Abstract
While the mental health of gender minority (GM) individuals has garnered increased attention in recent years, GM older adults (i.e., aged 50 and older) remain overlooked in research. Thus, we conducted a systematic review with the aim of synthesizing and evaluating existing research regarding mental health concerns and disparities, risk factors, and protective factors among GM older adults in the United States. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, we conducted a search in PubMed, PsycINFO, PsychiatryOnline, Gender Studies Database, GenderWatch, Scopus, and Web of Science. We included peer-reviewed journal articles that were published in English from 2010 onwards, reported research conducted in the United States, and presented data on mental health-related outcomes among GM adults aged 50 years or older. The 31 studies included in this review identified disparities in suicidality, depression and other specific mental health conditions, and general measures of mental health among GM older adults. Studies highlighted risk factors including stigma, violence, and discrimination, along with protective factors including access to social support and affirming health care resources. However, patterns of methodological characteristics (e.g., unrepresentative samples, cross-sectional designs, measures and analyses that obscured GM older adults’ diverse identities) presented important limitations, while the small and heterogenous nature of the literature yielded limited evidence regarding specific mental health outcomes. There is a critical need for further research that addresses existing methodological gaps and investigates how intersecting forms of marginalization impact the mental health of GM older adults across the life course.
Keywords: gender minority, transgender, older adults, mental health, systematic review
Recent years have seen rapidly growing interest in the health and well-being of gender minority (GM) populations, broadly including transgender, nonbinary, and other gender diverse individuals. Consequently, a plethora of studies have documented the wide range of health inequities that GM individuals face, including within the mental health domain (for reviews, see Reisner et al., 2016; White Hughto & Reisner, 2015; Winter et al., 2016; Valentine & Shipherd, 2018). The literature on GM mental health has consistently identified a greater prevalence of several specific mental health conditions among GM individuals, with depression and other mood disorders, suicidal and non-suicidal self-injury, and anxiety disorders being the most commonly investigated (Reisner et al., 2016). Additionally, disparities persist with respect to both negative and positive measures of general mental health. For example, 39% of respondents to the 2015 U.S. Transgender Survey reported experiencing serious psychological distress, compared to 5% of the overall U.S. population (James et al., 2016), while meta-analytic evidence indicates that GM individuals consistently report poorer mental health-related quality of life compared to the overall population (Nobili et al., 2018).
Several empirically driven frameworks serve to contextualize these widespread mental health inequities. For example, Hendricks & Testa (2012) adapted Meyer’s (2003) original minority stress model, which explains how chronic exposure to stigma, discrimination, and prejudice may shape mental health disparities for sexual minorities, to account for the specific stressors that GM individuals face. These gender minority stressors include gender identity-based discrimination, rejection, victimization, and other forms of marginalization, as Testa et al. (2015) later identified. White Hughto et al.’s (2015) social ecological model of transgender stigma draws upon this concept of gender minority stress to illustrate the adverse mental and physical impacts of stigma at the individual, interpersonal, and structural levels, respectively referring to personal beliefs and behaviors, everyday interactions with others, and social norms, conditions, and policies. Through the gender affirmation framework, Sevelius (2013) proposed that societal oppression creates psychological distress and impedes access to gender identity-affirming interactions for GM individuals, particularly transgender women of color, leading to health jeopardizing coping behaviors. Finally, the Intersectionality Research for Transgender Health Justice framework developed by Wesp et al. (2019) elucidates how transphobia, racism, sexism, ageism, and other structures of domination intersect to shape the institutional systems (e.g., health care, legal systems) and socio-structural processes (e.g., pathologization, criminalization) which produce health inequities.
Given these understandings, the intersection of transphobia and ageism may engender distinct threats to the mental health of GM older adults (i.e., those aged 50 years and older). Indeed, the Institute of Medicine (US) Committee on Lesbian, Gay, Bisexual, and Transgender Health Issues and Research Gaps and Opportunities (2011) highlighted stigma targeting both GM identity and older age, combined with the historical repression of gender diversity in the United States, as important factors influencing this population’s mental and physical health. However, while previous systematic reviews have focused on the mental health of sexual minority older adults (e.g., McParland & Camic, 2016) and sexual and gender minority (SGM) older adults collectively (e.g., Fredriksen-Goldsen et al., 2019; Marshall & Cahill, 2022), research specific to the mental health of GM older adults remains emergent. A few notable book chapters and reviews have discussed mental health as an aspect of GM older adults’ overall aging and health needs (e.g., Cook-Daniels, 2016; Finkenauer et al., 2012; Witten, 2017) or within the context of clinical guidance (e.g., dickey & Bower, 2017; Porter et al., 2016). These works have importantly outlined challenges facing GM older adults, such as lifetime experiences of transphobia, discrimination in health care and aging services, and limited social support. However, existing reviews have not aimed to comprehensively assess the content and quality of the current academic literature specific to GM older adults’ mental health. Furthermore, given associations between recent waves of anti-transgender legislation and mental health inequities among the collective U.S. GM population (Tebbe et al., 2022), increased attention to the mental health of GM older adults is especially warranted at this time.
This study therefore aims to systematically review the academic literature addressing mental health among GM older adults in the United States. Specifically, this review seeks to identify the major concerns and disparities, risk factors, and protective factors determining the mental health of GM older adults, in addition to evaluating the methodological characteristics of the literature with respect to study design, sample characteristics, and measurement and analysis of key demographic variables.
Methods
Eligibility Criteria
We developed the protocol for this review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Moher et al., 2015; Page et al., 2021). Inclusion criteria required that studies be peer-reviewed journal articles, published in English, report original quantitative and/or qualitative data (e.g., not reviews or commentaries), and report research conducted in the United States. We included studies published from 2010 onward, given the dearth of literature regarding GM older adults’ health since 2010 (Fredriksen-Goldsen & Muraco, 2010). Studies had to address mental health-related outcomes, inclusive of specific mental health conditions, general measures of adverse symptoms (e.g., psychological distress), and general measures of positive mental states (e.g., psychological well-being). Finally, studies had to include gender minorities aged 50 or older within their samples. We considered “gender minorities” to inclusively refer to individuals whose gender identity differs from their sex assigned at birth, such as transgender men, transgender women, and nonbinary and genderqueer individuals (Ayhan et al., 2020; Centers for Disease Control and Prevention [CDC], 2019). While definitions of “older adult” vary, this review used a minimum age cutoff of 50 years due to its alignment with the inclusion criteria of one of the first federally funded studies of SGM health and aging (Fredriksen-Goldsen et al., 2011).
Studies were excluded if they failed to meet all inclusion criteria. Additionally, to address ambiguities around eligibility that arose during the full text screening phase, criteria were refined to exclude studies that included participants aged 50 and older within a broader sample but did not report mental health-related findings specific to participants aged 50 and older (i.e., not disaggregating data by age groups). Similarly, we excluded studies that described participants using umbrella terms such as “SGM” or “lesbian, gay, bisexual, and transgender (LGBT)” but did not report mental health-related findings specific to GM participants (i.e., not disaggregating data across GM and non-GM groups).
Information Sources and Search Strategy
We searched the databases PubMed, PsycINFO, PsychiatryOnline, Gender Studies Database, GenderWatch, Scopus, and Web of Science. All authors contributed to the development of the search strategy, in consultation with a subject librarian with expertise in gender and sexuality. The search strategy for all databases was entered as follows: (“transgender” OR “nonbinary” OR “non-binary” OR “nonconforming” OR “non-conforming” OR “gender minority”) AND (“elderly” OR “elder” OR “older adult” OR “older” OR “senior” OR “aging” OR “ageing” OR “over 50”) AND (“mental health” OR “mental illness” OR “mental disorder” OR “psychological distress” OR “psychiatric disorder” OR “emotional health” OR “behavioral health” OR “depression” OR “anxiety” OR “PTSD” OR “substance abuse” OR “suicid*”). The wildcard operator “*” was used to broadly capture variations of the term “suicide,” including “suicidality” and “suicidal.” Filters limited results to English-language works published in peer-reviewed journals since January 1, 2010. All searches were entered on March 4, 2022.
Selection Process
Records retrieved from each database were uploaded to the citation management system Zotero, where duplicates and records flagged by the system as ineligible publication types (e.g., books, commentaries) were automatically removed. The remaining titles and abstracts were uploaded to a Microsoft Excel spreadsheet for screening. As shown in the PRISMA flow diagram (Figure 1), study selection consisted of two screening stages. The first and second authors both independently screened each title and abstract against eligibility criteria, with no conflicts occurring in this initial round. After obtaining the full texts of records which met all eligibility criteria, the first and second authors both independently reviewed each of the full texts for eligibility. Each reviewer indicated a primary reason for excluding a study, and all conflicts were documented using a shared spreadsheet. The first and second authors first discussed conflicts amongst themselves and then brought any unresolved conflicts to the full author team for input. During this stage, exclusion criteria were refined as previously described and added to the protocol as amendments.
Figure 1.
PRISMA Flow Diagram
Data Collection and Items
The included studies were divided approximately in half among the first and second authors for independent data collection using a data collection spreadsheet. Each author then checked the other’s work for accuracy. For each study, we sought the following items: methodology (e.g., quantitative, qualitative), study design (e.g., cross-sectional survey, retrospective study), population of interest (e.g., SGM older adults, GM older adults), sampling procedure (e.g., probability, convenience), sample scope (e.g., national, state), setting (e.g., administrative claims database, state in which sampling took place), overall sample size, GM older adult subsample size (if the sample was not exclusive to GM older adults), overall sample age range, study aim and mental health outcomes captured (including specific psychiatric conditions and general measures of positive or negative mental health), and key findings related to mental health outcomes, risk factors, and protective factors. Additionally, we recorded how each study reported gender identity, age, sexual orientation, and race and ethnicity as demographic characteristics, in addition to whether quantitative studies examined differences in mental health outcomes by these characteristics within their samples.
