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Review: Prevalence and Co-Occurrence of Addictions Among Sexual Minority Subgroups

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Abstract

The purpose of this study is to present current data on the prevalence and co-occurrence of 12 substance and behavioral addictions among adult cisgender sexual minorities (SM). We utilized MEDLINE, PsycINFO, and Google Scholar databases to systematically review the literature on alcohol, nicotine, cannabis, illicit drugs, gambling, eating/food, Internet, sex, love, exercise, work, and shopping within the SM community. Peer reviewed empirical articles in English from 2000 to 2019 were included. When possible, we compared prevalence and co-occurrence statistics between four SM subgroups (stratified into lesbian women, bisexual women, gay men, and bisexual men), and used heterosexual women and men as reference groups. Studies were scant within each area of addiction with the most studies focusing on addictions acknowledged within the DSM-V (alcohol, nicotine, cannabis, illicit drugs, gambling). Significantly fewer studies addressed the prevalence and co-occurrence of behavioral addictions across SM subgroups. Most studies assessing addiction among SM populations either categorize SMs into a single group or only stratify by gender. However, even with limited research, the findings from this review suggest that significant differences in addictive behaviors exist when comparing one SM subgroup to another. There is a strong need for more research that quantifies these disparities through prevalence and co-occurrence statistics.

STATEMENT OF PUBLIC HEALTH SIGNIFICANCE

By better understanding the differences that exist between SM subgroups in terms of addictive behaviors, clinicians will be better able to screen at-risk patients, which would allow for earlier intervention, more tailored treatments, and reductions in healthcare expenditures.

INTRODUCTION

Despite growing acceptance of sexual minorities (SMs) over the past decade, substantial health disparities still exist among these subgroups of the U.S. population.1 Recently, studies have been conducted on the prevalence and co-occurrence of substance use disorders (SUDs) and behavioral addictions among general populations of adults.24 One review in particular concluded that 46% of adults displayed signs of addictive behavior in the past year, with a 23% co-occurrence of addictions.5 A follow-up study completed a review of these behaviors as a function of ethnicity and gender.6 While there is a growing number of studies exploring addictive behaviors within the SM community, this is the first review to analyze the prevalence and co-occurrence of both SUDs and behavioral addictions between SM subgroups.7,8 The present review focuses specifically on cisgender SMs.

There is a strong body of research linking discrimination and sexual minority stress to the elevated addiction rates within SMs.9,10 Recently, there has been a growing number of studies analyzing the sociocultural factors unique to individual SM subgroups and how these factors may explain the different patterns of addiction within each subset of the LGBTQ community. For instance, among sexual minority men, studies suggest that there is an elevated comorbid presentation of sexual compulsivity and use of inhalants and amphetamines (two substances that can be used to enhance sexual experiences).11 Other studies, which directly measured addiction instead of substance use, concluded that significantly elevated rates of SM men suffered from multiple drug addictions, with amphetamines and inhalants ranking among the most common substances.12,13 These co-occurring addictions may be linked to high attendance at gay-circuit parties (large dance events often associated with casual sex and drug use) and location-based dating/hookup mobile apps geared toward gay and bisexual men.8,14 Newer studies are also investigating the concept of “biphobia” (the heightened levels of discrimination that bisexual individuals experience) and the role that this form of discrimination may have on predisposing bisexual individuals to addictive behaviors.15 Thus, it is important not only to look how the fact that SM individuals have higher rates of certain addictions than their heterosexual counterparts, but also to look within this population at the subgroups (gay men, lesbian women, bisexual men, bisexual women) to understand the differences in prevalence and co-occurrence of addictions among these groups.16

In this study, as in previous reviews, we investigated whether participants met the criteria for at least one of 12 addictions (substances: alcohol, nicotine, marijuana, illicit drugs; behaviors: gambling, food/eating, Internet, exercise, sex, love, shopping, work).5,6 When available, we presented results for each addiction based on total U.S. prevalence as well as prevalence within four stratified SM subgroups (i.e., lesbian women, bisexual women, gay men and bisexual men). We also included prevalence statistics for co-occurring addictions when this information was attainable. When quantitative data was unavailable, we decided to reference a selection of nonprevalence studies investigating factors that may lead certain SM subgroups to develop an addictive behavior. Finally, we discussed aspects of this field that warrant additional research as well as considerations that should be acknowledged when analyzing this high-risk but understudied population.

METHODS

We used MEDLINE, PsycINFO, and Google Scholar databases to examine articles published before June 2019. Search terms included: (“Sexual Minority” OR LGB OR LGBT OR LGBTQ OR lesbian OR gay OR bisexual) AND (prevalence OR incidence) AND (co-occurrence OR comorbidity OR “co-occurring disorders” OR “co-occurring addictions”). A wide variety of formal and informal terms were selected across population identity and addiction research to attempt to include a comprehensive set of empirical works. We also included terms for each category of addiction used in Sussman et al.17 as well as pertinent terms from the Diagnostic Statistical Manual of Mental Disorders—Fifth Edition (DSM-V).18 Table 1 includes a complete list of search terms utilized for each addiction.

TABLE 1.
Complete List of Search Terms for Each Addiction
CategorySearch Terms
General“substance use disorder,” “behavioral addiction,” addiction
Alcohol“alcohol dependence,” “alcohol use disorder,” alcoholism
Tobacco“tobacco addiction,” “tobacco use disorder,” “nicotine addiction,” “nicotine dependence”
Marijuana“marijuana abuse,” “marijuana dependence,” “marijuana use disorder,” “cannabis dependence,” “cannabis use disorder”
Illicit Substances“illicit drug abuse,” “drug abuse,” “drug dependence,” “drug addiction,” “substance use disorder”
Gambling“gambling addiction,” “compulsive gambling,” “pathological gambling,” “gambling disorder”
Eating“overeating addiction,” “food addiction,” “eating addiction,” “binge eating disorder,” “overeating dependence,” “eating disorder,” “feeding disorder”
Internet“internet addiction,” “web addiction,” “pathological internet use,” “video game addiction”
Love“love addiction,” “pathological love,” “sexual dependency”
Sex“sex addiction,” “sexual compulsivity”
Exercise“physical activity addiction,” “exercise addiction,” “compulsive exercise”
Work“workaholic,” “workaholism,” “work addiction”
Shopping“shopping addiction,” “compulsive shopping”

As outlined in Figure 1, we identified 718 articles using the aforementioned search criteria, including publications that contained these terms in the title or body of the manuscript. We identified an additional 37 manuscripts by examining reference sections using front/back searches for relevant articles not located through database searches. A total of 125 duplicate manuscripts were identified and removed, resulting in a total of 630 screened articles.

Figure 1.

Diagram of study identification and selection process.

sgrlgbtq_1_3_213

Titles and abstracts of these 630 articles were reviewed in order to identify those of potential relevance. We applied the following inclusion and exclusion criteria:

  1. Studies addressed the prevalence and/or co-occurrence of at least one SUD or behavioral addiction (inclusion).

  2. The study samples included adult patients who identified as cisgender SMs (inclusion).

  3. Studies included more than one SM population in the analysis and/or a heterosexual comparator population (inclusion).

  4. We removed studies with particularly selective samples, for example, inpatients (exclusion).

  5. Studies were peer-reviewed (inclusion).

We also prioritized studies conducted in the United States, but due to the paucity of relevant studies we considered non-U.S. publications as well. After applying these criteria, 121 studies were retained for additional review. The reference lists of these selected papers were searched and an additional six studies were located. Of these 127 eligible studies, an additional 89 articles were excluded for reasons outlined in Figure 1, which resulted in 38 studies that were included in our manuscript.

As outlined in Table 2, there were only 14 studies located through the database search that related to the behavioral addiction categories. As a result, we conducted additional searches to locate any more articles that may provide information regarding these less recognized forms of addiction. In addition to analyzing the reference sections of these 17 articles, we also used Google Scholar to examine any relevant papers that had cited one of these articles. These searches returned 15 additional relevant studies.

TABLE 2.
Summary of Behavioral Addiction Studies
AddictionStudy NameSample SizePurpose of StudyMethod of AssessmentMain Outcomes
GamblingGrant (2006)105 adult men who met DSM-IV criteria for PG.To examine the sexual orientation and clinical correlates of men with PGAll subjects met DSM-IV criteria for PG using the clinician-administered Structured Clinical Interview for Pathologic Gambling, a valid and reliable diagnostic instrument. Psychiatric diagnoses substance use disorders were assessed using the Structured Clinical Interview for DSM-IV.Co-occurrence of lifetime compulsive sexual behavior in individuals meeting the criteria for PG: SM men: 59.1%, heterosexual men: 16.9%

Co-occurrence of current compulsive sexual behavior in individuals meeting the criteria for PG: SM men: 50.0%, heterosexual men: 9.6%

SM men differed significantly from their heterosexual counterparts in both lifetime and current co-occurring disorders, p < .001
SexMorgenstern et al.19183 gay and bisexual male individuals living in the New York City areaTo explore the features of NPCSB in a community sample of gay and bisexual men in New York City who reported difficulty controlling their sexual behaviorSubjects were assessed using the DISC, a semi-structured interview created by the study team to assess NPCSB symptoms based on the Structured Clinical Interview for the DSM-IV substance abuse and dependence modulesAmong those SM men meeting the criteria for sexual compulsivity, 23.0% reported a co-occurring DUD while 20.2% reported a co-occurring AUD.
SexParsons et al. (2012)2,361 gay and bisexual men at a series of gay, lesbian, and bisexual community events in New York CityTo evaluate whether sexual compulsivity fits into a syndemic framework, in which sexual compulsivity is one of a number of co-occurring psychosocial health problems that increase HIV risk among MSM.Subjects were assessed using the Sexual Compulsivity Scale (α = 0.90)Among a sample of SM men, 19.3% met the criteria for sexual compulsivity.
SexKelly et al.201,629 adults members of the LGB community at two large LGB community events in New York CityTo assess the prevalence of SC in a community sample of gay and bisexual men and lesbian and bisexual women and to identify differences in sexual practices based on classification as sexually compulsive within gender.Subject were assessed using the KSCS. Individuals with a score of 24 or above on the KSCS were identified as sexually compulsive.Prevalence of current Sexual Compulsivity among LGBs: SM men: 19.92% (SD = 6.92), SM women: 17.13 (SD = 6.53)

Among those meeting the criteria for SC, 39.4% of SM men reported co-occurring drug use while 24.0% of SM women reported co-occurring drug use.
SexCarrico et al.21879 SM men residing in San FranciscoTo examine whether and how psychological factors are associated with engagement in any stimulant use in the broader population of SM men.The six-item Sexual Preoccupation Scale was completed in the mail-in questionnaire to assess cognitive dimensions of sexual compulsivity.Higher sexual compulsivity scores (AOR = 1.46; 95% CI = 1.18–1.80) were independently associated with increased odds of stimulant use.
FoodRainey et al.22356 adult participants (43.3% SM)To test whether food addiction is elevated in SMs (relative to heterosexuals) and if discrimination and self-compassion may be related to food addiction among SMS.Addictive-like eating was measured using YFASPercentage of participants meeting food addiction criteria: SM: 17.5%, heterosexual: 9.9%; p-value < .05
FoodFeldman (2007)524 adult respondents were interviewed in person (128 heterosexual and 388 LGB)To estimate the prevalence of eating disorders in LGB men and women, and examines the association between participation in the gay community and eating disorder prevalence in gay and bisexual men.WMH-CIDI, a fully structured measure used in the National Comorbidity Study and based on DSM-IV criteria for binge eating disorderLifetime prevalence of binge eating disorder: SM men: 5.2%, SM women: 4.6%, heterosexual women: 1.6%, heterosexual men: 1.5%
FoodRussell (2002)122 adult men recruited from the community via advertisement for heterosexual or homosexual men to participate in a study on sexual orientation and eating patterns (64 heterosexual and 58 SM s)To examine whether homosexuality is a specific risk factor for disordered eating in men.Participants completed six questionnaires, one of which was the Eating Attitudes Test-26 (an assessment of disordered eating)ANCOVAs of disordered eating among male participants: Gay male: mean = 11.43 (SD = 8.91), heterosexual male: mean = 5.03 (SD = 4.35)
FoodLaska et al.2333,907 students participating in a Minnesota state-based survey of 40 two- and four-year colleges and universitiesTo assess disparities in weight and weight-related behaviors among college students by sexual orientation and gender.Three survey items were used to assess frequency of unhealthy weight control behaviors during the past year, including using laxatives to control weight, taking diet pills, and inducing vomiting to control weight. One survey item assessed binge eating, and one item assessed overall satisfaction with body image or size over the past 30 daysPrevalence of past-year binge eating: Bisexual women: 30.2%, lesbian women: 23.3%, gay men: 22.1%, bisexual men: 18.7%, heterosexual women: 17.3%, heterosexual men: 11.4%.

