Transgender Adults Have Higher Rates Of Disability Than Their Cisgender Counterparts – healthaffairs.org
As the US population ages, the proportion of adults living with some sort of disability is projected to increase. Research has established that disability is not equally distributed in the population but follows patterns of social stratification. Women, for example, are more likely than men to have a disability as they age.1,2 However, very little is known about the experiences of gender minorities compared with cisgender patterns. (The term cisgender refers to people whose sex assigned at birth [male or female] aligns with their gender identity [man or woman] and expression [masculine or feminine].) This is concerning, given the particular vulnerability of gender minorities in both physical and mental health outcomes.3
Gender disparities in physical health stem from several sources. Biological differences predispose health outcomes, but different processes of socialization also prepare men and women for distinct social expectations, affecting health.4,5 Further, social structures constrain health behaviors and health-enhancing resources, depending on gender.6 Research on gendered disparities in disability remains almost exclusively reliant on a cisgender paradigm,7,8 excluding the estimated 1 in 250 adults in the US who are transgender (those whose sex assigned at birth does not correspond to their gender identity).9
Overlooking transgender experiences obscures disparities, as transgender adults tend to have poorer health outcomes than their cisgender counterparts. Transgender people have worse self-rated health, poorer health care access and use,10 more poor mental health days,11 and higher rates of smoking, on average, compared with cisgender people.12
Scholars link disparities to transgender people’s disadvantaged social position relative to the cisgender majority. Transgender people experience “minority stress,”13 facing discrimination across multiple social arenas,14 including at work15,16 and from health care providers17 and policies.18,19 Transgender stigma (systematic interpersonal and institutional discrimination against transgender people) has been theorized as a fundamental cause of health disparities.20–22
Despite evidence of transgender disadvantage, the rates of disability of transgender people at the population level are largely unknown.23,24 Transgender health research still suffers from a lack of data that include a cisgender comparison group.25 Available samples are often restricted to particular communities, age groups, or a few states.26–30 Limited sample sizes often prohibit the intersection of age with transgender identity, even though age is an important predictor of health.31
In this study I drew on the Behavioral Risk Factor Surveillance System (BRFSS), one of the largest national samples including cisgender and transgender groups, to intersect age, transgender identity, and disability status. Results spotlight the compound vulnerabilities faced by gender minorities in the US.
Study Data And Methods
The BRFSS is a random-digit-dial telephone survey designed by the Centers for Disease Control and Prevention (CDC) and administered by state health departments. All responses were weighted to account for national differences in age, race and ethnicity, education level, and marital status. I pooled seven waves of cross-sectional data spanning 2014–20 from forty-three US states and one territory (Guam).
The outcome was a binary measure of whether a person had a functional limitation (defined as any difficulty walking or climbing stairs, dressing or bathing, running errands alone, concentrating, remembering, or making decisions). The predictor variable was a three-category measure of gender identity. In 2014 the CDC added an optional module to the BRFSS to collect data on sexual orientation and gender identity. I categorized respondents as transgender if they answered “yes” to the question, “Do you consider yourself to be transgender?” and cisgender if they answered “no.” Cisgender respondents were further categorized as men and women by their self-reported sex (male or female).
Demographic covariates were age at interview, partnership status, racial or ethnic minority status (non-Hispanic Black, Hispanic, Asian, Native American, and other), and sexual orientation (heterosexual, gay or lesbian, and bisexual). Socioeconomic covariates include education (high school and below, some college, and college degree or higher), employment status, a four-category measure of annual household income, and insurance status. Health behavior covariates included smoking status, heavy alcohol consumption,32 and obesity (body mass index, ).
