Abstract
Transgender women of color (TWOC) are disproportionately impacted by psychological distress. Though gender-affirming care (GAC) has been recommended to alleviate this distress, research examining associations between perceived access to GAC, specific gender-affirming medical interventions (GAMIs), and mental health among TWOC in the United States remains limited. In this study, we examine cross-sectional and longitudinal associations between perceived access to GAC, completion of specific GAMIs, and psychological distress among TWOC, using modified Poisson regression and multilevel linear modeling. Data came from the Trying to Understand Relationships, Networks and Neighborhoods Among Transgender Women of Color (TURNNT) Cohort Study. In multivariable analyses, increased access to GAC was associated with reduced psychological distress risk. All assessed GAMIs suggested protective effects against psychological distress (aRR < 1), with statistical significance found for breast augmentation and facial feminization surgery. On average, those with unmet GAMI needs experienced higher distress risk than those without. Longitudinally, those experiencing reduced access to GAC over 6 months faced the highest distress risk among all trajectory groups (aRR: 1.40, 95% CI, 1.08-1.82). Our findings support the need for further inquiry in this area and suggest that policies protecting and increasing access to GAC may improve mental health among TWOC.
This article is part of a Special Collection on Methods in Social Epidemiology.
Keywords: access, gender-affirming care, psychological distress, mental health, transgender, transgender women of color, race
Introduction
Transgender (trans) people are disproportionately impacted by psychological distress.1-9 Findings from the US Transgender Survey (USTS) show that 44% of respondents reported experiencing serious psychological distress.10 This is almost 12 times the prevalence of serious psychological distress reported in the general population (3.7%).11 Trans women of color (TWOC) in particular experience some of the highest risks of psychological distress compared to both the general population and other sexual and gender minority groups.7
Among TWOC, these inequalities are rooted in overlapping systems of oppression that operate within broader sociopolitical contexts. Intersectionality theory provides a framework for understanding how homophobia, transphobia, sexism, racism, and misogyny converge to create unique and compounded vulnerabilities for TWOC, who simultaneously hold various identities targeted by these forces.12,13 In urban environments, these intersecting forces drive inequities like gentrification, poverty, housing and food instability, housing discrimination, and police violence, which can exacerbate psychological distress for TWOC. Ecosocial theory offers an explanation of how these social and environmental factors shape health outcomes among TWOC, suggesting that population health patterns are created by individuals’ biological embodiment of their unique lived experiences.14,15 This is consistent with the minority stress model, which posits that mental health disparities among sexual minority populations are driven by social stigma14,15 and has since been expanded for transgender populations.16,17 Gender dysphoria, or distress resulting from a mismatch between one’s assigned sex at birth and gender identity, also contributes to psychological distress among TWOC.5,18 Gender-affirming care (GAC) has been identified as a meaningful way to alleviate gender dysphoria, and through this pathway, may improve other mental health outcomes.5,19
The World Health Organization defines GAC as “social, psychological, behavioral or medical interventions designed to support and affirm an individual’s gender identity.”20 Though not all TWOC want or need to medically transition, GAC is critical for those who do.21 For many TWOC, this includes gender-affirming medical interventions (GAMIs) like hormone therapy, breast augmentation, orchiectomy, vaginoplasty, fillers, facial feminization surgery, and hair removal, each varying in cost, coverage, and risk.22 However, significant barriers exist in accessing such care. In the US, GAMIs are expensive and insurance coverage is inconsistent,23 with only about half of all states explicitly protecting GAMI coverage for private insurance (49.0%) and Medicaid (52.9%).24 The COVID-19 pandemic has reduced access to GAC around the world25 while unprecedented anti-transgender legislation has increasingly banned access across the country.26 Despite these challenges, research shows that when critical needs for gender affirmation remain unmet, TWOC may seek it in ways that place them at further risk, such as engaging in sex work or illicitly using dangerous fillers or silicone injections.16 Given this political and economic climate, disaggregated analyses could help identify the unique contributions of specific interventions to mental health outcomes, providing useful insights into cost-effective strategies to advance health justice for TWOC.
Though most studies investigating associations between GAMIs and mental health suggest that GAMIs may improve mental health outcomes, few of these studies focus on TWOC and various studies have found no, negative, or mixed associations.27,28 A recent systematic review by Swan et al. identified 53 studies exploring mental health and quality of life outcomes of gender-affirming surgery (GAS).28 Of these, 27 (51%) reported significant associations, and only 11 (20.7%) included transgender women in the US.28 For example, Tomita et al.27 examined associations between select GAMIs (hormone therapy, chest surgery, and genital surgery) and mental health outcomes and found largely nonsignificant results among transgender women. Nonsignificant findings on this topic are not uncommon and have been attributed to limitations like small sample sizes, retention issues, uncontrolled confounders, lack of control groups, and selection bias.27,29,30 Additionally, despite their unique vulnerabilities, even fewer of these studies have examined associations among TWOC specifically.28
Existing research has also been limited by study design and methodological challenges.8,31 Most existing analyses are cross-sectional while longitudinal associations remain underexplored.8,25 A 2024 systematic review of prospective studies exploring gender-affirming and mental health interventions identified only four studies in the United States. None focused on people of color and only one examined medical interventions, assessing hormone use among transgender men.32 Methodologically, experts underscore the importance of distinguishing between trans people who want GAMIs and those who do not during analysis to accurately assess the impact of these interventions, recognizing that not all trans people want the same GAMIs.8,27,31 Most studies have not made this distinction, which has been implicated in biased and inconsistent findings.8 More research is needed to address these methodological challenges and clarify associations among TWOC. The need for research studying the impact of GAC among trans-subpopulations is more urgent than ever, including the examination of specific GAMIs that may uniquely impact mental health for TWOC as more restrictive policies are enacted and enforced across the country.
