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research-article2013

JAPXXX10.1177/1078390313511328Journal of the American Psychiatric Nurses Association 19(6)Herrick et al.

Advancing Health Equity in Disparity Populations: Lesbian, Gay, Bisexual, and Transgender People

Demographic, Psychosocial, and Contextual Factors Associated With Sexual Risk Behaviors Among Young Sexual Minority Women

Journal of the American Psychiatric Nurses Association 19(6) 345­–355 © The Author(s) 2013 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1078390313511328 jap.sagepub.com

Amy Herrick1, Lisa Kuhns2, Suzanne Kinsky3, Amy Johnson4, and Rob Garofalo5

Abstract Young sexual minority women are at risk for negative sexual health outcomes, including sexually transmitted infections and unintended pregnancies, yet little is known about these risks. We examined factors that may influence sexual risk from a psychosocial and contextual perspective. Analyses were conducted to examine within group relationships between sexual behaviors, negative outcomes, and related factors in a sample of young sexual minority women. Participants (N = 131) were young (mean = 19.8) and diverse in terms of race/ethnicity (57% non-White). Sex under the influence, having multiple partners, and having unprotected sex were common behaviors, and pregnancy (20%) and sexually transmitted infection (12%) were common outcomes. Risk behaviors were associated with age, alcohol abuse, and older partners. Results support the need for further research to understand how these factors contribute to risk in order to target risk reduction programs for this population. Keywords lesbian and bisexual girls, sexual minority, sexual risk behaviors, sexually transmitted infections, pregnancy, adolescent health

Introduction Despite declines in pregnancy rates and certain types of sexual activities among teenagers in recent years (Centers for Disease Control and Prevention [CDC], 2011; Hamilton & Ventura, 2012), the overall rate of unintended pregnancy has remained unchanged (Finer & Zolna, 2011; Mosher, Jones, & Abma, 2012), and unintended pregnancies among teenage women is double that of adult women (Finer, 2010). As many as a quarter of young women ages 14 to 19 years have had a sexually transmitted infection (STI; Forhan et al., 2009). In 2011, for young women ages 15-19, rates of Chlamydia increased 3.5% from 2010 (CDC, 2012) and rates of both Chlamydia and Gonorrhea were the second highest compared to any other age group (CDC, 2012). The prevention of negative sexual health outcomes among young women, including unintended pregnancy, STIs, and infertility secondary to STIs, is a major objective of Healthy People 2020 (U.S. Department of Health and Human Services [HHS], 2011). Recent findings suggest that young sexual minority women (YSMW) may be at particular risk for negative sexual health outcomes (Austin,

Roberts, Corliss, & Molnar, 2008; Mays, Yancey, Cochran, Weber, & Fielding, 2002). YSMW are individuals who self-label as lesbian, bisexual, or other nonheterosexual identity or are attracted to or have sex with women, estimated to be comprise approximately 5% to 15% of female adolescents (Russell & Joyner, 2001; Savin-Williams & Ream, 2007). Despite a once-common perception that YSMW are at less risk of negative sexual health outcomes compared to heterosexuals (White, & Dull, 1997; Marrazzo, Coffey, & Bingham, 2005), 1

Amy Herrick, PhD, University of Pittsburgh, Pittsburgh, PA, USA Lisa Kuhns, PhD, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, USA 3 Suzanne Kinsky, MPH, University of Pittsburgh, Pittsburgh, PA, USA 4 Amy Johnson, MSW, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, USA 5 Rob Garofalo, MD, MPH, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, USA 2

Corresponding Author: Amy Herrick, Department of Behavioral and Community Health Sciences, Graduate School of Public Health, University of Pittsburgh, 224C Parran Hall, 130 DeSoto Street, Pittsburgh, PA 15260, USA. Email: [email protected]

