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. Author manuscript; available in PMC: 2024 Apr 1.
Published in final edited form as: Public Health. 2023 Mar 1;217:81–88. doi: 10.1016/j.puhe.2023.01.017

Stressors in Healthcare and Their Association to Symptoms Experienced by Gender Minority People

Kristen D Clark 1, Annesa Flentje 2,3, Jae M Sevelius 4,5, Carol Dawson-Rose 2, Sandra J Weiss 6
PMCID: PMC10354568  NIHMSID: NIHMS1879317  PMID: 36867986

Abstract

Objectives:

Many individuals whose gender does not align with the sex they were assigned at birth (gender diverse (GD) people) report stressful healthcare encounters. We examined the relationship of these stressors to symptoms of emotional distress and impaired physical functioning among GD.

Study Design:

This study was conducted using a cross-sectional design with data from the 2015 United States Transgender Survey.

Methods:

Composite metrics of healthcare stressors and physical impairments were developed and the Kessler Psychological Distress Scale (K-6) provided a measure of emotional distress. Linear and logistic regression were used to analyze the aims.

Results:

22,705 participants from diverse gender identity subgroups were included. Participants who experienced at least one stressor in healthcare during the past 12 months had more symptoms of emotional distress (β=0.14, p<.001) and 85% greater odds of having a physical impairment (OR=1.85, p<.001). Transgender men exposed to stressors were more likely than transgender women to experience emotional distress and have a physical impairment, with other gender identity subgroups reporting less distress. Black participants exposed to stressful encounters reported more symptoms of emotional distress than White participants.

Conclusions:

Results suggest that stressful encounters in healthcare are associated with symptoms of emotional distress and greater odds of physical impairment for GD people, with transgender men and Black individuals being at greatest risk of emotional distress. Findings indicate the need for assessment of factors that contribute to discriminatory or biased healthcare for GD people, education of healthcare workers, and support for GD people to reduce their risk of stressor-related symptoms.

Keywords: sexual and gender minority, physical health, mental health, healthcare system

Introduction

Health disparities experienced by gender diverse (GD) individuals represent a growing public health concern. Gender diverse populations include varied groups of individuals whose gender identity is not aligned with the sex that was assigned to them at birth.1 This includes transgender people (such as transgender men and transgender women) andnon-binary individuals (individuals whose gender identity is not solely masculine or feminine ormay be in between or shift between masculine and feminine). Non-binary identities also include individuals who describe their gender as agender (or without gender). High rates of health disparities, both psychological and physical have been observed in this GD community, including a greater prevalence of suicide attempts,2 depression, and substance use3 when compared to the general population as well as poorer overall physical health.4 These poor health outcomes have been associated with chronic stress and stigma due to their socially marginalized status.5,6 As described in the Minority Stress Model, stress related to one’s minoritized identity, may be experienced in the form of distal and proximal stressors. The stressors experienced by GD people when accessing healthcare exemplify both distal and proximal stressors.7,8

Distal stressors in healthcare (i.e., stigma such as discrimination, verbal harassment, or physical harm) have been reported by GD people in numerous studies.9 GD people frequently describe encounters with providers who lack knowledge on GD people and their specific health needs, leaving patients with the burden of educating providers themselves.10 Overt discrimination, such as refusal of healthcare services, is also frequently reported, contributing to proximal stressors, such as delaying or avoiding of healthcare by GD people.9 However, little is known about these stressors among particular subgroups of GD people, such as transgender men, transgender women, non-binary people and people who self-identify as crossdressers. Healthcare experiences of transgender women have been most widely studied, describing stressors such as the refusal of healthcare services and inadequate provider knowledge.9 Similar findings have been observed among transgender men and non-binary people, although they have been less widely studied.9 Although research provides evidence that these stressors occur and are associated with poor mental health outcomes,11,12 their relationship to physical health symptoms experienced by GD people is not well understood, although broadly, stress has been associated with poorer physical health outcomes among GD people.4,13

