Nonprescribed Sex Hormone Use Among Trans Women: The Complex Interplay of Public Policies, Social Context, and Discrimination

Abstract

Purpose: Trans women are systematically excluded from basic human rights, possibly due to social contexts of transphobia. In health care, such barriers may result in nonprescribed sex hormone use and lead to significant health complications. As few studies investigated this phenomenon, we analyzed factors associated with nonprescribed sex hormone use by trans women in seven municipalities of São Paulo, Brazil.

Methods: Muriel was a cross-sectional study (2014/2015), in which 673 transgender people answered a face-to-face survey. This analysis focused on trans women (n=616). Poisson regression models were used to assess factors associated with nonprescribed sex hormone use. A direct acyclic graph was built with a priori knowledge on the matter and was used for covariate selection.

Results: A total of 90.7% of participants reported ever taking sex hormones. Most of those detailed nonprescribed use, which was associated with sex work, starting to use hormones before 18, identifying as travesti and lower education. Having the chosen name honored in public health services was found to be protective against this outcome.

Conclusion: A high proportion of nonprescribed sex hormone use was observed in our sample. Our findings suggest barriers to health care and the need for trans women to resort to medically unsupervised transition procedures. Among sex workers, this may also be due to higher economic and access needs than other groups. Ensuring social rights and providing adequate health care services may lessen nonprescribed sex hormone use, preventing subsequent risks and resulting in better health outcomes for trans women.

Introduction

In Brazil, transgender women are systematically excluded from basic human and social rights due to their gender identity. Education experiences are marked by transphobia and exclusion, resulting in school dropouts and difficulties to navigate the educational system.¹ Interpersonal and institutionalized transphobia, stigma toward chosen name use, issues respecting the use of bathrooms, and rules of use of uniforms have been associated with low access and permanence in the job market,^2,3 compelling many to sex work.⁴ Access to general and specialized health care presents barriers such as having to inform providers about specific health care needs and dealing with discrimination.^5,6 In addition, trans women are frequently victims of harassment and physical violence and may be severely injured and murdered.

Brazil has the highest figures of transgender murder worldwide.⁷ This context is likely to play a role in the production and perpetuation of syndemics, comprising depression,^8–12 suicidal ideation and suicide,^8,9,12,13 harmful substance use,¹⁴ HIV risk behavior,¹³ and HIV infection.^15–17

On the contrary, trans women might wish to undergo medical procedures of body change to adequate their bodies to their own identities and enhance social acceptance and gender validation.^12,18,19 Genital surgery and sex hormone therapy may provide consistent improvement in mental health indicators, such as quality of life and self-esteem,¹² while reducing prevalence of depressive symptoms¹² and binge drinking episodes.^20,21

In Brazil, “travesties” and “trans women/transsexual women” are the most common terms used respecting the female spectrum of transgender persons whose gender identity does not correspond to sex assigned to them at birth. Although travesti was the earliest term used in Brazilian Portuguese (in that period, the word “transgender” was restricted to the vocabulary of some researchers [e.g., ethnographers], but it was not used by the population at large) to identify persons assigned male at birth who identified themselves as females, currently both terms coexist and the differences between them seem to be fluid and context-dependent.^22,23

As stated by Magno et al., “both terms relay differing levels of performance as a woman and claim the legitimacy of their identity beyond the binary parameters of masculine and feminine, adequacy of their physical image and their bodies using hormone therapy and silicone, desiring to be treated in the feminine and by the name with which they identified.”²⁴

Sex hormone therapy and other body change procedures had their offer first regulated in the Brazilian public health system in 2008 by ordinance 457, which established the so-called processo transexualizador package.²⁵ This set of procedures demanded the diagnosis of transsexualism²⁶ to initiate sex hormone therapy and clinical follow-up under the supervision of a multidisciplinary health care team and other procedures.²⁵ Despite being regarded as a breakthrough in terms of access, the “processo transexualizador” notably pathologized transgender identities as it was based on medical diagnosis; it was also limited to only those who manifest desire to have genital surgery, excluding the ones identified as travestis.²⁷ In 2013 a new ordinance was released, expanding the former initiatives, providing care and management to travestis, but keeping diagnostic requirements. This ordinance regulates hormone therapy and clinical follow-up for 18 or older trans women, and genital and other surgical procedures for 21 or older.²⁸