SM subgroups were significantly more likely to report past-year binge eating when compared to their heterosexual counterparts.
FoodAustin et al.2413,795 participants between the ages of 12 and 23; information collected by self-administered questionnaires from six waves of data collection.To describe patterns of purging and binge eating from early through late adolescence in female and male youth across a range of sexual orientations.Items assessing weight-control behaviors were adapted from the YRBSS questionnaire.Using heterosexual women as a reference group, bisexual women were 120% (OR: 2.2, 95% CI: 1.6–3.2) more likely to report past-year binge eating disorder while lesbian women were 110% (OR: 2.1, 95% CI: 1.0–4.6) more likely.

Using heterosexual men as a reference group, bisexual men were 360% (OR: 4.6, 95% CI: 1.2–18.1) more likely to report a past-year binge eating disorder while gay men were 620% (OR: 7.2, 95% CI: 3.7–14.0) more likely.
ExerciseMor et al.(2014)379 adult Israeli men (182 SM men and 197 heterosexual men who train in gyms in Tel Aviv)To associate physical activity and sexual behavior among men in gyms in Tel Aviv by sexual orientation, and also to explore factors associating physical activity with psychological attributes and sexual-risk behavior.Participants responded anonymously to 82 questions about their health and sexual behavior, body image attributes, gym exercise pattern, reason for training, knowledge about HIV transmission, and other attitudes and beliefs about sexual-risk behavior.Percentage of participants who reported anabolic steroid use within the previous six months: SM men: 5.5%, heterosexual men: 0%, p-value < .001

Average number of weekly anaerobic training hours: SM men: 5.0, heterosexual men: 3.9, p-value < .001
ExerciseYelland (2003)158 Australian adults (a community sample of 52 homosexual men, as well as two comparison groups comprising 51 heterosexual men and 55 heterosexual women)To explore body dissatisfaction and disordered eating in homosexual menParticipants were asked to indicate whether they ever exercised. Those who responded positively then rated on five-point scales the importance of eight different reasons for exercising (weight control, fitness, mood, health, attractiveness, enjoyment, to build up muscles, body tone)Gay men rated attractiveness (M = 3.59, SD = 1.09) and to build up muscles (M = 3.49, SD = 1.26) as significantly more important reasons to exercise when compared to both heterosexual men (attractiveness M = 2.75, SD = 1.04, t(130) = 3.38, p < .001; muscles M = 2.86, SD = 1.03, t(129) = 2.44, p < .05) and heterosexual women (attractiveness M = 2.92, SD = 1.20, t(130) = 2.79, p < .05; muscles M = 2.96, SD = 1.15, t(129) = 2.13, p < .05).
ShoppingNicoli de Mattos et al.25171 compulsive buyers (20 men and 151 women) voluntarily seeking treatment in São Paulo, BrazilTo examine the potential gender differences in compulsive buying severity, demographics and psychiatric comorbidities in a treatment seeking sample of compulsive buyers.Compulsive buying severity was assessed using the Portuguese adapted version of the CBSMale compulsive buyers (33.7%) were significantly more likely to report their sexual orientation as nonheterosexual than female compulsive buyers (3.5%), p < .001.
InternetPeltzer (2016)3,262 undergraduate university students (Mean age = 20.5 years, SD = 1.6); 5% (153/3,262) of eligible participants considered themselves as LGBT youthsTo examine health indicators in relation to LGBT among university students in five ASEAN countries (Indonesia, Malaysia, Myanmar, Thailand, and Vietnam).Participants completed a questionnaire including health indicators, gender identity, and sexual orientationAmong those who identified as a SM, 46.4% engaged in pathological Internet use.

Using heterosexuals as a reference group, SMs were 50% more likely to engage in pathological Internet use (AOR 1.5, 95% CI 1.1, 2.1).

Abbreviations: Analysis of Covariance; Adjusted Odds Ratio; AUD = alcohol use disorder; CBS = Compulsive Buying Scale; DISC = Diagnostic Interview for Sexual Compulsivity; DUD = drug use disorder; KSCS = Kalichman Sexual Compulsivity Scale; MSM = men who have sex with men; NPCSB = nonparaphilic compulsive sexual behavior; PG = pathological gambling; SM = sexual minority; World Mental Health Composite International Diagnostic Interview; YFAS = Yale Food Addiction Scale; YRBSS = Youth Risk Behavior Surveillance System.

RESULTS

Alcohol

Prevalence

The most recent data examining the prevalence of alcohol use disorders (AUDs) among U.S. SMs comes from the National Epidemiologic Survey on Alcohol and Related Conditions-III, or NESARC-III.26 This study conducted interviews in 2012–2013 with a nationally representative sample of 36,309 adults. Participants in the study reported both past-year and lifetime prevalence of AUDs and were stratified based on sexual orientation and gender into four SM subgroups (bisexual men, bisexual women, gay men, lesbian women) as well as two reference groups (heterosexual men, heterosexual women). Among the entire NESARC-III sample, past-year and lifetime prevalence of DSM-V AUD were 13.9% and 29.1%, respectively. In comparison to these sample-wide statistics, AUD prevalence rates were elevated in each of the four SM subgroups. Bisexual men reported the highest past-year and lifetime DSM-V AUD prevalence rates (31.4%, 52.6%) followed by bisexual women (29.7%, 51.7%), gay men (26.6%, 46.0%), and lesbian women (24.9%, 45.8%). All four SM groups, regardless of sexual orientation or gender, reported higher AUD prevalence statistics in comparison to the two reference groups: heterosexual men (17.3%, 35.7%) and heterosexual women (9.7%, 21.8%).

The NESARC-III study also presented odds ratios adjusted for sociodemographic characteristics. Since men generally have higher rates of AUD than women in the general population,2730 these odds ratios reduce the confounding impact of gender and indicate the heightened disparities faced specifically by SM women. For instance, while gay men were 30% more likely to report a past-year AUD compared to heterosexual men (Adjusted Odds Ratio 1.3, 95% CI 1.03–1.77), lesbian women were shown to be 120% more likely to report a past-year AUD when compared to heterosexual women (AOR 2.2, 95% CI 1.66–2.91). Several other studies have also indicated that SM women are at a significantly increased risk of developing an AUD.3134

Using NESARC-II data, McCabe et al. examined associations between sexual attraction and AUDs.35 While 2% of this sample identified as either lesbian, gay, or bisexual, 6% identified as having some degree of same-sex sexual attraction, indicating a substantial group of participants who experience attraction to the same gender without personally identifying with a particular SM classification. After being stratified by gender, participants were separated into five groups based on sexual attraction (i.e., only attracted to females, mostly attracted to females, equally attracted to males and females, mostly attracted to males, and only attracted to males). Then, 7.2% of female participants reported same-sex attraction compared to 4.3% of the men in the study.

Among the male participants, those who reported being “mostly attracted to males” reported the highest past-year AUD prevalence (13.3%), followed by those “only attracted to males” (9.4%) and “equally attracted to males and females” (7.6%). Men who reported being “mostly attracted to females” and “only attracted to females” reported the lowest past-year AUD prevalence at 6.3% and 6.2%, respectively. While men displaying predominantly same-sex sexual attraction showed higher prevalence of AUDs when compared to men attracted only to females, no statistically significant differences were found between the groups.

In contrast to the male participants, female participants were found to be at an increased risk of developing an AUD regardless of whether they reported predominantly same-sex or opposite-sex attraction. While 2.4% of women “attracted only to men” reported a past-year AUD, 15.5% of women “mostly attracted to women” and 6.8% of women “attracted mostly to men” reported a past-year AUD. In fact, when using women “only attracted to males” as the reference group, it was found that women “mostly attracted to males” were nearly twice as likely to have a past-year AUD (AOR 1.8, 95% CI 1.3–2.5) while women who reported being “mostly attracted to females” were almost five times more likely to have a past-year AUD (AOR 4.8, 95% CI 1.8–12.8). These findings are of importance since these two groups represent a subset of women who may be less likely to identify with conventional sexual-identity titles. Based on the findings of this study, females who report being “mostly attracted” to one sex or the other may represent a vulnerable subset of SM women who are not always accounted for by traditional sexual identity categories.

Co-occurrence

Two studies were found that examined the lifetime comorbidity of AUDs with cannabis use disorders (CUDs) and illicit drug use disorders (DUDs) among SMs.36,37 Both studies used NESARC-II data; however, SMs were only stratified into two groups by gender (SM men and SM women). Comorbidity of AUD and CUDs was highest among SM women (39.7%) followed by SM men (36.6%), heterosexual men (24.3%), and heterosexual women (20.3%). The same rank order was seen when assessing the comorbidity of AUDs with illicit drug disorders (which include hallucinogens, cocaine, inhalants/solvents, and heroin): SM women (23.3%), SM men (18.3%), heterosexual men (10.8%), and heterosexual women (9.9%).

Another study, which analyzed co-occurring drug use among a sexually diverse sample of 198 men who met the criteria for AUD, concluded that SM men were significantly more likely than their heterosexual counterparts to report co-occurring stimulant use (13.1% vs. 1.8%, χ2 = 5.37, p < .02); there were no significant differences among other drug types, which included opiates, cocaine, marijuana, hallucinogens, ecstasy, Gamma Hydroxybutyrate, and ketamine.38 Given the findings from the two NESARC-II studies, which found SM women to be at the highest risk for co-occurring AUD and drug use, future research should analyze drug use behavior among a sexually diverse sample of women with AUDs.

Nicotine

Prevalence

Elevated smoking prevalence is one of the most consistently identified health disparities among SMs.39 Sample wide prevalence of past-year and lifetime DSM-V nicotine use disorders (NUDs) in NESARC-III were 20.0% and 27.9%, respectively.40 When stratified based on sexual orientation and gender, Kerridge et al.26 found that past-year and lifetime rates were highest among bisexual men (40.8% [SE, 5.54], 51.9% [SE, 5.23]), followed by bisexual women (36.3% [SE, 3.16], 42.2% [SE, 3.34]), gay men (30.0% [SE, 3.56], 40.7% [SE, 3.30]), lesbian women (27.3% [SE, 3.48], 37.1% [SE, 3.58]), heterosexual men (23.0% [SE, 0.55], 31.8% [SE, 0.71]), and heterosexual women (16.4% [SE, 0.43], 23.3% [SE, 0.54]). While SM men had higher NUD prevalence, this study revealed that SM women were more likely to report a past-year NUD compared to their heterosexual counterparts. In fact, lesbians and bisexual women were each 100% more likely to report a NUD when compared to heterosexual women (AOR 2.0, 95% CI 1.45–2.88; AOR 2.0, 95% CI 1.48–2.80). Bisexual men were 80% more likely to have reported a past-year NUD when compared to heterosexual men (AOR 1.8, 95% CI 1.13–2.88), while gay men did not show a significant difference.

Through a secondary analysis of the 2009–2010 National Adult Tobacco Survey (n = 66,922), Fallin et al. examined nicotine dependence among SM subgroups.41 It should be noted that nicotine dependence was measured based on an individual's time to first cigarette (TTFC) upon awakening in the morning, which other studies have concluded is a particularly strong proxy for nicotine addiction.42,43 While bisexual women reported the highest rates of nicotine dependence at 56.05%, there were no statistically significant differences between subgroups. However, when participants were assessed based on current smoking status, rank order of the Fallin study was consistent with NESARC-III data and significant differences were noted. Bisexual men reported the highest rates of current smoking at 33.7%, followed by bisexual women (32.0%), gay men (25.9%), lesbian women (22.4%), heterosexual men (15.9%), and heterosexual women (13.2%). In addition to prevalence, Fallin et al. also utilized odds ratio statistics and concluded that lesbian women were 130% more likely to meet the criteria for nicotine dependence (AOR 2.30, 95% CI 1.05–5.11), while bisexual women, gay men, and bisexual men did not show a significant increase in likelihood, when compared to their heterosexual male and female counterparts.