Study objectives
Using data from the Trying to Understand Relationships, Networks, and Neighborhoods Among Transgender Women of Color (TURNNT) Study in New York City, the objectives of the current study were: (1) to examine associations between perceived access to GAC, completion of specific GAMIs, and psychological distress, (2) to investigate longitudinal trajectories of psychological distress with changes in perceived access to GAC over 12 months, and (3) to quantify associations between the completion of specific GAMIs and psychological distress at 6 months and 12 months based on an individual’s desire for each GAMI, using as a reference group those who expressed a desire for but had not yet received the respective GAMI.8
Methods
Study data
The TURNNT study was a one-year prospective longitudinal cohort study exploring health among TWOC in New York City. Study data was collected during the COVID-19 pandemic through quantitative surveys in English and Spanish, HIV testing, and GPS monitoring at baseline, 6-month follow-up (Wave 2), and 12-month follow-up (Wave 3).33,34 In total, 314 TWOC were enrolled and completed baseline visits between August 2020 and November 2022. Wave 2 data were collected from May 2021 to April 2023 (n = 219), and Wave 3 data were collected from November 2021 to December 2023 (n = 179).
Eligibility and recruitment
Study inclusion criteria were (1) identifying as a transgender woman of color, (2) being between 18 and 55 years old at enrollment, (3) living in New York City metropolitan area, and (4) speaking English or Spanish. Various recruitment strategies were used to recruit participants, including social media marketing, print advertising in community spaces, event-based recruiting, organizational referrals, and snowball sampling. Retention strategies included escalating financial incentives, 3-month check-ins, and a community newsletter for participants. Participants were eligible for $100 at baseline, $150 during Wave 2, and $250 during Wave 3.
Measures
All measures were self-reported by TURNNT participants. The full survey instrument was created and piloted prior to cohort recruitment with a sub-sample of TWOC in New York City. Participants completed the survey and a short semi-structured interview focused on comprehension, language, and overall experience. Results were used to refine the instrument. Variables on GAMIs and GAC were adapted from several other large surveys of trans health in close consultation with leaders from local communities of TWOC.33
Perceived access to gender-affirming care at baseline, 6 months, and 12 months
Perceived access to GAC was assessed using a single-item question at baseline, 6 months, and 12 months: “How would you rate your access to transgender-related health care? Please think about ‘access’ as your ability to attend these services based on their location, affordability, and so on.” There were five response options: (1) great; you can access whatever you need, (2) good; you can access most of what you need, (3) ok; you can access some of what you need, (4) poor; you mainly struggle to access what you need, and (5) nonexistent; no access. Nonexistent was re-coded as poor to maintain statistical power.
We also assessed COVID-19-related reductions in GAC access at baseline by asking participants how the pandemic affected their access to GAC, with response options (1) significantly decreased, (2) somewhat decreased, (3) no effect, (4) somewhat increased, and (5) significantly increased.
Changes in perceived access to gender-affirming care at baseline and 6 months
We derived a variable characterizing the longitudinal trajectories of participants’ access to GAC based on their responses at baseline and 6 months. Responses at both time points were dichotomized into (1) good access—if ranked as “great” or “good,” and (2) bad access—if ranked as “ok,” “poor,” or “nonexistent.” We then categorized participants’ responses into four longitudinal groups: (1) good-good, (2) good-bad, (3) bad-good, and (4) bad-bad, reflecting their level of access at baseline and 6 months.
Completed gender affirmation medical interventions at baseline, 6 months, and 12 months
Participants were asked to indicate whether they had completed the following GAMIs: hormone therapy, breast augmentation, injection of silicone or other fillers, vaginoplasty, facial feminization surgery, and orchiectomy. At baseline, there were three response options for each: (1) have had or done it, (2) want to have or do someday, (3) do not want. At 6 months and 12 months, there were four response options: (1) have had or done in the past 6 months, (2) want to have or do someday, (3) do not want, and (4) have had or done 6 or more months ago. We re-categorized the follow-up categories as follows: (1) have ever had it (2) do not want, and (3) want to have or do someday. Implausible responses (less than 5% of the data) were reclassified. For example, participants who indicated they had completed a particular GAMI at baseline but answered “do not want” at 6 months were reclassified to “have had or done 6 or more months ago” at 6 months.
Psychological distress
Psychological distress was measured using the 10-item Kessler Psychological Distress Scale (K10).35,36 Psychological distress was categorized as a binary variable for logistic regression using established thresholds from past studies (scores ≥20).34 We also described mild (scores: 20–24), moderate (scores: 25–29), and severe (scores: 30–50) distress.37 The Cronbach alpha of the scale in our sample was 0.90 across all time points.