In contrast to gender identity, adverse healthcare experiences based on race/ethnicity have been described widely.14 Experiences of racial and ethnic minority groups range from lack of provider knowledge on assessment findings unique to darker pigmented skin15 to discrimination.16 The limited literature examining healthcare experiences of GD people of color indicates mixed results ranging from no difference among racial or ethnic subgroups17,18 to a greater likelihood of reported poor experiences in healthcare settings.19,20 Intersectionality theory, a theory developed by Black feminist scholars, points to an interlocking relationship between social identities where there are differences in power.21–23 Race, ethnicity, and gender are areas where distinct types of marginalization interface and interlock to shape differential exposure to stigma and resources, such as healthcare access.24 Still, there were few studies that examined the relationship of these stressful encounters in healthcare to psychological or physical symptoms of GD people of color. Understanding these relationships can help in clarifying the impact of these healthcare stressors and in developing needed interventions within healthcare environments and for GD people. The primary aims of this study were to assess the relationship of stressors experienced in healthcare to symptoms of emotional distress and impaired physical functioning among GD people. We also assessed the moderating roles of gender identity as well as race and ethnicity in the association between these stressors and reported symptoms. We hypothesized that a greater number of stressors experienced in healthcare would be associated with more symptoms of both emotional distress and impaired physical functioning. We also hypothesized that both gender identity and race/ethnicity would moderate these relationships.

Methods

Data from the 2015 United States Transgender Survey (USTS) were used for these analyses. The USTS is the largest sample of GD people in the U.S (N=27,715). The survey was developed by the National Center for Transgender Equality to describe the characteristics, experiences, and health of a sample of GD people in the United States.2 Recruitment efforts were expansive, led by a recruitment advisory group. These efforts included outreach through more than 800 healthcare organizations, community organizations, online recruitment, survey-focused events, and participant prizes. Participants include individuals who identify as GD, are 18 years of age or older who resided in the United States, its territories, and foreign military bases.

Demographics

Except for variables regarding gender identity and race/ethnicity, demographic data were used primarily for descriptive purposes. This information included age, education, individual gross income, and sexual orientation. Education was measured by fourteen levels (e.g., less than 8th grade, professional degree). This was recoded to four items.25 Individual gross income was measured by asking participants to identify what their individual income was in 2014 with 18-levels ranging from “no income”, $1-$5,000 to “$150,000 or more” and recoded to a 6-level categorical variable for greater ease in analysis. Race/ethnicity were measured by 9 discrete options (e.g., Alaska Native, Middle Eastern/North African) and a fill-in-the-blank that were recoded to an 8-item variable to facilitate comparison of race/ethnicity categories to standard census reports. Gender identity was assessed using an item for participants to self-select the description closest to their self-described gender. Participants were provided six options (i.e., crossdresser, woman, man, “trans woman”, “trans man”, non-binary/genderqueer) that were then recoded and categorized into four groups (i.e., crossdresser, non-binary, transgender man, and transgender woman).

Stressors in Healthcare

Ten items from the USTS survey were used to measure potential stressors in healthcare. Participants who reported that they accessed healthcare within the past 12 months were asked whether they had encountered each of the ten items during healthcare interactions. Participants could answer ‘yes’ or ‘no’ (e.g., “I had to teach my doctor or other healthcare provider about trans people so that I could get appropriate care”). The items were developed by a review of the literature performed by scholars in the field of GD health, followed by group consensus regarding which items to include in the final survey.26 Due to a severely right-skewed distribution, we recoded the items into a single dichotomous variable, indicating no experience of a healthcare stressor (0) or reports of 1 or more stressors (1).

Symptoms of Emotional Distress

Participants’ scores on the Kessler-6 (K-6) scale were used to assess symptoms of emotional distress during the last 30 days.27 The K-6 is a Likert-type scale, with higher scores indicating more distress (range 6–30). The measure has shown excellent validity with the sensitivity to detect serious mental illness ranging from 0.98 to 0.99 and a Cronbach Alpha ranging from 0.89 to 0.80.28 The K-6 also has demonstrated moderate to high test-retest correlation coefficients.29,30 The sum score was used in this analysis, with a log transformation to improve normality of the distribution.