Notwithstanding its benefits, sex hormone therapy should be prescribed and monitored by at least one health care professional, as it can lead to life-threatening adverse effects.^29–31 Still, the nonprescribed use of sex hormone may be as high as 26.8–49.1% in different studies conducted in the United States^32,33 and Canada.³⁴ Trans women possibly acquire hormone through different ways, such as over the counter in drugstores, via the Internet, or from friends and acquaintances. In such cases, sex hormone use might be done in high doses and intermittently,³⁵ making adverse effects more likely.

At the same time, even where specific policies aiming to promote their access to health care are available, trans women often feel uncomfortable to talk to their providers about their health and frequently have to face discrimination in health care services due to their gender identity.^5,6 Framed in a context of psychological suffering and social oppression, translated as transphobia, rejection, sexual and self-objectification, such oppressive feelings and unpleasant experiences may intensify the need for gender affirmation. In circumstances of reduced access to gender-affirming procedures, such unmet needs may lead trans women to risky behaviors, including unprotected intercourse, harmful patterns of substance use, unsafe filler injection (usually performed by noncertified people), and hazardous sex hormone use.³⁶

Despite recent public health policies aiming to address the needs of the transgender population in Brazil, few population-based studies characterized factors associated with nonprescribed sex hormone use, as well as barriers to access sex hormone therapy in health care services.³⁷ To address this gap, we surveyed transgender people in health care and social welfare services in the state of São Paulo, Brazil.

Methods

Study design

This analysis is based on “Projeto Muriel: vulnerabilidades, demandas de saúde e acesso a serviços da população de travestis e transexuais do estado de São Paulo.” Muriel was a cross-sectional study conducted in seven municipalities of the state of São Paulo, Brazil, in 2014/2015. It was a mixed-methods study, combining qualitative and quantitative components. The quantitative component recruited potential participants in public health and social welfare services.

Participants

Expecting 30% loss, a sample size of 700 potential participants was estimated based on a preliminary assessment of potential participants reach in both facility- and street-based activities offered by these services, as there were no consistent data on population size. A consecutive quota sampling was then conducted, proportional to the previous assessment of each recruitment site. Participants answered an interviewer-administered semistructured questionnaire on basic sociodemographic information, professional experiences, general, sexual, and reproductive health indicators, access to services, violence, discrimination in different settings, transition procedures, and access to gender-affirming care. This study was approved by Comitê de Ética do CRT DST/Aids (CEPNCRT), securing informed consent to all participants.

Inclusion criteria were being 16 or older at survey date (1); identifying as transsexual/transexual, travesti, transgender/transgênero, or any other gender nonconforming identity (2); and living in the state of São Paulo for at least 6 months (3). For this analysis, a subsample of trans women was selected, excluding participants who reported any sex assigned at birth other than male.

Sociodemographic characteristics

Sociodemographic variables assessed were history of moving inside and/or outside the country (did not move, moved inside the country only, or moved outside Brazil); race/ethnicity (white, black, parda, Asian, or indigenous); education (less than elementary school, less than high school, high school, college or higher); employment status (currently employed, currently unemployed); sex work as current main occupation (yes, no); region of residency in the state (São Paulo city, São Paulo countryside, coastal area, ABC cities area); age (16–19, 20–29, 30–39, 40–49, 50 or older); and previous month individual income in monthly minimum wages (more than 4, from 1 to 4, less than 1).

Gender identity and stigma experiences

We also assessed gender identity (woman/mulher, transexual/transsexual, travesti, transgender/transgênero, other); age of initiation of hormone use (younger than 18, 18–24, 25 or older); chosen name honored by health care providers (always, eventually, never); ever experienced any discrimination due to gender identity (yes, no); ever experienced any violence due to gender identity (yes, no); ever experienced physical aggression due to gender identity (yes, no); ever experienced verbal aggression due to gender identity (yes, no); ever experienced humiliation, mobbing, or bullying due to gender identity (yes, no); ever experienced sexual harassment due to gender identity (yes, no); ever used fillers (yes, no); ever had health complications of filler use (yes, no); and ever had genital gender affirmation surgery (yes, no).

