The field of transgender studies has grown exponentially in sociology over the last decade. In this review, we track the development of this field through a critical overview of the sociological scholarship from the last 50 years. We identify two major paradigms that have characterized this research: a focus on gender deviance (1960s–1990s) and a focus on gender difference (1990s–present). We then examine three major areas of study that represent the current state of the field: research that explores the diversity of transgender people's identities and social locations, research that examines transgender people's experiences within institutional and organizational contexts, and research that presents quantitative approaches to transgender people's identities and experiences. We conclude with an agenda for future areas of inquiry.

Looking beyond binary measurements of “male” or “female” can illuminate health inequality patterns that correspond to gender identity rather than biological sex. This study examines disparities in overall health among transgender men, transgender women, gender-nonconforming adults, and cisgender (nontransgender) men and women in the U.S. population. Behavioral Risk Factor Surveillance System (BRFSS) data from 32 U.S. states and territories between 2014 and 2016 yield an analytic sample that identifies 2,229 transgender and gender-nonconforming adults and 516,753 cisgender adults. Estimates from logistic regression models, using cisgender men as a reference group, show that gender-nonconforming respondents have significantly higher odds of reporting poor self-rated health than any other gender identity group. Transgender men also display higher odds of reporting poor health in some models, corresponding to their relative socioeconomic disadvantage. I find no apparent health disadvantage among transgender women and a persistent, if slight, disadvantage among cisgender women. Gender-nonconforming respondents’ predicted probabilities of reporting poor health remain nearly twice as high as those of cisgender men after adjustments for demographic, socioeconomic, and behavioral factors. Their persistent patterns of health-related disadvantage underscore the need for higher-quality data on gender-nonconforming respondents that account for sex assigned at birth.

This study examines the link between self-rated health and two aspects of gender: an individual’s gender identity, and whether strangers classify that person’s voice as male or female. In a phone-based general health survey, interviewers classified the sex of transgender women ( n = 722) and transgender men ( n = 446) based on assumptions they made after hearing respondents’ voices. The flawed design of the original survey produced inconsistent sex classification among transgender men and transgender women respondents; this study repurposes these discrepancies to look more closely at the implications of voice-based gender classification for the health of transgender men and women. Average marginal effects from logistic regression models show transgender men who are classified as women based on their voices are more likely to report poor self-rated health compared to transgender men who are classified as men. Conversely, transgender women who are classified as men are less likely to report poor self-rated health than are transgender women who are classified as women. Additionally, Black transgender men are more likely than any other group to be classified inconsistently with their gender identity, suggesting a link between race/ethnicity and gender perception.

In 2018, the General Social Survey (GSS) asked some respondents for their sex assigned at birth and current gender identity, in addition to the ongoing practice of having survey interviewers code respondent sex. Between 0.44% and 0.93% of the respondents who were surveyed identified as transgender, identified with a gender that does not conventionally correspond to the sex they were assigned at birth, or identified the sex they were assigned at birth inconsistently with the interviewer's assessment of respondent sex. These results corroborate previous estimates of the transgender population size in the United States. Furthermore, the implementation of these new questions mirrors the successful inclusion of other small populations represented in the GSS, such as lesbian, gay, and bisexual people, as well as Muslims, Buddhists, and Hindus. Data on transgender and gender-nonconforming populations can be pooled together over time to assess these populations' attitudes, beliefs, behaviors, and social inequality patterns. We identified inconsistencies between interviewer-coded sex, self-reported sex, and gender identity. As with the coding of race in the GSS, interviewer-coded assessments can mismatch respondents' self-reported identification. Our findings underscore the importance of continuing to ask respondents to self-report gender identity separately from sex assigned at birth in the GSS and other surveys.

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