Symptoms of Impaired Physical Functioning

Participants’ symptoms of impaired physical functioning were measured using four dichotomous items in the USTS that were adapted from CDC’s Behavioral Risk Factor Surveillance System31 and the National Health Interview Survey.32 Items assess (1) difficulty walking or climbing stairs, (2) difficulty dressing or bathing, (3) difficulty concentrating, remembering, or making decisions, and (4) difficulty independently performing activities such as errands, visiting a doctor’s office or shopping. Due to a severely right skewed distribution and an inability to correct the skew with various transformations, we created a single dichotomous variable from the four items indicating whether the participant had 1 or more symptoms of impaired physical functioning (1) or no symptoms of impairment (0).

Data Analysis

All analyses were run using Stata 15.33 Individual items were assessed for distribution and missingness. Multicollinearity of the independent variables was assessed by examining their Variance Inflation Factors and tolerance.34 No evidence of multicollinearity was identified. USTS survey participants who did not complete items about the healthcare stressors because they had not accessed healthcare in the past 12 months (n=3,743) or who had missing data for measures of emotional distress anad physical functioning (n=921) were excluded from analysis. Descriptive statistics were used to determine demographics of the remaining sample (e.g., age, highest level of education). Differences between demographic characteristics of the group that accessed healthcare during the past 12 months and the group that did not access healthcare were evaluated using a two-sample test of proportions and Wilcoxon-Mann-Whitney tests.

We employed Chi square analyses to evaluate the association between stressors in healthcare and individual gender identities. Linear regression was used to examine the relationship between stressors in healthcare and symptoms of emotional distress. To examine the relationship between stressors in healthcare and symptoms of impaired physical functioning (a dichotomous variable), logistic regression was used. Healthcare stressors were treated as a dichotomous predictor (experienced stressors or not) in all models. All models were adjusted to account for variance due to age, education, and individual gross income.

The moderating effects of gender identity as well as race and ethnicity were evaluated by building interaction terms into the regression models. Dichotomous variables were created for each gender identity group: crossdresser, non-binary, transgender men, and transgender women. Transgender women were chosen as the reference group in analyses due to the more substantial research about this group. Dichotomous variables were also created for categories of race/ethnicity: Alaskan Native/Native American, Asian, Black, Latino/Hispanic, multiracial, Pacific Islander, White, and race-not-listed. White participants were chosen as the reference group because of the robust body of research showing minority racial and ethnic groups having poorer health outcomes than White individuals.25

Results

Sociodemographic characteristics of the sample are described in full in Table 1 (N=22,705). The mean age of participants was 31.5 (SD=3.6). Within our sample, 83.1% of participants were White, 5.1% were Latino/x or Hispanic, 4.9% were multiracial, 2.8% were Black, and 4.1% were other racial groups (see Table 1). The representation of gender identities was diverse: 33.9% transgender women, 29.9% transgender men, 33.8% non-binary, and 2.4% crossdressers. Participants also reported diverse sexual orientations: 21.3% queer, 17.8% pansexual, 14.7% bisexual, 12.6% heterosexual/straight, and the remaining (33.6%) identified other sexual orientations. The sample was highly educated, with 85.7% reporting at least some college. It is important to note that participants who accessed healthcare during the past 12 months (n=22,705), and were thus included in this analysis, had higher incomes (p<.001) and more education (p<.001) than individuals who had not accessed healthcare and were not included in this analysis (n=3,743; see Table 1).

Table 1.

Sample Characteristics of the 2015 United States Transgender Survey (N = 27,715)

