## Abstract

Sexual and gender minority (SGM) populations experience disadvantages in physical health, mental health, and socioeconomic status relative to cisgender heterosexual populations. However, extant population research has tended to use objective measures and ignore subjective measures, examined well-being outcomes in isolation, and lacked information on less well studied but possibly more disadvantaged SGM subgroups. In this study, we use Gallup's National Health and Well-Being Index, which permits identification of gay/lesbian, bisexual, queer, same-gender-loving, those who identify as more than one sexual identity, transgender men, transgender women, and nonbinary/genderqueer populations. We estimate bivariate associations and ordinary least-squares regression models to examine differences along five dimensions of well-being: life purpose, residential community belonging, physical and mental health, financial well-being, and social connectedness. The results reveal that most SGM groups experience stark disadvantages relative to heterosexuals and cisgender men, which are most pronounced among bisexual, queer, and nonbinary/genderqueer populations. Intergroup and intragroup variations illuminate even greater disparities in well-being than prior research has uncovered, bringing us closer to a holistic profile of SGM well-being at the population level.

## Introduction

Sexual and gender minority (SGM) populations, including people who identify as gay, lesbian, bisexual, queer, transgender, and gender nonbinary, are a growing demographic in the United States (Jones 2021). Research has demonstrated that relative to heterosexual and cisgender populations, SGM populations face disadvantages in a range of health outcomes (National Academies of Sciences, Engineering, and Medicine 2020), including higher rates of poor physical health, poor mental health, and risky health behaviors (Boehmer et al. 2012; Fredriksen-Goldsen et al. 2017; Gonzales et al. 2016; Liu and Reczek 2021; Meyer 2003; Reisner et al. 2015; Rimes et al. 2019; Ueno 2010). Those health disadvantages are theorized to be the result of structural and interpersonal anti-SGM stigma and discrimination described by the minority stress theory model (Brooks 1981; Meyer 1995).

Following that critically important research, three knowledge gaps prevent a more holistic understanding of SGM well-being. First, research has generally prioritized single, objective physical and mental health outcomes, preventing a more inclusive view of a general well-being profile of SGM populations. The singular use of more objective measures (e.g., functional limitations, smoking behavior, cardiovascular disease) may underestimate SGM populations' level of disadvantage. In contrast, leveraging both objective and subjective measures of well-being (e.g., having enough energy to do daily what one wants to do, satisfaction with standard of living relative to others) may provide better insight into SGM people's everyday experiences and illuminate how disadvantage accumulates. Second, we know relatively less about residential community belonging, social connectedness, and financial well-being among SGM groups than about their health. Third, because of data limitations, research examining health and other disparities has primarily compared gay, lesbian, same-sex partnered, and (less often) bisexual people with heterosexual people. Few population-level sources of data include other SGM people, particularly gender minorities (e.g., people who identify as transgender or gender nonbinary), and few previous studies compare SGM groups with one another. Such limitations have precluded a fuller view of well-being among those who might be most disadvantaged.

To address these limitations, we explore the associations of sexual and gender identities with five well-being indices: life purpose, residential community belonging, physical and mental health, financial well-being, and social connectedness. Advancing past work, we examine differences between SGM groups and cisgender and heterosexual people and differences within the SGM population. Given the fundamental association of socioeconomic status (SES), union status, and parental status with both SGM status and well-being (Spiker et at. 2021), we also consider how these characteristics explain differences in well-being. Our data come from Gallup's National Health and Well-Being Index, a nationally representative repeated cross-sectional study with a diverse sample of sexual and gender minorities. We use these data to shed new light on how sexual and gender identities are associated with well-being, showing more pronounced disparities than previous research has found.

## Background

### SGM Populations and Health, Financial, and Social Disparities

The dominant paradigm used to explain SGM health disparities is minority stress theory (Brooks 1981). Minority stress is unique, chronic, and socially based, materializing from the totality of experience in the dominant culture (Meyer 1995). SGM individuals are subject to cisnormative (i.e., presumption of being cisgender) and heteronormative (i.e., presumption of heterosexuality) environments that normalize and legitimize heterosexuality and congruence between sex assigned at birth and gender identity (i.e., cisgender identity) (Martin 2009; Sumerau et al. 2016). Dominant culture subjects SGM people to two types of stressors: (1) distal stressors experienced through direct discrimination, stigma, and violence (Herek and Berrill 1992; Meyer 2015) and (2) proximal stressors experienced through the expectations of discrimination, stigma, and violence (Ross 1985), which often result in the concealing of one's identity and internalized queerphobia1 (DiPlacido 1998). Over time, minority stressors accumulate, ultimately leading to physical and mental health disparities (Liu and Reczek 2021; Meyer 2003; Meyer et al. 2021).

Minority stress theory further emphasizes that minority stressors are unevenly distributed across the SGM population. For instance, bisexual erasure, in which both heterosexuals and other sexual minorities invalidate bisexuality (Yoshino 1999), presents unique stressors that likely differentially expose bisexual people to heightened stress, likely creating unique disadvantages in well-being. Additionally, transgender and gender nonbinary people may face unique stressors that shape health distinctly from that of cisgender sexual minorities (Lagos 2019).

#### SGM Health Disparities and a Composite Measure of Health

Compared with heterosexual people, gay, lesbian, and bisexual people experience more chronic conditions (Fredriksen-Goldsen et al. 2017); worse health behavior, such as drinking, smoking, and drug use (Amroussia et al. 2020; Boehmer et al. 2012; McCabe et al. 2018; Wheldon et al. 2019); and worse mental health outcomes (Gonzales et al. 2016; Meyer 2003; Ueno 2010). Additionally, because of economic discrimination in society and bias in the medical community, SGM people are more likely to skip medications and avoid seeking health care than cisgender and heterosexual people (Dahlhamer et al. 2016). As a result of varying minority stressors, bisexual individuals have a significantly higher risk of substance use, suicidality, and lower self-rated health and are less likely to use primary and preventive health care compared with their same-gender sexual minority and heterosexual counterparts (Boehmer et al. 2012; Dahlhamer et al. 2016; Hsieh and Liu 2019).

Gender minorities—people who identify as transgender, gender nonbinary, genderqueer, agender, or other noncisgender categories—experience stark disadvantages compared with cisgender people because of societal, institutional, and interpersonal stigma and discrimination, which present stressors that can undermine health and well-being. Gender minorities report higher rates of substance use and suicide ideation than cisgender men and cisgender women (Reisner et al. 2015; Rimes et al. 2019). Moreover, transgender people report elevated levels of skipping medication and health care visits, lower rates of health insurance coverage, and less primary care and general health care access compared with the cisgender population (Dahlhamer et al. 2016; Gonzales and Henning-Smith 2017; Shuster 2021). They also experience higher rates of psychological distress and mental disorders than cisgender people (Timmins et al. 2017). Lastly, recent research has found important within-group differences in the experiences of stressors and health outcomes among gender minorities. For instance, gender-nonconforming individuals experience worse self-rated health than transgender women, cisgender men, and cisgender women (Lagos 2018).

Taken together, this body of research suggests that SGM populations experience a wide range of physical and mental health detriments at least partly due to minority stressors. Examining isolated measures, however, can obscure a more holistic picture of well-being. For example, heightened psychological distress and greater functional limitations relative to cisgender and heterosexual populations (Hsieh and Liu 2019; Meyer et al. 2021) might be fully or partly compensated for by more health-promoting behaviors (e.g., exercising, eating healthily), the absence of other conditions (e.g., diabetes, cardiovascular disease, cancer), or other dimensions of health (e.g., body mass index). Thus, analyzing differences in components of a physical and mental health index—including functional limitations, psychological health, health behaviors, and the presence of conditions such as hypertension, diabetes, and cancer—among a nationally representative sample provides a comprehensive understanding of health beyond that provided by examining isolated outcomes.