Covariates
Sociodemographic covariates included age group (18–24, 25–34, 35-44, 45–55), education (high school graduate/GED, less, more), race/ethnicity (Black, Latina, unlisted), health insurance (no, yes), income (no income, <$10 000, $10000-29 999, ≥ $30000), sex work history (yes, no), incarceration history (yes, no), nativity (US-born, foreign-born), and HIV status (positive, negative, unknown). These variables were identified a priori as potential confounders across all studied associations, informed by prior research, directed acyclic graphs (DAGs), and previous analyses conducted using this data source.34
Statistical analysis
First, descriptive statistics were calculated for participants at all time points. Retention analysis using standardized differences (SD) was used to understand retention patterns, with SD < 0.10 indicating negligible differences between samples at study initiation and completion.38,39 Second, modified Poisson regression was used to obtain prevalence ratios (PRs) comparing different levels of perceived access to GAC with psychological distress, using “great” as the reference category.40,41 PRs for psychological distress were also calculated comparing those who had accessed GAMIs and those who had not, regardless of treatment desire. A sensitivity analysis was conducted by categorizing participant desire for each GAMI. Third, modified Poisson regression was used to estimate risk ratios (RR) for distress at 6 months and 12 months based on changes in perceived access to GAC from baseline to 6 months, with the good-good trajectory as the reference category.40,41 To understand longitudinal trajectories of psychological distress, distress scores at baseline, 6 months, and 12 months were plotted and stratified by baseline access to GAC. A multilevel linear model with a random intercept, which assumed individual-specific baseline distress values, was used to estimate changes in distress scores across levels of access to GAC, with “great” access serving as the reference group. Finally, modified Poisson regression was used to assess the association between desire for each GAMI and psychological distress at 6 months and 12 months. A sensitivity analysis was conducted excluding implausible responses regarding GAMI completion at 6 months and 12 months.
Covariates were treated as fixed effects in the multilevel model, considering only participants’ baseline characteristics. Longitudinal analyses were adjusted for distress at baseline. All analyses were conducted using R 4.3.2 and multilevel models were run using the lme4 package.42
Results
Descriptive results
Table 1 summarizes descriptive statistics for our sample. At baseline (n = 314), 68.6% were between the ages of 25 and 44 and 66.4% had completed high school. All participants identified as people of color: 46.0% were Latinx, 28.8% were Black, and 25.2% were unlisted. The unlisted category included multiracial, Asian, Middle Eastern/North African, Guyanese, Aboriginal, and Native participants. Over 90% reported having insurance coverage in the last 6 months. Most of the cohort had a low annual income, with 44% reporting less than $10 000. Around 75% reported a history of sex work and about half (50.2%) reported a history of incarceration. Over half (58.1%) were born in the United States and most were single (62.3%).
Table 1.
Socio-demographic characteristics, perceived access to gender-affirming care, gender-affirming medical intervention completion, and psychological distress of TURNNT cohort participants: baseline, 6 months, and 12 month comparisons, New York City, 2020-2023.
| Characteristics a | All participants at baseline (n = 314) | All participants at 6 months (n = 219) | All participants at 12 months (n = 179) | Standardized difference between baseline and 12 months b |
|---|---|---|---|---|
| Age | 0.174 | |||
| 18 to 24 | 32 (10.4%) | 22 (10.2%) | 13 (7.4%) | |
| 25 to 34 | 93 (30.1%) | 63 (29.2%) | 47 (26.7%) | |
| 35 to 44 | 119 (38.5%) | 79 (36.6%) | 68 (38.6%) | |
| 45 to 55 | 65 (21.0%) | 52 (24.1%) | 48 (27.3%) | |
| Unknown | 5 | 3 | 3 | |
| Race/Ethnicity | 0.125 | |||
| Black | 90 (28.8%) | 58 (26.5%) | 42 (23.5%) | |
| Latinx | 144 (46.0%) | 98 (44.7%) | 86 (48.0%) | |
| Unlisted | 79 (25.2%) | 63 (28.8%) | 51 (28.5%) | |