Predictor variables

Some categories of variables were collapsed in the bivariate and multivariate regression model analysis: region of residency in the state (São Paulo city, outside São Paulo); gender identity (travesti, other identities); and chosen name honored by health care providers (yes, no). Discrimination and violence in specific settings, sex hormone use, hormone acquisition means, and hormone formulation type were also described.

Outcome variable

The main binary outcome variable was “use of nonprescribed sex hormones,” extracted from the multiple spontaneous answer question “Where did/do you acquire your sex hormones?” for which only those who did not report ever taking hormones “prescribed by a public health provider” and/or “prescribed by a private health provider” were considered nonprescribed sex hormone users; participants who reported no sex hormone use were counted as missing.

Theoretical framework and statistical analyses

A direct acyclic graph (DAG) (Fig. 1) was built to summarize our a priori knowledge on direct and indirect causal pathways in which predictor variables may lead to or prevent nonprescribed sex hormone use.³⁸ As literature review found scarce quantitative evidence of how such factors play out, we based our DAG largely on a qualitative theoretical framework, combining gender affirmation theory and syndemic theory.^15,36,37

FIG. 1.

Direct acyclic graph for multivariate model covariate selection.⁵⁰ Arrows indicate presumed causal pathways; circular shapes indicate variables with their name below; green indicates variables included in the final multivariate model as exposures; blue with “I” in the middle indicates the outcome variable; red indicates confounders that were included in the final multivariate model; blue indicates variables that are ancestors of the outcome, but were not included in the final model; dark gray variables not included in the final model; light gray indicates latent variable. This figure was built with DAGitty, a free Internet-based environment for causal graph building.

Qualitative variables were described by absolute and relative frequencies, while numeric variables were described by mean and standard deviation. Chi-square tests were used to compare proportions of sex hormone use and possible associated variables. Poisson regression models with robust variance estimation were used to analyze association between the main outcome and predictor variables, as well as estimate prevalence ratios (PR), given the binary nature and high prevalence of the outcome.³⁹ Multivariate Poisson regression models provided adjusted PRs (aPR) to estimate the effect of independent variables on the main outcome. Covariate selection was done in three steps, first defining a set of hypothesized predictor variables, including only those that presented p<0.2 in bivariate regression models, then adding structural confounders found in the DAG (red), and finally proceeding to a purposeful selection of covariates⁴⁰ with the predictor variable set to define which variables would be kept as exposure variables (green), producing a DAG full model.³⁸ Note that a minimal set of confounder variables (ethnicity, region of residency, and age) found in the DAG were not submitted to purposeful selection, as causal criteria were prioritized over change-in-estimate criteria. Also, despite statically significant variables that had no hypothesized causal effect on the outcome (genital surgery, filler use, and health complication of filler use) not being included in the multivariate model, as such correlations might be spurious or give rise to collider bias.

Results

Six hundred seventy-three transgender people were recruited. This analysis describes a subset of this sample, made of those who identified with female identities such as travesti, mulher, transsexual, and transgênero (n=616), hereinafter referred as trans women. The mean age of trans women participants was 32.4 (± 9.9) years and 42.3% were between 20 and 29 years of age, and the subset was ethnically diverse with 44.3% self-identified as parda, 36.2% white, and 15.1% black; while 49.7% reported living in São Paulo city, 35.2% lived in the state countryside. Most (54.4%) had less than high school level of education, while 13.5% had college education or higher; 39.0% reported income lower than one minimum wage and 15.6% had an income higher than four. As of gender identity, 49.0% of the participants identified as travesti, 28.4% as transsexual, and 17.0% as woman; more than half (53.4%) trans women referred sex work as their main occupation (Table 1).

Table 1.