The Kerridge and Fallin et al. studies used different criteria to assess smoking behavior; however, both studies reported similar findings, which are outlined in Table 3. We also located several studies which indicated bisexual women had the highest prevalence of NUDs; however, compared to the Kerridge and Fallin papers, these studies included a smaller number of participants and nonrepresentative sampling.4446 Furthermore, we located other smaller scale prevalence studies which supported NESARC-II data and concluded that SM males had the highest prevalence of NUDs.4749

TABLE 3.
Summary of Substance Use Disorder Studies
AddictionStudy NameSample SizePurpose of StudyMethod of AssessmentMain Outcomes
AlcoholKerridge et al.2636,309 U.S. adults; 586 gay/lesbians, 566 bisexual men/womenTo present current nationally representative data on the prevalences, sociodemographic correlates and risk of DSM-5 substance use disorders and other psychiatric disorders among SMs relative to heterosexuals, and among SMs by gender.NIAAA AUDAD1S-5 to measure DSM-VAUDs12-month AUD prevalence: Bisexual men: 31.4%, bisexual women: 29.7%, gay men: 26.6%, lesbian women: 24.9%, heterosexual men: 17.3%, heterosexual women: 9.7%

Lifetime AUD prevalence: Bisexual men: 52.6%, bisexual women: 51.7%, gay men: 46.0%, lesbian women: 45.8%, heterosexual men: 35.7%, heterosexual women: 21.8%.

Gay men were 30% more likely to report a past-year AUD compared to heterosexual men (AOR 1.3, 95% CI 1.03–1.77)

Lesbian women were 120% more likely to report a past-year AUD when compared to heterosexual women (AOR 2.2, 95% CI 1.66–2.91).
AlcoholMcCabe et al.3534,653 U.S. adults; approximately 2% of the sample self-identified as lesbian, gay or bisexualTo assess past-year prevalence rates of substance use behaviors and substance dependence across three major dimensions of sexual orientation (identity, attraction, and behavior) in a large national sample of adult women and men in the United States.Alcohol Use Disorder and Associated Disabilities Interview Schedule DSM-IV Version (AUDADIS-IV)Stratified by sexual identity: past-year alcohol dependence: bisexual men: 19.5%, gay men: 16.8%, bisexual women: 15.6%, lesbian women: 13.3%

Stratified by sexual attraction: past-year alcohol dependence: men mostly attracted to males: 11.3%, men only attracted to males: 9.4%, men equally attracted to females and males: 7.6%. men mostly attracted to females: 6.3%, men only attracted to females: 6.2%

Women mostly attracted to females: 15.5%, women mostly attracted to males: 6.8%, women only attracted to females: 5.1%, women equally attracted to males and females: 5.1%, women only attracted to males: 2.4%
Women “mostly attracted to males” were 1.8x as likely to have a past-year AUD when compared to women “only attracted to males” (AOR 1.8, 95% CI 1.3–2.5)

Women “mostly attracted to females” were 4.8 times more likely to have a past-year AUD when compared to women “only attracted to males” (AOR 4.8, 95% CI 1.8–12.8).
AlcoholLee et al.366,899 adult males with AUDs, 176 identified as gay or bisexualTo compare the prevalence of diagnostic co-occurring psychiatric disorders and DUD among SM men with AUD compared with heterosexual males with a lifetime AUD diagnosis.Lifetime substance use disorders were assessed using the AUDADIS-IVAmong SM men with a lifetime AUD, 43.7% (95% CI: 35.3–52.5) reported any lifetime DUD; compared to 28.3% (95% CI: 26.8–29.8) of heterosexual men with a lifetime AUD; p-value < .001

Among SM men with a lifetime AUD, 36.6% (95% CI: 28.5–45.4) reported a lifetime cannabis use disorder; compared to 24.3% (95% CI: 22.9–25.7) of heterosexual men with a lifetime AUD; p-value < .01
AlcoholMereish et al.374,342 adult females with AUDs, 191 identified as lesbian or bisexualTo examine disparities in lifetime co-occurring psychiatric and DUDs among a nationally representative sample of women with lifetime AUDsLifetime substance use disorders were assessed using the AUDADIS-IVAmong SM women with a lifetime AUD, 49.0% (95% CI: 40.4–57.6) reported any lifetime DUD; compared to 26.1% (95% CI: 24.4–27.8) of heterosexual women with a lifetime AUD; p-value < .0001

Among SM women with a lifetime AUD, 39.7% (95% CI: 31.2–48.9) reported a lifetime cannabis use disorder; compared to 20.3% (95% CI: 18.8–21.9) of heterosexual women with a lifetime AUD; p-value < .0001
AlcoholIrwin (2005)198 adult men with a diagnosis of alcohol abuse or dependence in the past 12 months; 145 identified as gay, 53 identified as nongayTo describe the alcohol- and drug-use patterns and alcohol and drug diagnoses in an ethnically and sexually diverse sample of treatment-seeking MSM whose primary diagnosis is either alcohol abuse or alcohol dependenceA semi-structured interview adapted from Composite International Diagnostic Interview was used to assess abuse and dependence of alcohol and of drugs in accordance with the Diagnostic and Statistical Manual–IV (DSM-IV) diagnostic criteria.13.1% of gay men reported stimulant use in the past six months, compared with 1.8% of nongay-identified men (χ2 = 5.37, p < .02)
AlcoholCoulter et al.3312,493 adult participants between 18 and 25 years oldTo estimate sexual orientation differences in alcohol use trajectories during emerging adulthood, and test whether alcohol use trajectories mediate sexual orientation differences in AUDs.Participants meeting the criteria for DSM-IV alcohol abuse or dependence were coded as having a probable AUD, creating a single binary variable.Prevalence of probable AUD: Gay men: 41.4%, bisexual men: 38.9%, mostly heterosexual men: 36.7%, completely heterosexual men (reference group): 26.6%

Prevalence of probable AUD: Mostly heterosexual women: 30.8%, bisexual women: 29.5%, lesbian women: 29.3%, completely heterosexual women (reference group): 14.0%

Using completely heterosexual men as a reference group, gay men were 59% more likely to report an AUD (RR: 1.59, 95% CI: 1.25–2.02) while mostly heterosexual men were 34% more likely to report an AUD (RR: 1.34, 95% CI: 1.10–1.64).

Using completely heterosexual women as a reference group, lesbian women were twice as likely to report an AUD (RR: 2.00, 95% CI: 1.41–2.83), bisexual women were 112% more likely to report an AUD (RR: 2.12, 95% CI: 1.59–2.83), and mostly heterosexual women were 117% more likely to report an AUD (RR: 2.17, 95% CI: 1.91–2.47).
AlcoholGattis et al.3234,653 U.S. adults; approximately 2% of the sample self-identified as lesbian, gay, or bisexualTo examine sexual orientation discordance, a mismatch between self-reported sexual identity and sexual behavior or sexual attraction, by describing the characteristics, substance use disorders, and mental health risks of heterosexual identified individuals who endorsed this pattern of sexual identification, behavior, and attraction.Lifetime substance use disorders were assessed using the AUDADIS-IVPrevalence of lifetime AUDs: Gay men: 59.44%, heterosexual men: 47.89%, heterosexual discordant men: 41.19%; χ2 = 6.25, p-value <. 01

Lesbian women: 58.65%, heterosexual women: 21.64%, heterosexual discordant women: 47.66%; χ2 = 35.57, p-value < .001
AlcoholDrabble et al.317,612 U.S. adults via a national population-based survey of all 50 states of the United States and Washington, DC.To examine the prevalence of abstinence, drinking, heavier drinking, alcohol-related problems, alcohol dependence and help-seeking among homosexual and bisexual women and men compared with heterosexuals.Respondents who reported three or more of the seven criteria in the last 12 months were considered positive for DSM-IV alcohol dependenceCurrent alcohol dependence: Bisexual women: 16.7%, lesbian women: 11.5%, gay men:10.4%, bisexual men: 5.6%, heterosexual men: 5.6%, heterosexual women: 2.3%

Bisexual and lesbian women each had a statistically significant (p-value < .001 for bisexual women, p-value < .01 for lesbian women) increased likelihood of meeting the criteria for current alcohol dependence when compared to their heterosexual female counterparts.
AlcoholGilman et al.348,098 U.S. adults via a nationally representative household surveyTo examine the risk of psychiatric disorders among individuals with same-sex sexual partners.Psychiatric disorders according to DSM-III-R criteria were assessed with a modified version of the Composite International Diagnostic Interview.Past-year alcohol dependence: SM women: 15.3%, SM men: 12.1%, heterosexual men: 11.6%, heterosexual women: 4.1%
NicotineKerridge et al.2636,309 U.S. adults; 586 gay/lesbians, 566 bisexual men/womenTo present current nationally representative data on the prevalences, sociodemographic correlates and risk of DSM-5 substance use disorders and other psychiatric disorders among SMs relative to heterosexuals, and among SMs by gender.NIAAA AUDAD1S-5 to measure DSM-V AUDsPrevalence of past-year NUD: Bisexual men: 40.8%, bisexual women: 36.3%, gay men: 30%, lesbian women: 27.3%, heterosexual men: 23.0%, heterosexual women: 16.4%

Bisexual men were 80% more likely to report a past-year NUD compared to their heterosexual counterparts (AOR: 1.8, 95% CI: 1.13–2.88).

Lesbian women were 120% more likely to report a past-year NUD compared to their heterosexual counterparts (AOR: 2.2, 95% CI: 1.62–3.01), while bisexual women were twice as likely (AOR: 2.0, 95% CI: 1.50–2.79).
NicotineFallin et al.41118,590 U.S. adults through a secondary analysis of the CDC's 2009–2010 National Adult Tobacco SurveyTo examine differences in smoking characteristics (advertising receptivity, age of first cigarette, nondaily smoking, cigarettes per day, nicotine dependence, desire to quit and past quit attempts) among lesbians, gay men, and female and male bisexual adults in the United States.Nicotine dependence was based on the question, “How soon after you wake up do you have your 1st cigarette?”

Current smoking was assessed based on two questions: (1) “Have you smoked at least 100 cigarettes in your entire life?” (choices: yes/no); and (2) “Do you now smoke cigarettes every day some days or not at all.”
Current smoking: Bisexual men: 33.7%, bisexual women: 31.98%, gay men: 25.91%, lesbian women: 22.4%, heterosexual men: 15.88%, heterosexual women: 13.22%

Each SM subgroup had a statistically significant increased likelihood of current smoking compared to their heterosexual counterparts (p < .001).
NicotineConron et al.4467,359 Massachusetts residents who reported sexual identities of heterosexual or straight, gay/lesbian or homosexual, or bisexual in a state-based system of health surveys.To provide estimates of several leading U.S. adult health indicators by sexual orientation identity and gender to fill gaps in the current literature.Self-reported survey assessing if participants were current daily smokersPrevalence of current daily smokers: Bisexual women: 36.9%, bisexual men: 35.4%, gay men: 32.5%, lesbian women: 26.3%, heterosexual men: 20.6%, heterosexual women: 19.4%
NicotinePizacani et al.4585,316 respondents from Oregon and Washington, for 2003–2005, random selection by gender and ageTo explore whether smoking-related knowledge, attitudes, and behaviors also differ between individual SM communities.Current smoking was assessed based on two questions: (1) “Have you smoked at least 100 cigarettes in your entire life?” (choices: yes/no); and (2) “Do you now smoke cigarettes every day some days or not at all.”Prevalence of current smokers: Bisexual men: 35.9% (95% CI: 28.3–44.3), bisexual women: 35.9% (95% CI: 31.3–40.7), gay men: 31.7% (95% CI: 26.8–37.1), lesbian women: 29.5% (95% CI: 25.2–34.2), heterosexual men: 20.3% (95% CI: 19.7–20.7), heterosexual women: 17.3% (95% CI: 16.9–17.8)

Using heterosexual men as a reference group, gay men were 120% (AOR: 2.2, 95% CI: 1.7–2.9) more likely to report current smoking while bisexual men were 90% (AOR: 1.9, 95% CI: 1.4–2.8) more likely.

Using heterosexual women as a reference group, lesbian women were 140% (AOR: 2.4, 95% CI: 1.9–3.0) more likely to report current smoking while bisexual women were 120% more likely (AOR: 2.2, 95% CI: 1.8–2.8).
NicotineCorliss et al. (2013)n = 64,397 high school students across the United States; 6,067 identified as SMsTo examine sexual orientation differences in adolescent smoking and intersections with race/ethnicity, gender, and ageParticipants were asked “Have you ever smoked cigarettes daily, that is, at least one cigarette every day for 30 days.” “During the past 30 days, on how many days did you smoke cigarettes?”Odds ratio of past month smoking when compared to heterosexual counterparts: Lesbian or gay: OR: 3.99, 95% CI: 1.08–14.69

Bisexual male or female: OR: 5.86, 95% CI: 2.76–12.44
NicotineTang et al.4744,606 respondents, 343 self-identified as lesbian; 593 self-identified as gay; and 793 identified themselves as bisexual (511 female and 282 male) via CHIS, a population-based telephone surveyTo compare the cigarette smoking rate of LGB with that of heterosexual individuals using a population-based sample with both male and female adults, and to identify which subsegments of LGB population are particularly burdened by tobacco use.Respondents were asked “Have you smoked at least 100 cigarettes in your entire life?” and “Do you now smoke cigarettes every day, some days, or not at all?”

