Abstract
Introduction
The relationship between discrimination and substance use has been a growing area of concern among marginalized populations facing intersecting systems of discrimination and oppression. 1 Discrimination, whether based on race or sexual orientation or gender identity (SOGI), can increase vulnerability to substance use disorders by exacerbating stress, trauma, and other mental health issues. 2 In the United States (US), the prevalence of substance use has risen significantly in recent decades, with patterns reflecting broader social and political changes. For example, shifts in opioid prescribing practices in the 1990s, the legalization, decriminalization, and politicization of cannabis in many states, and evolving attitudes toward other substances have contributed to increasing rates of use across different demographics. 3,4
Current estimates suggest that approximately 70.5 million (25%) adults in the US used illicit drugs in the past year, with higher rates observed in marginalized groups. 5 Transgender women of color (TWOC), in particular, experience elevated rates of substance use. For example, 2019–2020 National HIV Behavior Surveillance data show that 59% of transgender women in 7 US cities reported substance use within the past year, with substances such as marijuana (∼53%), cocaine (∼21%), and methamphetamine (∼18%) being most common. 6 Comparatively, data from the 2020 National Survey on Drug Use and Health show that 19.8% of cisgender women reported substance use in the past year, with estimates for marijuana, cocaine, and methamphetamine use at 16%, 1.3%, and 0.9%, respectively. 7 This disparity highlights the critical need to understand the social determinants influencing substance use patterns among TWOC.
Policy changes in the US have also played a role in shaping substance use trends, particularly among vulnerable communities. The decriminalization of cannabis in many states, while reducing the burden of criminalization for some, may increase access and normalization of use, 8 potentially influencing substance use behaviors among those experiencing discrimination. Conversely, punitive policies targeting drug offenses can exacerbate inequities, disproportionately affecting racial and gender minorities. Recent research suggests that while cannabis decriminalization and legalization may reduce overall arrest rates across racial groups, these policies do not eliminate (and may even widen) relative racial disparities in arrests, particularly among Black youth and adults. 9 This complex interplay between policy, discrimination, and substance use necessitates a nuanced understanding of how systemic factors contribute to substance use disparities.
In dense urban settings like New York City, systemic factors such as housing instability, policing practices, and health care access disparities contribute to the increased vulnerability of TWOC to substance use. For instance, the aggressive enforcement of “quality-of-life” policing tactics, such as stop-and-frisk practices, has historically targeted marginalized groups, including racial and gender minorities. 10 TWOC are particularly at risk for such negative encounters due to intersecting stigmatized identities and a reliance on sex work and other illegal/illicit forms of income due to exclusion from the formal economy. 11 Research shows that sexual and gender minority adults who have experienced police discrimination are more likely to report higher levels of substance use. 12
Studies show that experiences of discrimination can exacerbate stress and trauma among sexual and gender minorities, leading to increased substance use as a coping mechanism. 1,2,13 Transgender women who experience discrimination are more likely to report using substances such as methamphetamine, cocaine, and opioids, with particularly high prevalence rates among TWOC. 14 Furthermore, structural barriers, such as inadequate health care access and employment discrimination, can further compound vulnerability to substance use. 15 While suggestive, there are limitations in the extant literature on discrimination and substance use among transgender populations that limit generalizability and application. Many studies rely on cross-sectional data, limiting the ability to establish a temporal association between discrimination and substance use. 1 The lack of longitudinal data has also precluded the capture of changes in substance use behaviors over time and the impact of discrimination on these behaviors. Additionally, the literature often lacks nuanced examinations of how various types of discrimination (e.g., racial vs. gender identity-based) differentially affect substance use behaviors, potentially oversimplifying the complexity of these experiences 1 —in fact, most studies do not examine intersectional discrimination.
The objective of the current study was to examine cross-sectional and longitudinal associations between intersectional discrimination and substance use among TWOC in New York City. Ongoing anti-transgender discriminatory laws and policies in the US, which contribute to systemic transphobia and exacerbate health inequities for transgender individuals, highlight the urgency of this analysis. Recent years have seen a surge in anti-transgender legislation, including laws that restrict access to gender-affirming health care, gender-congruent bathrooms, and legal documents; prohibit participation in gender-appropriate sports; and allow for discrimination in public schools and institutions. 16 These laws not only reinforce societal stigma but also create environments where transgender individuals, particularly those of color, face heightened stress and anxiety. 17 Understanding the impact of these structural and interpersonal forms of discrimination on substance use behaviors is crucial for informing targeted interventions aimed at reducing substance use and promoting health equity within this population.