Sociodemographic Characteristics of Trans Women Surveyed in State of Sao Paulo, Brazil, 2014–2015 (n=616)

	N	%
Age
16–19	28	4.6
20–29	261	42.4
30–39	178	28.9
40–49	119	19.3
50+	30	4.9
Education
Postsecondary school or higher	83	13.5
Complete secondary school	198	32.1
Incomplete secondary school	175	28.4
Incomplete primary school	160	26.0
Race/ethnicity
White	223	36.2
Parda	273	44.3
Black	93	15.1
Asian and indigenous	25	4.1
Did not answer/did not know	2	0.3
Employment status
Currently employed	468	76.0
Currently unemployed	148	24.0
Income in monthly minimum wages
More than 4	96	15.6
From 1 to 4	280	45.5
Less than 1	240	39.0
Sex work as current main occupation
No	329	53.4
Yes	277	45.0
Did not answer/did not know	10	1.6
Region of residency
Sao Paulo city	306	49.7
Sao Paulo countryside	217	35.2
Coastal area	54	8.8
ABC area	39	6.3
Ever moved inside and/or outside the country
Did not move	133	21.6
Moved inside the country only	393	63.8
Moved outside the country	90	14.6

Overall (90.8%; 95% confidence interval [CI] 88.2–92.8), participants reported current or previous sex hormone use; 79.4% (95% CI 75.8–82.6) informed only using hormones without medical prescription (i.e., nonprescribed sex hormone use); among those who reported any sexual hormone use (n=559), the most common way to acquire hormones was over the counter at drugstores (84.4%), followed by prescription by a health provider (19.0%). The most commonly used hormone formulation reported was injectable progesterone and estrogen (33.5%) and the mean age for starting hormone use was 17.0 (±5.6). The majority (58.6%) of participants reported always having their chosen name honored in health care services and 8.8% never had (Table 2).

Table 2.

Gender Affirmation and Discrimination Among Trans Women Surveyed in State of Sao Paulo, Brazil, 2014–2015

	N	%
Chosen name use by health providers
Yes, always	361	58.6
Yes, eventually	196	31.8
No	54	8.8
Did not answer/did not know	5	0.8
Ever experienced discrimination for being trans (n=616)
No	79	12.8
Yes	529	85.9
Did not answer/did not know	8	1.3
Discrimination settings (n=529)
Work	374	70.7
Shop/commerce and leisure places	467	88.3
Health care services	260	49.2
School	365	69.0
Friends	252	47.6
Family	405	76.6
Religious sites	291	55.0
Police station	350	66.2
Social welfare services	99	18.7
Public transportation	341	64.5
Among neighbors	340	64.3
Partners	160	30.3
Public document and registration services	164	31.0
Did not answer/did not know	19	3.6
Ever experienced violence for being trans (n=616)
No	38	6.2
Yes	578	93.8
Violence type (n=578)
Physical aggression	389	67.3
Verbal aggression	539	93.3
Humiliation, mobbing, bullying	498	86.2
Sexual harassment	194	33.6
Blackmail, extortion	182	31.5
Police violence	291	50.3
Gender identity (n=616)
Woman	105	17.1
Transsexual	175	28.4
Travesti	302	49.0
Transgender	24	3.9
Other	9	1.5
Did not answer/did not know	1	0.2
Filler use (n=616)
No	331	53.7
Yes	285	46.3
Health complications of filler use (n=285)
No	163	57.2
Yes	121	42.5
Did not answer/did not know	1	0.4
Genital surgery (n=616)
No	602	97.7
Yes	14	2.3
Hormone use (n=616)
Yes, present use	336	54.6
Yes, previous use	223	36.2
No	57	9.3
Hormone acquisition means (n=559)
Drugstore	472	84.4
Work colleagues	39	7.0
“Bombadeiras”	2	0.4
Internet	2	0.4
SUS physician prescribed	106	19.0
Private physician prescribed	9	1.6
Others	6	1.1
Did not answer/did not know	1	0.2
Ever used nonprescribed hormones (n=559)
Yes	444	79.4
No	115	20.6
Current unprescribed hormone use (n=336)
Yes	229	68.2
No	107	31.9
Hormone type (n=559)
Oral estrogen	131	23.4
Oral progesterone and estrogen	152	27.2
Injectable progesterone and estrogen	187	33.5
Injectable progesterone	76	13.6
Antiandrogens	79	14.1
Testosterone	5	0.9
Others	181	32.4
Age of start of hormone use (n=559)
Older than 24 years	40	7.1
Between 18 and 24 years old	169	30.1
Younger than 18 years	339	60.8
Did not answer/did not know	11	2.0

There was no significant difference in the percentage of trans women using sex hormones by gender identity. Sex hormones were used by 86.7% in the 50 years and older trans women. Between race/ethnicity groups, the use was more frequent among black trans women (92.5%) than white (90.6%) and parda (90.1%). Also, we did not find differences between participants who, engaging in sex work as the current main occupation, used hormones (93.1%) and those who did not (88.8%) (Table 3).

