versus marijuana and cigarette use. First, SMW’s marijuana use was elevated such that their use might be less sensitive to any experiences of sexual violence specifically. During adolescence, half of sexual minority girls report using marijuana, compared to only 21% of heterosexual girls (Marshal et al., 2013). More work is needed to understand trajectories and determinants of marijuana use as sexual minority girls age into and across adulthood. Second, the motivational context for cigarette and marijuana use might differ from heavy alcohol use (e.g., Simons et al., 2000). Second, marijuana and cigarette use might not be as closely associated with violence risk as heavy alcohol use because of less exposure to perpetrators (e.g., bar patronage and perpetrators’ alcohol-sex expectancies; Abbey et al., 2001). Finally, it is possible that methodological differences in the way that substance use was assessed produced different results. The measure of alcohol use focused on heavy alcohol consumption whereas the marijuana and cigarette measures reflected any use, due to less clear guidelines for hazardous use. It is possible that our alcohol measure was more sensitive. However, measures for cannabis consumption are less precise (Cuttler & Spradlin 2017). Therefore, future research should examine indicators of heavier or more persistent marijuana use, as research with other populations suggests a strong association between traumatic experiences and marijuana use (Metrik, Jackson, Bassett, Zvolensky, Seal, & Borsari, 2016).

Intersecting Racial/Ethnic and Sexual Orientation Identities: Non-Additive Effects

Scholars have highlighted the importance of taking more nuanced intersectional perspectives that do not simply assume women with multiple minority identities experience the worst outcomes in an additive fashion (e.g., Bowleg, 2008). The current findings provide empirical support for this view, in that there were few differences in rates of sexual violence, substance use, or their intersection as a function of both race/ethnicity and sexual orientation. Instead, SMW evinced elevated rates of sexual violence and all substance use outcomes, with few differences by race/ethnicity. In fact, there was only one indicator suggesting that Black/Latinx SMW had poorer health outcomes compared to White SMW, and that was for cigarette use.

In contrast to the hypothesis that dual minority status might expose SMW of color to even greater risks, it was White SMW who exhibited the highest rates of violence. Consistent with this study’s focus on intersectionality, it is important to interpret findings mindfully given women’s other characteristics. The current sample was predominantly lower-income, such that half of the sample (45% of White; 56% of Black/Latinx) reported an annual income less than $18,000. Given that Black/Latinx women in the national population report lower incomes (Fontenot et al., 2018), which is a risk factor for violence (Planty et al., 2013), research findings should be interpreted in the context of income (e.g., Lewis et al., 2017). Therefore, it might be that White SMW of lower socioeconomic status, as in this study, have the highest rates of violence, but this might not generalize to other populations of women.

Because we did not assess explanatory mechanisms of risk, it is not clear why White SMW are at higher risk of sexual violence. However, we hypothesize there are several factors that might explain why non-Hispanic White SMW have increased risk of sexual violence compared to non-Hispanic White heterosexual women as well as Black/Latinx SMW. First, these findings might reflect a reporting artifact. It is possible that the differences observed between Black/Latinx and White SMW reflect cultural differences in what women (a) consider to be sexual violence and (b) are willing to disclose to a stranger in a medical research setting. Latinx women appear less likely to consider some unwanted sexual acts as “assault.” For example, among married women who have experienced forced sex by their spouse, Latinx women are less likely to label this as “rape” (Bergen, 1996). Further, disclosing sexual violence, particularly to someone unknown to the participant, is more normative in Anglo compared to Latinx cultures (Cuevas & Sabina, 2010). Given that most women in our racial/ethnic minority group (69%) identified as Latinx, these cultural mores might contribute to hesitancy to disclose unwanted sex within a research study. These cultural differences in reporting sexual behaviors might be even more pronounced among SMW. Black SMW report sexual orientation stigma and race-based mistrust within medical settings, which predicts low engagement with healthcare (Brenick, Romano, Kegler, & Eaton, 2017). Therefore, Black/Latinx SMW might be the least likely to disclose sensitive sexual information in the context of this research study with non-familiar researchers.