#### SGM Socioeconomic Disparities and a Composite Measure of Financial Well-being

SGM groups experience socioeconomic disadvantages resulting from heterosexism and cisnormativity. Resume audit studies have found employment discrimination against gay men (Tilcsik 2011) and queer women (Mishel 2016). Further, several studies have shown that gay men tend to earn less than heterosexual men, whereas lesbian women earn approximately the same or more than heterosexual women (Badgett 1995; Baumle and Poston 2011; Black et al. 2003; Denier and Waite 2019). However, bisexual men and women tend to experience the greatest wage penalties relative to heterosexuals and gay/lesbian individuals, and these penalties are partly driven by discrimination in the workplace (Mize 2016). Indeed, sexual minorities are more than four times as likely as heterosexuals to report being fired from a job (Mays and Cochran 2001), whereas transgender individuals report heightened workplace discrimination relative to cisgender people (Granberg et al. 2020; James et al. 2016). SGM individuals also experience a higher risk of poverty (Badgett et al. 2019; James et al. 2016). Disparities in education also exist: gay and lesbian individuals have higher average educational attainment than heterosexuals, but bisexual women (Black et al. 2000; Mollborn and Everett 2015) and transgender adults (Carpenter et al. 2020) experience disadvantages in high school and college completion relative to their cisgender and heterosexual counterparts.

Minority stressors may shape financial well-being given that SGM people tend to experience disadvantages attributable to discrimination and institutional exclusion—for example, in job attainment, unemployment rates, and wage penalties. However, less is known about how SGM individuals experience and rate their subjective financial well-being. SGM populations might be disadvantaged relative to cisgender and heterosexual populations subjectively in terms of having insufficient economic resources to do what one wants to do daily, frequent worries about money, and lower levels of satisfaction with standard of living (Chai and Maroto 2020). An index of these measures and the use of a nationally representative sample can illuminate subjective stratification and deeper financial disparities than can single objective measures.

#### SGM Social Disparities and Composite Measures of Social Well-being

Although research on other aspects of SGM well-being (e.g., life purpose, residential community belonging, and social connectedness) is sparse, some evidence links SGM status to neighborhoods and social networks. For instance, sexual minorities tend to think of their neighborhoods as less trustworthy and less helpful than do heterosexuals (Henning-Smith and Gonzales 2018; King 2016), save for those who live in “gayborhoods”—neighborhoods containing at least a sizable minority of LGBTQ residents (Ghaziani 2015). Similarly, sexual minorities tend to experience more loneliness in later life than heterosexuals (Hsieh and Liu 2021), which is attributable largely to lower partnership rates and, to a lesser extent, friendship strain and a lack of familial support. Compared with heterosexual individuals, sexual minorities enjoy larger networks but fewer family-of-origin ties (Fischer 2022). However, research is relatively scant and overwhelmingly focuses on gay and lesbian people, ignoring queer and bisexual people as well as gender minorities. Minority stressors from queerphobia in one's neighborhood or family-of-origin tension or estrangement could lead to social disparities (Reczek and Bosley-Smith 2022).

Similar to the potential of health and financial well-being indices, examining life purpose, residential community belonging, and social connectedness indices at the population level offers benefits. Such aspects of well-being, which have been relatively overlooked in research on SGM people, are important for holistically understanding SGM well-being. In addition, these measures can illuminate how individuals take stock of the broader state of their lives. The life purpose index measures whether people feel they are reaching their goals and enjoying what they do each day (Zilioli et al. 2015). The residential community belonging index assesses whether people feel as if where they live is great for them, they feel safe and secure, and they derive pride from where they live (Ross 2002). Finally, the social connectedness index provides knowledge beyond that offered by examining loneliness or networks (Fischer 2022; Hsieh and Liu 2021), including the presence of supportive and loving relationships and positive energy from a support network.

### A Broader Understanding of Well-being for SGM Populations

As past research and minority stress theory suggest, SGM populations experience acute physical and mental health disadvantages relative to cisgender and heterosexual populations. Relatively less work has examined other aspects of well-being. Yet, most analyses have examined outcomes in isolation, sacrificing breadth for depth, and few have leveraged the strength of subjective measures. Consequently, examining both objective and subjective measures of well-being should be a priority for social demographers interested in SGM well-being.

The strength of well-being profiles lies in their ability to capture perceptions of well-being more holistically. Asking people to assess various aspects of their lives—from health to community to finances—is important for understanding well-being. When people examine their lives, they are unlikely to focus on single outcomes in isolation from other dimensions of their lives. They are likely to think about the state of their health holistically, considering such factors as their health behaviors, how they feel, their functional limitations, and their medical conditions. Indeed, this sort of broader assessment of health is one reason why self-rated health is an important and independent predictor of mortality, morbidity, and disability (Idler and Benyamini 1997; Jylhä 2009). When it comes to finances, we contend that people are unlikely to examine their educational attainment with reference to averages or perhaps even relative to others. Instead, they are thinking about their ability to secure food for themselves or their families (Gundersen and Ziliak 2015), whether they can do what they want to do with the money they have (Ringen 1991), and whether they worry about making ends meet (Cooper 2014). We posit that the five indices of well-being provide a window into a collective understanding of well-being.

In this study, we take a broader view of well-being by relying on Gallup's National Health and Well-Being Index to measure life purpose, residential community belonging, physical and mental health, financial well-being, and social connectedness. Gallup's indices operationalize each dimension of well-being, allowing us to examine composite well-being differences. We thus provide a more holistic demographic profile of SGM well-being at the population level than previous research. Our well-being analysis is one of the first to harness Gallup's unparalleled SGM sample. We include sexual minorities who identify as queer, same-gender loving, or more than one sexual identity, in addition to gay, lesbian, and bisexual; we also include transgender men, transgender women, and gender nonbinary/genderqueer individuals (Schilt and Lagos 2017). Our study improves on past work that relied on limited sexual identity categories (e.g., lesbian, gay), inferred sexual identity from partnership status, or used binary measures of sex and gender, which conflate sex and gender and preclude identification of transgender and other gender minority populations (Westbrook et al. forthcoming; Westbrook and Saperstein 2015). Importantly, we advance research by comparing SGM people with cisgender and heterosexual people and examining differences within SGM populations to understand who is most vulnerable to well-being detriments.

## Data and Methods

### Data

We use data from Gallup's National Health and Well-Being Index, proprietary data from Gallup's U.S. daily tracking microdata files. The survey, which began in 2008, uses a repeated cross-section design. It samples approximately 1,000 respondents each day on a wide array of topics, including politics, health and well-being, and sociodemographic characteristics. We limit our analysis to data from 2018 and 2019 because these data are the most recent and offer a sufficient level of detail on our predictors and outcomes of interest.

Starting in January 2018, Gallup collected data from U.S. adults aged 18 or older using a dual mail- and web-based methodology. Gallup sampled individuals via an address-based sampling frame, which included a representative list of all U.S. households in all 50 states and the District of Columbia. Sample members were provided a mail survey and a link with a unique access code to complete the survey online if they were interested. Respondents within households were chosen by which member has the next birthday. Gallup sent surveys once per month at the start of the month and closed data collection for that month on the fifth day of the following calendar month, after which survey responses were not accepted. In 2018, the response rate was 17.3%. Most data were collected in 2018, but a small portion of data comes from 2019, owing to a deteriorating funding situation at Gallup that limited data collection after 2018.

