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. Author manuscript; available in PMC: 2025 Aug 16.
Published in final edited form as: Am J Prev Med. 2022 Aug 23;63(5):669–680. doi: 10.1016/j.amepre.2022.06.013

Intersectionality of Sexual Orientation With Race and Ethnicity and Associations With E-Cigarette Use Status Among U.S. Youth

Juhan Lee 1, Andy SL Tan 2,3
PMCID: PMC12355321  NIHMSID: NIHMS2100400  PMID: 36272758

Abstract

Introduction:

Although structural discrimination against sexual and racial/ethnicity minorities is a putative risk factor for youth tobacco use, understanding health disparities in youth E-cigarette use at the intersection of sexual orientation, race, and ethnicity is still lacking. This study aims to examine the differences in E-cigarette use prevalence among U.S. youth at the intersections of sexual orientation with race and ethnicity.

Methods:

E-cigarette use status (never, experimental, or current use) was analyzed among 38,510 U.S. youth using a pooled data set from the Youth Risk Behavior Surveillance System 2015–2019. The weighted E-cigarette use status between youth at the intersections of sexual orientation with race and ethnicity was reported, stratified by sex. Multivariable multinomial regression adjusting for relevant covariates was further conducted. Data analyses were performed in April 2022.

Results:

After controlling for other covariates, the RRR of current E-cigarette use compared with never use between lesbian Black girls (and heterosexual Black girls) was higher than between lesbian White girls (and heterosexual White girls) (adjusted RRR=6.99; 95% CI=2.21, 22.14). The RRR of current E-cigarette use compared with never use between lesbian other race/multiracial girls (and heterosexual other race/multi-racial girls) was higher than between lesbian White girls (and heterosexual White girls) (adjusted RRR=3.60; 95% CI=1.06, 12.26).

Conclusions:

This study has shown that sexual minority Black girls were more likely to currently use E-cigarettes than heterosexual Black girls. Future studies should examine the underlying reasons for current E-cigarette use among girls with intersectional identities, including race and sexual orientation.

INTRODUCTION

Since being introduced to the U.S. commercial market in 2013–2014, E-cigarettes have gained popularity, particularly among young people.1 E-cigarette use (or vaping), especially in younger age groups, is particularly concerning because it is associated with negative health outcomes such as the initiation and escalation of cigarette smoking.2 Previous studies have indicated that young people who identify as sexual minority report higher rates of E-cigarette use.3–6 Furthermore, sexual minority youth were more likely to initiate E-cigarette use at a younger age than heterosexual youth, and differences in such prevalence of E-cigarette use by sexual orientation become more pronounced in adulthood.7 According to the Centers for Disease Control and Prevention (CDC), “sexual minorities include, but are not limited to, individuals who identify as gay, lesbian, or bisexual, or who are attracted to or have sexual contact with people of the same gender.”8,9

Factors associated with a higher prevalence of E-cigarette use and other forms of tobacco among sexual minority youth may be associated with coping with minority stress from structural sexual orientation‒based discrimination.4,10–14 Furthermore, E-cigarette use might be encouraged by normative influences in sexual minority youth networks, such as having more peers who use E-cigarettes,15 and tobacco use is viewed as a sign of social group belonging.16 Another underlying mechanism is the tobacco industry’s targeted E-cigarette marketing among traditionally marginalized groups. Sexual, racial, and ethnic minority populations are historically targeted by tobacco industry marketing, particularly in neighborhoods and social settings (e.g., bars, clubs).17–19 This might be similar to E-cigarette marketing, which is pervasive in traditional channels as well as online and on social media, targeting sexual, race, and ethnic minority populations.20

Given that, incorporating intersectionality in youth E-cigarette use research is important because youth E-cigarette use may be influenced by complex and multiple axes of marginalization and privilege experienced by youth with intersecting identities and backgrounds, including sexual orientation, sex, race, and ethnicity. Previous studies reported differences in the prevalence of cigarette smoking at the intersections of sexual orientation, sex, race, and ethnicity among adolescents and young adults.21–24 Race and ethnicity add additional layers to the observed disparities in E-cigarette use by sex and sexual orientation. E-cigarette use is more prevalent among non-Hispanic White youth than among Black and Hispanic youth; however, a sizable minority of Black and Hispanic youth still use E-cigarettes.25 Furthermore, frequent use of E-cigarettes (used ≥20 days in the past 30 days) increased among Hispanic youth between 2014 and 2019, and non-Hispanic Black youth who used E-cigarettes were more likely to be dual users in 2019 (i.e., co-use of E-cigarettes and cigarettes or other tobacco products).26

Nonetheless, previous studies have not examined the differences in E-cigarette use prevalence among youth at the intersections of sexual orientation, sex, race, and ethnicity. Previous studies examined youth and adult tobacco use, including cigarettes and cigars at the intersection of sexual orientation and gender identity with race and ethnicity22,27–29; however, these studies did not include E-cigarettes. Therefore, the objectives of this study are to examine the prevalence of E-cigarette use at the intersections between sexual orientation, race, and ethnicity, stratified by sex, using a U.S. national data set. Potential disparities in the prevalence of E-cigarette use at the intersections of these identities may inform future research on the underlying drivers of E-cigarette use disparities among youth from traditionally marginalized populations.

