Abstract
Background:
Gender diversity, encompassing gender identity beyond traditional binary frameworks, has been associated with substance use during adolescence. However, there is a paucity of studies that consider different dimensions of gender diversity. This study investigates associations between multiple dimensions of gender diversity and substance experimentation in early adolescents.
Methods:
Data from 10,092 adolescents aged 12–13 years from the Adolescent Brain Cognitive Development (ABCD) study were used to assess the relationship between gender diversity and substance experimentation. Gender diversity was measured using multiple dimensions, including identity (transgender), felt gender (congruence between gender identity and assigned sex), gender non-contentedness (dissatisfaction with one’s gender), gender expression (adherence to gender expression norms), and place on the gender spectrum (masculine to feminine). Substance use was evaluated using self-reported lifetime and new experimentation (past year) of alcohol, nicotine, and cannabis use. Logistic regression models adjusted for sociodemographic factors were analyzed.
Results:
More gender-diverse responses for felt gender, gender non-contentedness, gender expression, and gender spectrum were associated with higher odds of lifetime alcohol experimentation. More gender-diverse responses for gender identity and gender non-contentedness were associated with higher odds of new nicotine experimentation, and more gender-diverse responses for gender identity, felt gender, gender non-contentedness, and gender expression were associated with higher odds of lifetime and new cannabis experimentation.
Conclusion:
Gender diversity is differentially associated with new and lifetime substance experimentation in early adolescence. Different dimensions of gender diversity may be uniquely associated with substance use behaviors, highlighting the need for targeted interventions in gender-diverse adolescents.
Keywords: Gender, Transgender, Gender diverse, Substance use, Alcohol, Nicotine, Smoking, Marijuana, Cannabis, Adolescent
1. Introduction
Substance use is a prominent public health issue in the United States, with alcohol and nicotine use among the leading lifestyle-related causes of death in the United States (Woolf and Schoomaker, 2019). In adolescents, substance use poses a specific concern due to increased risk-taking behaviors and substance use initiation frequently occurring during this period of development (Feldstein Ewing et al., 2015). The Monitoring the Future study has documented the increased prevalence of adolescent substance use in recent years (Johnston et al., 2019). Factors associated with adolescent substance use are multifaceted and may include family dynamics, peer influence, and co-occurring mental health morbidities (Kaminer et al., 2007, Buu et al., 2009).
Gender identity has been identified as an important factor associated with substance use among adolescents (Fahey et al., 2023). For many, gender is a central aspect of one’s self-image and identity. Gender identity in individuals encompasses their internal feelings about their gender, how they express their gender, their level of contentment with their gender, and their self-described position on the gender spectrum, ranging from masculine to feminine (Potter et al., 2022). Gender identity that differs from the sex assigned at birth is often considered a form of gender diversity. Adolescence is a significant period of gender identity formation during which young people are influenced by social expectations and pubertal development (McHale et al., 2009). During this important developmental period, incongruence between an adolescent’s sex assigned at birth and gender identity can lead to poor gender contentedness and result in unhappiness and other negative emotional outcomes (Rawee et al., 2024). Poor gender contentedness and gender minority stressors, including prejudice and victimization, may increase the risk of substance use in gender-minority adolescents (Katz-Wise et al., 2021). Previous investigations suggest that substance use may serve as a coping mechanism in gender-diverse adolescents encountering these stressors (Lowry et al., 2020). Indeed, transgender and gender-diverse adolescents experience a high prevalence of substance use, including alcohol, nicotine, and cannabis (Fahey et al., 2023). In their investigation, Day et al. estimated that the prevalence of substance use was 2.5–4 times higher in transgender youth relative to their cisgender peers (Day et al., 2017). These findings highlight a disparity in adolescent substance use between gender-diverse and cisgender adolescents, as well as the importance of studies focusing on substance use among gender-diverse adolescents in the U.S.