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evidence is building to the contrary, indicating that YSMW are as likely or more likely to engage in risky sexual behavior and to experience elevated rates of both STIs and pregnancy compared to heterosexual young women (Gorgos & Marrazzo, 2011; Marrazzo et al., 2005; Marrazzo, Stine, & Wald, 2003; Saewyc, Bearinger, Blum, & Resnick, 1999; Singh, Fine, & Marrazzo, 2011). Although much focus has been placed on intrapsychic influences on sexual risk for STIs among adolescents and young adults (e.g., perceived risks, benefits, and barriers), these factors may have limited predictive power without consideration of the social and contextual factors that influence them (DiClemente, Salazar, Crosby, & Rosenthal, 2005). This may be particularly true for YSMW, for whom social determinants of health appear to play a primary role (Corliss, Austin, Roberts, & Molnar, 2009). The recently published Institute of Medicine (2011) report on the health of lesbian, gay, bisexual, and transgender individuals summarizes two decades of research documenting disproportionate levels of harassment, victimization, and violence experienced by YSMW in comparison to heterosexual peers, as well as evidence of elevated rates of mood and anxiety disorders and substance use (Institute of Medicine, 2011). In addition, evidence is beginning to emerge that this victimization and related comorbidities may play a role in sexual risk for STIs, as well. An analysis of follow-up data in the National Longitudinal Survey of Adolescent Health (Add Health) suggests that victimization partially mediates the relationship between sexual orientation and STI risk among young adult women (Everett, 2013). Furthermore, mental health disorders may mediate the risk between sexual victimization in childhood and STI risk among adult sexual minority women (Sweet, Polansky, & Welles, 2013). Although family members may also play a role in victimization of YSMW (Friedman et al., 2011), the role of parental support in reducing sexual risk behavior among adolescents more generally is well supported (Perrino, Gonzalez-Soldevilla, Pantin, & Szapocznik, 2000). A recent study by Corliss et al. (2009) suggests that family support partially mediates the relationship between sexual orientation (i.e., “mostly heterosexual” vs. “heterosexual”) and sexual risk behavior. Finally, the context of sexual relationships, including having an older partner (Staras, Cook, & Clark, 2009), sex while intoxicated (Arata, Stafford, & Tims, 2003; J. W. Miller, Naimi, Brewer, & Jones, 2007), and sex with high-risk partners (Staras et al., 2009), is an important factor in predicting sexual risk in young women more generally, and thus may play a role among YSMW also, particularly given the vulnerability that may result from social marginalization. The purpose of this study is to examine the sexual risk behaviors and sexual health outcomes in an ethnically

diverse sample of YSMW and to conduct an exploration of psychosocial and contextual factors associated with risk behaviors within group that may be amenable to health promotion interventions. In this study we addressed two research questions: Research Question 1: What are the relationships between demographic characteristics, sexual risk behaviors, and negative sexual health outcomes in YSMW? Research Question 2: What is the relationship between psychosocial and contextual factors (i.e., victimization, emotional distress, substance use, familial context, context of sexual relationships) and sexual risk behaviors? Study findings may have important implications for the development of sexual health education programs and health promotion messaging aimed at improving the sexual health of sexual minority adolescent females.

Method Recruitment and Data Collection Data are from a larger study of urban lesbian, gay, bisexual, and transgender youth (N = 496; see Garofalo, Mustanski, & Donenberg, 2008; Garofalo, Mustanski, McKirnan, Herrick, & Donenberg, 2007; Mustanski, Garofalo, Herrick, & Donenberg, 2007) conducted in 2004-2005. Study participants were recruited by the study coordinator from a variety of community-based venues using flyers posted in retail locations, flyers posted in agencies serving gay youth, e-mail advertisements posted on high school and college listserves, and palm cards distributed in gay-identified neighborhoods and through referral from enrolled participants. Recruitment did not take place in traditionally high-risk venues such as bars, clubs, or bathhouses. Before enrolling any participant, trained staff assessed the participant’s decisional capacity to consent and reviewed study procedures and risks and benefits of participation. To maximize confidentiality, verbal rather than written consent was obtained. The informed-consent procedure highlighted that participation was voluntary and anonymous and that declining would have no effect on access to services. To increase confidentiality and comfort in answering sensitive questions, all surveys were administered using computer-assisted self-interviewing in private rooms and lasted approximately 90 minutes, on average. All study procedures, including waiver of written assent/ consent and waiver of parental permission for minors, were approved by the institutional review boards from Howard Brown Health Center and Ann & Robert H. Lurie

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Herrick et al. Children’s Hospital of Chicago (formerly known as Children’s Memorial Hospital). Participants received a $30 stipend for completion of the survey.

