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. Author manuscript; available in PMC: 2026 Jan 2.
Published before final editing as: Psychol Sex Orientat Gend Divers. 2025 Jan 2:10.1037/sgd0000794. doi: 10.1037/sgd0000794

Prevalence and Correlates of Nonsuicidal Self-Injury Among Transgender People: Results from a U.S. Probability Sample

Kasey B Jackman 1,2, Walter O Bockting 1,3, Shahrzad Divsalar 4, Winston Luhur 5, Sarah I Leonard 6,*, Andy Lin 4, Ilan H Meyer 7
PMCID: PMC12439629  NIHMSID: NIHMS2057629  PMID: 40964447

Abstract

Nonsuicidal self-injury (NSSI), intentional harm to the body without intent to die, is a major public health concern. Transgender people may be at higher risk for NSSI compared to cisgender peers, but evidence is limited regarding prevalence, demographic correlates, and risk factors. This study is the first to examine NSSI in a probability sample of the U.S. transgender population. We analyzed data from the first U.S. nationally representative sample of transgender people which was recruited through random-digit-dial methods and address-based sampling. Using logistic regression, we examined associations between demographic factors, minority stress processes, early life adversity, and lifetime history of NSSI. The sample consisted of 270 transgender individuals; 144 (53.3%) were transfeminine or nonbinary assigned male at birth and 126 (46.7%) were transmasculine or nonbinary assigned female at birth. The mean age was 34.2 (SD = 17.1, range: 18–81); 68.5% identified as non-Hispanic White and 31.5% as Black, Latino, or multi-race. NSSI was reported by 50% of the sample. Victimization and discrimination, adverse childhood experiences, lower nonconformity in childhood gender expression, and transgender community connectedness were associated with higher odds of NSSI. NSSI is common among transgender people in the U.S. Victimization and discrimination, adverse childhood experiences, and factors related to gender identity development may increase vulnerability to NSSI. Additional research is needed to better understand the relationships between these variables and NSSI. Findings can inform tailored interventions to address specific risk factors that affect this population.

Keywords: Transgender, nonbinary, nonsuicidal self-injury, mental health, minority stress

Introduction

Transgender people, whose gender identity differs from their sex assigned at birth, experience multiple health disparities and have been designated by the National Institutes of Health as a health disparity population (Institute of Medicine, 2011; Pérez-Stable, 2016). Studies reveal significant mental health disparities among transgender people compared to cisgender (i.e., non-transgender) peers including suicidal thoughts and behaviors, depression, anxiety, and substance use (Dhejne et al., 2016; Kidd et al., 2023; Reisner et al., 2016; Tupler et al., 2017). Evidence suggests the mental health disparities include nonsuicidal self-injury (NSSI) (Davey et al., 2016; Marshall et al., 2016), which refers to intentional harm to the body’s surface without intent to die (Nock, 2010). NSSI is a significant public health problem due to its high correlation with suicidal thoughts and behaviors and other mental health problems (Klonsky et al., 2013; Nock et al., 2006).

According to the minority stress model, mental health disparities among transgender people are related to the chronic stressors perpetuated against transgender people interpersonally, in institutions, and on a societal level (Hendricks & Testa, 2012; Meyer, 2003). Minority stress processes are described in two categories: distal to proximal. Distal minority stressors, also referred to as enacted stigma, include observable events such as victimization, harassment, and discrimination (Meyer, 2003). These contribute to proximal minority stress processes, also referred to as felt stigma, which include expectations of rejection, efforts to conceal one’s gender identity, lack of affirmation of one’s gender identity by others, and internalized stigma about one’s gender identity (i.e., internalized transphobia) (Bockting et al., 2016; Bockting et al., 2020; Hendricks & Testa, 2012; Meyer, 2003). Studies support the deleterious effects of minority stress on the mental health of transgender people as well as the buffering effects of resilience factors such as transgender community connectedness and social support (Austin & Goodman, 2017; Bockting et al., 2013; Tebbe & Moradi, 2016; Testa et al., 2017; Zeluf et al., 2018). These represent modifiable resilience factors that can be addressed in clinical practice and by community-based interventions.