Second, it is possible that the results reflect true differences in sexual violence rates. However, given the study’s focus on lifetime rates of sexual violence, it is unclear whether White SMW face pronounced risk just in childhood/adolescence, in adulthood, or across their lifetime. Future research clarifying this pattern of risk would also enhance understanding about the mechanisms driving these discrepancies. For example, if White SMW face heightened risk primarily in adolescence and adulthood, then perhaps something makes them more vulnerable to perpetrators, such as White bisexual women’s heavier alcohol use (Kim & Fredriksen-Goldsen, 2012), which is associated with increased risk of sexual violence (Testa et al., 2010). More nuanced examinations of how women’s identities intersect is warranted given the variability in research methods (e.g., assessment instruments) and the conceptualization of sexual orientation, race/ethnicity, and sexual violence.

In contrast to rates of sexual violence, victimization history was consistently associated with substance use based on sexual orientation, and this did not differ as a function of race/ethnicity. Although little work has examined the strength of the association between violence and substance use based on intersectionality among SMW, finding that race/ethnicity did not interact with sexual violence history to influence substance use is consistent with prior meta-analytic work on race/ethnicity more broadly (Dworkin, Menon, Bystrynski, & Allen, 2017). However, these findings contrast with the work of Sigurvinsdottir and Ullman (2015; 2016a; 2016b) on sexual assault survivors. These authors found that Black bisexual assault survivors evince greater rates of alcohol problems specifically than White bisexual women and heterosexual women. Several methodological differences might explain the mixed nature of the findings. First, there might be important differences between the experiences of Black women who have experienced sexual violence in Chicago, and the experiences of Black/Latinx women in this study. Second, we recruited from a community-based healthcare clinic and limited participation to women aged 18–29, regardless of victimization status. In contrast, Sigurvinsdottir’s research focused exclusively on women reporting a history of sexual violence and targeted university students, agencies that directly serve survivors of violence (e.g., rape crisis centers), and substance use treatment centers, recruiting women ages 18 to 71. It is possible that recruiting women from these settings might reflect women engaging in heavier and different patterns of substance use. For example, women’s substance use changes temporally as a function of time following an assault (e.g., Kaysen et al., 2011; Kilpatrick et al., 1997). Therefore, recruiting women who recently experienced an assault might reflect very different patterns of use than in our study. Third, it is possible that heavy alcohol use does not differ, but that alcohol problems do differ. These contradictory findings highlight the need for more research in order to provide more information in this area. Finally, without a more nuanced understanding of differences in racial composition at their recruitment sites, it is difficult to synthesize results across studies. Nevertheless, it is possible that if racial demographics differed across sites (e.g., more Black women recruited from community sites) then reported substance use might also differ. This underscores the need for research to understand which subgroups of SMW are most at risk.

Limitations

These findings should be interpreted in light of the study limitations. First, this study is cross-sectional; thus, causal pathways between substance use and violence risk are not warranted. For example, prior research highlights the role of substance use in prospectively predicting violence risk, and vice versa (Norris et al., 2019; Testa et al., 2010). However, regression analyses demonstrate associations between these constructs rather than directionality. Regardless, the strength of the associations between sexual violence history and substance use support efforts to develop prevention programming that concurrently reduces women’s risk for substance use, assault, and distress (e.g., Gilmore et al., 2014).

Second, we used global demographic identity variables that limited our ability to identify nuanced cultural variation. Our analyses focused on non-Hispanic White women compared to Latinx and/or Black women; there is variation in drinking patterns, consequences from alcohol use, and sexual behavior among and within racial and ethnic subgroups (Caetano, Clark, & Tam, 1998; Gil, Wagner, & Vega, 2000; Lui & Zamboanga, 2018; Ríos-Bedoya & Freile-Salinas, 2014). Relatedly, we did not measure level of acculturation, which contributes to differences in sexual behavior and substance use (Lui & Zamboanga, 2018). Given the inherent limitations to investigating intersectionality via quantitative research (Bowleg, 2008; Cole, 2009; Crenshaw, 1993), future research might use mixed methods research to investigate how women make meaning of their assault experiences and coping, as some have done with SMW in general (cf. López & Yeater, 2018). Third, we recruited women from one clinic in the northeastern U. S. Assessing geographic differences by sampling from multiple clinics in different locations is a worthwhile next step, particularly given the demographic makeup of this sample.

