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. Author manuscript; available in PMC: 2021 Jul 27.
Published in final edited form as: Youth Soc. 2019 May 29;52(7):1153–1173. doi: 10.1177/0044118x19851892

Sexual Orientation–Based Alcohol, Tobacco, and Other Drug Use Disparities: The Protective Role of School-Based Health Centers

Lei Zhang 1, Laura J Finan 2, Melina Bersamin 2, Deborah A Fisher 3, Mallie J Paschall 2
PMCID: PMC8315521  NIHMSID: NIHMS1607043  PMID: 34321700

Abstract

This study investigated whether the presence of school-based health centers (SBHCs) was associated with six substance use behaviors among sexual minority youth (SMY) and their heterosexual peers. Data from the 2015 Oregon Healthy Teens Survey, including 13,608 11th graders in 137 schools (26 with SBHCs) were used in the current study. Multilevel logistic regression analyses were performed. Results revealed significant SBHC by SMY status interactions indicating a relatively lower likelihood of past 30-day alcohol use (23%), binge drinking (43%), use of e-cigarettes (22%), marijuana (44%), and unprescribed prescription drugs (28%) among SMY in SBHC schools compared with non-SMY at SBHC schools. Furthermore, SMY in SBHC schools reported lower likelihood of aforementioned substance use behaviors than SMY attending non-SBHC schools. Conversely, no differences in these outcomes were observed for non-SMY in SBHC and non-SBHC schools. Findings from this study suggest SBHCs may help to mitigate substance use disparities among marginalized populations, such as SMY.

Keywords: adolescent substance use, sexual minority youth, health disparities, school- based health centers

Adolescence presents various developmental challenges for youth during their transition to adulthood. Sexual minority youth (SMY), including lesbian, gay, and bisexual adolescents, face additional challenges due to the social stigma associated with their sexual orientation. As a result, they may engage in health risk behaviors, such as substance use, and develop undesirable health outcomes (Coker, Austin, & Schuster, 2010; Hadland, Yehia, & Makadon, 2016; Luk, Gilman, Haynie, & Simons-Morton, 2017). Previous studies have documented disparities in substance use between SMY and their heterosexual peers. Specifically, SMY are at disproportionate risk for sub- stance use (Marshal et al., 2008) and are more likely than their heterosexual peers to smoke cigarettes (Azagba, Asbridge, Langille, & Baskerville, 2014; Caputi, 2018; Corliss et al., 2014; Corliss et al., 2013; Coulter, Bersamin, Russell, & Mair, 2018; Dermody, 2018; Marshal et al., 2008; Ott et al., 2013; Watson, Goodenow, Porta, Adjei, & Saewyc, 2018), drink alcohol (Caputi, 2018; Corliss, Rosario, Wypij, Fisher, & Austin, 2008; Coulter et al., 2018; Coulter et al., 2016; Dermody, 2018; Fish & Baams, 2018; Marshal et al., 2008; Talley, Hughes, Aranda, Birkett, & Marshal, 2014; Watson et al., 2018), use marijuana (Caputi, 2018; Dermody, 2018; Heck et al., 2014; Marshal et al., 2008; Ott et al., 2013; Watson et al., 2018), and engage in prescription drug misuse (Caputi, 2018; Dermody, 2018; Heck et al., 2014; Kecojevic et al., 2012). Recent longitudinal studies showed that disparities in substance use narrowed in male SMY, yet, remained unchanged or worsened among female SMY (e.g., Caputi, 2018; Watson et al., 2018).

Concurrently, SMY need the same comprehensive health care services and value the same health care provider characteristics as do their heterosexual peers (Coker et al., 2010; Ginsburg et al., 2002; Hadland et al., 2016; Hoffman, Freeman, & Swann, 2009; Luk et al., 2017; Newman, Passidomo, Gormley, & Manley, 2014), including confidentiality, privacy, respect, competency, and nonjudgmental attitudes from health care professional. Youth also are concerned about accessibility of health care services in terms of cost, hours of access, and ease of making appointments (Ginsburg et al., 2002; Newman et al., 2014). Unfortunately, SMY often face personal and structural barriers that reduce access to much-needed health services (Institute of Medicine, Board on the Health of Select Populations, Committee on Lesbian, Gay, Bisexual, and Transgender Health Issues and Research Gaps and Opportunities, 2011) and studies suggest these youth report forgoing care and have unmet health care needs (Ramos, Sebastian, & Rosero, 2017; Williams & Chapman, 2011).