Current smokers were defined as persons who reported having smoked >100 cigarettes during their lifetimes and who currently smoked every day or on some days.
Prevalence of current smokers: Gay men: 33.2% (95% CI: 27.8–38.7), lesbian women: 25.3% (95% CI: 19.5–31.0), heterosexual men: 21.3% (95% CI: 20.5–22.1), heterosexual women: 14.9% (95% CI: 14.3–15.5)

Prevalence of current smoking among bisexual males and bisexual females was not included; however, it was reported that bisexual females were 108% (OR: 2.08, 95% CI: 1.55–2.79) more likely to report current smoking compared to their heterosexual female counterparts.
NicotineGruskin et al.481,950 LGB adults residing in California;

Data were derived from a 2003–2004 survey of LGB individuals living in California as well as from the 2002 version of the California Tobacco Survey, which gathered data on the state's general population
To conduct a large, population-based study to assess tobacco use in California's LGB population.Current smokers were defined as those who reported having smoked 100 or more cigarettes during their lifetime and who currently smoked every day or on some days.Prevalence of current daily smokers: Bisexual women: 22.6% (95% CI: 15.7–31.6), lesbian women: 22.2% (95% CI: 15.3–31.2), gay men: 19.6% (95% CI: 14.7–25.7), bisexual men: 16.2% (95% CI: 7.2–32.4), heterosexual men: 13.9% (95% CI: 13.5, 14.3), heterosexual women: 9.1% (95% CI: 8.8–9.4).
NicotineBlosnich et al.4993,414 adults randomly selected across ten U.S. statesTo compare health indicators by gender and sexual orientation statuses.Current smokers were defined as those who reported having smoked 100 or more cigarettes during their lifetime and who currently smoked every day or on some days.Prevalence of current daily smokers: Bisexual men: 33.3%, bisexual women: 29.7%, gay men: 22.9%, lesbian women: 19.1%, heterosexual men: 15.8%, heterosexual women: 11.7%

Using heterosexual men as a reference group, gay men were 93% (AOR: 1.93, 95% CI: 1.27–2.93) more likely to report daily smoking, while bisexual men were 92% (AOR: 1.92, 95% CI: 1.04–3.53) more likely.

Using heterosexual women as a reference group, lesbian women were 91% (AOR: 1.91, 95% CI: 1.26–2.91) more likely to report current smoking, while bisexual women were 113% (AOR: 2.13, 95% CI: 1.33–3.42) more likely.
CannabisMcCabe et al.3534,653 U.S. adults; approximately 2% of the sample self-identified as lesbian, gay, or bisexualTo assess past-year prevalence rates of substance use behaviors and substance dependence across three major dimensions of sexual orientation (identity, attraction, and behavior) in a large national sample of adult women and men in the United States.Substance use disorders were assessed using the AUDADIS-IVPast-year prevalence of cannabis dependence: Lesbian women: 5.7%, bisexual women: 3.0%, bisexual men: 1.1%, gay men: 0.6%, heterosexual men: 0.5%, heterosexual women: 0.4%.

Using heterosexual women as a reference group, lesbian women were 11.3 times (AOR: 11.3, 95% CI: 1.7–75.9) more likely to report past-year marijuana dependence.
CannabisGattis et al.3234,653 U.S. adults; approximately 2% of the sample self-identified as lesbian, gay, or bisexualTo examine sexual orientation discordance, a mismatch between self-reported sexual identity and sexual behavior or sexual attraction, by describing the characteristics, substance use disorders, and mental health risks of heterosexual identified individuals who endorsed this pattern of sexual identification, behavior, and attraction.Lifetime substance use disorders were assessed using the AUDADIS-IVPrevalence of lifetime cannabis use disorders: Gay men: 25.38%, heterosexual discordant men: 18.16%, heterosexual men: 13.45%; χ2 = 7.21, p-value < .001

Lesbian women: 28.74%, heterosexual discordant women: 18.34%, heterosexual women: 5.62%; χ2 = 24.73, p-value < .001
CannabisCochran et al.509,888 U.S. adults; 174 SMs (98 men, 96 women) and 9,714 heterosexual (3,922 men, 5,792 women) respondents.To compare patterns of drug use and dependence between homosexually experienced and exclusively heterosexually experienced individuals.Respondents answered questions assessing the presence or absence of six of seven symptoms of drug dependence within in the prior year. Items reflected DSM-IV defining symptoms of drug dependencePast-year cannabis dependence: SM men: 5.7%, SM women: 3.9%, heterosexual men: 2.1%, heterosexual women: 0.9%
CannabisHequembourg (2013)389 U.S. adults in Buffalo, New York; 97 gay men, 87 bisexual men, 98 lesbians, and 107 bisexual women with a mean age of 24.4 (SD = 4.3; range: 18–35) years old.To examine the interrelationships among shame-proneness, guilt-proneness, internalized heterosexism, and problematic substance use among 389 gay, lesbian, and bisexual men and women.Drug dependence was assessed based on five questions from the Diagnostic Interview Schedule concerning lifetime problematic use of each of the specified illicit drugs (e.g., “Have you ever used [club drugs] for 2 weeks or more?”). Response options were 0 = “no” and 1 = “yes.” Participants’ scores indicated drug dependence if they answered “yes” to at least one of the five questions about problematic use, and their scores indicated severe dependence if they answered “yes” to four or five of the questions.Cannabis dependence: Bisexual men: 57.5%, bisexual women: 46.7%, gay men: 44.8%, lesbian women: 25.5%

Severe cannabis dependence: Bisexual men: 20.7%, bisexual women: 20.6%, gay men: 13.5%, lesbian women: 8.0%.
Illicit DrugsHatzenbuehler et al.5134,653 U.S. adults; approximately 2% of the sample self-identified as lesbian, gay, or bisexualTo investigate the modifying effect of state-level policies on the association between lesbian, gay, or bisexual status and the prevalence of psychiatric disorders.Substance use disorders were assessed using the AUDADIS-IVPrevalence of past-year DUD: LGB men and women: 11.7%, heterosexual men and women: 2.3%

Compared to heterosexual participants, LGB men and women were 320% (AOR: 4.21, 95% CI: 2.83–6.25) more likely to meet the criteria for a past-year DUD.
Illicit DrugsKerridge et al.2636,309 U.S. adults; 586 gay/lesbians, 566 bisexual men/womenTo present current nationally representative data on the prevalences, sociodemographic correlates and risk of DSM-5 substance use disorders and other psychiatric disorders among SMs relative to heterosexuals, and among SMs by gender.NIAAA AUDADIS-5 to measure DSM-V AUDsPrevalence of past-year DUD: Bisexual women: 30.8%, bisexual men: 26.5%, gay men: 19.6%, lesbian women: 19.2%, heterosexual men: 12.1%, heterosexual women: 7.0%

Using heterosexual men as a reference group, bisexual men were 90% (AOR: 1.9, 95% CI: 1.18–3.01) more likely to report a past-year DUD.

Using heterosexual women as a reference group, bisexual women were 280% (AOR: 3.8, 95% CI: 2.64–5.42) more likely to report a past-year DUD while lesbian women were 170% (AOR: 2.7, 95% CI: 1.82–4.09) more likely to report one.
Illicit DrugsMcCabe et al.5234,653 adults; approximately 2% of the sample self-identified as lesbian, gay, or bisexualTo examine substance abuse treatment utilization across three dimensions of sexual orientation (identity, attraction, behavior) in a large national sample of adults in the United States.Substance use disorders were assessed using the AUDADIS-IVPrevalence of lifetime DUD: Bisexual women: 40.4%, gay men: 32.7%, bisexual men: 25.4%, lesbian women: 24.5%, heterosexual men: 15.7% heterosexual women: 8.0%.

Using heterosexual women as a reference group, lesbian women were 170% (AOR: 2.7, 95% CI: 1.5–4.7) more likely to report a lifetime DUD, while bisexual women were 290% (AOR: 3.9, 95% CI: 2.5–6.3) more likely.

Using heterosexual men as a reference group, gay men were 160% (AOR: 2.6, 95% CI: 1.7–4.0) more likely to report a lifetime DUD, while bisexual men were 120% (AOR: 2.2, 95% CI: 1.1–4.1) more likely.

Abbreviations: Adjusted Odds Ratio; AUD = alcohol use disorder; AUDADIS-5 = Alcohol Use Disorder and Associated Disabilities Interview Schedule-5; CHIS = California Health Interview Survey; Center for Disease Control and Prevention; The National Institute on Alcohol Abuse and Alcoholism; NUD = nicotine use disorder; SM = sexual minority.

Co-occurence

We found no nicotine dependence-related studies examining its comorbidity with other addictions between SM subgroups.

Cannabis

Prevalence

The most recent prevalence statistics for CUDs among U.S. SMs have come from NESARC-II data, which used DSM-IV criteria to define SUDs.35 When stratified into SM subgroups, lesbian women reported the highest levels of past-year CUDs at 2.8% followed by bisexual women at 1.4%, bisexual men at 1.1%, and gay men at 0.6%. Also, 0.5% of heterosexual men and 0.2% of heterosexual women reported past-year CUDs. In addition to reporting the highest prevalence of CUDs, lesbian women also had significantly elevated odds of reporting this addiction when compared their heterosexual counterparts (AOR, 11.3; 95% CI 1.7–75.9). The remaining three SM subgroups showed no significant difference in addictions when compared to their heterosexual reference groups. Another study examined lifetime CUDs using NESARC-II data and again concluded that SM women had the highest prevalence.32 We also located two smaller scale prevalence studies that indicated SM males had the highest prevalence of CUD; however, both of these studies had smaller sample sizes and relied on less rigid addiction criteria (i.e., recent marijuana use as a proxy for addiction).50,53

Co-occurrence

No marijuana dependence studies were found examining its comorbidity with other addictions between SM subgroups.

Illicit Drugs

Prevalence

For the purposes of this review, we did not include any prevalence studies that analyzed a specific substance and instead, we examined studies that defined DUDs as an encompassing term. Through an analysis of NESARC-II data, Hatzenbuehler et al.51 found that 11.7% of SMs reported a past-year DUD compared to only 2.3% of individuals belonging to the heterosexual reference group.51 This statistically significant elevation in DUDs was expanded on by Kerridge, who analyzed NESARC-III data to investigate the prevalence of past-year and lifetime DSM-V DUDs among specific SM subgroups.26 Prevalence of past-year DUDs was highest among bisexual women (11.3%) followed by bisexual men (10.3%), lesbian women (7.9%), gay men (7.1%), heterosexual men (4.8%), and heterosexual women (2.7%). When compared to their heterosexual counterparts, both bisexual and lesbian women were significantly more likely to report both past-year and lifetime DUDs. Most notably, bisexual women were found to be 280% more likely to have a lifetime DUD (AOR 3.8, 95% CI 2.64–5.42) while lesbian women were 170% more likely to report a DUD (AOR 2.7, 95% CI 1.82–4.09). Bisexual men were 90% more likely to report a lifetime DUD than their heterosexual counterparts (AOR 1.9, 95% CI 1.18–3.01); however, no significant differences were observed among gay men (AOR 1.4, 95% CI 0.91–2.11). McCabe et al. examined the prevalence of lifetime DUDs using NESARC-II data.52 The results of this study again showed that bisexual women had the highest prevalence of DUDs, indicating that this SM subgroup is at the highest of risk of both past-year and lifetime DUDs.

Co-occurence

No studies were located that examined the co-occurrence of DUDs among SMs and their heterosexual counterparts.

Pathological Gambling

Prevalence

Despite concerted efforts by casinos to market toward specific SM subgroups, there has been limited research on pathological gambling (PG) as a function of SM status.54 While no studies were located that examined PG across all SM subgroups, Grant and Potenza examined the sexual orientation and clinical correlates in a group of 105 men who met the criteria for DSM-IV PG.55 The study showed that 21% (95% CI 13.2%–28.8%) of the men in this sample identified as either gay or bisexual, which is markedly higher than the national estimate of 3.6%.44 Due to the small sample size and absence of control groups, prevalence statistics from this study could not be reported. However, these findings coupled with marketing efforts by casinos to target members of the LGBTQ community suggest that PG prevalence among SM men may be elevated in comparison to their heterosexual counterparts.

