Abstract
Introduction
Using Asia’s first nationwide cohort dataset, this study aimed to assess the prevalence of anti-transgender discrimination and healthcare avoidance and delay (HAD) and examine their associations among transgender and gender diverse (TGD) adults in South Korea.
Methods
We analyzed a two-wave (2020–2021) longitudinal dataset of 190 Korean TGD adults. Anti-transgender discrimination were classified accordingly: experienced at (1) neither wave, (2) baseline (2020) only, (3) follow-up (2021) only, and (4) both waves. We also asked about HAD in the past 12 months at follow-up for both transition-related and non-transition-related healthcare services. Multivariate modified Poisson regression was used to examine the associations between anti-transgender discrimination and HAD.
Results
Of 190 participants, 102 (53.7%) experienced anti-transgender discrimination at both waves, and 130 (68.4%) reported HAD at follow-up. Compared to those without any experiences of anti-transgender discrimination, those who experienced it in both waves had a 1.78-times (95% CI: 1.21–2.63) higher prevalence of non-transition-related HAD, but not among those who experienced it in either wave. In contrast, anti-transgender discrimination was not associated with transition-related HAD.
Conclusion
In order to enhance healthcare access for transgender and gender diverse (TGD) individuals, it is necessary to implement interventions, such as anti-discrimination laws, that protect them from discrimination.
Keywords: Access to healthcare, discrimination, healthcare avoidance and delay, South Korea, transgender people
Introduction
Transgender is an umbrella term describing individuals with gender identities that are incongruent with their sex assigned at birth (American Psychological Association, 2011). A growing body of literature has documented greater health difficulties within the transgender and gender diverse (TGD) population in comparison to cisgender populations (Reisner et al., 2016). Compared to cisgender people, TGD people are more likely to suffer from both poor physical health conditions (e.g. asthma, diabetes, and human immunodeficiency virus; Abramovich et al., 2020) and negative mental health outcomes (e.g. lifetime suicide attempt, suicidal ideation, depressive symptoms, and anxiety symptoms; Lee et al., 2020; Millet et al., 2017; Reisner et al., 2014).
Given the greater healthcare needs among TGD individuals, it is important for them to have access to appropriate healthcare services (Lee et al., 2018; Yi et al., 2015). Access to healthcare is defined as “the timely use of personal health services to achieve the best possible health outcomes” (Millman, 1993). However, prior literature has found that TGD people do not receive needed healthcare at greater rates than cisgender people (Giblon & Bauer, 2017; Macapagal et al., 2016). Furthermore, avoidance or delay in seeking healthcare services has been explored as a potential cause of health disparities that TGD people experience (Reisner et al., 2016). Previous studies have found that several factors such as living in poverty and lack of knowledge or skills among transgender-specific healthcare providers may increase the rate of healthcare avoidance and delay (HAD) among TGD people (Jaffee et al., 2016; Kattari et al., 2015; Kcomt et al., 2020; White Hughto et al., 2015).
In addition, discrimination faced by transgender people has also been suggested as a contributing factor to HAD (Drabish & Theeke, 2022). Several quantitative studies have shown that discrimination in the healthcare setting is related to HAD among TGD people (Costa et al., 2018; Glick et al., 2018; Reisner et al., 2015; Socías et al., 2014). For example, a study of 452 transgender people in Massachusetts, USA reported that TGD people who had been discriminated against in healthcare settings were more likely to delay seeking necessary treatments when they were sick or injured or to postpone routine checkups (Reisner et al., 2015). Moreover, a nationwide cross-sectional study from South Korea showed that TGD people who experienced discrimination due to transgender identity had a prevalence of HAD that was more than two times greater than that of those who never experienced any discrimination (Lee et al., 2022).
However, the aforementioned studies had several limitations. First, to our knowledge, there is no longitudinal study that observed the association between discrimination and HAD among TGD people; all existing studies used cross-sectional designs and could not establish temporality (Costa et al., 2018; Glick et al., 2018; Lee et al., 2022; Reisner et al., 2015; Socías et al., 2014). In the cases where TGD people avoided or delayed seeking healthcare out of expectations of discrimination, they would have experienced discrimination less. This would then have lead to inaccurate estimations of the associations. Therefore, there is a need for a study with a temporal order established between experiences of discrimination and HAD, using a longitudinal dataset.
Second, existing studies on HAD among TGD individuals do not differentiate between transition-related HAD and non-transition-related HAD (Costa et al., 2018; Glick et al., 2018; Jaffee et al., 2016; Kattari et al., 2015; Kcomt et al., 2020; Lee et al., 2022; Reisner et al., 2015; Socías et al., 2014). Medical institutions that provide transition-related services (e.g. hormone therapy and gender affirmation surgery) used by TGD people may be more trans-friendly than facilities for other healthcare needs in general, such as common cold and regular medical checkups. Then, it may be expected that differences exist in avoiding or delaying of using healthcare related to transition as opposed to healthcare unrelated to transition. Moreover, experiences of discrimination may affect the use of these two types of healthcare services in different ways. Therefore, when reporting on the associations between discrimination and HAD, it is necessary that transition-related HAD and non-transition-related HAD are distinguished from one another.