Measures Outcome Measures Sexual risk behavior.  The AIDS Risk Behavior Assessment (ARBA), adapted for sexual minority women, was used to assess sexual risk taking (Donenberg, Emerson, Bryant, Wilson, & Weber-Shifrin, 2001). A composite sexual risk index was constructed using five items: (a) any unprotected vaginal sex in the past 12 months (receptive vaginal sex involving a sex toy, penis, or other object; 1 = yes, 0 = no); (b) any unprotected anal sex with a male partner in the past 12 months (1 = yes, 0 = no); (c) any vaginal, anal, or oral sex while drinking or using drugs in the past 12 months (1 = yes, 0 = no) (d) vaginal, oral, and/ or anal sex with multiple partners (more than one partner) in the past 3 months (1 = yes, 0 = no); and (e) any lifetime vaginal and/or anal sex with a high-risk partner (i.e., injection drug users, commercial sex worker, or HIV positive; 1 = yes, 0 = no). Questions regarding sexual behavior specified voluntary sexual activity. Scores on the sexual risk index ranged from 0 to 5 (M = 2.09, SD = 1.38), with higher scores reflecting higher levels of risk. Negative sexual health outcomes.  History of STIs was measured by eight self-report items that assessed lifetime diagnoses of anal warts/human papillomavirus, chlamydia, genital warts/human papillomavirus, gonorrhea, hepatitis, genital herpes, syphilis, and/or HIV/AIDS (0 = none, 1 = one or more STI). History of pregnancy was measured with the following question: “Have you ever been pregnant?” (0 = no, 1 = yes). Predictor Variables Demographics.  Participants reported age, race/ethnicity, and socioeconomic status and sexual identity. Socioeconomic status was assessed by asking participants, “How would you categorize the home you grew up in?” (1 = lower class, 2 = middle class, and 3 = upper class). Sexual identity was measured by the question, “Which of the following best describes you?” Response options included “gay,” “lesbian,” “bisexual,” “heterosexual,” and “questioning/unsure.” Victimization. The adapted version of the Victimization Scale (D’Augelli, Hershberger, & Pilkington, 1998) measured victimization due to sexual minority status on a 4-point scale (1 = never, 4 = three times or more; i.e., “How many times in your life have you been threatened with physical violence because you are, or were thought to be gay, lesbian, bisexual, or transgender?”). Relationship

abuse was measured with a composite index of five items created for this study (i.e., “Have you ever been threatened by someone with whom you have had a same-sex romantic relationship?”). Sexual coercion was created by combining two items from the ARBA, which assess sexual coercion with regard to vaginal or anal sex (0 = neither, 1 = either or both). Familial context.  Family support was measured by the average score on the family subscale of the 12-item Multidimensional Scale of Perceived Social Support (Zimet, Dahlem, Zimet, & Farley, 1988; Cronbach’s α = .94). Perceived family cohesion was measured using a sum score on the 10-item family cohesion subscale of the Family Adaptability and Cohesion Evaluation Scale (Olson, 1986; Cronbach’s α = .89). Emotional distress. The anxiety and depression subscales of the 18-item Brief Symptom Inventory (Derogatis & Melisaratos, 1983) were used to measure emotional distress. The subscales provide an estimate of symptoms associated with depression (6 items; α = .90, scale sum range = 0-23, M = 7.65, SD = 6.32) and anxiety (6 items; Cronbach’s α = .88, scale sum range = 0-24, M = 6.93, SD = 5.62). Substance use. An indicator of drug use was created using 12 items from the ARBA (Donenberg et al., 2001) reflecting self-reported drug use in the past year (e.g., marijuana, cocaine, heroin; 1 = yes, 0 = no). Responses for each item were summed to create the index (range = 0-12, M = .81, SD = 2.04). An index of alcohol abuse was created using 5 items reflecting abuse in the past 12 months (e.g., “How often did you have five or more drinks of alcohol in one day?” and “How many mornings have you felt, ‘hungover’ from drinking alcohol the night before?”). Responses were dichotomized (0 = never, 1 = at least once) and summed (range = 0-5, M = 1.30, SD = 1.54). Contextual Sexual context.  To measure contexts that may be associated with greater sexual risk behavior, we selected three items from the ARBA: whether or not (1 = yes, 0 = no) participants (a) ever had sex (oral, anal, or vaginal) with someone they met on the Internet, (b) ever had sex (oral, anal, or vaginal) in exchange for money or drugs, (c) ever had vaginal sex with an older partner (defined as >5 years older than the participant).