School-based health centers (SBHCs) may be one health service access point to address SMY’s health concerns and needs by offering them accessible, affordable, and confidential services. SBHCs are health clinics located in schools or on school grounds that are staffed by doctors, nurses, or other medical professionals. These centers are designed to work within the school to provide comprehensive, low-cost, convenient, and youth-friendly health care services for school children and adolescents (Allison et al., 2007). Located in both urban and rural areas, SBHCs deliver preventive and treatment services including immunizations and physical check-ups. Many also provide substance use, reproductive care, and mental health services. Importantly, they often serve disadvantaged students who have limited access to health care (Keeton, Soleimanpour, & Brindis, 2012). In Oregon, for example, SBHCs serve children and youth, even if they do not have insurance or cannot pay for services. Any school, district, or community can decide to open an SBHC, and many SBHCs in Oregon receive state funding or receive sponsorship from other community medical providers (Oregon Health Authority, n.d.). As such, the reach of these centers is widespread and serves a diverse range of youth in the state. Importantly, studies suggest SBHCs are beneficial for adolescents’ mental health and have had substantial effects on other youth health outcomes, including increased use of primary care services and reductions in emergency room visits and hospitalizations (Bains & Diallo, 2016; Santelli, Kouzis, & Newcomer, 1996; Soleimanpour, Geierstanger, Kaller, McCarter, & Brindis, 2010).

SBHCs can positively impact young people’s health behavior through direct and indirect pathways. In terms of direct pathways, SBHCs location in schools offers opportunities for health care professionals to (a) reduce health service access barriers, (b) facilitate conversations between health care providers and young people in accessible settings, and (c) shape young people’s conversations and knowledge about health and health behaviors. In addition, youth may be indirectly exposed to health care messages through SBHC activities (e.g., marketing messages) or through friends’ engagement with SBHCs. Consistent with social cognitive theory perspectives (Bandura, 1998), SBHCs may change the norms surrounding health behaviors and may, therefore, shape young people’s knowledge and attitudes, which, in turn, positively influence their self-efficacy toward seeking care or maintaining their health. For example, SBHCs may positively impact school norms and young people’s knowledge, attitudes, and beliefs surrounding health risk behaviors, including substance use.

SBHC access may be particularly impactful for marginalized populations, including SMY. In line with social cognitive and ecological theories, through altering individual and contextual factors these centers may reduce access barriers found in traditional health care settings, creating positive changes in youths’ help-seeking and health care behavior (Bandura, 1998; Sallis & Owen, 2015). Indeed, studies suggest that SMY report financial and privacy barriers to care (Snyder, Burack, & Petrova, 2017; Williams & Chapman, 2011). Furthermore, some research suggests SMY prefer to access health ser- vices in school settings (Wells et al., 2013) and that SMY use more health services than their heterosexual peers (Filice & Meyer, 2018; McGuire & Russell, 2007; Williams & Chapman, 2015). Studies of SBHC also have shown that SMY make up considerable portions of SBHC users (Ramos et al., 2017). By informing SMY knowledge, perspectives on normative health behaviors, and reducing barriers to care, SBHC may be important health service access points for this population.

Few studies have examined whether SBHC access may be related to alcohol, tobacco, and other drug use among students, particularly SMY. One study indicated that among inner-city African American high school students in the Midwest, use rates for cigarettes and marijuana were lower among ninth and 11th graders and among 11th graders only, respectively, in SBHC schools compared with non-SBHC schools (Robinson, Harper, & Schoeny, 2003). Similarly, among a largely African American sample, students with access to an SBHC were more likely to have utilized behavioral health ser- vices and less likely to have drunk alcohol and smoked marijuana compared with students without SBHC access (Broussard, Brown, Hutchinson, & Kohler Chrestman, 2012). A recent study demonstrated that SBHC access was (a) negatively associated with alcohol use, binge drinking, cigarette, and e-cigarette use among African American students and (b) negatively associated with cigarette and marijuana use among Asian/Pacific Islanders (Bersamin, Paschall, & Fisher, 2017). Although one study found that SBHC access was associated with lower mental health disparities among SMY (Zhang, Finan, Bersamin, & Fisher, 2018), extant research has yet to examine whether SBHCs access is associated with substance use among SMY.

Therefore, the current study sought to examine possible associations between access to SBHCs and substance use behaviors of SMY, including past 30-day alcohol use, binge drinking, cigarette use, e-cigarette use, marijuana use, and unprescribed prescription drug use. Considering the observed disparity in substance use rates between SMY and non-SMY, and that SMY tend to use more health services relative to their heterosexual peers, we expected that SMY would report more substance use than their non-SMY peers. However, we also hypothesized SBHCs would have a protective effect such that SMY in SBHC schools would report lower substance use rates than SMY in non-SBHC schools.

