Structural stigma and alcohol use among sexual and gender minority adults: A systematic review

Highlights • Structural stigma is positively associated with negative alcohol-related outcomes.• There are differences by gender, race, ethnicity, and sexual identity.• Most studies are cross-sectional and used non-probability samples.• Gender minority people and many sexual identity subgroups are underrepresented.• Sexual and gender minority people of color are underrepresented.

• Structural stigma is positively associated with negative alcohol-related outcomes.
• There are differences by gender, race, ethnicity, and sexual identity.
• Most studies are cross-sectional and used non-probability samples.
• Gender minority people and many sexual identity subgroups are underrepresented.
• Sexual and gender minority people of color are underrepresented.Background: Sexual and gender minority (SGM) people are more likely than their cisgender, heterosexual counterparts to report negative alcohol-related outcomes.Although the association between individual-and interpersonal-level minority stressors and negative alcohol-related outcomes among SGM people is wellestablished, structural-level minority stressors are understudied.This systematic review examined structurallevel stigma and alcohol-related outcomes among SGM people to inform future research, interventions, and policy.Methods: We used five electronic databases to search for studies published between January 2010 and May 2022 that examined associations between structural stigma and alcohol use among SGM adults in the United States.Peer-reviewed, quantitative studies available in English were included.We conducted quality appraisal using the Joanna Briggs Institute checklist.Results: The final sample included 11 studies.Overall, there was moderate to strong support for a positive association between structural stigma and negative alcohol-related outcomes among SGM people, with differences by gender, sexual identity, race, and ethnicity.All studies used cross-sectional designs, and nearly half utilized non-probability samples.Transgender and nonbinary people, SGM people of color, and sexual identity subgroups beyond gay, lesbian, and heterosexual were underrepresented.Structural stigma was most commonly measured as a state-level index.Alcohol measures were heterogeneous.Multilevel stigma and resiliency factors were understudied.Conclusions: Addressing structural stigma is critical in reducing negative alcohol-related outcomes and inequities among SGM people.Research is needed that includes probability samples, longitudinal designs, and samples that reflect the diversity of SGM people.Future studies should examine the influence of multilevel stigma and resiliency factors on alcohol-related outcomes.