METHODS

Study Sample

Data were from CDC’s Youth Risk Behavior Surveillance System (YRBSS)30 from the combined survey years of 2015 (n=15,624), 2017 (n=14,765), and 2019 (n=13,677). The YRBSS is a school-based national survey on health behaviors. It uses a multistage cluster sampling design; thus, the sample respondents represent U.S. population estimates.30 The overall response rates were 60%, 60%, and 60.3% in 2015, 2017, and 2019, respectively. Respondents were asked to self-report their sexual orientation with 1 question asking, Which of the following best describe you? with response options of heterosexual (straight), gay or lesbian, bisexual, and not sure. Consistent with analytical methodology in a previous study,4 participants who were missing (n=2,280) were excluded.

For assessing E-cigarette use status, the following 2 questions were used: (1) have you ever used an electronic vapor product? And (2) during the past 30 days, on how many days did you use an electronic vapor product? Participants were categorized as (1) never users (never used E-cigarettes), (2) experimental users (ever used E-cigarettes but 0-day use in the past 30 days), and (3) current E-cigarette users (ever used E-cigarettes and used E-cigarettes ≥1 day). Responses from youth who had complete information on questions regarding their sexual orientation and E-cigarette use behaviors were included for a final analytic sample of 38,510 respondents.

Measures

The YRBSS asked about ethnicity and race in separate questions. Race and ethnicity were examined separately because conflating race and ethnicity could lose the nuances in interpreting intersections with sexual orientation. Ethnicity was measured with the question Are you Hispanic or Latino? with response options of yes or no. Race was measured with the question What is your race? (select 1 or more responses) with response options of A. American Indian or Alaska Native (AIAN); B. Asian; C. Black or African American; D. Native Hawaiian or Other Pacific Islander (NH/PI); or E. White. The YRBSS provided this as a string variable (e.g., C, E, B, BC, CD); thus, this study categorized youth who only reported E as White only, youth who only reported C as Black only, and other responses as Other races or more than one race. Consequently, other specific racial groups (e.g., American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander) could not be examined because of the small cell sizes of each group for each of the sexual orientation identity categories.

Potential covariates were selected on the basis of previous studies.31 These included survey year (2015, 2017, 2019; treated as a categorical variable), age (12–15 years or ≥16–18 years), current cigarette smoking (yes or no), current other tobacco use (i.e., smokeless tobacco and cigars) (any or none), current alcohol use (yes or no), current cannabis use (yes or no), lifetime any illicit drug use32 (opioid misuse, cocaine, Lysergic acid diethylamide (LSD), inhalant, heroin, methamphetamines, ecstasy, steroid, illegal injection), being bullied in the past 12 months either at school or electronically (none or any),14 past 12-month externalizing tendencies (during the past 12 months, how many times were you in a physical fight? yes or no),33 and internalizing tendencies (during the past 12 months, did you ever feel so sad or hopeless almost every day for 2 weeks or more in a row that you stopped doing some usual activities? yes or no).34

Statistical Analysis

First, Rao-Scott adjusted chi-square tests were conducted to compare the significant difference in the prevalence of E-cigarette use status by each predictor. To examine the intersectionality of sexual orientation and race on predicting E-cigarette use status, a series of multivariable multinomial logistic regression models on E-cigarette use status by sexual orientation and race were conducted, after controlling for other associated factors, and stratified by sex. The same set of analyses was performed to examine the intersectionality between sexual orientation and ethnicity in predicting E-cigarette use status. The regression models were stratified by sex because of previous research indicating that lesbian and bisexual girls had significantly higher odds of E-cigarette use than heterosexual girls, whereas there were no significant differences in E-cigarette use prevalence among boys on the basis of sexual identity.24,31,35 Those multivariable multinomial logistic regression models simultaneously tested main effects and interactions. As RR measures could overstate differences between groups, the absolute risk differences of each group (marginal effect) were also estimated.36

Because this study used pooled data sets of 3 survey years, the weight variable was divided by 3 and used in variance estimation using Taylor series linearization.37 A p<0.05 (2-tailed) was considered statistically significant. The observational, secondary data analyses of publicly available, deidentified data sets were deemed exempt by Yale University IRB. Data analyses were conducted in April 2022.