Method

Study Sample and School Characteristics

The Oregon Healthy Teens (OHT) Survey monitors the health and well-being of adolescents. This anonymous and voluntary survey is administered to a sample of eighth and 11th grades statewide during the spring semester every 2 years and is designed to be completed during a class period. Parents give passive consent or active objection to their child’s participation in the OHT. The survey includes questions on substance use, perceptions of personal safety, diet and exercise, sexual behavior, and mental health. The OHT sampling frame is designed to be representative of eighth- and 11th-grade students in public schools across all counties in the state. Post hoc sample weights are developed for each county and the state based on the actual number of students in Grades 8 and 11 in each school, county, and the entire state (Oregon Health Authority, 2015a).

The current study was based on 137 public high schools that participated in the OHT Survey in 2015 with a total of 13,608 students. Among 137 schools, a total of 26 schools had SBHCs at this time. The population of Oregon is predominantly White (87%) and non-Hispanic (75%), with 13% of the population living at or below poverty level (U.S. Census, n.d.). This study was approved by the Institutional Review Board of the Pacific Institute for Research and Evaluation.

Measures

Sexual orientation.

There is no standard method of assessing sexual orientation among adolescents. Researchers tend to measure different dimensions of orientation (Marshal et al., 2008; Matthews, Blosnich, Farmer, & Adams, 2014), and adolescents’ ongoing process of sexual development suggests that sexual orientation identity may be dynamic (Marshal et al., 2008). Hence, defining SMY is challenging. The definition of sexual orientation may vary depending on the research focus (Mustanski, Van Wagenen, Birkett, Eyster, & Corliss, 2014), and health indicators may differ depending on how sexual orientation has been operationalized (Matthews et al., 2014). The current study followed operationalizations used in other large national epidemiological studies (e.g., Coulter et al., 2018) and created a binary variable for SMY indicating those who endorsed a minority sexual orientation. Students were asked, “Do you think of yourself as. (a) lesbian or gay, (b) straight (that is, not lesbian or gay), (c) bisexual, (d) something else, or (e) don’t know/not sure.” Given that the number of students represented within the specific sexual minority response option categories of “lesbian/gay,” “bisexual,” and “something else” were small (i.e., respectively 1.5%, 5.1%, and 2.0%, unweighted), we created a dichotomous status indicator with 1 = SMY (Categories a, c, and d) and 0 = heterosexual youth or non-SMY (Category b). Adolescents endorsing the “don’t know/not sure” response option (2.5%, unweighted) were removed from analyses because we could not discern whether this selection corresponded with their gender or sexual identity and the sample size of this group was too small to examine separately.

Past 30-day substance use behaviors.

Adolescents reported their recent alcohol use, binge drinking, cigarette use, e-cigarette use, marijuana use, and unprescribed prescription drug use. Specifically, participants were asked, “During the past 30 days, on how many days did you have… (a) at least one drink of alcohol? (b) 5 or more drinks of alcohol in a row, that is within a couple of hours? (c) smoke cigarettes? (d) use an e-cigarette or other vaping product? (e) use marijuana or hashish (weed, hash, pot)? and (f) use prescription drugs (such as Oxycontin, Percocet, Vicodin, Codeine, Adderall, Ritalin, or Xanax) without a doctor’s orders?” Dichotomous indicators (0 = no; 1 = yes) were created for each substance to examine any use of these substances in the past 30 days.

Student demographic characteristics.

Students reported their grade, age, gen- der, and whether they were receiving free or reduced-price lunch at school. Also, students were asked if they were Hispanic or Latino and to select their race with options including (a) American Indian or Alaska Native, (b) Asian, (c) Black or African American, (d) Native Hawaiian or Other Pacific Islander, and (e) White. Hispanic ethnicity (0 = non-Hispanic; 1 = Hispanic) was treated as a dichotomous variable. Given that multiple selections in the race question were allowed and selections could overlap, all non-White race groups appeared small, that is, American Indian or Alaska Native (7.2%, n = 853), Asian (7.0%, n = 829), Black or African American (4.1%, n = 492), and Hawaiian or Other Pacific Islander (3.0%, n = 361; percent- ages and ns unweighted). As such, the self-identified race option White was used as a race indicator (0 = non-White; 1 = White).

School characteristics.

School characteristics included school type (0 = serve both middle and high school students or 1 = serve only high school students), total student enrollment, percent eligible for free or reduced-price lunch, SBHC presence in the school (0 = no; 1 = yes), These characteristics were provided in the OHT 2015 survey data.

