Hierarchical Analysis of Disparities in Suicidal Outcomes With Intersection of Sexual Minority and Gender Among U.S. Youth,2017

Abstract

Sexual minority youth have a higher risk of suicidal behaviors than their straight peers. Despite this alarming trend, there is limited information on how health-risk factors are systematically associated with suicidal outcomes in relation to the intersection of sex and sexual orientation identity. Data from the 2017 Youth Risk Behavior Survey (Grades 9–12, N = 14,108) were analyzed to examine three distinct suicidal outcomes (i.e., suicidal ideation, suicide planning, and suicide attempt). Separate hierarchical logistic regression models were performed to gradually adjust for influencing factors in examining the association between suicidal outcomes and sexual orientation identity (i.e., heterosexual, gay/lesbian, bisexual, and unsure), stratified by self-reported sex. There exist significant differences in youth suicidal behaviors based on sexual orientation identity and sex: lesbians (adjusted odds ratio [AOR] = 2.7, 95% CI [1.5, 5.0]), bisexual girls (AOR = 1.9, 95% CI [1.3, 2.6]) and bisexual boys (AOR = 2.6, 95% CI [1.3, 5.2]) had higher odds of suicide attempts than their straight peers. Unsure boys and girls also reported higher risks of suicidal ideation and suicide plan as compared with their straight peers. Having a very short sleep duration, reporting ever use of illicit drugs, being bullied, and feeling sad/hopeless were associated with elevated risks of suicidality across males and females. This study identified potential disparities in suicidal outcomes by sexual orientation identity as well as factors that attenuate or strengthen this relationship in a representative sample of adolescents across the United States. An improved understanding of the differences in suicidal outcomes will serve as an opportunity to ameliorate any potential inequalities and improve sexual minority youth’ health outcomes.

Keywords

LGBQ suicidal ideation suicide attempt suicide plan youth YRBS

There has been a marked increase in suicidal behaviors among youths and young adults in the United States over the past decade (Han et al., 2018; The Centers for Disease Control and Prevention, 2019), with a 2.7% increase in suicidal ideation, 2.3% increase in suicide plan, and 0.5% increase in suicide attempts among U.S. adolescents from 2007 to 2017 (The Centers for Disease Control and Prevention, 2019). This increase in the prevalence of suicidality represents one of the largest modifiable risk factors for adolescent deaths in the United States—suicide is already the second leading cause of death for those aged 10 to 19 years (Heron, 2019). The disparity between suicidal thoughts and behaviors in adolescence among lesbian, gay, bisexual, and questioning (LGBQ) and their straight peers has been documented. For instance, a 2017 meta-analysis found that sexual orientation identity represented a significant increase in the odds of suicide attempts in adolescents (Miranda-Mendizabal et al., 2017). However, knowledge underlying the relationship of these suicidal outcomes, sexual orientation identity, and predictive behavioral/influencing factors is limited.

There are a variety of factors that may contribute to youth suicidal behaviors. Challenges associated with certain demographic groups, such as race and ethnicity due to racism, sex due to sexism, homophobia, and transphobia, and age due to developmental changes, and their intersections, have been documented as risk or protective factors for suicidal thoughts and behaviors (Cash & Bridge, 2009; Lindsey et al., 2019). For instance, a study (Lindsey et al., 2019) reported a significant increase in suicide attempts among non-Hispanic (NH) Black adolescents from 1991 to 2017, while there was a decreasing trend among other racial/ethnic adolescents. A growing body of literature has examined these factors. A demonstrated prospective relationship between sleep deprivation and depression (Roberts & Duong, 2014) indicates that sleep disturbances are associated with suicidal ideation and behaviors among adolescents (Bernert & Joiner, 2007; Goldstein et al., 2008). Excessive use of electronic media (e.g., watching TV, video, or computer use) has been found to be associated with adolescents’ sleep deprivation (Cain & Gradisar, 2010; Johnson et al., 2004), mood disturbance (Hoge et al., 2017; Rikkers et al., 2016), and increased risk of suicidal behaviors (Robertson et al., 2012; Rostad et al., 2018). A 2015 meta-analysis of 31 studies also found that those who partook in excessive substance abuse had nearly doubled the risk for suicidal ideation and about two-fold increased risk in a suicide attempt and death from suicide (Darvishi et al., 2015). This relationship is particularly troubling as previous literature has found that adolescence who are sexual minorities are more likely to abuse substances (Corliss et al., 2010; Dai, 2017). Victimization, such as forced sexual behaviors and bullying, has been shown to be a factor that is related to suicidal behavior in adolescence. (Messias et al., 2014) Furthermore, LGBQ adolescents are more likely to experience victimization and depressive symptoms than their straight peers, partly due to social stigma from heterosexism and lack of protective policies in school and communities (Collier et al., 2013; Mustanski et al., 2016). The “Minority Stress Theory” posits that stressful social environments, which LGBQ youth are regularly forced to confront, can contribute to increased health complications as compared with their straight peers (Meyer, 2003; Meyer & Frost, 2013). However, these influencing factors on suicidal behaviors have not been fully evaluated among LGBQ adolescents.