Variable Accessed healthcare during past 12 months (n=22,705)
n (%) 		No healthcare access during past 12 months (n=3,743)
Personal Characteristics
Age, in years (Mean, SD) 31.5, 13.6 28.3, 11.61 p<.001
 18 to 24 9,420 (41.5) 1,952 (52.2)
 25 to 44 9,137 (40.2) 1,387 (37.1)
 45 to 64 3,473 (15.3) 344 (9.2)
 65+ 675 (3.0) 60 (1.6)
Race/Ethnicity
 Alaska Native/American Indian 265 (1.2) 33 (0.0) p=.373
 Asian/Asian American 569 (2.5) 104 (2.8) p=.325
 Black/African American 614 (2.7) 117 (3.1) p=.145
 Latino/a/Hispanic 1,139 (5.0) 238 (6.4) p<.001
 Multiracial 1,006 (4.4) 218 (5.8) p<.001
 Native Hawaiian/Pacific Islander 49 (0.2) 9 (0.2) p=.774
 Racial/ethnic identity not listed 487 (2.1) 90 (2.4) p=.341
 White 18,473 (81.4) 2,914 (77.9) p<.001
Gender Identity
 Crossdresser 554 (2.4) 162 (4.3) p<.001
 Non-binary (assigned female at birth) 7,670 (33.8) 1,695 (45.3) p<.001
 Transgender man 6,784 (29.9) 824 (22.0) p<.001
 Transgender woman 7,697 (33.9) 1,062 (28.4) p<.001
Sexual Orientation
 Asexual 2,314 (10.2) 544 (14.5) p<.001
 Bisexual 3,344 (14.7) 574 (15.3) p=.355
 Gay 1,076 (4.7) 172 (4.6) p=.702
 Heterosexual/Straight 2,849 (12.6) 358 (9.6) p<.001
 Lesbian 2,556 (11.3) 330 (8.8) p<.001
 Same-gender loving 211 (0.9) 39 (1.0) p=.503
 Pansexual 4,045 (17.8) 799 (21.4) p<.001
 Queer 4,828 (21.3) 639 (17.1) p<.001
 Demisexual 223 (1.0) 55 (1.5) p<.01
 Sexual orientation not listed 1,259 (5.6) 233 (6.2) p=.096
Socioeconomic Position
Annual Individual Income p<.001
 No income 3,014 (13.3) 731 (20.7)
 $1 to $9,999 6,234 (27.5) 1,184 (32.8)
 $10,000 to $24,999 4,904 (21.6) 912 (25.3)
 $25,000 to $49,999 3,834 (16.9) 435 (12.1)
 $50,000 to $100,000 2,847 (12.5) 240 (6.7)
 $100,000 + 1,457 (6.4) 106 (2.9)
Educational Attainment p<.001
 Less than high school 679 (3.0) 192 (5.1)
 High school grad/GED 2,581 (11.4) 705 (18.8)
 Some college/Associate’s degree 10,394 (45.8) 1,849 (49.4)
 Bachelor’s degree or higher 9,051 (39.9) 997 (26.6)
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At least one stressor in healthcare was reported by 66% of the participants in our sample. The most frequently endorsed stressor was answering “no” in response to the item “My doctor knew I was trans and treated [me] with respect” (Table 2). All stressors in healthcare showed differences across gender identities (p<.05).

Table 2.

Items from 2015 United States Transgender Survey representing stressors in healthcare that were posed to participants who have accessed healthcare in the past 12 months (n = 22,705).

Question Experienced stressor n (%) Crossdresser n (%) Non-binary n (%) Transgender Men n (%) Transgender Women n (%)
My doctor knew I was trans and treated with respect.* 13,609 (59.9) 443 (80.0) 5,539 (72.2) 1,633 (24.1) 1,481 (19.2)
I had to teach my doctor or other health care provider about trans people so that I could get appropriate care. 5,354 (23.6) 16 (2.9) 1,221 (15.9) 2,144 (31.6) 1,973 (25.6)
A doctor or other health care provider refused to give me trans-related care. 1,804 (8.0) 7 (1.3) 321 (4.2) 687 (10.1) 789 (10.3)
A doctor or other health care provider refused to give me other health care (e.g., flu shot, physical). 662 (2.9) 3 (0.5) 194 (2.5) 219 (3.2) 246 (3.2)
My doctor asked me unnecessary/invasive questions about my trans status that were not related to the reason for my visit. 3,377 (14.9) 6 (1.1) 839 (10.9) 1,422 (21.0) 1,110 (14.4)
A doctor or other health care provider used harsh or abusive language when treating me. 1,083 (4.8) 2 (0.4) 52 (3.7) 382 (5.6) 360 (4.7)
A doctor or other health care provider was physically rough or abusive when treating me. 375 (1.7) 2 (0.4) 110 (1.43) 123 (1.8) 140 (1.8)
Was verbally harassed in a health care setting. 1,289 (5.7) 6 (1.1) 318 (4.2) 456 (6.7) 509 (6.6)
I was physically attacked by someone during my visit in a health care setting. 116 (0.5) 1 (0.2) 24 (0.31) 29 (0.4) 62 (0.8)
I experienced unwanted sexual contact in a health care setting. 279 (1.2) 3 (0.5) 60 (0.8) 66 (1.0) 150 (2.0)
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*