Table 3.

Bivariate Correlates of Sex Hormone Use Among Transgender Women, Sao Paulo State, Brazil, 2014–2015 (n=616)

	Ever used sex hormones
	No, N (%)	Yes, N (%)	p
Race/ethnicity			0.73
White	21 (9.4)	202 (90.6)
Parda	27 (9.9)	246 (90.1)
Black	7 (7.5)	86 (92.5)
Other	1 (4.0)	24 (96.0)
Education			0.172
College and higher	13 (15.7)	70 (84.3)
High school	18 (9.1)	180 (90.9)
Less than high school	13 (7.4)	162 (92.6)
Less than elementary school	13 (8.1)	147 (91.9)
Region			0.709
Sao Paulo city	25 (8.2)	281 (91.8)
Sao Paulo countryside	24 (11.1)	193 (88.9)
Coastal area	5 (9.3)	49 (90.7)
ABC area	3 (7.7)	36 (92.3)
Age			0.760
16–19	3 (10.7)	25 (89.3)
20–29	24 (9.2)	237 (90.8)
30–39	13 (7.3)	165 (92.7)
40–49	13 (10.9)	106 (89.1)
50+	4 (13.3)	26 (86.7)
Monthly income (in minimum wages*)			0.867
More than 4	12 (12.5)	84 (87.5)
From 1 to 4	23 (8.2)	257 (91.8)
Less than 1	22 (9.2)	218 (90.8)
Gender identity			0.149
Woman	6 (5.7)	99 (94.3)
Transsexual	13 (7.4)	162 (92.6)
Travesti	32 (10.6)	270 (89.4)
Transgender	5 (20.8)	19 (79.2)
Other	1 (11.1)	8 (88.9)

^*Monthly minimum wages of the state in 2015.

Black trans women were more likely to use nonprescribed hormones when compared with white trans women (87.2% vs. 72.81%). The use of nonprescribed sex hormones was also more common among those who reported ever experiencing sexual harassment (85.1%) or physical aggression (82.5%) due to their gender identity; moreover, when compared with other identities, travestis reported nonprescribed sex hormone use more frequently (90.7%), while those who identified as women reported considerably less (59.6%). Even though only 14 participants had genital surgery, nonprescribed sex hormone use was markedly low (28.6%) among this group. Among participants who reported current or previous sex hormone use (n=559), nonprescribed use was higher when trans women had previously used fillers (87.3%). The use of nonprescribed sex hormone and its bivariate correlates can be found in Table 4.

Table 4.

Bivariate and Multivariate Correlates of Nonprescribed Hormone Use Among Transgender Women, Sao Paulo State, Brazil, 2014–2015 (n=558)