There are currently a number of studies that assess substance use in gender-diverse adolescents in the literature (Andrzejewski et al., 2023, Arayasirikul et al., 2018, Buttazzoni et al., 2021, Coulter et al., 2018, De Pedro et al., 2017, Fish et al., 2021). However, these investigations often use binary or categorical dichotomizations of gender and are limited in their ability to describe diverse aspects of gender identity. Moreover, early adolescents may not identify as transgender but may identify with qualities that are gender-diverse. There is currently a paucity of studies that assess adolescent substance use using multidimensional measures of gender diversity that capture the nuances of an individual’s unique gender experience (Potter et al., 2022). This investigation aimed to assess the association between gender diversity and substance use in a demographically diverse national sample of early adolescents aged 12–13 years old in the United States using multidimensional gender measures. We hypothesized that higher gender diversity would be associated with higher odds of substance use in early adolescents.
2. Materials and methods
2.1. Study population
Data from the Adolescent Brain Cognitive Development (ABCD) study were used for this analysis. ABCD is a longitudinal cohort study following 11,875 adolescents across 21 United States research sites. For the present analysis, we utilized data from the 5.1 release of the ABCD data (Year 0 [2016–2018] to Year 3 [2019–2021]). Assent was obtained from each adolescent participant, along with consent from their caregivers. Institutional review board (IRB) approval was obtained from both the University of California, San Diego (UCSD) IRB and the local IRB at each participating research site. Additional study details, including further details on participant recruitment, have been described previously (Garavan et al., 2018). To assess the association between gender diversity at Year 3 and substance use behaviors at Year 3 of the ABCD study, we used a cross-sectional study design. Of the original 11,875 adolescents, we excluded 1766 that did not report gender identity data at Year 3 and an additional 17 without linked ABCD sampling weights based on the American Community Survey from the US Census (Heeringa and Berglund, 2020), leaving 10,092 eligible individuals. Differences between included and excluded adolescents are summarized in Supplemental Table A.
3. Measures
3.1. Independent variables
3.1.1. Gender diversity
Gender diversity measures based on those used in previous research (Potter et al., 2021, Reisner et al., 2015, Egan and Perry, 2001, Potter et al., 2022) were derived from youth’s self-reported responses to questions in the gender identity and sexual health component of the core ABCD study. See Supplemental Table B for detailed definitions. For this study, we utilized two categorical measures (transgender identity, felt gender) and four ordinal/continuous measures (felt gender, gender non-contentedness, gender expression, and gender spectrum) to assess the association between gender and substance use. All categorical measures were coded based on increasing gender diversity (i.e., the adolescent’s gender identity and feelings of gender differ from their sex assigned at birth), and all ordinal or continuous measures were coded with higher scores, indicating greater gender diversity. As the ABCD study did not add questions assessing gender spectrum until Year 3, we only utilized data from the Year 3 follow-up for this analysis.
3.1.2. Transgender identity
A categorical measure for adolescents’ transgender identity was created based on the “Are you transgender?” background item asked of all participating adolescents as part of the Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS-5) questionnaire (Kaufman and Birmaher, 2013). Adolescents’ responses (1=Yes, 2=Maybe, 3=No) were used as categories for the transgender identity measure. Responses of “I do not understand” and “Refuse to answer” were regarded as missing.
3.1.3. Felt gender
Felt gender, or the congruence between gender identity and assigned sex was assessed as both a categorical measure and a continuous measure. The categorical measure was coded according to definitions provided by Potter et al., 2021 (refer to Supplemental Table C for details). To align directionality with higher scores indicating greater gender diversity, the continuous felt gender measure was created by taking the average of the reverse-coded scores for the questions “How much do you feel like a boy?” (re-defined as 1 = “Totally” to 5 = “Not at all” for those born as boys) and “How much do you feel like a girl?” (re-defined as 1 = “Not at all” to 5 = “Totally” for those born as boys) (Potter et al., 2021).
3.1.4. Gender non-contentedness
Gender non-contentedness, or the level of satisfaction with one’s gender was measured using an ordinal variable based on responses ranging from 1 (Always) to 5 (Never) to the question “How much have you had the wish to be a girl?” for adolescents assigned male at birth and vice versa for adolescents assigned female at birth (Potter et al., 2021). Responses were reverse-coded for directionality to create the gender non-contentedness measure.