the n (%) of participants who indicated “no” on this item is reported here.

Bolded values indicate a statistically significant chi2 result between gender and stressor in healthcare (p<.05).

Symptoms of Emotional Distress

The mean emotional distress score for the sample was 10.39, with a range of 0 to 24. For participants who experienced at least one stressor in healthcare during the past 12 months, there was a 0.10 increase in symptoms of emotional distress (β=0.14, p<.001, partial η2=0.03). The participants’ highest level of education, and individual income were held constant (see Table 3 for full results).

Table 3.

Results of multiple linear regression models evaluating stressors in healthcare on symptoms of emotional distress in the 2015 United States Transgender Survey (n = 22,705).

Variables included in the model R 2 Adj. R 2 B β t p
Model 1: Age, Education, Individual Income, Stressors in Healthcare (dichotomous) 0.26 0.25 <.001
 Stressors in Healthcare (dichotomous) 0.10 0.14 24.45 <.001
Model 2: Age, Education, Individual Income, Stressors in Healthcare (continuous >0) 0.22 0.22 <.001
 Stressors in Healthcare (continuous >0) 0.03 0.13 17.34 <.001
Model 3: Age, Education, Individual Income, Stressors in Healthcare (dichotomous) X Gender Identity 0.26 0.26 <.001
 Stressors in Healthcare (dichotomous; main effect) 0.15 16.05 <.001
 Crossdresser (main effect) 0.00 0.06 .955
 Stressors in Healthcare x Crossdresser −0.05 −3.39 <.01
 Non-binary (main effect) 0.03 1.98 .048
 Stressors in Healthcare x Non-binary −0.07 −4.21 <.001
 Transgender men (main effect) −0.11 −10.58 <.01
 Stressors in Healthcare x Transgender men 0.03 2.71 <.01
Transgender women (comparison group) − − −
Model 4: Age, Education, Individual Income, Stressors in Healthcare (dichotomous) X Race/Ethnicity 0.25 0.25 <.001
 Stressors in Healthcare (dichotomous; main effect) 0.09 0.13 20.87 <.001
 Alaskan Native/American Indian (main effect) −0.01 0.00 −0.27 .785
 Stressors in Healthcare X Alaskan Native/American Indian 0.06 0.02 1.65 .125
 Asian/Asian American (main effect) −0.07 −0.04 −3.84 <.001
 Stressors in Healthcare X Asian/Asian American 0.04 0.02 1.85 .064
 Black (main effect) −0.05 −0.03 −3.03 <.01
 Stressors in Healthcare X Black/African American 0.06 0.03 2.85 <.01
 Latino/Hispanic −0.02 −0.02 −1.73 .084
 Stressors in Healthcare X Latino/Hispanic 0.03 0.02 1.78 ..075
 Multiracial (main effect) −0.02 −0.01 −1.06 .289
 Stressors in Healthcare X Multiracial 0.02 0.01 1.18 .237
 Native Hawaiian/Pacific Islander (main effect) −0.08 −0.01 −1.38 .166
 Stressors in Healthcare X Native Hawaiian/Pacific Islander 0.15 0.02 1.91 .056
 Race/Ethnicity not listed (main effect) 0.14 0.02 1.83 .067
 Stressors in Healthcare X Race/Ethnicity not listed −0.06 −0.01 −0.68 .497
 Stressors in Healthcare X White (comparison) − − −
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All models covaried for age, education, and individual income

We found significant effects when testing the moderating role of gender identity in the association between exposure to stressors and symptoms of emotional distress. Individuals who identified as crossdressers (β=−0.05, p<.01, partial η2 = 0.001) and non-binary people (β=−0.05, p<.01, partial η2 = 0.001) who experienced stressors in healthcare had less symptoms of emotional distress than transgender women. However, transgender men who experienced stressors in healthcare had greater symptoms of emotional distress than transgender women (β=0.03, p<.01, partial η2 = 0.0003).