Introduction
Excessive alcohol use is a major public health issue in the United States (U.S.), contributing annually to more than 140,000 deaths and nearly 3.6 million years of lost life between 2015 and 2019 Centers for Disease Control and Prevention (2022).Risk for negative alcohol-related outcomes differs by sexual identity (how an individual identifies sexually or romantically, e.g., lesbian, gay, bisexual, heterosexual) and gender identity (an individual's experience of gender, e.g., man, woman, nonbinary, agender, or elsewhere along a gender spectrum).Sexual minority (e.g., lesbian, gay, bisexual) and gender minority (e.g., transgender, nonbinary) people have higher prevalence of alcohol use and poorer alcohol-related health outcomes than their cisgender, heterosexual counterparts (Drabble et al., 2021;Hughto et al., 2021;Krueger et al., 2020;Schuler et al., 2018).For example, in analyses of the National Epidemiologic Survey on Alcohol and Related Conditions III, sexual minority people had 1.6-1.9times higher odds of past-12-month alcohol use disorder (AUD) and 1.7-2.4times higher odds of lifetime AUD than their heterosexual counterparts (Kerridge et al., 2017).This disparity was more pronounced among women; sexual minority women (SMW) had 2.1-2.5 times higher odds of past-12-month AUD and 2.2-2.7 times higher odds of lifetime AUD than heterosexual women (Kerridge et al., 2017).
Alcohol outcomes also differ within the overall SGM population.For example, in the 2013-2014 National Health Interview Survey, compared with their heterosexual counterparts, bisexual men were 3.15 times more likely, lesbian women were 2.62 times more likely, and bisexual women were 2.07 times more likely to report heavy drinking (Gonzales et al., 2016).In the 2014-2017 Behavioral Risk Factor Surveillance System (BRFSS), compared to cisgender women, "gender nonconforming" individuals had 2.09 times higher odds of heavy drinking and 1.94 times higher odds of binge drinking, and "male to female" transgender individuals had 1.88 times higher odds of binge drinking (Azagba et al., 2019).Further, in a national study of insurance claims data, the prevalence of AUD among transgender adults was 2.75 times higher than among cisgender adults (Hughto et al., 2021).There are also differences by race and ethnicity, particularly among SMW (Schuler et al., 2020).For example, compared to heterosexual counterparts of the same race/ethnicity, there was a greater disparity in heavy episodic drinking risk among Hispanic SMW (adjusted risk ratio = 1.55-1.68)and Black SMW (adjusted risk ratio = 1.38-1.56)than among White SMW (adjusted risk ratio = 1.0-1.23;Schuler et al., 2020).
Minority stress, i.e., exposure to stressors such as discrimination related to stigmatized minority status (e.g., sexual or gender identity, race, ethnicity; Brooks, 1981;Meyer, 2003), is the predominant explanatory framework used to understand SGM-related alcohol-use disparities.The minority stress model illustrates how distal minority stressors (e.g., experiences of discrimination) lead to more proximal internalizations of social stigma (e.g., internalized stigma, or negative feelings about one's sexual identity; Meyer, 2003).Minority stress wears on individuals and is associated with numerous poor physical, mental, and behavioral health outcomes among sexual and gender minority (SGM) people (Frost et al., 2015;Lewis et al., 2016Lewis et al., , 2017)).Further, SGM people with multiple marginalized identities may experience additional stressors, such as racism, that compound risk (Bowleg, 2008(Bowleg, , 2012;;Meyer, 2010).
The minority stress model focuses on minority stressors at the individual and interpersonal levels, which are well established in the literature as contributing factors to alcohol risk among SGM people.For example, internalized homophobia (Felner et al., 2020;Hequembourg and Dearing, 2013;Hughes et al., 2020), stigma consciousness (Felner et al., 2020;Lewis et al., 2017), family rejection (Everett et al., 2021;Hughes et al., 2020), and discrimination based on sexual orientation or gender identity (Hughes et al., 2016;Kcomt et al., 2020;McCabe et al., 2010McCabe et al., , 2019;;Wilson et al., 2016) have each been associated with poor alcohol-related outcomes among SGM people.However, despite evidence of harms of SGM stigma at the individual and interpersonal levels, there has been relatively little attention to stigma at the structural level (Hatzenbuehler, 2016;Hughes et al., 2020).
Some researchers more broadly interpret minority stress theory to include stigma at the structural level (Hatzenbuehler, 2016;Hatzenbuehler and Pachankis, 2016).Structural stigma is defined as "societal-level conditions, cultural norms, and institutional policies that constrain opportunities, resources, and well-being of the stigmatized" (Hatzenbuehler and Link, 2014, p. 2).Examples are policies that permit discrimination in public accommodations (e.g., refusing to provide services to SGM people) or that make it difficult for same-sex couples to adopt a child.More specific examples include "Don't Say Gay" bills, which ban discussion of sexual orientation or gender identity in public school classrooms and permit parents to sue teachers and schools for perceived violations, and bans on gender-affirming care for transgender people of all ages, including adults (Goldberg, 2023;Movement Advancement Project, 2023a).Structural stigma has primarily been conceptualized and measured via policy analysis or aggregated measures of social attitudes (Hatzenbuehler, 2016).To adequately measure stigma, it is important to differentiate structural-level factors from individual-or interpersonal-level factors.For example, absence of a state-level employment nondiscrimination law is a structural-level factor, being fired from a job due to sexual or gender identity is an interpersonal-level factor, and internalizing that experience by taking on a negative view of one's SGM identity is an individual-level factor.
Current research on minority stress and alcohol use among SGM people primarily focuses on the individual and interpersonal levels, and although there is a growing body of research on structural stigma and poor health outcomes among SGM people (Hatzenbuehler, 2014(Hatzenbuehler, , 2016(Hatzenbuehler, , 2018)), few studies focus explicitly on alcohol-related outcomes.This research gap limits understanding and effective interventions to reduce inequities in alcohol-related outcomes among SGM people (Hatzenbuehler, 2016;Krieger, 2014).Therefore, the objective of this review was to identify, evaluate, and synthesize recent literature on structural stigma and alcohol-related outcomes among SGM adults to better inform multilevel interventions aimed at alleviating alcohol-related inequities among SGM people.

Literature search
This review followed the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines (Page et al., 2021).Although the research team developed the protocol a priori, the review was not preregistered.We performed a comprehensive search of five electronic databases, i.e., PubMed, PsycInfo, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase, and LGTBQ+ Source, in May 2022.Searches included keywords and database-specific subject headings for SGM people (population), structural stigma (exposure), and alcohol use (outcome).See Appendix A for the full PubMed search strategy.