Methods
Study design and sample
Study population
Data came from the Trying to Understand Neighborhoods and Networks Among Transgender Women of Color (TURNNT) Cohort Study. 18–20 In total, 314 TWOC were enrolled in a 1-year prospective cohort study between August 2020 and November 2022. Eligible participants identified as TWOC, spoke English or Spanish, were between 18 and 55 years old at enrollment, and lived in the New York City metropolitan area. Participants were recruited through various channels, including social media, print advertising, event-based recruitment, referrals from organizational partners, and snowball sampling via referrals from enrolled participants. Each participant completed interviewer-administered surveys at baseline, 6 months, and 12 months, which assessed general health and well-being, socioeconomic characteristics, gender affirmation, social networks, neighborhood and housing characteristics, HIV prevention and care behaviors, sex work, substance use, sleep, mental health, discrimination and violence, and experiences with the COVID-19 pandemic. The study was approved by the Institutional Review Board at Columbia University Irving Medical Center (IRB-AAAS8164). Of the 314 enrolled participants, 293 were included in the analytic sample for the present study after excluding individuals with missing baseline discrimination data.
Measures
Discrimination
Discrimination was self-reported and measured at baseline using a modified version of the five-item Everyday Discrimination Scale (EDS). 21 This modified EDS captured experiences of perceived discrimination by asking participants, “In the past six months, how often have any of the following things happened to you: (1) You were treated with less courtesy or respect than other people, (2) You received poorer service than other people at restaurants or stores, (3) People acted as if they think you are not smart, (4) People acted as if they were afraid of you, and (5) You were threatened or harassed.” Responses were coded with values ranging from 1 to 4, with 1 representing “never,” 2 representing “a few times a month,” 3 representing “at least once a week,” and 4 representing “almost every day.” Response values were summed (range: 5–20) and categorized as low (EDS < 7), moderate (7 ≤ EDS < 10), or high (EDS ≥ 10) levels of discrimination based on a condensed five-level categorization of the EDS from previous work. 22 Internal consistency was high (Cronbach’s α = 0.87).
Substance use
We assessed substance use at baseline, 6-month, and 12-month follow-up. Three types of substance use were examined: recreational substance use, frequent alcohol use, and use of specific substances. At all time points, participants were asked: “Over the past 6 months, how frequently have you used drugs (other than alcohol) for recreational purposes?” Response options included: “daily or almost daily,” “a few times a week,” “a few times a month,” “once every few months,” “once or twice total,” and “never.” The same question and response options were used to assess alcohol use. Responses were recoded into binary indicators, with “never” coded as “no” and all other responses coded as “yes.”
At the 6- and 12-month follow-ups, participants also reported their use of specific substances including marijuana, opioids, prescription stimulants, cocaine, heroin, meth, lysergic acid diethylamide, phencyclidine, 3,4-methylenedioxymethamphetamine, gamma-hydroxybutyrate, and ketamine, with the following response options for each: (1) Yes, within the past 6 months; (2) Yes, but not within the past 6 months; or (3) No, never. Responses were recoded into binary indicators, with both (1) and (2) categorized as “yes” and (3) categorized as “no.” In this study, we focused on cannabis, cocaine, and methamphetamine use at the 6- and 12-month follow-ups, as these items were not assessed at baseline.
Covariates
Sociodemographic covariates included age (18–24; 25–34; 35–44; ≥45 years), education (high school graduate/GED; less than high school; more than high school), income (no income; $1–9,999; $10,000–29,999; $30,000–49,999; ≥$50,000; or missing), and sex work history (yes, no). A minimally adjusted model was used in the analyses to avoid overfitting, 19 given the relatively low prevalence of substance use in the sample.