In testing the moderating effect of race/ethnicity, Black GD people had greater emotional distress associated with exposure to stressors in healthcare when compared to White GD people (β=0.06, p<.01, partial η2 = 0.001). No differences were found among other racial or ethnic groups.

All significant relationships between stressors and emotional distress had standardized beta coefficients ranging from β=0.03 to β=0.14. Partial eta squared values ranged from η2= 0.0003 to η2= 0.03. These coefficients would be interpreted as small effects sizes. 35,36

Symptoms of Physical Impairment

In our sample, 37.5% (n=8,523) of participants reported 1 or more symptoms of physical impairment. As shown in Table 4, participants reporting at least one stressor in healthcare during the past 12 months had 86% greater odds (OR=1.86, p<.001, 95% CI 1.74–1.98) of at least one symptom of physical impairment compared to participants who reported no stressors. The model adjusted for age, highest level of education, and individual income (see Table 4).

Table 4.

Results of logistic regression models evaluating stressors in healthcare on symptoms of emotional distress in the 2015 United States Transgender Survey (n = 22,705).

Variables included in the model OR CI p
Model 1: Age, Education, Individual Income, Stressors in Healthcare (dichotomous)
 Stressors in Healthcare (dichotomous) 1.86 1.74, 1.98 <.001
Model 2: Age, Education, Individual Income, Stressors in Healthcare (dichotomous) X Gender Identity
 Stressors in Healthcare (dichotomous; main effect) 1.57 1.41, 1.74 <.001
 Crossdresser (main effect) 1.44 0.86, 2.43 .168
 Stressors in Healthcare × Crossdresser 0.36 0.20, 0.65 <.01
 Non-binary (main effect) 1.94 1.66, 2.27 <.001
 Stressors in Healthcare x Non-binary 0.96 0.81, 1.15 .686
 Transgender men (main effect) 1.00 0.88, 1.13 .958
 Stressors in Healthcare × Transgender men 1.20 1.03, 1.40 <.05
 Transgender women (comparison group) − − −
Model 3: Age, Education, Individual Income, Stressors in Healthcare (dichotomous) X Race/Ethnicity
Stressors in Healthcare (dichotomous; main effect) 1.80 1.68, 1.94 <.001
 Alaskan Native/American Indian (main effect) 1.60 0.96, 2.68 .074
 Stressors in Healthcare X Alaskan Native/American Indian 1.00 0.55, 1.82 1.00
 Asian/Asian American (main effect) 0.58 0.40, 0.85 <.01
 Stressors in Healthcare X Asian/Asian American 1.32 0.86, 2.04 .205
 Black (main effect) 0.93 0.69, 1.26 .631
 Stressors in Healthcare X Black/African American 1.17 0.81, 1.71 .38
 Latino/x/Hispanic 0.79 0.61, 1.02 .069
 Stressors in Healthcare X Latino/Hispanic 1.23 0.91, 1.66 .169
 Multiracial (main effect) 1.31 1.03, 1.68 .030
 Stressors in Healthcare X Multiracial 0.99 0.74, 1.33 .964
 Native Hawaiian/Pacific Islander (main effect) 1.10 0.42, 2.88 .847
 Stressors in Healthcare X Native Hawaiian/Pacific Islander 1.12 0.32, 3.94 .864
 Race/Ethnicity not listed (main effect) 3.22 0.91, 11.44 .070
 Stressors in Healthcare X Race/Ethnicity not listed 0.67 0.15, 3.07 .611
Stressors in Healthcare X White (comparison) − − −
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All models covaried for age, education, and individual income

We found significant differences for two gender identity subgroups when compared to the reference group, transgender women. Individuals who identified as crossdressers had lower odds of healthcare stressors being associated with symptoms of physical impairment than did transgender women (OR=0.36, p<.01; 95% CI 0.20, 0.65). In contrast, transgender men who experienced stressors in healthcare had greater odds of healthcare stressors being associated with symptoms of physical impairment than did transgender women (OR=1.20, p<.05; 95% CI 1.03, 1.40). Tests for the moderating effect of race/ethnicity indicated no differences between racial/ethnic groups in the relationship between stressors in healthcare and symptoms of physical impairment.