Study selection
Identified articles were uploaded to the EndNote citation manager to manually remove duplicates, then uploaded to Covidence (an online systematic review tool).Two authors (S.S.Z. and J.A.B) screened titles and abstracts and excluded articles that were not relevant.This process continued through full text review of remaining articles.Consensus was reached on all disagreements after discussion.Initial disagreements primarily related to whether measures of structural stigma fit the research team's predetermined definition and criteria of an objective structural stigma measure, meaning that the measure had to objectively reflect the sociopolitical environment rather than participants' subjective experiences of structural stigma.After completion of the full text S.S. Zollweg et al.
review, we performed ascendancy and descendancy searches (i.e., a search of all studies cited by each included article and a search of all articles that cited each article, respectively) to identify additional relevant articles.See Fig. 1 for a flowchart of the search process.

Inclusion and exclusion
To meet inclusion criteria, articles had to report findings from peerreviewed studies published in English between January 1, 2010, and May 18, 2022.Included articles quantitatively examined the relationship between structural stigma and alcohol-related outcomes among SGM adults in the U.S. using an objective measure of structural stigma.For example, measures such as presence or absence of state-level policies that are discriminatory toward SGM people met inclusion criteria.In contrast, measures evaluating participants' perceptions of their exposure to structural stigma did not fit the predetermined definition of an objective measure.Because sociopolitical climate and attitudes toward SGM people vary widely between countries, studies outside the U.S. were excluded.Additionally, qualitative studies, literature reviews, case studies and case series, unpublished dissertations, op-eds and other opinion pieces, and editorials were excluded.
We chose 2010 as the earliest date for our search because this marked the beginning of a rapid succession of changes in the sociopolitical environment for SGM people, making earlier studies potentially less relevant to the current context.For example, in 2010, Don't Ask, Don't Tell (a policy that prohibited people in the military from disclosing SGM identities) was repealed (Don't Ask, Don't Tell Repeal Act, 2010) and the Office of Disease Prevention and Health Promotion's (2010) Healthy People objectives included SGM health as a priority for the first time.In 2011, Joint Commission published a lesbian, gay, bisexual, transgender (LGBT) field guide (Tschurtz et al., 2011), and the Institute of Medicine (now the National Academy of Medicine) published a landmark report on LGBT health (Institute of Medicine, 2011).In addition to these sociopolitical changes and increasing attention to sexual and gender identity-related health disparities, 2010 also marked the emergence of early research studies focused on structural stigma and health among SGM people, with few articles on this topic prior to 2010.Specifically, the first seminal studies that included alcohol-related outcomes (among other psychiatric outcomes) related to structural stigma (i.e., on state ballot initiatives banning same-sex marriage in the U.S.) were published between December 2009 and March 2010 (Hatzenbuehler et al., 2009(Hatzenbuehler et al., , 2010;;Keyes et al., 2012).

Data extraction
Publication year, study population, location, sampling strategy, data source, study design, time frame, sample characteristics, study purpose, measures of structural stigma and alcohol use, and study findings were extracted into an excel table by the first author.Data extraction was then checked by the second author for accuracy and completeness.

Quality appraisal
The first author used the 8-item Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Analytical Cross-Sectional Studies (Joanna Briggs Institute, 2020) to appraise quality of studies and risk of bias, and the second author confirmed these appraisals (see Table 1).Response options were "Yes" and "No."The total number of "Yes" responses for each study were tallied.However, JBI checklists do not evaluate studies with overall ratings or percentage scores to avoid the implication that all items are weighed equally.Therefore, the tally of "Yes" responses is not intended as such.

Study and sample characteristics
We retrieved 5645 articles through the database search.After removing 1752 duplicates, we screened 3893 titles and abstracts.At this stage we excluded 3606 irrelevant articles, resulting in 287 full text articles for review.During full text review we excluded 279 articles that did not meet criteria, yielding seven studies.We identified an additional four articles via ascendancy and descendancy searches, resulting in a final sample of 11 articles.
Table 2 includes a summary of study characteristics.All 11 studies were cross-sectional and just over half used probability samples.Studies included data from a variety of sources, including computer-assisted telephone surveys, online surveys, face-to-face computer-assisted personal interviews, and health records.One study used a sample recruited in the Chicago metropolitan area, and the remaining 10 studies used national U.S. samples or samples that represented a majority of states, with wide representation of U.S. regions.Data for all studies were collected between 2000 and 2019.
For sample characteristics, see Table 3.There was a wide range of sample sizes, from 119 to 863,257, with a median size of 3057.Six studies reported mean age, ranging from 34.04 to 54.8 years old.In five of the nine studies reporting race and ethnicity, samples were more than 70% non-Hispanic White, ranging from 37.2% to 81.2%, with a median of 70.92% non-Hispanic White.Two studies did not report numbers or percentages of race or ethnicity.Only two studies examined differences by race or ethnicity and no studies examined age differences.
Nearly all (n = 9) studies focused on sexual minority people.Of these, six reported self-identified sex (i.e., male, female) or gender (i.e., man, woman) without reporting whether participants were cisgender.Two of these nine studies explicitly excluded participants who were not cisgender and one study included cisgender and transgender participants, but the sample was 99.2% cisgender.Of these nine studies, two focused on SMW, two focused on sexual minority men (SMM), and five included SMW and SMM.Of the studies that included both SMW and SMM, four examined gender differences.Four studies included a heterosexual comparison group and three studies examined differences between sexual minority subgroups (e.g., lesbian and bisexual).Overall, sexual identities beyond lesbian and gay were underrepresented, and sexual minority samples were very small compared to heterosexual comparison groups (see Table 3).Only two studies focused on