Risk of Bias Assessment
The Mixed Methods Appraisal Tool (MMAT) was selected to assess the risk of bias within included studies, given that the tool is designed for use in mixed studies reviews (Hong et al., 2018). The MMAT distinguishes between five methodological categories, including qualitative, quantitative randomized control trials, quantitative non-randomized, quantitative descriptive, and mixed methods. For all studies, the assessment begins with the same two screening questions (“Are there clear research questions?” and “Do the collected data allow to address the research questions?”). Distinct sets of five questions then assess criteria which correspond to the different methodological categories. All criteria receive ratings of “yes,” “no,” or “can’t tell.” After determining the appropriate methodological category for each study using the explanations provided by Hong et al. (2018), the first and second authors both independently rated each criterion for each study. The elaborations provided by Hong et al. (2018) for each criterion served as a common basis for ratings. The first and second authors discussed and resolved conflicts amongst themselves. As recommended by Hong et al. (2018), studies were not excluded from the review synthesis due to poor quality indicated by MMAT ratings.
Synthesis Methods
Given our aim of characterizing the state of an emergent and methodologically diverse body of literature, we performed a narrative synthesis following the process outlined by Popay et al. (2006), as opposed to conducting meta-analyses for specific outcomes. First, the first and second authors composed brief textual summaries of relevant findings from each study throughout the data collection process, which are displayed in Table 1. To explore relationships within and between studies, we then compared findings within broad categories based on the review aims (i.e., major concerns and disparities, risk factors, protective factors), summarizing areas of convergence and highlighting areas of divergence. For example, within the category of risk factors, we identified studies that examined similar variables as potential predictors of worse mental health outcomes and noted any consistencies or inconsistencies between study results. We examined patterns across the risk of bias assessments using the MMAT to evaluate the overall certainty of synthesis findings (Popay et al., 2006). All authors reviewed and approved the final written synthesis.
Table 1.
Characteristics of Included Studies (N=31)
| Author/Date | Sample Description | Design and Methods | Demographic Measures and Analysis | Aim and Mental Health Outcomes | Relevant Findings |
|---|---|---|---|---|---|
| Boyer et al. (2021) | Participants: Transgender compared to cisgender VHA users Sample total: 32,441 GM older adults: 961 (aged 65+) Overall sample age: 18–65+, M = NR |
Scope/Setting: National (VHA database) Methodology: Quantitative Study design: Retrospective analysis of VHA records Sampling procedures: Algorithm based on gender identity-related diagnostic codes |
Gender: Only measured sex; not examined Sexual orientation: NR Age: Measured; compared transgender and cisgender veterans within and across age groups (18–39, 40–64, 65+) Race/ethnicity: 66.5% NHW; not examined |
Aim: Compare the prevalence of suicide, homicide, and all-cause mortality between transgender and cisgender veterans receiving care in the VHA. Outcomes: Suicide death (records in National Death Index) |
Overall, transgender veterans had over twice the risk of suicide mortality as cisgender veterans. Transgender veterans aged 65+ had a suicide prevalence of 0.8% and over nine times the risk of suicide as cisgender veterans aged 65+. Among those aged 40–64, transgender veterans had a suicide prevalence of 0.8% and about twice the risk of suicide as cisgender veterans. |
| Brown & Patterson (2020) | Participants: SGM compared to non-SGM older adults Sample total: 36,734 GM older adults: 88 Overall sample age: 45–80+, M = NR |
Scope/Setting: State (seven states with relevant BRFSS data) Methodology: Quantitative Study design: Cross-sectional analysis of BRFSS data Sampling procedures: Probability |
Gender: Measured using options of male-to-female, female-to-male, or gender nonconforming; compared by sex for overall sample Sexual orientation: Measured separately from gender identity for all; only compared by “SGM” or “non-SGM” status Age: Measured; compared by age group (45–59, 60–69, 70–79, 80+) within overall sample only Race/ethnicity: 85.3% NHW; examined within overall sample only |
Aim: Examine possible disparities in subjective cognitive decline and risk factors between SGM vs. non-SGM, transgender vs. non-transgender, and male vs. female older adults. Outcomes: Depression diagnosis (yes/no, self-report); subjective cognitive decline (worsened confusion or memory loss, self-report) |
Transgender older adults were significantly more likely to report depression than non-transgender older adults (33.2 vs. 20.3%). After adjusting for depression and sociodemographic confounders, there was no significant association between transgender identity and subjective cognitive decline. |
| Carroll (2017) | Participants: Older transgender woman Sample total: 1 GM older adults: 1 Overall sample age: 58 |
Scope/Setting: Individual (clinic-based) Methodology: Qualitative Study design: Case vignette Sampling procedures: Purposive |
Gender: Described participant as trans woman Sexual orientation: Described participant as bisexual Age: Described participant as aged 58 Race/ethnicity: Described participant as White |
Aim: Describe therapeutic issues with transgender and nonconforming older adults, using a case vignette to illustrate the interplay between age, life phase, and sociocultural and historical contexts. Outcomes: Qualitative discussion of depression, trauma |
Transition barriers such as discrimination and fears of family rejection contributed to the participant’s depression. Important aspects of her treatment included emphasizing resilience, connecting her to events and resources in the transgender community, addressing trauma, and exploring coming out. |
| Cortes et al. (2019) | Participants: LGBT veterans Sample total: 254 GM older adults: 46 Overall sample age: 19–78, M = 47.4 |
Scope/Setting: National (community-based) Methodology: Quantitative Study design: Cross-sectional analysis of survey data Sampling procedures: Convenience |
Gender: Measured for all as man or woman; examined outcomes within groups of transgender men and transgender women Sexual orientation: Measured separately from gender identity for all; examined outcomes within mutually exclusive subgroups of lesbian woman, gay man, bisexual, transwoman, and transman Age: Measured; examined differences between younger (aged <50) and older (aged 50+) groups Race/ethnicity: 78.2% NHW; not examined |
Aim: Examine differences in mental health and identity between older and younger LGBT veterans. Outcomes: Depression (Patient Health Questionnaire), anxiety (Overall Anxiety Severity and Impairment Scale), excessive alcohol use (Alcohol Use Disorders Identification Test-Consumption) |
Transgender women aged 50 years and older had significantly lower mean alcohol use scores than younger transgender women (1.98 vs. 2.97), with no differences by age among transgender men. No age differences in anxiety or depression were found for any LGBT subgroups. Older LGBT veterans reported less harassment and rejection than their younger peers overall, although no age differences were found among transgender men or transgender women. |
| Dragon et al. (2017) | Participants: Transgender compared to cisgender Medicare beneficiaries Sample total: 39,143,683 GM older adults: 2,133 (aged 65+) Overall sample age: 18–85+, M (overall) = NR, M(transgender) = 53.1, M(cisgender) = 70.9 |
Scope/Setting: National (Medicare claims database) Methodology: Quantitative Study design: Cross-sectional analysis of Medicare claims data Sampling procedures: Algorithm based on gender identity-related diagnostic codes |
Gender: Only measured sex; not examined Sexual orientation: NR Age: Measured; only compared transgender vs. cisgender beneficiaries within entitlement groups based on age (aged 65+) or disability (aged <65) Race/ethnicity: 76.8% NHW; not examined |
Aim: Analyze differences in chronic conditions between transgender and cisgender Medicare beneficiaries, as well as within cohorts based on age and disability. Outcomes: Anxiety, bipolar disorder, depression, personality disorders, post-traumatic stress disorder, schizophrenia and other psychotic disorders, substance use disorders (diagnosis codes in claims) |
Transgender vs. cisgender beneficiaries aged 65+ were significantly more likely to have diagnoses of anxiety (38.9 vs. 17.3%), bipolar disorder (12.4 vs. 2.4%), depression (45.6 vs. 19.1%), personality disorders (8.1 vs. 0.7%), post-traumatic stress disorder (6.2 vs. 0.6%), schizophrenia and other psychotic disorders (13.3 vs. 4.1%), and substance use disorders (8.44 vs. 2.0%). |
| Elder (2016) | Participants: Transgender and gender nonconforming older adults Sample total: 10 GM older adults: 10 Overall sample age: 60–83, M = NR |
Scope/Setting: San Francisco Bay Area Methodology: Qualitative Study design: Semi-structured interviews Sampling procedures: Convenience |
Gender: Measured using open-ended question; identities included female, transgender woman, “male-to-female and back,” trans man, and male Sexual orientation: Measured using separate open-ended question Age: Measured and reported in demographics Race/ethnicity: 80.0% White (ethnicity NR) |
Aim: Offer perspectives that are often overlooked due to marginalization to improve the quality of psychotherapeutic care for gender-diverse people. Outcomes: Qualitative discussion of trauma, suicide, and various experiences of mental distress |
Participants described healing experiences with knowledgeable therapists who affirmed their gender identities, as well as harmful experiences with distant, transphobic, and uninformed therapists. Sources of distress included the past pathologization and repression of transgender identities, discrimination, family rejection, and abuse. Involvement in the transgender community was a source of resilience. |
| Fabbre (2014) | Participants: Older transgender women Sample total: 22 GM older adults: 22 Overall sample age: 50–82, M = NR |
Scope/Setting: Chicago metropolitan area; community-based conferences in multiple regions Methodology: Qualitative Study design: In-depth interviews and participant observation Sampling procedures: Purposive |
Gender: Described all participants as transgender women Sexual orientation: Collected partnership status and partner gender Age: Measured and reported in demographics Race/ethnicity: 81.8% NHW |
Aim: Describe the experiences of transgender women who pursued gender transitions later in life to develop queer conceptualizations of health and “successful aging.” Outcomes: Qualitative discussion of trauma, distress, substance abuse, suicidality |
Participants experienced trauma, substance abuse, suicidality, and various mental health difficulties related to their sense of “failure” under oppressive gender expectations. Identity acceptance and transition processes in later life led participants to a sense of wellbeing and “success on new terms.” |
| Fabbre & Gaveras (2020) a | Participants: Transgender and gender nonconforming older adults Sample total: 88 GM older adults: 88 Overall sample age: 50–90, M = NR |
Scope/Setting: National (community-based) Methodology: Qualitative Study design: Secondary content analysis of biographical interviews Sampling procedures: Purposive |
Gender: Measured and described in demographics as trans woman, trans man, or non-binary Sexual orientation: NR Age: Measured and reported in demographics Race/ethnicity: 61.4% NHW |
Aim: Examine experiences of multi-level (individual, interpersonal, and structural) stigma among transgender and gender nonconforming older adults. Outcomes: Qualitative discussion of substance abuse, depression, anxiety, suicidality |