Discussion

Results indicate that experiencing even one stressor in healthcare is associated with greater symptoms of emotional distress. These findings are consistent with previous literature describing discrimination as associated with poor mental health outcomes such as suicidal ideation,37 depression,38 and anxiety.39 Discrimination in healthcare has also specifically been associated with suicidal ideation,11 depression18 and psychological distress among GD people. Despite the significance of our results, all beta and eta squared coefficients indicate small effect sizes, suggesting only modest relationships between exposure to stressors and emotional distress and the consequent need for further study.

Some of our most important findings center on the vulnerability of gender identity subgroups. The relationship between experiencing healthcare stressors and emotional distress was significantly stronger for transgender women than crossdressers or non-binary people. Although we can’t assume a causal effect due to the cross-sectional nature of these data, results suggest that the emotional well-being of transgender women may be more adversely affected by the disrespect or discrimination they experience in healthcare than individuals in many other GD groups This finding extends previous research showing that transgender women are highly stigmatized compared to the general population2,40 by providing evidence of potential effects of such stigmatization on their mental health. However, transgender men had an even greater association between healthcare stressors and symptoms of emotional distress than did transgender women. Because greater avoidance of healthcare has been noted among transgender men when they experience stressors in healthcare,17 delayed access to needed services could contribute to their increased symptoms of distress.

Our results for the moderating effect of race/ethnicity show differences between Black and White GD people but for no other racial/ethnic groups. Black participants had a greater effect size for the relationship between reported stressors and symptoms of emotional distress compared to White participants. While previous literature has found higher rates of stigma and discrimination among Black GD people,38 our results indicate that these types of stressors may have a more substantial impact on the emotional well-being of Black GD people.

Results also indicate that GD people who experience stressors in healthcare have greater odds of physical impairment than individuals who don’t experience stressors. Stressors in healthcare have been shown previously to have deleterious effects on physical health as well as on one’s willingness to seek healthcare services.9,12,41 Individuals who have experienced mistreatment in healthcare settings may delay care, with negative effects on their physical health, or they may experience a greater impact on physical symptoms because they are more sensitized to healthcare stressors.12 Because we cannot assume the direction of the relationship in these analyses, it is also possible that individuals who have more frequent healthcare visits because of impairments in physical functioning are more frequently exposed to stressors in healthcare.

Our findings for differences between gender identity subgroups in the relationship between healthcare stressors and physical functioning show a similar pattern as our results for emotional distress. Transgender men appeared to be at greatest risk of physical impairments in relation to healthcare stressors when compared to the other gender identity subgroups in our analysis. While research on mental health outcomes among gender identity subgroups is limited, there is some evidence that mental health disorders, such as anxiety, may be more prevalent among transgender men.42 Studies are needed to examine potential biological and psychosocial factors that may increase the potential for increased vulnerability of transgender men to healthcare stressors and symptom development.

There were no moderating effects of race/ethnicity on the relationship between reported stressors in healthcare and symptoms of physical impairment. A meta-analysis on the effects of racism in healthcare indicated that discrimination in healthcare settings had a greater association with mental health outcomes such as depression than with physical or general health.43 This could explain why we found that Black GD people experienced greater symptoms of emotional distress in relation to healthcare stressors than White participants but found no racial differences for physical impairment. However, despite our large sample, it is important to note that statistical power may be a root cause of our lack of more moderating effects for race and ethnicity. The proportion of racial and ethnic minority participants was small, with groups ranging from 0.2%–5%, in comparison to our White sample (81.4%). Further, in addition to improved efforts for gender affirming healthcare environments, multilevel antiracism efforts are needed to address inequities among GD people who are marginalized both in gender and racial identities.44