	Ever used nonprescribed hormones		Bivariate models			Multivariate model
	No, N (%)	Yes, N (%)	PR	p	95% CI	aPR	p	95% CI
Moved				0.081
Did not move	31 (27.19)	83 (72.81)	1	—	—	—	—	—
Moved inside or outside Brazil	84 (18.92)	360 (81.08)	1.13	0.081	—	—	—	—
Race/ethnicity				0.025
White	53 (19.51)	148 (73.63)	1	—	—	1	—	—
Parda	48 (19.51)	198 (80.49)	1.09	0.091	0.99–1.21	1.05	0.308	0.96–1.15
Black	11 (12.79)	75 (87.21)	1.18	0.004	1.05–1.33	1.09	0.130	0.97–1.23
Asian and indigenous	3 (12.50)	21 (87.50)	1.19	0.050	1.00–1.41	1.11	0.247	0.93–1.32
missing	0	1 (100)	—	—	—	—	—	—
Education				<0.001
College or higher	27 (38.57)	43 (61.43)	1	—	—	1	—	—
High school	50 (27.78)	130 (72.22)	1.18	0.125	0.96–1.45	1.09	0.386	0.89–1.34
Less than high school	23 (14.29)	138 (85.71)	1.40	0.001	1.15–1.70	1.21	0.052	1.00–1.48
Less than elementary school	15 (10.20)	132 (89.80)	1.46	< 0.001	1.20–1.77	1.23	0.037	1.01–1.50
Employment				0.571
Currently employed	85 (20.05)	339 (79.95)	1	—	—	—	—	—
Currently unemployed	30 (22.39)	104 (77.61)	1.03	0.571	0.93–1.14	—	—	—
Sex work (as current main occupation)				<0.001
No	87 (29.90)	204 (70.10)	1	—	—	1	—	—
Yes	25 (9.69)	233 (90.31)	1.28	< 0.001	1.18–1.40	1.17	< 0.001	1.07–1.28
Region				0.414
Sao Paulo city	54 (19.22)	227 (80.78)	1	—	—	1	—	—
Outside São Paulo city	61 (22.02)	216 (77.98)	0.97	0.414	0.89–1.05	0.94	0.144	0.87–1.02
Age				0.185
16–19	5 (20.00)	20 (80.00)	1	—	—	—	—	—
20–29	38 (16.03)	199 (83.97)	1.05	0.642	0.86–1.29	1.04	0.691	0.86–1.26
30–39	41 (24.85)	124 (75.15)	0.94	0.569	0.76–1.16	1.02	0.877	0.83–1.25
40–49	23 (21.70)	83 (78.30)	0.98	0.849	0.79–1.22	1.07	0.528	0.86–1.33
50 or older	8 (32.00)	17 (68.00)	0.85	0.339	0.61–1.19	0.97	0.865	0.71–1.33
Monthly income (in minimum wages*)				0.867
More than 4	19 (22.62)	65 (77.38)	1	—	—	—	—	—
From 1 to 4	51 (19.84)	206 (80.16)	1.04	0.597	0.91–1.18	—	—	—
Less than 1	45 (20.74)	172 (79.26)	1.02	0.726	0.90–1.17	—	—	—
Chosen name use by health providers				0.016
No	111 (21.64)	402 (78.36)	1	—	—	1	—	—
Yes	4 (10.00)	36 (90.00)	0.87	0.016	0.78–0.97	0.83	<0.001	0.75–0.92
Ever experienced discrimination for being trans				0.787
No	11 (15.94)	58 (84.06)	1.00	—	—	—	—	—
Yes	100 (20.79)	381 (79.21)	0.98	0.787	0.87–1.10	—	—	—
Ever experienced violence for being trans				0.238
No	10 (8.70)	105 (91.30)	1	—	—	—	—	—
Yes	23 (5.19)	420 (94.81)	1.15	0.238	0.91–1.44	—	—	—
Ever experienced physical aggression				0.020
No	53 (26.24)	149 (73.76)	1	—	—	—	—	—
Yes	62 (17.42)	294 (82.58)	1.11	0.020	1.01–1.23	—	—	—
Ever experienced verbal aggression				0.103
No	20 (29.41)	48 (70.59)	1	—	—	—	—	—
Yes	95 (19.39)	395 (80.61)	1.14	0.103	0.97–1.33	—	—	—
Ever experienced humiliation, mobbing, or bullying				0.795
No	22 (21.57)	80 (78.43)	1	—	—	—	—	—
Yes	93 (20.39)	363 (79.61)	1.01	0.795	0.90–1.13	—	—	—
Ever experienced sexual harassment				0.013
No	88 (23.34)	289 (76.66)	1	—	—	—	—	—
Yes	27 (14.92)	154 (85.08)	1.10	0.013	1.02–1.20	—	—	—
Gender identity				<0.001
Other identities	89 (30.90)	199 (69.10)	1	—	—	1	—	—
Travesti	25 (9.29)	244 (90.71)	1.31	<0.001	1.20–1.43	1.18	< 0.001	1.08–1.28
Filler use				<0.001
No	79 (27.53)	208 (72.47)	1	—	—	—	—	—
Yes	36 (13.28)	235 (86.72)	1.20	<0.001	1.10–1.30	—	—	—
Health complications of filler use				0.005
No	100 (22.73)	340 (72.77)	1	—	—	—	—	—
Yes	15 (12.71)	103 (87.29)	1.12	0.005	1.03–1.23	—	—	—
Genital gender affirmation surgery				0.014
No	105 (19.30)	439 (80.70)	1	—	—	—	—	—
Yes	10 (71.43)	4 (28.57)	0.35	0.014	0.15–0.81	—	—	—
Age of start of hormone use				0.015
25 or older	20 (50.00)	20 (50.00)	1	—	—	1	—	—
18–24	40 (23.67)	129 (76.33)	1.52	0.010	1.10–2.10	1.39	0.045	1.01–1.91
Younger than 18	52 (15.34)	287 (84.66)	1.69	0.001	1.23–2.31	1.47	0.018	1.07–2.02