Statistical analysis
Descriptive analyses were conducted to summarize the sociodemographic characteristics, experiences of discrimination, and substance use behaviors. To examine the relationship between baseline discrimination and substance use at baseline, 6 months, and 12 months, we used multivariable modified Poisson regression models to estimate adjusted prevalence ratios (aPRs). Longitudinal associations between intersectional discrimination and substance use were examined using generalized estimating equations (GEE) with a logit link and an autoregressive (AR1) working correlation structure; using GEE allowed us to account for clustering due to repeated measures on the same subjects and to estimate the adjusted effects of discrimination on substance use behaviors over time (adjusted odds ratios [aORs]). Additionally, using data from the 6-month follow-up (n = 199) and 12-month (n = 177) follow-ups, we examined the association between baseline discrimination and three specific types of substance (cannabis, cocaine, and methamphetamine) use via aPRs. All models were adjusted for age, education, income, and sex work. All statistical analyses were conducted using Stata 18 (StataCorp, College Station, TX), with statistical significance set at p < 0.05.
Results
Sample characteristics
Table 1 presents the sociodemographic characteristics, experiences of discrimination, and substance use patterns among the cohort (N = 293). The largest age group was 35–44 years (38.6%), followed by 25–34 (28.7%) and 18–24 (9.9%). Most participants had at least a high school education, with 28.3% completing high school or GED and 36.9% reporting more. Over half of the participants reported an annual income below $10,000 (56.7%), with 16.4% indicating no income. A majority (75.1%) reported engaging in sex work. Based on the EDS score, 25.3% reported high levels of discrimination. Recreational substance use was reported by 34.8% of participants at baseline, 19.1% at 6 months, and 22.6% at 12 months. Frequent alcohol use was reported by 27.0% of participants at baseline, 67.8% at 6 months, and 62.7% at 12 months.
Discrimination, Substance Use, and Sociodemographics of Transgender Women of Color, the Trying to Understand Neighborhoods and Networks Among Transgender Women of Color Cohort Study in New York City (N = 293) a
a N = 7 were excluded due to missing values in baseline Everyday Discrimination Scale score.
bThese data are drawn from 6-month follow-up data (n = 199).
cThese data are drawn from 12-month follow-up data (n = 177).
GED, General Educational Development; HS, high school.
Associations between discrimination and substance use
Table 2 presents the multivariable associations between baseline discrimination and substance use at baseline, 6 months, and 12 months. Compared to participants in the low discrimination group, those reporting moderate discrimination were more likely to report substance use at baseline (aPR = 1.75, 95% confidence interval [CI]: 1.11–2.77), 6 months (aPR = 1.86, 95% CI: 0.90–3.87), and 12 months (aPR = 3.14, 95% CI: 1.26–7.85). Participants in the high discrimination group also reported greater substance use at baseline (aPR = 1.77, 95% CI: 1.08–2.91) and 12 months (aPR = 3.06, 95% CI: 1.15–8.17), but not at 6 months (aPR = 1.00, 95% CI: 0.42–2.36). No significant associations were observed between discrimination and frequent alcohol use at any time point.
Multivariable Associations Between Baseline Discrimination and Substance Use, the Trying to Understand Neighborhoods and Networks Among Transgender Women of Color Cohort Study (N = 293) a
aMultivariable modified Poisson regression was used to estimate adjusted prevalence ratios (aPRs), adjusting for age, education, income, and sex work.
bThese data are drawn from 6-month follow-up data (n = 218).
cThese data are drawn from 12-month follow-up data (n = 193).
*p < 0.05.
aPR, adjusted prevalence ratio; CI, confidence interval.
Table 3 presents the longitudinal associations between baseline discrimination and substance use. After adjusting for study wave, age, education, income, and engagement in sex work, participants in the moderate discrimination group (aOR = 2.97, 95% CI: 1.54–5.72) and the high discrimination group (aOR = 2.39, 95% CI: 1.14–4.99) were more likely to report substance use over time compared to those in the low discrimination group. No significant association was observed between baseline discrimination and frequent alcohol use over time.
Longitudinal Associations (Generalized Estimating Equations) Between Baseline Discrimination and Recreational Substance Use, the Trying to Understand Neighborhoods and Networks Among Transgender Women of Color Cohort Study a
aGeneralized estimating equations with a logit link and an autoregressive (AR1) working correlation structure were used to estimate aORs, adjusted for study wave, age, education, income, and sex work.
*p < 0.05.
**p < 0.01.
aPR, adjusted prevalence ratio; CI, confidence interval.