| Insurance coverage | 0.013 | |||
| No | 27 (8.6%) | 21 (9.6%) | 16 (8.9%) | |
| Yes, in the last 6 months | 286 (91.4%) | 198 (90.4%) | 163 (91.1%) | |
| Annual income | 0.135 | |||
| < $10 000 | 122 (44.2%) | 84 (43.5%) | 72 (44.7%) | |
| ≥ $30 000 | 34 (12.3%) | 27 (14.0%) | 25 (15.5%) | |
| $10 000 − $29 999 | 69 (25.0%) | 46 (23.8%) | 41 (25.5%) | |
| No income | 51 (18.5%) | 36 (18.7%) | 23 (14.3%) | |
| Unknown | 38 | 26 | 18 | |
| Sex work history | 235 (75.1%) | 164 (74.9%) | 136 (76.0%) | 0.017 |
| Education | 0.013 | |||
| High-school graduate/GED | 89 (28.4%) | 64 (29.2%) | 50 (27.9%) | |
| Less than high school | 105 (33.5%) | 72 (32.9%) | 60 (33.5%) | |
| More than high school | 119 (38.0%) | 83 (37.9%) | 69 (38.5%) | |
| Incarceration history | 157 (50.2%) | 106 (48.4%) | 89 (49.7%) | 0.009 |
| Nativity (US born) | 0.001 | |||
| No | 129 (41.2%) | 86 (39.4%) | 74 (41.6%) | |
| Yes | 182 (58.1%) | 132 (60.6%) | 104 (58.4%) | |
| Do not know | 3 | 1 | 1 | |
| HIV status | 0.011 | |||
| Negative | 145 (46.3%) | 102 (46.6%) | 82 (45.8%) | |
| Positive | 161 (51.4%) | 112 (51.1%) | 93 (52%) | |
| Do not know | 8 | 5 | 4 | |
| Relationship status | 0.092 | |||
| Single | 195 (62.3%) | 131 (59.8%) | 104 (58.1%) | |
| In a relationship | 113 (36.1%) | 84 (39.1%) | 73 (40.8%) | |
| Do not know | 6 | 4 | 2 | |
| Perceived access to gender-affirming care | 0.003 | |||
| Good or great | 227 (72.5%) | 158 (72%) | 130 (72.5%) | |
| Ok or poor | 86 (27.5%) | 61 (28%) | 49 (27.5%) | |
| Gender-affirming medical intervention | ||||
| Hormone therapy | 277 (89.6%) | 191 (88.4%) | 154 (87.5%) | 0.059 |
| Breast augmentation | 131 (44%) | 86 (41.5%) | 70 (40.7%) | 0.060 |
| Silicone or filler injection | 61 (20.2%) | 46 (21.8%) | 39 (22.4%) | 0.049 |
| Facial feminization surgery | 53 (17.7%) | 42 (19.9%) | 34 (22.4%) | 0.055 |
| Orchiectomy | 48 (17.1%) | 35 (17.9%) | 24 (15%) | 0.055 |
| Bottom surgery | 34 (12.3%) | 24 (12.5%) | 17 (10.9%) | 0.042 |
| Psychological distress | 191 (61%) | 140 (63.9%) | 118 (65.9%) | 0.097 |
Abbreviations: GED, General Education Development; HIV, Human Immunodeficiency Virus; US, United States of America; TURNNT; Trying to Understand Relationships, Networks and Neighborhoods Among Transgender Women of Color.
All characteristics presented are from baseline measures, including the frequencies for 6-month and 12-month follow-ups.
Standardized difference was calculated using the formula in Austin 2008. Standardized difference < 0.10 indicates negligible difference between 12 month and baseline data.
The range of psychological distress scores was 10 to 50, with a mean baseline score of 23.27. 61.1% of the cohort experienced psychological distress at baseline: 19.7% reported mild distress, 16.9% reported moderate distress, and 24.5% reported severe distress. 36.0% and 36.6% reported having “good” or “great” access to GAC at baseline, respectively, while 19.1% and 8.3% reported having “ok” or “poor” access at baseline, respectively. 53.2% reported decreased access to GAC due to COVID-19.
Retention analysis
Our retention rate was 69.7% at 6 months and 57.0% at 12 months. There were no major differences between participants at baseline and 12-month follow-up related to insurance coverage, sex work history, education, incarceration history, HIV status, relationship status, birthplace, and perceived access to GAC (SD < 0.10). There were some differences in age and income. Participants aged 45–55 were more likely to return at 12 months (SD = 0.174), while those without income were less likely to return at 12 months compared to other income groups (SD = 0.135) (Table 1).
Cross-sectional analysis
Table 2 shows results from our baseline analysis, revealing that, on average, psychological distress risk decreased as perceived access to GAC increased. For example, participants who reported “ok” access had 1.44 times the risk of distress compared to those who reported “great” access, and this association remained significant in the multivariable model (aPR: 1.44, 95% CI, 1.08–1.91).
Table 2.
Estimated prevalence ratios for associations between perceived access to gender-affirming care, completion of gender-affirming medical interventions, and psychological distress at baseline, TURNNT cohort study, New York City, 2020-2023.