3.1.5. Gender expression
Gender expression, or the adherence to the expression of gender norms was created as an ordinal measure based on the responses (from 1 = “Always” to 5 = “Never”) to the question “How much have you dressed or acted as a girl during play?” for adolescents assigned male at birth, and the analogous question for those assigned female at birth (Potter et al., 2021). Responses were reverse-coded for directionality to create the gender expression measure.
3.1.6. Gender spectrum
Gender spectrum, or the continuum of gender from masculine to feminine, was a continuous measure derived from responses to the questions, “How do you think other people would describe you?” and “How would you describe yourself?” The original responses for this measure (1 = “Very Masculine” to 7 = “Very Feminine” for boys at birth, and the opposite for girls at birth) were already such that a higher score indicated more gender diversity, and were directly averaged without reverse coding to provide the final measure used in this study.
3.2. Dependent variables
3.2.1. Substance use experimentation
Substance use experimentation measures low levels of substance use from the youth’s self-reported responses to questions found in the substance use component of the ABCD study. Adolescents were asked, “Have you ever tried ____ at any time in your life?” (at baseline) or “Since we last saw you, have you tried ___?” (at subsequent visits) for various substances. Alcohol experimentation utilized responses for “A sip of alcohol such as beer, wine or liquor (rum, vodka, gin, whiskey).” Nicotine experimentation was derived from responses for “A puff from a tobacco or electronic cigarette, or vape pens, or e-hookah.” Responses to “A puff or eaten any marijuana, also called pot, grass, weed or ganja?” were used to determine cannabis experimentation. Any substance experimentation was defined as “yes” if at least one of the substances was “yes.” Baseline to Year 3 responses provided by each adolescent regarding alcohol, nicotine, and cannabis use were converted into two binary measures: lifetime experimentation and new experimentation (Lisdahl et al., 2018, Lisdahl et al., 2021).
3.2.2. Lifetime experimentation
Yearly responses to this question for alcohol, nicotine, and cannabis were reviewed to create the lifetime experimentation measure for each substance. If an adolescent answered “yes” at any time point (Year 0–3), they were coded as having lifetime experimentation. If they never answered “yes,” they were coded as not having lifetime experimentation.
3.2.3. New experimentation
New experimentation was defined as low-level use (e.g., sip or puff) of the respective substance at the Year 3 follow-up visit with no history of experimentation in previous years. If the adolescent reported substance experimentation in any of the previous years, they were not considered to have new experimentation. Those reporting no substance experimentation at Year 3 were also coded as not having new experimentation.
3.3. Covariates of interest
Covariates of interest for this study included age (at Year 3), sex assigned at birth (male or female), race/ethnicity, parental education level, household income level, and research site location, based on previous research that these variables may be associated with both gender identity and substance use (Kaltiala et al., 2023, Zucker, 2017, Andrabi et al., 2017). All sociodemographic variables were collected from parental baseline surveys. We categorized race/ethnicity as White, Latino, Black, Asian, Native American, and Other; parental education as “high school or less” and “more than high school”; and household income as six categories ranging from an annual income of less than $25,000 to more than $200,000.
3.4. Statistical analyses
To improve the generalizability of our findings, all statistical analyses used propensity-weighted data that incorporated the ABCD sampling weights based on the American Community Survey from the US Census (Heeringa and Berglund, 2020). Statistical analyses were conducted using R version 4.4.0. Descriptive statistics (Table 1) were assessed using the survey package version 4.4–2 and the gtsummary package version 1.7.2. Logistic regression models were used to assess the associations between gender identity and substance use; models were fit using the survey package. All models were adjusted for age, sex assigned at birth, race/ethnicity, parental education level, household income level, and study site location.
Table 1.
Sociodemographic and gender characteristics of Adolescent Brain Cognitive Development (ABCD) Study participants (N = 10,092).