RESULTS

Table 1 shows the sample characteristics by E-cigarette use status. Overall, self-reported sexual minority identity was higher in girls (lesbian: 2.4%; bisexual: 11.9%, weighted) than in boys (gay: 1.9%; bisexual: 2.7%, respectively). There were significant associations between sexual orientation and E-cigarette use status both among boys and girls. Of the analytic sample (n=38,510), 23.7% were Hispanic, 69.1% were White, 15.0% were Black, and 16.0% were of other races or multiracial. Other characteristics by sexual orientation are provided in Appendix Table 1 (available online). After controlling for other covariates, there was no significant interaction effect between sexual orientation and race/ethnicity on experimental use of E-cigarettes (Table 2).

Table 1.

Results of Bivariate Associations Between Sexual Identity and E-Cigarette Use Status Survey Years, 2015—2019 (N=38,510)

Variables Total Overall, n (weighted %) Never n=21,779; 56.8%, n (weighted %) Experimentala (ever but not currently) n=7,700; 19.7%, n (weighted %) Currentb n=9,031; 23.5%, n (weighted %) p-valuec
Sex and sexual orientation
 Boys <0.001
  Heterosexual 17,319 (92.5) 9,492 (55.3) 3,447 (19.8) 4,380 (24.9)
  Gay 382 (1.9) 202 (56.8) 81 (21.6) 99 (21.6)
  Bisexual 501 (2.7) 286 (59.2) 94 (18.4) 121(22.4)
  Unsure 559 (2.9) 382 (68.5) 67 (12.2) 110 (19.3)
 Girls <0.001
  Heterosexual 15,709 (81.0) 9,358 (59.6) 3,097 (19.1) 3,254 (21.3)
  Lesbian 506 (2.4) 252 (50.5) 125 (23.7) 129 (25.8)
  Bisexual 2,347 (11.9) 1,091 (46.2) 570 (24.6) 686 (29.2)
  Unsure 927 (4.7) 568 (60.5) 175 (19.1) 184 (20.4)
Hispanic <0.001
 No 27,513 (76.4) 15,925 (57.9) 5,043 (18.6) 6,545 (23.5)
 Yes 10,431 (23.7) 5,519 (53.4) 2,559 (23.3) 2,353 (23.4)
Race <0.001
 White only 21,553 (69.1) 11,637 (55.4) 4,093 (18.6) 5,823 (26.1)
 Black only 6,024 (15.0) 3,961 (63.1) 1,183 (20.8) 880 (16.2)
 Other races/multiracial 6,048 (16.0) 3,488 (58.4) 1,252 (20.9) 1,308 (20.7)
Survey years <0.001
 2015 14,229 (37.2) 7,495 (55.1) 3,104 (20.9) 3,630 (24.1)
 2017 12,208 (31.0) 7,972 (64.1) 2,679 (22.4) 1,557 (13.5)
 2019 12,073 (31.8) 6,312 (51.8) 1,917 (15.7) 3,844 (32.5)
Age, years <0.001
 12–15 14,293 (36.9) 9,108 (64.6) 2,423 (16.9) 2,762 (18.5)
 16–18 or older 24,048 (63.2) 12,577 (52.3) 5,244 (21.3) 6,227 (26.4)
Past 12-month externalizing <0.001
 No 24,833 (78.0) 15,306 (62.1) 5,016 (19.4) 4,511 (18.6)
 Yes 6,862 (22.0) 2,703 (39.2) 1,482 (21.5) 2,677 (39.3)
Past 12-month internalizing <0.001
 No 25,631 (67.6) 15,880 (62.5) 4,789 (18.5) 4,962 (19.1)
 Yes 12,561 (32.5) 5,714 (45.0) 2,842 (22.3) 4,005 (32.7)
Past 12-month any bully <0.001
 None 29,038 (75.1) 17,238 (59.5) 5,772 (19.5) 6,028 (21.0)
 Any 9,190 (24.9) 4,389 (48.8) 1,862 (20.2) 2,939 (31.0)
Current cigarette <0.001
 No 33,733 (91.3) 20,814 (62.0) 6,836 (19.8) 6,083 (18.2)
 Yes 3,120 (8.7) 298 (9.0) 531 (17.4) 2,291(73.6)
Current other tobacco <0.001
 No 33,712 (89.4) 20,883 (62.5) 6,741 (19.7) 6,088 (17.8)
 Yes 3,771 (10.6) 449 (11.1) 725 (19.9) 2,597 (69.0)
Current alcohol <0.001
 No 24,988 (70.2) 17,895 (72.5) 4,583 (17.7) 2,510 (9.8)
 Yes 10,421 (29.8) 2,523 (23.8) 2,378 (23.0) 5,520 (53.2)
Current cannabis <0.001
 No 30,209 (79.5) 20,247 (67.8) 5,788 (18.7) 4,174 (13.6)
 Yes 7,794 (20.5) 1,344 (15.6) 1,808 (23.7) 4,642 (60.8)
Ever any illicit drug <0.001
 No 21,405 (76.4) 13,951 (65.2) 3,991 (18.0) 3,463 (16.8)
 Yes 7,982 (23.6) 2,238 (26.9) 1,972 (25.3) 3,772 (47.8)
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Note: Boldface indicates statistical significance (p<0.001).