Data Analysis  To assess the impact of sexual risk behavior on health outcomes of interest (STI diagnoses and pregnancy), we calculated adjusted odds ratios (ORs) for each outcome

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for increasing levels of sexual risk (controlling for sociodemographics). Next, we examined the relationship of psychosocial (victimization, familial context, emotional distress, substance use) and sexual context factors (sex with an older partner, sex for money, sex with someone met on the Internet) with sexual risk behavior in simple linear regression analysis, followed by hierarchical multiple regression of sexual risk on factors found to be significant in the initial bivariate analysis. Following Cohen and Cohen (1983), we entered status variables in the hierarchical model first (1: age, sexual identity), followed by a sequence of variables ordered to reflect presumed causal priority (2: victimization, 3: psychological distress, 4: substance use, and 5: sexual context). Age was entered as a continuous variable. A dummy variable was created for race (1 = African American, 0 = non–African American), given the higher rate of both STIs and pregnancy among African American young women (CDC, 2011, 2012). Because of the small number of participants indicating “gay” and “questioning/unsure” status (n = 4 and n = 5, respectively), and the similarity in the distribution of participants in these categories to “lesbian” and “bisexual,” respectively, with regard to outcomes of interest (STI, pregnancy, and sexual risk), we collapsed participants into “gay/lesbian” and “bisexual/questioning” categories (0 = gay/lesbian, 1 = bisexual/questioning/unsure).

Table 1.  Sociodemographic Characteristics, Sexual Risk Behaviors, and Sexual Health Outcomes of Sample (N = 131).

Results Table 1 shows the demographic characteristics, sexual risk behaviors, and sexual health outcomes of the sample. The mean age of the sample was 19.8 years (SD = 2.35, range = 16-24). The sample was ethnically diverse, with 57% of participants reporting a “non-White” racial/ethnic identity. The vast majority (94%) of our sample reported being sexually active, with 29% of participants reporting having been14 years old or younger at sexual debut. Eight out of 10 participants reported engaging in at least one risk behavior, with a group average of two risk behaviors. The most frequently reported sexual risk behaviors included sex under the influence of drugs/alcohol, a history of multiple sexual partners, and unprotected vaginal sex. Twenty percent of the sample reported a history of pregnancy, 12% reported a history of an STI diagnosis, and 3% of the sample reported being HIV positive. Approximately one third of YSMW reported a history of forced sex. Analysis of the relationship between sexual risk and STI and pregnancy outcomes indicated that the odds ratio of each outcome increased significantly with increasing levels of sexual risk, controlling for demographic factors (see Table 2). The odds of prior

Characteristics Age (M = 19.8, range = 16-24), years  16-18  19-21  22-24 Race/ethnicity   African American  Latina  White  Other Socioeconomic status   Lower class   Middle class   Upper class Sexual orientation  Gay/lesbian  Bisexual  Questioning/unsure Sexual risk behaviors   Unprotected vaginal sex (past 12 months)   Unprotected anal sex with male (past 12 months)   Sex under the influence (past 12 months)   Multiple partners (past 3 months)   High-risk partners (lifetime) Sexual health outcomes   History of pregnancy   History of sexually transmitted infection