Participants described experiences of individual stigma (shame, self-isolation, fear), interpersonal stigma (familial rejection), and structural stigma (exclusion from “LGBT” spaces, health care discrimination), which they linked to substance abuse, depression, anxiety, and suicidality. Activism within the transgender community was a source of resilience. |
| Ferron et al. (2010) | Participants: Older transgender woman Sample total: 1 GM older adults: 1 Overall sample age: 68 |
Scope/Setting: Individual (clinic-based) Methodology: Qualitative Study design: Case study Sampling procedures: Purposive |
Gender: Described participant as male-to-female transgender Sexual orientation: NR Age: Described participant as 68 years Race/ethnicity: Described participant as Hispanic |
Aim: Present a case study of a 68-year-old transgender woman with HIV to provide a model of integrated mental and physical health care. Outcomes: Depression (diagnosis in clinical chart) |
Transgender older adults with HIV may encounter intersecting challenges related to aging and physical conditions, depression and other mental health conditions, and social factors such as discrimination and stigma, creating complex health care needs. |
| Flatt et al. (2021) | Participants: SGM compared to non-SGM older adults Sample total: 119,128 GM older adults: 441 Overall sample age: 45–80+, M = 59.9 |
Scope/Setting: State (25 states with relevant BRFSS data) Methodology: Quantitative Study design: Cross-sectional analysis of BRFSS data Sampling procedures: Probability |
Gender: Measured using options of male-to-female, female-to-male, or gender nonconforming; not examined Sexual orientation: Measured separately from gender identity for all; examined single transgender group and other mutually exclusive SGM subgroups (e.g., cisgender heterosexual women, cisgender gay men, cisgender lesbian women) Age: Measured; only compared subjective cognitive decline by older age (aged 60+) for overall sample Race/ethnicity: 71.8% NHW; not examined |
Aim: Describe the prevalence of subjective cognitive decline among adults aged 45+ by SGM identity and examine the roles of demographics, chronic conditions, functional limitations, physical health, and depression as predictors. Outcomes: Depression diagnosis (yes/no, self-report); subjective cognitive decline (worsened confusion or memory loss, self-report) |
SGM older adults overall were more likely than non-SGM older adults to report depression (28.0 vs. 17.4%) and subjective cognitive decline (15.7 vs. 10.5%), along with poor/fair health, diabetes, and functional limitations. Transgender older adults had the highest prevalence of subjective cognitive decline (17.3%) after cisgender bisexual older adults, but adjusting for depression attenuated differences in subjective cognitive decline. |
| Fredriksen-Goldsen et al. (2014) b | Participants: Transgender compared to cisgender LGB older adults Sample total: 2,546 GM older adults: 174 Overall sample age: 50+, M = 66.47 |
Scope/Setting: National (community-based) Methodology: Quantitative Study design: Cross-sectional analysis of survey data Sampling procedures: Convenience, snowball |
Gender: Measured using options of man or woman for all; analyzed single transgender group Sexual orientation: NR; only described as transgender or cisgender LGB Age: Measured; not examined Race/ethnicity: 86.5% NHW; not examined |
Aim: Compare differences among transgender and cisgender LGB older adults in physical health, disability, stress, and depression; explore the mediating role of various risk and protective factors. Outcomes: Depressive symptomatology (Center for Epidemiological Studies Depression Scale), stress (Perceived Stress Scale) |
Compared to cisgender LGB older adults, transgender older adults had greater mean scores for depression (10.34 vs. 7.20) and stress (1.56 vs. 1.22), as well as worse physical health and greater disability. Victimization and discrimination, fear of accessing health services, identity concealment, physical inactivity, internalized stigma, lack of social support, and lower LGBT community belonging largely explained these worse outcomes among transgender older adults. |
| Fredriksen-Goldsen et al. (2015) b | Participants: LGBT older adults Sample total: 2,463 GM older adults: 101 Overall sample age: 50–80+, M = NR |
Scope/Setting: National (community-based) Methodology: Quantitative Study design: Cross-sectional analysis of survey data Sampling procedures: Convenience, snowball |
Gender: Measured for all using options of man or woman; analyzed single transgender group Sexual orientation: Measured separately from gender identity for all; examined as predictor within overall sample Age: Measured; compared by age group (50–64, 65–79, 80+) within overall sample Race/ethnicity: 86.9% NHW; compared by race only within overall sample |
Aim: Investigate the relationship between physical and mental health-related quality of life and covariates (i.e., victimization, positive identity, identity disclosure, social resources, health-promoting behaviors, socioeconomic resources, background characteristics) among LGBT older adults by age group. Outcomes: Mental health quality of life (SF-8 Health Survey) |
For LGBT older adults overall, victimization and discrimination were associated with poorer mental and physical health quality of life. These effects were strongest among the oldest LGBT adults, who also had the least social resources. Transgender compared to cisgender LGB older adults reported poorer mental health at the bivariate level but better mental health after controlling for risks and resources. |
| Fredriksen-Goldsen et al. (2017) b | Participants: LGBT older adults Sample total: 2,450 GM older adults: 411 Overall sample age: 50–80+, M = 61.41 |
Scope/Setting: National (community-based) Methodology: Quantitative Study design: Cross-sectional analysis of survey data Sampling procedures: Convenience, snowball |
Gender: Measured for all using man, woman, and other; compared transgender men, transgender women, and other for life events only Sexual orientation: Measured separately from gender identity for all; examined in relation to life events for overall sample Age: Measured; compared life events by age group (50–64, 65–79, 80+) for overall sample Race/ethnicity: 77.6% NHW; examined in relation to life events for overall sample |
Aim: Identify how patterns of key life events and transitions relate to mental health, physical health, and quality of life among LGBT older adults. Outcomes: Depressive symptomatology (Center for Epidemiological Studies Depression Scale), stress (Perceived Stress Scale), psychological quality of life (World Health Organization – BREF) |
Of four identified clusters based on key life events, the cluster with the highest proportion of transgender older adults had relatively high levels of some social and socioeconomic resources compared to other clusters. However, this cluster did not have significant advantages in mental health outcomes, potentially related to the elevated risks (e.g., job discrimination) identified among transgender older adults. |
| Gaveras et al. (2021) a | Participants: Transgender older adults Sample total: 14 GM older adults: 14 Overall sample age: 50–70, M = NR |
Scope/Setting: National (community-based) Methodology: Qualitative Study design: Content analysis of previously conducted biographical interviews Sampling procedures: Purposive |
Gender: Described in demographics as trans woman, trans man, or nonbinary Sexual orientation: NR Age: Measured and reported in demographics Race/ethnicity: 85.7% NHW |
Aim: Examine how transgender older adults describe and understand their past experiences of suicidal ideation and behavior, resilience, and recovery in biographical interviews. Outcomes: Suicidal ideation, suicide plans, suicide attempts (based on definitions from Center for Disease Control and Prevention) |
Participants described recovery from suicidality in terms of impossible and possible paths. Impossible paths were shaped by oppressive societal gender expectations, trauma, and abuse. Support from friends, family, and accepting mental health providers facilitated possible paths toward gender affirmation and recovery. |
| Hillman (2021) | Participants: Transgender older adults Sample total: 3,462 GM older adults: 3,462 Overall sample age: 50–100, M = NR |
Scope/Setting: National (community-based) Methodology: Quantitative Study design: Cross-sectional analysis of survey data Sampling procedures: Convenience, snowball |
Gender: Measured using options of female, male, or nonbinary; not examined Sexual orientation: Measured separately from gender identity; not examined Age: Compared intimate partner violence but not health outcomes by age group (50–64 vs. 65–100) Race/ethnicity: 90.5% NHW; not examined |
Aim: Examine the lifetime prevalence of intimate partner violence among transgender older adults, along with its relationship to mental and physical health outcomes. Outcomes: Lifetime attempted suicide (yes/no, self-report), severe mental distress (K6 Non-Specific Distress Scale), substance use (National Survey on Drug Use and Health items) |
Over half of respondents used substances, 12% experienced severe mental distress, and 28% had a lifetime suicide attempt. Over half of respondents reported intimate partner violence, most commonly targeting gender identity. Intimate partner violence predicted greater smoking, drug use, psychological distress, suicide attempts, poor health, and disability. Gender identity-specific intimate partner violence accounted for additional risk. |
| Hoy-Ellis & Fredriksen-Goldsen (2017) b | Participants: Transgender older adults Sample total: 174 GM older adults: 174 Overall sample age: 50–86, M = 60.97 |
Scope/Setting: National (community-based) Methodology: Quantitative Study design: Cross-sectional analysis of survey data Sampling procedures: Convenience, snowball |
Gender: Measured using options of woman or man; not examined Sexual orientation: Measured separately from gender identity; not examined Age: Measured; not examined Race/ethnicity: 82.4% NHW; not examined |
Aim: Explore the relative contributions of general stress, internalized heterosexism, and identity disclosure to depression among transgender older adults. Outcomes: Depressive symptomatology (Center for Epidemiological Studies Depression Scale), stress (Perceived Stress Scale) |
The prevalence of clinically significant depression scores was 47.9%. Internalized heterosexism predicted greater general stress, which predicted greater depression. Identity disclosure was not related to depression but predicted lower internalized heterosexism. General stress predicted depression independently from minority stressors. |
| Hoy-Ellis et al. (2017) b | Participants: Transgender older adults Sample total: 183 GM older adults: 183 Overall sample age: No range reported; M = 60.11 |
Scope/Setting: National (community-based) Methodology: Quantitative Study design: Cross-sectional analysis of survey data Sampling procedures: Convenience, snowball |
Gender: Measured using options of women, men, or something else; examined as a moderator Sexual orientation: NR Age: Measured; not examined Race/ethnicity: 68.0% NHW; not examined |
Aim: Examine the relationship between prior military service, identity stigma, psychological health-related quality of life, and depressive symptomatology among transgender older adults. Outcomes: Depressive symptomatology (Center for Epidemiological Studies Depression Scale), psychological quality of life (World Health Organization – BREF) |
Transgender older adults overall had mean depression and psychological quality of life scores of 9.00 and 64.12, respectively. Veterans vs. non-veterans had lower depression (7.00 vs. 9.80) and higher psychological quality of life (70.30 vs. 61.82). Identity stigma was associated with greater depression and lower psychological QoL. The association between identity stigma and depression was weaker for veterans vs. non-veterans. |
| Johnson et al. (2018) | Participants: Older transgender woman Sample total: 1 GM older adults: 1 Overall sample age: 70 |