a

Have ever used E-cigarettes but not used in past 30 days.

b

Have ever used E-cigarettes and used in the past 30 days.

c

Rao-Scott adjusted chi-square tests.

Table 2.

Adjusted Results of Interaction Model on E-Cigarette Use Status by Sexual Orientation and Ethnicity, Stratified by Sex

Boys
 Girls
Experiment
 Current
 Experiment
 Current
aRRR (95% CI) p-value aRRR (95% CI) p-value aRRR (95% CI) p-value aRRR (95% CI) p-value
Sexual orientation
 Heterosexual ref ref ref ref
 Gay or lesbian 1.45 (0.85, 2.47) 0.173 0.68 (0.31, 1.52) 0.349 0.90 (0.55, 1.45) 0.657 0.79 (0.45, 1.39) 0.405
 Bisexual 0.78 (0.51, 1.20) 0.261 0.43 (0.23, 0.78) 0.006 1.19 (0.96, 1.48) 0.112 0.77 (0.57, 1.04) 0.085
 Unsure 0.54 (0.31, 0.95) 0.033 0.34 (0.15, 0.75) 0.008 0.85 (0.57, 1.25) 0.401 0.55 (0.37, 0.84) 0.005
Hispanic
 No ref ref ref ref
 Yes 1.27 (1.06, 1.53) 0.010 0.90 (0.73, 1.12) 0.350 1.27 (1.05, 1.54) 0.014 0.84 (0.62, 1.14) 0.261
Sexual orientationa Hispanic
 Heterosexuala non-Hispanic ref ref ref ref
 Gay/lesbiana Hispanic 0.42 (0.12, 1.41) 0.158 0.96 (0.19, 4.74) 0.958 0.63 (0.18, 2.14) 0.454 1.13 (0.28, 4.47) 0.863
 Bisexuala Hispanic 2.60 (0.72, 9.44) 0.145 2.02 (0.73, 5.59) 0.175 0.85 (0.54, 1.34) 0.478 1.30 (0.70, 2.39) 0.399
 Unsurea Hispanic 0.97 (0.36, 2.60) 0.945 1.08 (0.32, 3.61) 0.905 1.23 (0.55, 2.75) 0.619 2.30 (0.84, 6.27) 0.102
Survey year
 2015 ref ref ref ref
 2017 1.05 (0.81, 1.35) 0.730 0.56 (0.37, 0.86) 0.009 0.88 (0.70, 1.09) 0.235 0.28 (0.20, 0.38) <0.001
 2019 1.12 (0.88, 1.43) 0.361 2.97 (2.13, 4.15) <0.001 1.04 (0.82, 1.32) 0.731 3.05 (2.32, 4.02) <0.001
Age, years
 12–15 ref ref ref ref
 16–18 or older 1.31 (1.12, 1.53) 0.001 1.34 (1.14, 1.58) 0.001 1.49 (1.30, 1.71) <0.001 1.26 (1.04, 1.52) 0.021
Race
 White only ref ref ref ref
 Black only 1.12 (0.88, 1.43) 0.359 0.55 (0.40, 0.76) <0.001 0.82 (0.64, 1.05) 0.120 0.45 (0.33, 0.61) <0.001
 Other races/>1 race 1.13 (0.89, 1.44) 0.300 0.90 (0.71, 1.14) 0.368 0.93 (0.77, 1.11) 0.406 0.71 (0.55, 0.91) 0.007
Past 12-month externalizing
 No ref ref ref ref
 Yes 1.20 (0.97, 1.49) 0.092 1.64 (1.39, 1.94) <0.001 1.18 (0.96, 1.45) 0.115 1.42 (1.15, 1.76) 0.001
Past 12-month internalizing
 No ref ref ref ref
 Yes 1.21 (1.00, 1.47) 0.045 1.09 (0.91, 1.30) 0.352 1.45 (1.27, 1.66) <0.001 1.75 (1.46, 2.10) <0.001
Past 12-month any bully
 None ref ref ref ref
 Any 0.87 0.210 1.11 0.370 1.08 0.316 1.29 0.010
(0.70, 1.08) (0.89, 1.38) (0.93, 1.27) (1.06, 1.56)
Current cigarette
 No ref ref ref ref
 Yes 1.92 (1.27, 2.90) 0.002 3.56 (2.22, 5.69) <0.001 1.97 (1.33, 2.93) 0.001 5.82 (3.93, 8.62) <0.001
Current other tobacco
 No ref ref ref ref
 Yes 3.20 <0.001 7.46 <0.001 1.95 0.018 2.89 <0.001
(2.28, 4.50) (5.09, 10.94) (1.12, 3.39) (1.61, 5.18)
Current alcohol
 No ref ref ref ref
 Yes 2.08 (1.71, 2.53) <0.001 4.73 (3.65, 6.15) <0.001 2.30 (1.94, 2.73) <0.001 7.37 (6.31, 8.62) <0.001
Current cannabis
 No ref ref ref ref
 Yes 3.15 (2.39, 4.15) <0.001 8.32 (6.08, 11.38) <0.001 3.43 (2.74, 4.30) <0.001 7.83 (5.86, 10.45) <0.001
Ever any illicit drug
 No ref ref ref ref
 Yes 2.13 (1.71, 2.65) <0.001 2.02 (1.60, 2.55) <0.001 1.95 (1.61, 2.37) <0.001 1.95 (1.57, 2.42) <0.001
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Note: Boldface indicates statistical significance (p<0.05).