transgender participants.
All 11 studies assessed structural stigma at the state level, with some variation in specific measures.The most common measure, used in six studies, was Movement Advancement Project's (MAP) measure of state policy environment, which is an index based on the number of protective and discriminatory SGM-related laws in each state.Similar to the MAP index, the Human Rights Campaign State Equality Index is based on protective and discriminatory state laws; this index was used by two studies.Greene et al. (2020) used both MAP and Human Rights Campaign indices and found complete agreement between the two.Two studies operationalized structural stigma as state-level laws permitting or banning civil union or marriage between two people of the same sex/gender.One study used a structural stigma index based on z-transformed scores of state-level LGB policies and state-level public attitudes toward LGB people.One study operationalized structural stigma as the presence of a state-level employment nondiscrimination law and state-level inclusion of gender identity or transgender status in hate crime laws; this was also the only study to use a city-level measure-the Municipality Equality Index.Finally, only one study investigated more than one level of minority stressors or stigma: Pachankis et al. (2014) examined whether rejection sensitivity (individual-level) interacted with structural stigma.
Studies varied widely in their use of alcohol outcome measures (see Table 3).Four studies used clinical measures for AUD, including the DSM-5 AUD, the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C), an ICD-9 code, and the Alcohol Use Disorder and Associated Disabilities Interview Schedule-5 (AUDADIS-5).Five studies used measures of binge drinking, heavy episodic drinking (HED), or high intensity binge drinking.Additional alcohol outcome measures include average number of alcoholic drinks per day, alcohol use (versus non-use), and hazardous drinking (i.e., HED, intoxication, adverse drinking consequences, and alcohol dependence symptoms).

Methodological quality
The methodological quality of included studies was high.Seven studies met all eight criteria for methodological quality (see Table 1) using the JBI cross-sectional studies checklist (Joanna Briggs Institute, 2020).The remaining four studies (du Bois et al., 2018;Greene et al., 2021;Greene et al., 2020;Pachankis et al., 2014) met all but one criterion.Two of these studies did not meet the criterion, "Were the outcomes measured in a valuable and reliable way" because they used alcohol measures that were not based on clinical criteria or established guidelines and were not previously validated (both measures used a single item; du Bois et al., 2018;Pachankis et al., 2014).The other two studies did not meet the criterion, "Were the study subjects and the setting described in detail?" -one did not include absolute numbers or percentages for age, education, or income (Greene et al., 2021), and neither study included absolute numbers or percentages for race or ethnicity (Greene et al., 2021(Greene et al., , 2020)).However, both studies used BRFSS data, which is a large probability sample of the U.S. non-institutionalized population, so the risk of bias remains low.JBI checklists are not intended for interpretation as scales with total scores.Although scores have been calculated as a reference, they should not be misconstrued as an overall rating (see Table 1).

Structural stigma and alcohol use disorder
Four studies examined the association between structural stigma and AUD.There was overall moderate support for a positive association.In a large national sample, Hatzenbuehler et al. (2010) found that both heterosexual and LGB adults had higher odds of AUD after passage of a same-sex marriage ban, compared to odds before the ban, with greater magnitude among LGB than heterosexual adults.Similarly, in an online study with SMM, anti-LGBTQ policy environment was positively associated with AUD, and anti-LGBTQ policy environment strengthened the positive association between structural racism and AUD among Black SMM (English et al., 2021).In the same study, neither anti-LGBTQ policy environment, nor structural racism, nor the interaction between the two, were significantly associated among White SMM (English et al., 2021).In a large national sample, Drabble et al. (2021) found no significant difference in probability of AUD among either SMW or SMM in states with comprehensive LGBTQ+ policy protections compared to those in states without comprehensive protections.Additionally, in a study of transgender veterans, there was no association between state-level inclusive hate crime laws or employment nondiscrimination laws and AUD (Blosnich et al., 2016).Further, opposite the hypothesized direction, veterans with AUD tended to live in cities with higher city-level LGTBQ equality, and higher city-level LGTBQ equality was associated with higher odds of AUD; however, the effect was very small (Blosnich et al., 2016).