Lastly, past research did not restrict their study population to those who needed healthcare (Costa et al., 2018; Glick et al., 2018; Lee et al., 2022; Reisner et al., 2015; Socías et al., 2014). Not all TGD people need healthcare services on a daily basis. For instance, there might have been TGD people who did not want transition-related healthcare services or need it anymore. Also, some TGD people might not have needed to see a healthcare provider because they were not sick. If a study population includes participants who did not need healthcare services even though they experienced discrimination, the relationship between discrimination and HAD could have been biased.
To fill these knowledge gaps, this study assessed transition-related HAD and non-transition-related HAD separately among TGD people who needed healthcare using the first nationwide longitudinal dataset of transgender adults in Asia. The research questions of this study are as follows: (1) What is the prevalence of anti-transgender discrimination and healthcare avoidance and delay? (2) Is there an association between discrimination and HAD among TGD adults in South Korea?
Methods
Dataset and study population
This study analyzed data from “Rainbow Connection Project III (RCP III)—Korean Transgender Adults’ Health Panel Study” which is a nationwide longitudinal survey of a non-probability sample of transgender adults in Korea. RCP III was conducted using SurveyMonkey, an online survey platform, over the course of two years: first wave was collected from October 7 to 31, 2020, and the second wave from October 7 to 31, 2021. During the first wave of the survey, online and offline materials including research purpose and procedure, online survey link, and QR codes were distributed through the following channels: Facebook page and online transgender groups, healthcare institutions that provide trans-related services, and LGBT (lesbian, gay, bisexual, and transgender) rights organizations. Eligibility criteria to participate in this study were as follows: (1) Korean citizen living in Korea, (2) 19 years or older, and (3) self-identify as transgender. In 2021, the link to the second wave survey was sent to the participants who agreed to be followed up and the follow-up rate was 60.0%. The survey was approved by the Korea University Institutional Review Board (KUIRB-2020-0189-01).
In the 1st wave, 591 individuals participated in the online survey. Of them, those who did not consent to be followed up (N = 108), and those who were lost to follow-up (N = 193) were excluded. Out of 290 participants who completed both waves of the survey, we further excluded those who did not need any kind of healthcare in the past 12 months at the 2nd wave (N = 29) and had missing responses for covariates (N = 71). The study population was 190 participants.
Measures
We assessed perceived discrimination at baseline (1st wave survey, 2020) and follow-up (2nd wave survey, 2021) with the question, “Have you ever experienced discrimination over the past year?” Participants could answer using the following options: (1) transgender identity or gender expression, (2) sex, (3) sexual orientation, (4) age, (5) educational level/background, (6) birth region, (7) economic situation, (8) religion, (9) physical appearance which includes height and weight, (10) disease, (11) disability, (12) family type, (13) national origins or race/ethnicity, (14) marital status, and (15) others. Participants were allowed to endorse multiple options. Responses to the option ‘(1) transgender identity or gender expression’ at both waves were used to construct the exposure variable, which was named ‘anti-transgender discrimination’. Based on reporting patterns of anti-transgender discrimination experiences, participants were classified into four groups: experienced anti-transgender discrimination at (1) neither wave (2) baseline only (3) follow-up only and (4) both waves. Responses at baseline regarding discrimination based on reasons other than transgender identity or gender expression were coded into a binary variable of experiences of discrimination due to reasons other than transgender identity (1: yes, experienced discrimination based on one or more reasons other than transgender identity, 0: no), which was included as a covariate in statisical analyses.
At follow up, HAD was measured using the question “Over the past 12 months, have you ever avoided or delayed seeking healthcare?” We measured three types of HAD: (a) transition-related healthcare (e.g. psychiatric diagnosis, hormone therapy, or surgical surgery necessary for gender affirmation/transition), (b) non-psychiatric healthcare unrelated to transition, and (c) psychiatric healthcare unrelated to transition. To each type of HAD, participants responded “yes,” “no,” or “did not need the healthcare services.” Four outcome variables of HAD were created using the responses: any HAD (1: “yes” to any of the three; 0: “no” to all three), transition-related HAD (responses to (a)), non-transition-related HAD (1: “yes” to (b) and (c); 0: “no” to both (b) and (c)), and psychiatric HAD unrelated to transition (responses to (c)). Those who answered that they did not need all of the corresponding HAD items were excluded in analyses specific to each HAD variables. HAD was also measured at baseline, using a question “Have you ever avoided or delayed seeking healthcare in the past 12 months because you identified as transgender?” (response options: yes, no, did not need healthcare services) and included as a covariate in statistical analyses.