| Prevalence ratio (95% CI—distress baseline)—unadjusted | Prevalence ratio (95% CI—distress baseline)—multivariablea | |
|---|---|---|
| Perceived access to gender-affirming care | ||
| Great (ref) | ||
| Good | 1.36 (1.08, 1.71) | 1.44 (1.14, 1.83) |
| Ok | 1.44 (1.12, 1.85) | 1.44 (1.08, 1.91) |
| Poor | 1.50 (1.11, 2.02) | 1.37 (0.95, 1.96) |
| Good & great vs ok & poor | 1.24 (1.04, 1.48) | 1.15 (0.93, 1.41) |
| Completed GAMIs | ||
| Hormone therapy | 0.82 (0.66, 1.03) | 0.83 (0.64, 1.08) |
| Breast augmentation | 0.82 (0.68, 0.99) | 0.77 (0.62, 0.94) |
| Silicone or filler injection | 0.93 (0.73, 1.17) | 0.86 (0.67, 1.11) |
| Facial feminization surgery | 0.81 (0.61, 1.07) | 0.70 (0.51, 0.95) |
| Orchiectomy | 0.72 (0.52, 0.99) | 0.78 (0.58, 1.06) |
| Bottom surgery | 0.85 (0.61, 1.19) | 0.82 (0.59, 1.14) |
| GAMI desire (ref: want it someday) Hormone therapyb | ||
| Have had it | NA | NA |
| Do not want | NA | NA |
| Breast augmentation | ||
| Have had it | 0.78 (0.64, 0.94) | 0.73 (0.59, 0.91) |
| Do not want | 0.72 (0.49, 1.05) | 0.73 (0.51, 1.04) |
| Silicone or filler injection | ||
| Have had it | 0.68 (0.52, 0.87) | 0.67 (0.49, 0.91) |
| Do not want | 0.66 (0.55, 0.79) | 0.75 (0.59, 0.95) |
| Facial feminization surgery | ||
| Have had it | 0.77 (0.58, 1.03) | 0.68 (0.49, 0.93) |
| Do not want | 0.84 (0.64, 1.11) | 0.87 (0.66, 1.16) |
| Orchiectomy | ||
| Have had it | 0.69 (0.49, 0.96) | 0.78 (0.57, 1.09) |
| Do not want | 0.88 (0.72, 1.07) | 0.94 (0.77, 1.16) |
| Bottom surgery | ||
| Have had it | 0.85 (0.60, 1.20) | 0.84 (0.59, 1.20) |
| Do not want | 0.92 (0.75, 1.14) | 0.95 (0.76, 1.18) |
Abbreviations: GAMI, Gender-Affirming Medical Intervention; TURNNT, Trying to Understand Relationships, Networks, and Neighborhoods Among Transgender Women of Color.
Adjusted for age group, race, insurance availability, income, sex work history, incarceration history, nativity (US born), and HIV status, as categorized in Table 1.
Too few people in the “do not want” category for hormone therapy (n=3) to meaningfully assess.
Examining specific GAMIs suggested that all interventions had protective effects against psychological distress risk, though statistical significance varied. Breast augmentation (aPR: 0.77, 95% CI, 0.62–0.94) and facial feminization surgery (aPR: 0.70, 95% CI, 0.51-0.95) were associated with significant reductions in psychological distress risk after adjusting for covariates. Results for hormone therapy, silicone or filler injections, orchiectomy, and bottom surgery were not statistically significant in multivariable models.
Our analysis by GAMI desire revealed that those with unmet needs for GAMIs experienced higher distress risk than those who had completed treatment (Table 2). The strongest association was observed for silicone or filler injection, where distress risk was reduced by about 33% for those who had it compared to those who had not but wanted to (aPR: 0.67, 95% CI, 0.49–0.91). Those who did not want fillers were also at reduced risk compared to those who wanted them but had not had them (aPR: 0.75, 95% CI, 0.59–0.95). Similarly, those who completed breast augmentation (aPR: 0.73, 95% CI, 0.59–0.91) and facial feminization surgery (aPR: 0.68, 95% CI, 0.49–0.93) were at reduced risk for distress compared to those who wanted to someday, whereas those with no desire were not at significant risk of distress.
Longitudinal analysis
Over the 12-month study period, those reporting “good,” “ok,” and “poor” perceived access to GAC at baseline experienced significant changes in distress scores compared to those reporting “great” access. As shown in Figure 1, those with the poorest baseline GAC access consistently had the highest mean distress scores, from 27.4 (baseline) to 30.0 (6 months) and 30.5 (12 months). Conversely, those with great baseline access had the lowest mean distress scores and showed decreasing distress levels overall from baseline to 12 months. This pattern was supported by results from the multilevel random intercept model (Table 3). Participants reporting “poor” perceived access to GAC at baseline showed the largest increase in psychological distress scores compared to those reporting “great” access after adjusting for covariates (5.55 points, 95% CI, 2.88–8.20). Participants reporting “ok” and “good” perceived access to GAC also showed significant increases in distress scores, by 3.11 (95% CI, 1.15–5.06) and 1.88 points (95% CI, 0.39–3.38), respectively.
Figure 1.
Psychological distress scores at baseline, 6 months, and 12 months stratified by baseline access to gender-affirming care: TURNNT cohort study, New York City, 2020-2023.
Table 3.
Longitudinal changes in distress scores by perceived access to gender-affirming care, TURNNT cohort study, New York City, 2020-2023.
| Changes in distress scores (95% CI) | ||
|---|---|---|
| Unadjusted | Adjusted a | |
| Perceived access to gender-affirming care at baseline (ref: Great) | ||
| Good | 1.76 (0.36, 3.17) | 1.88 (0.39, 3.38) |
| Ok | 3.42 (1.58, 5.25) | 3.11 (1.15, 5.06) |
| Poor | 6.46 (3.89, 9.01) | 5.55 (2.88, 8.20) |
Abbreviation: TURNNT, Trying to Understand Relationships, Networks, and Neighborhoods Among Transgender Women of Color.
Adjusted for age group, race, insurance availability, income, sex work history, incarceration history, nativity (US born), and HIV status, all at baseline, as categorized in Table 1.
Table 4 shows results from our longitudinal analysis of the association between changes in access to GAC over time and psychological distress. Those who reported their access to GAC as “good” at baseline but “bad” at 6 months (good-bad) experienced the highest risk of psychological distress of all groups, with an adjusted RR of 1.40 (95% CI, 1.08–1.82) compared to the good-good trajectory. This association was no longer observed at 12 months, where changes in perceived access to GAC from baseline to 6 months did not significantly impact the risk of distress at 12 months in both univariate and multivariable analysis.