Bold indicates race/ethnicity general p-values in the regression instead of the category p-values.

^*Monthly minimum wages of the state in 2015.

In multivariate analysis adjusted for ethnicity, age, and region of residency, starting to use hormones before the age of 18 years (aPR 1.47, 95% CI 1.07–2.02); less than elementary school education (aPR 1.23, 95% CI 1.01–1.50); sex work as current main occupation (aPR 1.17, 95% CI 1.07–1.28), and travesti gender identity (aPR 1.18, 95% CI 1.08–1.28) were predictors of nonprescribed hormone use. Furthermore, having the chosen name honored in health care services was protective (aPR 0.83, 95% CI 0.75–0.92) against this practice (Table 4).

Discussion

In our study, participants with a lower education, who began using sex hormone earlier in life, sex workers, and those who identified as travesti were more likely to use nonprescribed sex hormones. Such findings support the existence of barriers to access due to the consequence of constrained resources to transition procedures performed at health care services, and also the existence of specific barriers for specific subgroups. Those self-identified as travesti, possibly due to the late inclusion in the “processo transexualizador” and the consequent diminished access to resources/accredited facilities,⁴¹ were more likely to use nonprescribed hormones. This explanation, however, is restricted to a narrow understanding of the historical processes shaping gender identity names, as well as the social function of the category boundaries, a deeper discussion beyond the scope of this study.

The accentuated use of nonprescribed hormones among trans women sex workers may be understood similarly to filler injections,⁴² as a means to attain desired body changes faster. That may be translated into attractiveness and possible increase of income.⁴³ Furthermore, sex work may act as a source of gender affirmation, as trans women are submitted to objectification in similar ways of cis-gender women,³⁶ reinforcing desire for faster body changes. Note that sex work was not specified in our survey, and may comprise safe, fairly paid conditions, as well as compulsory or subsistence sex work, therefore limiting interpretation of related findings.

Nonprescribed hormone use was also associated with early initiation, before the age limits of “processo transexualizador,” available on public health services exclusively for people aged 18+.²⁵ This requirement does not appear to prevent early sex hormone use but rather to foster nonprescribed use, setting another barrier to proper care. Notwithstanding, there is evidence that pubertal hormone suppression with GnRH analogues is safe and may decrease rates of depression and improve global functioning among transgender youth.⁴⁴ It has been recommended to be initiated timely, at the beginning of clinically observed puberty.⁴⁴ In addition, guidelines support the initiation of sex hormone therapy at the age in which the person is capable of giving informed consent, around 16 years old in most contexts.⁴⁵

Lower education levels also seem to be associated with nonprescribed hormone use, which is in line with the understanding of education and its benefits, at individual and community levels. Education can function as gateways to reduction of poverty, greater access to resources, and empowerment.⁴⁶ One study, carried out in San Francisco, USA,³² showed an association between nonprescribed sex hormone use and previous experience of verbal abuse; despite not being considered in the present analysis, this correlation could be useful to interpret the protective effect of having one's chosen name honored by health care providers, since this public policy aims to minimize the incidence of a specific sort of verbal abuse at health facilities.^47,48