Limited evidence suggests that NSSI may differ by subgroup of the transgender population with people who are transmasculine or nonbinary assigned female sex at birth reporting higher rates of NSSI compared to people who are transfeminine or nonbinary assigned male sex at birth (Marshall et al., 2016). Findings from previous research examining minority stressors in relation to NSSI among transgender people have been mixed (Breslow et al., 2020; Jackman, Dolezal, et al., 2018; Jackman, Edgar, et al., 2018; Staples et al., 2018). In one study, NSSI was associated with felt stigma, but not enacted stigma, whereas congruence between gender identity and gender expression was associated with lower odds of NSSI in the past year (Jackman, Dolezal, et al., 2018). Gender-affirming care that fosters such congruence may thus result in better psychological adaptation among transgender people (Breslow et al., 2020). However, other researchers identified a pattern of association between enacted stigma and NSSI among transgender people with high internalized transphobia, but this association did not reach statistical significance (Staples et al., 2018). In a qualitative study of NSSI among transmasculine people, participants highlighted the ways that proximal minority stress processes such as expectations of rejection and concealment of one’s transgender identity contributed to NSSI (Jackman, Edgar, et al., 2018).

According to Nock’s theoretical model of NSSI, risk factors for NSSI also include adverse childhood experiences such as abuse or maltreatment and family hostility or criticism (Nock, 2010). Research indicates that adverse childhood experiences, including experiences such as sexual abuse and neglect, are highly prevalent among transgender people (Craig et al., 2020; Fontanari et al., 2018; Suarez et al., 2021) and are associated with long-term negative mental health outcomes (Fontanari et al., 2018; Suarez et al., 2021). Additionally, nonconformity in childhood gender expression, which is present among some transgender people (Grossman et al., 2006), contributes to the likelihood of abuse and victimization by peers and family, as well as long-term negative mental health sequelae (Roberts et al., 2012; Roberts et al., 2013). Qualitative research has linked stress from others’ reactions to nonconformity in childhood gender expression to NSSI among transmasculine people (Jackman, Edgar, et al., 2018). Transgender adolescents also report higher rates of bullying and peer victimization compared to cisgender counterparts (Jackman et al., 2019; Pampati et al., 2020), which has been shown to be associated with anxiety, depression, and low self-esteem (Witcomb et al., 2019).

The existing research on NSSI among transgender people has been limited by a reliance on convenience and nonprobability samples (Davey et al., 2016; Marshall et al., 2016). Studies have used samples of transgender people recruited in clinical settings or at transgender conferences (Marshall et al., 2016), precluding generalization of findings to transgender people outside of these settings. This leaves a critical gap. The prevalence of NSSI among transgender people outside of these specific settings remains unknown, as does its relationship with demographic factors and potential risk factors. To fill this important gap, we studied NSSI using data from the first study of a national probability sample the U.S. transgender population. In this sample, we aimed to (1) examine the prevalence of NSSI, (2) analyze associations between demographic factors, minority stress processes, early life adversity, and NSSI.

Methods

Sampling, Recruitment and Data Collection

We used data from the first nationally representative sample of the U.S. population of transgender adults, aged 18 years and older, with access to phone or mailings. Data were collected between April 2016 and August 2016 and between June 2017 and December 2018 as part of the U.S. Transgender Population Health Survey (TransPop; www.transpop.org). Gallup Inc. recruited respondents through random-digit-dial methods of cell phones and landlines. Then, in January 2018, following industry trends, it switched to address-based sampling. Respondents were eligible if they (1) had a 6th grade education or higher, (2) were aged 18 years or older, (3) were transgender, and (4) were able to complete the survey in English. Transgender identity was measured based on a two-step question where respondents are first asked for their sex assigned at birth and then asked about their current gender identity. Respondents whose sex at birth differed from their current gender identity and those who identified as “transgender” as their current gender identity (regardless of sex at birth) were classified as transgender and deemed eligible for the TransPop survey. Eligible respondents were emailed a web link or mailed a paper questionnaire to self-administer the survey. Respondents who agreed to participate were provided a $25 gift certificate (by email) or $25 cash (by mail). In total, 581,844 respondents were screened and 0.21% identified as transgender.

The final sample size for the TransPop study is 274, representing a cooperation rate of 28.7% calculated as completed surveys out of study-eligible people. Two respondents indicated their sex at birth as female and gender identity as transgender woman. We excluded these two respondents from analysis for this study because we could not determine their transfeminine or transmasculine identity according to our definition (as described in the Introduction section).

Missing data occurred at low percentages across variables, specifically missing data for NSSI was 0.73% (n = 2). These two respondents were excluded from the analysis. We imputed missing data due to non-response except for the outcome variable (NSSI). We used single imputation by chained equations (fully conditional specification), using predictive mean matching (Krueger et al., 2020). We applied sample weights to account for non-response (e.g., eligible individuals who did not opt-in to the study, individuals who opted-in but did not complete the survey) and selection probability. Sample weights were based on a national sample of sexual and gender minority people that had previously been recruited by Gallup as well as national demographics.

Study and consent protocol was approved by the University of California, Los Angeles IRB and IRBs of collaborating institutions. Additional documentation of study methodology and population demographics are described elsewhere (Krueger et al., 2020). Data are available upon request from the authors.