Analysis Strategy

Descriptive analyses were first conducted to examine sample characteristics and compare schools with and without SBHCs. Next, multilevel random effects logistic regression models were performed predicting each of the sub- stance use outcomes. Student characteristics were included at Level 1 and school characteristics at Level 2. Main effects were tested first, and then cross- level interactions between SMY status and SBHC status were examined. Where significant cross-level interactions were observed, additional subgroup analyses (i.e., predicted probability analyses) were performed to examine the nature of the interactions. Exploratory multilevel random effects logistic regression models also were conducted to examine (a) whether cross-level interactions between SBHC and SMY status would differ between males and females; and (b) whether there were any significant cross-level interactions between SBHC and SMY subgroups status within SMY, while holding all school and individual-level variables constant. Missing data on SMY was about 3.6%, and missing data on past 30-day substance outcomes ranged from 5.8% to 10.2%. All missing cases were listwise deleted by the statistical pro- gram. All analyses were performed with SAS Version 9.4 software (SAS, 2002-2016) and the PROC GLIMMIX procedure to adjust for variance attributable to student observations nested within schools (Raudenbush & Bryk, 2002). Sample weights provided with the OHT survey data were applied in descriptive and regression analyses.

Results

Sample Characteristics

School and student characteristics for the sample overall are provided in Table 1, along with comparisons between schools with and without SBHCs. At the school level, SBHC schools had significantly higher enrollments than non-SBHC schools. No differences, however, emerged with respect to school socioeconomic status, as measured by overall percentage of students eligible for free or reduced-price lunch, or the school grades served. At the student level, non-SBHC schools had significantly higher percentages of Hispanic students, White students, and students receiving free or reduced-price lunch. Both SBHC and non-SBHC schools had similar percentages of female and SMY students. Students’ ages in both SBHC and non-SBHC schools appeared to be very similar. Apart from student enrollment, differences between SBHC and non-SBHC schools in school and student-level variables were very small (Cohen, 1988).

Table 1.

Differences in School and Student Characteristics by SBHC presence in School.

Variables Total
sample		 SBHC
schools		 Non-SBHC
schools		 Effect size
(Cohen’s d)
School level N = 137 n = 26 n = 111
Middle/high school, n (%) 35 (25.6) 5 (19.2) 30 (27.0) 0.08
High school, n (%) 102 (74.4) 21 (80.8) 81 (73.0) −0.08
Student enrollment, M (SD) 697 (634) 1030 (767) 619 (575)** 0.67
Mean proportion of free/reduced price lunch, M (SD) 52.0 (18.1) 51.5 (15.4) 52.2 (18.8) 0.05
Student level N = 13,608 n = 4,067 n = 9,541
Age, M (SD) 16.6 (0.9) 16.6 (0.9) 16.6 (0.9)* 0.02
Female, n (%) 6804 (50.2) 2042 (50.1) 4762 (50.2) 0.0003
Hispanic, n (%) 3135 (23.6) 876 (19.4) 2259 (25.4)** 0.08
White, n (%) 10509 (89.3) 3058 (86.9) 7451 (90.4)** 0.06
Received free/reduced price lunch, n (%) 4729 (39.7) 1411 (35.8) 3318 (41.3)*** 0.06
SMY, n (%) 1166 (8.7) 358 (8.5) 808 (8.7) 0.01
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Note. High schools served as the reference groups for middle/high schools and vice versa. Male students, non-Hispanic students, non-White students, students who did not receive free or reduced-price lunch, and non-SMY served as the reference groups for the female, Hispanic, White, received free or reduced-price lunch, and SMY variables, respectively. School-level sample sizes were unweighted, while percentages of student-level study variables were obtained with sample weights. The value of the average student age in SBHC and non-SBHC schools appears the same due to rounding. SBHC = school-based health center; SMY = sexual minority youth.

*

p < .05.

**

p < .01.

***

p < .001.

Differences in sexual orientation response option endorsements based on SBHC status and gender are provided in Table 2. Both SBHC and non-SBHC schools had similar percentages of students in SMY subgroups except in the “bisexual” category. Female students were more likely to endorse the “bisex- ual,” “something else,” or “don’t know/not sure” sexual orientation responses; whereas male students were more likely to endorse a “straight” or “gay” sexual orientation options. Again, effect sizes showed that the sizes of the significant differences between males and females or the difference between SBHC schools and non-SBHC schools were very small (Cohen, 1988).

Table 2.

Differences in Sexual Orientation Response Option Endorsements based on SBHC status and gender.