Suicidal behaviors occur on a continuum of severity that progresses from ideation of suicide thoughts and planning for suicide attempts to actual attempts of suicide (Uddin et al., 2019). Subjects with suicidal risks usually start with having symptoms of suicidal ideation (Mann et al., 2005) and studies have found a strong association between suicide planning and subsequent suicide attempts which constitutes a psychiatric emergency (Han et al., 2015; Mann et al., 2005). Furthermore, a suicide attempt is the strongest predictor of suicide death (Coryell & Young, 2005). As a result, these three suicidal outcomes (i.e., suicidal ideation, suicide plan, and suicide attempt) are distinct categories of suicidal elements with separate prediction and prevention strategies in both clinical and nonclinical settings (Nock et al., 2013). It is important to enhance understanding of mechanisms that affect different suicidal behaviors among LGBQ adolescents and identify the hierarchical chain in which the influencing factors might moderate this relationship.

To fill the gap in the literature, we analyzed the 2017 Youth Risk Behavior Survey (YRBS) data to assess the prevalence of these three suicidal measures by sexual orientation identity.

Method

Study Sample

Data were collected by the 2017 national YRBS, a cross-sectional study conducted in the spring of every odd year since 1991 to monitor adolescent health behaviors (The Centers for Disease Control and Prevention, 2021). A three-stage cluster sampling design, stratified by metropolitan statistical area (MSA) status and racial/ethnic concentration, was employed to get a nationally representative sample of high school students in Grades 9–12 across the United States. High school students completed this survey voluntarily and anonymously. The survey includes a weight factor to account for the complex survey design. The 2017 national YRBS had a school response rate of 75% and a student response rate of 81%, yielding an overall response rate of 60% (The Centers for Disease Control and Prevention, 2018). Given the use of public data with deidentified information, the University of Nebraska institutional review board determined this study to be nonhuman subject research.

Measures

Sexual orientation identity was determined by the item: “Which of the following best describe you?” with possible responses ranging from “Heterosexual (straight),” “Gay or Lesbian,” “Bisexual,” and “Not Sure.” We excluded 848 students who opted not to answer with missing sexual orientation identity, resulting in a participant pool of 14,108.

Three questions were used as measures of suicidal thoughts or actions. The first gauged suicidal ideation was assessed by the item: “During the past 12 months, did you ever seriously consider attempting suicide?” with dichotomous responses of “Yes” and “No. A further question sought to measure suicidal planning—“During the past 12 months, did you make a plan about how you would attempt suicide?” which again provided a dichotomous “Yes”/”No” choice. The third question sought to measure the number of suicide attempts —“During the past 12 months, how many times did you actually attempt suicide?” with answers ranging from “0 times,” “1 time,” “2 or 3 times,” “4 or 5 times,” to “6 or more times.” We consolidated responses with one or more attempts into a dichotomous outcome (yes, no) for the experience of ≥1 suicide attempt.

Based on previous research in the literature (Bilsen, 2018; Corliss et al., 2010; Goldstein et al., 2008; Messias et al., 2014), we included variables that could potentially influence the association between suicide outcomes and sexual orientation identity. The influencing factors included demographic variables, sleep duration, excessive use of electronic media, substance abuse, and experiences of victimization and mental illness.

Demographic factors include race and ethnicity (NH White, NH Black, Hispanic, and NH others), age (≤15 or >15 years old), and self-reported sex (female vs. male).

Sleep duration was assessed by the question: “On an average school night, how many hours of sleep do you get?” Response options included “4 or less hours,” “5 hours,” “6 hours,” “7 hours,” “8 hours,” “9 hours,” and “10 or more hours.” We categorized respondents’ sleep as very short duration (≤5 hours), short duration (6–7 hours), and normal duration (≥8 hours; Kann et al., 2016).

Excessive use of electronic media includes ≥3 hours of TV watching per school day (yes/no) and ≥3 hours of video or computer use per school day (yes/no; Johnson et al., 2004).

Substance abuse was characterized by the following dichotomous elements: tobacco use (current; ≥1 day of using tobacco products in the previous 30 days), marijuana use (current; ≥1 time using marijuana products in the previous 30 days), alcohol use (current; ≥1 drink of alcohol products in the previous 30 days), ever use of illicit drugs, including synthetic marijuana, other illicit drugs, and nonmedical prescription drug use in their lifetime (Demissie et al., 2017).

Experience of victimization and depressive symptoms were selected based on a review of existing research (Lowry et al., 2017; Stone et al., 2014). The variables included being bullied on school property or electronically in the past 12 months (yes vs. no) and the victim of forced sexual intercourse (yes vs. no). In addition, students were asked whether they felt sad or hopeless almost every day for 2 weeks or more prompting them to stop some usual activities (yes vs. no; Lowry et al., 2017; Stone et al., 2014).