Measures

Outcome: Lifetime Nonsuicidal Self-Injury.

Nonsuicidal self-injury was assessed with the item “Did you ever do something to hurt yourself on purpose, but without wanting to die (e.g., cutting yourself, hitting yourself, or burning yourself)?” (Ursano & Stein, n.d.). We collapsed the response options, “Yes, once,” “Yes, more than once,” and “No,” into two responses, “Yes” and “No,” for analysis (1= yes, 0 = no).

Sociodemographic variables

Sociodemographic variables included self-reported age, race, ethnicity, income (dichotomized to below the federal poverty level or not), education, and sexual identity (dichotomized to heterosexual or sexual minority, i.e., non-heterosexual).

Transfeminine and Transmasculine spectrum identity.

We classified respondents as transfeminine or transmasculine based on their self-reported gender identity and sex assigned at birth. Gender identity was assessed by the question: “Do you currently describe yourself as a man, woman, or transgender?” Participants who selected the response option transgender were then asked: “Are you…?” with response options “trans woman (male-to-female),” “trans man (female-to-male),” and “non-binary/genderqueer.” Sex assigned at birth was assessed with the question: “On your original birth certificate, was your sex assigned as female or male?” We categorized respondents who reported their gender identity as woman, trans woman (male-to-female), or non-binary/genderqueer, and their sex assigned at birth as male, as transfeminine. We categorized respondents who reported their gender identity as man, trans man (female-to-male), or non-binary/genderqueer, and their sex assigned at birth as female, as transmasculine.

Nonbinary Gender Identity.

We categorized respondents who reported their gender identity as “non-binary/genderqueer” as nonbinary (1), and all others as binary (0).

Minority Stress Processes

Distal Minority Stressors.

We analyzed measures of five distal minority stressors.

Victimization and Discrimination.

Victimization and discrimination were assessed based on respondents’ answers to six items regarding experiences being victimized or discriminated against since the age of 18 (Herek, 2009). Items included “You were hit, beaten, physically attacked or sexually assaulted,” “Someone threw and object at you,” and “Someone threatened you with violence.” Response options included “Never” (0), “Once” (1), “Twice” (2), or “Three or more times” (3). For this investigation, we calculated a mean score across all 6 items which could range from 0 to 3, with higher scores indicating more frequent experiences of victimization and discrimination.

Everyday Discrimination.

Everyday discrimination was assessed with the 9-item Everyday Discrimination Scale (Cronbach’s alpha=.92 in this sample) which includes items related to experiences of unfair treatment and discrimination on a day-to-day basis (Williams et al., 1997). Items included “You were treated with less courtesy than other people,” “You were treated with less respect than other people,” and “You were called names or insulted.” Participants were asked to report experiences over the past year. Responses for each discrimination experience were recorded on a 4-point Likert scale ranging from “often” to “never.” We calculated a mean score across the 9 items. Mean scores could range from 1 to 4 where a higher score indicated more frequent discrimination.

Interpersonal Stressful Life Events.

Interpersonal stressful life events was assessed with an adapted version of the stressful life events measure in the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) Wave 2 (National Institute on Alcohol Abuse and Alcoholism, 2007). Four items were used to assess respondents’ interpersonal stress in the past 12 months. Items used were “Did you move or have anyone new come to live with you?” “Have you had trouble with your boss or a coworker?” “Did you get separated or divorced or break off a steady relationship?” and “Have you had serious problems with a neighbor, friend or relative?” We summed the number of “yes” responses across the 4 items to calculate a final composite score ranging from 0–4.

Employment-related Stressful Life Events.

Employment-related stressful life events were also assessed with a modified version of the stressful life event measures in the NESARC Wave 2 (National Institute on Alcohol Abuse and Alcoholism, 2007). Select stressful life event items related to employment and finances were used to assess the degree to which a respondent experienced job-related or financial stress in the past 12 months. Items used were “Were you fired or laid off from a job?” “Were you unemployed and looking for a job for more than a month?” “Did you change jobs, job responsibilities or work hour?” and “Have you experienced a major financial crisis, declared bankruptcy or more than once been unable to pay your bills on time?” We counted the number of “yes” responses across these 4 items to create a final composite score ranging from 0–4.

Non-Affirmation of Gender Identity.

Non-affirmation of gender identity was measured using a 6-item scale (Cronbach’s alpha=.93 in this sample) to assess the degree to which a one’s gender identity is not affirmed by others (Testa et al., 2015). Response options are based on a 5-point Likert scale from “strongly disagree” to “strongly agree.” We calculated the final scale score as a mean of the 6 items with scores ranging from 1 to 5.

Proximal Minority Stress Processes.

We analyzed three proximal minority stress processes.