Co-occurrence

Using the same sample of 105 men diagnosed with DSM-IV PG, Grant and Potenza also examined the co-occurrence of PG with other forms of addictive behavior.55 This analysis found that 59.1% of SM men with PG reported having a lifetime SUD (including alcohol and drugs). This co-occurrence rate was significantly higher compared to the 31.3% of heterosexual gamblers reporting a lifetime SUD (χ2 = 5.7, p < .05). However, the most significant discrepancy was seen in the co-occurrence of both current and lifetime compulsive sexual behavior: 50.0% of SM men with PG concurrently suffered from compulsive sexual behavior compared to 9.6% of heterosexual men with PG (χ2 = 19.1, p < .001). In addition, 59.1% of SM male gamblers reported lifetime compulsive sexual behavior compared to 16.9% of their heterosexual counterparts (χ2 = 16.2, p < .001). Despite the inherent limitations of a small sample size, this study indicates a significant elevation in the co-occurrence of PG and compulsive sexual behavior specifically among SM men. These findings may be suggestive of an unacknowledged and vulnerable subset of the SM population that should be further investigated.

Overview of Addictions Not Included in the DSM-V

The remaining seven subtypes of addiction, which are primarily behavioral in nature, include sexual compulsivity, food addiction, exercise addiction, compulsive shopping, Internet addiction, love addiction, and work addiction. Although there is a growing body of evidence suggesting that behavioral addictions mirror substance addictions in many respects, there is currently minimal research that explores the prevalence and co-occurrence of these nonsubstance addictions across SM subgroups.57 However, while these addiction subtypes are not explicitly acknowledged in the DSM-V, the DSM-V Task Force expanded upon its predecessor by proposing a new category of Addiction and Related Disorders, which encompasses both SUDs and nonsubstance addictions.18 For example, Internet addiction was listed by the DSM-V as “a condition for further study,” suggesting that future iterations of the DSM may incorporate such behavioral addictions as distinct clinical diagnoses. Despite significant gaps in the literature, there is still compelling evidence to suggest that SM individuals are significantly impacted by these nonsubstance addictions. Here, we highlight behavioral addictions not currently included in the DSM-V as they relate to SM subgroups.

Sexual compulsivity represents a behavioral addiction that is not currently acknowledged in the DSM-V; however, a growing number of studies suggest that SMs, particularly gay and bisexual men, have a markedly elevated likelihood of meeting the criteria for this condition.19,58,59 While no large epidemiological studies have been performed to date, the prevalence rate of sexual compulsivity is estimated to be approximately 3%–6% among the general population.60 A 2010 study screening for impulse control disorders on a private college campus (n = 791) came to a similar conclusion, concluding that 3.7% (95% CI 2.52%–5.15%) of participants met the criteria for sexual compulsivity.61 Another study analyzing 240 university students determined that 17.4% of participants had sexually addictive traits, although rates of sexual compulsivity were not directly reported.62 Kelly et al. conducted a study examining the sexual behaviors of 1,543 predominantly LGB adults in NYC and found that SM men in the sample reported significantly higher mean scores on the Kalichman Sexual Compulsivity Scale (KSCS) than SM women (19.92, SD = 6.92 vs. 17.13, SD = 6.53, p < .05).20 While the rates of sexual compulsivity appear to be elevated among SMs when compared to the general population, it is difficult to draw any significant comparisons between these studies given the differences in study designs. Additional research should assess the prevalence of sexual compulsivity in a sample composed of SM subgroups and a heterosexual control group. Another study analyzing stimulant use among 879 gay and bisexual men found a strong positive correlation between sexual compulsivity scores and stimulant use.21 A limited number of studies have investigated the use of stimulants among SM men to enhance the pleasure of intercourse.63 This phenomenon, which seems to primarily impact SM men, is referred to as “Party n’ Play” or “PnP.”64 The suggested interrelationship between stimulant use and sexual compulsivity, although understudied, may partially explain the elevated rate of co-occurring drug use specifically among SM men with sexual compulsivity. It is also worth noting that there is no universally accepted classification of sexual compulsivity and that current definitions may not be culturally responsive outside of heterosexual communities.

Emerging research also indicates that SMs may be at higher risk for developing food addictions. Rainey et al. analyzed a community sample of 356 U.S. participants and found that that the prevalence of food addiction among SMs (16.9%) was nearly twice as high as the prevalence among heterosexuals (8.9%).22 Although this study examined SMs as a single, nonstratified group, we located additional studies that investigated the prevalence of binge eating disorders (BEDs) and other forms of disordered eating among SM subgroups. It is important to note that while there are theoretical differences between BED and food addiction, studies conclude that the core features of BED seem strongly linked to addiction given the core features of the disorder, which include compulsive eating, excessive consumption despite adverse consequences, and diminished self-control over eating behaviors.65 For this reason, along with the fact that there is no validated tool to operationalize food addiction, BED is empirically accepted as a reasonable and standardized proxy for food addiction. Feldman et al. examined the lifetime prevalence of full syndrome BEDs in a sample of 128 heterosexual adults and 388 SMs stratified by gender into two subgroups.66 SM men reported the highest rates of BEDs at 5.2% followed by SM women (4.6%), heterosexual women (1.6%), and heterosexual men (1.5%). Aside from one study which concluded that past-year BEDs are highest among bisexual women, most studies indicated that disparities in binge eating are more pronounced in SM men than SM women.23,67,68 For instance, in a study of 13,795 young adults, Austin et al. found that gay males were 620% more likely to report past-year binge eating compared to heterosexual men (95% CI 3.7–14.0, p < .0001) while bisexual males were 360% more likely to report past-year binge eating compared their heterosexual counterparts (95% CI 1.2–18.1, p < .05).24 Sexual identity played a less prominent role among female participants. While bisexual females were 120% more likely than heterosexual females to report past-year binge eating (95% CI 1.6–2.9, p < .001), lesbian females did not show a statistically significant difference in risk when compared to their heterosexual counterparts.

We were unable to locate any studies that reported prevalence statistics for exercise addiction among SMs; however, a few studies did suggest elevated levels of compulsive exercise specifically among SM men and explored some of the factors that may contribute to increased rates. Mor et al. analyzed the exercising behaviors of both SM and heterosexual men across five gyms in Tel Aviv, Israel.69 The SM men in this sample were significantly more likely than their heterosexual counterparts to use anabolic steroids and perform intensive anaerobic training, two outcomes that are suggestive of compulsive exercise.70 Yelland et al. examined body dissatisfaction among a group of SM men, heterosexual men, and heterosexual women.71 The results of this study suggested that SM men shared with women a strong desire to be thin, which may put them at risk for disordered eating and excessive exercise to lose weight. However, it was also found that SM men have an additional desire to attain high levels of muscularity, and that they are more likely than heterosexual men to engage in behaviors such as steroid use and excessive weightlifting. Research has also indicated that SM men experience elevated rates of body dysmorphia (a preoccupation with an imagined or minor physical defect that is generally undetected by others), which may be closely linked to increased levels of compulsive exercise. In fact, Peplau et al. analyzed a sample of 2,512 adults and found that nearly twice as many gay men experienced body dissatisfaction compared to heterosexual men (42% vs. 22%).72 There are a multitude of factors that uniquely predispose SM men to body dysmorphia. It is believed that SM men are more likely to experience shame-based trauma during childhood and adolescence, which is thought to play a significant role in how SM men construct their sense of self.73 Objectification theory may also explain this discordance.74 This theory suggests that SM men, like heterosexual women, are faced with increased pressure to achieve an idealized body type in an attempt to attract men as sexual partners and that men, regardless of sexual orientation, emphasize physical appearance more than women when selecting a partner. This emphasis on physical appearance is embedded in many aspects of SM male culture; for instance, it is common for gay men to categorize other gay men by their physical appearance by using terms such as twink, otter, and bear.75 While additional research is needed, it is possible that many of the factors that fuel body dysmorphia among SM men may also perpetuate unhealthy and compulsive exercise behavior.

There has been almost no discussion of compulsive buying disorder as a function of sexual identity. Mattos et al. investigated gender differences among 171 compulsive buyers seeking treatment in São Paulo, Brazil and found that a significantly higher percentage of men in the sample identified as nonheterosexual when compared to the female participants.25 In fact, 33.7% of men meeting the criteria for compulsive buying disorder identified as a SM compared to 3.5% of female compulsive buyers (p < .001). While research indicates that more women than men meet the criteria for compulsive buying disorders, this study suggests that among SMs, men may be a particularly vulnerable subgroup.76,77

While there has been minimal discussion of the prevalence of Internet addiction among SM subgroups, we found a few studies that suggest elevated rates among this community. In a cross-sectional study of 3,262 randomly selected undergraduate students from five ASEAN (Association of Southeast Asian Nations) countries, it was found LGBTQ individuals were 50% more likely than their heterosexual counterparts to have engaged in pathological Internet use (AOR 1.5, 95% CI 1.1–2.1).78 In a review of gay dating app studies, Wu (2018) highlights the rising prevalence of app usage among SM men.79 In particular, he acknowledges that it has been historically challenging for marginalized gay men to access publicly visible gay communities and how this macroscopic landscape of existing social relations has amplified how SM men interface with dating apps in the digital era. Other studies have suggested that dating apps serve a larger purpose for SMs by providing them with a sense of safety and community that their heterosexual counterparts may take for granted.80 These studies suggest that SMs not only use dating apps with higher frequency, but they also engage with these apps differently than heterosexuals. A few recent studies have investigated the impacts of Grindr, a geosocial dating application geared specifically toward SM men.81,82 In a study investigating how Grindr impacts the identity of its users, Jaspal et al. found a recurrence of SM men reporting a self-perceived addiction to the application.14

We also investigated both love addiction and work addiction as functions of sexual identity, but were unable to locate any significant studies that examined these two behavioral addictions across SM subgroups.

DISCUSSION

While there is a strong body of research investigating alcohol, nicotine, and cannabis addiction rates among SMs as a single group, our review indicates that relatively little research has examined and compared the prevalence and co-occurrence of addictions between distinct SM subgroups. By stratifying individuals by gender and sexual attraction, we are able to expand upon the empirically accepted conclusion that SMs as a whole are at increased risk of addiction by pinpointing those individual SM subgroups that are disproportionately susceptible to a particular category of addiction. This allows future research to investigate the unique factors that may predispose, for example, bisexual women to a certain addiction versus the individualized factors that may predispose gay men to another addiction. Establishing a deeper understanding of a subgroup's culture and predispositions has clinically important implications for screening at-risk patients and tailoring treatments.

The most comprehensive information in our analysis related to studies examining the prevalence of substance addictions across different SM groups. There was far less research that addressed other addictions or co-occurring addictions; the studies that did tended to focus on a single SM subgroup. While studies focusing on a single SM subgroup are important and allow for in-depth analyses, there is also a need for broader studies that analyze and compare the pervasiveness of other addictions and co-occurring addictions among distinct SM subgroups. Future researchers may draw attention to vulnerable and previously overlooked subgroups that have yet to be the subject of a more focused and individualized study. Information regarding behavioral addictions was very limited, which reflects the reality that these addictive behaviors are often not accepted as “addictions” by clinicians and researchers. Even the work revealed in several studies that assessed individuals on recent substance use provided limited insight into addictive behavior. While certain aspects of substance use are predictive of addiction, future research should assess participants using DSM-V SUD criteria; this would result in a more comprehensive understanding of these patients and allow for increased comparability between studies.83

Since base rates of certain addictions are higher in cisgender men (e.g., AUDs, NUDs), while others are higher in cisgender women (e.g., food addiction/binge eating), rank order of prevalence data does not always accurately identify the most at-risk groups.31,84,85 Odds ratio statistics help to address the confounding impact of gender on SM subgroups. For instance, according to NESARC-III data, bisexual men had the highest AUD prevalence while lesbian women ranked last among SM subgroups.26 However, OR analysis of the same sample found that bisexual men were no more likely to have a past-year AUD than heterosexual men while lesbian women were 120% more likely to have a past-year AUD compared to heterosexual women (AOR 2.2, 95% CI 1.66–2.91).

We focused primarily on studies that divided SMs into four groups based on gender and orientation. Unfortunately, much of the current literature examining substance abuse among SMs limits their stratification to binary gender. While this is preferable to examining SMs as a single group, this approach ultimately overlooks the major differences that exist between gay/lesbian individuals and bisexual individuals belonging to the same gender. This discrepancy is most pronounced among SM women. For instance, NESARC-III data showed that bisexual women reported the highest prevalence of lifetime DUDs while rates among lesbian women ranked last. Therefore, we strongly suggest that, assuming sufficient sample sizes can be attained, future research avoid combining two distinct populations such as bisexuals and gay/lesbian individuals into a single group. That is, researchers should not overlook the complex array of factors that predispose each of these subgroups to various addictive behaviors, which ultimately reduces the opportunity to develop individualized treatment modalities.