Statistical Methods

Weighted estimates and 95% confidence intervals (CIs) of demographics and health behaviors, as well as the three suicidal outcome measures, were reported by sexual orientation identity (heterosexual, gay/lesbian, bisexual, and not sure). To adjust for the survey sampling design, we performed Rao-Scott Chi-square tests to detect group differences by sexual orientation identity (McHugh, 2013). Separate nested hierarchical logistic models by sex (female vs. male) were performed to compare differences in suicidal ideation, suicide plan, and suicide attempt by sexual orientation identity. The regression models were incrementally adjusted for influencing factors such as demographics, sleep duration, excessive use of electronic media, substance abuse, experiences of victimization, and depressive symptoms. Since suicide attempts are the most prominent risk factor associated with suicide deaths, multivariable analyses of suicidal attempts are included in the main text, and the analyses of suicidal ideation and suicide plan are included in the appendix. We also reported the relationship among three suicide outcome variables and multivariable analyses of suicide attempts using suicidal ideation and suicide plan as predictive variables in the appendix. Adjusted odds ratios (AOR) are presented to measure the associations between influencing factors and the outcomes of interest. Missing covariate observations were relatively small, ranging from 0 (alcohol use and sleep duration) to 690 (≥3 hours of video or computer use; see details in the footnote of Table 1), and these observations were removed from the multivariable regression models. Statistical analyses were performed using SAS 9.4 (Cary, NC). A p value <.05 was considered statistically significant.

Table 1.

Sample Characteristics by Self-Reported Sexual Orientation Identity, 2017 YRBS (N = 14,108).

Factors^a	Heterosexual/Straight % [95% CI]	Gay/Lesbian % [95% CI]	Bisexual % [95% CI]	Unsure % [95% CI]	p ^b
n	12,012	357	1,137	602
Weighted % [95% CI]	85.4 [84.6, 86.2]	2.4 [2.0, 2.7]	8.0 [7.5, 8.6]	4.2 [3.7, 4.6]
Sex
Female	46.3 [45.2, 47.5]	50.0 [42.7, 57.3]	82.3 [79.2, 85.3]	59.6 [54.2, 65.0]	<.0001
Male	53.7 [52.5, 54.8]	50.0 [42.7, 57.3]	17.7 [14.7, 20.8]	40.4 [35.0, 45.8]
Age, years
≤15	36.5 [35.4, 37.6]	34.0 [27.0, 41.0]	36.8 [33.0, 40.5]	41.6 [36.3, 46.9]	.2574
>15	63.5 [62.4, 64.6]	66.0 [59.0, 73.0]	63.2 [59.5, 67.0]	58.4 [53.1, 63.7]
Grade
9 to 10	52.5 [51.4, 53.7]	51.8 [44.6, 59.0]	53.0 [49.1, 56.9]	57.2 [51.8, 62.6]	.4230
11 to 12	47.5 [46.3, 48.6]	48.2 [41.0, 55.4]	47.0 [43.1, 50.9]	42.8 [37.4, 48.2]
Race and ethnicity
NH-White	52.3 [51.2, 53.4]	45.6 [38.3, 53]	51.1 [47.1, 55]	53.5 [48.1, 58.9]	.0024
NH-Black	12.9 [12.2, 13.7]	22.2 [16.4, 28]	17.3 [14.3, 20.3]	14.3 [10.6, 18.0]
Hispanic	10.4 [9.8, 11.1]	7.7 [3.8, 11.6]	9.0 [6.7, 11.3]	8.4 [5.6, 11.2]
Others	24.3 [23.4, 25.3]	24.5 [18.5, 30.5]	22.6 [19.5, 25.7]	23.8 [19.6, 28.1]
Sleep and media use
Very short sleep (≤5 hours)	18.6 [17.7, 19.5]	28.3 [21.7, 34.9]	35.9 [32.1, 39.7]	24.9 [20.0, 29.7]	<.0001
TV ≥3 hours per day	20.5 [19.5, 21.5]	22.7 [16.1, 29.3]	26.4 [22.8, 30.0]	24.4 [19.4, 29.3]	.005
Video or computer games ≥3 hours per day	42.6 [41.5, 43.8]	43.0 [35.5, 50.5]	55.7 [51.8, 59.7]	47.4 [41.9, 52.9]	<.0001
Substance abuse
Current tobacco use	16.8 [15.9, 17.6]	21.3 [16.1, 26.5]	23.3 [20.0, 26.6]	16.6 [12.4, 20.8]	.001
Current marijuana use	19.1 [18.2, 20.1]	30.0 [22.9, 37.0]	30.8 [27.2, 34.5]	18.9 [14.7, 23.2]	<.0001
Current alcohol use	26.3 [25.3, 27.3]	28.6 [22.3, 34.9]	33.0 [29.3, 36.7]	18.7 [14.7, 22.8]	<.0001
Ever use of illicit drugs	25.9 [24.9, 26.9]	37.5 [30.5, 44.4]	40.9 [37.0, 44.7]	39.1 [33.7, 44.4]	<.0001
Victimization and depressive symptoms
Being bullied, school property/online	21.8 [20.8, 22.7]	34.4 [27.5, 41.4]	43.3 [39.4, 47.2]	32.0 [27.0, 37.0]	<.0001
Victim of forced intercourse	5.4 [4.9, 5.9]	21.2 [15.1, 27.2]	22.1 [18.7, 25.4]	13.1 [9.1, 17.1]	<.0001
Feeling sad or hopeless	27.5 [26.5, 28.6]	53.1 [45.8, 60.4]	66.0 [62.3, 69.6]	46.4 [40.9, 51.8]	<.0001

Note. YRBS = Youth Risk Behavior Survey; NH = non-Hispanic.