Study limitations should be considered. The cross-sectional design prevents causal inferences about the direction of the relationship between stressors in healthcare and symptoms. In addition, items representing stressors in healthcare were only given to participants in the USTS survey who indicated that they had accessed healthcare in the past 12 months, eliminating some participants from analysis. As noted under the results, individuals who did not complete the survey appeared to have more socioeconomic challenges (lower incomes and less education), decreasing our ability to generalize to these important populations. Additionally, original items in the survey representing stressors in healthcare only offered participants the response options of ‘yes’ or ‘no’, precluding the ability to know the frequency or severity, or in what setting participants experienced each stressor. Further, social desirability bias may have influenced participant responses to sensitive questions, particularly around experiences of mistreatment or violence in healthcare settings. The mismatch between time frames assessed for health care stressors (the past 12 months) and symptoms of emotional distress (the past 30 days) may have limited our ability to identify concurrent associations between stressors and symptoms experienced earlier in the year. Future work with more nuanced measurements of stressors in healthcare would help advance our understanding of this phenomenon,45 particularly to assist in determining the clinical significance of these relationships.

Our need to dichotomize the variables measuring stressors in healthcare and symptoms of physical impairment (because of their skewed distributions) reduced variability and our power to detect significant effects.46,47 Because this was a secondary analysis, our measure of physical impairment was limited in scope, representing a small portion of the varied symptoms associated with impairments in physical functioning. As a result, we may have missed participants with symptoms of other impairments, some of which may not affect their daily function but none-the-less impact their health (e.g., hypertension, diabetes). It is not clear whether the increase in symptom burden that was related to stressors for particular groups is due to their frequency of experiencing stressors in healthcare, the severity or intensity of particular stressors, the unique perception/interpretation of the stressor(s) by the individual, or other factors. Lastly, our sample was 83% White non-Hispanic, which is greater than population estimates for GD people in the U.S.48 Similarly, Black & African American participants accounted for only 2.7% of our total sample but are estimated to account for 16% of the GD populations in the U.S. Representativeness was also limited in terms of the educational status and income levels of our sample’s participants. Our sample was highly educated with almost 40% of our sample reporting that they have a Bachelors’ degree or higher. This varies from what is known about the education level of the broader GD populations, of whom 13% are estimated to have completed college as described by a population-based sample.49 However, non-probability samples, such as the USTS, allow for analysis of questions, such as stressors in healthcare, that are unique to the GD community and would be otherwise unaddressed in population-based surveys.50

Still, this study provides an important foundation for future research. Further studies can explore the nature of stressors experienced by people of different gender identities as well as the frequency and severity of stressors. Findings also indicate a need for assessment of organizational and individual factors within healthcare systems that contribute to discrimination, abusive, or insensitive care for GD people. Additionally, future research should be extended to specific types of emotional distress and other physical impairments with a more diverse sample. Tailoring recruitment efforts to include both researchers and study personnel from the minoritized groups who are being sought, such as racial and ethnic minority groups, is a key component to effective recruitment practices.51,52

Conclusions

Stressors in healthcare were associated with symptoms of emotional distress and physical impairment among GD people in our sample. Most notably, transgender men and Black participants had a greater symptom burden in association with stressors in healthcare when compared to transgender women and White participants. Increased research on the characteristics of stressors in healthcare and how these are experienced among diverse gender and racial groups will increase the opportunity for the development of targeted interventions. The development of affirming and inclusive healthcare environments that incorporate antiracism principles, including diversifying the healthcare workforce, should be prioritized to improve the healthcare experiences of diverse groups of GD people. Further, healthcare systems can employ a more inclusive workforce that reflects the communities they serve.

Acknowledgements

We would like to acknowledge the National Center for Transgender Equality for their tremendous effort in conducting survey and willingness to share the resulting data. We also wish to acknowledge the members of the transgender and nonbinary community for their time and effort to participate.

Footnotes

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