#### Outcome Variables

Our dependent variables are five indices of health and well-being: (1) life purpose, (2) residential community belonging, (3) physical and mental health, (4) financial well-being, and (5) social connectedness. The survey items and response categories are described in Table 1. The life purpose index includes five measures of feelings of meaningfulness and inspiration. The residential community belonging index is composed of four measures and captures respondents' feelings of safety, pride, and belonging in their communities. The physical and mental health index, composed of 16 items, includes measures of physical and mental health and their influence on daily life. The financial well-being index includes four items that tap into subjective measures of SES. Finally, the social connectedness index includes four measures that capture the strength of close relationships with family and significant others. These five Gallup-created well-being indices include both objective and subjective measures to profile a broad view of well-being. Each index has a range of 0–100, with higher values indicating better well-being.

Each well-being index comprehensively and reliably captures global aspects of well-being. The indices show valid and reliable psychometric measurement, high correlation with previously validated well-being measures, and predictive power regarding important outcomes, such as productivity and health care use (see Sears et al. 2014). Gallup developed the indices by taking the following steps: (1) reducing the number of items necessary from widely accepted health and well-being items to achieve measurement goals; (2) conducting exploratory factor analysis to identify the underlying latent data structure and provide insight into scoring; (3) scoring the items by assigning them to one of the five latent factors (purpose, community, physical, financial, and social well-being) and conducting confirmatory factor analysis to examine the structural validity of the model; and (4) validating scores using accepted criteria, such as goodness-of-fit index, comparative fit index, root-mean-square error of approximation, and standardized root-mean-square residual values. The five well-being indices show impressive fit to the data, high or acceptable reliability, very high convergent validity between indices and other measures, and impressive Cronbach's alpha scores, suggesting high consistency among items in each index (see Sears et al. 2014).

#### Independent Variables

Scholars have long suggested incorporating a sufficient range of sexual identity and gender response categories to better facilitate the identification of SGM populations (Lagos and Compton 2021; Westbrook et al. forthcoming; Westbrook and Saperstein 2015). In this article, we leverage recent advancements in measurement and data collection to include more diverse SGM populations. Our independent variables are sexual identity and gender identity.

First, we include queer-identified people (a growing subset of the SGM community), same-gender-loving individuals,2 and those who indicate more than one sexual identity, alongside lesbian, gay, and bisexual people. Respondents were asked, “Which of the following do you consider yourself to be? You may select one or more.” Response categories included (1) straight or heterosexual, (2) lesbian, (3) gay, (4) bisexual, (5) queer, and (6) same-gender loving. We collapse lesbian and gay into one category because of the gendered nature of the terms.3 A sizable portion of sexual minorities self-identified as belonging to more than one sexual identity category; we create an additional response category to capture these individuals.4

Second, we construct our gender identity indicator from a three-part gender question that circumvents problems with binary sex/gender measures and allows for the identification of transgender and gender-nonconforming respondents. Respondents were first asked about their sex assigned at birth: “On your original birth certificate, was your sex assigned as male or female?” Response options were (1) male or (2) female. Next, they were asked, “Do you currently describe yourself as a man, woman, or transgender?”5 If a participant identified as transgender, a follow-up question appeared: “Are you . . . ?,” with response categories of (1) “Trans Woman (Male-to-female),” (2) “Trans Man (Female-to-male),” and (3) “Non-binary/Genderqueer.” We use this three-part gender question to create a new gender indicator. We code respondents as cisgender men if they were assigned male at birth and currently identify as men; as cisgender women if they were assigned female at birth and currently identify as women; as transgender men if they were assigned female at birth and currently identify as men or if they were assigned female at birth, identify as transgender, and identify as transgender men; as transgender women if they were assigned male at birth and identify as women or if they were assigned male at birth, identify as transgender, and identify as transgender women; and as nonbinary/genderqueer if they currently identify as transgender and then, in the follow-up question, identify as nonbinary/genderqueer regardless of the sex they reported being assigned at birth. On the basis of the wording and branching of this gender indicator, only those nonbinary/genderqueer individuals who also identified as transgender are identifiable in these data. Although some nonbinary people consider themselves transgender, others do not (see Darwin 2020; Garrison 2018), and thus our sample of nonbinary/genderqueer people includes only those who also identify as transgender. We return to the implications of this methodological limitation in the Discussion section.

#### Covariates

We adjust for several sociodemographic characteristics in our models that might confound the association between SGM identity and well-being. Sociodemographic variables include age (in years), race/ethnicity (White, Other,6 Black, Asian, or Hispanic), region (South, Northeast, Midwest, or West), and survey year (2018 or 2019). We also include objective measures of SES, including current employment status (yes or no), education (less than high school, high school diploma or GED, technical/vocational/some college, college degree, or advanced degree), and income ($11,999 or less,$12,000 to $35,999,$36,000 to $59,999,$60,000 to $89,999,$90,000 to $119,999, or$120,000 or more). Finally, we control for union status (single/never married, married, cohabiting/domestic partnership, or divorced/widowed/separated) and residential parent status (i.e., whether any children are present in the household; no or yes).

We adjust for sociodemographic variables to account for the possibility that some existing sociodemographic differences between SGM groups might influence our primary associations. We then adjust for SES characteristics, union status, and residential parent status in separate models because these characteristics have been shown to be influenced by sexual and gender identities (e.g., Mishel 2016; Mize 2016) and are predictive of physical and mental health (e.g., Clouston and Link 2021). Additionally, because many of the measures used in the indices are subjective and any observed subjective differences might be the result of objective differences among and between SGM groups, we adjust for more objective indicators of SES and family characteristics. In doing so, we can demonstrate which results remain significant after we adjust for SES, union status, and residential parent status.

### Analytic Plan

From an eligible 123,200 individuals, we limit the analytic sample to 107,310 after excluding 15,890 individuals who had no reported well-being index values across one or more of the outcomes or did not report their sexual identity or sex or gender identity. To avoid the additional loss of data, we employ multiple imputation using chained equations (imputations = 20) to impute missing values on our covariates: race/ethnicity (n = 969), age (n = 626), employment status (n = 493), income (n = 4,628), education (n = 211), union status (n = 162), and residential parent status (n = 1,160). We do not impute missing information on our main independent variables because it is reasonable to expect that those who refused to report their sexual or gender identity are qualitatively different than those who did, which might have implications for respondents' well-being.7 Multiply imputed results are nearly identical to results using listwise deletion, highlighting the robustness of our results. To account for the sampling design, adjust for nonresponse, and achieve population representation, we weight the analyses using Gallup's sample weights. We use the 2018 sample weights for the 94% of the sample surveyed in 2018 and the 2019 sample weights for the remaining 6% surveyed the following year.

We first discuss descriptive statistics of our analytic sample before multiple imputation. We then present weighted bivariate analyses of the associations between sexual and gender identities and the five well-being indices using Bonferroni-adjusted significance tests. Finally, we estimate ordinary least-squares (OLS) regression models to predict each well-being index as a function of sexual identity and gender identity. In the first set of models, we include basic sociodemographic characteristics: age, race/ethnicity, region, and survey year. In the second set of models, we add objective SES (employment status, education, and income) characteristics, union status, and residential parent status variables to examine whether these measures explain any of the associations between SGM identities and our measures of well-being. We conduct all analyses using Stata, version 15.