Other covariates included were transgender identity, sexual orientation, age, highest educational attainment, monthly individual income, residential area, employment status, and data collection channel. Transgender identity was categorized into four groups: trans woman, trans man, nonbinary assigned female at birth (AFAB), and nonbinary assigned male at birth (AMAB). This variable was created by combining the responses to questions on sex assigned at birth (female or male) and current gender identity (woman, man, or neither woman nor man) following the ‘2-step method’ of measuring transgender identity (Tate et al., 2013). Sexual orientation was categorized into five groups: heterosexual, lesbian/gay, bisexual, asexual, and others. Age (in years) was divided into four groups: 19-24, 25-29, 30-39, and 40-60. Highest educational attainment was classified into four groups: high school graduate or lower, 2-year college, 4-year college, and graduate school. Monthly individual income (in 1000 Korean Won) was divided into five groups: none, <1000, 1000-1999, 2000-2999, ≥3000. 1,000 Korean Won was equivalent to 0.92 and 0.84 US dollars in 2020 and 2021, respectively. The residential area was classified as Seoul metropolitan city, other metropolitan cities, and other cities and counties. All covariates were measured at baseline (2020).
Statistical analyses
Pearson’s Chi-square tests were used to compare the distribution of any HAD and anti-transgender discrimination across covariates in the study population. Since the prevalence of HAD was high among the study population, a log-linked Poisson regression model with a robust sandwich variance estimator (Zou, 2004) was applied to examine the association between discrimination and HAD and estimate prevlence ratios (PR) and confidence intervals (CI) after adjusting for the covariates including HAD at baseline. All covariates were included as categorical variables in the analyses. Multivariate analyses were carried out separately for each of the outcome variables, after excluding those who responded that they did not need all of the relevant HAD. All statistical analyses were performed using STATA/MP version 16.0 (Stata Corp, College Station, TX, USA).
Results
Table 1 presents the distribution of sociodemographic characteristics and other covariates at baseline, any HAD at follow-up, and anti-transgender discrimination. In our analysis, 190 Korean TGD adults were included. Overall, 53.7% of TGD people reported experiencing anti-transgender discrimination over the past year at both baseline and follow-up. Among the participants in this study, 68.4% reported any HAD over the past 12 months at follow-up. Experiences of anti-transgender discrimination was more common among participants who experience discrimination based on reason(s) other than transgender identity.
Table 1.
Distribution of sociodemographic characteristics and other covariates at baseline (2020), any healthcare avoidance and delay at follow-up (2021), and experienced discrimination due to transgender identity among 190 South Korean transgender adults.
| Distribution | Any HADa |
Experienced anti-transgender discriminationb |
||||||
|---|---|---|---|---|---|---|---|---|
| at neither wave | at baseline only | at follow-up only | at both waves | |||||
| N (%) | N (%) | P-valuec | N (%) | N (%) | N (%) | N (%) | P-valuec | |
| Total | 190 (100.0) | 130 (68.4) | 36 (19.0) | 35 (18.4) | 17 (9.0) | 102 (53.7) | ||
| Transgender identity | <0.001 | 0.008 | ||||||
| Trans woman | 64 (33.7) | 36 (56.3) | 15 (23.4) | 10 (15.6) | 9 (14.1) | 30 (46.9) | ||
| Trans man | 23 (12.1) | 14 (60.9) | 10 (43.5) | 6 (26.1) | 0 (0.0) | 7 (30.4) | ||
| Nonbinary AFAB | 74 (38.9) | 64 (86.5) | 7 (9.5) | 15 (20.3) | 5 (6.8) | 47 (63.5) | ||
| Nonbinary AMAB | 29 (15.3) | 16 (55.2) | 4 (13.8) | 4 (13.8) | 3 (10.3) | 18 (62.1) | ||
| Sexual orientation | 0.010 | 0.030 | ||||||
| Heterosexual | 31 (16.3) | 14 (45.2) | 11 (35.5) | 4 (12.9) | 1 (3.2) | 15 (48.4) | ||