Missing covariate observations included sex (n = 119), age (n = 77), grade (n = 133), race and ethnicity (n = 304), sleep duration (n = 0), TV ≥3 hours per day (n = 668), ≥3 hours of video or computer us (n = 690), current tobacco use (n = 170), current marijuana use (n = 234), current alcohol use (n = 0), ever use of illicit drugs (n = 25), being bullied, school property/online (n = 150), victim of forced intercourse (n = 146), and feeling sad or hopeless (n = 204). ^bRao-Scott chi-square test was performed to compare the distribution of factors by sexual orientation identity.

Results

Table 1 presents sample characteristics by sexual orientation identity. Of the 14,108 students who expressed their self-identified sexual orientation, 85.4% (12,012) were heterosexual, 2.4% (357) were gay/lesbian, 8.0% (1,137) were bisexual, and 4.2% (602) were unsure. Differences by sex existed for adolescents who identified as bisexual (82.3% female and 17.7% male) and those who were unsure (59.6% female and 40.4% male; p < .0001). A higher percentage of gay/lesbian and bisexual students were NH Black people than heterosexual students (p = .0024). LGBQ students reported a higher prevalence of very short sleep duration (≤5 hours) than their straight peers (p < .0001). Gay/lesbian or bisexual students also reported a higher prevalence of substance abuse (e.g., current tobacco use (p = .0001), marijuana use (p < .0001), alcohol use (p < .0001), or ever use of illicit drugs (p < .0001)) than straight students. LGBQ students also had a higher prevalence of experiences of victimization or depressive symptoms. For instance, 66.0% of bisexual, 53.1% of gay/lesbian, and 46.4% of unsure students reported feeling sad or hopeless compared with 27.5% of straight students (p < .0001).

Table 2 displays the prevalence of three suicide outcomes (suicidal ideation, suicidal planning, and suicidal attempts) by sexual orientation identity. Overall LGBQ students had a higher prevalence of all three suicide outcomes than their straight counterparts. For instance, the prevalence of suicide attempts was higher for gay/lesbian (18.6%), bisexual (24.2%), and unsure (14.3%) adolescents—as compared with their heterosexual peers (5.4%; p < .0001). Furthermore, suicide outcomes were different by sex group and were more pronounced among female (vs. male) students. For instance, 50.8%, 39.4%, and 22.9% of lesbian students reported suicidal ideation, planning, and attempts, respectively, versus 30.3%, 24.8%, and 11.7% for gay students, respectively. In comparison, 16.9%, 12.8%, and 7.0% of straight females reported suicidal ideation, planning, and attempts, respectively, versus 10.2%, 8.2%, and 4.1% for straight males, respectively (p < .0001 for all outcomes).

Table 2.

Prevalence, % [95% CI], of Suicide Outcomes by Sex and Sexual Orientation Identity, 2017 YRBS (N = 14,108).

Sex group	Suicide outcomes	Heterosexual/straight	Gay/Lesbian	Bisexual	Unsure	p ^a
Overall	Suicide ideation	13.3 [12.5, 14.1]	41.4 [34.2, 48.6]	49.6 [45.7, 53.5]	31.8 [26.6, 36.9]	<.0001
	Suicide planning	10.4 [9.7, 11.2]	33.2 [26.3, 40.0]	39.4 [35.6, 43.3]	25.6 [20.7, 30.4]	<.0001
	Suicide attempts	5.4 [4.8, 6.0]	18.6 [12.1, 25.0]	24.2 [20.6, 27.8]	14.3 [10.3, 18.3]	<.0001
Female	Suicide ideation	16.9 [15.7, 18.2]	50.8 [41.3, 60.3]	51.1 [46.7, 55.4]	35.9 [29.1, 42.6]	<.0001
	Suicide planning	12.8 [11.7, 14.0]	39.4 [29.9, 48.8]	41.1 [36.8, 45.4]	26.8 [20.6, 33.0]	<.0001
	Suicide Attempts	7.0 [6.0, 7.9]	22.9 [13.2, 32.7]	23.8 [19.8, 27.8]	12.9 [8.2, 17.7]	<.0001
Male	Suicide ideation	10.2 [9.2, 11.1]	30.3 [19.8, 40.8]	42.5 [33.1, 52]	23.9 [16.1, 31.7]	<.0001
	Suicide planning	8.2 [7.3, 9.1]	24.8 [15.3, 34.3]	32.0 [23.1, 40.9]	21.9 [14.3, 29.5]	<.0001
	Suicide attempts	4.1 [3.3, 4.8]	11.7 [3.7, 19.6]	23.5 [14.5, 32.5]	13.8 [7.3, 20.3]	<.0001

Note. YRBS = Youth Risk Behavior Survey.

Rao-Scott chi-square test was performed to compare the distribution of suicide outcomes by sexual orientation identity.

