Substance use disorders affect more than 20 million individuals in the United States annually, increasing risk for psychiatric disorders, chronic diseases, and disruptions to social, family, and work lives . SUD prevalence peaks during young adulthood , with co-occurrence of multiple SUDs also common during this time period, which increases clinical severity and complicates treatment . Previous research has established that, compared to completely heterosexual and cisgender individuals , sexual and gender minorities engage in greater substance use beginning in adolescence and extending throughout life.Even fewer have examined more serious SUD outcomes by sexual orientation or gender identity or have focused on SUDs during young adulthood . The present study addresses these gaps by examining associations between SGM statuses and past 12-month prevalence of SUDs in a community cohort of U.S. young adults. SGM disparities in SUDs persist because SGMs use substance to cope with SGM-related minority stressors, including self-stigma and interpersonal and structural-level discrimination. Disparities may also be driven by differences in substance use norms within SGM communities . For example, research indicates that sexual minorities perceive greater availability of substances and have more tolerant use norms than do heterosexuals . Additionally, gender minority youth may perceive less risk associated with substance use than cisgender youth .Research has found persistent variation in SUD risk by sex. In the general population,grow tables 4×8 men experience single and co-occurring SUDs at higher levels than women . Among SMs, however, sex differences are typically reduced or even reversed, with greater sexual orientation disparities among adult women compared to men, and especially elevated rates among bisexual women .
Nonetheless, studies have rarely tested whether sex modifies relationships between sexual orientation and SUDs by including interaction terms in statistical models. Prevalence of SUDs tends to peak around age 25 and declines with age . Research examining SUDs among SMs, however, suggests a slower agenormative decline . Rarely have researchers compared sexual orientation or gender identity disparities in SUDs among individuals older than 25 years with those in younger age groups. Knowledge of how the magnitude of sexual orientation and gender identity differences in SUDs vary by birth sex and age can help identify subgroups in need of interventions. This study analyzed data from the longitudinal Growing Up Today Study when participants were aged 20-35 to estimate sexual orientation and gender identity differences in probable SUDs. Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria were used to assess past 12-month nicotine dependence, alcohol abuse/dependence, drug abuse/dependence, any SUD, and co-occurring multiple SUDs . Because research demonstrates sex differences in associations between sexual orientation and substance outcomes , we estimated statistical interactions between 1) sexual orientation and birth sex, and 2) gender identity and birth sex, and present birth-sex-stratified estimates. We hypothesized that SGMs would be more likely than non-SGMs of their same birth sex to meet criteria for SUDs, and that sexual orientation differences would be larger among participants assigned female at birth compared to those assigned male. Additionally, we estimated statistical interactions between 1) sexual orientation and age, and 2) gender identity and age. We hypothesized that sexual orientation and gender identity differences in SUD risk would be larger in older versus younger periods. Among participants meeting criteria for a past 12-month drug use disorder, we examined associations of sexual orientation and gender identity with past 12-month specific drug use.
Data are from two ongoing GUTS cohorts: GUTS1 and GUTS2. In 1996, GUTS1 participants were aged 9-14 at baseline. In 2004, GUTS2 participants were aged 10-15 at baseline.More information about GUTS is available elsewhere . Data collection procedures were approved by Partners Healthcare IRB. The current analysis includes 17,496 observations from 8,701 GUTS1 and 3,727 GUTS2 participants of: wave 2010 and a 2015-2017 GUTS Substance Sub-study . The proportion of participants included in the current analysis was lower among those assigned male compared to those assigned female at birth due to greater attrition among males.Past 12-month nicotine dependence, alcohol abuse/dependence, and drug abuse/dependence were assessed in 2010 and 2015-2017 with questions adapted from the National Survey on Drug Use and Health corresponding to DSM-IV criteria for SUDs . We coded responses as evidencing or not evidencing symptoms of dependence and abuse , classifying participants as having probable substance dependence if they endorsed 3 or more of 7 dependence symptoms and as having probable abuse if they endorsed at least 1 of 4 abuse symptoms. We then created 4 SUD variables: nicotine dependence , alcohol use disorder , drug use disorder , and co-occurring multiple SUDs . GUTS questionnaires cover multiple health-related topics. Thus, to reduce participant burden, questions assessing drug use disorder for marijuana and other drugs were combined into a single set of questions. Although less comprehensive than the assessment of each drug separately, our approach is supported by findings that marijuana and other drug use frequently co-occur, and they have similar impacts on well-being .Analyses were stratified by birth sex . Unadjusted prevalences of past 12-month SUD outcomes were examined for each sexual orientation and gender identity subgroup. We estimated multi-variable associations of SGM statuses with SUDs using generalized estimating equations with exchangeable correlations structure to account for non-independence of sibling clusters and repeated measures among individuals . When exchangeable correlation structure did not yield convergence for three models estimating drug type , we used independence correlation structure. For nicotine dependence, binary logistic regression estimated adjusted odd ratios . For alcohol use disorders, drug use disorders, and co-occurring SUDs, multi-nomial logistic regression estimated AOR.