N

%

41 56 34

31 43 26

24 33 55 19

18 25 42 14

17 92 22

13 70 17

66 60 5

50 46 4

64

49

17

13

84

64

83 23

63 18

26 16

20 12

diagnoses of any STI increased by a factor of 1.79 and the odds of prior/current pregnancy increased by a factor of 2.13 for each additional increment in sexual risk behavior. In addition, increasing age was associated with both STI diagnoses (OR = 1.48) and prior/current pregnancy (OR = 1.31); being African American (vs. non– African American) also increased STI risk (OR = 13.28) but not risk of pregnancy. Self-reported SES was not significantly related to either outcome. Simple linear regression analyses were conducted to examine relationships between sexual risk behaviors and demographic, psychosocial, and sexual context factors. As shown in Table 3, older age and bisexual/unsure sexual identity were positively and significantly associated with higher rates of sexual risk behavior. Several psychosocial factors were also positively and significant associated with sexual risk behaviors, including a history of sexual coercion and symptoms of depression, anxiety, alcohol use, and drug use. All of the sexual context variables were positively associated with sexual risk.

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Table 2.  Adjusted Associations Between Negative Sexual Health Outcomes and Demographics and Sexual Risk Behaviors (N = 129). STI Characteristic

Pregnancy

Adjusted ORa

95% CI

Adjusted ORa

1.48*

[1.09, 2.00]

1.31*

[1.03, 1.66]

13.28**

[2.88, 61.32]

2.92

[0.80, 10.60]

1.29

[0.45, 3.74]

1.01

[0.43, 2.37]

2.44 1.79*

[0.66, 9.06] [1.04, 3.08]

2.09 2.13**

[0.73, 5.99] [1.35, 3.35]

Age Race/ethnicity   African American Socioeconomic status  Self-reported Sexual orientation  Bisexual/unsure Sexual risk index

95% CI

Note. STI = sexually transmitted infection; OR = odds ratio; CI = confidence interval. a. Adjusted models include all covariates (i.e., age, race/ethnicity, socioeconomic status, sexual orientation, and sexual risk index). *p ≤ .05. **p ≤ .01.

Table 3.  Simple Linear Regression of Sexual Risk Behavior on Sociodemographic and Psychosocial Factors (N = 131). Variable

B (SE)

Sociodemographic characteristics  Age   Race/ethnicity (African American)   Socioeconomic status   Sexual orientation (bisexual/unsure) Victimization   Sexual minority victimization   Sexual coercion   Relationship violence Familial context   Family cohesion   Family social support Psychological distress  Depression  Anxiety Substance use   Alcohol abuse   Drug use Sexual context   Older sex partners   Sex in exchange for money or drugs   Internet sex partners

0.18 (0.05)** −0.27 (0.31) 0.32 (0.22) 0.53 (0.24)* 0.34 (0.21) 1.04 (0.25)** 0.19 (0.11) −0.02 (0.01) −0.04 (0.07) 0.06 (0.02)** 0.07 (0.02)** 0.31 (0.08)** 0.25 (0.06)** 1.11 (0.26)** 1.42 (0.44)** 0.63 (0.30)*

Hierarchical linear regression was used to examine the relative contribution of demographic, psychosocial, and contextual factors to variation in sexual risk behaviors (see Table 4). We entered demographic variables in the hierarchical model first (1: age, sexual identity), followed by a sequence of variables ordered to reflect presumed causal priority (psychosocial factors, including 2: victimization (sexual coercion), 3: psychological distress, 4: substance use, and finally 5: sexual context variables). In Step 1, demographic variables accounted for 13% (12%