Fourth, we operationalized sexual orientation based on sexual attraction, and few women reported attraction only to women. This is important, because rates of sexual violence and substance use differ within sexual minority subgroups. Bisexual and mostly heterosexual women have the highest rates of sexual violence (Rothman et al., 2011; Walters, Chen, & Breiding, 2013) and substance use (Marshal et al., 2008), as well as the strongest associations between violence and heavy alcohol use (Hughes et al., 2010). Further, research on health outcomes based on intersections of sexual orientation and race/ethnicity have revealed nuanced differences by bisexual versus lesbian identities, with some researchers finding that White bisexual women report the poorest quality health compared to White heterosexual and Black bisexual women (e.g., Yette & Ahern, 2018). Therefore, this study might not generalize to lesbian women in particular, and the findings highlight that a reproductive health clinic like this one might have low reach to lesbian women specifically. Investigating these associations using more nuanced measures of sexual orientation is encouraged.

Fifth, the study prioritized engagement by choosing brevity in screening measures, including our assessment of sexual violence. This operationalization did not allow for the understanding of severity, frequency, nor timing/recency of victimization. However, these might be important variables with explanatory power. For example, in samples of SMW, assault severity predicts greater substance use (Gilmore et al., 2014). Similarly, some researchers have found different associations between how women were assaulted (e.g., incapacitated versus forcible) and substance use (McCauley, Ruggiero, Resnick, Conoscenti, & Kilpatrick, 2009). Therefore, future work might investigate the characteristics of women’s sexual violence experiences to better understand the observed risk of SMW in this sample.

Conclusions

Women present to reproductive health clinics with high rates of sexual violence, and women with a history of sexual violence report greater substance use. However, the rates of sexual violence, as well as how it is associated with substance use, differ mostly as a function of women’s sexual orientation, although there are several differences by race/ethnicity. In this sample of predominantly low-income women, non-Hispanic White SMW reported the highest rates of sexual violence. Continued research is needed to understand the mechanisms of this risk. Therefore, there is a need for services to directly support SMW regarding substance use, and services for alcohol use specifically should be trauma-informed.

Table 3.

Substance use rates by racial/ethnic identity, sexual minority status, and history of sexual victimization.

Non-Hispanic White
n = 268		 Black/Latinx
n = 263
Heterosexual Sexual Minority χ2 Heterosexual Sexual Minority χ2
Heavy Alcohol Use
No SV 10% 18% 1.83 12% 12% 0.01
SV History 10% 32% 7.38** 2% 21% 7.56**
Marijuana User
No SV 32% 53% 5.30* 30% 64% 21.00***
SV History 55% 56% 0.01 51% 61% 0.74
Cigarette User
No SV 15% 40% 10.11*** 9% 20% 5.14*
SV History 26% 37% 1.30 13% 27% 2.42
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Note.

***

p < .001.

**

p < .01.

*

p < .05. SV = sexual violence.

Heavy alcohol use refers to exceeding the weekly drinking limit for moderate drinking as defined by NIAAA. Chi-square significance tests comparing sexual orientation differences based on sexual victimization. Tests reflect non-Hispanic White women as the contrast group for Black/Latinx women.

Acknowledgments

We gratefully acknowledge the contributions of the study participants as well as the staff at the Providence Health Center. This research was supported by a grant R34-AA023158 from the National Institute on Alcohol Abuse and Alcoholism to Michael P. Carey. The funding sources did not influence the outcomes of our work. The authors declare that they have no competing interests. The findings and conclusions in this article are those of the authors and do not necessarily reflect the views of the National Institute on Alcohol Abuse and Alcoholism or the Planned Parenthood Federation of America.

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