It should also be noted that none of these studies included queer or asexual identities, despite these being identities that are growing in visibility. In fact, there is a significant number of distinct sexual and gender identities (i.e., pansexual, demisexual, questioning, etc.) that remain largely understudied. Likewise, there may be a large number of persons who, despite being attracted to the same gender, do not personally identify with traditional SM categories. For example, looking at NESARC II data,26 one study found that there were a sizeable number of male and female participants who reported being “mostly attracted” to the same or another gender. These participants are perhaps even less likely to self-identify as one of the four most common SM subgroups. Most importantly, both men and women participants who reported being “mostly attracted” to a particular gender had higher prevalence rates of addiction when compared to subgroups that were attracted to one or the other.

These findings contribute to a growing number of recent studies that have investigated the importance of distinguishing sexual identity and attraction in determining an individual's risk for addiction.86 While most research suggests that addiction among SMs is primarily related to external forces such as discrimination, violence, and stigma, it has also been shown that internalized homophobia, or the internalization of negative social views about homosexuality, contributes significantly to minority stress and one's development of self-hatred and poor self-regard.87,88 It can also be argued that individuals who experience same-sex attraction yet identify as heterosexual, despite experiencing significantly less external discrimination compared to those who outwardly associate with a specific SM subgroup, still endure heightened levels of internalized conflict without experiencing the protective effects of belonging to a sociocultural group like the LGBTQ community. While more research is needed, expanding the stratification of SMs to include dimensions other than sexual identity could pinpoint a new group of highly at-risk SMs that have been overlooked by traditional SM categorizations. While future studies should offer more options of SM identities for participants to select, there should also be continued efforts directed at improving the collection of sexual orientation and gender identity information as it relates to general clinical health data. Studies shows that LGBTQ individuals feel anxious when asked about their sexual or gender identity in a clinical setting, which ultimately makes them less likely to seek medical care.89 This aversion to treatment may be even more pronounced among those individuals who associate with an identity that is less known. While LGBTQ patients should have the option to describe their sexual or gender identity in an open-ended manner, healthcare institutions should also formulate educational information that clearly explains the importance of collecting this information from a treatment perspective. These educational materials should be distributed to staff as well as patients, which may help to dampen both the real and perceived discrimination that many LGBTQ individuals face in the healthcare setting.

Through our analysis of the literature, we only identified a few studies that examined the prevalence of co-occurring addictions among SMs. While there were significantly more studies investigating the factors that lead to the co-occurrence of addictions within particular SM subgroups, there is a strong need to quantify these co-occurring addictions through prevalence statistics. In addition to investigating the interconnectedness of these addictions with one another, there is also a need to explore how individual and co-occurring addictions are associated with other negative health outcomes and disease processes. For instance, the elevated rates of inhalant use among men who have receptive anal intercourse with other men may predispose this population to greater STI acquisition (inhalants increase vasodilation of the anal sphincter, which can increase disease transmission).90

Future reviews should be performed in order to assess the prevalence and co-occurrence of SUDs and behavioral addictions among transgender individuals.

Among published research conducted on this topic, many studies are informative, but hampered by small sample sizes, nonrepresentative samples, and other methodological problems.25,55,69 For example, regarding SM men's subgroups, many studies focused specifically on individuals who have HIV/AIDS, which despite being a high-risk group, are not representative of the broader gay and bisexual population.91,92 The authors also recognize that there are a significant number of studies focusing on the addictive behaviors of individual SM groups (i.e., gay men), however, the emphasis of this analysis was to investigate addiction rates across groups and therefore studies analyzing a single group were excluded. By focusing on studies with a heterosexual comparator and/or multiple SM groups, we were able to highlight statistically significant differences in addiction rates that existed between subgroups. This not only provided additional context for prevalence and co-occurrence statistics, but it also allowed for a broader discussion regarding the relationship of SM subgroups to one another in the context of a particular addiction.

As noted in previous systematic reviews on LGBTQ tobacco use, inconsistencies in defining sexual orientation (e.g., differentiating sexual identity from sexual behavior) and analysis issues (e.g., sometimes combining gay and bisexual men into a single group to increase sample size, and sometimes not) make it difficult to compare findings from one study to another.93,94 Additionally, the vast majority of these studies only focused on cisgender individuals; transgender and gender-diverse individuals who are also SMs may have different experiences than their cisgender counterparts.

Transgender and other gender nonbinary identities represent an important yet understudied part of the SM community; this subset of the SM community also faces heightened levels of discrimination in comparison to their cisgender (nontransgender) counterparts.95 It should also be noted that transgender and gender nonbinary individuals are exposed to significantly elevated rates of external discrimination in comparison to traditional SM subgroups, putting them at an even higher risk for addiction.95 While studying transgender and nonbinary identities was beyond the scope of this review, there is an undeniable need for future research aimed at assessing SUDs and behavioral addictions as a function of gender identity.

CONCLUSIONS

It is widely accepted that SMs are at an increased risk for developing various addictions; however, the majority of published studies focus on SMs as a single homogenous group. Our review is unique in that it not only focuses on distinct SM subgroups, but it also emphasizes how these differences in identity ultimately translate into markedly different addictive behaviors. From a treatment perspective, it is essential that future studies acknowledge the diversity of LGBTQ subgroups in order to better screen at-risk patients; this would allow for earlier intervention, more tailored treatments, and reductions in healthcare expenditures. This review also contributes to the literature by assessing both SUDs and behavioral addictions as functions of sexual identity.

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Disclosure

The authors have no relevant financial interest or affiliations with any commercial interests related to the subjects discussed within this article.

Acknowledgments

We acknowledge helpful comments from Jennifer Unger on previous versions of this article.

Funding

Ryan Ruppert was awarded the Keck Summer Research Fellowship, a medical student grant offered by the Keck School of Medicine of USC, which partially funded the initial research of this article.

Figures

Figure 1.

Diagram of study identification and selection process.

sgrlgbtq_1_3_213View in Context

Tables

TABLE 1.
Complete List of Search Terms for Each Addiction
CategorySearch Terms
General“substance use disorder,” “behavioral addiction,” addiction
Alcohol“alcohol dependence,” “alcohol use disorder,” alcoholism
Tobacco“tobacco addiction,” “tobacco use disorder,” “nicotine addiction,” “nicotine dependence”
Marijuana“marijuana abuse,” “marijuana dependence,” “marijuana use disorder,” “cannabis dependence,” “cannabis use disorder”
Illicit Substances“illicit drug abuse,” “drug abuse,” “drug dependence,” “drug addiction,” “substance use disorder”
Gambling“gambling addiction,” “compulsive gambling,” “pathological gambling,” “gambling disorder”
Eating“overeating addiction,” “food addiction,” “eating addiction,” “binge eating disorder,” “overeating dependence,” “eating disorder,” “feeding disorder”
Internet“internet addiction,” “web addiction,” “pathological internet use,” “video game addiction”
Love“love addiction,” “pathological love,” “sexual dependency”
Sex“sex addiction,” “sexual compulsivity”
Exercise“physical activity addiction,” “exercise addiction,” “compulsive exercise”
Work“workaholic,” “workaholism,” “work addiction”
Shopping“shopping addiction,” “compulsive shopping”
View in Context
TABLE 2.
Summary of Behavioral Addiction Studies
AddictionStudy NameSample SizePurpose of StudyMethod of AssessmentMain Outcomes
GamblingGrant (2006)105 adult men who met DSM-IV criteria for PG.To examine the sexual orientation and clinical correlates of men with PGAll subjects met DSM-IV criteria for PG using the clinician-administered Structured Clinical Interview for Pathologic Gambling, a valid and reliable diagnostic instrument. Psychiatric diagnoses substance use disorders were assessed using the Structured Clinical Interview for DSM-IV.Co-occurrence of lifetime compulsive sexual behavior in individuals meeting the criteria for PG: SM men: 59.1%, heterosexual men: 16.9%

Co-occurrence of current compulsive sexual behavior in individuals meeting the criteria for PG: SM men: 50.0%, heterosexual men: 9.6%

SM men differed significantly from their heterosexual counterparts in both lifetime and current co-occurring disorders, p < .001
SexMorgenstern et al.19183 gay and bisexual male individuals living in the New York City areaTo explore the features of NPCSB in a community sample of gay and bisexual men in New York City who reported difficulty controlling their sexual behaviorSubjects were assessed using the DISC, a semi-structured interview created by the study team to assess NPCSB symptoms based on the Structured Clinical Interview for the DSM-IV substance abuse and dependence modulesAmong those SM men meeting the criteria for sexual compulsivity, 23.0% reported a co-occurring DUD while 20.2% reported a co-occurring AUD.
SexParsons et al. (2012)2,361 gay and bisexual men at a series of gay, lesbian, and bisexual community events in New York CityTo evaluate whether sexual compulsivity fits into a syndemic framework, in which sexual compulsivity is one of a number of co-occurring psychosocial health problems that increase HIV risk among MSM.Subjects were assessed using the Sexual Compulsivity Scale (α = 0.90)Among a sample of SM men, 19.3% met the criteria for sexual compulsivity.
SexKelly et al.201,629 adults members of the LGB community at two large LGB community events in New York CityTo assess the prevalence of SC in a community sample of gay and bisexual men and lesbian and bisexual women and to identify differences in sexual practices based on classification as sexually compulsive within gender.Subject were assessed using the KSCS. Individuals with a score of 24 or above on the KSCS were identified as sexually compulsive.Prevalence of current Sexual Compulsivity among LGBs: SM men: 19.92% (SD = 6.92), SM women: 17.13 (SD = 6.53)

Among those meeting the criteria for SC, 39.4% of SM men reported co-occurring drug use while 24.0% of SM women reported co-occurring drug use.
SexCarrico et al.21879 SM men residing in San FranciscoTo examine whether and how psychological factors are associated with engagement in any stimulant use in the broader population of SM men.The six-item Sexual Preoccupation Scale was completed in the mail-in questionnaire to assess cognitive dimensions of sexual compulsivity.Higher sexual compulsivity scores (AOR = 1.46; 95% CI = 1.18–1.80) were independently associated with increased odds of stimulant use.
FoodRainey et al.22356 adult participants (43.3% SM)To test whether food addiction is elevated in SMs (relative to heterosexuals) and if discrimination and self-compassion may be related to food addiction among SMS.Addictive-like eating was measured using YFASPercentage of participants meeting food addiction criteria: SM: 17.5%, heterosexual: 9.9%; p-value < .05
FoodFeldman (2007)524 adult respondents were interviewed in person (128 heterosexual and 388 LGB)To estimate the prevalence of eating disorders in LGB men and women, and examines the association between participation in the gay community and eating disorder prevalence in gay and bisexual men.WMH-CIDI, a fully structured measure used in the National Comorbidity Study and based on DSM-IV criteria for binge eating disorderLifetime prevalence of binge eating disorder: SM men: 5.2%, SM women: 4.6%, heterosexual women: 1.6%, heterosexual men: 1.5%
FoodRussell (2002)122 adult men recruited from the community via advertisement for heterosexual or homosexual men to participate in a study on sexual orientation and eating patterns (64 heterosexual and 58 SM s)To examine whether homosexuality is a specific risk factor for disordered eating in men.Participants completed six questionnaires, one of which was the Eating Attitudes Test-26 (an assessment of disordered eating)ANCOVAs of disordered eating among male participants: Gay male: mean = 11.43 (SD = 8.91), heterosexual male: mean = 5.03 (SD = 4.35)
FoodLaska et al.2333,907 students participating in a Minnesota state-based survey of 40 two- and four-year colleges and universitiesTo assess disparities in weight and weight-related behaviors among college students by sexual orientation and gender.Three survey items were used to assess frequency of unhealthy weight control behaviors during the past year, including using laxatives to control weight, taking diet pills, and inducing vomiting to control weight. One survey item assessed binge eating, and one item assessed overall satisfaction with body image or size over the past 30 daysPrevalence of past-year binge eating: Bisexual women: 30.2%, lesbian women: 23.3%, gay men: 22.1%, bisexual men: 18.7%, heterosexual women: 17.3%, heterosexual men: 11.4%.

SM subgroups were significantly more likely to report past-year binge eating when compared to their heterosexual counterparts.
FoodAustin et al.2413,795 participants between the ages of 12 and 23; information collected by self-administered questionnaires from six waves of data collection.To describe patterns of purging and binge eating from early through late adolescence in female and male youth across a range of sexual orientations.Items assessing weight-control behaviors were adapted from the YRBSS questionnaire.Using heterosexual women as a reference group, bisexual women were 120% (OR: 2.2, 95% CI: 1.6–3.2) more likely to report past-year binge eating disorder while lesbian women were 110% (OR: 2.1, 95% CI: 1.0–4.6) more likely.