a

Main effects and interaction effects are simultaneously tested in each model.

aRRR, adjusted RRR.

Among boys (Figure 1A), bisexual Hispanics reported the highest level of experimental use of E-cigarettes (46.1%), followed by gay non-Hispanic boys (32.8%). Among girls (Figure 1B), bisexual Hispanic girls reported the highest rate of experimental E-cigarette use (29.5%), followed by heterosexual Hispanic girls (29.2%). Among boys (Figure 1C), gay boys who were of other races/multiracial had the highest prevalence of experimental E-cigarette use (40.4%), followed by gay Black boys (38.9%). Among girls (Figure 1D), Black girls who reported being unsure in the sexual orientation question reported the highest rate of experimental E-cigarette use (36.2%), followed by bisexual White girls (29.4%).

Figure 1.

Figure 1.

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Weighted prevalence of E-cigarette use status by sexual orientation and race and ethnicity among U.S. adolescents, stratified by sex – A: by sexual orientation and ethnicity among boys; B: by sexual orientation and ethnicity among girls; C: by sexual orientation and race among boys; D: sexual orientation and race among girls.

Note: Asterisks indicate the statistical significance of aRRR (p<0.05).

aRRR, adjusted RRR.

Among non-Hispanic girls, bisexual non-Hispanic girls (versus heterosexual non-Hispanic girls) reported a 3.8% higher prevalence of experimental E-cigarette use. Among White girls, bisexual White girls (versus heterosexual White girls) reported a 3.9% higher prevalence of experimental E-cigarette use. Experimental-use prevalence was lower by 10.4% and 10.7% among boys reporting other racial identities and being unsure of their sexual orientation than among boys reporting other racial identities and being heterosexual, respectively (Appendix Table 2, available online).

After controlling for other covariates, there was no significant interaction effect between sexual orientation and ethnicity on current use of E-cigarettes (Table 2). However, a significant interaction effect was found between sexual orientation and race on current E-cigarette use among girls such that the RRR of current E-cigarette use compared with never use between lesbian Black girls and heterosexual Black girls was 6.99 times higher than the RRR between lesbian White girls and heterosexual White girls (adjusted RRR=6.99; 95% CI=2.21, 22.14). In addition, the RRR of current E-cigarette use compared with never use between lesbian girls who were of other races/multiracial and heterosexual girls who were of other races/multiracial was 3.60 times higher than the RRR between lesbian White girls and heterosexual White girls (adjusted RRR=3.60; 95% CI=1.06, 12.26) (Table 3).

Table 3.