Gender Identity Non-Disclosure.

Gender identity non-disclosure was assessed with a 5-item scale (Cronbach’s alpha=.76 in this sample) measuring the degree to which a respondent conceals their gender identity from others (Testa et al., 2015). Response options are based on a 5-point Likert scale ranging from “strongly disagree” to “strongly agree.” We calculated the final scale score as a mean of the 5 items with scores ranging from 1 to 5.

Negative Expectation for Future Events.

Negative expectation for future events was measured with a 9-item scale (Cronbach’s alpha=.91 in this sample) which assessed the degree to which a respondent expected rejection due to their gender identity (Testa et al., 2015). Response options were based on a 5-point Likert scale from “strongly disagree” to “strongly agree.” We calculated a final scale score as a mean of the 9 items with scores ranging from 1 to 5.

Internalized Transphobia.

Internalized transphobia was measured using a 6-item scale (Cronbach’s alpha=.86 in this sample) to assess the degree a respondent has internalized negative beliefs about one’s own transgender identity (Testa et al., 2015). Response options are based on a 5-point Likert scale from “strongly disagree” to “strongly agree.” We calculated the mean of the 6 items as a final score, with scores ranging from 1–5.

Coping and Social Support Variables.

We analyzed two coping and social support variables.

Social Support.

Social support was measured with the Multidimensional Scale of Perceived Social Support, a 12-item scale (Cronbach’s alpha=.92 in this sample) (Zimet et al., 1990). Responses were recorded on a 7-point Likert scale ranging from “very strongly disagree” to “very strongly agree,” with neutral in the middle. We calculated the mean of the 12 items as the final score, with scores ranging from 1 to 7.

Transgender Community Connectedness.

Transgender community connectedness was assessed with a 5-item scale (Cronbach’s alpha=.78 in this sample) that measured respondents’ strength of affiliation to a transgender community (Testa et al., 2015). Examples of items included “I feel a part of a community of people who share my gender identity” and “I feel isolated and separate from other people who share my gender identity” (reverse coded). Responses for each item were recorded on a 5-point Likert scale ranging from “strongly disagree” to “strongly agree.” We calculated the final scale score as a mean of the 5 items with scores ranging from 1 to 5.

Early Life Adversity

Nonconformity in childhood gender expression.

This scale measured discordance between prescribed gender roles and gender behavior in childhood (Zucker et al., 2006). Responses were recorded on a 5-point Likert scale where the lowest values represent the most masculine behaviors, the highest values represent the most feminine behaviors, and middle values represent equally masculine and feminine behaviors. We calculated a nonconformity in childhood gender expression score using the mean score of all items compared to the respondent’s sex at birth. Consistent with previous research (Reisner et al., 2014; Roberts et al., 2012), we generated a final categorical score by determining whether the gender expression nonconformity score fell within the top decile of nonconformity scores for the sample (most gender nonconforming), between the median and top decile, or below the median (least gender nonconforming), with percentiles calculated separately by sex assigned at birth.

Adverse Childhood Experiences.

Adverse childhood experiences were assessed using an 11-item scale (Cronbach’s alpha=.76 in this sample) (Centers for Disease Control and Prevention, 2010). We combined items based on eight categories of adverse childhood experiences: emotional abuse, physical abuse, sexual abuse, household intimate partner violence, household substance use, household mental illness, parental separation or divorce, and incarcerated household member. We summed the eight resulting categories to form a final score ranging from 0 to 8.

Bullying.

Bullying was assessed with the question “How often, if ever, were you bullied before you were 18 years old?” (Meyer et al., 2016). We collapsed the response choices “often,” “sometimes,” “rarely,” and “never” into “often/sometimes” (=1) and “rarely/never” (=0).

Statistical Analysis

We conducted bivariate analyses to test for differences in demographic variables, minority stress processes, and early life adversity between respondents who reported lifetime NSSI and respondents who reported no lifetime NSSI. We used logistic regression models to estimate the associations, expressed as odds ratios (ORs), of demographic variables, minority stress processes, and early life adversity with the outcome lifetime NSSI. Model 1 included only demographic variables, while Model 2 included demographic variables and minority stress processes, and Model 3 included demographic variables, minority stress processes, and early life adversity. We ran each additional model to test whether the effect and magnitude of effect held after adjusting for confounders in the previous model. In Models 2 and 3, we only included minority stress processes and early life adversity variables that were significantly associated with NSSI at the bivariate level. We did not interpret effect size and confidence intervals associated with variables as significant unless the overall test was significant. We set level of significance at p < .05. We conducted all analyses in Stata version 16.1 using the sampling weights to generate population estimates.