adjusted R2) of the variance in sexual risk behaviors. Older age and bisexual/unsure sexual identity were positively associated with sexual risk. In Step 2, victimization in the form of sexual coercion was added. This model accounted for an additional 7% of variance in sexual risk (p < .01) over and above that which was explained by the demographic variables. Psychological distress factors, including measures of depression and anxiety, were added in Step 3. Together, these variables accounted for an additional 5% of variance in sexual risk over that which was explained by demographics and victimization variables (p < .05); however, neither of the psychological factors was independently associated with sexual risk. Substance use factors, including alcohol abuse and drug use, were added in Step 4. Together, these variables accounted for an additional 5% of variance in sexual risk behaviors over that which was explained by the demographic, victimization, and psychological distress (p < .05). Alcohol use was positively and significantly associated with sexual risk. Finally, in Step 5, we added the sexual context variables. Together these variables explained a significant amount of additional variance in the model (p < .01). Having sex with older partners was significantly and positively associated with elevated sexual risk scores. Controlling for all other factors, older age, alcohol abuse, and having an older sexual partner remained significant and positive predictors of sexual risk in the final model, accounting for 37% of the variation in sexual risk behaviors among YSMW.

Discussion The overall objective of this study was to evaluate sexual risk behaviors in a sample of YSMW and to identify factors associated with elevated sexual risk profiles and negative health outcomes. In line with a growing body of literature on the sexual health of YSMW, study

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Table 4.  Hierarchical Multiple Regression of Sexual Risk Behavior on Demographic, Psychosocial, and Contextual Factors (N = 124)a. Variable 1. Demographic characteristics  Age   Sexual orientation (bisexual/ unsure) Psychosocial variables   2. Victimization   Sexual coercion   3. Psychological distress   Depression   Anxiety   4. Substance use   Alcohol abuse   Drug use Contextual factors   5. Sexual context    Older sex partners    Sex in exchange for money    Internet sex partners Model R2 (adjusted R2) Change in R2

Step 1, B (SE)

Step 2, B (SE)

Step 3, B (SE)

Step 4, B (SE)

Step 5, B (SE)

0.18 (0.05)** 0.56 (0.23)*

0.16 (0.05)** 0.53 (0.22)*

0.18 (0.05)** 0.48 (0.22)*

0.14 (0.05)** 0.38 (0.22)

0.10 (0.05)* 0.36 (0.21)

0.81 (0.24)**

0.61 (0.25)*

0.47 (0.25)

0.23 (0.26)

0.04 (0.03) 0.02 (0.03)

0.05 (0.03) 0.00 (0.03)

0.05 (0.03) −0.01 (0.03)

0.13 (0.12)

0.20 (0.18) 0.07**

0.25 (0.22) 0.054*

0.17 (0.07)* 0.08 (0.07)

0.18 (0.07)* 0.07 (0.07)

0.30 (0.25) 0.05*

0.70 (0.24)** 0.69 (0.42) 0.36 (0.27) 0.37 (0.31) 0.07**

a. Tolerance was >0.7 for all variables in all steps of the model. *p ≤ .05. **p ≤ .01.

participants reported engaging in a range of sexual risk behaviors, including high-risk sex with male partners. Reports of negative sexual and reproductive outcomes were also high. After controlling for sexual risk behaviors, older age was associated with both STI and pregnancy rates. The association between risk and increasing age in our sample of YSMW is consistent with national trends (Gavin et al., 2009). National data on adolescent sexual behaviors suggest that African American females are disproportionately affected by STIs and teen pregnancy (CDC, 2011, 2012). In our sample, African American race was associated with higher risk for STIs but not pregnancy outcomes. In the general population, sexual risk behaviors alone do not fully account for race differences in STI prevalence rates (Harawa, Greenland, Cochran, Cunningham, & Visscher, 2003; W. C. Miller et al., 2004). That is, African American adolescents are at increased risk for STIs even when their risk behaviors are normative (Hallfors, Iritani, Miller, & Bauer, 2007; Halpern et al., 2004). Similarly, African American race was not associated with sexual risk behaviors in our sample, suggesting that elevated risk for STIs among African American YSMW appears to be associated with factors beyond sexual risk behaviors. Factors thought to account for these disparities among African American adolescents include poverty, lack of access to adequate health care, poor access to culturally appropriate sexual health education, and myriad other inequalities resulting from the lower social position of racial/ethnic minorities