Table 4.
Estimated RRs for associations between changes in access to gender-affirming care from baseline to 6 months and psychological distress at 6 months and 12 months and, TURNNT cohort study, New York City, 2020-2023.
| RR for psychological distress (95% CI) | ||||
|---|---|---|---|---|
| 6 months: baseline model a | 6 months: multivariable b | 12 months: baseline model c | 12 months: multivariable d | |
| Changes in access to gender-affirming care from baseline to 6 months | ||||
| Good–good (ref) | ||||
| Good–bad | 1.57 (1.26, 1.96) | 1.40 (1.08, 1.82) | 1.10 (0.77, 1.57) | 1.14 (0.79, 1.64) |
| Bad–good | 1.03 (0.75, 1.42) | 0.99 (0.70, 1.42) | 1.00 (0.70, 1.45) | 1.00 (0.68, 1.49) |
| Bad–bad | 1.35 (1.02, 1.78) | 1.30 (0.93, 1.81) | 1.33 (0.99, 1.79) | 1.42 (1.03, 1.96) |
Abbreviations: RR, risk ratio; TURNNT, Trying to Understand Relationships, Networks, and Neighborhoods Among Transgender Women of Color.
Baseline model was adjusted for baseline distress.
Adjusted for age group, race, insurance availability, income, sex work history, incarceration history, nativity (US born), and HIV status, as categorized in Table 1.
Baseline model was adjusted for baseline distress and access to GAC at 12 months.
Adjusted for age group, race, insurance availability, income, sex work history, incarceration history, nativity (US born), HIV status, baseline distress, and access at 12 month. Sociodemographic variables were categorized as shown in Table 1.
Table 5 shows results from our longitudinal analysis of the impact of each GAMI on psychological distress at 6 months and 12 months, adjusting for baseline distress and treatment desire. Only bottom surgery was associated with increased distress at 6 months after controlling for covariates (aRR: 1.79, 95% CI, 1.04–3.09). All other analyzed GAMIs did not exhibit significant associations with distress at 6 months in both unadjusted and adjusted models. At 12 months, no GAMIs were significantly associated with psychological distress. Results from our sensitivity analysis excluding implausible GAMI completion values are displayed in Appendix 1, showing that results remained consistent.
Table 5.
Estimated RRs for associations between gender-affirming medical intervention desire and psychological distress at 6 months and 12 months controlling for baseline distress, TURNNT cohort study, New York City, 2020-2023.
| RR for psychological distress (95% CI) | ||||
|---|---|---|---|---|
| 6 month: baseline model a | 6 month: multivariable b | 12 months: baseline model a | 12 months: multivariable b | |
| GAMI desire (ref: want it someday) | ||||
| Hormone therapyc | ||||
| Have had it | NA | NA | NA | NA |
| Do not want | NA | NA | NA | NA |
| Breast augmentation | ||||
| Have had it | 1.04 (0.82, 1.32) | 0.81 (0.49, 1.34) | 1.11 (0.87, 1.42) | 0.83 (0.60, 1.15) |
| Do not want | 1.10 (0.80, 1.51) | 0.99 (0.66, 1.48) | 1.01 (0.65, 1.55) | 0.65 (0.34, 1.26) |
| Silicone or filler injection | ||||
| Have had it | 0.66 (0.50, 0.88) | 0.43 (0.18, 1.04) | 1.07 (0.75, 1.53) | 1.45 (0.68, 3.10) |
| Do not want | 0.66 (0.55, 0.79) | 0.71 (0.55, 0.90) | 0.87 (0.64, 1.19) | 0.90 (0.57, 1.42) |
| Facial feminization surgery | ||||
| Have had it | 1.20 (0.94, 1.53) | 1.01 (0.64, 1.59) | 1.12 (0.83, 1.50) | 0.97 (0.67, 1.40) |
| Do not want | 0.99 (0.76, 1.29) | 0.86 (0.60, 1.23) | 1.23 (0.91, 1.67) | 1.12 (0.80, 1.58) |
| Orchiectomy | ||||
| Have had it | 1.13 (0.83, 1.54) | 0.83 (0.38, 1.83) | 1.07 (0.71, 1.59) | 0.96 (0.41, 2.26) |
| Do not want | 0.93 (0.73, 1.19) | 0.99 (0.72, 1.37) | 1.17 (0.92, 1.50) | 1.13 (0.83, 154) |
| Bottom surgery | ||||
| Have had it | 1.20 (0.86, 1.68) | 1.79 (1.04, 3.09) | 1.32 (0.87, 1.99) | 1.45 (0.67, 3.14) |
| Do not want | 1.02 (0.80, 1.29) | 1.16 (0.82, 1.65) | 1.01 (0.77, 1.32) | 0.81 (0.58, 1.14) |
Abbreviations: GAMI, Gender-Affirming Medical Intervention; RR, risk ratio.
Baseline models were adjusted for baseline distress.
Adjusted for GAMI status (ie, the completion of each GAMI of interest) at baseline, age group, race, insurance availability, income, sex work history, incarceration history, nativity (US born), and HIV status (as categorized in Table 1).
Too few people in the “do not want” category for hormone therapy (n=3) to meaningfully assess.