Results

Of the total sample (N = 270), 50.0% reported NSSI in their lifetime (Table 1). Results of the bivariate analyses of differences between participants who did versus did not report lifetime NSSI are included in Tables 1 and 2. The results of the logistic regression models examining associations between minority stress processes, early life adversity, and NSSI are included in Table 3. In Model 1, which included only demographic factors, we found that 4 variables (age, race, nonbinary gender identity, and education) were significantly associated with NSSI. Nonbinary gender identity became non-significant with the addition of minority stress processes in Model 2. In the fully adjusted (third) model, the other three demographic factors remained significantly associated with NSSI: age, race, and education. Age was associated with lower odds of NSSI such that for each 1-year increase in age, the odds of NSSI decreased by a factor of 0.93 (AOR = 0.93, 95% CI: 0.90–0.97). Regarding race, compared to White participants, Black participants had lower odds of NSSI (AOR = 0.07, 95% CI: 0.02–0.30). Finally, compared to participants with more than a college degree, those with a college education had higher odds of NSSI (AOR = 4.31, 95% CI: 1.05–17.7).

Table 1.

Sociodemographic correlates of lifetime nonsuicidal self-injury (NSSI) among a U.S. probability sample of transgender people (N = 270).

YES Lifetime NSSI (n = 135) NO Lifetime NSSI (n = 135) Design-based F
n Weighted % or Mean 95% CI or ±SD n Weighted % or Mean 95% CI or ±SD
SOCIODEMOGRAPHIC CHARACTERISTICS
Gender identity/assigned sex at birth
 Transmasculine/female at birth 78 59.9 [49.0, 70.0] 48 45.9 [34.7, 57.6] 3.0
 Transfeminine/male at birth 57 40.1 [30.0, 51.0] 87 54.1 [42.4, 65.3]
Nonbinary gender identity
 Binary identity 84 58.4 [47.3, 68.7] 110 80.9 [70.4, 88.3] 9.3 **
 Nonbinary identity 51 41.6 [31.3, 52.7] 25 19.1 [11.7, 29.6]
Age (mean) 135 28.1 9.6 135 41.9 17.4 44.4 ***
Race and ethnicity
 White 101 60.4 [49.0, 70.8] 84 51.5 [40.0, 62.8] 2.7 *
 Black 5 3.4 [1.3, 8.7] 15 16.5 [9.1, 28.1]
 Latino 12 15.3 [8.4, 26.2] 14 16.7 [9.3, 28.4]
 Multirace 12 14.1 [7.5, 24.8] 11 5.8 [2.5, 12.9]
 Other 5 6.8 [2.8, 15.7] 11 9.4 [4.5, 18.9]
Sexual minority identity
 Heterosexual 18 10.7 [5.9, 18.6] 41 27.2 [18.4, 38.3] 7.9 **
 Sexual minority 117 89.3 [81.4, 94.1] 94 72.8 [61.7, 81.6]
Poverty
 Not in poverty 103 78.0 [68.0, 85.6] 103 65.3 [52.9, 75.9] 3.0
 Living in poverty 32 22.0 [14.4, 32.0] 32 34.7 [24.1, 47.1]
Education
 High school or less 32 48.6 [37.9, 59.5] 26 38.2 [27.2, 50.5] 3.2 *
 Some college 48 26.8 [18.9, 36.5] 51 35.4 [25.4, 46.9]
 College 35 17.8 [11.8, 26.0] 25 9.8 [5.8, 16.3]
 More than college 20 6.7 [4.0, 11.1] 33 16.6 [10.2, 25.7]
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*

p < .05;

**

p < .01;

***

p < .001

Table 2.

Prevalence and correlates of minority stress constructs and early life factors with lifetime nonsuicidal self-injury (NSSI) among a U.S. probability sample of transgender people (N = 270).