Scope/Setting: Individual (non-clinical) Methodology: Qualitative Study design: Interview and review Sampling procedures: Purposive |
Gender: Described participant as trans woman Sexual orientation: Participant described her own experiences navigating sexual orientation Age: Described participant as 70 years Race/ethnicity: NR |
Aim: Provide background information on the mental health of transgender older adults and a model of interdisciplinary care, along with an interview with an older transgender woman regarding her life journey and transition. Outcomes: Qualitative discussion of depression |
The participant described how fears of discrimination while transitioning contributed to her depression. She stressed the importance of encouraging and accepting mental health care providers, in addition to access to transgender specific support groups. |
| Kim et al. (2017) b | Participants: LGBT older adults Sample total: 2,450 GM older adults: 206 Overall sample age: 50–98, M = 66.2 |
Scope/Setting: National (community-based) Methodology: Quantitative Study design: Cross-sectional analysis of survey data Sampling procedures: Convenience, snowball |
Gender: Measured for all using options of male or female; examined in relation to social network types for overall sample Sexual orientation: Measured separately from gender identity; examined in relation to network types for overall sample Age: Measured; examined in relation to network types for overall sample Race/ethnicity: 77.6% NHW; examined in relation to network types for overall sample |
Aim: Describe the social network types of LGBT older adults in terms of relationship status, number of close ties, and frequencies of contact with various types of individuals; examine the relationship between social network types and mental health. Outcomes: Mental health (psychological quality of life on the World Health Organization – BREF) |
Social network types included: diverse, diverse/no children, immediate family-focused, friend-centered/restricted, and fully restricted. Transgender participants were more likely to have the immediate family-focused and fully restricted network types, and the fully restricted network type was associated with the poorest mental health. Larger and more diverse networks predicted better mental health overall. |
| Pharr (2021) | Participants: LGBT and nonbinary older adults Sample total: 3,960 GM older adults: 421 Overall sample age: 50–80+; M = NR |
Scope/Setting: State (31 states with relevant BRFSS data) Methodology: Quantitative Study design: Analysis of cross-sectional data from the BRFSS survey Sampling procedures: Probability |
Gender: Measured and compared as transgender women, transgender men, or nonbinary Sexual orientation: Measured separately from gender identity; examined mutually exclusive subgroups (e.g., cisgender gay men, cisgender lesbian women, all transgender men, all transgender women) Age: Compared age groups of 50–64 vs. 65+ within each subgroup Race/ethnicity: 70.2% NHW; not examined |
Aim: Examine disparities in health care access, disability, heath risk and healthy behaviors, general health, and chronic disease/conditions among LGBT and nonbinary adults aged 50 years and older. Outcomes: Depression diagnosis (self-report); heavy drinking (self-reported drinks per week); poor mental health (reported number of days that mental health was not good during the past 30 days) |
Compared to other subgroups, nonbinary individuals had significantly higher levels of poor mental health days (32%) and depression (38%), as well as disability and poor physical health. Additionally, transgender women and nonbinary individuals were significantly more likely than other subgroups to not have a personal doctor and not have a recent medical checkup. |
| Progovac et al. (2018) c | Participants: GM compared to non-GM Medicare beneficiaries Sample total: Varied by year; ranged from 1,525,926–1,547,650 GM older adults: Ranged from 335–657 (aged 65+) Overall sample age: <65–85+, M = NR |
Scope/Setting: National (Medicare claims database) Methodology: Quantitative Study design: Cross-sectional analysis of Medicare claims Sampling procedures: Algorithm based on gender identity-related diagnostic codes |
Gender: Only measured sex; not examined Sexual orientation: NR Age: Measured; compared GM and non-GM groups within eligibility cohorts based on age (65+) or disability (under 65+) with no other comparison by age Race/ethnicity: Overall: NR; GM, disability: 73% NHW; GM, older age: 88% NHW; not examined |
Aim: Compare chronic conditions and utilization rates of various health care services among GM and non-GM Medicare beneficiaries within eligibility cohorts based on disability or age. Outcomes: Outpatient mental health visits, inpatient mental health visits, psychotropic medications, (all from claims records); any mental health diagnoses (in beneficiary files) |
GM older adults were more likely than non-GM older adults to report multiple chronic conditions (84 vs. 75%) and any mental health conditions (43 vs. 24%). GM older adults were also more likely to have any outpatient (10.3 vs. 3.7%) and inpatient mental health visits (0.15 vs. 0.09%) and psychotropic medication fills (23.2 vs. 18.6%). Similar patterns were found for GM vs. non-GM adults in the disability-eligible cohort. |
| Progovac et al. (2020) c | Participants: GM compared to non-GM Medicare beneficiaries Sample total: 2,244,505 GM older adults: 2,018 (aged 65+) Overall sample age: 18–85+, M = NR |
Scope/Setting: National (Medicare claims database) Methodology: Quantitative Study design: Retrospective analysis of Medicare claims Sampling procedures: Algorithm based on gender identity-related diagnostic codes |
Gender: Only measured sex; not examined Sexual orientation: NR Age: Measured; compared GM and non-GM groups within eligibility cohorts based on age (65+) or disability (under 65+); no other comparison by age Race/ethnicity: NR (referred to previous study for details); examined as a predictor for all groups except GM older adults (too small to report) |
Aim: Compare the prevalence of suicidality among four cohorts of Medicare beneficiaries (GM older adults, GM disabled adults, non-GM older adults, non-GM disabled adults); determine significant predictors of suicidality for these groups. Outcomes: Suicide attempt, suicide ideation, potential suicide attempt (codes in claims records) |
GM older adults were significantly more likely than non-GM older adults to have a suicide attempt (0.5 vs. 0.1%) and suicidal ideation (1.1 vs. 0.4%) but less likely to have a potential suicide attempt (1.7 vs. 3.1%). After adjusting for age and mental health, GM older adults had over twice the odds of any suicidality than non-GM older adults. Predictors of suicidality for GM older adults included Medicaid eligibility, depression, mental health conditions, avoidable hospitalizations, and violence victimization. |
| Puckett et al. (2022) | Participants: Transgender and gender diverse adults Sample total: 695 GM older adults: 27 (Boomers+, born before 1964) Overall sample age: 16–73, M = 25.52 |
Scope/Setting: National (community-based) Methodology: Quantitative Study design: Cross-sectional analysis of survey data Sampling procedures: Convenience |
Gender: Measured using a list with several options, including a write-in; compared subgroups of transgender man, transgender woman, genderqueer, nonbinary, agender, and not listed Sexual orientation: Measured separately from gender identity; not examined Age: Measured; compared generations (Generation Z, Millennials, Generation X, and Boomers+) Race/ethnicity: 75.7% NHW; not examined |
Aim: Examine differences among transgender and gender diverse individuals by gender identity and generation with respect to the timing of identity-related milestones; explore how gender identity, generation, and identity milestones relate to mental health and minority stress. Outcomes: Anxiety (Patient-Reported Outcomes Measurement Information System-Anxiety Scale), depression (Patient-Reported Outcomes Measurement Information System-Depression Scale) |
The Boomers+ group had mean anxiety and depression scores of 53.91 and 50.43, respectively, which were near national averages. Younger generations reported greater internalized stigma, anxiety, and depression than older generations. While older generations attained milestones at older ages than younger generations, living full time in one’s affirmed gender and receiving transition-related medical care predicted lower levels of depression and anxiety overall and within each generation. |
| Putney et al. (2018) | Participants: LGBT older adults Sample total: 50 GM older adults: 3 Overall sample age: 55–87, M = 67 |
Scope/Setting: Multiple communities across one state in the Northeast Methodology: Qualitative Study design: Focus groups Sampling procedures: Convenience, snowball |
Gender: Described as male, female, and transgender Sexual orientation: Measured separately from gender identity Age: Measured and reported in demographics Race/ethnicity: 78% White, 96% non-Hispanic |
Aim: Identify the anticipated needs and fears of LGBT older adults with respect to aging and long-term care facilities. Outcomes: Qualitative discussion of suicidal ideation, fear, distress |
Focus groups expressed concerns about the cost of long-term care, dementia, discrimination, and isolation. They also discussed needs for LGBT-friendly care environments. Transgender participants described fears of anti-transgender bias, suicide ideation due to gender discrimination, and a need for staff trained in transgender-specific care. |
| Rosenwohl-Mack et al. (2022) | Participants: Residents of an LGBTQIA-friendly housing program for older adults Sample total: 21 GM older adults: 3 Overall sample age: 55+; M = 61 |
Scope/Setting: Housing development in a Western U.S. metropolitan area Methodology: Qualitative Study design: Focus groups Sampling procedures: Convenience |
Gender: Described as female, male, and transgender female Sexual orientation: Measured separately from gender identity Age: Measured and reported in demographics Race/ethnicity: 48% White (plurality) |
Aim: Examine the experiences of older adults living in an LGBTQIA+ welcoming and affordable senior housing development, especially in relation to health outcomes. Outcomes: Qualitative discussion of general mental well-being, stress |
Participants overall and transgender participants specifically described the development as improving their mental well-being and decreasing their stress through housing stability, a sense of safety, protection from discrimination, access to health services, and a sense of community. |
| Stanton et al. (2016) | Participants: Transgender and gender nonconforming adults Sample total: 402 GM older adults: 54 Overall sample age: 18–50+, M = NR |
Scope/Setting: National (community-based) Methodology: Quantitative Study design: Analysis of cross-sectional data from U.S. Social Justice Sexuality Survey Sampling procedures: Respondent-driven, snowball, convenience |
Gender: Measured using options of male, female, male-to-female transgender, female-to-male transgender, and other; not examined Sexual orientation: Measured separately from gender identity; not examined Age: Measured; examined age group (18–24, 25–49, 50+) as a predictor Race/ethnicity: 23% NHW; examined as a predictor |
Aim: Examine good health, gender affirming health care, family support, and LGBT community connectedness and participation as predictors of well-being among transgender and gender nonconforming individuals. Outcomes: Well-being (composite self-reported frequency of feeling as good as other people, hopeful for the future, happy, and enjoying life in the past week) |
Within the overall sample, 63% reported high levels of well-being, which was predicted by LGBT community connection, better general health, family support, and perceiving one’s health care provider to be comfortable with one’s identity. Exact well-being scores were not reported within age groups, but being aged 18–24 predicted lower well-being, and being aged 50 years and older predicted higher well-being. |