Statistical Analysis
I first produced weighted descriptive statistics to display how relevant characteristics differed by gender. I then estimated a series of nested logistic regression models predicting disability by gender identity. The adjusted models attempted to isolate the association of identifying as transgender person with the likelihood of having a functional limitation across age groups. I therefore controlled for factors that were associated with disability or differed across gender identity samples. Model 1 was bivariate, predicting disability with gender identity. Model 2 added demographic controls, model 3 added socioeconomic controls, and model 4 added health behaviors. All models also controlled for state and year fixed effects (see the online appendix for detailed model results and methods).33 Finally, I calculated the adjusted predicted probability of reporting a disability. Missing data were imputed using multiple imputation with chained equations in Stata 15.
Limitations
This study had several limitations. First, it relied on self-reported survey measures of disability and gender identity that have been simplified because of small sample sizes. Although aggregating different kinds of functional limitations into one dichotomous measure is imperfect, very little is known about how disability among transgender adults compares with disability among cisgender counterparts. As larger samples become available, future studies should disaggregate limitation types (given evidence that the ability to successfully accommodate limitations through the use of special equipment varies)9 and disaggregate gender identities (given evidence of within-group differences across transgender subgroups in self-rated health,22,27,29 poor physical health days,26 experiences of discrimination,12 mental health, and health behaviors28). Findings of excess disability among transgender people may be driven by particular experiences among trans men, trans women, or gender-nonconforming respondents.
Second, a limitation of the BRFSS gender identity module is that some gender-nonconforming people might not consider themselves transgender and would therefore be inaccurately classified. This analysis was only able to capture gender minority respondents who answered, “yes” to the question, “Do you consider yourself to be transgender?”
Third, data on gender identity were available only for forty-three US states (the omitted states were Alabama, Maine, Nebraska, New Hampshire, North Dakota, Oregon, and South Dakota) and the territory of Guam. The findings are therefore only representative of forty-three states and Guam. The omitted states contain less than 0.5 percent of the US population.34 It is unlikely that the experience of transgender people in these states would dramatically influence trends in disability. Of these states, Maine, Oregon, and New Hampshire offer some nondiscrimination legal protections on the basis of gender identity.35 Transgender adults in these states may be better positioned to enjoy improved health outcomes. Alabama, Nebraska, North Dakota, and South Dakota remain among those states lacking any explicit legal protections from discrimination based on gender identity. If discrimination is higher in states with more unfriendly policy contexts, transgender people may expect worse health outcomes because of barriers to care and elevated stress. Omitting these states from the analysis thus would suggest that any disparities found are conservative estimates of burden of disability among transgender adults.
Fourth, although this study was able to intersect age, transgender identity, and disability status, it excluded other key axes of inequality such as race and ethnicity. Transgender people of color, in particular, experience compounding vulnerability accompanying multiple disadvantaged statuses.36
Study Results
Descriptive Trends In Disability
The unweighted sample consisted of 1,400,043 adults, ages eighteen and older. In the weighted sample (exhibit 1), transgender adults tended to be younger and were less likely to be partnered or to have graduated from high school. They were more likely to be a sexual minority, be a racial minority, and have low income compared with cisgender respondents. These differences demonstrate the importance of controlling for such factors when estimating disparities in disability.