| Lesbian/gay | 23 (12.1) | 13 (56.5) | 9 (39.1) | 3 (13.0) | 1 (4.3) | 10 (43.5) | ||
| Bisexual | 82 (43.2) | 61 (74.4) | 8 (9.8) | 17 (20.7) | 12 (14.6) | 45 (54.9) | ||
| Asexual | 41 (21.6) | 31 (75.6) | 7 (17.1) | 7 (17.1) | 2 (4.9) | 25 (61.0) | ||
| Others | 13 (6.8) | 11 (84.6) | 1 (7.7) | 4 (30.8) | 1 (7.7) | 7 (53.8) | ||
| Age (years) | 0.941 | 0.064 | ||||||
| 19-24 | 101 (53.2) | 70 (69.3) | 13 (12.9) | 19 (18.8) | 12 (11.9) | 57 (56.4) | ||
| 25-29 | 54 (28.4) | 37 (68.5) | 12 (22.2) | 12 (22.2) | 4 (7.4) | 26 (48.1) | ||
| 30-39 | 33 (17.4) | 22 (66.7) | 9 (27.3) | 4 (12.1) | 1 (3.0) | 19 (57.6) | ||
| 40-60 | 2 (1.1) | 1 (50.0) | 2 (100.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) | ||
| Highest educational attainment | 0.488 | 0.687 | ||||||
| High school graduate or lower | 124 (65.3) | 88 (71.0) | 22 (17.7) | 21 (16.9) | 12 (9.7) | 69 (55.6) | ||
| 2-year college | 14 (7.4) | 8 (57.1) | 5 (35.7) | 3 (21.4) | 1 (7.1) | 5 (35.7) | ||
| 4-year college | 46 (24.2) | 29 (63.0) | 9 (19.6) | 10 (21.7) | 4 (8.7) | 23 (50.0) | ||
| Graduate school | 6 (3.2) | 5 (83.3) | 0 (0.0) | 1 (16.7) | 0 (0.0) | 5 (83.3) | ||
| Monthly individual income (1000 Korean Won) | 0.094 | 0.470 | ||||||
| None | 109 (57.4) | 79 (72.5) | 17 (15.6) | 24 (22.0) | 10 (9.2) | 58 (53.2) | ||
| <1000 | 25 (13.2) | 17 (68.0) | 5 (20.0) | 0 (0.0) | 3 (12.0) | 17 (68.0) | ||
| 1000-1999 | 35 (18.4) | 23 (65.7) | 8 (22.9) | 7 (20.0) | 2 (5.7) | 18 (51.4) | ||
| 2000-2999 | 13 (6.8) | 9 (69.2) | 3 (23.1) | 2 (15.4) | 2 (15.4) | 6 (46.2) | ||
| ≥3000 | 8 (4.2) | 2 (25.0) | 3 (37.5) | 2 (25.0) | 0 (0.0) | 3 (37.5) | ||
| Residential area | 0.684 | 0.504 | ||||||
| Seoul metropolitan city | 80 (42.1) | 55 (68.8) | 18 (22.5) | 17 (21.3) | 6 (7.5) | 39 (48.8) | ||
| Other metropolitan cities | 41 (21.6) | 30 (73.2) | 4 (9.8) | 8 (19.5) | 3 (7.3) | 26 (63.4) | ||
| Other cities and counties | 69 (36.3) | 45 (65.2) | 14 (20.3) | 10 (14.5) | 8 (11.6) | 37 (53.6) | ||
| Employment status | 0.671 | 0.299 | ||||||
| Student | 85 (44.7) | 61 (71.8) | 9 (10.6) | 21 (24.7) | 10 (11.8) | 45 (52.9) | ||
| Nonpermanent worker | 27 (14.2) | 18 (66.7) | 6 (22.2) | 3 (11.1) | 4 (14.8) | 14 (51.9) | ||
| Permanent worker | 26 (13.7) | 15 (57.7) | 7 (26.9) | 4 (15.4) | 1 (3.8) | 14 (53.8) | ||
| Self-employed | 13 (6.8) | 8 (61.5) | 3 (23.1) | 2 (15.4) | 0 (0.0) | 8 (61.5) | ||
| Unemployment | 39 (20.5) | 28 (71.8) | 11 (28.2) | 5 (12.8) | 2 (5.1) | 21 (53.8) | ||
| Data collection channel | 0.082 | 0.364 | ||||||
| Facebook page or online transgender groups | 51 (26.8) | 33 (64.7) | 9 (17.6) | 14 (27.5) | 4 (7.8) | 24 (47.1) | ||
| Healthcare institutions | 19 (10.0) | 9 (47.4) | 6 (31.6) | 4 (21.1) | 2 (10.5) | 7 (36.8) | ||
| LGBT rights organizations | 29 (15.3) | 23 (79.3) | 6 (20.7) | 4 (13.8) | 1 (3.4) | 18 (62.1) | ||
| Acquaintances or friends | 75 (39.5) | 56 (74.7) | 12 (16.0) | 9 (12.0) | 10 (13.3) | 44 (58.7) | ||
| Others | 16 (8.4) | 9 (56.3) | 3 (18.8) | 4 (25.0) | 0 (0.0) | 9 (56.3) | ||
| Experiences of discrimination due to reasons other than transgender identity d | 0.075 | <0.001 | ||||||
| No | 31 (16.3) | 17 (54.8) | 14 (45.2) | 6 (19.4) | 4 (12.9) | 7 (22.6) | ||
| Yes | 159 (83.7) | 113 (71.1) | 22 (13.8) | 29 (18.2) | 13 (8.2) | 95 (59.7) | ||
HAD, Healthcare avoidance and delay; AFAB, assigned female at birth; AMAB, assigned male at birth.
Any HAD over the past 12 months was measured at follow-up (2021).
Experienced anti-transgender discrimination based on reporting patterns at baseline (2020) and follow-up (2021).
P-value was calculated using the chi-square test, comparing the prevalence of anti-transgender discrimination and HAD across the different groups.
Other reason includes: sex, sexual orientation, age, educational level/backgrounds, birth region, economic situation, religion, physical appearance which includes height and weight, disease, disability, family type, national origins or race/ethnicity, marital status, and others. This measure is assessed at baseline (2020).