## Results

### Descriptive Results

Table 2 shows the unweighted and weighted descriptive statistics for our sample before multiple imputation. The weighted means are 59.3 for life purpose, 61.8 for residential community belonging, 61.0 for physical and mental health, 61.0 for financial well-being, and 50.7 for social connectedness. Approximately 2.3% of the sample are gay or lesbian, 2.2% are bisexual, 0.3% are queer, 0.9% are same-gender loving, and 1.3% have more than one sexual identity. In total, sexual minorities represent more than 7% of the sample. Lastly, 0.17% of the sample are transgender men, 0.12% are transgender women, and 0.16% are nonbinary/genderqueer.

### Bivariate Results

Table 3 shows weighted bivariate analyses of well-being by sexuality and gender identity. The results suggest that gay and lesbian individuals experience disadvantages relative to heterosexuals across every measure of well-being except for physical and mental health, with the largest disparities in financial well-being and social connectedness. Bisexual and queer people are the most disadvantaged across each well-being index relative to heterosexuals and gay/lesbian individuals. For instance, bisexual individuals have an average financial well-being score of 45.4—16.5 units lower than that of heterosexuals (p < .001). Queer people have an average physical well-being score of 52.3, which is nearly 9.0 units lower than that of heterosexuals (p < .001). Same-gender-loving individuals, who represent an often-overlooked but important sexual minority group, face only physical and mental health and financial well-being disadvantages relative to heterosexual people. In fact, same-gender-loving people experience advantages relative to heterosexuals and other sexual minorities on most well-being indices. Finally, those who indicated more than one sexual identity experience a disadvantage on each index relative to heterosexuals.

Table 3 also shows bivariate results for well-being indices across gender identity categories. Transgender men are disadvantaged in residential community belonging, physical and mental health, and financial well-being relative to cisgender men and are disadvantaged in social connectedness relative to cisgender women. Transgender men score, on average, 9.9 points lower on residential community belonging than cisgender men (p < .001) and 9.5 points lower than cisgender women (p < .05); discrepancies for financial well-being are even greater. Transgender women and nonbinary/genderqueer individuals experience disadvantages on all indices relative to cisgender men, providing initial evidence that these two gender minority groups might experience the worst well-being. Bivariate results show stark disparities in financial well-being for transgender women and nonbinary/genderqueer populations relative to cisgender populations. On the financial well-being index, transgender women average 48.7, and nonbinary/genderqueer individuals average approximately 44.0, which are 14.7 (p < .001) and 19.4 (p < .001) units lower, respectively, than the average for cisgender men.

### Regression Results

Model 1 in Table 4 shows the OLS regression results for each of the five well-being indices on sexual and gender identity with controls for basic demographic covariates (age, race/ethnicity, region, and survey year). Sexual minorities experience many disadvantages relative to heterosexual individuals. Gay and lesbian people report significantly worse well-being than heterosexual people on each index except residential community belonging, where a bivariate difference is explained by sociodemographic characteristics. Bisexual individuals fare worse than heterosexuals and gay/lesbian populations on all well-being indices, especially financial well-being. Queer people also experience disadvantages relative to heterosexuals except in life purpose, where a bivariate disparity is explained by added controls. Controlling for basic sociodemographic factors accounts for the same-gender-loving group's disadvantage in physical and mental health relative to heterosexual individuals. Model 1 further shows that same-gender-loving individuals are disadvantaged relative to heterosexuals only in financial well-being. Finally, disadvantages persist across all indices for those indicating more than one sexual identity relative to heterosexuals.

The basic sociodemographic controls introduced in Model 1 explain transgender men's bivariate disadvantages relative to cisgender men. In contrast, transgender women fare worse than cisgender men on financial well-being and worse than cisgender women on social connectedness. After basic sociodemographic controls are added, transgender women no longer experience lower life purpose, residential community belonging, and physical and mental health scores relative to the cisgender population. Nonbinary/genderqueer people remain disadvantaged relative to cisgender men across each well-being index except financial well-being, with the worst disadvantage occurring on the social connectedness index. In fact, nonbinary/genderqueer populations score lower on the social connectedness index than transgender men, another gender minority group.

In Model 2 of Table 4, we add employment status, income, education, union status, and residential parent status as additional covariates. Most associations remain negative across sexual identity categories, suggesting that socioeconomic, union, and residential parent statuses do not explain most of the well-being disparities. Gay and lesbian individuals score lower on physical and mental health and financial well-being relative to heterosexuals when we control for all covariates. Bisexual individuals fare worse on each outcome relative to heterosexuals and score lower than gay/lesbian and same-gender-loving individuals on life purpose, residential community belonging, and physical and mental health. Disadvantages for queer people compared with heterosexuals persist for residential community belonging, physical and mental health, financial well-being, and social connectedness indices in Model 2. Conversely, same-gender-loving people score higher than heterosexuals on several well-being measures after we account for SES, union status, and residential parent status. This finding implies that SES and family status differences suppress differences between same-gender-loving and heterosexual respondents. Finally, those who indicated more than one sexual identity experience disadvantages in life purpose, physical and mental health, and financial well-being relative to heterosexuals net of additional covariates. Figure 1 shows the predicted values of the well-being indices across categories of the sexual identity variable, with covariates held at their means.

Turning to Model 2 showing results across gender identity categories, we see that nonbinary/genderqueer people score lower on residential community belonging, physical and mental health, and social connectedness relative to cisgender men and cisgender women, and have lower life purpose scores than cisgender women. They appear to fare the worst on social connectedness, where a detriment of more than 10 units separates them from cisgender men (p < .01). Importantly, this group also averages lower well-being scores than other gender minorities across some outcomes. For example, nonbinary/genderqueer people have lower social connectedness scores than transgender men and transgender women, underscoring acute disadvantage. Figure 2 shows the predicted values of the well-being indices across categories of the gender identity variable, with covariates held at their means.

There are other cases in which Model 2's inclusion of SES, union status, and residential parent status controls fully explains associations between sexuality or gender identity and our well-being outcomes. Additional controls account for the disadvantages that gay and lesbian individuals experience in life purpose and social connectedness and that same-gender-loving individuals experience in financial well-being relative to heterosexuals. After we add these controls, compared with cisgender men, nonbinary/genderqueer people no longer fare worse on life purpose and transgender women no longer experience worse financial well-being. After we add all controls, transgender women score similar to cisgender people on the well-being indices.

## Discussion

A burgeoning body of work has found physical and mental health disadvantages for SGM populations compared with their heterosexual and cisgender counterparts, with additional disadvantages for bisexual individuals compared with their gay and lesbian counterparts (e.g., Hsieh and Shuster 2021; Meyer et al. 2021; National Academies of Sciences, Engineering, and Medicine 2020). Those findings are often explained by the distal and proximal stressors unique to one's minority status, such as discrimination, stigma, and violence (Meyer 2003; Williams and Mann 2017). Although past work contributed immensely to our understanding of SGM health, the literature lacks a holistic account of well-being. In analyzing a population-based SGM sample, we found global well-being disparities associated with sexual and gender identities. Generally, bisexual, queer, and nonbinary/genderqueer individuals experienced the greatest well-being disadvantages relative to their cisgender and heterosexual counterparts as well as many of their SGM counterparts. Remarkably, objective indicators of SES, union status, and residential parent status did not explain most of these associations. This study makes notable strides in increasing our knowledge of SGM well-being in the United States today.