| Sociodemographic and gender characteristics | Mean (SD) / %a |
|---|---|
| Age at Year 3 (years) | 12.91 (0.97) |
| Sex (%) | |
| Male | 51.7 % |
| Female | 48.3 % |
| Race/ethnicity (%) | |
| White | 54.4 % |
| Latino | 19.9 % |
| Black | 15.6 % |
| Asian | 5.5 % |
| Native American | 3.1 % |
| Other | 1.4 % |
| Household income (%) | |
| Less than $25,000 | 16.3 % |
| $25,000 to <$50,000 | 20.0 % |
| $50,000 to <$75,000 | 17.9 % |
| $75,000 to <$100,000 | 14.0 % |
| $100,000 to <$200,000 | 24.2 % |
| $200,000 or higher | 7.7 % |
| Parents’ highest education (%) | |
| More than high school | 82.1 % |
| High school or less | 17.9 % |
| Felt gender groupb | |
| Cisgender/SCFG | 79.6 % |
| 1-STEP | 8.3 % |
| 2-STEP | 5.0 % |
| Minority group | 7.0 % |
| Are you transgender? | |
| No | 97.9 % |
| Maybe | 1.1 % |
| Yes | 1.0 % |
| Felt gender (mean score)c | 1.24 (0.60) |
| Gender non-contentednessc | 1.23 (0.63) |
| Gender expressionc | 1.36 (0.76) |
| Gender spectrum (mean score)d | 2.18 (1.18) |
ABCD Study sampling weights were applied based on the American Community Survey from the US Census
Categories represent increasing gender diverse identities based on questions of adolescents’ felt gender. In increasing order, categories are cisgender/SCFG, 1-STEP, 2-STEP, and minority group from Potter et al. (2021); SCFG = sex congruent felt gender
Scored from 1 (gender conforming) to 5 (gender diverse)
Scored from 1 (gender conforming) to 7 (gender diverse)
4. Results
4.1. Sociodemographic characteristics and gender diversity
Table 1 displays the weighted sociodemographic characteristics and gender measures for our sample of 10,092 adolescents (Mage = 12.91, SDage = 0.97), of which 48.3 % were assigned female at birth and 45.6 % were racial/ethnic minorities. Gender-diverse responses were rare for all measures of gender that were used for this study. Specifically, only 1 % of adolescents identified as transgender, and an additional 1.1% responded with ‘Maybe’ to the transgender identity question. Approximately 7 % of adolescents were classified as the minority group for diverse feelings of gender (see Table 1). Table 2 shows the proportions of adolescents engaging in substance use (lifetime experimentation and new experimentation reported at the Year 3 visit) overall and within each of the gender categories. In general, more gender-diverse adolescents reported higher lifetime substance use experimentation and new experimentation at Year 3.
Table 2.
Proportion of Adolescent Brain Cognitive Development (ABCD) Study participants within each gender category who have experimented (lifetime and new experimentation at Year 3) with each type of substance use.a
| Total sample | “Are you transgender?” | Felt gender categoriesb | ||||||
|---|---|---|---|---|---|---|---|---|
| Substance use characteristics | % | % | % | % | % | % | % | % |
| Substance use (lifetime experimentation) | ||||||||
| Alcohol | 15.3 % | 15.2 % | 24.8 % | 29.0 % | 14.6 % | 18.2 % | 18.8 % | 17.4 % |
| Nicotine | 2.8 % | 2.8 % | 1.1 % | 7.4 % | 2.7 % | 2.5 % | 3.5 % | 3.9 % |
| Cannabis | 2.0 % | 1.9 % | (−) | 9.1 % | 1.7 % | 1.5 % | 2.3 % | 5.3 % |
| Any substance | 28.2 % | 27.9 % | 38.7 % | 40.9 % | 26.9 % | 32.5 % | 36.2 % | 31.5 % |
| Substance use (new experimentation at Year 3) | ||||||||
| Alcohol | 4.7 % | 4.7 % | 4.9 % | 6.0 % | 4.1 % | 8.0 % | 7.3 % | 5.2 % |
| Nicotine | 1.8 % | 1.8 % | (−) | 6.1 % | 1.7 % | 1.8 % | 2.7 % | 2.5 % |
| Cannabis | 1.2 % | 1.2 % | (−) | 5.9 % | 1.1 % | 1.0 % | 1.9 % | 2.8 % |
| Any substance | 12.6 % | 12.5 % | 8.7 % | 19.3 % | 11.3 % | 18.0 % | 21.1 % | 14.5 % |
ABCD Study sampling weights were applied based on the American Community Survey from the US Census; (−) indicates no data available for the subgroup.