Discussion
Limited research exists assessing GAC, GAMIs, and mental health among TWOC, which represents a major gap in the literature. To address this gap, this study examined associations between perceived access to GAC, specific GAMI completion, and psychological distress among a diverse cohort of TWOC in New York City. This analysis is among the first to use an optimal reference group of those who desire GAMIs but have not yet received them among TWOC, which is critical to account for the diversity of desire in our cohort and strengthen methodological rigor.8,31 There are four main findings to discuss.
First, our baseline analysis found that increasing levels of access to GAC were associated with a reduced risk of psychological distress, supporting existing research on this topic5,8,43 and suggesting that improving access to GAC can help reduce health inequalities for TWOC. Additionally, all assessed GAMIs suggested protective effects against psychological distress risk, with statistical significance found for breast augmentation and facial feminization surgery after controlling for covariates. This may be related to the high external visibility of breast augmentation and facial feminization surgery, which can improve everyday alignment between one’s outward appearance and gender identity more significantly than other analyzed GAMIs. According to the gender-affirmation framework, such alignment can be protective against stigma, violence, and discrimination for TWOC, reducing stigma-related distress as a result, which is also in line with ecosocial and minority stress theory.15,19 It is important to note, however, that while GAC can reduce distress through alleviating gender dysphoria, it may not directly address minority stress or other societal exposures, which can continue to impact mental health long after GAC.
Second, our findings suggest that for all analyzed GAMIs, those who completed treatment had a significantly lower risk of distress compared to those who wanted treatment one day but had not yet received it, with statistical significance found for breast augmentation, fillers, and facial feminization surgery after controlling for covariates. Put differently, participants with unmet needs for gender-affirmation experienced higher psychological distress risk. This complements recent findings from Levine et al., which reported that doctor refusal of desired trans-related care was associated with severe psychological distress risk among USTS respondents.43 This also highlights the importance of tailoring interventions to meet individual needs, recognizing that GAC and GAMIs are only as protective as one’s need for them.
Third, our longitudinal analysis showed that those experiencing a shift from good perceived access to bad perceived access over 6 months faced the highest risk of psychological distress. This highlights the vulnerability of those facing disruptions in access to GAC, which is particularly relevant given the current wave of legislation limiting access to GAC across the country and COVID-related reductions in access to GAC, which affected over half (53.2%) of our cohort.25 Our data challenges recent anti-translegislation and suggests that reducing the accessibility of GAC, as currently proposed and practiced in many American states, can have devastating psychological effects for TWOC.
Finally, 61.2% of our cohort experienced psychological distress at baseline, with 24.5% reporting severe distress. Comparatively, the prevalence of serious psychological distress is 44% among transgender people in the US10 and 5% among the general population in New York City.44 This lower rate of serious distress compared to the general transpopulation may be explained in part by the unique context of New York City, which hosts one of the country’s largest transgender populations and offers some of the most protected and expansive coverage of GAMIs.45 Still, in New York City, our findings suggest that TWOC are nearly 5 times as likely to experience severe psychological distress than the general population. In cities and states with more restricted access to community support and GAC, inequities may be even greater.
Future directions
More research is needed to strengthen external validity and research translation. This includes research among different trans-subpopulations across diverse racial, ethnic, and gender identities in varied geographic contexts. Future studies should consider larger sample sizes to increase statistical power to better inform policies and practices. Future research should prioritize longitudinal study designs with additional time points to allow researchers to assess cross-year changes in access to GAC, GAMIs, and psychological distress. A natural experiment design could be employed using ongoing nationwide cohorts to assess the impact of GAC on distress among TWOC by leveraging variations in access due to external factors (eg, policy changes) to infer causal relationships. Additionally, while we were able to analyze longitudinal changes in access to GAC and distress, more advanced analysis could account for the time-varying confounders with methods such as marginal structural models.46
Limitations
There were several limitations to this study. First, there is a potential for selection bias due to the use of convenience sampling which may limit the generalizability of our findings.47 For example, our sample included TWOC who likely had greater access to community support and healthcare given our community- and clinic-based recruitment strategies. Moreover, not all subpopulations were adequately represented. We had difficulty recruiting from Asian, Native Hawaiian/Pacific Islander, Native American, and Middle Eastern/Southwest Asian/North African communities. As a result, the experiences of individuals in this sample may not be representative of all TWOC, all transgender women, or all trans people. Factors such as social and legal transition steps and minority stress, which are highly relevant to this cohort, were not included in this analysis and represent unmeasured confounders that may influence psychological outcomes. Furthermore, reliance on self-reported data makes this study vulnerable to misclassification and same source bias, despite the use of validated screening tools. Our retention rate was 69.7% at 6 months and 57.0% at 12 months. Statistically, some of our analyses, particularly our longitudinal analyses, could be underpowered, which may explain null and unexpected findings. For example, bottom surgery was associated with an increased risk of distress at 6 months in our longitudinal analysis but a previous review found that bottom surgery was associated with improvements in mental health.32 This discrepancy could be related to short-term complications following bottom surgery48 or due to unstable estimates. Additionally, we used distress scores rather than clinical distress to examine trajectories and to increase power, but this analysis could be improved by understanding the transition between different clinical states of distress. We also acknowledge the possibility that differences among individuals lost to follow-up, such as variations in age, income, and unobserved factors, could influence our findings. Finally, given the observational design and the limited capacity for causal inference inherent in our analytic approach, the findings should not be interpreted as establishing causality.