To test whether birth sex modified relationships between sexual orientation and SUDs and gender identity and SUDs, we included sexual-orientation-bysex and gender-identity-by-sex interaction terms. To test whether age modified relationships between sexual orientation and SUDs and gender identity and SUDs, we included sexual orientation-by-age and gender-identity-by-age interaction terms stratified by birth sex. To estimate sexual orientation and gender identity differences in past 12-month use of specific drugs, we used binary logistic regression. In these analyses,plants racks we combined LGB participants into one category due to small sample sizes. In all models, CH and cisgender participants were referent groups. Corresponding 95% confidence intervals and p-values were estimated. Multi-variable models adjusted for age, race/ethnicity, cohort, region of residence, and birth sex . All analyses were performed with SAS software, version 9.4, with a significance level of 0.05.In numerous instances, birth sex modified relationships with sexual orientation, with sexual-orientation differences larger among participants assigned female compared to assigned male at birth. Differences between MHs and CHs were larger among individuals assigned female for nicotine dependence , alcohol abuse , alcohol dependence , drug dependence , one SUD , and multiple co-occurring SUDs . Although differences between bisexuals and CHs were generally larger among individuals assigned female than assigned male, statistical significance was observed only for drug dependence and marginally for multiple co-occurring SUDs , likely due to low power resulting from the small number of bisexual males. Differences between lesbian and gay participants compared to CHs were also larger among individuals assigned female than assigned male for nicotine dependence , drug abuse , drug dependence , and multiple co-occurring SUDs . Gender-identity-by-birth-sex interactions were not significant . For more information, see Appendix Table 1. Table 3 presents the multi-variable associations of sexual orientation, gender identity, and other covariates with SUDs among participants assigned female at birth. The odds of evidencing each SUD and co-occurring multiple SUDs were greater among all SM groups compared to CHs. Associations between gender identity and SUDs were not statistically significant. Table 4 presents the multi-variable associations of sexual orientation, gender identity, and other covariates with SUDs among participants assigned male at birth. All SM groups had elevated odds for nicotine dependence and one SUD compared to CHs. MHs also had elevated odds of alcohol dependence, drug abuse and dependence, and having 2 or more SUDs. Gay men also evidenced elevated odds for alcohol abuse and dependence, drug dependence, and having 2 or more SUDs compared to CHs. GMs had significantly higher odds of alcohol dependence than their cisgender peers.
Like patterns observed among participants assigned female, associations Table 5 presents the prevalence and multi-variable associations of sexual orientation and gender identity with past 12-month drug use among participants evidencing a drug use disorder, stratified by birth sex. Regardless of sexual orientation and gender identity, marijuana was the most prevalent drug reported. Among participants assigned female, LGBs were more likely than CHs to report using MDMA/ecstasy and LSD/mushrooms and GMs were more likely than their cisgender counterparts to report using LSD/mushrooms. Among those assigned male, LGBs were more likely than CHs to report using methamphetamine and inhalant and GMs were more likely than cisgender peers to report using heroin, amphetamines, inhalants, and non-medical use of prescription painkillers.Our study quantified sexual orientation and gender identity differences in SUD risk during young adulthood, when SUD prevalence in the general U.S. population is high . We examined SUDs based on DSM-IV criteria including nicotine dependence, alcohol abuse and dependence, drug abuse and dependence, and multiple co-occurring SUDs. Aligning with previous literature , we found that SM status was associated with greater odds of past 12-month SUDs among young adults assigned female, and to a lesser extent among those assigned male. Co-occurrence of 2 or more SUDs in the past 12-months was also more common among SMs compared CHs, aligning with previous studies of lifetime SUD co-occurrence . Contrary to our hypothesis, age-related declines in SUD prevalence were largely similar across sexual orientation and gender identity groups. This finding may be due, in part, to our sample age range and age periods compared in analysis . Previous studies have shown differential age-related declines in alcohol problems between SMs and heterosexuals and noted the largest sexual orientation differences in ages 40 or older . An analysis of representative U.S. data showed declines in the prevalence of tobacco and alcohol disorders among SMs between ages 26-35 but increases in prevalence between the mid-30s to mid-40s . We uniquely examined how GM status is related to risk for SUDs. This is an important contribution as studies assessing SUDs by gender identity are limited and typically focused on substance use instead of abuse . In contrast to findings related to sexual orientation, we did not find consistent evidence of greater prevalence of SUDs among GMs after accounting for sexual orientation in statistical models. The only exception is that GMs assigned male evidenced elevated odds for alcohol dependence. This lack of evidence, however, should be interpreted with caution considering small numbers of GM participants in GUTS and previous evidence indicating their disproportionate substance use . Additional studies quantifying associations between gender identity and SUDs are needed.Among the general population, more people assigned male at birth report probable SUDs than do people assigned female at birth . In contrast, we found SMs assigned female generally had similar or higher levels of SUDs compared to SMs assigned male, and sexual-orientation differences were larger in assigned females than assigned males. One reason is that comparisons between SM and CH women will yield relatively large effect sizes because CH women have the lowest levels of SUDs of all groups defined by sexual orientation and birth sex. Beyond this explanation, there is little insight into why SM women are at especially elevated risk, though some have proposed that SM women are at greater risk for minority-specific stressors and mood disorders, resulting in greater risk for SUDs . Among participants with a drug use disorder, we found that some subgroups of SGMs had elevated odds of reporting use of certain drugs compared with CHs and cisgender participants. Studies examining sexual orientation or gender identity differences in drug use among individuals with drug use disorders are rare; however, cross-sectional studies with participants of the NSDUH found that SM adults were significantly more likely than heterosexuals to report past-year marijuana and other drug use . This indicates that SGMs may be more likely to use different substances than non-SGMs, which has implications for screening, intervention, and treatment . The DSM-IV defined separate criteria for substance abuse and dependence, whereas in the updated DSM-5, abuse and dependence are combined into a single SUD diagnosis .