Nonbinary AFAB had a higher prevalence of any HAD compared to those with other transgender identities (Table 1). Table 2 provides information on transition-related and non-transition-related HAD according to transgender identity groups. Likewise, nonbinary AFAB showed the highest prevalence of both transition-related HAD and non-transition-related HAD.
Table 2.
Distribution of transition-related HAD and non-transition-related HAD by transgender identity among Korean transgender adults.
| Transgender identity | Transition-related HAD (N = 152)a |
Non-transition-related HAD (N = 184)b |
||||
|---|---|---|---|---|---|---|
| Total | Prevalence |
Total | Prevalence |
|||
| N | N (%) | P-valuec | N | N (%) | P-valuec | |
| Trans woman | 61 | 13 (21.3) | 0.028 | 61 | 32 (52.5) | 0.002 |
| Trans man | 21 | 4 (19.1) | 23 | 14 (60.9) | ||
| Nonbinary AFAB | 44 | 20 (45.5) | 72 | 57 (79.2) | ||
| Nonbinary AMAB | 26 | 6 (23.1) | 28 | 13 (46.4) | ||
HAD, Healthcare avoidance and delay; AFAB, assigned female at birth; AMAB, assigned male at birth.
Of the total of 190 participants, 38 participants responded that they "did not need transition-related healthcare service" and were excluded in this sample.
Of the total of 190 participants, 6 participants responded that they "did not need non-transition-related healthcare service" and were excluded in this sample.
After adjusting for potential confounders, Tables 3–5 shows how experiencing anti-transgender discrimination is related to any HAD, transition-related HAD, and non-transition-related HAD, respectively. The prevalence of any HAD was statistically higher among TGD adults who experience anti-transgender discrimination at both baseline and follow-up (adjusted PR [aPR] = 1.55; 95% CI: 1.10-2.19). This association was significant even when HAD at baseline was further adjusted (aPR: 1.52, 95% CI: 1.10-2.10). (Table 3) However, the association between discrimination and transition-related HAD was not statistically significant (Table 4). When TGD adults experienced anti-transgender discrimination, the prevalence of non-transition-related HAD was statistically higher (aPR: 1.80, 95% CI: 1.18-2.74), and this association remained statistically significant when HAD at baseline was adjusted (aPR: 1.78, 95% CI: 1.21-2.63) (Table 5).
Table 3.
Association between discrimination due to gender identity and any healthcare avoidance and delay among South Korean transgender adults (N = 190).
| Experienced discrimination due to transgender identity | Total | Prevalence of any HAD | Model 1a |
Model 2b |
Model 3c |
|||
|---|---|---|---|---|---|---|---|---|
| N (%) | N (%) | PR | 95% CI | PR | 95% CI | PR | 95% CI | |
| At neither wave | 36 (19.0) | 17 (47.2) | 1 | Reference | 1 | Reference | 1 | Reference |
| At baseline only | 35 (18.4) | 19 (54.3) | 1.15 | (0.72, 1.82) | 1.00 | (0.65, 1.56) | 0.99 | (0.65, 1.51) |
| At follow-up only | 17 (9.0) | 11 (64.7) | 1.37 | (0.84, 2.25) | 1.19 | (0.71, 1.99) | 1.18 | (0.69, 1.99) |
| At both waves | 102 (53.7) | 83 (81.4) | 1.72** | (1.20, 2.47) | 1.55* | (1.10, 2.19) | 1.52* | (1.10, 2.10) |
CI, confidence interval; PR, prevalence ratio; HAD, healthcare avoidance and delay.
p < 0.05;
**p < 0.01
Unadjusted model.
Model adjusted for gender identity, sexual orientation, age, highest educational attainment, monthly individual income, residential area, employment status, data collection channel, and discrimination due to reasons other than transgender identity.
In addition model 2, adjusted for any HAD at baseline.
Table 4.
Association between discrimination due to gender identity and transition related healthcare avoidance and delay among South Korean transgender adults (N = 152)a.
| Experienced discrimination due to transgender identity | Total | Prevalence of transition-related HAD | Model 1b |
Model 2c |
Model 3d |
|||
|---|---|---|---|---|---|---|---|---|
| N (%) | N (%) | PR | 95% CI | PR | 95% CI | PR | 95% CI | |
| At neither wave | 30 (19.7) | 6 (20.0) | 1 | Reference | 1 | Reference | 1 | Reference |
| At baseline only | 32 (21.1) | 6 (18.8) | 0.94 | (0.34, 2.60) | 0.57 | (0.21, 1.58) | 0.48 | (0.17, 1.30) |
| At follow-up only | 14 (9.2) | 4 (28.6) | 1.43 | (0.48, 4.28) | 1.31 | (0.39, 4.38) | 1.08 | (0.30, 3.84) |
| At both waves | 76 (50.5) | 27 (35.5) | 1.78 | (0.81, 3.87) | 1.53 | (0.70, 3.33) | 1.09 | (0.47, 2.55) |
CI, confidence interval; PR, prevalence ratio; HAD, healthcare avoidance and delay.
p < 0.05;
**p < 0.01.
Of the total of 190 participants, 38 participants responded that they "did not need transition-related healthcare service" and were excluded in this sample.