YES Lifetime NSSI (n = 135) NO Lifetime NSSI (n = 135) Design-based F
n Weighted % or Mean 95% CI or ±SD n Weighted % or Mean 95% CI or ±SD
MINORITY STRESS CONSTRUCTS
Everyday discrimination (1–4) 135 2.4 0.7 135 2.0 0.7 12.4 ***
Major victimization and discrimination (0–3) 135 1.2 0.7 135 0.8 0.8 12.0 ***
Stressful life events: interpersonal (0–4) 135 1.8 1.1 135 1.0 1.1 16.0 ***
Stressful life events: employment (0–4) 135 1.6 1.1 135 0.9 1.1 12.3 ***
Gender identity non-disclosure (1–5) 135 3.6 0.7 135 3.2 1.0 6.8 **
Non-affirmation of gender identity (1–5) 135 3.5 1.1 135 2.6 1.2 22.8 ***
Negative expectations for future events (1–5) 135 3.4 0.7 135 3.0 0.9 13.3 ***
Internalized transphobia (1–5) 135 2.6 0.8 135 2.6 1.1 0.0
Social support (1–7) 135 4.9 1.2 135 5.1 1.5 0.7
Transgender community connectedness (1–5) 135 3.6 0.7 135 3.3 0.8 3.9 *
EARLY LIFE FACTORS
Nonconformity childhood gender expression
 Top Decile (Most GNC) 10 5.6 [2.4, 12.6] 30 27.7 [18.3, 39.5] 7.9 ***
 Median to Top Decile 55 42.1 [31.9, 53.1] 54 38.0 [27.8, 49.4]
 Lowest Decile (Least GNC) 70 52.3 [41.4, 62.9] 51 34.4 [24.3, 46.0]
Adverse childhood experiences (0–8) 135 4.2 1.7 135 2.8 2.1 21.7 ***
Bullying
 Rarely/never 26 20.4 [12.9, 30.7] 57 41.7 [30.8, 53.3] 8.1 **
 Often/sometimes 109 79.6 [69.3, 87.1] 78 58.3 [46.7, 69.2]
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*

p < .05;

**

p < .01;

***

p < .001; GNC = gender nonconforming

Table 3.

Logistic regression models of sociodemographic characteristics, minority stress constructs, and early life factors by lifetime nonsuicidal self-injury (NSSI) (n = 135).

YES Lifetime NSSI (n = 135)
Model 1 Model 2 Model 3
OR 95% CI AOR 95% CI AOR 95% CI
SOCIODEMOGRAPHIC CHARACTERISTICS
Age 0.93 [0.91, 0.96] *** 0.93 [0.89, 0.96] *** 0.93 [0.90, 0.97] ***
Race and ethnicity (ref: White)
 Black 0.18 [0.05, 0.63] ** 0.14 [0.03, 0.65] * 0.07 [0.02, 0.30] ***
 Latino 0.74 [0.24, 2.30] 0.61 [0.16, 2.33] 0.41 [0.12, 1.46]
 Multirace 2.09 [0.51, 8.62] 1.74 [0.51, 5.93] 1.83 [0.44, 7.55]
 Other 0.54 [0.14, 1.99] 1.10 [0.30, 4.08] 0.99 [0.29, 3.37]
Gender identity/assigned sex at birth (ref: Transfeminine/male at birth)
 Transmasculine/female at birth 1.01 [0.48, 2.13] 0.77 [0.35, 1.69] 0.83 [0.35, 1.95]
Sexual minority identity (ref: Heterosexual)
 Sexual minority 1.66 [0.63, 4.33] 1.27 [0.41, 3.92] 0.65 [0.20, 2.11]
Gender nonbinary (ref: Binary trans)
 Nonbinary trans 2.60 [1.13, 5.97] * 2.53 [0.91, 7.03] 2.65 [0.87, 8.08]
Poverty (ref: Not living in poverty)
 Living in poverty 0.70 [0.27, 1.79] 0.56 [0.21, 1.51] 0.44 [0.14, 1.36]
Education (ref: More than college)
 High school or less 3.10 [1.07, 9.01] * 2.45 [0.72, 8.30] 3.87 [0.94, 15.94]
 Some college 1.53 [0.51, 4.57] 1.07 [0.33, 3.44] 1.43 [0.38, 5.34]
 College 4.18 [1.30, 13.39] * 2.93 [0.80, 10.74] 4.31 [1.05, 17.70] *
MINORITY STRESS PROCESSES
Everyday discrimination 0.94 [0.41, 2.12] 1.01 [0.43, 2.40]
Major victimization and discrimination 2.95 [1.47, 5.93] ** 3.35 [1.61, 6.98] **
Stressful life events: interpersonal issues 1.09 [0.72, 1.66] 1.03 [0.66, 1.59]
Stressful life events: employment instability 1.12 [0.76, 1.65] 0.96 [0.65, 1.42]
Gender identity non-disclosure 1.00 [0.60, 1.66] 0.89 [0.52, 1.51]
Non-affirmation of gender identity 1.01 [0.66, 1.56] 0.88 [0.56, 1.37]
Negative expectations for future events 1.59 [0.84, 2.99] 1.62 [0.89, 2.95]
Transgender community connectedness 1.73 [1.06, 2.82] * 1.85 [1.10, 3.12] *
EARLY LIFE FACTORS
Nonconformity childhood gender expression (ref: Top Decile [Most GNC])
 Median to Top Decile 10.68 [2.55, 44.68] **
 Lowest Decile (Least GNC) 18.41 [3.95, 85.93] ***
Adverse childhood experiences 1.39 [1.09, 1.76] **
Bullying (ref: Rarely/never)
 Often/sometimes 1.17 [0.40, 3.47]
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Note: Model 1 adjusts for sociodemographic characteristics. Model 2 adjusts for sociodemographic characteristics and minority stress constructs. Model 3 adjusts for sociodemographic characteristics, minority stress constructs, and early life factors. GNC = gender nonconforming.