Categories represent increasing gender diverse identities based on questions of adolescents’ felt gender. In increasing order, categories are cisgender/SCFG, 1-STEP, 2-STEP, and minority group from Potter et al. (2021); SCFG = sex congruent felt gender
4.2. Lifetime experimentation
Across all gender measures, gender-diverse responses were significantly associated with higher odds of lifetime experimentation with alcohol after adjusting for covariates (Table 3). Adolescents who answered “Yes” to being transgender had a 2.13 (95 % CI 1.10–4.14) higher odds of lifetime experimentation with alcohol, compared to peers who answered “No.” This was again seen with felt gender, where more diverse felt gender groups were associated with roughly 56–65 % higher odds of lifetime alcohol experimentation compared with the sex congruent felt gender group. There were also associations for the continuous/ordinal measures of felt gender (AOR 1.28, 95 % CI 1.13–1.46), gender non-contentedness (AOR 1.31, 95 % CI 1.16–1.47), gender expression (AOR 1.52, 95 % CI 1.37–1.68), and gender spectrum (AOR 1.27, 95 % CI 1.14–1.42) and lifetime alcohol experimentation.
Table 3.
Associations between gender diversity and substance use (lifetime experimentation) in Year 3 of the Adolescent Brain Cognitive Development (ABCD) Study (N = 10,092).
| Alcohol | Nicotine | Cannabis | Any substance | |
|---|---|---|---|---|
| Gender Diversity Measure | AOR (95 % CI) | AOR (95 % CI) | AOR (95 % CI) | AOR (95 % CI) |
| Felt gender groupa | ||||
| Cisgender/SCFG (reference) | ||||
| 1-STEP | 1.56 (1.18, 2.06) | 0.87 (0.45, 1.71) | 0.82 (0.30, 2.27) | 1.46 (1.09, 1.97) |
| 2-STEP | 1.65 (1.16, 2.34) | 0.93 (0.42, 2.06) | 1.23 (0.45, 3.40) | 1.58 (1.08, 2.31) |
| Minority group | 1.60 (1.16, 2.22) | 1.38 (0.77, 2.47) | 2.77 (1.36, 5.65) | 1.59 (1.13, 2.23) |
| Are you transgender?a | ||||
| No (reference) | ||||
| Maybe | 2.02 (1.00, 4.11) | 0.30 (0.04, 2.47) | (−) | 1.78 (0.80, 3.98) |
| Yes | 2.13 (1.10, 4.14) | 2.83 (1.05, 7.61) | 6.41 (2.00, 20.55) | 1.67 (0.83, 3.38) |
| Felt gender (mean score)b | 1.28 (1.13, 1.46) | 1.22 (0.95, 1.57) | 1.67 (1.27, 2.20) | 1.25 (1.09, 1.44) |
| Gender non-contentednessb | 1.31 (1.16, 1.47) | 1.19 (0.96, 1.48) | 1.45 (1.12, 1.88) | 1.30 (1.14, 1.49) |
| Gender expressionb | 1.52 (1.37, 1.68) | 1.21 (0.98, 1.48) | 1.71 (1.33, 2.19) | 1.46 (1.31, 1.64) |
| Gender spectrum (mean score)c | 1.27 (1.14, 1.42) | 1.10 (0.87, 1.40) | 0.99 (0.69, 1.41) | 1.18 (1.04, 1.33) |
ABCD Study sampling weights were applied based on the American Community Survey from the US Census; bold indicates p < 0.05; (−) indicates insufficient data for the subgroup
Categories represent increasing gender diverse identities based on questions of adolescents’ felt gender. In increasing order, categories are cisgender/SCFG, 1-STEP, 2-STEP, and minority group. SCFG = sex congruent felt gender (Potter et al., 2021). AOR > 1 indicates higher odds of substance use outcomes.
Scores rated on a scale from 1 (most gender conforming) to 5 (most gender diverse); AOR > 1 indicates higher odds of substance use outcomes in gender diverse individuals.
Scores rated on a scale from 1 (most gender conforming) to 7 (most gender diverse); AOR > 1 indicates higher odds of substance use outcomes in gender diverse individuals.