Using heterosexual men as a reference group, bisexual men were 360% (OR: 4.6, 95% CI: 1.2–18.1) more likely to report a past-year binge eating disorder while gay men were 620% (OR: 7.2, 95% CI: 3.7–14.0) more likely.
ExerciseMor et al.(2014)379 adult Israeli men (182 SM men and 197 heterosexual men who train in gyms in Tel Aviv)To associate physical activity and sexual behavior among men in gyms in Tel Aviv by sexual orientation, and also to explore factors associating physical activity with psychological attributes and sexual-risk behavior.Participants responded anonymously to 82 questions about their health and sexual behavior, body image attributes, gym exercise pattern, reason for training, knowledge about HIV transmission, and other attitudes and beliefs about sexual-risk behavior.Percentage of participants who reported anabolic steroid use within the previous six months: SM men: 5.5%, heterosexual men: 0%, p-value < .001

Average number of weekly anaerobic training hours: SM men: 5.0, heterosexual men: 3.9, p-value < .001
ExerciseYelland (2003)158 Australian adults (a community sample of 52 homosexual men, as well as two comparison groups comprising 51 heterosexual men and 55 heterosexual women)To explore body dissatisfaction and disordered eating in homosexual menParticipants were asked to indicate whether they ever exercised. Those who responded positively then rated on five-point scales the importance of eight different reasons for exercising (weight control, fitness, mood, health, attractiveness, enjoyment, to build up muscles, body tone)Gay men rated attractiveness (M = 3.59, SD = 1.09) and to build up muscles (M = 3.49, SD = 1.26) as significantly more important reasons to exercise when compared to both heterosexual men (attractiveness M = 2.75, SD = 1.04, t(130) = 3.38, p < .001; muscles M = 2.86, SD = 1.03, t(129) = 2.44, p < .05) and heterosexual women (attractiveness M = 2.92, SD = 1.20, t(130) = 2.79, p < .05; muscles M = 2.96, SD = 1.15, t(129) = 2.13, p < .05).
ShoppingNicoli de Mattos et al.25171 compulsive buyers (20 men and 151 women) voluntarily seeking treatment in São Paulo, BrazilTo examine the potential gender differences in compulsive buying severity, demographics and psychiatric comorbidities in a treatment seeking sample of compulsive buyers.Compulsive buying severity was assessed using the Portuguese adapted version of the CBSMale compulsive buyers (33.7%) were significantly more likely to report their sexual orientation as nonheterosexual than female compulsive buyers (3.5%), p < .001.
InternetPeltzer (2016)3,262 undergraduate university students (Mean age = 20.5 years, SD = 1.6); 5% (153/3,262) of eligible participants considered themselves as LGBT youthsTo examine health indicators in relation to LGBT among university students in five ASEAN countries (Indonesia, Malaysia, Myanmar, Thailand, and Vietnam).Participants completed a questionnaire including health indicators, gender identity, and sexual orientationAmong those who identified as a SM, 46.4% engaged in pathological Internet use.

Using heterosexuals as a reference group, SMs were 50% more likely to engage in pathological Internet use (AOR 1.5, 95% CI 1.1, 2.1).

Abbreviations: Analysis of Covariance; Adjusted Odds Ratio; AUD = alcohol use disorder; CBS = Compulsive Buying Scale; DISC = Diagnostic Interview for Sexual Compulsivity; DUD = drug use disorder; KSCS = Kalichman Sexual Compulsivity Scale; MSM = men who have sex with men; NPCSB = nonparaphilic compulsive sexual behavior; PG = pathological gambling; SM = sexual minority; World Mental Health Composite International Diagnostic Interview; YFAS = Yale Food Addiction Scale; YRBSS = Youth Risk Behavior Surveillance System.

View in Context
TABLE 3.
Summary of Substance Use Disorder Studies
AddictionStudy NameSample SizePurpose of StudyMethod of AssessmentMain Outcomes
AlcoholKerridge et al.2636,309 U.S. adults; 586 gay/lesbians, 566 bisexual men/womenTo present current nationally representative data on the prevalences, sociodemographic correlates and risk of DSM-5 substance use disorders and other psychiatric disorders among SMs relative to heterosexuals, and among SMs by gender.NIAAA AUDAD1S-5 to measure DSM-VAUDs12-month AUD prevalence: Bisexual men: 31.4%, bisexual women: 29.7%, gay men: 26.6%, lesbian women: 24.9%, heterosexual men: 17.3%, heterosexual women: 9.7%

Lifetime AUD prevalence: Bisexual men: 52.6%, bisexual women: 51.7%, gay men: 46.0%, lesbian women: 45.8%, heterosexual men: 35.7%, heterosexual women: 21.8%.

Gay men were 30% more likely to report a past-year AUD compared to heterosexual men (AOR 1.3, 95% CI 1.03–1.77)

Lesbian women were 120% more likely to report a past-year AUD when compared to heterosexual women (AOR 2.2, 95% CI 1.66–2.91).
AlcoholMcCabe et al.3534,653 U.S. adults; approximately 2% of the sample self-identified as lesbian, gay or bisexualTo assess past-year prevalence rates of substance use behaviors and substance dependence across three major dimensions of sexual orientation (identity, attraction, and behavior) in a large national sample of adult women and men in the United States.Alcohol Use Disorder and Associated Disabilities Interview Schedule DSM-IV Version (AUDADIS-IV)Stratified by sexual identity: past-year alcohol dependence: bisexual men: 19.5%, gay men: 16.8%, bisexual women: 15.6%, lesbian women: 13.3%

Stratified by sexual attraction: past-year alcohol dependence: men mostly attracted to males: 11.3%, men only attracted to males: 9.4%, men equally attracted to females and males: 7.6%. men mostly attracted to females: 6.3%, men only attracted to females: 6.2%

Women mostly attracted to females: 15.5%, women mostly attracted to males: 6.8%, women only attracted to females: 5.1%, women equally attracted to males and females: 5.1%, women only attracted to males: 2.4%
Women “mostly attracted to males” were 1.8x as likely to have a past-year AUD when compared to women “only attracted to males” (AOR 1.8, 95% CI 1.3–2.5)

Women “mostly attracted to females” were 4.8 times more likely to have a past-year AUD when compared to women “only attracted to males” (AOR 4.8, 95% CI 1.8–12.8).
AlcoholLee et al.366,899 adult males with AUDs, 176 identified as gay or bisexualTo compare the prevalence of diagnostic co-occurring psychiatric disorders and DUD among SM men with AUD compared with heterosexual males with a lifetime AUD diagnosis.Lifetime substance use disorders were assessed using the AUDADIS-IVAmong SM men with a lifetime AUD, 43.7% (95% CI: 35.3–52.5) reported any lifetime DUD; compared to 28.3% (95% CI: 26.8–29.8) of heterosexual men with a lifetime AUD; p-value < .001

Among SM men with a lifetime AUD, 36.6% (95% CI: 28.5–45.4) reported a lifetime cannabis use disorder; compared to 24.3% (95% CI: 22.9–25.7) of heterosexual men with a lifetime AUD; p-value < .01
AlcoholMereish et al.374,342 adult females with AUDs, 191 identified as lesbian or bisexualTo examine disparities in lifetime co-occurring psychiatric and DUDs among a nationally representative sample of women with lifetime AUDsLifetime substance use disorders were assessed using the AUDADIS-IVAmong SM women with a lifetime AUD, 49.0% (95% CI: 40.4–57.6) reported any lifetime DUD; compared to 26.1% (95% CI: 24.4–27.8) of heterosexual women with a lifetime AUD; p-value < .0001

Among SM women with a lifetime AUD, 39.7% (95% CI: 31.2–48.9) reported a lifetime cannabis use disorder; compared to 20.3% (95% CI: 18.8–21.9) of heterosexual women with a lifetime AUD; p-value < .0001
AlcoholIrwin (2005)198 adult men with a diagnosis of alcohol abuse or dependence in the past 12 months; 145 identified as gay, 53 identified as nongayTo describe the alcohol- and drug-use patterns and alcohol and drug diagnoses in an ethnically and sexually diverse sample of treatment-seeking MSM whose primary diagnosis is either alcohol abuse or alcohol dependenceA semi-structured interview adapted from Composite International Diagnostic Interview was used to assess abuse and dependence of alcohol and of drugs in accordance with the Diagnostic and Statistical Manual–IV (DSM-IV) diagnostic criteria.13.1% of gay men reported stimulant use in the past six months, compared with 1.8% of nongay-identified men (χ2 = 5.37, p < .02)
AlcoholCoulter et al.3312,493 adult participants between 18 and 25 years oldTo estimate sexual orientation differences in alcohol use trajectories during emerging adulthood, and test whether alcohol use trajectories mediate sexual orientation differences in AUDs.Participants meeting the criteria for DSM-IV alcohol abuse or dependence were coded as having a probable AUD, creating a single binary variable.Prevalence of probable AUD: Gay men: 41.4%, bisexual men: 38.9%, mostly heterosexual men: 36.7%, completely heterosexual men (reference group): 26.6%

Prevalence of probable AUD: Mostly heterosexual women: 30.8%, bisexual women: 29.5%, lesbian women: 29.3%, completely heterosexual women (reference group): 14.0%

Using completely heterosexual men as a reference group, gay men were 59% more likely to report an AUD (RR: 1.59, 95% CI: 1.25–2.02) while mostly heterosexual men were 34% more likely to report an AUD (RR: 1.34, 95% CI: 1.10–1.64).

Using completely heterosexual women as a reference group, lesbian women were twice as likely to report an AUD (RR: 2.00, 95% CI: 1.41–2.83), bisexual women were 112% more likely to report an AUD (RR: 2.12, 95% CI: 1.59–2.83), and mostly heterosexual women were 117% more likely to report an AUD (RR: 2.17, 95% CI: 1.91–2.47).
AlcoholGattis et al.3234,653 U.S. adults; approximately 2% of the sample self-identified as lesbian, gay, or bisexualTo examine sexual orientation discordance, a mismatch between self-reported sexual identity and sexual behavior or sexual attraction, by describing the characteristics, substance use disorders, and mental health risks of heterosexual identified individuals who endorsed this pattern of sexual identification, behavior, and attraction.Lifetime substance use disorders were assessed using the AUDADIS-IVPrevalence of lifetime AUDs: Gay men: 59.44%, heterosexual men: 47.89%, heterosexual discordant men: 41.19%; χ2 = 6.25, p-value <. 01

Lesbian women: 58.65%, heterosexual women: 21.64%, heterosexual discordant women: 47.66%; χ2 = 35.57, p-value < .001
AlcoholDrabble et al.317,612 U.S. adults via a national population-based survey of all 50 states of the United States and Washington, DC.To examine the prevalence of abstinence, drinking, heavier drinking, alcohol-related problems, alcohol dependence and help-seeking among homosexual and bisexual women and men compared with heterosexuals.Respondents who reported three or more of the seven criteria in the last 12 months were considered positive for DSM-IV alcohol dependenceCurrent alcohol dependence: Bisexual women: 16.7%, lesbian women: 11.5%, gay men:10.4%, bisexual men: 5.6%, heterosexual men: 5.6%, heterosexual women: 2.3%

Bisexual and lesbian women each had a statistically significant (p-value < .001 for bisexual women, p-value < .01 for lesbian women) increased likelihood of meeting the criteria for current alcohol dependence when compared to their heterosexual female counterparts.
AlcoholGilman et al.348,098 U.S. adults via a nationally representative household surveyTo examine the risk of psychiatric disorders among individuals with same-sex sexual partners.Psychiatric disorders according to DSM-III-R criteria were assessed with a modified version of the Composite International Diagnostic Interview.Past-year alcohol dependence: SM women: 15.3%, SM men: 12.1%, heterosexual men: 11.6%, heterosexual women: 4.1%
NicotineKerridge et al.2636,309 U.S. adults; 586 gay/lesbians, 566 bisexual men/womenTo present current nationally representative data on the prevalences, sociodemographic correlates and risk of DSM-5 substance use disorders and other psychiatric disorders among SMs relative to heterosexuals, and among SMs by gender.NIAAA AUDAD1S-5 to measure DSM-V AUDsPrevalence of past-year NUD: Bisexual men: 40.8%, bisexual women: 36.3%, gay men: 30%, lesbian women: 27.3%, heterosexual men: 23.0%, heterosexual women: 16.4%

Bisexual men were 80% more likely to report a past-year NUD compared to their heterosexual counterparts (AOR: 1.8, 95% CI: 1.13–2.88).