Associations between discrimination and specific substance use outcomes
Results for specific substance use are presented in Tables 1 and 4. At the 6- and 12-month follow-ups, participants reported use of cannabis (14.1–20.9%), cocaine (12.1–13.6%), and methamphetamine (6.0–7.3%; Table 1). Multivariable analyses showed that moderate and high levels of baseline discrimination were significantly associated with increased use of cannabis at 12 months (aPR = 2.81 and 3.08, respectively) and cocaine use at 12 months (aPR = 9.13 and 11.16 for moderate and high vs. low, respectively), compared to those with low discrimination (Table 4). No significant associations were found between baseline discrimination and methamphetamine use.
aMultivariable modified Poisson regression was used to estimate adjusted prevalence ratios, adjusting for age, education, income, and sex work.
bSample sizes were n = 199 at 6-month follow-up and n = 177 at 12-month follow-up.
*p < 0.05.
NA, not available.
Discussion
This study found that experiences of discrimination were associated with increased substance use behaviors among TWOC. Notably, participants in the moderate and high discrimination groups were roughly threefold more likely to report recreational substance use over time compared to those in the low discrimination group. Additionally, baseline experiences of discrimination appeared to have increasing effects over time among our sample, aligning with previous literature identifying the role of discrimination as a chronic stressor that fosters conditions conducive to substance use. 1,14 Our findings suggest that TWOC facing discrimination, whether related to race or SOGI, are more likely to use substances, such as cannabis and cocaine, likely as a coping strategy to mitigate the psychological and physiological impacts of discrimination-related stressors. 1,14,23
The theoretical framework underlying the association between discrimination and substance use can be further explored through models of stress and coping. 24 The minority stress theory posits that marginalized groups face unique stressors, such as prejudice and stigmatization, that negatively impact mental health and elevate the risk of substance use as a maladaptive coping strategy. 25 Discrimination-induced stress often leads to hypervigilance, anxiety, and depressive symptoms, creating a context in which substances emerge as an easy way to alleviate these psychological burdens. 1
Our findings must also be contextualized within the broader current sociopolitical climate, where legislation and rhetoric targeting transgender communities have been increasing. In the United States, hundreds of bills have been introduced (with a marked increase beginning in 2021) that restrict access to gender-affirming care, bathroom facilities, school policies, and even drag performances. 26,27 These policies effectively aim to legalize and institutionalize forms of discrimination against transgender people 26,27 and reduce access to supportive health and social resources. The “Project 2025” policy blueprint, a US-based initiative published in 2023 by the Heritage Foundation, illustrates an emerging effort to dismantle legal recognition, health care access, and data collection for transgender populations, with potential to exacerbate health inequalities. 28 These developments reflect what Stanley (2021) 29 refers to as “atmospheres of violence” by legitimizing stigma and embedding it into law. For TWOC, this adverse environment can heighten experiences of everyday discrimination, limit access to supportive resources, and increase the stressors that can contribute to reliance on substances as a coping strategy, consistent with our results.
Discrimination’s role in perpetuating substance use also reflects a lack of access to protective resources such as supportive mental health services, educational opportunities, and community networks. TWOC often face systemic barriers to accessing these resources, and even when they are available, they may be culturally insensitive or stigmatizing, deterring utilization. 30 These findings also echo prior studies on the role of neighborhood safety and police violence in affecting mental health outcomes for communities of color, suggesting that addressing these structural inequities could reduce discrimination-related substance use. 20,31
Our findings highlight the importance of implementing policy reforms to address discrimination and its association with substance use. Policies that address structural determinants, such as neighborhood revitalization, equitable access to health care, and employment opportunities, could reduce exposure to discrimination and, by extension, reduce substance use among affected populations. Mental health policies that focus on culturally responsive care and trauma-informed approaches are also critical, as they offer avenues for individuals to process and cope with experiences of discrimination. 1 These should be coupled with substance use prevention and treatment programs tailored specifically to the experiences of marginalized communities. 24 A holistic approach to discrimination and substance use would involve multi-sectoral collaboration among policymakers, health care providers, community leaders, and mental health advocates, working together to create environments that reduce both discrimination and the need for maladaptive coping strategies. 1
Further research is needed to clarify causal mechanisms linking discrimination and substance use among TWOC. Longitudinal studies with longer follow-up periods could identify critical periods where discrimination may have the most significant impact on substance use behaviors, given our finding of a stronger effect of discrimination over time. 1 Ecological momentary assessment methods could be employed to capture real-time experiences of discrimination and substance use, 32 and biomarker data (e.g., cortisol, inflammatory markers) could provide objective measures of stress response to corroborate self-reported findings 33,34 and elucidate physiological pathways linking discrimination to substance use. Experimental research designs, such as natural experiments that examine policy changes in specific contexts, could help establish causal effects. Moreover, investigating how intersecting identities compound the effects of discrimination on substance use could yield nuanced insights, fostering interventions that are tailored to the complex realities of multiply marginalized populations such as TWOC.