Characteristics | Cisgender men | Cisgender women | Transgender |
Has at least one functional limitation | 18% | 24% | 30% |
Age (years) | |||
18–24 | 13% | 11% | 25% |
25–29 | 8 | 7 | 10 |
30–34 | 9 | 9 | 8 |
35–39 | 8 | 8 | 7 |
40–44 | 8 | 8 | 7 |
45–49 | 8 | 8 | 6 |
50–54 | 10 | 9 | 8 |
55–59 | 9 | 9 | 8 |
60–64 | 9 | 9 | 7 |
65–69 | 7 | 7 | 5 |
70–74 | 5 | 6 | 4 |
75–79 | 4 | 5 | 3 |
80+ | 4 | 5 | 3 |
Partnered | 58 | 54 | 45 |
Racial minoritya | 36 | 36 | 43 |
Sexual orientation | |||
Heterosexual | 96 | 96 | 67 |
Gay or lesbian | 2 | 01 | 12 |
Bisexual | 2 | 03 | 21 |
Education | |||
High school and below | 42% | 38% | 55% |
Some college | 30 | 33 | 29 |
College and above | 27 | 28 | 16 |
Employed | 64 | 51 | 51 |
Annual household income | |||
<$25,000 | 23 | 3 | 42 |
$25,000–$49,999 | 23 | 24 | 25 |
$50,000–$74,999 | 16 | 15 | 12 |
$75,000+ | 38 | 31 | 21 |
Insured | 87 | 90 | 84 |
Current smoker | 18% | 14S% | 20% |
Heavy drinker | 9 | 6 | 7 |
Obese | 31 | 31 | 32 |
Transgender adults reported higher rates of disability (30 percent) compared with cisgender women (24 percent) or cisgender men (18 percent). This measure aggregated four categories of functional limitation, displayed in exhibit 2. Taken together, the probabilities of disability in exhibit 2 display a mixed pattern by gender identity. Cisgender women had the highest overall proportion of disability, but transgender people experienced higher rates of difficulty doing errands alone and of concentrating, remembering, and making decisions. Cisgender men consistently reported the lowest proportion of limitation.
Cisgender men
|
Cisgender women
|
Transgender
|
||||
Functional limitations | Percent | Number | Percent | Number | Percent | Number |
Difficulty walking or climbing stairs | 19.44 | 84,928 | 21.90 | 151,971 | 17.01 | 1,305 |
Difficulty dressing or bathing | 4.39 | 23,942 | 7.94 | 34,285 | 4.19 | 473 |
Difficulty doing errands alone | 5.42 | 33,154 | 9.11 | 71,101 | 15.09 | 898 |
Difficulty concentrating, remembering, or making decisions | 9.03 | 55,215 | 11.07 | 86,386 | 22.79 | 1,357 |
Difficulty with any of the above | 26.60 | 124,259 | 37.71 | 208,163 | 23.88 | 2,251 |
Multivariable Analysis
Across all four models, transgender people had higher odds of disability relative to cisgender men, even after relevant controls were included (exhibit 3). The same pattern held for cisgender women compared with cisgender men, replicating prior findings.3 Notably, the strength of the association between gender identity and disability diminished slightly with the introduction of controls. This suggests that observable differences such as education, income, and health behaviors mediate the association between gender identity and disability. In all of the models, the gender coefficients remained significantly higher relative to those of cisgender men. This shows that no one set of factors independently mediates gendered disparities in disability; rather, all categories of factors combine to shape patterns of disadvantage.
Odds ratios
|
||||
Characteristics | Model 1 | Model 2 | Model 3 | Model 4 |
Gender identity (ref, cisgender men) | ||||
Cisgender women | 1.35*** | 1.25*** | 1.08*** | 1.11*** |
Transgender | 2.28*** | 1.94*** | 1.49*** | 1.55*** |
Demographic controls | ||||
Age | 1.03*** | 1.02*** | 1.02*** | |
Partnered | 0.49*** | 0.77*** | 0.76*** | |
Racial minoritya | 1.22*** | 0.93*** | 0.95*** | |
Sexual orientation (ref, heterosexual) | ||||
Gay or lesbian | 1.42*** | 1.63*** | 1.56*** | |
Bisexual | 2.69*** | 2.43*** | 2.34*** | |
Socioeconomic controls | ||||
Insured | 1.16*** | 1.19*** | ||
Employed | 0.39*** | 0.37*** | ||
Annual household income (ref, <$25,000) | ||||
$25,000–$49,999 | 0.59*** | 0.62*** | ||
$50,000–$74,999 | 0.45*** | 0.48*** | ||
$75,000+ | 0.33*** | 0.36*** | ||
Education (ref, high school or less) | ||||
Some college | 0.85*** | 0.88*** | ||
College or more | 0.53*** | 0.60*** | ||
Health behaviors | ||||
Current smoker | 2.00*** | |||
Heavy drinker | 1.01 | |||
Obese | 1.86*** |
Although models demonstrate disparity compared with cisgender men, transgender people may also differ from cisgender women. Exhibit 4 shows the probability of reporting any disability, adjusted for demographic, socioeconomic, and behavioral factors, as in model 4. Age at interview is plotted in five-year increments to examine how disparities shift depending on age group.