Sexual orientation responses Total sample N
= 13,448		 SBHC schools
n = 4,022		 Non-SBHC schools
n = 9,426		 Effect size
(Cohen’s d)
“Straight”, n (%) 11947 (88.7) 3556 (88.8) 8391 (88.7) −0.004
“Lesbian or gay”, n (%) 199 (1.4) 58 (1.4) 141 (1.4) −0.0001
“Bisexual”, n (%) 700 (5.3) 219 (4.9) 481 (5.4)* 0.01
“Something else”, n (%) 267 (1.8) 81 (2.0) 186 (1.7) −0.01
“Don’t know/not sure”, n (%) 335 (2.9) 108 (3.0) 227 (2.8) −0.01
Sexual orientation responses Total sample N
= 13,448		 Male
n = 6,723		 Female
n = 6,725		 Effect size
(Cohen’s d)
“Straight”, n (%) 11947 (88.7) 6213 (92.0) 5734 (85.5)*** 0.11
“Lesbian or gay”, n (%) 199 (1.4) 101 (1.5) 98 (1.2)** 0.02
“Bisexual”, n (%) 700 (5.3) 175 (2.7) 525 (7.7)*** −0.13
“Something else”, n (%) 267 (1.8) 97 (1.5) 170 (2.2)*** −0.03
“Don’t know/not sure”, n (%) 335 (2.9) 137 (2.3) 198 (3.4)*** −0.04
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Note. Sample sizes were unweighted, while percentages were obtained with sample weights. SBHC = school-based health center.

*

p < .05

**

p < .01

***

p < .001

The total sample prevalence rates for past 30-day alcohol use, binge drinking, cigarette use, e-cigarette use, marijuana use, and unprescribed prescription drug use were 29.1%, 16.5%, 8.3%, 17.2%, 19.2%, and 6.5%, respectively. Bivariate analyses showed that SMY reported significantly higher prevalence rates than non-SMY on all substance use indicators: past 30-day alcohol use (37.3% vs. 28.4%), binge drinking (19.1% vs. 16.4%), cigarette use (21.1% vs.7.0%), e-cigarette use (26.2% vs. 16.3%), marijuana use (32.1% vs. 17.9%), and unprescribed prescription drug use (12.9% vs. 5.8%).

Regression Analyses

Results of multilevel logistic regression analyses with student- and school- level covariates and cross-level interaction terms are provided in Table 3. At the school level, the only significant finding was that students in high school were more likely to report cigarette use; no other school-level factors were associated with any substance use outcomes. At the student level, students who were eligible for free or reduced-price lunch were more likely to engage in all substance use behaviors. Similarly, SMY were more likely than non- SMY to use all substances. Older students were more likely to engage in binge drinking, smoke cigarettes, and use unprescribed prescription drugs, yet, were less likely to use marijuana. Both Hispanic and White students were more likely to report alcohol use, binge drinking, and marijuana use. Furthermore, Hispanic students were more likely to use unprescribed pre- scription drugs, whereas White students were more likely to use smoke cigarettes and use e-cigarettes. Finally, females were less likely than males to binge drink, smoke cigarettes, smoke e-cigarettes, and use marijuana.

Table 3.

Effects of SBHC services on the likelihood of past-30-day substance use behaviors in 2015, odds ratio (95% confidence interval)

Variable Alcohol use Binge drinking Cigarette smoking E-cigarette use Marijuana use Un-prescribed
prescription drug use
OR (95% confidence interval)
School level
High school 0.98 (0.78, 1.23) 0.82 (0.62, 1.08) 1.45 (1.00, 2.10)* 1.18 (0.87, 1.60) 0.88 (0.62, 1.24) 1.36 (0.92, 2.00)
Student enrollment 0.99 (0.97, 1.00) 0.99 (0.97, 1.00) 0.96 (0.94, 0.98) 0.99 (0.97, 1.01) 1.02 (0.99, 1.04) 0.99 (0.97, 1.01)
Percent eligible for free/reduced price lunch 0.75 (0.46, 1.24) 0.84 (0.46, 1.55) 1.51 (0.69, 3.34) 1.06 (0.55, 2.05) 1.17 (0.56, 2.46) 0.72 (0.33, 1.60)
SBHC 1.05 (0.86, 1.28) 0.98 (0.77, 1.25) 0.92 (0.67, 1.26) 1.00 (0.77, 1.30) 1.06 (0.81, 1.51) 0.86 (0.62, 1.18)
Student level
Age 1.02 (0.97, 1.07) 1.06 (1.00, 1.13)* 1.20 (1.11, 1.31)*** 1.03 (0.97, 1.09) 0.93 (0.88, 0.99)* 1.11 (1.01, 1.22)*
Female 1.02 (0.97, 1.07) 0.88 (0.83, 0.94)*** 0.82 (0.75, 0.89)*** 0.64 (0.60, 0.69)*** 0.94 (0.88, 1.00)* 1.09 (0.99, 1.20)
Hispanic 1.11 (1.03, 1.20)** 1.15 (1.05, 1.27)** 0.99 (0.87, 1.13) 1.03 (0.94, 1.14) 1.19 (1.09, 1.31)*** 1.11 (0.96, 1.28)*
White 1.44 (1.31, 1.58)*** 1.34 (1.19, 1.50)*** 1.53 (1.30, 1.81)*** 1.30 (1.67, 1.46)*** 1.19 (1.07, 1.32)*** 1.15 (0.97, 1.36)
Receive free/reduced price lunch 1.18 (1.11, 1.25)*** 1.12 (1.05, 1.21)** 1.54 (1.40, 1.69)*** 1.36 (1.27, 1.45)*** 1.59 (1.48, 1.70)*** 1.10 (0.99, 1.23)*
SMY 1.44 (1.30, 1.59)*** 1.22 (1.07, 1.38)** 3.60 (3.17, 4.09)*** 1.99 (1.78, 2.23)*** 2.56 (2.30, 2.85)*** 2.50 (2.16, 2.89)***
Cross-level
SBHC × SMY 0.77 (0.63, 0.93)** 0.57 (0.44, 0.74)*** 0.88 (0.69, 1.13) 0.78 (0.63, 0.96)* 0.56 (0.46, 0.69)*** 0.72 (0.53, 0.98)*
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Note. At the school level, middle/high schools served as the reference group for the high school variable. At the student level, male students, non-Hispanic students, non-White students, students who did not receive free or reduced-price lunch, and non-SMY served as the reference groups for the following variables, respectively: female, Hispanic, white, received free or reduced-price lunch, and SMY variables. Sampling weights were applied to these analyses. OR = odds ratio; SBHC = school-based health center; SMY = sexual minority youth.