Unadjusted model.
Model adjusted for gender identity, sexual orientation, age, highest educational attainment, monthly individual income, residential area, employment status, data collection channel, and discrimination due to reasons other than transgender identity.
In addition model 2, adjusted for any HAD at baseline.
Table 5.
Association between discrimination due to gender identity and non-transition related healthcare avoidance and delay among South Korean transgender adults (N = 184)a.
| Experienced discrimination due to transgender identity | Total | Prevalence of non-transition-related HAD | Model 1b |
Model 2c |
Model 3d |
|||
|---|---|---|---|---|---|---|---|---|
| N (%) | N (%) | PR | 95% CI | PR | 95% CI | PR | 95% CI | |
| At neither wave | 35 (19.0) | 14 (40.0) | 1 | Reference | 1 | Reference | 1 | Reference |
| At baseline only | 33 (17.9) | 16 (48.5) | 1.21 | (0.71, 2.08) | 1.06 | (0.63, 1.79) | 1.06 | (0.65, 1.72) |
| At follow-up only | 16 (8.7) | 9 (56.3) | 1.41 | (0.78, 2.55) | 1.20 | (0.66, 2.20) | 1.18 | (0.64, 2.19) |
| At both waves | 100 (54.4) | 77 (77.0) | 1.93** | (1.26, 2.93) | 1.80** | (1.18, 2.74) | 1.78** | (1.21, 2.63) |
CI, confidence interval; PR, prevalence ratio; HAD, healthcare avoidance and delay.
p < 0.01.
Of the total of 190 participants, 6 participants responded that they "did not need non-transition-related healthcare service" and were excluded in this sample.
Unadjusted model.
Model adjusted for gender identity, sexual orientation, age, highest educational attainment, monthly individual income, residential area, employment status, data collection channel, and discrimination due to reasons other than transgender identity.
In addition model 2, adjusted for any HAD at baseline.
Table 6 shows the association between anti-transgender discrimination and psychiatric healthcare avoidance and delay unrelated to transition. After adjusting for potential confounders, the association was not statistically significant.
Table 6.
Association between discrimination due to gender identity and psychiatric healthcare avoidance and delay unrelated to transition among South Korean transgender adults (N = 167)a.
| Experienced discrimination due to transgender identity | Total | Prevalence of psychiatric HAD unrelated to transition | Model 1b |
Model 2c |
Model 3d |
|||
|---|---|---|---|---|---|---|---|---|
| N (%) | N (%) | PR | 95% CI | PR | 95% CI | PR | 95% CI | |
| At neither wave | 32 (19.2) | 8 (25.0) | 1 | Reference | 1 | Reference | 1 | Reference |
| At baseline only | 31 (18.6) | 7 (22.6) | 0.90 | (0.37, 2.20) | 0.65 | (2.67, 1.60) | 0.65 | (0.27, 1.57) |
| At follow-up only | 15 (9.0) | 7 (46.7) | 1.87 | (0.83, 4.20) | 1.38 | (0.61, 3.11) | 1.38 | (0.58, 3.30) |
| At both waves | 89 (53.3) | 52 (58.4) | 2.34** | (1.25, 4.38) | 1.71 | (0.90, 3.28) | 1.69 | (0.91, 3.14) |
CI, confidence interval; PR, prevalence ratio; HAD, healthcare avoidance and delay.
p < 0.01.
Of the total of 190 participants, 23 participants responded that they "did not need non-transition-related healthcare service" and were excluded in this sample.
Unadjusted model.
Model adjusted for gender identity, sexual orientation, age, highest educational attainment, monthly individual income, residential area, employment status, data collection channel, and discrimination due to reasons other than transgender identity.
In addition model 2, adjusted for any HAD at baseline.
Discussion
Using a nationwide longitudinal dataset, this study found that more than half (53.7%) of the 190 participants reported having consistently experienced past-year anti-transgender discrimination at both baseline and follow-up. Our study assessed the prevalence of HAD by different transgender identities. Nonbinary AFAB had the highest prevalence of any HAD (86.5%), compared to others whose prevalence ranged between 55.2% and 60.9%. When we divided HAD by transition-related or not, nonbinary AFAB had highest prevalence of transition related HAD (45.5%) and non-transition-related HAD (79.2%).
Findings from previous studies comparing the prevalence of HAD in nonbinary and binary transgender people are inconsistent (Boyer et al., 2022; Kachen & Pharr, 2020; Kcomt et al., 2021; Kcomt et al., 2020; Reisner & Hughto, 2019). Moreover, no previous study decomposed the prevalence of HAD among nonbinary people into their birth-assigned sex (i.e. either AFAB or AMAB). Our findings suggest a need for future studies to explore potential differences in patterns of HAD by gender and sex among TGD individuals.