| Wang et al. (2021) | Participants: Transgender compared to non-transgender VHA users Sample total: 11,560 GM older adults: 1,403 Overall sample age: 18–71+, no mean reported |
Scope/Setting: National (VHA database) Methodology: Quantitative Study design: Retrospective analysis of VHA records Sampling procedures: Algorithm based on gender identity-related diagnostic codes, using a pre-established patient cohort |
Gender: Only measured sex; not examined Sexual orientation: NR Age: Measured; compared health care mobility by age group (18–25, 26–40, 41–50, 51–60, 61–70, and 71+) Race/ethnicity: 84.5% NHW; examined as a predictor of health care mobility for overall sample |
Aim: Determine whether transgender veterans show greater health care mobility within the VHA network than non-transgender veterans; describe demographic and clinical predictors of health care mobility. Outcomes: Depression and post-traumatic stress disorder diagnoses (codes in electronic health records) |
Overall, transgender veterans were more likely than non-transgender veterans to be health care mobile and to travel across states for care. They also had greater diagnoses of depression, post-traumatic stress disorder, and other chronic conditions, which predicted greater mobility. Those aged 61 and older showed less health care mobility compared to younger veterans. |
| White Hughto & Reisner (2018) | Participants: Transgender older adults Sample total: 61 GM older adults: 61 Overall sample age: 50–75, M = 57.7 |
Scope/Setting: State (Massachusetts) Methodology: Quantitative Study design: Cross-sectional survey Sampling procedures: Convenience |
Gender: Measured using several response options; recategorized and compared using “male-to-female” and “female-to-male” spectrum subgroups Sexual orientation: NR Age: Measured; examined age group (50–54, 55–59, 60–64, 65–69, 70–75) as a predictor at bivariate level Race/ethnicity: 78.7% NHW; examined as a predictor at bivariate level |
Aim: Examine the relationship between gender- and age-related discrimination and depressive distress among transgender older adults. Outcomes: Depressive distress (Center for Epidemiological Studies Depression Scale) |
Over half (55.5%) of participants met criteria for past-week depressive distress. Controlling for demographics and number of discrimination experiences unrelated to gender or age, a greater number of discrimination experiences and experiencing gender-based discrimination predicted greater depressive distress. Having a larger number of close friends was protective against depression. |
| White Hughto et al. (2021) | Participants: Transgender compared to cisgender adults Sample total: 62,548 GM older adults: 4,541 Overall sample age: 18–61+, M = NR |
Scope/Setting: National (private insurance claims data warehouse) Methodology: Quantitative Study design: Cross-sectional analysis of insurance claims data Sampling procedures: Algorithm based on gender identity-related diagnostic codes, surgical procedures, and hormone prescriptions |
Gender: Categorized transgender participants as transfeminine, transmasculine, or unknown; compared by gender within overall GM sample only Sexual orientation: NR Age: Measured; stratified comparisons by age groups (18–25, 26–30, 31–35, 36–40, 41–45, 46–50, 51–55, 56–60, 61+) Race/ethnicity: NR |
Aim: Identify the prevalence of substance use disorders among transgender vs. cisgender adults, comparing differences by age, gender, and geographic location. Outcomes: Substance use disorder diagnoses, including alcohol, nicotine, cannabis, cocaine, and opioids (codes in claims records) |
In every age category, transgender adults had significantly higher rates of every substance use disorder than cisgender adults. Nicotine-related disorders were especially prevalent among transgender adults aged 61+ (27%). Overall, transfeminine adults had significantly higher rates of every substance use disorder than transmasculine adults. |
| Witten (2014) | Participants: Transgender adults Sample total: 1,963 GM older adults: 922 Overall sample age: 18–70+, M = NR |
Scope/Setting: National (community-based) Methodology: Mixed methods Study design: Cross-sectional analysis of survey data Sampling procedures: Convenience, snowball |
Gender: Measured and reported using list of 14 options (e.g., transgender, transman, gender queer) Sexual orientation: Measured and reported separately from gender identity Age: Measured and reported in demographics Race/ethnicity: 85.0% NHW |
Aim: Provide relevant results from the Trans MetLife Survey on Later-Life Preparedness and Perceptions in Transgender-Identified Individuals while summarizing literature on transgender aging. Outcomes: Qualitative discussion of anxiety, suicide ideation |
Qualitative responses from transgender older adults revealed worries about aging and end-of-life care as related to their transgender identity. Some revealed thoughts of de-transitioning or suicide due to anxiety about discrimination or victimization in health care settings. They also described fears of discrimination related to ageism, disability, and other prejudices. |
| Yang et al. (2017) | Participants: LGBT older adults Sample total: 222 GM older adults: 17 Overall sample age: 45–65+, M = NR |
Scope/Setting: Metropolitan area in North Carolina Methodology: Quantitative Study design: Cross-sectional survey Sampling procedures: Convenience |
Gender: NR Sexual orientation: Measured and examined only using a mutually exclusive measure of “LGBT identity” (lesbian, gay, bisexual, transgender, or other) Age: Measured; examined age group (45–54, 55–64, and 65+) as a predictor for overall sample Race/ethnicity: 93% White and 96% non-Hispanic; not examined |
Aim: Examine whether experiences with LGBT-welcoming aging service providers are associated with lower levels of perceived isolation among LGBT midlife and older adults and whether these experiences moderate the effects of living alone. Outcomes: Perceived isolation (self-reported feeling of being isolated, somewhat isolated, or not isolated) |
There was no significant difference in perceived isolation between transgender and other subgroups, likely due to an underpowered sample size. For the overall sample, having experiences with welcoming aging service providers both predicted lower perceived isolation and buffered the negative effects of living alone on perceived isolation. |
Note. The use of terms such as “transgender” and “gender minority” in this table reflect the language used in each source. Under “Sample Description,” “GM older adults” represents the number of GM participants aged 50 years or older, or if not reported exactly, the closest available reports using other age groups (e.g., aged 65 and older). Under “Demographic Measures and Analysis,” “Gender” describes whether studies measured gender identity among GM participants, the gender identities represented within these measures, and whether studies (if quantitative) compared differences in relevant outcomes by gender identity. “Sexual Orientation,” “Age,” and “Race/ethnicity” similarly describe whether these characteristics were measured and whether studies (if quantitative) compared differences in relevant outcomes by these characteristics. BRFSS = Behavioral Risk Factor Surveillance System. GM = gender minority. LGBT = lesbian, gay, bisexual, and transgender. NHW = non-Hispanic White. NR = not reported. SGM = sexual and gender minority. VHA = Veterans Health Administration.
Studies are from the To Survive on This Shore project.
Studies are from the Aging with Pride: National Health, Aging, and Sexuality/Gender Study.
Studies are from the same sample of Medicare beneficiaries.
Results
Study Selection
Figure 1 shows the results of the search and selection process. The search produced a total of 1,439 records across all databases, with 1,000 records remaining after removing duplicates and studies automatically flagged as ineligible publication types. After title and abstract screening, 140 records met inclusion criteria. The full text screening resulted in the exclusion of 109 records, for a total of 31 studies included in the final review. These studies represent 24 unique data sources, as two studies (Fabbre & Gaveras, 2020; Gaveras et al., 2021) analyzed data from the interview project To Survive on this Shore, two (Progovac et al., 2018, 2020) analyzed data from the same cohort of Medicare beneficiaries, and six (Fredriksen-Goldsen et al., 2014, 2015, 2017; Hoy-Ellis & Fredriksen-Goldsen, 2017; Hoy-Ellis et al., 2017; Kim et al., 2017) analyzed data from the Aging with Pride: National Health, Aging, and Sexuality/Gender Study.
Study Characteristics
Table 1 provides detailed information regarding the objectives, key findings, and methodological characteristics of the 31 studies included in our review. With respect to methodology, 21 studies (68%) were quantitative, 9 (29%) were qualitative, and one (3%) was mixed methods. Most of the quantitative studies (86%, n = 18/21) used cross-sectional designs, while the rest (14%, n = 3/21) used retrospective designs. The single mixed methods study presented descriptive quantitative and qualitative survey data. Most quantitative studies (71%, n = 15/21) collected survey data, while most qualitative studies (56%, n = 5/9) collected data using individual interviews.
While 39% of all studies (n = 12/31) focused primarily on GM older adults, most had broader target populations but reported findings specific to GM older adults. Specifically, 10 of 31 studies (32%) focused on SGM older adults, and nine (29%) focused on GM adults of all ages. Most studies (71%, n = 22/31) relied upon non-probability sampling methods, such as convenience, snowball, and purposive sampling. Three studies (10%) utilized data from Behavioral Risk Factor Surveillance System (BRFSS) and thus included state level probability samples, although these were not representative of the national GM population due to differences in available data across states. The remaining six studies (19%) identified GM individuals within administrative and health care databases using algorithms based on gender identity-related diagnostic codes. GM older adult sample/subsample sizes (based on the reported number of GM participants aged 50 and older, or the closest available reports if studies described their samples using different age categories) ranged from 1 to 88 among qualitative studies and 17 to 4,541 among the mixed methods and quantitative studies.
Risk of Bias Within and Across Studies
The selected risk of bias assessment tool for this review, the MMAT, is not intended to produce a composite score for included studies (Hong et al., 2018). Thus, we present the ratings of each criterion for each study (Table S1) and a narrative summary of patterns across studies. All 21 quantitative studies were assessed using the criteria for the “quantitative non-randomized” category based on their reported methods, while all nine qualitative studies and the one mixed methods study were assessed using the criteria for the “qualitative” and “mixed methods” categories, respectively. Overall, samples which were unrepresentative of their target populations posed the most common risk of bias among quantitative studies, as none of the quantitative studies included national population-based probability samples. The most common risk of bias among qualitative studies was inadequate data collection methods (n = 7), particularly due to samples which lacked representation of diverse racial and ethnic groups. Additionally, quantitative studies most commonly received ratings of “can’t tell” due to inadequate information for the criterion regarding the completeness of outcome data (n = 9), while qualitative studies most commonly received “can’t tell” ratings for criteria regarding how findings were derived from the data (n = 3), how interpretations were substantiated by data (n = 3), and the coherence of data sources, collection, analysis, and interpretation (n = 3). Potential sources of bias for the mixed methods study were similarly related to non-probability sampling methods and limited descriptions of the analytic process.