There were less consistent associations between gender diversity and lifetime experimentation with both nicotine and cannabis (Table 3). For example, higher gender-diverse responses for felt gender (OR 1.67, CI 1.27–2.20), gender non-contentedness (OR 1.45, CI 1.12–1.88), and gender expression (OR 1.71, CI 1.33–2.19) were associated with lifetime cannabis experimentation, but none were associated with lifetime nicotine experimentation. Transgender identity was associated with significant odds ratios for lifetime nicotine and cannabis experimentation, though very few adolescents reported both being a gender minority within this measure (“Maybe” or “Yes”) and experimenting with these substances.
4.3. New experimentation
Gender-diverse responses were also associated with higher odds of new experimentation with some substance use at Year 3 (Table 4). As with lifetime experimentation, the most significant associations were for alcohol and any substance, followed by cannabis and nicotine. For example, after adjusting for covariates, more gender-diverse felt gender groups were associated with a 2.12 (95 % CI 1.22–3.70) to 2.28 (95 % CI 1.47–3.54) times the odds of new alcohol experimentation, with similar associations across felt gender, gender expression, and gender spectrum measures. For new experimentation of any substance, more diverse felt gender groups were generally associated with higher odds of new experimentation compared to the cisgender/sex congruent felt gender group. Likewise, higher gender diversity in the felt gender (AOR 1.22, 95 % CI 1.03–1.45) and gender expression (AOR 1.34, 95 % CI 1.15–1.55) measures were associated with higher odds of new experimentation with any substance.
Table 4.
Associations between gender diversity and substance use (new experimentation) in Year 3 of the Adolescent Brain Cognitive Development (ABCD) Study (N = 10,092).
| Alcohol | Nicotine | Cannabis | Any substance | |
|---|---|---|---|---|
| Gender Diversity Measure | AOR (95 % CI) | AOR (95 % CI) | AOR (95 % CI) | AOR (95 % CI) |
| Felt gender groupa | ||||
| Cisgender/SCFG (reference) | ||||
| 1-STEP | 2.28 (1.47, 3.54) | 1.03 (0.47, 2.23) | 1.01 (0.28, 3.62) | 1.87 (1.24, 2.80) |
| 2-STEP | 2.12 (1.22, 3.70) | 0.99 (0.38, 2.58) | 2.06 (0.69, 6.18) | 1.95 (1.17, 3.23) |
| Minority group | 1.26 (0.72, 2.21) | 1.30 (0.63, 2.69) | 2.30 (0.93, 5.70) | 1.29 (0.81, 2.05) |
| Are you transgender?a | ||||
| No (reference) | ||||
| Maybe | 0.99 (0.32, 3.12) | (−) | (−) | 0.56 (0.17, 1.81) |
| Yes | 0.83 (0.18, 3.79) | 3.37 (1.04, 10.92) | 5.85 (1.40, 24.36) | 1.37 (0.52, 3.59) |
| Felt gender (mean score)b | 1.25 (1.03, 1.51) | 1.17 (0.85, 1.61) | 1.59 (1.15, 2.22) | 1.22 (1.03, 1.45) |
| Gender non-contentednessb | 1.06 (0.86, 1.31) | 1.30 (1.02, 1.66) | 1.55 (1.17, 2.04) | 1.18 (1.00, 1.40) |
| Gender expressionb | 1.27 (1.08, 1.50) | 1.21 (0.95, 1.55) | 1.91 (1.45, 2.53) | 1.34 (1.15, 1.55) |
| Gender spectrum (mean score)c | 1.23 (1.04, 1.46) | 0.98 (0.75, 1.28) | 0.83 (0.54, 1.26) | 1.07 (0.91, 1.27) |
ABCD Study sampling weights were applied based on the American Community Survey from the US Census; bold indicates p < 0.05; (−) indicates insufficient data for the subgroup
Categories represent increasing gender diverse identities based on questions of adolescents’ felt gender. In increasing order, categories are cisgender, 1-STEP, 2-STEP, and minority group. SCFG = sex congruent felt gender (Potter et al., 2021). AOR > 1 indicates higher odds of substance use outcomes.
Scores rated on a scale from 1 (most gender conforming) to 5 (most gender diverse); AOR > 1 indicates higher odds of substance use outcomes in gender diverse individuals.