Summary
This study provides critical insights into the associations between perceived access to GAC, completion of GAMI, and psychological distress among TWOC. Our findings offer strong empirical support for policies and programs that expand and protect access to GAC for TWOC who seek it. Effective strategies include recognizing GAC as essential in the policy frameworks, reducing costs through sustainable funding for GAMIs, and training providers in culturally responsive care for TWOC. Existing LGBTQ and trans-specific interventions may not adequately address the distinct needs and social realities faced by TWOC.
Acknowledgments
We 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. We also thank you 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. We 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, MPH, and Kevalyn Bharadwaj, MPH. We also thank Callen-Lorde Community Health Center staff that contributed to this project. We further thank the following colleagues for their thoughtful input on coding racial and ethnic categories for our 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. We also thank the participants for engaging in this research.
Appendix
Appendix 1.
Sensitivity analysis for associations between gender-affirming medical intervention desire and psychological distress at 6 months and 12 months, controlling for baseline distress and excluding implausible values at 6 months and 12 months, TURNNT cohort study, New York City, 2020-2023.
| RR for psychological distress (95% CI) | ||||
|---|---|---|---|---|
| 6 month: baseline model a | 6 month: multivariable b | 12 months: baseline model a | 12 months: multivariable b | |
| GAMI desire (ref: want it someday) | ||||
| Hormone therapyc | NA | NA | NA | NA |
| Breast augmentation | ||||
| Have had it | 1.04 (0.82, 1.32) | 0.81 (0.49, 1.34) | 1.10 (0.86, 1.41) | 0.86 (0.62, 1.20) |
| Do not want | 1.10 (0.80, 1.51) | 0.99 (0.66, 1.48) | 1.00 (0.65, 1.55) | 0.70 (0.37, 1.35) |
| Silicone or filler injection | ||||
| Have had it | 0.76 (0.57, 1.00) | 0.41 (0.16, 1.07) | 1.04 (0.71, 1.52) | 0.85 (0.34, 2.16) |
| Do not want | 0.67 (0.55, 0.80) | 0.70 (0.55, 0.89) | 0.89 (0.65, 1.21) | 0.78 (0.48, 1.25) |
| Facial feminization surgery | ||||
| Have had it | 1.16 (0.90, 1.151) | 1.00 (0.63, 1.60) | 1.16 (0.87, 1.54) | 0.99 (0.69, 1.43) |
| Do not want | 0.99 (0.76, 1.29) | 0.86 (0.60, 1.23) | 1.24 (0.91, 1.68) | 1.10 (0.78, 1.55) |
| Orchiectomy | ||||
| Have had it | 1.14 (0.83, 1.56) | 0.83 (0.38, 1.82) | 1.08 (0.73, 1.61) | 1.04 (0.45, 2.42) |
| Do not want | 0.93 (0.73, 1.19) | 1.00 (0.72, 1.38) | 1.17 (0.91, 1.49) | 1.13 (0.83, 1.54) |
| Bottom surgery | ||||
| Have had it | 1.19 (0.84, 1.69) | 1.83 (1.06, 3.16) | 1.32 (0.87, 1.99) | 1.33 (0.63, 2.80) |
| Do not want | 1.02 (0.80, 1.29) | 1.14 (0.80, 1.63) | 1.01 (0.77, 1.32) | 0.85 (0.60, 1.21) |
Abbreviations: GAMI, Gender-Affirming Medical Intervention; RR, Risk Ratio.
Baseline models were adjusted for baseline distress.
Adjusted for GAMI status at baseline, age group, race, insurance availability, income, sex work history, incarceration history, nativity (US born), and HIV status (as categorized in Table 1).
Too few people in the “do not want” category for hormone therapy to complete analysis.
Contributor Information
Jenesis Merriman, Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, United States.
Christoffer Dharma, Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, United States; Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.
Su Hyun Park, Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, United States; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 117549, Singapore.
Andrea Joiner, Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, United States.
Roberta Scheinmann, Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, United States.
Kim Watson, Community Kinship Life, New York, NY, United States.
Cristina Herrera, Translatinx Network, New York, NY, United States.
John A Schneider, Department of Medicine, University of Chicago, Chicago, IL, United States; Chicago Center for HIV Elimination, University of Chicago, Chicago, IL, United States; Crown School of Social Work, University of Chicago, Chicago, IL, United States; Department of Public Health Sciences, University of Chicago, Chicago, IL, United States.
Sahnah Lim, Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States.
Chau Trinh-Shevrin, Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States.
Asa Radix, Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, United States; Research and Education, Callen-Lorde Community Health Center, New York, NY, United States.
Dustin T Duncan, Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, United States.
Funding
This work was supported by the National Institute on Minority Health and Health Disparities (grants R01MD013554, 3R01MD013554-02S1, and 3R01MD013554-05S1).
Conflict of interest
The authors declare no conflicts of interest.
Disclaimer
The work described herein is the sole responsibility of the authors and does not represent the official views of NIH or its institutes.
Data availability
The data that support the findings of this study are available from the corresponding author [DTD] upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author [DTD] upon reasonable request.