Structural stigma and heavy episodic drinking
Six studies investigated associations between structural stigma and HED; findings provided moderate to strong evidence of a positive association, especially among SMW.In a national online study, comprehensive LGBTQ+ policy protections were significantly associated with fewer days of HED among SMW, particularly bisexual women (Drabble et al., 2022).Further, in a large national sample, Greene et al. (2020) found that lesbian women in states without LGBTQ+ inclusive statutes had higher odds of binge drinking than straight (heterosexual) women, whereas odds did not significantly differ in states with inclusive statutes (i.e., the disparity was only significant in more hostile policy environments).Bisexual women in this study had higher odds of binge drinking than straight women in all states, but this disparity was substantially smaller in states with an inclusive policy environment.In another study using the same dataset, Greene et al. (2021) found that in states with inclusive statutes, a stricter alcohol policy environment was associated with lower odds of binge drinking among women, but there was no association in states without inclusive statutes, suggesting that stricter alcohol policies may be protective against binge drinking among women, but only in LGBTQ+ inclusive policy environments (Greene et al., 2021).Similarly, in a subsample from a national study, structural stigma was positively associated with binge drinking among lesbian women (Manser and Du Bois, 2021).
Two studies had mixed or null findings among SMW.One study utilized a quasi-experimental design to compare SMW in a community sample who were interviewed at various points throughout the legislation process of passing a state bill permitting civil unions (i.e., before bill signing, after signing but pre-enactment, or after enactment; Everett et al., 2016).SMW with high school education or less reported lower HED after the bill was signed compared to those interviewed before; however, enactment of this legislation was associated with higher HED among the full sample (Everett et al., 2016).Similarly, in a large national sample, comprehensive LGBTQ+ protections were not associated with either odds or probability of high intensity (8+ drinks/day) drinking among SMW or heterosexual women (Drabble et al., 2021).
There was some evidence of a positive association between structural stigma and HED among SMM.In a large national sample, comprehensive LGBTQ+ protections were associated with lower odds of high intensity (8+ drinks/day) drinking among SMM, but not among heterosexual men (Drabble et al., 2021).Additionally, in states with comprehensive LGBTQ+ protections, SMM had lower probability of high intensity drinking than SMM in states without such protections (Drabble et al., 2021).However, some studies had null findings among SMM.In a large national sample, there was no significant interaction between sexual identity and inclusive policy environment for gay and bisexual men (Greene et al., 2020).In another study using the same dataset, there were no significant associations between sexual identity, alcohol policy environment, presence of inclusive statutes, and binge drinking among men (Greene et al., 2021).Similarly, in a subsample from a national study, structural stigma was not associated with binge drinking among gay men (Manser and Du Bois, 2021).

Structural stigma and additional alcohol measures
Three studies examined the association between structural stigma and alcohol-related outcomes other than AUD or HED; there was overall moderate to strong support for a positive association with these outcomes.In a community sample of SMW, the signing and enactment of state-level legislation allowing same-sex civil unions were associated with fewer adverse drinking consequences, but not alcohol dependence symptoms or intoxication (Everett et al., 2016).In a subsample of transgender adults from a national study, a more inclusive policy environment was associated with a decrease in average number of alcoholic drinks per day (du Bois et al., 2018).In an online sample of SMM university students, there was no association between past (i.e., during high school) or current structural stigma and alcohol use; however, past structural stigma strengthened the association between rejection sensitivity and more frequent alcohol use (Pachankis et al., 2014).

Racial/ethnic differences
Only two studies examined racial/ethnic differences in the association between structural stigma and negative alcohol-related outcomes among SGM people and findings were mixed.In one study, structural stigma was positively associated with AUD among Black SMM, but not White SMM (English et al., 2021).Further, anti-LGBTQ policy environment strengthened the positive association between structural racism and AUD among Black SMM (English et al., 2021).In contrast, the second study found that White SMW reported more alcohol dependence symptoms after legislation permitting same-sex civil unions was signed compared to White SMW interviewed prior to bill signing, but Black and Latina SMW did not.(Everett et al., 2016).Further, after the bill was signed, Black and Latina SMW reported less frequent intoxication than White SMW (Everett et al., 2016).