Exhibit 4 shows that transgender people enter young adulthood with a statistically significant disadvantage in disability relative to both cisgender men and cisgender women. They are nearly twice as likely to report a disability as cisgender men at every age group. They are also more likely to have a disability than cisgender women. This higher probability of disability among transgender adults holds across each age group. Relative to cisgender men and women, transgender people display a higher burden of disability at younger chronological ages.
Discussion
This study used data from the BRFSS to identify an outsize burden of disability among transgender adults. Repeated experiences of discrimination, victimization, and violence bring chronic stress to transgender populations.21,22 Scholars link the experience of minority stress and transgender stigma to the accumulation of negative health outcomes.19,21 Public policy and empirical research must continue to address the causes and consequences of transgender people’s disadvantaged social position relative to cisgender women and cisgender men. For instance, the significance of socioeconomic measures in predicting disability highlights the health gains for transgender people that would accompany improvement in their socioeconomic standing. At a minimum, socioeconomic improvement may improve years spent without functional limitations for transgender people at the population level.
Overall, results suggest a constellation of disadvantage that requires multifaceted policy interventions. That transgender adults entered young adulthood with higher odds of disability highlights the need for a life-course perspective on disability disparities. Although the age-based findings in this study may reflect cohort differences rather than changing disability risk over time, enduring disparity highlights the need to consider all ages when researching disability. Because the BRFSS is a cross-sectional survey, respondents represent a cross-section of various birth cohorts. These cohorts have lived through distinct periods of history, particularly from the perspective of transgender representation and acceptance, but also in changing understandings of work, family, and health behaviors such as smoking.
To continue identifying minority groups with disproportionate needs, gender identity must be included in core modules of national survey instruments and standardized across states. In particular, longitudinal studies that contain information on transgender identity are lacking at both the state and national levels. Efforts to standardize measurement could follow the recent report from the National Academies of Sciences, Engineering, and Medicine37 or could commission a national investigation of best practices around survey methodology for identifying sexual and gender minority groups.
Finally, gender minorities need policies at the federal level that extend nondiscrimination protections to gender identity as a protected class, without religious refusal exemptions. The 2021 state legislative session saw 147 bills filed regulating transgender-related issues—the highest number since the Human Rights Campaign began tracking this legislation in 2004. Further, forty-four bills were filed to allow providers to refuse to provide certain services, including medical care, if they assert a religious justification. The Human Rights Campaign anticipates the 2022 legislative session to exceed the 2021 record in both trans-specific laws and religious exemption clauses.38 If transgender adults have higher rates of disability across the life course, they will likely have an increased need for health care services. Research has established that transgender adults face high rates of provider discrimination and care avoidance.27,39–41 Findings of excess disability burden raise concerns about available care opportunities for transgender people with functional limitations. If policies for gender minority care remain subject to religious freedom exemptions, transgender people may face steep barriers to access despite disproportionate need.
Conclusion
Although the findings of this study begin to shed light on gendered disability disparities, they fail to capture the full picture.
Although the findings of this study begin to shed light on gendered disability disparities, they fail to capture the full picture. By using gender as a primary category, this analysis likely obscures other important trends, such as race and ethnicity.42 Overall, this study demonstrates the impact of considering the intersections of disability with other axes of disadvantage, such as gender identity and age, across the life course. As the US population ages and their functional limitations increase, paying attention to gender minority cohorts who experience discrimination will be crucial for developing targeted health policy interventions.
ACKNOWLEDGMENTS
The author thanks Bridget Gorman for feedback on the study design. This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt, and build upon this work, for commercial use, provided the original work is properly cited. See http://creativecommons.org/licenses/by/4.0/.
NOTES
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