### Sexuality and Well-being

Studies have documented disadvantages for sexual minority individuals on measures of physical health, such as self-rated health (Reczek et al. 2017), functional limitations (Hsieh and Liu 2019), and socioeconomic status (e.g., wages; Mize 2016). Our results support previous research but widen the scope of known SGM well-being disadvantages (Meyer 2003; Williams and Mann 2017). After accounting for covariates, we found that gay and lesbian individuals had well-being detriments relative to heterosexuals only in physical and mental health and financial well-being. Those findings align with research on self-rated health, functional limitations, and psychological distress (Meyer 2003; Williams and Mann 2017), as well as wages (Badgett 1995; Mize 2016) and elevated poverty rates (Badgett et al. 2019). Accounting for SES, union status, and residential parent status explained life purpose and social connectedness disadvantages for gay and lesbian individuals, implying that these characteristics play a part in driving these disparities. In this sense, it is important to continue striving for socioeconomic equality and toward a society that does not confer more status to some family forms than to others (see Mize 2016); such efforts might continue to narrow the well-being gaps that we observed by decreasing exposure to distal and proximal stressors that are inversely related to health and well-being.

We found that bisexual individuals faced disadvantages on each well-being index relative to heterosexuals—and in some cases, relative to gay and lesbian individuals—after we adjusted for all covariates. Minority stressors might explain those findings: heterosexism and heteronormativity in the United States may undermine the well-being of bisexual individuals differently than that of gay and lesbian individuals. The double discrimination bisexual individuals experience from both heterosexual and lesbian/gay communities (i.e., biphobia; Ochs 1996) greatly impacts bisexual individuals' well-being in diverse areas of social life (Mulick and Wright 2002). Further, queer-identified people in our data are in a similar position of disadvantage relative to heterosexuals, save for life purpose. Although those who indicated more than one sexual identity category are likely a heterogeneous group, their disadvantages were quite pronounced and even paralleled those experienced by queer people.

Taken together, living outside of the heterosexual–homosexual binary is associated with worse well-being that might be explained by relatively acute minority stressors, as is the case for those who are bisexual, queer, or have more than one sexual identity. This minority stress might materialize as a result of harsher stereotypes (Herek 2002), more negative attitudes (Yost and Thomas 2012), or heightened erasure and invisibility (Yoshino 1999) applied to bisexual and potentially queer people relative to gay and lesbian populations. Or perhaps the essentialist “born this way” discourse benefitted gay and lesbian populations while largely leaving behind more marginalized sexual minorities (see Mize 2016). People who identify as queer, bisexual, and more than one sexual identity might experience greater stressors, undermining health and well-being differently than among gay and lesbian populations.

Surprisingly, same-gender-loving individuals were relatively advantaged on most dimensions of well-being relative to heterosexuals and many sexual minorities. The term same-gender loving tends to be a “culturally affirming alternative” relative to other terms (Lassiter 2014:179), such as men who have sex with men, which Black sexual minority men describe as dehumanizing (Truong et al. 2016). The use of same-gender loving and identification with it understandably involve some selection effects: Black same-gender-loving men are more likely to think that homophobia is a problem within communities of color compared with gay and bisexual Black men and report higher levels of connectedness to the LGBT community compared with bisexual Black men (Keene et al. 2022). For these reasons, same-gender-loving individuals might exhibit lower levels of internalized racism and queerphobia, leading to relatively better health and well-being (Gale et al. 2020; James 2020; Meyer 2003). For White respondents, who chose this identity category despite its Afrocentric origins, these findings are more difficult to interpret. Diffusion of the term into White sexual minority communities offers one explanation; identification with the action-oriented same-gender loving and a misunderstanding of the broader context of the term's origins offers another. In any case, more evidence is needed to fully understand the advantages we have observed.

One key theme of our findings is that financial well-being constitutes an important axis of disadvantage for nearly all sexual minorities; it is the index that was most prominently stratified by sexual identity. Remarkably, accounting for objective measures of SES—employment status, income, and education—did not fully explain disparities in financial well-being for individuals who identified as gay/lesbian, bisexual, queer, and more than one sexual identity relative to heterosexual individuals, suggesting that other factors help explain subjective financial well-being detriments. Given that the financial well-being index includes measures of food insecurity (Gundersen and Ziliak 2015), relative satisfaction with standard of living (Ringen 1991), and worrying about making ends meet (Cooper 2014), the presence of more heterogeneous class interactions among sexual minorities might lead sexual minorities to create reference categories from higher SES sexual minorities. In that sense, relative deprivation might play a larger role among sexual minorities than heterosexuals (Crosby 1976), explaining why objective SES measures do not account for disadvantages in subjective financial well-being. Future work is needed to fully understand the causes of these disparities, but our results show that the average financial well-being of sexual minorities pales in comparison with that of heterosexuals.

### Gender and Well-being

Our findings suggest that nonbinary/genderqueer populations face the strongest well-being disadvantages compared with cisgender people and, in some cases, compared with other gender minorities. Nonbinary/genderqueer people faced pronounced disparities in residential community belonging, physical and mental health, and social connectedness. Recent population-level research found that gender-nonconforming individuals experience the greatest detriments in self-rated health relative to cisgender and transgender populations (Lagos 2018). Although some nonbinary/genderqueer people might also identify as gender-nonconforming and vice versa, the two populations might differ to no small degree, even as both appear to live outside of the gender binary. In this way, our study is one of the first to examine population-level nonbinary/genderqueer well-being. Our findings align with those of Lagos (2018) and build on past work by illuminating that disparities persist in comprehensive health indices and extend to other dimensions of well-being.

Transgender men and transgender women experience many bivariate disadvantages relative to cisgender men and cisgender women, but sociodemographic characteristics explain many disparities. Those null results after accounting for sociodemographic characteristics of transgender populations may be explained by very small sample sizes, which render only stark differences or differences with low variance detectable. We urge caution in interpreting the results to mean that transgender men and transgender women face negligible disadvantages relative to cisgender people after adjusting for sociodemographic characteristics. Given the magnitude of the bivariate disadvantages, the regression results may reflect an artifact of sample size rather than a genuine finding of no difference.

### Limitations and Conclusions

Several limitations to this study warrant consideration. First, sexuality has three distinct components: sexual identity, sexual attraction, and sexual behavior (see Mishel 2019; Mize 2016; Westbrook et al. forthcoming). Similarly, multiple dimensions (e.g., identity, expression) combine to create gender, and social actors interpret gender in various ways—all of which affect health and well-being (see Hart et al. 2019; Lagos 2019). Our data reflect only sexual and gender identities, precluding us from analyzing other aspects of sexuality and gender that might show different associations with well-being. For instance, those who identify as straight but engage in same-sex behavior might experience their communities and workplaces differently, and their communities and workplaces might react to them differently, affecting their well-being scores. Second, the cross-sectional data do not permit causal claims, and we are unable to address issues of reverse causality. An individual's community or financial well-being, for example, might provide them with the social and economic resources to realize that they are indeed bisexual or transgender, or influence self-reporting of a sexual or gender minority identity. Finally, the sample of nonbinary/genderqueer people includes only those who also identified as transgender. Those who identify as nonbinary/genderqueer and transgender might differ considerably from those who identify as only nonbinary/genderqueer. Considerable ambivalence exists among nonbinary people about identifying as transgender, with some not feeling “trans enough,” citing concerns about not suffering sufficiently or not undergoing hormonal therapy or surgery (Darwin 2020). Well-being disparities for this group, then, might likely exceed those of nonbinary/genderqueer people who do not also identify as transgender.