Discussion
This review fills a gap by summarizing and synthesizing the small but growing body of literature on the relationship between structural stigma and alcohol use among SGM people, which to our knowledge has not been done previously.Findings provided moderate to strong support for a positive association between structural stigma and negative alcoholrelated outcomes including AUD, HED, and adverse drinking consequences.This association was more pronounced among SMW than SMM, and among bisexual women than lesbian women.Overall, findings indicate that approaches to reducing poor alcohol-related outcomes and inequities among SGM people will likely be more effective if they address structural stigma.
Subgroup differences in the positive association between structural stigma and poor alcohol-related outcomes among sexual minority people are consistent with prior research documenting variation in alcohol outcomes by sexual identity and gender.In general, associations between structural stigma and alcohol use were stronger among SMW than among SMM (Greene et al., 2020(Greene et al., , 2021;;Manser and Du Bois, 2021); this is unsurprising given previous findings that alcohol-use disparities are more pronounced among SMW than SMM (Hughes et al., 2016(Hughes et al., , 2020;;McCabe et al., 2019).Further, findings of stronger associations between structural stigma and alcohol use among bisexual women than lesbian women (Drabble et al., 2022;Greene et al., 2020Greene et al., , 2021) ) are in line with previous findings that bisexual women experience worse alcohol-related outcomes than lesbian women (Hughes et al., 2020;Schuler and Collins, 2020).However, few studies in this review examined differences by gender or sexual identity.
Some findings suggest that associations between structural stigma and negative alcohol-related outcomes may differ by race or ethnicity, but overall, relevant findings were mixed.English et al. (2021) found that structural stigma was more strongly associated with AUD among Black SMM than White SMM, and that it amplified the positive association between structural racism and AUD.This echoes previous findings that Black sexual minority people may experience worse alcohol-related outcomes than their White counterparts (Greene et al., 2020;Schuler et al., 2020).Drinking may serve as a coping mechanism, in particular among people who experience multiple forms of oppression (e.g., racism, homophobia, transphobia) simultaneously (Lewis et al., 2016).This may be related to the harm of multiple interlocking systems of oppression (e.g., sexism, racism, homophobia, class oppression; Collins, 1991;Crenshaw, 1989Crenshaw, , 1991Crenshaw, , 1995;;The Combahee River Collective, 1977) on health, above and beyond a sum of its parts (Bowleg, 2008(Bowleg, , 2012)).In contrast, however, Everett et al. (2016) found an unexpected positive association between protective legislation and greater alcohol dependence symptoms among White SMW, but not among Black or Latina SMW.Given that findings were mixed and given the small number of studies that examined racial or ethnic differences, caution is warranted in interpretation of these findings.Future work is needed to further investigate potential racial/ethnic differences in the relationship of structural stigma and alcohol-related outcomes among SGM people, as well as the role of interlocking systems of oppression.
Only two studies examined the relationship between structural stigma and alcohol-related outcomes among gender minority people, and findings were mixed.du Bois et al. (2018) found that a more inclusive policy environment was associated with lower alcohol use among transgender adults.In contrast, Blosnich et al. (2016) found the opposite; however, the effect was very small, and could potentially be explained by endogeneity.Additionally, this study included patients who had an ICD-9 diagnosis of gender identity disorder, so those who concealed their minority gender identity would have been missed (Blosnich et al., 2016).Previous studies have shown that lower structural stigma is associated with lower odds of avoiding healthcare due to fear of mistreatment among transgender people (Goldenberg et al., 2020).It is possible that people in higher equality environments were more likely to disclose gender identity and to seek AUD treatment when needed, thereby creating a spurious positive association between high equality and greater odds of AUD.It is also possible that higher equality fosters connectedness to the SGM community, which has been associated with higher substance use in previous studies (Demant et al., 2018;Feinstein et al., 2017), possibly due to more permissive alcohol norms (Cochran et al., 2012) or perceived permissive alcohol norms (Boyle et al., 2020) among sexual minority people, although it is unclear if this is also the case for gender minority adults.Finally, AUD may be too high of a threshold, leading to potential misclassification.
Although findings overall were supportive of a moderate to strong association between structural stigma and poorer alcohol-related outcomes among SGM people, there were also some unexpected findings.For example, Everett et al. (2016) found that signing and enactment of a bill permitting same-sex civil unions were associated with worse alcohol-related outcomes compared to pre-signing and pre-enactment among some SMW.However, alcohol measures were based on the past 12 months and may not have been sensitive to legislative changes that were confined to a four-month period.Further, changes in alcohol use in response to legislation may not have been immediate enough to be reflected in the study findings.