To discern sex-based differences, the hierarchical models for the three outcomes were conducted separately by sex. Table 3 presents results from the nested hierarchical model of suicide attempts among female adolescents. As shown in the base model (Model I), lesbian (odds ratio [OR] = 4.0, 95% CI [2.2, 7.0]), bisexual (OR = 4.2, CI [3.2, 5.4]), and unsure (OR = 2.0, CI [1.3, 3.1]) students had significantly higher odds of reporting suicidal attempts in the past 12 months than their heterosexual peers. This relationship was attenuated after adjustment for demographic factors, sleep and excessive use of electronic media, substance use, experiences of victimization, and depressive symptoms. The full model (Model V) showed that even with these relevant predictors accounted for, the relationship between sexual orientation identity and suicide attempts was still significant except for unsure students. As compared with straight female students, those who identified as lesbian (AOR = 2.7, CI [1.5, 5.0]) and bisexual (AOR = 1.9, CI [1.3, 2.6]) possessed higher odds of engaging in a suicide attempt. Furthermore, younger adolescents (vs. older adolescents, AOR = 1.6, CI [1.2, 2.2]), NH Black adolescents (vs. NH Whites AOR = 2.0, CI [1.3, 3.2]) and other races (vs. NH Whites AOR = 1.7, CI [1.2, 2.3]) were more likely to report suicide attempts. The prevalence of suicide attempts was also higher among female students who reported a very short sleep duration (≤5 hours vs. ≥8 hours, AOR = 2.0, CI [1.3, 2.9]), watching TV ≥3 hours (AOR =1.6, CI [1.1, 2.2]), current marijuana use (AOR = 1.7, CI [1.2, 2.3]), ever use of illicit drugs (AOR = 1.7, CI [1.2, 2.4]), being bullied on school property or online (AOR = 2.5, CI [1.8, 3.3]), being forced to engage in sexual intercourse (AOR = 2.9, CI [2.1, 4.0]), and feeling sad or hopeless (AOR = 6.0, CI [4.0, 9.0]).

Table 3.

Nested Hierarchical Model^a of Suicidal Attempts Among Female Students (n = 7,211), 2017 YRBS.

Suicide attempt	Model I (Base: sexual orientation identity)	Model II (Base + demographic factors)	Model III (Base + demographic factors + sleep and media use)	Model IV (Base + demographic factors + sleep and media use + substance use)	Model V (Base + demographic factors + sleep & media use + substance use + experiences of victimization)
Females	OR [CI]	AOR [CI]	AOR [CI]	AOR [CI]	AOR [CI]
Sexual orientation identity
Heterosexual/straight	Reference	Reference	Reference	Reference	Reference
Lesbian	4.0 [2.2, 7.0]***	4.1 [2.3, 7.5]***	4.5 [2.3, 8.7]***	4.0 [2.0, 7.8]***	2.7 [1.5, 5.0]**
Bisexual	4.2 [3.2, 5.4]***	4.2 [3.2, 5.5]***	3.5 [2.6, 4.6]***	3.1 [2.3, 4.3]***	1.9 [1.3, 2.6]***
Unsure	2.0 [1.3, 3.1]**	2 [1.3, 3.2]**	1.9 [1.1, 3.0]*	1.7 [1.0, 2.9]	1.1 [0.6, 1.9]
Demographic factors
Age, years
≤15		1.4 [1.1, 1.8]**	1.6 [1.2, 2.0]**	1.6 [1.2, 2.1]***	1.6 [1.2, 2.2]**
>15		Reference	Reference	Reference	Reference
Race and ethnicity
NH-White		Reference	Reference	Reference	Reference
NH-Black		1.4 [1, 2.1]	1.2 [0.8, 1.7]	1.5 [1.0, 2.2]	2.0 [1.3, 3.2]**
Hispanic		1.0 [0.6, 1.5]	1.1 [0.7, 1.6]	1.0 [0.7, 1.6]	1.3 [0.9, 2.0]
Others		1.6 [1.2, 2.2]***	1.6 [1.2, 2.2]**	1.7 [1.2, 2.3]**	1.7 [1.2, 2.3]**
Physical health and excess use of media
Very short sleep (≤5 hours)			3.2 [2.2, 4.7]***	2.9 [2.0, 4.3]***	2.0 [1.3, 2.9]**
TV ≥3 hours			1.8 [1.3, 2.4]***	1.5 [1.1, 2.1]**	1.6 [1.1, 2.2]**
Video or computer games ≥3 hours			1.2 [0.9, 1.5]	1.3 [1.0, 1.7]	1.2 [0.9, 1.6]
Substance abuse
Current tobacco use				1.4 [1.0, 2.2]	1.3 [0.9, 2.0]
Current marijuana use				2.0 [1.4, 2.8]***	1.7 [1.2, 2.3]**
Current alcohol use				0.9 [0.7, 1.3]	0.9 [0.6, 1.2]
Ever use of illicit drugs				2.5 [1.9, 3.4]***	1.7 [1.2, 2.4]**
Victimization and depressive symptoms
Being bullied, school property/online					2.5 [1.8, 3.3]***
Forced intercourse					2.9 [2.1, 4.0]***
Feeling sad or hopeless					6.0 [4.0, 9.0]***

Note. YRBS = Youth Risk Behavior Survey; OR = odds ratio; AOR = adjusted odds ratio; NH = non-Hispanic.

Logistic regression models by sex were performed to incrementally adjust for predictors in the associations between sexual orientation identity and suicide attempt. The outcome is having ≥1 suicide attempt in the past 12 months versus not.

p < .05. ^**p < .01. ^***p < .001.