Limitations
This study has several limitations. First, although we adjusted for age, education, income, and sex work engagement, unmeasured confounding may still be present. While most individual substances were not significantly associated with discrimination, this may be due to small sample sizes for specific drugs and should not necessarily be interpreted as evidence of no association. Additionally, self-reported measures of discrimination and substance use may introduce bias, as individuals may underreport sensitive information or fail to recall certain experiences. For example, recall bias, social desirability bias, and same-source bias as plausible. However, our use of validated scales that have been widely used in similar populations lends reliability to our findings. Last, the TURNNT cohort was sampled in a single US city using convenience sampling methods, including snowball sampling and recruitment from health clinics. 18 As such, external validity is limited, and results may not be generalizable. However, we note that the TURNNT cohort is one of the largest cohorts of TWOC; the research team prioritized internal validity and statistical power to create inferences.
Conclusion
This study provides evidence of the association between discrimination and substance use among TWOC, highlighting the urgent need for comprehensive strategies to address discrimination as a determinant of substance use, particularly as discriminatory policies targeting transgender people continue to be introduced, passed, and implemented in the United States.
Footnotes
Acknowledgments
The authors thank the Community Advisory Board members: Cristina Herrera of Translatinx Network, Ceyenne Doroshow of GLITS (Gay and Lesbian in a Transgender World), Kim Watson of Community Kinship Life, Kiara St. James of New York Transgender Advocacy Group, Bianey Garcia of Make the Road NY, Morticia Godiva of Black Trans Travel Fund, Xoai Pham of Transgender Law Center, Egyptt LaBeija of the House of LaBeija, and Nala Toussaint. They also thank Scientific Advisory Board members: Sari Reisner, ScD, of Harvard Medical School; Tonia Poteat, PhD, of the University of North Carolina, Chapel Hill; Rachel Bluebond-Langner, MD, of New York University School of Medicine; Robert Garofalo, MD, of Northwestern University; Walter Bockting, PhD, of Columbia University; and Jae Sevelius, PhD, of Columbia University. The authors additionally thank TURNNT study staff including Krish J. Bhatt, MPH; Jessica Contreras, BA; Roberta Scheinmann, MPH; Jenesis Merriman, MPH; Magdalena Palavecino, MPH; Laura Staeheli, MPH; Kobe Pereira, MPH; Mia N. Campbell, MHS; Elias Preciado, MPH; Astrea Villarroel-Sanchez; and Kevalyn Bharadwaj, MPH. They further thank the following colleagues for their thoughtful input on coding racial and ethnic categories for their data: Renee M. Johnson, PhD, MPH, of Johns Hopkins University; Paris “AJ” Adkins-Jackson, PhD, of Columbia University; Carlos Rodriguez-Diaz, PhD, of The George Washington University; as well as Howard Shih, MSE, and Ryan Vinh from AAPI Data. They also thank the participants for engaging in this research.
Authors’ Contributions
J.M.: Writing—original draft preparation, writing—review and editing, methodology, and project administration. S.H.P.: Methodology, formal analysis, and validation. M.O.S.: Writing—original draft preparation. A.M.W., A.A.M.L., J.K., S.L., and C.T.-S.: Writing—review and editing. A.F.: Methodology and validation. D.C., A.R., and K.W.: Investigation and writing—review and editing. D.T.D.: Funding acquisition, conceptualization, investigation, methodology, writing—review and editing, and supervision.
Author Disclosure Statement
The authors have no conflicts of interest to declare.
Funding Information
This work was funded through grants from the National Institute on Minority Health and Health Disparities (Grant Numbers: R01MD013554, 3R01MD013554-02S1, and 3R01MD013554-05S1; Principal Investigator: D.T.D., ScD). The work described herein is the sole responsibility of the authors and does not represent the official views of National Institutes of Health or its institutes.