*

p < .05

**

p < .01

***

p < .001

Significant cross-level interactions between SBHC and SMY status were observed for all substance use behaviors except cigarette use. For past 30-day alcohol use and binge drinking, an inverse association between having an SBHC and these behaviors among SMY relative to non-SMY was observed. Odds ratios for the interaction terms showed a 23% relative reduction in the likelihood of past 30-day alcohol use and a 43% relative reduction in the likelihood of binge drinking. Results similarly indicated a significant negative association between SBHC presence and past 30-day e-cigarette, marijuana, and unprescribed prescription drug use among SMY compared with non-SMY peers, showing a 22% relative reduction in the likelihood of any e-cigarette use, a 44% relative reduction in the likelihood of marijuana use, and 28% relative reduction in the likelihood of unprescribed prescription drug use.

To further explore the nature of these interactions, plots of predicted prob- abilities for the SBHC status by SMY status are shown in Figure 1. Compared to SMY at schools without SBHCs, SMY at schools with SBHCs were less likely to use alcohol (31.0% vs. 36.0%), less likely to engage in binge drinking (12.0% vs. 19.0%), and less likely to smoke e-cigarettes (22% vs. 26.0%) in the past 30 days. Similar patterns were observed for past 30-day marijuana use (24% vs. 33%) and unprescribed prescription drug use (9% vs. 14%) among SMY students at schools with SBHCs, compared with SMY at non- SBHC schools. There were no significant differences by SBHC school status for non-SMY students across the substance use outcomes.

Figure 1.

Figure 1.

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Proportion of students reporting past 30-day alcohol use (A), binge drinking (B), e-cigarette use (C), marijuana use (D), and unprescribed prescription drug use (E) among SMY (solid line) and non-SMY (dashed line) at schools with and without SBHCs in 2015. Proportions rates are adjusted for student and school demographic characteristics. SBHC = school-based health center; SMY = sexual minority youth.

Next, we ran supplemental, exploratory analyses to examine whether cross-level interactions between SBHC and SMY status would differ between males and females. The same set of models was run separately for males and females. For males, the cross-level interactions between SBHC and SMY status were similar to the pattern we observed in the whole sample. Specifically, significant interactions were observed for all ATOD (alcohol, tobacco, and other drug) outcomes except for cigarette use and unprescribed prescription drug use (past 30-day alcohol use, OR = 0.47, p < .0001; binge drinking, OR = 0.25, p < .0001; e-cigarette use OR = 0.47, p < .001; and marijuana use, OR = 0.34, p < .0001). Conversely, for females, the only significant cross-level interaction was on past 30-day marijuana use (OR = 0.69, p < .01). Predicted probabilities analyses of these significant interactions also exhibited a comparable pattern that we observed in the whole sample: SMY at schools with SBHCs were less likely to report substance use behaviors than SMY at schools without SBHCs. No differences were observed for non-SMY at schools with SBHCs versus those at schools without SBHCs.

We also conducted exploratory analyses to investigate whether significant cross-level interactions between SBHC and SMY status were observed among subgroups within SMY. We created indicators of “lesbian/gay,” “bisexual,” and “something else” sexual orientation response option sub- groups and ran the same set of models among SMY students only. We ran two sets of models. First, we used “lesbian/gay” responses as reference group and tested the interactions between SBHC and “bisexual” response and the inter- action between SBHC and “something else” response simultaneously to obtain comparisons among “lesbian/gay,” “bisexual,” and “something else” response options (i.e., “lesbian/gay” vs. “bisexual,” “lesbian/gay” vs. “some- thing else”). Compared to the reference group “lesbian/gay” response, the interaction SBHC by “bisexual” response was only significant on past 30-day marijuana use (OR = 0.49, p < .05), whereas the interaction SBHC by “something else” response was significant on past 30-day alcohol use (OR =1.91, p < .05) and e-cigarette use (OR = 3.66, p < .001).