Future work should consider these limitations and attempt to build on the present study. One important step would be directly examining the associations of both sexual and gender minority stress on well-being. Such research could also highlight stress proliferation at the intersection of sexual and gender minority stress. Additionally, research could test whether well-being indices mediate SGM health disparities (Liu and Reczek 2021; Timmins et al. 2017). All of those endeavors would help extend research on SGM well-being and minority stress theory to examine health and well-being more holistically.

Our study builds on previous work by examining associations between sexual and gender identities and five dimensions of well-being: (1) life purpose, (2) residential community belonging, (3) physical and mental health, (4) financial well-being, and (5) social connectedness. In so doing, we provide a more holistic profile of SGM well-being at the population level, reflecting a wide range of measures that encapsulate people's everyday experiences. Despite decades of demographic research on disadvantages in health and well-being by race/ethnicity, class, and gender, demographers have been slow to incorporate sexuality and nondichotomous measures of gender (Schnabel 2018; Westbrook and Saperstein 2015). A lack of available data that include informative measures of sex, gender, and sexuality often precludes SGM inclusion (Compton 2018). Thus, we echo others in encouraging improved measures to better understand how sex, gender, and sexuality are associated with and pattern inequality (for important suggestions, see Lagos and Compton 2021; Saperstein and Westbrook 2021; Westbrook et al. forthcoming). As evidence of the deficit in understanding created by the dearth of SGM data, our results show marked associations between sexual and gender identities and well-being, even after we adjust for sociodemographic and socioeconomic covariates. Taken together, these results echo and bolster other scholars' suggestions to pay more attention to sexuality and a more complex form of gender (Schnabel 2018), given that both show important associations with well-being. Most importantly, our approach shows more ubiquitous SGM well-being disparities across five important dimensions than previous research using single measures has suggested, highlighting the necessity of more holistic profiles of well-being.

## Acknowledgments

This research was supported by the Institute for Population Research at The Ohio State University and the National Institute of Child Health and Human Development at the National Institutes of Health through center grant P2CHD058484. For thought-provoking questions and insightful comments, we thank Trent Mize and participants of the Sexual and Gender Minority Populations session at the 2021 annual meeting of the Population Association of America, where an early version of this paper was presented. We are also indebted to Jake Hays and Natasha Quadlin, without whom our figures would not be nearly as colorful or illustrative. Finally, we thank the three anonymous reviewers, the deputy editor, and Mark Hayward for feedback that improved our work considerably.

## Notes

1

We use queerphobia as an umbrella term to refer to internalized homophobia, biphobia, and transphobia because it relates to all SGM individuals.

2

“Same-gender loving” was coined by Black activist Cleo Manago in the early 1990s. Viewing mainstream terms for sexual minorities, such as lesbian and gay, through the lens of Whiteness, Manago sought to create a term that was decidedly Afrocentric. Descriptive results show that those who identify as same-gender loving are disproportionately people of color (37.33%), many of whom are Black, even though a sizable portion identify racially as White (62.67%).

3

Theoretically, lesbian and gay individuals’ identity self-reports are predicated on same-sex attraction or behavior, and both lesbian and gay imply something about the gender of the person claiming the identity and the gender of the person to whom one is attracted or with whom one engages in sexual behavior. Methodologically, only 3.6% of gay individuals identified as cisgender women or transgender women, and only 1.7% of lesbian individuals identified as cisgender men or transgender men. Therefore, we collapse these categories to avoid inadvertently modeling interaction associations between sexual identity and gender identity for lesbian and gay populations regarding our outcome variable predictions.

4

Those who identified as exclusively lesbian and gay are categorized as belonging to the collapsed lesbian/gay category.

5

Unlike the sexuality measure, the gender measure does not allow an individual to choose more than one gender. The three-part gender question’s phrasing is an improvement on past binary gender measurements, but it has two limitations: (1) it implies that those who are men or women are not transgender and vice versa (see Westbrook and Saperstein 2015); and (2) it relies on anachronistic terms to describe transgender individuals (e.g., “male-to-female”).

6

Those coded as “Other” in the race/ethnicity variable identified as either “American Indian or Alaska Native” or “Native Hawaiian or Pacific Islander” or identified as more than one racial category. These groups were combined and collapsed into one category owing to small sample sizes.

7

Although it is also reasonable to expect that those who did not specify their race/ethnicity are different from those who did, we impute missing information on race/ethnicity because we are chiefly interested in associations of sexual identity and gender identity on well-being. Moreover, only a small portion (less than 1%) left their race/ethnicity blank, which is unlikely to alter the results substantially—especially compared with sexual identity, for which more than one tenth of the data are missing. Finally, our listwise deleted regression results are nearly identical to our multiply imputed results, suggesting that we can impute data on our missing covariates without sacrificing accuracy.