Table 4 presents the results of nested hierarchical modeling on suicidal attempts among male students. In the base model, students who were identified as gay (OR = 3.1, CI [1.4, 6.9]), bisexual (OR = 7.3, CI [4.3, 12.4]), or unsure (OR = 3.8, CI [2.1, 6.8]) had increased odds of reporting suicide attempts as compared with their straight peers. The final model shows that these odds were attenuated to be insignificant by the covariates for students who identified as gay or unsure, but the association continued to be significant for bisexual males (AOR = 2.6, CI [1.3, 5.2]). Predictors that were associated with an elevated risk of suicide attempts in male students included: a very short sleep (AOR = 2.0, CI [1.1, 3.7]), TV ≤3 hours (AOR = 1.9, CI [1.2, 2.9]), ever use of illicit drugs (AOR = 2.0, CI [1.2, 3.3]), being bullied (AOR = 2.0, CI [1.3, 3.1]), being forced to engage in sexual intercourse (AOR = 3.6, CI [1.9, 6.9]), and feeling sad/hopeless (AOR = 8.1, CI [5.1, 12.9]).

Table 4.

Nested Hierarchical Model^a of Suicidal Attempts Among Male Students (n = 6,778), 2017 YRBS.

Suicide attempt	Model I (Base: Sexual orientation identity)	Model II (Base + demographic factors)	Model III (Base + demographic factors + sleep and media use)	Model IV (Base + demographic factors + sleep and media use + substance use)	Model V (Base + demographic factors + sleep and media use + substance use + experiences of victimization)
Males	OR [CI]	AOR [CI]	AOR [CI]	AOR [CI]	AOR [CI]
Sexual orientation identity
Heterosexual/straight	Reference	Reference	Reference	Reference	Reference
Gay	3.1 [1.4, 6.9]**	3.1 [1.4, 6.7]**	2.1 [0.8, 5.6]	2.7 [1.2, 6.0]*	1.3 [0.4, 3.9]
Bisexual	7.3 [4.3, 12.4]***	7.5 [4.4, 13.0]***	4.9 [2.6, 9.4]***	5.3 [2.8, 10.0]***	2.6 [1.3, 5.2]**
Unsure	3.8 [2.1, 6.8]***	3.9 [2.2, 6.9]***	3.2 [1.7, 6.0]***	2.7 [1.4, 5.2]**	0.9 [0.4, 2.1]
Demographic factors
Age
≤15		1.2 [0.8, 1.7]	1.4 [1.0, 2.0]	1.6 [1.1, 2.4]*	1.5 [1.0, 2.3]
>15		Reference	Reference	Reference	Reference
Race and ethnicity
NH-White		Reference	Reference	Reference	Reference
NH-Black		1.4 [0.9, 2.4]	1.1 [0.6, 1.9]	1.1 [0.6, 1.9]	1.4 [0.8, 2.5]
Hispanic		1.0 [0.5, 1.8]	0.9 [0.5, 1.7]	0.9 [0.4, 1.7]	0.9 [0.4, 1.9]
Others		1.2 [0.9, 1.8]	1.1 (0.8, 1.7]	1.1 [0.7, 1.7]	1.2 [0.7, 1.9]
Physical health and excess use of media
Very short sleep (≤5 hours)			3.2 [1.9, 5.3]***	2.7 [1.6, 4.5]***	2.0 [1.1, 3.7]*
TV ≥3 hours			1.7 [1.1, 2.4]**	1.7 [1.2, 2.5]**	1.9 [1.2, 2.9]**
Video or computer games ≥3 hours			1.3 [0.9, 1.9]	1.4 [1.0, 2.0]	1.3 [0.8, 1.9]
Substance abuse
Current tobacco use				1.5 [0.9, 2.6]	1.5 [0.9, 2.6]
Current marijuana use				1.7 [1.1, 2.7]*	1.3 [0.8, 2.2]
Current alcohol use				0.9 [0.5, 1.6]	0.7 [0.4, 1.2]
Ever use of illicit drugs				2.9 [1.9, 4.4]***	2.0 [1.2, 3.3]**
Victimization and depressive symptoms
Being bullied, school property/online					2.0 [1.3, 3.1]**
Forced intercourse					3.6 [1.9, 6.9]***
Feeling sad or hopeless					8.1 [5.1, 12.9]***

Note. YRBS = Youth Risk Behavior Survey; OR = odds ratio; AOR = adjusted odds ratio; NH = non-Hispanic.

p < .05. ^**p < .01. ^***p < .001.

Appendix Tables A1 and A2 represent the findings of the same nested hierarchical model with the outcome of suicidal ideation for females and males, respectively. Appendix Tables A3 and A4 show the results of suicide planning. Overall, female sexual minorities (lesbian, bisexual, and unsure) had higher odds of reporting suicidal ideation and planning than their straight peers. Male bisexual and unsure students also reported higher odds of suicidal ideation and planning than straight students. A very short sleep duration, being bullied on school property or online, being forced to engage in sexual intercourse, and feeling sad or hopeless are consistently associated with suicidal ideation or planning for both female and male students. NH Black adolescents were less likely than NH Whites to report suicidal ideation and planning among male students, but not among female students.