*

p < .05;

**

p < .01;

***

p < .001

Two minority stressors were significantly associated with NSSI. The first was victimization and discrimination, which was associated with higher odds of NSSI (AOR=3.35, 95% CI: 1.61–6.91). This association increased in magnitude from Model 2 to Model 3 with the addition of early life adversity variables. Transgender community connectedness was also associated with higher odds of NSSI (AOR=1.85, 95% CI: 1.10–3.12). Two early life adversity variables were also associated with NSSI. Adverse childhood experiences were associated higher odds of NSSI (AOR=1.39, 95% CI: 1.09–1.76). Lower levels of nonconformity in childhood gender expression were associated with higher odds of NSSI compared to the highest level of nonconformity in childhood gender expression (lowest decile AOR=18.41, 95% CI: 3.95–85.93; median to top decile AOR=10.68, 95% CI: 2.55–44.68). The remaining minority stress processes and early life adversity variables were not significantly associated with NSSI in the fully adjusted model.

Discussion

This study provides the first data about NSSI among a national probability sample of the U.S. transgender population. Contrary to previous findings that suggest people who are transmasculine or nonbinary assigned female sex at birth are more likely to engage in NSSI (Marshall et al., 2016), we did not find a significant difference in lifetime NSSI based on sex assigned at birth. This is finding is interesting in light of evidence about NSSI in the general population which indicates it is more common among women than among men (Bresin & Schoenleber, 2015). This suggests that differences in NSSI prevalence might be better explained by factors other than sex assigned at birth such as adverse life experiences and victimization.

We found that nonbinary-identified participants had higher odds of NSSI compared to binary-identified participants in our initial regression model. This finding became non-significant after adding minority stress processes and early life adversity in Models 2 and 3, respectively. This is congruent with recent studies that have found evidence of increased mental health vulnerability among nonbinary compared to binary identified transgender people (Burgwal et al., 2019; James et al., 2016; Reisner & Hughto, 2019). The increased vulnerability of nonbinary transgender people may be related to invalidation and lack of recognition of gender identities that are outside of the binary conceptualization of gender (Johnson et al., 2019).

In terms of minority stressors, two factors (victimization and discrimination and transgender community connectedness) were significantly associated with lifetime NSSI. Conflicting evidence exists in the literature about the relationship between distal minority stressors (such as victimization and discrimination) and NSSI; one study suggested they may be associated (Staples et al., 2018) but another study found no association (Jackman, Dolezal, et al., 2018). On the contrary, Jackman and colleagues (2018) found that past-year NSSI was associated with felt stigma, a proximal minority stress process, which appears to align with research among the general population which suggests that the most common reason people engage in NSSI is to cope with negative feelings (Nock, 2010). The interplay between minority stressors and NSSI should be further examined in future research, which could also take into account additional minority stress factors such as invalidation (Johnson et al., 2019).

The positive association between transgender community connectedness and NSSI was contrary to the hypothesis derived from the minority stress model. In the minority stress model, connectedness with similar peers is conceptualized as a resilience factor that supports positive adjustment and well-being (Meyer, 2003). The minority stress model suggests that for individuals who are members of a stigmatized minority group, comparing oneself to similar peers rather than general societal norms is a source of resilience (Meyer, 2003). Our finding, along with previous qualitative findings that NSSI is perceived by transmasculine spectrum people as common among transgender people (Jackman, Edgar, et al., 2018), indicate that this behavior might be seen as normative in the transgender community. NSSI could play a role in reinforcing one’s group identity, as has been shown in certain youth subgroups (Young et al., 2014). Some authors have suggested that NSSI may be a way to signal strength and ability to withstand adversity, particularly among people who fear victimization (Bornstein, 2006; Nock, 2008). Transgender people with higher levels of connection to the transgender community may also experience stress vicariously by hearing about the victimization and discrimination of their transgender peers (Koziara et al., 2021). Indeed, literature indicates that transgender community connectedness may not always be protective concerning psychological distress and sexual risk behaviors (Breslow et al., 2015; Nuttbrock et al., 2015).