Second, we used “bisexual” response as reference group and tested the interactions between SBHC and “lesbian/gay” response and the interaction between SBHC and “something else” response to obtain the comparison “bisexual” versus “something else” responses. Compared to the reference group “bisexual” response, the interactions between SBHC and “something else” response were significant on past 30-day cigarette use (OR = 2.66, p <.001), e-cigarette use (OR = 3.56, p < .0001), and marijuana use (OR = 1.72, p < .05). Predicted probabilities analyses of these significant interactions indicated that those who reported the “something else” response and attended SBHC schools tended to report more past 30-day cigarette use, e-cigarette use, and marijuana use than their counterparts in non-SBHC schools; whereas the “lesbian/gay” or “bisexual” groups at schools with SBHCs were less likely to report these substance use behaviors than the “lesbian/gay” or “bisexual” groups at schools without SBHCs. We noted that among SMY, the “something else” response group reported overall lower rates of these substance use behaviors than the groups endorsing “lesbian/ gay” or “bisexual” options (results available upon request).

Discussion

SBHCs are accessible and convenient health care service access points. A growing body of research has demonstrated the utility of these centers as effective health promotion investments, which have the potential to enhance adolescent health and well-being. For example, SBHCs have been linked with increased use of primary care services and reductions in emergency room visits and hospitalizations (Allison et al., 2007; Santelli et al., 1996; Soleimanpour et al., 2010). The current study adds to this literature both by drawing associations between SBHC access and adolescents’ substance use behavior, and by examining SMY, a marginalized youth population that has not been studied extensively.

In line with past research (Azagba et al., 2014; Corliss et al., 2014, 2008, 2013; Heck et al., 2014; Kecojevic et al., 2012; Marshal et al., 2008; Ott et al., 2013; Talley et al., 2014), we found that SMY reported greater alcohol, tobacco, and other drug use than their heterosexual peers. Importantly, how- ever, results highlighted the potentially protective role of SBHCs for this population. SMY in schools with SBHCs were less likely to drink alcohol, use e-cigarettes, use marijuana, and use unprescribed prescription drugs com- pared with SMY in schools without SBHCs, controlling for key student and school-level characteristics. The marked differences observed in SMY sub- stance use behaviors in schools with SBHCs highlight the potential for SBHCs to reduce health disparities among SMY.

Studies suggest SMY report greater unmet health care needs than their heterosexual peers (Ramos et al., 2017; Williams & Chapman, 2011). Perhaps SBHCs may be particularly adaptive health service centers for reducing adolescents’ barriers to the receipt of health services (e.g., access; Ginsburg et al., 2002; Newman et al., 2014). Indeed, SMY report greater service utilization (Filice & Meyer, 2018) and a preference for accessing health services in school settings (Wells et al., 2013), which may translate to greater expo- sure, information, and resources that support health behaviors, including reduced alcohol, tobacco, and other drug use. This additional utilization of health services may explain why the current study did not find that SBHC presence was associated with non-SMY health risk behaviors. Future research is necessary to examine the pathways by which SBHCs can support the health and reduced risk behaviors of students to assist SBHCs with identifying effective and efficient strategies to increase positive health behavior.

Furthermore, given SBHCs are often located in schools with greater numbers of marginalized or disadvantaged youth (Keeton et al., 2012; School- based Health Alliance, n.d.), staff may be better trained to conduct effective outreach or more adept at identifying marginalized populations compared with staff at non-SBHC schools. Educators, school administrators, or staff also may work with SBHC staff to ensure youth needing services are referred. Together, efforts may lead to greater engagement with and exposure to SBHC services for marginalized youth, which may ultimately support health out- comes. Although in the current study SBHC and non-SBHC schools were similar with respect to indicators of school-level economic disadvantage, we may have been underpowered to observe such school-level differences due to limited numbers of SBHC schools. The similarity in indicators of socioeconomic disadvantage may be attributable to both needs and local resources available for school-based health services across Oregon communities.

Alternatively, perhaps schools with SBHCs are better able to administer prevention-based messages. Indeed, a recent SBHC patient satisfaction sur- vey in Oregon indicated that a clear majority (approximately 90%) of students reported discussion of at least one prevention-based message with SBHC health care providers (Oregon Health Authority, 2015b). Future research should attempt to explore what specific and targeted SBHC activities have the greatest impacts on the health and behaviors of various adolescent subpopulations.