Appendix Table A5 presents the relationship between suicidal ideation, suicide plan, and suicide attempts. The prevalence of suicide attempts was much higher among those with suicidal ideation or suicide plan (vs. not). Appendix Table A6 shows the base model and full model for factors associated with suicidal attempts when suicidal ideation and suicide plan were included in the predictive model. Due to the strong multicollinearity of suicidal ideation and suicide plan with other influencing factors, many of these factors were no longer significant. For instance, the relationship between sexual orientation identity and suicide attempts was not significant in the base model except among bisexual male students.

Discussion

This study utilized data from a nationally representative sample of high-school students to determine factors associated with suicidal behaviors, emphasizing the roles and sex and sexual orientation identity. Consistent with previous studies (Raifman et al., 2020; Zaza et al., 2016), this study identified stark disparities in suicide behaviors, with LGBQ adolescents reporting more than three times higher adverse outcomes than their straight counterparts. While this association has been previously established, findings from this study contribute to the growing literature by identifying modifiable risk factors associated with risks in three suicidal outcomes among LGBQ high school students. We found that bisexual male students reported elevated suicidal outcomes than their gay peers, while bisexual and lesbian females exhibited similarly elevated suicidal outcomes. This disparity may be due to lack of social support among bisexual males as studies have shown that social connectedness to the LGBTQ community is more limited among bisexual males than gay men (Abichahine & Veenstra, 2017; Kertzner et al., 2009), and self-concealment is a strong predictor of suicide behaviors (Friedlander et al., 2012). These findings underscored the importance of examining the potential heterogeneity among LGB subgroups by identifying unique characteristics within each sexual orientation identity and its intersection with sex groups related to suicidal outcomes.

Suicidal ideation and suicide plan are precursors of suicide attempt, which is the most robust risk factor associated with a suicide death (Borges et al., 2010). Previous studies have reported the elevated risk of suicidal behaviors among LGBQ youth (Miranda-Mendizabal et al., 2017). Our study adds to the existing literature by further identifying heterogeneous effects across three distinct suicide outcomes with the intersection between sex and sexual orientation identity. For female adolescents, there existed a significant association between all three suicidal outcomes and sexual orientation identity except that this relationship was attenuated to be insignificant for suicide attempts among unsure females. For male adolescents, being bisexual represented an increase in the odds of suicidal ideation, planning, and attempts, but the relationship between being gay and all three outcomes of suicidal behavior was attenuated to be insignificant after adjusting for influencing factors. This was also the case for unsure high school males and suicide attempts. Researchers have laid out a minority stress model as the theoretical framework to elucidate the root cause of health disparities and increased risky behaviors among LGBQ populations (Meyer, 2003). In-depth investigation on the social and psychological domains shows that LGBQ people who live in a hostile environment with homophobic culture could suffer from a lifetime of harassment, maltreatment, discrimination, and victimization (Marshal et al., 2011; Meyer, 2003), which could lead to deteriorated health outcomes and risky behaviors in many aspects. Our study adds empirical evidence to support the minority stress theory, with strong evidence showing these stresses are at an elevated level in the early stage of life. The distinct patterns of suicidal outcomes with the intersection of sexual orientation identity and sex underscore that LGBQ adolescents are heterogeneous. A one-size-fits-all approach might not work for LGBQ youth, and tailored evidence-based strategies are needed to counter the elevated suicide risk among this vulnerable population.

Suicide prevention interventions should focus on key protective risk factors that may ameliorate stigma and reduce risk-seeking behaviors related to suicide. Consistent with previous literature (Bernert & Joiner, 2007; Goldstein et al., 2008; Messias et al., 2014; Wu et al., 2004), our study identified having a very short sleep duration, ever use of illicit drugs, being bullied, and feeling sad/hopeless as key indicators of suicidality in both boys and girls—demonstrating that these are integral areas that must be addressed to reduce suicidal behaviors in adolescents. However, unique factors related to distinct suicide outcomes were also identified across sex and sexual orientation identity. For instance, being younger (vs. older) or NH Black females (vs. White) are associated with an increased risk of suicide attempts but not for males. The higher suicide attempts among NH Black girls may be due to low rate utilization of mental health treatment (Wu et al., 1999), which could be related to racism (Lanier et al., 2017), mistrust of health care providers (Lindsey et al., 2010), varied perception of mental health care in the Black community, limited access to culturally sensitive treatment in consideration of slavery and colonialism (Adewale et al., 2016), and not wanting to be viewed as a weak person and refusing to acknowledge mental illness symptoms (Lindsey et al., 2006). These factors could further increase the burden of psychosocial stress among LGBQ youths who are already at an increased risk of suicidal behavior as a result of nonacceptant, inadequate support within their closest social network, and an inadequate LGBQ support movement ( Poštuvan et al., 2019). Treatments in both clinical and nonclinical settings should focus on reducing the symptoms or signs of suicidal behaviors. School educators, parents, and health practitioners can also play an important role in screening risk indicators of suicide outcomes, such as screening of very short sleep duration, sadness/hopelessness, and ever use of illicit drugs. Future research should evaluate how interventions or treatments can integrate these modifiable predictors associated with suicidality identified here for those in high-risk groups.