Scores rated on a scale from 1 (most gender conforming) to 7 (most gender diverse); AOR > 1 indicates higher odds of substance use outcomes in gender diverse individuals.
Similar to lifetime experimentation, being gender-diverse was associated with higher odds of new experimentation of both cannabis and nicotine across several domains but less consistently across the gender measures we examined (Table 4). Specifically, adolescents who provided more gender-diverse responses for gender non-contentedness had higher odds of both nicotine (AOR 1.30, 95 % CI 1.02–1.66) and cannabis (AOR 1.55, 95 % CI 1.17–2.04) new experimentation, and gender diverse responses for the continuous felt gender measure was associated with a 59 % higher odds of new cannabis experimentation.
5. Discussion
Our analysis of a diverse group of adolescents aged 12–13 years old found nuanced differences in the associations among gender diversity across several measures and substance experimentation, which differed by substance (alcohol, nicotine, cannabis) and by lifetime versus new experimentation. Higher gender diversity scores across all ordinal or continuous gender measures were associated with higher odds of lifetime alcohol experimentation. More diverse responses in gender identity felt gender, gender non-contentedness, and gender expression were associated with greater odds of new and lifetime experimentation of cannabis. Additionally, higher gender diversity measured by felt gender group was associated with higher odds of new and lifetime experimentation of alcohol, as well as higher odds of lifetime experimentation of cannabis. These results suggest that different dimensions of gender diversity may contribute to unique patterns of substance use experimentation in adolescents.
We used multidimensional measurements of gender experience to assess associations with substance use. No studies to our knowledge assess the relationship between gender diversity across multiple measures and substance use experimentation in early adolescence (Potter et al., 2022, Reisner et al., 2014). While we observed no association between identification as transgender and new alcohol experimentation, significant positive associations with new alcohol experimentation were found using three multidimensional measures of gender diversity. Adolescents may respond differently to indirect questions (such as those comprising felt gender, gender expression, and gender spectrum) compared to direct questions (such as “Are you transgender?”) (Potter et al., 2021). An individual with a response of “No” to being transgender may have responses to felt gender, gender expression, gender non-contentedness, and gender spectrum questions indicating gender diverse characteristics. It is possible that adolescents may not fully understand what is being asked during direct questioning or may be biased in responding to direct questioning in a way that is more socially conforming (Latkin et al., 2017). Future investigations should continue to implement multidimensional definitions of gender to more accurately elucidate relationships between gender diversity and substance use outcomes.
Gender-diverse adolescents have significantly higher odds of substance use compared to their cisgender peers. This finding is mostly in line with the results of previous investigations assessing the association between diverse gender identity and substance use (De Pedro et al., 2017, Fish et al., 2021). Gender-diverse adolescents experience unique minority stressors associated with poor health outcomes (Hunter et al., 2021). These stressors often include violence, victimization, harassment, stigma, and gender dysphoria, which increase the likelihood of substance use (Lowry et al., 2020, Watson et al., 2019, Connolly and Gilchrist, 2020, Coulter et al., 2018, Goldbach et al., 2014). Similarly, we found that higher felt gender scores were generally associated with higher odds of lifetime and new experimentation with alcohol and cannabis, possibly due to higher feelings of dysphoria (Connolly and Gilchrist, 2020). These findings are of particular concern as substance use initiation during adolescence can have long-term impacts and increase the risk of substance use disorder and overdose death through adolescence and adulthood (Quinn et al., 2020, Zhang et al., 2021, Boer et al., 2024). Additionally, more diverse responses for gender expression were positively associated with alcohol and cannabis for new and lifetime experimentation. One possible explanation is that adolescents who are more outwardly expressive of their gender diverseness experience greater discrimination and victimization from their peers in contrast to adolescents who internally question their gender identity but do not outwardly express it. This discrimination and victimization may lead to substance use as a mechanism to cope with and manage emotions. Interventions targeting social acceptance of diverse gender expression may, therefore, play a role in reducing substance use in gender-diverse adolescents. School-based programs aimed at fostering a more inclusive environment could play a role in reducing stigma and victimization (Russell et al., 2021). Additionally, anti-bullying policies protecting gender-diverse students may mitigate some of the stressors contributing to substance use (Watson et al., 2021). Future investigations should continue to investigate effective interventions aimed at reducing stigma directed toward gender-diverse adolescents.