Adjusted Results of Interaction Model on E-Cigarette Use Status by Sexual Orientation and Race, Stratified by Sex

Variables Boys
 Girls
Experiment
 Current
 Experiment
 Current
aRRR (95% CI) p-value aRRR (95% CI) p-value aRRR (95% CI) p-value aRRR (95% CI) p-value
Sexual orientation
 Heterosexual ref ref ref ref
 Gay or lesbian 1.08 (0.60, 1.92) 0.799 0.70 (0.32, 1.53) 0.369 0.68 (0.41, 1.13) 0.139 0.48 (0.24, 0.94) 0.032
 Bisexual 0.92 (0.58, 1.48) 0.743 0.41 (0.22, 0.77) 0.005 1.21 (0.93, 1.57) 0.164 0.80 (0.57, 1.11) 0.185
 Unsure 0.73 (0.43, 1.26) 0.256 0.51 (0.24, 1.08) 0.079 0.77 (0.51, 1.17) 0.223 0.54 (0.36, 0.81) 0.003
Race
 White only ref ref ref ref
 Black only 1.14 (0.89, 1.47) 0.305 0.57 (0.41, 0.80) 0.001 0.76 (0.57, 1.02) 0.071 0.37 (0.27, 0.53) <0.001
 Others 1.15 (0.90, 1.48) 0.265 0.91 (0.71, 1.16) 0.439 0.96 (0.78, 1.17) 0.666 0.70 (0.53, 0.92) 0.011
Sexual orientationa race
 Heterosexuala White only ref ref ref ref
 Gay/lesbian X Black 1.42 (0.45, 4.46) 0.542 0.84 (0.08, 8.75) 0.886 2.39 (0.98, 5.85) 0.055 6.99 (2.21, 22.14) 0.001
 Gay/lesbian X others 1.61 (0.47, 5.59) 0.447 0.98 (0.22, 4.40) 0.981 1.79 (0.57, 5.62) 0.313 3.60 (1.06, 12.26) 0.041
 Bisexual X Black 0.68 (0.23, 2.04) 0.492 2.06 (0.16, 26.66) 0.578 0.97 (0.50, 1.89) 0.924 1.30 (0.66, 2.53) 0.446
 Bisexual X others 0.91 (0.33, 2.55) 0.861 1.90 (0.61, 5.87) 0.264 0.81 (0.48, 1.38) 0.438 0.89 (0.40, 2.00) 0.782
 Unsure X Black 0.36 (0.04, 3.02) 0.345 0.10 (0.01, 1.39) 0.086 2.69 (0.91, 7.90) 0.072 2.98 (0.97, 9.09) 0.055
 Unsure X others 0.31 (0.07, 1.33) 0.144 0.28 (0.10, 0.76) 0.013 0.80 (0.39, 1.66) 0.552 1.28 (0.50, 3.30) 0.609
Survey year
 2015 ref ref ref ref
 2017 1.04 (0.81, 1.35) 0.734 0.56 (0.37, 0.85) 0.008 0.88 (0.70, 1.09) 0.237 0.28 (0.20, 0.38) <0.001
 2019 1.12 (0.88, 1.43) 0.355 2.97 (2.13, 4.13) <0.001 1.04 (0.83, 1.32) 0.710 3.07 (2.32, 4.06) <0.001
Age, years
 12–15 ref ref ref ref
 16–18 or older 1.31 (1.12, 1.53) 0.001 1.35 (1.14, 1.59) 0.001 1.49 (1.30, 1.70) <0.001 1.25 (1.03, 1.51) 0.023
Hispanic
 No ref ref ref ref
 Yes 1.28 (1.08, 1.53) 0.006 0.92 (0.76, 1.13) 0.434 1.24 (1.01, 1.52) 0.037 0.91 (0.69, 1.20) 0.507
Past 12-month externalizing
 No ref ref ref ref
 Yes 1.19 (0.96, 1.48) 0.107 1.63 (1.38, 1.93) <0.001 1.18 (0.96, 1.45) 0.106 1.43 (1.16, 1.77) 0.001
Past 12-month internalizing
 No ref ref ref ref
 Yes 1.20 (1.00, 1.45) 0.051 1.08 (0.90, 1.29) 0.394 1.46 (1.28, 1.67) <0.001 1.78 (1.48, 2.13) <0.001
Past 12-month any bully
 None ref ref ref ref
 Any 0.87 (0.70, 1.09) 0.233 1.12 (0.90, 1.39) 0.316 1.08 (0.93, 1.27) 0.315 1.30 (1.07, 1.58) 0.008
Current cigarette
 No ref ref ref ref
 Yes 1.89 (1.25, 2.86) 0.003 3.55 (2.23, 5.66) <0.001 1.97 (1.33, 2.94) 0.001 5.88 (3.97, 8.72) <0.001
Current other tobacco
 No ref ref ref ref
 Yes 3.20 (2.26, 4.53) <0.001 7.55 (5.19, 10.99) <0.001 1.93 (1.11, 3.35) 0.021 2.83 (1.60, 4.99) <0.001
Current alcohol
 No ref ref ref ref
 Yes 2.10 (1.73, 2.54) <0.001 4.75 (3.67, 6.16) <0.001 2.29 (1.94, 2.71) <0.001 7.34 (6.27, 8.59) <0.001
Current cannabis
 No ref ref ref ref
 Yes 3.14 (2.38, 4.15) <0.001 8.34 (6.06, 11.49) <0.001 3.43 (2.73, 4.30) <0.001 7.84 (5.88, 10.44) <0.001
Ever any illicit drug
 No ref ref ref ref
 Yes 2.12 (1.70, 2.64) <0.001 2.01 (1.58, 2.55) <0.001 1.95 (1.61, 2.37) <0.001 1.94 (1.56, 2.40) <0.001
Open in a new tab