Our study found a high proportion of nonprescribed sex hormone use among trans women in São Paulo, Brazil. When compared with different studies carried out in North America,^32–34 the observed proportion in our study is higher—which is likely due to lack of accessible services. This unsupervised use of sex hormones may give rise to general health concerns. Despite scarce data on cardiovascular risk of sex hormone use among trans women, high doses of oral ethinyl estradiol, available over the counter and via the Internet, have been associated with venous thrombosis and increased cardiovascular mortality.³⁰ Effects on incidence of breast cancer, associated with hormone therapy on postmenopausal cis-women, meningioma, is more prevalent among cis-women when compared with cis-men, as well as the differential prevalence of other malignancies remains hypothetical.⁴⁹

We also observed a preference for drugstore acquisition of sex hormones. The most common formulations were injectable progesterone and estrogen, followed by oral combinations of progesterone and estrogen, frequently indicated for female contraception and easily obtained over the counter.

Sociodemographic description showed high proportions of unemployment and sex work as the current main occupation. These findings show the precarious insertion of transgender women in the job market, still marked by insufficient job offer and the need to rely on sex work. The frequent occurrence of gender-related discrimination and violence in the same population should not be understood as casual, but suggestive of syndemic dynamics.¹⁵ This interplay of harmful effects often precipitates adverse health outcomes and higher mortality.^16,17

This study could not draw a probability sample and should be defined as exploratory, providing sound foundations for future, more refined, studies. Impossibility of defining reliable sampling frames may have led to selection bias. Our strategy might have oversampled more connected trans women social networks. Furthermore, enrollment from health care and social welfare services may have undersampled trans women who do not access health care services, possibly underestimating nonprescribed sex hormone use and other indicators. To minimize that, trans women reached by preventive activities carried out by the social and health services were included. Another limitation is the a priori defined age inclusion criteria, comprising people 16 years and older, possibly underestimating relevant exposures, such as the early start of hormone use. In this analysis, the choice for an exploratory approach with multiple independent variables included in the multivariate model may give rise to spurious associations and collinearity problems. To mitigate these effects, at the final model, covariate selection was based on structural criteria observed in the DAG built by the study team, profiting from a priori knowledge of studied phenomena.

Conclusion

Despite its limitations, this study might help to establish directions for future population-based surveys and analysis on this matter, as we found no local precedents of trans women sex hormone use investigations. It also provides additional evidence of lack of access to transition-related care, especially in the use of sex hormones, aiming to better understand its underlying structure and entangled factors, as it reveals to be closely associated with adverse social conditions.

Gender affirmation is a useful theoretical framework to better understand the complex links between social oppression and psychological distress vis-à-vis health disparities in a context of sexual and self-objectification. Our findings highlight some of the consequences of the interplay of gender-affirming and potentially harmful procedures. Further research should explore in detail other consequences for the health of transgender population in a broader sense.

Notwithstanding, gender affirmation is key to guide strategies that may help to mitigate those disparities, as exemplified by the positive effect of using chosen names (as documented by the international literature). Our findings suggest that policies need to take gender affirmation into account, what should not mean to neglect structural inequalities. In a context where social, racial, and gender inequalities are so pronounced such as in Brazil, structural interventions are key to the efforts to make health care to transgender women accessible, nonjudgmental, and comprehensive.

Abbreviation Used

DAG

direct acyclic graph

Disclaimer

Some of the preliminary results of this analysis were presented as an abstract in the International AIDS Society's 9th HIV Science Conference during July 23–26, 2017, Paris, France.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

“Projeto Muriel: vulnerabilidades, demandas de saúde e acesso a serviços da população de travestis e transexuais do estado de São Paulo” was funded by Fundação de Amparo à Pesquisa do Estado de São Paulo (Fapesp; process number 2013/22366-7).

Cite this article as: Maschião LF, Bastos FI, Wilson E, McFarland W, Turner C, Pestana T, Veras MA (2020) Nonprescribed sex hormone use among trans women: the complex interplay of public policies, social context, and discrimination, Transgender Health 5:4, 205–215, DOI: 10.1089/trgh.2020.0012.