The body of literature reviewed has several strengths and limitations that should inform future research.Most studies used national samples or represented a majority of U.S. states and regions.Additionally, most studies had large sample sizes.Studies were also of high methodological quality.However, nearly half used non-probability samples and all studies were cross-sectional; research with probability samples and longitudinal designs is needed to capture periods of policy change.Additionally, even among studies using large national samples, samples of SGM participants were relatively small, making it less likely they were representative, despite probability sampling.Studies underrepresented transgender and nonbinary people, SGM people of color, and sexual identity subgroups beyond gay and lesbian (e.g., bisexual, pansexual, queer).Further, even among studies with diverse samples, few examined subgroup differences by race, ethnicity, gender, or sexual identity, and none examined age group differences.Researchers should strive to recruit samples that are representative of the diversity of SGM people and consider oversampling of smaller groups that may not otherwise be adequately represented.Given prior research that shows subgroup differences (e.g., by race, ethnicity, sexual identity, gender identity) in the relationship between stigma and alcohol use at the individual and interpersonal levels, studies are needed that investigate such differences in associations between structural stigma and alcohol use.
There were also potential alcohol measurement concerns in the included studies.In particular, alcohol measures were heterogeneous and ranged from a very low threshold, such as whether a participant drank any amount of alcohol each day (Pachankis et al., 2014), to a high threshold, such as meeting diagnostic criteria for AUD (Blosnich et al., 2016;Drabble et al., 2021;English et al., 2021;Hatzenbuehler et al., 2010).Although low threshold and high threshold measures are appropriate for certain research questions, a low bar may not meaningfully differentiate participants who drink enough to harm health, and a high bar may miss participants whose use is harmful to their health but falls short of AUD.Given that previous research has found that permissive cultural norms and perceived norms are associated with heavier alcohol use among sexual minority people (Boyle et al., 2020;Cochran et al., 2012), it may be especially important to design studies that capture whether structural stigma is associated with heavier alcohol use that may not reach AUD criteria.
This review illuminates the need for expanded measures of structural stigma in future research.Only one study examined public opinion or social stigma (Pachankis et al., 2014), despite it being both a potential cause and effect of anti-SGM policies, and only one study examined city-level structural stigma (Blosnich et al., 2016).Future research S.S. Zollweg et al. should investigate the influence of public opinion and social stigma on SGM alcohol use.Future research should also examine whether more proximal measures of structural stigma at institutional, neighborhood, and regional levels are associated with alcohol use among SGM people, and whether proximal measures are equally, or more important, than more distal measures of stigma at the state or national levels.Additionally, most included studies utilized an index of multiple laws and policies to measure structural stigma, which provides a picture of how the overall policy environment influences alcohol use among SGM people.However, future research should examine which specific policies and policy types are most impactful to help prioritize intervention and advocacy targets.
Findings in this review point to several important gaps in the literature with implications for future research.First, there was an overall lack of multilevel (i.e., individual, interpersonal, and structural) stigma research; only one study examined more than one level simultaneously (Pachankis et al., 2014).It is important to understand how the different levels influence alcohol use among SGM people, both alone and synergistically, to inform interventions that adequately address the harms of multilevel stigma.Second, no studies examined how resiliency factors (e.g., LGBTQ community connectedness) may buffer against structural stigma.Future studies should aim to identify resiliency factors to inform intervention strategies to mitigate the harms of structural stigma.Third, due to numerous underrepresented groups as mentioned previously, greater diversity (e.g., by race, ethnicity, sexual identity subgroup, gender identity subgroup) of SGM samples would enhance generalizability of the findings.Due to the rapid escalation of anti-SGM legislation in recent years aimed at gender minority people in particular (e.g., criminalization of gender-affirming care for transgender people of all ages), the need for future research on structural stigma and alcohol use among this population is especially critical (Movement Advancement Project, 2023a, 2023b).Relatedly, data collection on SGM identity in health care and on national surveys in line with current recommendations (e.g.., expansive sexual identity and gender identity response options) is crucial to making progress in stigma-related research (National Academies of Sciences Engineering and Medicine, 2020) by improving availability of datasets with large, diverse samples.