Note: Boldface indicates statistical significance (p<0.05).

Main effects and interaction effects are simultaneously tested in each model.

a

Main effects and interaction effects are simultaneously tested in each model.

aRRR, adjusted RRR.

Among boys (Figure 1A), heterosexual non-Hispanic boys had the highest prevalence of current E-cigarette use (16.6%), followed by heterosexual Hispanics (14.3%). Furthermore, heterosexual White boys showed the highest rate of current E-cigarette use (17.5%), followed by heterosexual boys who were of other races/multiracial (15.6%) (Figure 1C). These patterns, however, differed among girls. Among girls (Figure 1B), heterosexual non-Hispanic girls showed the highest rate of current E-cigarette use (14.7%), followed by Hispanic girls who reported unsure in sexual orientation question (14.4%). Lesbian Black girls reported the highest rate of current E-cigarette use (18.2%), followed by lesbian girls who were of other races/multiracial (17.9%) (Figure 1D).

Current E-cigarette use prevalence was lower by 7% among non-Hispanic bisexual boys and lower by 7.5% among non-Hispanic boys who were unsure of their sexual orientation than among non-Hispanic heterosexual boys. Similarly, current E-cigarette use prevalence was lower by 3.4% among non-Hispanic bisexual girls and lower by 4.9% among girls who were unsure of their sexual orientation than among non-Hispanic heterosexual girls. Current E-cigarette use prevalence was lower by 8% among bisexual White boys than among heterosexual White boys and was lower by 13.5% among Black boys who were unsure of their sexual orientation than among heterosexual Black boys. Current E-cigarette use prevalence was lower by 10.4% and 10.7% among boys reporting other racial identities and being unsure of their sexual orientation, respectively, than among boys reporting other racial identities and being heterosexual. Finally, current E-cigarette use prevalence was lower by 5.7% among gay/lesbian White girls, lower by 3.2% among bisexual White girls, and lower by 4.9% among White girls who were unsure of their sexual orientation than among heterosexual White girls (Appendix Table 2, available online).

DISCUSSION

The findings highlight the disparities in E-cigarette use among youth at the intersections of sex, sexual orientation, race, and ethnicity. The significant interaction effects between sexual orientation and race or ethnicity on E-cigarette use status were not found among boys. However, a significant interaction effect in girls between sexual orientation and race on current E-cigarette use was found but not between sexual orientation and ethnicity.

This may suggest that lesbian Black and other race/multiracial girls may be at increased risks of current E-cigarette use, whereas lesbian White girls had lower risks than their heterosexual counterparts of the same race. The reasons are still unclear; however, this might be driven by inequities in exposure to E-cigarette marketing at the intersection of sexual identity and race among females. Tan and colleagues found that young women aged 18–24 years who identified as bisexual and Black reported the highest level of exposure to E-cigarette advertising.38 Specifically, 61.5% of bisexual Black young women reported exposure to E-cigarette advertisements in the past 12 months compared with 39.0% of heterosexual White young women. Thus far, there are no studies that examined the differences in E-cigarette advertising among youth with intersectional identities on the basis of their sexual orientation and race. However, the complex patterns of E-cigarette use at the intersections of sexual orientation, sex, race, and ethnicity among youth remain understudied. Future research should examine the reasons for a higher prevalence of E-cigarette use among lesbian Black girls than among heterosexual Black girls to inform appropriate vaping prevention interventions. Furthermore, surveillance and monitoring of E-cigarette marketing that appeals to youth from traditionally marginalized groups are warranted.