Measurement and Analysis of Key Variables
As shown in Table 1, studies varied widely with respect to the measurement and analysis of gender identity as a variable among GM participants. Twenty-three percent of included studies (n = 7/31) only described GM participants as “transgender” or “gender minorities” or reported sex without indicating gender identity (e.g., man, woman, nonbinary), which was often the consequence of relying upon clinical and administrative records without separate fields for gender identity and sex assigned at birth. While most studies (77%, n = 24/31) did report gender identity among GM participants, they diverged in the identities that they reflected. Out of these 24 studies, five (21%) only included transgender women in their samples, five (21%) described participants in exclusively binary terms (i.e., man or woman), and four (17%) included additional descriptors such as “other” or “unknown” for gender identity. Ten of these 24 studies (42%) explicitly included identities beyond the gender binary (e.g., nonbinary, genderqueer, gender nonconforming) in their measures, although one of these (White Hughto & Reisner, 2018) subsequently assigned participants to either a “male-to-female” or “female-to-male” comparison group. Furthermore, even when studies specified GM participants’ gender identities in their demographic descriptions, they often did not retain such distinctions in their analyses. In fact, only seven of the 21 quantitative studies (33%) reported mental health-related across multiple GM subgroups (e.g., transgender women, transgender men, nonbinary individuals) or examined specific gender identity as an explanatory variable for these outcomes.
Studies also differed in their considerations of sexual orientation. Thirty-nine percent of all studies (n = 12/31), which all focused upon GM adults or GM older adults, did not present any sexual orientation information, while 61% (n = 19/31) of all studies included some measure or description of participants’ sexual orientations. Of the studies that reported sexual orientation, about half (53%, n = 10/19) focused on SGM older adults as a broader population and generally did not describe sexual orientation within GM older adult subsamples. Moreover, none of the quantitative studies analyzed potential differences in mental health-related outcomes by sexual orientation among GM older adults, even when they measured both sexual orientation and GM identity as distinct variables.
Nearly all studies (90%, n = 28/31) included race/ethnicity when reporting demographic information, although three (10%) did not. Among the 28 studies that reported race/ethnicity, 25 (89%) examined samples in which non-Hispanic White participants comprised a majority. The remaining three (11%) studies were a case study including one older transgender woman described as Hispanic (Ferron et al., 2010), a qualitative study in which non-Hispanic White participants still comprised a plurality (48%) of the sample (Rosenwohl-Mack et al., 2022), and a quantitative study using data from a survey specifically aimed toward SGM people of color (Stanton et al., 2016). A majority (67%, n = 14/21) of the quantitative studies in this review did not investigate differences in mental health-related outcomes by race/ethnicity, generally controlling for these variables in their analyses. Five (24%) of the 21 quantitative studies examined race/ethnicity as a predictor of mental health-related outcomes only within samples that were not exclusive to GM older adults. Notably, only two (10%) studies (Progovac et al., 2020; White Hughto & Reisner; 2018) examined differences in outcomes of interest by race/ethnicity specifically among GM older adults, with Progovac et al. (2020) being unable to report the results of these analyses among GM older adults due to a small subsample size.
All studies included age in their demographic descriptions. However, most (52%, n = 11/21) quantitative studies analyzed singular “older adult” age groups (e.g., aged 50 and older, aged 65 and older) without examining further variation in mental health-related outcomes by age within these groups. Five (24%) of the 21 quantitative studies examined differences in mental health-related outcomes by age within broader samples of SGM older adults, but not specifically among GM older adults. Only five (24%) of the quantitative studies tested for differences in mental health-related outcomes by age specifically within samples or subsamples of GM older adults.
Synthesis of Findings
Major Concerns and Disparities
The examined literature presented quantitative descriptions of a wide range of mental health concerns among GM older adults. Three studies measured the prevalence of suicide-related outcomes among GM older adults, including suicide deaths (Boyer et al., 2021), attempts (Hillman, 2021; Progovac et al., 2020), and ideation (Progovac et al., 2020). Two of these (Boyer et al., 2021; Progovac et al., 2020) found that GM older adults had significantly greater risks for suicide-related outcomes compared to non-GM older adults, while the other (Hillman, 2021) did not include a non-GM comparison group. Differences in study populations, data sources, and measures resulted in divergent findings for the two sources which both examined suicide attempts; using Medicare claims data, Progovac et al. (2020) reported that 0.5% of GM beneficiaries aged 65 and older had records of suicide attempts, while Hillman (2021) found that 28% of respondents to the U.S. Transgender Survey aged 50 and older reported lifetime suicide attempts.
Five studies measured the prevalence of depression among GM older adults, specifically using self-reported diagnosis (Brown & Patterson, 2020; Pharr, 2021), clinical and administrative records (Dragon et al., 2017), and defined cut-off scores on self-reported depression screeners (Hoy-Ellis & Fredriksen-Goldsen, 2017; White Hughto & Reisner, 2018). Among these, prevalence estimates ranged from 29.6% (Pharr, 2021) to 55.7% (White Hughto & Reisner, 2018). Notably, Pharr (2021) reported findings separately by gender identity among GM older adults, finding this estimate of 29.6% specifically among older transgender women. Four studies (Cortes et al., 2019; Fredriksen-Goldsen et al., 2014; Hoy-Ellis et al., 2017; Puckett et al., 2022) did not estimate the categorical prevalence of depression among GM older adults but presented mean scores on varying self-reported depression screeners. The studies that compared depression outcomes between samples of GM and non-GM older adults (Brown & Patterson, 2020; Dragon et al., 2017; Fredriksen-Goldsen et al., 2014; Pharr, 2021) found that GM older adults had a significantly greater prevalence of depression diagnoses compared to non-GM older adults (Brown & Patterson et al., 2020; Dragon et al., 2017) and higher levels of depression symptoms compared to non-GM sexual minority older adults (Fredriksen-Goldsen et al., 2014). Pharr (2021) reported that nonbinary older adults specifically had a significantly greater prevalence of depression diagnoses compared to older transgender men, older transgender women, and subgroups of non-GM sexual minority older adults.
Four studies described the prevalence of substance use disorders or clinically significant substance use among GM older adults, although these varied in the specific outcomes that they examined. Two of these used insurance claims data to examine any substance use disorder diagnoses (Dragon et al., 2017) and specific substance use disorder diagnoses (White Hughto et al., 2021), and two (Hillman, 2021; Pharr, 2021) examined self-reported past 30-day binge drinking. Among the studies that compared GM and non-GM older adults, Dragon et al. (2017) and White Hughto et al. (2021) each found that GM older adults had a significantly greater prevalence of substance use disorders overall, with White Hughto et al. (2021) noting that nicotine use disorders were especially common among GM adults aged 61 and older. Pharr (2021) found that nonbinary older adults had significantly elevated levels of binge drinking compared to other subgroups of SGM older adults, while Hillman (2021) did not include any comparisons. Another study (Cortes et al., 2019) presented the mean scores of GM veterans aged 50 and older on a self-reported alcohol use disorders screener but did not report the prevalence of scores above a defined threshold or compare scores to non-GM older adults.
Two studies (Cortes et al., 2019; Puckett et al., 2022) presented the mean scores of GM older adults on different self-reported anxiety screeners, although neither described the prevalence of clinically significant scores. Only one study (Dragon et al., 2017) examined the prevalence of clinical anxiety among GM older adults, using Medicare claims data to conclude that GM beneficiaries aged 65 and older were significantly more likely than non-GM beneficiaries aged 65 and older to have anxiety diagnoses. Dragon et al. (2017) also found that GM older adult beneficiaries had a greater prevalence of bipolar disorder, personality disorders, post-traumatic stress disorder, and schizophrenia and other psychotic disorders compared to non-GM older adult beneficiaries. While no other studies examined these specific conditions, Progovac et al. (2018) also examined Medicare claims data and found that GM older adults were more likely than non-GM older adults to have diagnoses of any mental health conditions.
Studies also used several different self-reported measures of general mental health outcomes. Four studies (Fredriksen-Goldsen et al., 2015, 2017; Hoy-Ellis et al., 2017; Kim et al., 2017) examined psychological quality of life, and two (Fredriksen-Goldsen et al., 2014; Hoy-Ellis & Fredriksen-Goldsen, 2017) examined perceived stress, with all reporting data from the Aging with Pride: National Health, Aging, and Sexuality/Gender Study. Other outcomes included severe mental distress (Hillman, 2021), past 30-day poor mental health days (Pharr, 2021), and perceived isolation (Yang et al., 2017). The studies that compared these general mental health outcomes among GM and non-GM older adult subgroups (Fredriksen-Goldsen et al., 2014, 2015; Pharr, 2021; Yang et al., 2017) generally found worse outcomes for GM older adults. However, Yang et al. (2017) found no significant association between GM identity and perceived isolation, citing their small sample size as a potential explanation. Additionally, Pharr (2021) found more poor mental health days specifically among nonbinary older adults compared to subgroups of other GM older adults and non-GM sexual minority older adults, reflecting variation by gender identity.