This study has several limitations. First, sexual orientation identity is self-reported and it is subject to recall and social desirability biases. Since sexual orientation identity is sensitive, some students may be more likely to underreport their sexual orientation out of concern that teachers, parents, or peers might see their responses. However, the YRBS survey questions have demonstrated good test–retest reliability (Brener et al., 2002). Second, since there was discordance between sexual orientation identity and sex of sexual contacts (Zaza et al., 2016) the sexual identity question yields a larger sample size as compared with the question of sex of sexual contacts (The Centers for Disease Control and Prevention, 2016); this study did not assess suicide behaviors by sexual orientation behavior or sexual orientation attraction. Third, the results obtained can only be generalized to high school students in the United States. Due to lack of school policies or practices that support LGB youth (Demissie et al., 2018), limited access to safe adults (Seelman et al., 2015) as well as low perceived safety at school and fear of physical violence or harassment among LGB youth (Hanson et al., 2019), LGBQ youth are more likely to have poorer school attendance than their straight peers (Aragon et al., 2014; Bidell, 2014; Robinson & Espelage, 2011; Seelman et al., 2015). Fourth, the 2017 YRBS data are cross-sectional. Thus we are unable to establish any causal effects. Finally, the data does not include information on transgender students.

Despite these limitations, results from this study can be used to identify potential disparities in three suicidal outcomes by sexual orientation identity and determine covariates that attenuate or strengthen this relationship in a representative sample of adolescents across the United States. An improved understanding of the differences in suicidal outcomes by sex and establishing factors strongly related to these outcomes will serve as an opportunity to ameliorate any potential inequalities and provide suggestions regarding where to allocate prevention efforts to help in the reduction of LGB high school suicide.

Footnotes

Appendix

Table A6.

Nested Hierarchical Model of Suicide Attempt^a, 2017 YRBS.

Suicidal outcomes	Sex = Female		Sex = Male
	Model I (Base: Suicide ideation and suicide plan + sexual orientation identity)	Model V (Base + demographic factors + sleep and media use + substance use + experiences of victimization)	Model I (Base: Suicide ideation and suicide plan + sexual orientation identity)	Model V (Base + demographic factors + sleep and media use + substance use + experiences of victimization)
	AOR [CI]	AOR [CI]	OR [CI]	AOR [CI]
Suicide ideation
No	Reference	Reference	Reference	Reference
Yes	21.6 [12.5, 37.4]***	20.3 [10.3, 40.1]***	16.1 [9.3, 27.7]***	31.7 [15.4, 65.0]***
Suicide plan
No	Reference	Reference	Reference	Reference
Yes	6.3 [4.4, 9.2]***	6.0 [4.0, 8.9]***	7.4 [4.7, 11.6]***	6.5 [3.8, 11.1]***
Sexual orientation identity
Heterosexual/straight	Reference	Reference	Reference	Reference
Lesbian/gay	1.0 [0.5, 2.0]	1.2 [0.6, 2.3]	1.4 [0.3, 5.8]	1.4 [0.4, 4.5]
Bisexual	1.2 [0.8, 1.6]	0.9 [0.6, 1.3]	2.6 [1.4, 4.7]**	2.2 [1.0, 4.7]
Unsure	0.7 [0.4, 1.3]	0.5 [0.2, 0.9]*	1.3 [0.5, 3.4]	0.5 [0.1, 1.8]
Demographic factors
Age, years
≤15		1.9 [1.3, 2.7]***		2.2 [1.3, 3.7]**
>15		Reference		Reference
Race and ethnicity
NH-White		Reference		Reference
NH-Black		2.6 [1.5, 4.5]**		3.1 [1.5, 6.5]**
Hispanic		1.5 [0.8, 2.7]		0.7 [0.3, 1.7]
Others		1.5 [1.0, 2.2]*		1.2 [0.7, 2.2]
Physical health and excess use of media
Very short sleep (≤5 hours)		1.7 [1, 2.9]*		1.3 [0.6, 2.7]
TV ≥3 hours		1.6 [1.1, 2.3]*		2.7 [1.5, 4.8]**
Video or computer games ≥3 hours		1.1 [0.8, 1.6]		0.8 [0.5, 1.3]
Substance abuse
Current tobacco use		1.2 [0.7, 1.8]		1.5 [0.8, 2.8]
Current marijuana use		1.5 [1.0, 2.3]*		1.4 [0.8, 2.6]
Current alcohol use		0.9 [0.6, 1.3]		0.7 [0.4, 1.4]
Ever use of illicit drugs		1.2 [0.8, 1.8]		1.8 [1.0, 3.1]*
Victimization and depressive symptoms
Being bullied, school property/online		2.0 [1.5, 2.8]***		1.1 [0.7, 1.9]
Forced intercourse		2.1 [1.5, 3.1]***		3.6 [1.4, 9.1]**
Feeling sad or hopeless		1.7 [1.0, 2.8]*		1.2 [0.7, 2.2]

Note. YRBS = Youth Risk Behavior Survey; OR = odds ratio; AOR = adjusted odds ratio; NH = non-Hispanic.

p < .05. ^**p < .01. ^***p < .001.

Declaration of Conflicting Interests

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

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Hongying Dai

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