Comparing absolute risk differences, the results suggest that bisexual girls—bisexual non-Hispanic girls (versus heterosexual non-Hispanic girls) and bisexual White girls (versus heterosexual White girls)—may be at-risk populations for E-cigarette use. Such patterns were not found in boys. A higher risk of substance use, E-cigarettes in this study, for bisexuals may be explained by double discriminations, possibly driven by pervasive biphobia.39,40 However, it is unclear which factors are driving sex-based differences in E-cigarette use disparities, and future studies should investigate the unique determinants of E-cigarette use among bisexual girls (versus boys) of diverse races and ethnicities.

Notably, this study found potential protective effects of identifying as a sexual minority on current E-cigarette use among non-Hispanic boys, non-Hispanic girls, White boys, Black boys, boys reporting other racial identities, and White girls. In addition, the magnitude of the protective effects tended to be larger among boys than among girls. In comparison, the authors noted that identifying as bisexual was associated with a higher prevalence of experimental E-cigarette use among non-Hispanic girls and White girls, and there were no protective effects of identifying as a sexual minority for this outcome. Given that experimentation with E-cigarettes is common during adolescence,41 there might be other more important factors related to E-cigarette experimentation, over and beyond sexual orientation. However, sexual orientation might play a stronger role in the continued use of E-cigarettes. The reasons for such discrepancies are still unclear; future studies should further examine the motivations of experimental versus current E-cigarette use behaviors by sexual orientation and race/ethnicity.

This study also observed other significant correlates for E-cigarette use: older adolescents, externalizing/internalizing tendencies, experience with being bullied, and current use of other substances. Because those factors are all well-known factors for youth E-cigarette use,2 having experiences of being bullied is noteworthy.14 Bullying victimization is more prevalent among sexual minority youth,42 which contributes to sexual minority stress.43,44 Accordingly to the Minority Stress Model,44 sexual minority youth may use tobacco products as a coping behavior for dealing with stress from violence and victimization. This might be related to externalizing and internalizing tendencies, which affect E-cigarette use behaviors.43

Limitations

These findings have several limitations. First, as a school-based survey, it does not represent all youth in the U.S., including home-schooled youth and those who have dropped out of school.31 Second, youth’s self-identity in terms of sexual orientation may be fluid in this age group. Self-reported sexual orientation may be subject to measurement error because youth may not be comfortable with identifying as a sexual minority in the context of a school-based survey. Third, the YRBS did not assess gender identity. Thus, whether gender identity was associated with E-cigarette use prevalence in this population was not assessed, although previous research indicates higher rates of vaping among transgender youth.29 Fourth, because of the small sample size and the need for parsimony of statistical models, American Indian or Alaska Native, Asian, and Native Hawaiian or Other Pacific Islander were categorized into other races. Therefore, whether there were differences in E-cigarette use at the intersection of sexual orientation and race among these groups was not able to be estimated. Future studies that oversample youth from these racial groups will be needed to examine the intersection of sexual orientation and individuals of these groups on E-cigarette use at a more granular level. Finally, future studies should consider different approaches (e.g., multiplicative approach; 3-way interactions, including sex, race/ethnicity, and sexual orientation).45,46

CONCLUSIONS

This study highlighted the complex patterns in E-cigarette use status at the intersections of sex, sexual identity, race, and ethnicity among U.S. youth. This study identified significant disparities in current E-cigarette use among sexual minority Black girls. Future studies should examine the potential underlying reasons for this difference such as targeted marketing by the E-cigarette industry as well as E-cigarette use norms and perceived risk of E-cigarettes among girls with intersectional identities, including race and sexual orientation. This understanding will inform culturally tailored vaping prevention interventions among youth populations who are at higher risk of E-cigarette use. For example, E-cigarette prevention campaigns tailored by sexual orientation, race, and ethnicity, similar to CDC’s Tips From Former Smokers,47 may be needed. Finally, surveillance and regulation of E-cigarette marketing potentially targeting sexual minority youth are warranted.

Supplementary Material

Appendix

Supplemental materials associated with this article can be found in the online version at https://doi.org/10.1016/j.amepre.2022.06.013.

ACKNOWLEDGMENTS

The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of NIH.

ASLT received funding from the National Cancer Institute and National Institute on Drug Abuse (R01CA237670, R21DA052421, and R01DA054236).

No financial disclosures were reported by the authors of this paper.

Footnotes

CREDIT AUTHOR STATEMENT

Juhan Lee: Conceptualization; Formal analysis; Investigation; Writing - original draft; Writing – review and editing. Andy S.L. Tan: Investigation; Supervision, Writing – review and editing.

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Supplementary Materials

Appendix
NIHMS2100400-supplement-Appendix.pdf (75.9KB, pdf)

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