Limitations of this review
This review, despite filling a gap in the literature on structural stigma and alcohol-related outcomes among SGM people, is not without limitations.It included peer-reviewed journal articles only.Because journals are more likely to publish significant findings, there is a potential for publication bias.Additionally, despite a comprehensive search strategy, it is possible that we did not identify all studies meeting inclusion criteria.In particular, authors do not always use the term "structural stigma" to describe measures that meet its definition and there are many possible ways to operationalize this construct, making it difficult to capture all articles that meet criteria.It is also possible that we missed relevant articles published prior to 2010.Finally, by restricting our search to studies conducted in the U.S., this may limit generalizability of findings to other countries, particularly those with very different sociopolitical contexts.

Implications for policy and practice
This review highlights the importance of reducing structural stigma through policy change, both by eliminating laws that are hostile to SGM people and by enacting laws that are protective.Stigma is a fundamental cause of population health inequities (Hatzenbuehler et al., 2013) such as alcohol-related health inequities among SGM people.Even as treatment of diseases improves over time, health inequities persist due to underlying social and structural factors (Link and Phelan, 1995;Phelan et al., 2010).If health professionals and policy makers do not address underlying structural issues, efforts to effectively address alcohol-related disparities and inequities will be impeded (Hatzenbuehler et al., 2013;Link and Phelan, 2001).Examples of hostile policies that should be eliminated include, but are not limited to, Don't Say Gay or Trans laws (i.e., laws that prohibit discussion of sexual or gender identity in public schools), gay and trans panic laws (i.e., laws that excuse violence, including murder, toward SGM people as justifiable "panic"), or religious exemption laws (e.g., government officials refusing marriage licenses to SGM people for religious reasons).Example protective laws include housing or employment non-discrimination laws that explicitly enumerate sexual identity and gender identity as protected classes, or bans on conversion therapy.
Even in protective policy environments, individual-and interpersonal-level interventions are needed.Enactment of a protective policy does not necessarily mean that policy will be implemented and/or enforced or that it will influence the social environment (e.g., interactions with neighbors, family, strangers), particularly in the short term.Further, the public discourse (e.g., anti-SGM ad campaigns) around an SGM-related ballot initiative may be harmful, regardless of whether the bill passes (Maisel and Fingerhut, 2011).Additionally, due to a long history of stigma and a hostile sociopolitical environment, changing policies may not undo harm or improve alcohol-related outcomes in the short term.Therefore, individual-and interpersonal-level interventions, such as SGM-tailored alcohol treatment, are important.Further, given the increasingly hostile policy landscape for gender minority people in particular, individual-and interpersonal-level interventions tailored for gender minority people, in addition to policy change, may be especially crucial.A recent study found that a decrease in structural stigma was longitudinally associated with an increase in SGM-tailored programming being offered at substance use treatment facilities (Cascalheira et al., 2022), thereby illustrating the potential of multilevel approaches in addressing alcohol-related health inequities among SGM people.Finally, given the impact of structural stigma on alcohol use among SGM people, clinicians need to be aware of these inequities, incorporate conversations about alcohol use into care for SGM people, and be competent in providing care to SGM people.

Conclusions
Findings from this review support the positive association between structural stigma and poor alcohol-related outcomes among sexual minority people, with stronger associations among SMW than among SMM, and among bisexual women in particular.Few studies included gender minority people or examined differences by race or ethnicity; further research is needed in these areas.Findings build on evidence in the existing literature that individual-and interpersonal-level stigma contribute to poor alcohol-related outcomes and inequities among SGM people and indicate that more research is needed to expand upon the small body of literature on stigma at the structural level.Findings suggest that to adequately address negative alcohol-related outcomes and inequities among SGM people, prevention and intervention efforts should focus on structural stigma as well as individual-and interpersonal-level factors.

Fig. 1 .
Fig. 1.PRISMA Flow Diagram.(For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Table 1
Quality appraisal of included studies.
Note.Scoring is Yes and No.This table includes questions from the JBI Critical Appraisal Checklist for Analytical Cross-Sectional Studies (Joanna Briggs Institute, 2020).S.S. Zollweg et al.

Table 2
Study characteristics.
Note.SOGI = Sexual orientation and gender identity.VA = Veterans Affairs.BRFSS = Behavioral Risk Factor Surveillance System.NESARC = National Epidemiologic Survey on Alcohol and Related Conditions.CHLEW = Chicago Health and Life Experiences of Women.CAPI = Computer Assisted Personal Interview.CATI = Computer Assisted Telephone Interview.SOGI = Sexual Orientation and Gender Identity.SMW = Sexual Minority Women.SMM = Sexual Minority Men.

Table 3
Study findings.
(continued on next page) S.S.Zollweg et al.

Table 3
○ Same-sex marriage ban ○ Employment nondiscrimination ○ Inclusive hate crime laws ○ Adoption ○ Hate Crimes ○ Health benefits ○ Job discrimination ○ Housing discrimination ○ Marriage equality ○ Sodomy ○ Civil unions