Nicotine was the only substance not associated with multiple domains of gender diversity, with only higher odds of new experimentation seen with gender non-contentedness, in contrast to alcohol and cannabis. The differential effects of gender diversity on the use of substances like alcohol, nicotine, and cannabis could be attributed to several factors. First, alcohol and cannabis may be more socially accepted among adolescents, potentially making it a more common substance for lifetime experimentation and new experimentation, especially in social settings where gender-diverse youth might feel pressure to conform or seek acceptance (Latimer and Zur, 2010, Friedman et al., 2018). In contrast, tobacco use may be less socially driven and more closely associated with coping mechanisms for stress or anxiety, which may be more prevalent for adolescents reporting higher diversity in felt gender and gender expression (Holliday and Gould, 2016). Furthermore, school-based prevention and media campaigns surrounding nicotine, especially tobacco and cigarettes, may be more prevalent than campaigns for alcohol and cannabis (Das et al., 2016). Alcohol and cannabis may not carry the same immediate health risk stigma of nicotine and tobacco products among adolescents, making alcohol and cannabis a preferred choice for those seeking to cope with gender-related challenges (Friedman et al., 2018).
Our investigation has several limitations and strengths. First, due to the young age of the study participants, certain gender identity groups and substance use groups might have few observations, limiting the strength of analyses for those subgroups. Additionally, recall bias and outcome misclassification is a possibility, given the stigma associated with substance use among adolescents. We also do not have data on substance use for religious purposes in the same timeframe as our substance experimentation data, so we are unable to adjust our analyses for substance use as part of a religious practice, which may bias our results. Nevertheless, our investigation has several notable strengths. First, we are one of few investigations using a diverse and current dataset assessing a representative sample of adolescents in the U.S. Second, we use multidimensional (continuous and ordinal) gender measures that may capture nuances in individual experiences of gender and may be differentially associated with different patterns of substance use.
6. Conclusion
This investigation demonstrates several associations involving different dimensions of gender with substance use in adolescents, including alcohol, cannabis, and nicotine. Notably, there were associations with these continuous and ordinal gender measures that did not exist with conventional gender measurements such as transgender identity. Future investigations should investigate how these different dimensions of gender contribute to substance use in gender-diverse adolescents with interventions focused on these specific mechanisms.
Supplementary Material
Highlights.
Gender diversity was measured across multiple dimensions.
Substance use included alcohol, nicotine, and cannabis experimentation.
Different dimensions of gender may influence different aspects of substance use.
Acknowledgments
J.M.N. was funded by the National Institutes of Health (K08HL159350 and R01MH135492) and the Doris Duke Charitable Foundation (2022056). The ABCD Study was supported by the National Institutes of Health and additional federal partners under award numbers U01DA041022, U01DA041025, U01DA041028, U01DA041048, U01DA041089, U01DA041093, U01DA041106, U01DA041117, U01DA041120, U01DA041134, U01DA041148, U01DA041156, U01DA041174, U24DA041123, and U24DA041147. A full list of supporters is available at https://abcdstudy.org/federal-partners/. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/principal-investigators.html. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in the analysis or writing of this report.
Abbreviations
- ABCD
Adolescent Brain Cognitive Development study
- KSADS-5
Kiddie Schedule for Affective Disorders and Schizophrenia questionnaire
Footnotes
CRediT authorship contribution statement
Jason M. Nagata: Writing – review & editing, Formal analysis, Data curation. Iris Y. Shao: Writing – review & editing, Writing – original draft, Formal analysis, Conceptualization. Christopher D. Otmar: Writing – review & editing. Kyle T. Ganson: Writing – review & editing. Patrick Low: Writing – review & editing, Writing – original draft. Shirley Sui: Writing – review & editing, Writing – original draft, Formal analysis. Jinbo He: Writing – review & editing. Fiona C. Baker: Writing – review & editing, Data curation. Alexander Testa: Writing – review & editing. Glenn-Milo Santos: Writing – review & editing.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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