Our findings showed that TGD people who experienced anti-transgender discrimination at both baseline and follow-up were more likely to avoid or delay seeking any kind of healthcare services at follow-up, compared to those who did not experience anti-transgender discrimination. This result was consistent with previous cross-sectional studies, all of which measured experiences of HAD in general (Costa et al., 2018; Glick et al., 2018; Lee et al., 2022; Reisner et al., 2015; Socías et al., 2014). The current study further inspected for potential differences in the associations between anti-transgender discrimination and HAD by whether HAD was related to transition or not.
In an analysis on non-transition-related HAD, its association with anti-transgender discrimination was statistically significant. One way to interpret this finding is that TGD people who had experienced anti-transgender discrimination chose HAD as a coping strategy to avoid future discrimination. The gender minority stress and resilience (GMSR) model may provide an explanation for the finding (Testa et al., 2015). Based on the minority stress model (Meyer, 2003), the GMSR model was developed to propose that when gender minority people are exposed to discrimination, they may develop internal stressors such as negative expectations and concealment (Testa et al., 2015). People who experienced discrimination can expect that others will devalue or reject them due to their transgender identity or gender expression (Reisner et al., 2015).
A study of 150 transgender men by White Hughto et al. (2018) found that they were more likely to avoid and delay healthcare use if they had received healthcare mistreatment such as refusal of care. They further found that transphobia-related rejection sensitivity, an individual’s level of anticipation and perception of rejection or mistreatment based on stigma against transgender individuals, can mediate this relationship (White Hughto et al., 2018). According to previous studies, most TGD people felt uncomfortable expressing their needs because health professionals did not respect TGD individuals and did not accept their gender identity; moreover, TGD individuals had to teach healthcare workers about their problems (Costa et al., 2018; Jaffee et al., 2016; Lee et al., 2018). For this reason, TGD people may choose to avoid and delay healthcare use after experiencing discrimination. However, the current study did not take into consideration for proximal stressors included in the GMSR model such as internalized transphobia, negative expectations, and concealment. More detailed studies are needed to examine which mechanisms link discrimination experience with avoidance of healthcare among TGD individuals.
Certainly, TGD people also need general healthcare services that are not related to transition. For example, trans men who maintain their uterus have the risk of cervical cancer and those who have had a hysterectomy are still at risk for HPV infection (Agenor et al., 2016; Reisner et al., 2017). Therefore, they need to see a gynecologist regardless of their transition status. In addition, they can go to the hospital for diseases such as flu or stomachache, as well as regular medical checkups. Non-transition-related general healthcare services play an important role to lead one’s daily life. Avoiding or delaying the use of healthcare can have adverse effects on an individual’s health.
We additionally analyzed a relationship between anti-transgender discrimination and psychiatric HAD unrelated to transition. Although it was not statistically significant for reasons such as the small sample size, the effect size of this association was 1.69 (95% CI: 0.91 − 3.14) after adjusting for potential confounders including HAD at baseline. Discrimination against the TGD population harms their mental health (Su et al., 2016; White Hughto et al., 2015). TGD people stigmatized by discrimination may internalize transphobia, which is associated with a high level of depressive symptoms, suicidal ideation, and suicide attempts (Lee et al., 2020). If TGD people have limited access to psychiatric care when their mental health has deteriorated because of discrimination, their mental health risks may increase. In particular, mental health disparities among TGD people have been identified, compared to the general population (Lee et al., 2020; Millet et al., 2017; Reisner et al., 2014) and even compared to other sexual minority groups (Su et al., 2016; Yi et al., 2017). To reduce these health disparities, general healthcare for TGD people should be considered as important in the field of public health. However, this finding needs to be confirmed with a larger sample in future studies.
With regards to transition-related HAD, its association with anti-transgender discrimination was not statistically significant. It is possible that the healthcare settings that TGD people go to for their transition-related healthcare may be trans-friendly. A 2020 survey of Korean TGD individuals reported that 257 out of 351 participants (73.2%) had intentionally sought after and used trans-friendly healthcare services for their medical transition procedures (Hong et al., 2020). In trans-friendly medical settings, they may feel safe to come out and communicate their transition-related healthcare needs without fear of discrimination. Gender dysphoria could be another possible explanation for the statistically insignificant association. Since not all but most TGD people suffer from gender dysphoria, they may seek to use transition-related healthcare which is known to help alleviate gender dysphoria in spite of potentials for discrimination (Coleman et al., 2022).
A further noteworthy point in the results of this study is that the effect size was the largest and statistically significant when anti-transgender discrimination was experienced at both baseline and follow-up compared to when anti-transgender discrimination was experienced only at baseline or follow-up. These results can be suggested as clues to assess the effect of differences in the frequency or intensity of discrimination experiences on HAD. In other words, it may imply a cumulative effect of discrimination. However, since the confidence interval of each category of discrimination overlaps, further studies with a large sample and multiple follow-up waves are required to confirm this interpretation of our results.