Lesbian women were 120% more likely to report a past-year NUD compared to their heterosexual counterparts (AOR: 2.2, 95% CI: 1.62–3.01), while bisexual women were twice as likely (AOR: 2.0, 95% CI: 1.50–2.79).
NicotineFallin et al.41118,590 U.S. adults through a secondary analysis of the CDC's 2009–2010 National Adult Tobacco SurveyTo examine differences in smoking characteristics (advertising receptivity, age of first cigarette, nondaily smoking, cigarettes per day, nicotine dependence, desire to quit and past quit attempts) among lesbians, gay men, and female and male bisexual adults in the United States.Nicotine dependence was based on the question, “How soon after you wake up do you have your 1st cigarette?”

Current smoking was assessed based on two questions: (1) “Have you smoked at least 100 cigarettes in your entire life?” (choices: yes/no); and (2) “Do you now smoke cigarettes every day some days or not at all.”
Current smoking: Bisexual men: 33.7%, bisexual women: 31.98%, gay men: 25.91%, lesbian women: 22.4%, heterosexual men: 15.88%, heterosexual women: 13.22%

Each SM subgroup had a statistically significant increased likelihood of current smoking compared to their heterosexual counterparts (p < .001).
NicotineConron et al.4467,359 Massachusetts residents who reported sexual identities of heterosexual or straight, gay/lesbian or homosexual, or bisexual in a state-based system of health surveys.To provide estimates of several leading U.S. adult health indicators by sexual orientation identity and gender to fill gaps in the current literature.Self-reported survey assessing if participants were current daily smokersPrevalence of current daily smokers: Bisexual women: 36.9%, bisexual men: 35.4%, gay men: 32.5%, lesbian women: 26.3%, heterosexual men: 20.6%, heterosexual women: 19.4%
NicotinePizacani et al.4585,316 respondents from Oregon and Washington, for 2003–2005, random selection by gender and ageTo explore whether smoking-related knowledge, attitudes, and behaviors also differ between individual SM communities.Current smoking was assessed based on two questions: (1) “Have you smoked at least 100 cigarettes in your entire life?” (choices: yes/no); and (2) “Do you now smoke cigarettes every day some days or not at all.”Prevalence of current smokers: Bisexual men: 35.9% (95% CI: 28.3–44.3), bisexual women: 35.9% (95% CI: 31.3–40.7), gay men: 31.7% (95% CI: 26.8–37.1), lesbian women: 29.5% (95% CI: 25.2–34.2), heterosexual men: 20.3% (95% CI: 19.7–20.7), heterosexual women: 17.3% (95% CI: 16.9–17.8)

Using heterosexual men as a reference group, gay men were 120% (AOR: 2.2, 95% CI: 1.7–2.9) more likely to report current smoking while bisexual men were 90% (AOR: 1.9, 95% CI: 1.4–2.8) more likely.

Using heterosexual women as a reference group, lesbian women were 140% (AOR: 2.4, 95% CI: 1.9–3.0) more likely to report current smoking while bisexual women were 120% more likely (AOR: 2.2, 95% CI: 1.8–2.8).
NicotineCorliss et al. (2013)n = 64,397 high school students across the United States; 6,067 identified as SMsTo examine sexual orientation differences in adolescent smoking and intersections with race/ethnicity, gender, and ageParticipants were asked “Have you ever smoked cigarettes daily, that is, at least one cigarette every day for 30 days.” “During the past 30 days, on how many days did you smoke cigarettes?”Odds ratio of past month smoking when compared to heterosexual counterparts: Lesbian or gay: OR: 3.99, 95% CI: 1.08–14.69

Bisexual male or female: OR: 5.86, 95% CI: 2.76–12.44
NicotineTang et al.4744,606 respondents, 343 self-identified as lesbian; 593 self-identified as gay; and 793 identified themselves as bisexual (511 female and 282 male) via CHIS, a population-based telephone surveyTo compare the cigarette smoking rate of LGB with that of heterosexual individuals using a population-based sample with both male and female adults, and to identify which subsegments of LGB population are particularly burdened by tobacco use.Respondents were asked “Have you smoked at least 100 cigarettes in your entire life?” and “Do you now smoke cigarettes every day, some days, or not at all?”

Current smokers were defined as persons who reported having smoked >100 cigarettes during their lifetimes and who currently smoked every day or on some days.
Prevalence of current smokers: Gay men: 33.2% (95% CI: 27.8–38.7), lesbian women: 25.3% (95% CI: 19.5–31.0), heterosexual men: 21.3% (95% CI: 20.5–22.1), heterosexual women: 14.9% (95% CI: 14.3–15.5)

Prevalence of current smoking among bisexual males and bisexual females was not included; however, it was reported that bisexual females were 108% (OR: 2.08, 95% CI: 1.55–2.79) more likely to report current smoking compared to their heterosexual female counterparts.
NicotineGruskin et al.481,950 LGB adults residing in California;

Data were derived from a 2003–2004 survey of LGB individuals living in California as well as from the 2002 version of the California Tobacco Survey, which gathered data on the state's general population
To conduct a large, population-based study to assess tobacco use in California's LGB population.Current smokers were defined as those who reported having smoked 100 or more cigarettes during their lifetime and who currently smoked every day or on some days.Prevalence of current daily smokers: Bisexual women: 22.6% (95% CI: 15.7–31.6), lesbian women: 22.2% (95% CI: 15.3–31.2), gay men: 19.6% (95% CI: 14.7–25.7), bisexual men: 16.2% (95% CI: 7.2–32.4), heterosexual men: 13.9% (95% CI: 13.5, 14.3), heterosexual women: 9.1% (95% CI: 8.8–9.4).
NicotineBlosnich et al.4993,414 adults randomly selected across ten U.S. statesTo compare health indicators by gender and sexual orientation statuses.Current smokers were defined as those who reported having smoked 100 or more cigarettes during their lifetime and who currently smoked every day or on some days.Prevalence of current daily smokers: Bisexual men: 33.3%, bisexual women: 29.7%, gay men: 22.9%, lesbian women: 19.1%, heterosexual men: 15.8%, heterosexual women: 11.7%

Using heterosexual men as a reference group, gay men were 93% (AOR: 1.93, 95% CI: 1.27–2.93) more likely to report daily smoking, while bisexual men were 92% (AOR: 1.92, 95% CI: 1.04–3.53) more likely.

Using heterosexual women as a reference group, lesbian women were 91% (AOR: 1.91, 95% CI: 1.26–2.91) more likely to report current smoking, while bisexual women were 113% (AOR: 2.13, 95% CI: 1.33–3.42) more likely.
CannabisMcCabe et al.3534,653 U.S. adults; approximately 2% of the sample self-identified as lesbian, gay, or bisexualTo assess past-year prevalence rates of substance use behaviors and substance dependence across three major dimensions of sexual orientation (identity, attraction, and behavior) in a large national sample of adult women and men in the United States.Substance use disorders were assessed using the AUDADIS-IVPast-year prevalence of cannabis dependence: Lesbian women: 5.7%, bisexual women: 3.0%, bisexual men: 1.1%, gay men: 0.6%, heterosexual men: 0.5%, heterosexual women: 0.4%.

Using heterosexual women as a reference group, lesbian women were 11.3 times (AOR: 11.3, 95% CI: 1.7–75.9) more likely to report past-year marijuana dependence.
CannabisGattis et al.3234,653 U.S. adults; approximately 2% of the sample self-identified as lesbian, gay, or bisexualTo examine sexual orientation discordance, a mismatch between self-reported sexual identity and sexual behavior or sexual attraction, by describing the characteristics, substance use disorders, and mental health risks of heterosexual identified individuals who endorsed this pattern of sexual identification, behavior, and attraction.Lifetime substance use disorders were assessed using the AUDADIS-IVPrevalence of lifetime cannabis use disorders: Gay men: 25.38%, heterosexual discordant men: 18.16%, heterosexual men: 13.45%; χ2 = 7.21, p-value < .001

Lesbian women: 28.74%, heterosexual discordant women: 18.34%, heterosexual women: 5.62%; χ2 = 24.73, p-value < .001
CannabisCochran et al.509,888 U.S. adults; 174 SMs (98 men, 96 women) and 9,714 heterosexual (3,922 men, 5,792 women) respondents.To compare patterns of drug use and dependence between homosexually experienced and exclusively heterosexually experienced individuals.Respondents answered questions assessing the presence or absence of six of seven symptoms of drug dependence within in the prior year. Items reflected DSM-IV defining symptoms of drug dependencePast-year cannabis dependence: SM men: 5.7%, SM women: 3.9%, heterosexual men: 2.1%, heterosexual women: 0.9%
CannabisHequembourg (2013)389 U.S. adults in Buffalo, New York; 97 gay men, 87 bisexual men, 98 lesbians, and 107 bisexual women with a mean age of 24.4 (SD = 4.3; range: 18–35) years old.To examine the interrelationships among shame-proneness, guilt-proneness, internalized heterosexism, and problematic substance use among 389 gay, lesbian, and bisexual men and women.Drug dependence was assessed based on five questions from the Diagnostic Interview Schedule concerning lifetime problematic use of each of the specified illicit drugs (e.g., “Have you ever used [club drugs] for 2 weeks or more?”). Response options were 0 = “no” and 1 = “yes.” Participants’ scores indicated drug dependence if they answered “yes” to at least one of the five questions about problematic use, and their scores indicated severe dependence if they answered “yes” to four or five of the questions.Cannabis dependence: Bisexual men: 57.5%, bisexual women: 46.7%, gay men: 44.8%, lesbian women: 25.5%

Severe cannabis dependence: Bisexual men: 20.7%, bisexual women: 20.6%, gay men: 13.5%, lesbian women: 8.0%.
Illicit DrugsHatzenbuehler et al.5134,653 U.S. adults; approximately 2% of the sample self-identified as lesbian, gay, or bisexualTo investigate the modifying effect of state-level policies on the association between lesbian, gay, or bisexual status and the prevalence of psychiatric disorders.Substance use disorders were assessed using the AUDADIS-IVPrevalence of past-year DUD: LGB men and women: 11.7%, heterosexual men and women: 2.3%

Compared to heterosexual participants, LGB men and women were 320% (AOR: 4.21, 95% CI: 2.83–6.25) more likely to meet the criteria for a past-year DUD.
Illicit DrugsKerridge et al.2636,309 U.S. adults; 586 gay/lesbians, 566 bisexual men/womenTo present current nationally representative data on the prevalences, sociodemographic correlates and risk of DSM-5 substance use disorders and other psychiatric disorders among SMs relative to heterosexuals, and among SMs by gender.NIAAA AUDADIS-5 to measure DSM-V AUDsPrevalence of past-year DUD: Bisexual women: 30.8%, bisexual men: 26.5%, gay men: 19.6%, lesbian women: 19.2%, heterosexual men: 12.1%, heterosexual women: 7.0%

Using heterosexual men as a reference group, bisexual men were 90% (AOR: 1.9, 95% CI: 1.18–3.01) more likely to report a past-year DUD.

Using heterosexual women as a reference group, bisexual women were 280% (AOR: 3.8, 95% CI: 2.64–5.42) more likely to report a past-year DUD while lesbian women were 170% (AOR: 2.7, 95% CI: 1.82–4.09) more likely to report one.
Illicit DrugsMcCabe et al.5234,653 adults; approximately 2% of the sample self-identified as lesbian, gay, or bisexualTo examine substance abuse treatment utilization across three dimensions of sexual orientation (identity, attraction, behavior) in a large national sample of adults in the United States.Substance use disorders were assessed using the AUDADIS-IVPrevalence of lifetime DUD: Bisexual women: 40.4%, gay men: 32.7%, bisexual men: 25.4%, lesbian women: 24.5%, heterosexual men: 15.7% heterosexual women: 8.0%.

Using heterosexual women as a reference group, lesbian women were 170% (AOR: 2.7, 95% CI: 1.5–4.7) more likely to report a lifetime DUD, while bisexual women were 290% (AOR: 3.9, 95% CI: 2.5–6.3) more likely.

Using heterosexual men as a reference group, gay men were 160% (AOR: 2.6, 95% CI: 1.7–4.0) more likely to report a lifetime DUD, while bisexual men were 120% (AOR: 2.2, 95% CI: 1.1–4.1) more likely.

Abbreviations: Adjusted Odds Ratio; AUD = alcohol use disorder; AUDADIS-5 = Alcohol Use Disorder and Associated Disabilities Interview Schedule-5; CHIS = California Health Interview Survey; Center for Disease Control and Prevention; The National Institute on Alcohol Abuse and Alcoholism; NUD = nicotine use disorder; SM = sexual minority.

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