Risk Factors for Mental Health Concerns
A large portion of the literature discussed connections between mental health concerns and risk factors related to stigma and oppression among GM older adults. Among quantitative studies, three studies examined and identified internalized stigma as a risk factor, specifically for greater depression (Fredriksen-Goldsen et al., 2014; Hoy-Ellis & Fredriksen-Goldsen, 2017; Hoy-Ellis et al., 2017), greater perceived stress (Fredriksen-Goldsen et al., 2014; Hoy-Ellis & Fredriksen-Goldsen, 2017), and lower psychological quality of life (Hoy-Ellis et al., 2017). Four studies examined identity-based discrimination, which was associated with greater depression (Fredriksen-Goldsen et al., 2014, 2017; White Hughto & Reisner, 2018) and worse mental health quality of life (Fredriksen-Goldsen et al., 2015). One study (Hillman, 2021) focused on lifetime intimate partner violence, finding that it was associated with greater substance use, psychological distress, and lifetime suicide attempts, while another study (Progovac et al., 2020) similarly identified any violence victimization as a risk factor for suicidality. Evidence from the qualitative studies generally aligned with these results. Among these, five studies (Carroll, 2017; Elder, 2016; Fabbre, 2014; Fabbre & Gaveras, 2020; Johnson et al., 2018) discussed how fears and experiences of discrimination, family rejection, and stigmatization contributed to struggles with depression, anxiety, and other forms of distress among GM older adults. Five qualitative studies (Carroll, 2017; Elder, 2016; Fabbre, 2014; Fabbre & Gaveras, 2020; Gaveras et al., 2021) also highlighted lifetime experiences of trauma and abuse among GM older adults, which participants often discussed in relation to suicidality, substance use, depression, and other mental health concerns later in life.
Four quantitative studies (Fredriksen-Goldsen et al., 2014; Progovac et al., 2018, 2020; Wang et al., 2021), three qualitative studies (Elder, 2016; Fabbre & Gaveras, 2020; Putney et al., 2018) and the mixed methods study (Witten, 2014) discussed broader issues of health care access and quality in relation to mental health concerns among GM older adults, with somewhat mixed findings. Quantitative analyses of claims data from the same sample of Medicare beneficiaries found greater needs-adjusted mental health service utilization (Progovac et al., 2018) and fewer avoidable hospitalizations, interpreted as a proxy for preventative health care barriers (Progovac et al., 2020), among GM compared to non-GM beneficiaries aged 65 and older. However, avoidable hospitalizations predicted greater suicidality among both groups (Progovac et al., 2020). Additionally, Wang et al. (2021) observed that GM veterans within the Veterans Health Administration were more likely than non-GM veterans to access multiple health care systems, which was related to disparities in depression and other chronic conditions, although this utilization of multiple systems decreased among GM veterans aged 61 and older. In contrast to these findings regarding health care access from studies using administrative records, Fredriksen-Goldsen et al. (2014) identified greater fears of accessing health services among GM older adults compared to non-GM sexual minority older adults, which partially explained disparities in self-reported depression and stress. The qualitative and mixed methods studies similarly identified transphobic and pathologizing past experiences in therapy (Elder, 2016), experiences of discrimination in general health care settings (Elder, 2016; Fabbre & Gaveras, 2020), and anticipated discrimination in long-term care settings (Fabbre & Gaveras, 2020; Putney et al., 2018; Witten, 2014) as sources of anxiety and distress among GM older adults.
Finally, studies explored relationships between mental and physical health-related outcomes among GM older adults. Among the three quantitative studies investigating this topic, Fredriksen-Goldsen et al. (2014) found that greater physical inactivity was associated with disparately high levels of depression and perceived stress among GM older adults compared to non-GM sexual minority older adults, and Brown & Patterson (2020) and Flatt et al. (2021) each found that the greater prevalence of depression among GM versus non-GM older adults was associated with disparately high levels of subjective cognitive decline. One qualitative case study (Ferron et al., 2010) similarly illustrated the complex interactions between co-occurring concerns of depression, HIV, and other chronic conditions among GM older adults.
Protective Factors for Mental Health Concerns
Studies also investigated resources and experiences that may mitigate some mental health concerns among GM older adults. Five quantitative studies proposed various social resources as protective factors among GM older adults, specifically examining the associations of social network size with depression (Fredriksen-Goldsen et al., 2014; White Hughto & Reisner, 2018), perceived stress (Fredriksen-Goldsen et al., 2014) and mental health quality of life (Fredriksen-Goldsen et al., 2015; Kim et al., 2017); general social support with depression (Fredriksen-Goldsen et al., 2014), perceived stress (Fredriksen-Goldsen et al., 2014), and mental health quality of life (Fredriksen-Goldsen et al., 2015); family support with depression (White Hughto & Reisner, 2018); and feelings of LGBT community belonging with depression and perceived stress (Fredriksen-Goldsen et al., 2014). These factors were generally associated with better mental health outcomes as predicted. However, Fredriksen-Goldsen et al. (2014) found that social network size was not associated with depression or perceived stress, in contrast to the protective relationship that White Hughto & Reisner (2018) identified. Additionally, White Hughto & Reisner (2018) noted that family support predicted lower depression at the bivariate but not multivariate level. Notably, Fredriksen-Goldsen et al. (2014) found that lower levels of social support and LGBT community belonging among GM older adults compared to non-GM sexual minority older adults partially explained disparities in depression and perceived stress, highlighting unequal access to some protective social resources. Six qualitative studies offered converging evidence of these relationships. While these studies named support from friends and family (Fabbre, 2014; Fabbre & Gaveras, 2020; Gaveras et al., 2021), activism and engagement within GM communities (Carroll, 2017; Elder, 2016; Fabbre & Gaveras, 2020), and a sense of community and safety from discrimination within long-term housing (Rosenwohl-Mack et al., 2022) as important sources of well-being for GM older adults, they also identified mixed experiences with family acceptance (Carroll, 2017; Elder, 2016; Fabbre & Gaveras, 2020) and ambivalent perceptions of connection to broader “LGBT” spaces (Fabbre & Gaveras, 2020; Rosenwohl-Mack et al., 2022).
Additionally, three quantitative studies (Fredriksen-Goldsen et al., 2014; Puckett et al., 2022; Hoy-Ellis & Fredriksen-Goldsen, 2017) specifically explored the relationships between mental health and identity-related processes among GM older adults. Among these, one study (Puckett et al., 2022) examined gender-affirming medical care and living as one’s affirmed gender, finding that these experiences predicted lower self-reported depression and anxiety among GM individuals within and across generational groups, including baby boomers and older. Two studies examined gender identity disclosure among the same sample of GM older adults but found mixed results. While gender identity disclosure was inversely related to perceived stress and depression in one study (Fredriksen-Goldsen et al., 2014), another analysis (Hoy-Ellis & Fredriksen-Goldsen, 2017) found no association between identity disclosure and perceived stress or depression. Qualitative findings within this domain were similarly nuanced. Overall, six qualitative studies (Carroll, 2017; Elder, 2016; Fabbre, 2014; Fabbre & Gaveras, 2020; Gaveras et al., 2021; Johnson et al., 2018) addressed the fraught nature of identity disclosure and transitioning due to societal stigma alongside the positive emotional impacts of the transition process, with supportive mental health professionals being important sources of gender affirmation.
Finally, seven quantitative studies (Boyer et al., 2021; Cortes et al., 2019; Pharr, 2021; Puckett et al., 2022; Stanton et al., 2016; White Hughto & Reiser, 2018; White Hughto et al., 2021) examined older age itself as a predictor of mental health outcomes among GM individuals, although there were few overlaps in study aims and findings. One study (Stanton et al., 2016) compared self-reported psychological well-being by age among GM adults, finding that being aged 50 and older predicted higher well-being while being aged 18–24 predicted lower well-being. Puckett et al. (2022) similarly reported that GM baby boomers and older reported significantly lower anxiety and depression than GM adults of younger generations. However, Cortes et al. (2019) found no differences in anxiety or depression between GM veterans aged 50 and older versus younger than 50, and Boyer et al. (2021) reported a stable prevalence of suicide across GM individuals aged 18–39, 40–64, and 65 and older in the Veterans Health Administration. Furthermore, specifically among GM adults aged 50 and older, White Hughto & Reisner (2018) found that older age was associated with greater self-reported depressive distress, while Pharr (2021) found no differences in self-reported depression diagnosis between GM adults aged 50–64 versus 65 and older. Among the two studies that examined substance use, Cortes et al. (2019) found that transgender female veterans, but not transgender male veterans, aged 50 and older reported less alcohol use than their peers aged younger than 50. Using insurance claims data, White Hughto et al. (2021) similarly found that alcohol use disorders were most prevalent among GM adults aged 18–25 compared to older age groups, although nicotine use disorders were most prevalent among GM adults aged 61 and older. Pharr (2021) found no differences in self-reported alcohol use between those aged 50–64 versus 65 and older within subgroups of transgender women, transgender men, and nonbinary individuals.
Discussion
This systematic review of the literature on the mental health of GM older adults in the United States has evaluated the methodological state of an emergent body of research, in addition to highlighting critical issues facing an overlooked population. The review identified 31 eligible studies, which were largely characterized by quantitative methodologies, cross-sectional designs, non-probability samples, and limited attention to the varying experiences of GM older adults across positions of gender identity, sexual orientation, race and ethnicity, and age. Overall, studies provided evidence of disparities in suicidality, specific mental health conditions, and general mental health measures among GM older adults, echoing findings among GM populations more broadly (Nobili et al., 2018; Reisner et al., 2016). Additionally, quantitative and qualitative findings regarding a wide range of proposed risk and protective factors revealed the social and structural context of mental health concerns among GM older adults.
These results were consistent with existing frameworks linking systemic oppression to health disparities. For example, many of the risk factors (e.g., discrimination, rejection, victimization, internalized stigma) and protective factors (e.g., community connectedness) that studies identified are included within the gender minority stress model (Hendricks & Testa, 2012; Testa et al., 2015). Hatzenbuehler et al.’s (2013) theory of stigma as a fundamental cause of health disparities, which subsequent studies have supported specifically among U.S. GM populations (Felt et al., 2021), similarly posits that stigma both produces health-impairing stressors and disrupts access to health-protective resources. In alignment with this theory, included studies frequently connected health care barriers, obstacles to transitioning, and uncertain access to social resources to mental health concerns among GM older adults. Notably, studies also captured manifestations of stigma specific to GM older adults’ experiences, such as lifetime exposure to transphobic victimization and anticipated bias in long-term care settings.