(Adimora & Schoenbach, 2005; American Social Health Association, 2005). In addition, this elevated risk observed independent of sexual risk behaviors can be interpreted through an intersectionality framework, which acknowledges that individuals are members of multiple groups or identities and that these identities intersect and interact to produce health disparities (Brooks, Bowleg, & Quina, 2009). The influence of stigma and discrimination on minority health disparities is well-documented (e.g., Gee, 2002; Mays, Cochran, & Barnes, 2007). Thus, experiences of stigma and discrimination based on not only racial minority status but also sexual minority status may increase health disparities for African American YSMW (Bowleg, 2012). In addition to demographic factors, several psychosocial factors have been associated with sexual risk behaviors among adolescent females, including victimization (sexual coercion), emotional distress, and substance use. Each of these factors was examined in hierarchical multivariate analyses, with the overall model accounting for 37% of the variance in sexual risk behaviors among YSMW. Controlling for other variables in the model, older age was positively and significantly associated with sexual risk behaviors. Additional risk factors for YSMW may include lack of culturally specific education materials, lack of culturally sensitive prevention and treatment services, and a perception of low personal risk (Marrazzo et al., 2005; Richardson, 2000; Scherzer, 2000).

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Herrick et al. Alcohol abuse and having older sexual partners were also associated with engagement in sexual risk behaviors in our final multivariate model. Frequent alcohol consumption is associated with unprotected sex (Cooper, 2002; Wingood & DiClemente, 1998), especially with casual partners (Kiene, Barta, Tennen, & Armeli, 2009). The extant literature reports that sexual minority youth are more likely to use alcohol and other substances compared to their heterosexual counterparts (Austin et al., 2004; Corliss et al., 2010; Easton, Jackson, Mowery, Comeau, & Sell, 2008; Garofalo, Wolf, Kessel, Palfrey, & DuRant, 1998; Marshal et al., 2008; Ziyadeh et al., 2007), potentially magnifying the risk. Sexual context variables are also critical to the understanding of sexual risk behaviors (Adimora et al., 2002; Baumgartner, Waszak Geary, Tucker, & Wedderburn, 2009; Staras et al., 2009). All three of our context variables (sex with older partners, exchange sex, Internet sex partners) were significantly associated with risky sexual behaviors in univariate analyses. After controlling for other factors, having an older sexual partner remained positively associated with higher levels of sexual risk behaviors. In other studies of sexual risk among young women, having an older partner was associated with earlier sexual debut and decreased protected sex compared to young women whose partners were equal in age (K. S. Miller, Clark & Moore, 1997; Vanoss Marín, Coyle, Gómez, Carvajal & Kirby, 2000). These results point to the need for more systematic examination of the influence of contextual factors on risk engagement and negative outcomes among YSMW. Specifically, additional research is needed to understand what community and cultural norms contribute to risk behaviors and what programs and resources are needed to lessen overall sexual risks.

Study Strengths and Limitations Study findings should be considered in light of several limitations. First, the sample was selected using nonprobability methods, and thus generalizability is limited. However, unlike most studies of YSMW, our sample was very diverse in terms of race/ethnicity and age, a factor that helps reduce some of the potential bias of convenience samples. To obtain a more generalizable risk profile of YSMW, additional research is needed using larger probability- and community-based samples of adolescents representing a range of nonheterosexual sexual identities. This is particularly true in light of recent research that suggests that YSMW that identify as “mostly heterosexual” or “bisexual” may be at higher risk for sexual behavior that may lead to negative health outcomes. Furthermore, less is known about sexual risk among YSMW who identify as “questioning.” In this analysis, in part due to small sample size, we collapsed categories of