Our exploratory findings also revealed there were gender differences regarding the effect of SBHC access. It appeared that male SMY benefited more than female SMY when both were afforded access to SBHCs. These findings might be due to different SBHC utilization patterns across gender. Additional research is needed to examine the gender-specific behaviors of utilizing health services among SMY students to shed light on how SBHCs can provide targeted services to improve health outcomes for females and males. Furthermore, among SMY subgroups, our exploratory analyses indicated that the students who selected the “something else” response differed from the students who selected either “lesbian/gay” or “bisexual” responses with regard to associations between SBHC access and certain past 30-day substance use behaviors. Considering that the “something else” response option group reported lower overall rates of past 30-day substance use behaviors than the other two groups of SMY, we were reluctant to speculate about the possible association with access to SBHCs given lack of research in this area and small sample size of these subgroups. However, our analyses high- light different trends in the possible protective effect of SBHC across sub- groups of SMY, for example, students who self-identified as bisexual were less likely to engage in past 30-day marijuana use than those who self-identified as lesbian/gay. We were hesitant to draw a conclusion that access to SBHCs was more protective for self-identified bisexual youth than for self- identified lesbian/gay youth given that the “lesbian/gay” group in schools with SBHCs (n = 58) was much smaller than the “bisexual” group (n = 219). These differences do point out a need to explore and understand these SMY subgroup differences in additional research with larger samples to help SBHCs maximize the potential benefits to marginalized population subgroups.

Although this study makes important contributions for understanding the association between SBHC access and SMY substance use behavior, results should be interpreted in light of several limitations. First, the cross-sectional survey design from which the data were drawn limits our ability to determine causality. Experimental or longitudinal study designs are needed to empirically test causality and directionality of hypothesized effects. Second, given the homogeneous sample, we were not able to address issues of intersectionality between sexual minority status and ethnic minority status and race. Relatedly, data were drawn from a single state, which may limit the generalizability of findings to diverse adolescents across the United States. Relationships between SBHC access and substance use behaviors among SMY should be examined using more representative samples in future research. Fourth, given the design of the study, we were not able to examine the specific services adolescents accessed within the SBHC, including those related to substance use and problems. Additional research is needed to examine the specific services adolescents used and how the use of these ser- vices affects alcohol, tobacco, and other drug use. Finally, this study was unable to explore other school variables (e.g., school climate; urbanicity, etc.) or other health services and supports provided to students, specifically SMY. Future studies that examine how SBHCs work in tandem with other services and supports will be important for understanding the role of SBHCs as health promotion centers.

Our findings provide important policy implications as results suggest that access to SBHCs may help ameliorate health disparities among marginalized youth populations, such as SMY. Hadland et al. (2016) argue that health services aimed at supporting SMY need to be available, accessible, acceptable, and equitable. SBHCs are conveniently located on school grounds and can serve important roles in meeting SMY’s health needs. These health service access points emphasize confidentiality as well as respect and provide an inclusive and affirmative environment that may reduce SMY’s barriers to health care.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by grants from the National Institute on Child Health and Human Development (NICHD; Grant R01 HD073386) and the National Institute on Alcohol Abuse and Alcoholism (NIAAA; Grant T32AA014125) of the National Institutes of Health (NIH).

Abbreviations:

SBHC

School-based health center

SMY

sexual minority youth

Biography

Lei Zhang is an associate research scientist at Pacific Institute for Research and Evaluation in Chapel Hill, NC. Her research interests include protective and risk fac- tors in adolescence regarding substance use, and multi-level contextual factors on adolescent health risk behaviors.

Laura J. Finan is an assistant professor at the Illinois State University in psychology. Her research focuses on individual, family, and contextual influences on adolescent health risk behaviors, particularly alcohol use.

Melina Bersamin is a senior research scientist at the Prevention Research Center in Berkeley and Psychology Professor at Berkeley City College. Her research has focused on identifying the psycho-social predictors of adolescent risky behavior including early sexual initiation, casual sex, and alcohol abuse. More recently, she has examined the direct and indirect role of structural and contextual factors on adolescent sexual behavior.

Deborah A. Fisher is a research scientist at Pacific Institute for Research and Evaluation in Calverton, MD. She received her Ph.D. in social psychology from The University of Texas at Austin. Her research focuses on youth risk taking, including alcohol and drug use and sexual behavior.

Mallie J. Paschall is a senior research scientist at the Prevention Research Center of the Pacific Institute for Research and Evaluation in Berkeley, California. Dr. Paschall obtained his doctorate in public health from the University of North Carolina – Chapel Hill in 1995. He conducts research on the etiology, epidemiology and prevention of substance use and related problems among adolescents and young adults.

Footnotes

Declaration of Conflicting Interests

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

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