This study proposes practice and policy implications for the social environment and access to healthcare that affect the health of TGD people. First, a nondiscriminatory attitude is needed for healthcare providers when they communicate with TGD people. Healthcare providers should respect patients with nonconforming gender identities and should not pathologize differences in gender identity or expression (Coleman et al., 2022). Healthcare providers’ discrimination and a lack of understanding on TGD people and their lives can directly affect transgender people’s health. For example, discrimination by healthcare providers may prevent TGD people from access to hospitals. For fear of stigma, TGD people may not go to the hospital to conceal their identity, even if they have an illness such as an infectious disease. This would not only deteriorate the health of the TGD individual, but it can lead to negative impacts on the public health.
Furthermore, TGD health protocols and culturally competency training for healthcare providers should be adopted given that they can help protect TGD people from discrimination as well as improve their health (Reisner et al., 2015). Healthcare providers can assist TGD people with gender incongruence to make decisions about undergoing gender-affirming medical or surgical treatments to alleviate their incongruence (Coleman et al., 2022). The lack of professional knowledge about on TGD people and their health and cultural competency among healthcare providers can result in inappropriate treatment of TGD patients. Especially, given that primary healthcare is the most commonly sought after by TGD people, appropriate training for primary healthcare providers is needed to improve their understanding of TGD health requirements (Winter et al., 2016).
Also, it is important to create an inclusive healthcare space for LGBT people, including transgender people. Explicit displays of items such as pride flags or LGBT-related leaflets, and books have been suggested as methods to enhance comfort for LGBT people in healthcare settings (Kuzma et al., 2019). Another way to increase transgender inclusivity in healthcare settings is to ensure safe access to bathrooms for TGD patients by installing gender-inclusive bathrooms in accessible areas of the building. TGD people are known to have difficulties using public bathrooms, which have shown to be significantly associated with their poor mental health (Lee et al., 2021). As such, equipping healthcare settings with gender-inclusive bathrooms would allow patients to use bathrooms that are congruent with their gender identity and improve access to care for TGD people.
Lastly, it is necessary to enact a comprehensive anti-discrimination law. As of 2023, there is no law prohibiting discrimination based on gender identity or gender expression in Korea. In 2007, the first anti-discrimination law was proposed in Korea. After that, the bill continued to be proposed, but it was repealed every time, centering on the anti-homosexual movement of conservative Christian churches (Yi & Kim, 2016). While unproductive discussions on the anti-discrimination law continue, TGD people in Korea continue to be exposed to discrimination and HAD. Anti-discrimination laws are required to protect TGD people from discrimination based on their gender identity and expression and to improve access to healthcare in a timely manner when they are injured or sick.
Limitations and strengths
This study has several limitations. First, this study cannot be generalized to the entire Korean TGD population because it used a non-probability sampling method. The methods of distribution of study participation materials we used may have led to over-representation of TGD people with higher awareness toward discrimination or unfair treatment. This would have overestimated the prevalence of discrimination experiences in this sample. To prevent this kind of selection bias, it is recommended that future studies collect participants with the method of probability sampling. In particular, if gender identity can be measured in a nationally representative survey, experiences of TGD people can be accurate assessed (Yi et al., 2022). Second, we divided HAD into transition-related HAD, and non-transition-related HAD, but did not specify the specific healthcare needs that were avoided or delayed within each category of HAD due to a lack of data. For example, it was not assessed whether transition-related HAD is hormone therapy or surgical surgery and whether non-transition-related HAD is preventive care or emergency medicine. Third, we could not stratify the associations between discrimination and HAD by transgender identities due to the small sample size. Lastly, another possibility of selection bias may exist. Participants who have suffered severe discrimination or experienced HAD may not have participated in the follow-up survey, which may move the estimates toward the null.
On the other hand, strengths of this study should be noted. This study is the first in Asia to use a nationwide longitudinal dataset on TGD people. In addition, this study is one of the few studies investigating the association between discrimination and HAD, and is the first longitudinal study of this association. Furthermore, this study excluded those who did not need healthcare services when evaluating the association between discrimination and HAD. Also, HAD was assessed by stratifying it into transition-related healthcare and general healthcare unrelated to transition. Moreover, this study adjusted for discrimination based on reason(s) other than transgender identity or gender expression, which may be important confounders in assessing the association between anti-transgender discrimination and HAD.
Conclusions
Building upon past literature that measured experiences of HAD in general, the current study further examined the association between anti-transgender discrimination and HAD by whether HAD was related to transition or not. This study showed that anti-transgender discrimination is associated with a higher prevalence of any HAD and non-transition-related HAD but not with transition-related HAD. These results suggest a need to promote nondiscriminatory attitude and awareness for transgender-specific health knowledge among healthcare providers. Moreover, the enactment of laws that prohibit discrimination is needed for transgender people to receive necessary healthcare in a timely manner.
Acknowledgments
The first author (Ranyeong Kim) was supported by the Health Fellowship Foundation of South Korea. The funding organizations had no role in the design and conduct of the study, in the collection, analysis, and interpretation of the data, and in the preparation, review, or approval of the manuscript. The authors would like to acknowledge the support of the professionals at the healthcare institutions involved in data collection. In addition, we also appreciate the transgender individuals who participated in our study.
Funding Statement
This study was supported by the Health Fellowship Foundation of the Republic of Korea.
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