sexual orientation that were similar in terms of their distribution on outcomes of interest to preserve larger subsamples for analysis. Therefore, our findings should be considered suggestive of patterns within YSMW that warrant further exploration. Additionally, sexual risk data were based on retrospective recall of partners and behaviors and may have been influenced by recall limitation or social desirability factors. However, sensitive information was collected using a computer-assisted self-interviewing program, which has been shown to reduce self-report bias (Kissinger et al., 1999; Morrison-Beedy, Carey, & Tu, 2006). Rates of pregnancy in our sample were high; yet we are unable to determine whether these pregnancies were intentional or unintentional. Also, our survey instrument included assessment of past STI diagnosis but not history of STI testing. Therefore, it is possible that history of STIs was underreported, as STIs in young women are often asymptomatic and go unnoticed, particularly in a population that perceives itself to be at low risk for infection. Finally, the study data was collected in a onetime, cross-sectional survey; therefore temporal ordering was not controlled for these analyses and the data should be interpreted with caution. Research using a longitudinal design is needed to provide evidence of causality.

Implications for Future Research The problems associated with unintended pregnancies among adolescents and young adults are well documented and include poor outcomes for mothers, including lower rates of high school or GED completion, greater reliance on public assistance, and increased likelihood of living in poverty than their peers who are not mothers (Hotz, McElroy, & Sanders, 1997). There are also notable concequences for the children of adolescent mothers, including higher risk of death and hospitalization, lower likelihood of high school completion, and increased risk of becoming teen parents themselves (Jutte et al., 2010). The results of this and previous research suggest that YSMW engage in sexual risk behaviors at rates as high or higher than their heterosexual peers (Blake et al., 2001; Kann et al., 2011; Morrow & Allsworth, 2000; Saewyc et al., 1999). Clinicians and health educators may assume that YSMW are at little or no risk for HIV, STIs and unintended pregnancy, when in fact, risk behaviors and barriers to care put YSMW at risk for all three (Brown & Melchiono, 2006). As such, the sexual health promotion needs of YSMW remain largely overlooked (Diamant, Lever, & Schuster, 2000) Consistent with recommendations from Healthy People 2020, additional research is needed to reduce disparities in sexual risk behaviors and adverse sexual health outcomes. This includes expanding our understanding of

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the influence of sexual orientation and identity on sexual risk behaviors. A major limitation of the extant research on YSMW is the lack of attention to subpopulation differences. For example, bisexually identified females consistently report higher levels of sexual risk behaviors and higher STI rates among adolescents and young adults (Everett, 2013; Kann et al., 2011; Koh, Gomez, Shade, & Rowley, 2005; Mercer et al., 2007). Recent studies are also suggesting that women who identify as mostly heterosexual have elevated sexual risk profiles (Corliss et al., 2009; Wilsnack et al., 2008). Although emerging research suggests potentially disparate sexual risk behaviors among bisexual adolescents, it is important to note that engagement in sexual risk behaviors with male partners was also common among YSMW who identified as lesbians. Clinicians and health educators should be aware of differences in risk profiles within YSMW based on selfidentification; however, a careful assessment of sexual risk behaviors—with both male and female partners— should be conducted with all sexual minority adolescents, regardless of reported sexual orientation (Brown & Melchiono, 2006). Furthermore, improved access to developmentally and culturally appropriate sexuality education is needed. YSMW need information and programs that specifically address their complex needs and encourage protective behaviors (Bailey & Phariss, 1996). Specifically, positioning sexual health within the larger framework of physical and mental health for this population may serve as a means for enhancing sexual risk reduction and promoting overall sexual health. Finally, although a significant proportion of YSMW engage in sexual risk behaviors, a larger proportion do not. As such, additional research is needed to identify protective factors so that we may learn what factors promote safe and healthy development for these young women.

Funding

Acknowledgments The authors would like to acknowledge the entire Youth Services staff of Howard Brown Health Center and the Broadway Youth Center, with special thanks to Gilberto Soberanis. We would also like to thank the queer youth community of Chicago for its assistance with this project.

Author Roles Drs. Herrick and Garofalo were responsible for data collection. Dr. Kuhns was responsible for data analysis. All authors contributed to the conceptualization and writing of the manuscript.

Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work has been supported by the National Institute of Mental Health (Grant R03MH070812; PI: R. Garofalo) and the Lesbian Health Fund (PI: A. Herrick).

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