## References

Amroussia, N., Gustafsson, P. E., & Pearson, J. L. (
2020
).
Do inequalities add up? Intersectional inequalities in smoking by sexual orientation and education among U.S. adults
.
Preventive Medicine Reports
,
17
,
1
7
.
Badgett, M. V. L. (
1995
).
The wage effects of sexual orientation discrimination
.
Industrial and Labor Relations Review
,
48
,
726
739
.
Badgett, M. V. L., Choi, S. K., & Wilson, B. D. H. (
2019
).
LGBT poverty in the United States: A study of differences between sexual orientation and gender identity groups
(Report).
Los Angeles
:
Williams Institute, UCLA School of Law, University of California, Los Angeles
. Retrieved from https://escholarship.org/content/qt37b617z8/qt37b617z8.pdf
Baumle, A. K., & Poston, D. L.Jr. (
2011
).
The economic cost of homosexuality: Multilevel analyses
.
Social Forces
,
89
,
1005
1031
.
Black, D., Gates, G., Sanders, S., & Taylor, L. (
2000
). Demographics of the gay and lesbian population in the United States: Evidence from available systematic data sources.
Demography
,
37
,
139
154
.
Black, D. A., Makar, H. R., Sanders, S. G., & Taylor, L. J. (
2003
).
The earnings effects of sexual orientation
.
Industrial and Labor Relations Review
,
56
,
449
469
.
Boehmer, U., Miao, X., Linkletter, C., & Clark, M. A. (
2012
).
Adult health behaviors over the life course by sexual orientation
.
American Journal of Public Health
,
102
,
292
300
.
Brooks, V. R. (
1981
).
Minority stress and lesbian women
.
Lexington, MA
:
Lexington Books
.
Carpenter, C. S., Eppink, S. T., & Gonzales, G. (
2020
).
Transgender status, gender identity, and socioeconomic outcomes in the United States
.
Industrial and Labor Relations Review
,
73
,
573
599
.
Chai, L., & Maroto, M. (
2020
).
Economic insecurity among gay and bisexual men: Evidence from the 1991–2016 U.S. General Social Survey
.
Sociological Perspectives
,
63
,
50
68
.
Clouston, S. A., & Link, B. G. (
2021
).
A retrospective on fundamental cause theory: State of the literature and goals for the future
.
Annual Review of Sociology
,
47
,
131
156
.
Compton, D. (
2018
).
How many (queer) cases do I need? Thinking through research design
. In Compton, D., Meadow, T., & Schilt, K. (Eds.),
Other, please specify: Queer methods in sociology
(pp.
185
201
).
Oakland
:
University of California Press
.
Cooper, M. (
2014
).
Cut adrift: Families in insecure times
.
Berkeley
:
University of California Press
.
Crosby, F. J. (
1976
).
A model of egoistical relative deprivation
.
Psychological Review
,
83
,
85
113
.
Dahlhamer, J. M., Galinsky, A. M., Joestl, S. S., & Ward, B. W. (
2016
).
Barriers to health care among adults identifying as sexual minorities: A U.S. national study
.
American Journal of Public Health
,
106
,
1116
1122
.
Darwin, H. (
2020
).
Challenging the cisgender/transgender binary: Nonbinary people and the transgender label
.
Gender & Society
,
34
,
357
380
.
Denier, N., & Waite, S. (
2019
).
Sexual orientation at work: Documenting and understanding wage inequality
.
Sociology Compass
,
13
,
e12667
. https://doi.org/10.1111/soc4.12667
DiPlacido, J. (
1998
).
Minority stress among lesbians, gay men, and bisexuals: A consequence of heterosexism, homophobia, and stigmatization
. In Herek, G. M. (Ed.),
Stigma and sexual orientation: Vol. 4. Understanding prejudice against lesbians, gay men, and bisexuals
(pp.
138
159
).
Thousand Oaks, CA
:
Sage Publications
.
Fischer, M. J. (
2022
).
Social exclusion and resilience: Examining social network stratification among people in same-sex and different-sex relationships
.
Social Forces
,
100
,
1284
1306
.
Fredriksen-Goldsen, K. I., Kim, H. J., Shui, C., & Bryan, A. E. (
2017
).
Chronic health conditions and key health indicators among lesbian, gay, and bisexual older U.S. adults, 2013–2014
.
American Journal of Public Health
,
107
,
1332
1338
.
Gale, M. M., Pieterse, A. L., Lee, D. L., Huynh, K., Powell, S., & Kirkinis, K. (
2020
).
A meta-analysis of the relationship between internalized racial oppression and health-related outcomes
.
Counseling Psychologist
,
48
,
498
525
.
Garrison, S. (
2018
).
On the limits of “trans enough”: Authenticating trans identity narratives
.
Gender & Society
,
32
,
613
637
.
Ghaziani, A. (
2015
).
There goes the gayborhood?
Princeton, NJ
:
Princeton University Press
.
Gonzales, G., & Henning-Smith, C. (
2017
).
The Affordable Care Act and health insurance coverage for lesbian, gay, and bisexual adults: Analysis of the Behavioral Risk Factor Surveillance System
.
LGBT Health
,
4
,
62
67
.
Gonzales, G., Przedworski, J., & Henning-Smith, C. (
2016
).
Comparison of health and health risk factors between lesbian, gay, and bisexual adults and heterosexual adults in the United States: Results from the National Health Interview Survey
.
JAMA Internal Medicine
,
176
,
1344
1351
.
Granberg, M., Andersson, P. A., & Ahmed, A. (
2020
).
Hiring discrimination against transgender people: Evidence from a field experiment
.
Labour Economics
,
65
,
101860
. https://doi.org/10.1016/j.labeco.2020.101860
Gundersen, C., & Ziliak, J. P. (
2015
).
Food insecurity and health outcomes
.
Health Affairs
,
34
,
1830
1839
.
Hart, C. G., Saperstein, A., Magliozzi, D., & Westbrook, L. (
2019
).
Gender and health: Beyond binary categorical measurement
.
Journal of Health and Social Behavior
,
60
,
101
118
.
Henning-Smith, C., & Gonzales, G. (
2018
).
Differences by sexual orientation in perceptions of neighborhood cohesion: Implications for health
.
Journal of Community Health
,
43
,
578
585
.
Herek, G. M. (
2002
).
Heterosexuals' attitudes toward bisexual men and women in the United States
.
Journal of Sex Research
,
39
,
264
274
.
Herek, G. M., & Berrill, K. T. (
1992
).
Hate crimes: Confronting violence against lesbians and gay men
.
Thousand Oaks, CA
:
Sage Publications
.
Hsieh, N., & Liu, H. (
2019
).
Bisexuality, union status, and gender composition of the couple: Reexamining marital advantage in health
.
Demography
,
56
,
1791
1825
.
Hsieh, N., & Liu, H. (
2021
).
Social relationships and loneliness in late adulthood: Disparities by sexual orientation
.
Journal of Marriage and Family
,
83
,
57
74
.
Hsieh, N., & Shuster, S. M. (
2021
).
Health and health care of sexual and gender minorities
.
Journal of Health and Social Behavior
,
62
,
318
333
.
Idler, E. L., & Benyamini, Y. (
1997
).
Self-rated health and mortality: A review of twenty-seven community studies
.
Journal of Health and Social Behavior
,
38
,
21
37
.
James, D. (
2020
).
Health and health-related correlates of internalized racism among racial/ethnic minorities: A review of the literature
.
Journal of Racial and Ethnic Health Disparities
,
7
,
785
806
.
James, S. E., Herman, J. L., Rankin, S., Keisling, M., Mottet, L., & Anafi, M. (
2016
). Executive summary. In
The report of the 2015 U.S. Transgender Survey
(pp.
3
17
).
Washington, DC
:
National Center for Transgender Equality
.
Jones, J. M. (
2021
, February 24).
LGBT identification rises to 5.6% in latest U.S. estimate
. Gallup. Retrieved from https://news.gallup.com/poll/329708/lgbt-identification-rises-latest-estimate.aspx
Jylhä, M. (
2009
).
What is self-rated health and why does it predict mortality? Towards a unified conceptual model
.
Social Science & Medicine
,
69
,
307
316
.
Keene, L. C., Heath, R. D., & Bouris, A. (
2022
).
Disclosure of sexual identities across social-relational contexts: Findings from a national sample of Black sexual minority men
.
Journal of Racial and Ethnic Health Disparities
,
9
,
201
214
.
King, A. (
2016
).
Older lesbian, gay and bisexual adults: Identities, intersections and institutions
.
Abingdon, UK
:
Routledge
.
Lagos, D. (
2018
).
Looking at population health beyond “male” and “female”: Implications of transgender identity and gender nonconformity for population health
.
Demography
,
55
,
2097
2117
.
Lagos, D. (