This review offers several implications for clinical practice, policy, and future research. First, findings support existing recommendations that clinicians understand both the mental health disparities that GM older adults face as well as the roles of stigma, discrimination, and violence in driving these disparities (American Psychological Association, 2015). Recognizing mental health disparities as resulting from systemic oppression rather than intrinsic factors is especially salient considering the longstanding pathologization of GM identities within the United States and internationally (Castro-Peraza et al., 2019). Indeed, as Elder (2016) described, some GM older adults have traumatic past experiences within mental health services due to construals of GM identities as mental illnesses. Thus, as others have suggested, clinicians should not only validate GM older adults’ gender identities but also maintain a critical awareness of how historical and cultural forces may inform their relationships to treatment (Porter et al., 2016). Clinicians working with GM older adults can also facilitate access to protective resources by helping their clients find social connections and opportunities for community engagement, identifying other affirming health and aging services, and providing support related to social, medical, and legal transition processes as their clients desire.
Review findings also have implications for policy interventions that may intervene in mental health disparities among GM older adults. For example, discrimination experiences both in everyday contexts and specifically in health, aging, and social services were overarching risk factors identified across the literature. Federal antidiscrimination legislation that explicitly includes gender identity, such as the Equality Act, would protect GM older adults within public accommodations and federally funded programs (e.g., senior centers, food assistance, transportation services), which existing federal laws do not cover (SAGE, 2021). Additionally, policy could address the limited visibility of GM older adults within key sources of public health data. The six studies that collected data from health care and administrative records relied upon gender identity-related diagnoses as a proxy for GM identity due to a lack of separate information about sex assigned at birth and gender identity. Such sampling methods exclude GM individuals without gender identity-related diagnoses, including those who do not meet diagnostic criteria, choose not to pursue transition-related care, or face barriers to accessing health care altogether. Likewise, not all states collect sexual orientation, sex assigned at birth, and gender identity information through BRFSS (CDC, 2021). As noted by the three studies that utilized BRFSS data, this limits the conclusions which can be drawn about the mental health of GM older adults nationwide. Policies supporting the implementation of consistent, validated measures of sex assigned at birth and gender identity in electronic health records and federal health surveys would facilitate efforts to address mental health disparities facing GM older adults and GM individuals more broadly (Henderson et al., 2019; Kronk et al., 2022).
Among the most notable implications of this review is the need for further research attention to the mental health of GM older adults. This review identified 31 studies from 24 unique data sources meeting eligibility criteria, with 19 (61%) of these including GM older adults as a subset of broader samples rather than an exclusive research focus. Thus, despite the breadth of mental health concerns investigated within the included literature, the cumulative evidence regarding each specific outcome among GM older adults remains limited. Consequently, future research should both explore new directions and further probe existing findings, particularly using designs that can bridge key methodological gaps. For example, given that 86% of quantitative studies (n = 17/21) used cross-sectional designs to identify correlates of specific mental health outcomes, longitudinal studies could clarify the temporal dimensions of these relationships. Longitudinal studies could also shed light on areas of ambiguity within the current literature, such as the pathways through which gender identity disclosure may have positive or negative effects on different mental health outcomes. Moreover, prospective cohort studies are specifically needed to reveal the long-term effects of risk factors such as stigmatization on the mental health of GM older adults across the life course.
Future research should also center the diverse and multifaceted experiences of GM older adults. For example, this review found that less than one quarter (24%, n = 5/21) of quantitative studies examined potential differences in their primary outcomes by age within samples or subsamples of GM older adults. However, evidence among the broader U.S. older adult population indicates that risk factors including loneliness and isolation (Ailshire and Crimmins, 2011; Barnes et al., 2021), chronic conditions, and functional limitations (Maresova et al., 2019) increase with age. In addition to health and social concerns associated with aging itself, the historical social contexts that GM older adults were born into may shape distinct life trajectories from generation to generation (Fredriksen-Goldsen et al., 2019). Quantitative and qualitative efforts are needed to understand how dynamic interactions between biological and psychological aging processes, historical and cultural forces, and contemporary manifestations of transphobia and ageism influence GM older adults’ mental health.
In alignment with previous works (e.g., Magliozzi et al., 2016; Suen et al., 2020), our review revealed tendencies to combine transgender men, transgender women, and nonbinary and other gender diverse individuals into one group for analysis. Studies also inconsistently represented identities beyond the male/female binary (e.g., nonbinary, genderqueer, two-spirit) in their gender identity measures. Importantly, some of the few studies that disaggregated data by gender identity found notable differences in mental health outcomes. For example, Pharr (2021) reported significantly greater binge drinking, depression, and poor mental health days among nonbinary older adults compared to older transgender men, older transgender women, and various subgroups of non-GM sexual minority older adults, evidencing the need for future research to explore the distinct experiences of GM older adults with different gender identities. Relatedly, the exclusion of GM older adults’ diverse sexual orientations within studies’ measures and analyses leaves critical knowledge gaps. Further research is needed to investigate the ways in which unequal distributions of health risks and resources by sexual orientation (Bränström et al., 2016) manifest specifically among GM older adults.
Paralleling broader patterns within SGM health and aging research (Fredriksen-Goldsen et al., 2019; Laganá et al., 2021), included studies were characterized by predominately non-Hispanic White samples and rarely examined differences in mental health outcomes among GM older adults by race and ethnicity. This represents a critical gap, especially considering that risk factors such as transphobic violence are disproportionately distributed among GM people of color (Fitzgerald, 2019) and that GM people of color face racialized disparities in access to protective resources such as gender affirming mental health care (Lett et al., 2022). Capturing the ways in which racism intersects with transphobia, ageism, and other systems of oppression to produce mental health disparities requires careful consideration of complex power relations throughout the research process, which others (Bauer, 2014; Bauer & Scheim, 2019; Bowleg, 2012; Wesp et al., 2019) have extensively discussed. At minimum, future work could formulate qualitative and quantitative research questions that center the experiences of racially and ethnically marginalized GM older adults, including those within Asian American, Black and African American, Hispanic and Latina/o/x, and Indigenous communities. Additionally, research must actively strive for samples that enable analyses within and across subgroups of GM older adults based on race and ethnicity.
Limitations
Overall, the small size of the literature combined with heterogeneous outcomes and measures weaken the certainty of evidence for quantitative claims about the prevalence or correlates of specific mental health concerns. When studies did examine the same mental health outcomes or predictive relationships, they were often inconsistent in their measures (e.g., self-reported diagnosis, various symptom questionnaires, diagnostic codes in health records) and reporting (e.g., frequency of scores above a specific cutoff or sample mean scores for symptom screeners), preventing any meaningful meta-analysis of results. Inconsistent definitions of “older adult” (e.g., aged 50 and older, 65 and older) also make comparisons of quantitative findings difficult. While this review used the term “gender minority (GM)” throughout for clarity and consistency, studies described their populations using varying language (e.g., gender minority, transgender, transgender and gender nonconforming), which can present similar challenges regarding comparison and synthesis.
As previously discussed, a reliance upon nonprobability sampling techniques limits the generalizability of quantitative findings from individual studies. As several studies (e.g., Fredriksen-Goldsen et al., 2014; Hillman, 2021; Puckett et al., 2022) acknowledged regarding their own methods, techniques such as convenience, community-based, and snowball sampling may systematically underrepresent GM older adults in rural areas, with less access to SGM community organizations, belonging to marginalized racial and ethnic groups, and with limited Internet access. The lack of longitudinal, particularly prospective cohort, study designs prevented quantitative studies from identifying causal relationships between mental health outcomes and their correlates. For studies that compared different age groups of GM older adults, this also prevented distinguishing between age-related and generational effects.
This review itself should be considered in the context of some limitations. First, we exclusively examined peer-reviewed journal articles, given our aim of describing the state of academic literature. Consequently, this review does not represent findings from gray literature, such as surveys by various health agencies and community organizations, that may be relevant to the mental health of GM older adults. This review focuses on GM older adults in the United States and does not reflect the content and characteristics of international literature, although some of the discussed implications for research, policy, and practice may hold international relevance. We also restricted our review to studies published since 2010, excluding potentially relevant literature published before this date. The search strategy may also have limitations. Given the examined time frame, the search strategy did not include outdated medical terms such as “transsexualism,” which may have omitted potentially eligible studies that exclusively used such terminology to refer to GM individuals. Additionally, studies that examined mental health-related outcomes among GM older adults but did not indicate this in their titles or abstracts may have been excluded in the first screening stage. Several otherwise eligible studies were excluded in the full text screening stage because they did not provide data specific to GM individuals (n = 16) or older adults (n = 22) despite explicitly including GM individuals and older adults within broader samples. We did not contact the authors of these excluded studies for disaggregated data given our intention of representing the literature as published, but this loss of information is vital for future research to consider. Finally, this body of literature, while small, is rapidly expanding; almost one-third of included studies (32%, n = 10/31) were published between 2021 and our final search date in March 2022. Therefore, it is possible that our review did not capture recently published studies that would have otherwise fallen within our scope.
Conclusion
Despite the recent increased interest in the mental health of GM individuals, GM older adults remain an understudied population. This systematic review synthesized the existing literature on this topic, finding evidence that GM older adults experience disparities in suicidality, depression and other specific mental health conditions, and general mental health measures compared to non-GM older adults. The literature also highlighted risk factors (e.g., violence, discrimination, broader health care inequities) and protective factors (e.g., social support, access to transition-related resources) that may have important implications for clinical practice and policy. However, the included studies were characterized by unrepresentative samples, cross-sectional designs, and methods that lacked attention to GM older adults’ multiple positionalities, including gender identity, age, sexual orientation, race, and ethnicity. Ultimately, this review reveals a critical need for further research that both addresses existing methodological limitations and investigates how intersecting systems of marginalization harm the mental health of GM older adults across the life course.
Supplementary Material
Public Significance:
This systematic review highlights mental health disparities facing gender minority older adults and identifies factors which may impact these outcomes, including stigma, violence, discrimination, and access to protective resources such as health care and social support. The results of this review have important implications for policy and for clinicians working with gender minority older adults, and they also reveal critical methodological limitations and gaps in knowledge for future research to address.
Support and Competing Interests
The authors have no sources of financial or non-financial support for this project nor have any conflicts of interest to disclose.
Registration and Data Availability
This protocol for this review is unregistered but available upon request, along with the completed PRISMA-P checklist. Template data collection forms are also available upon request. The completed PRISMA 2020 checklist is available as supplemental material (Table S2).
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
This protocol for this review is unregistered but available upon request, along with the completed PRISMA-P checklist. Template data collection forms are also available upon request. The completed PRISMA 2020 checklist is available as supplemental material (Table S2).