As expected, based on the theoretical model of NSSI (Nock, 2008), adverse childhood experiences predicted lifetime NSSI. However, contrary to expectations lower, not higher, nonconformity in childhood gender expression predicted lifetime NSSI. One way to understand this finding is that transgender people with lower nonconformity in childhood gender expression may come out as transgender later in life and may have spent longer coping with felt stigma and internalized stigma prior to coming out (Bockting, 2014). Additionally, they may have less experience developing resilience in the face of adversity related to their gender expression. This finding also suggests that different gender identity developmental trajectories may affect vulnerability to NSSI among transgender people. Foundational qualitative work has shown that while stigma is an important factor affecting NSSI among transgender people, challenges related to gender identity development may also contribute to NSSI (Jackman, Edgar, et al., 2018). Level of nonconformity in childhood gender expression may be an indicator of a path of gender identity development. More research is needed to understand how these developmental trajectories intersect with mental health vulnerabilities for transgender people.

Limitations and Future Directions

This is a cross-sectional study, so no causal relationships can be determined. Data were collected by retrospective self-report which introduces the possibility of recall bias, particularly for some processes such as early life adversity which may have occurred years ago depending on the age of the participant. NSSI is a stigmatized behavior (Simone & Hamza, 2020) so participants may have been reluctant to endorse it leading to possible underreporting of our outcome of interest. On the other hand, although the item used to measure NSSI is commonly used in this field, it could lack specificity in interpretation for some participants leading to overreporting of the behavior. In addition, since NSSI is associated with younger age and our measure of NSSI was over the lifetime, it is possible that some NSSI occurred prior to the independent variables we examined. Finally, the measures of victimization and discrimination and everyday discrimination and did not ask about these experiences related to transgender identity, which may mean these measures lack specificity regarding participants’ experiences as a transgender person and.

Future research should examine NSSI from a longitudinal perspective and incorporate more detailed questions about NSSI to collect fine-grain data. Use of standard measures of NSSI, particularly those exploring the functions of the behavior, may not be adequate to capture the range of experiences of transgender people (Morris & Galupo, 2019). Therefore, future research should adapt measures of NSSI to be appropriate for transgender populations and their unique experiences. In addition, more nuanced data about the type, frequency, and severity of NSSI would provide more insight into the role of NSSI in the lives of transgender people, essential information needed to develop interventions targeting this behavior. Although not examined in this study, future research about NSSI among transgender people could explore the role of gender dysphoria since evidence suggests that gender dysphoria may contribute to NSSI in multiple ways (Morris & Galupo, 2019). Furthermore, gender dysphoria has been proposed as a proximal minority stress process (Lindley & Galupo, 2020) which allows it to be incorporated from a theoretical perspective in future research about NSSI among transgender people providing a fuller picture of the role of this behavior.

This study makes a significant contribution to the literature by elucidating correlates of NSSI among transgender people based on two theoretical models: minority stress theory and Nock’s theory of NSSI. Using data from the first national probability sample of transgender people we identified two minority stressors and two early life factors that may contribute to the high rates of NSSI in this population. Drawing upon complimentary theoretical models to inform this investigation provided new insights into this complex and multi-faceted behavior which is a significant public health concern due to its high prevalence among transgender people and its association with suicidality. Further theory-informed research in this area will lead to identification of intervention targets and inform future tailored interventions to prevent and decrease NSSI among transgender people.

Public Significance Statement:

This study shows that approximately 50% of transgender adults in the United States report non-suicidal self-injury (NSSI; e.g., cutting the skin without an intent to die) in their lifetime, a much higher prevalence than in the general population. Certain negative experiences, such as victimization and discrimination, are associated with increased risk for NSSI. Efforts to protect transgender people from victimization, discrimination, and other negative experiences may reduce vulnerability to NSSI in this population.

Acknowledgements:

During the time of this work, Dr. Jackman was supported by NINR T32NR007969 (PI: Bakken). Sarah I. Leonard was supported by NINR F31NR020733-01. TransPop is funded by a grant from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD grant R01HD090468) and through Supplement to grant R01HD078526 from the National Institutes of Health, Office of Behavioral and Social Sciences Research and the Office of Research on Women’s Health. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The TransPop investigators are: Ilan H. Meyer, Ph.D. (PI), Walter O. Bockting, Ph.D., Jody L. Herman, Ph.D., and Sari L. Reisner, ScD (Co-Investigators, listed alphabetically).

Footnotes

CRediT Authorship Statement: Conceptualization, K.B.J., W.O.B., S.D., W.L., A.L., and I.H.M.; Methodology, K.B.J., W.O.B., and I.H.M.; Formal Analysis, S.D., W.L., and A.L.; Resources, W.O.B. and I.H.M.; Data Curation, S.D. and W.L.; Writing –Original Draft, K.B.J. and W.O.B; Writing –Review & Editing, S.D., W.L., S.I.L., and I.H.M.; Funding Acquisition, I.H.M. and W.O.B.; Project Administration, W.L.; Supervision, W.O.B. and I.H.M.

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