2019
).
Hearing gender: Voice-based gender classification processes and transgender health inequality
.
American Sociological Review
,
84
,
801
827
.
Lagos, D., & Compton, D. L. (
2021
).
Evaluating the use of a two-step gender identity measure in the 2018 General Social Survey
.
Demography
,
58
,
763
772
.
Lassiter, J. M. (
2014
).
Extracting dirt from water: A strengths-based approach to religion for African American same-gender-loving men
.
Journal of Religion and Health
,
53
,
178
189
.
Liu, H., & Reczek, R. (
2021
).
Birth cohort trends in health disparities by sexual orientation
.
Demography
,
58
,
1445
1472
.
Martin, K. A. (
2009
).
Normalizing heterosexuality: Mothers' assumptions, talk, and strategies with young children
.
American Sociological Review
,
74
,
190
207
.
Mays, V. M., & Cochran, S. D. (
2001
).
Mental health correlates of perceived discrimination among lesbian, gay, and bisexual adults in the United States
.
American Journal of Public Health
,
91
,
1869
1876
.
McCabe, S. E., Matthews, A. K., Lee, J. G., Veliz, P., Hughes, T. L., & Boyd, C. J. (
2018
).
Tobacco use and sexual orientation in a national cross-sectional study: Age, race/ethnicity, and sexual identity–attraction differences
.
American Journal of Preventive Medicine
,
54
,
736
745
.
Meyer, D. (
2015
).
Violence against queer people: Race, class, gender, and the persistence of anti-LGBT discrimination
.
New Brunswick, NJ
:
Rutgers University Press
.
Meyer, I. H. (
1995
).
Minority stress and mental health in gay men
.
Journal of Health and Social Behavior
,
36
,
38
56
.
Meyer, I. H. (
2003
).
Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: Conceptual issues and research evidence
.
Psychological Bulletin
,
129
,
674
697
.
Meyer, I. H., Russell, S. T., Hammack, P. L., Frost, D. M., & Wilson, B. D. M. (
2021
).
Minority stress, distress, and suicide attempts in three cohorts of sexual minority adults: A U.S. probability sample
.
PloS One
,
16
,
e0246827
. https://doi.org/10.1371/journal.pone.0246827
Mishel, E.. (
2016
).
Discrimination against queer women in the U.S. workforce: A résumé audit study
.
Socius
,
2
. https://doi.org/10.1177/2378023115621316
Mishel, E. (
2019
).
Intersections between sexual identity, sexual attraction, and sexual behavior among a nationally representative sample of American men and women
.
Journal of Official Statistics
,
35
,
859
884
.
Mize, T. D. (
2016
).
Sexual orientation in the labor market
.
American Sociological Review
,
81
,
1132
1160
.
Mollborn, S., & Everett, B. (
2015
).
Understanding the educational attainment of sexual minority women and men
.
Research in Social Stratification and Mobility
,
41
,
40
55
.
Mulick, P. S., & Wright, L. W.Jr. (
2002
).
Examining the existence of biphobia in the heterosexual and homosexual populations
.
Journal of Bisexuality
,
2
(
4
),
45
64
.
National Academies of Sciences, Engineering, and Medicine
. (
2020
).
Understanding the well-being of LGBTQI+ populations
.
Washington, DC
:
National Academies Press
.
Ochs, R. (
1996
).
Biphobia: It goes more than two ways
. In Firestein, B. A. (Ed.),
Bisexuality: The psychology and politics of an invisible minority
(pp.
217
239
).
Thousand Oaks, CA
:
Sage Publications
.
Reczek, C., Liu, H., & Spiker, R. (
2017
).
Self-rated health at the intersection of sexual identity and union status
.
Social Science Research
,
63
,
242
252
.
Reczek, R., & Bosley-Smith, E. (
2022
).
Families we keep: LGBTQ people and their enduring bonds with parents
.
New York
:
New York University Press
.
Reisner, S. L., Vetters, R., Leclerc, M., Zaslow, S., Wolfrum, S., Shumer, D., & Mimiaga, M. J. (
2015
).
Mental health of transgender youth in care at an adolescent urban community health center: A matched retrospective cohort study
.
Journal of Adolescent Health
,
56
,
274
279
.
Rimes, K. A., Goodship, N., Ussher, G., Baker, D., & West, E. (
2019
).
Non-binary and binary transgender youth: Comparison of mental health, self-harm, suicidality, substance use and victimization experiences
.
International Journal of Transgenderism
,
20
,
230
240
.
Ringen, S. (
1991
).
Households, standard of living, and inequality
.
Review of Income and Wealth
,
37
,
1
13
.
Ross, M. W. (
1985
).
Actual and anticipated societal reaction to homosexuality and adjustment in two societies
.
Journal of Sex Research
,
21
,
40
55
.
Ross, N. (
2002
).
Community belonging and health
.
Health Reports
,
13
(
3
),
33
39
.
Saperstein, A., & Westbrook, L. (
2021
).
Categorical and gradational: Alternative survey measures of sex and gender
.
European Journal of Politics and Gender
,
4
,
11
30
.
Schilt, K., & Lagos, D. (
2017
).
The development of transgender studies in sociology
.
Annual Review of Sociology
,
43
,
425
443
.
Schnabel, L. (
2018
).
Sexual orientation and social attitudes
.
Socius, 4
. https://doi.org/10.1177/2378023118769550
Sears, L. E., Agrawal, S., Sidney, J. A., Castle, P. H., Rula, E. Y., Coberley, C. R., . . . Harter, J. K. (
2014
).
The Well-Being 5: Development and validation of a diagnostic instrument to improve population well-being
.
Population Health Management
,
17
,
357
365
.
Shuster, S. M. (
2021
).
Trans medicine: The emergence and practice of treating gender
.
New York
:
New York University Press
.
Spiker, R., Stacey, L., & Reczek, C. (
2021
).
Sexual and gender minority health: Toward a more complete accounting of social class
. In LeBlanc, A. & Perry, B. (Eds.),
Advances in medical sociology: Vol. 21. Sexual and gender minority health
(pp.
17
37
).
Bingley, UK
:
Emerald Publishing
.
Sumerau, J. E., Cragun, R. T., & Mathers, L. A. (
2016
).
Contemporary religion and the cisgendering of reality
.
Social Currents
,
3
,
293
311
.
Tilcsik, A. (
2011
).
Pride and prejudice: Employment discrimination against openly gay men in the United States
.
American Journal of Sociology
,
117
,
586
626
.
Timmins, L., Rimes, K. A., & Rahman, Q. (
2017
).
Minority stressors and psychological distress in transgender individuals
.
Psychology of Sexual Orientation and Gender Diversity
,
4
,
328
340
.
Truong, N., Perez-Brumer, A., Burton, M., Gipson, J., & Hickson, D. (
2016
). What is in a label? Multiple meanings of ‘MSM’ among same-gender-loving Black men in Mississippi.
Global Public Health
,
11
,
937
952
.
Ueno, K. (
2010
).
Mental health differences between young adults with and without same-sex contact: A simultaneous examination of underlying mechanisms
.
Journal of Health and Social Behavior
,
51
,
391
407
.
Westbrook, L., Budnick, J., & Saperstein, A. (forthcoming).
Dangerous data: Seeing social surveys through the sexuality prism
.
Sexualities
. Advance online publication. https://doi.org/10.1177/1363460720986927
Westbrook, L., & Saperstein, A. (
2015
).
New categories are not enough: Rethinking the measurement of sex and gender in social surveys
.
Gender & Society
,
29
,
534
560
.
Wheldon, C. W., Watson, R. J., Fish, J. N., & Gamarel, K. (
2019
).
Cigarette smoking among youth at the intersection of sexual orientation and gender identity
.
LGBT Health
,
6
,
235
241
.
Williams, S. L., & Mann, A. K. (
2017
).
Sexual and gender minority health disparities as a social issue: How stigma and intergroup relations can explain and reduce health disparities
.
Journal of Social Issues
,
73
,
450
461
.
Yoshino, K. (
1999
).
The epistemic contract of bisexual erasure
.
Stanford Law Review
,
52
,
353
461
.
Yost, M. R., & Thomas, G. D. (
2012
).
Gender and binegativity: Men's and women's attitudes toward male and female bisexuals
.
Archives of Sexual Behavior
,
41
,
691
702
.
Zilioli, S., Slatcher, R. B., Ong, A. D., & Gruenewald, T. L. (
2015
).
Purpose in life predicts allostatic load ten years later
.
Journal of Psychosomatic Research
,
79
,
451
457
.
This is an open access article distributed under the terms of a Creative Commons license (CC BY-NC-ND 4.0).