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. Author manuscript; available in PMC: 2022 Aug 1.
Published in final edited form as: Drug Alcohol Depend. 2021 May 21;225:108749. doi: 10.1016/j.drugalcdep.2021.108749

Exploring the relationship between the Alcohol Policy Environment and Nondiscrimination Laws: Implications for Binge Drinking Disparities among LGB Adults in the United States

Naomi Greene a, Renee M Johnson b, Joanne Rosen c, Danielle German a, Joanna E Cohen a
PMCID: PMC8282708  NIHMSID: NIHMS1706852  PMID: 34049096

Abstract

Background:

Alcohol policies reduce population-level binge drinking; however, they may not reduce binge drinking disparities between different populations. We examined the association between the alcohol policy environment and binge drinking among Lesbian, Gay and Bisexual (LGB) and heterosexual adults in the presence and absence of state laws protecting LGB people from discrimination.

Methods:

The 2015–2018 Behavioral Risk Factor Surveillance System (BRFSS) provided information about individual-level binge drinking, sexual identity, and individual-level covariates. The Alcohol Policy Scale (APS) score measures the strength of the alcohol policy environment. Presence of state-level nondiscrimination protections based on sexual orientation came from the Movement Advancement Project. Logistic regression models were used to test whether nondiscrimination statutes modified the association between the alcohol policy environment and binge drinking and whether this interaction differed for LGB and heterosexual adults.

Results:

Among women, a 10 percentage-point increase in APS score was significantly associated with 7% lower odds of binge drinking in states with inclusive nondiscrimination laws (aOR: 0.93 [95% CI: 0.89–0.97; p=0.0003]) but was not associated with binge drinking in states without inclusive laws (aOR: 0.98 [95% CI: 0.93–1.03] p=0.4781). Moreover, binge drinking disparities comparing lesbian/bisexual women with heterosexual women were narrower in states with inclusive nondiscrimination. No significant association was found among men.

Conclusions:

Binge drinking disparities between lesbian and heterosexual women are negligible in states with inclusive laws and strong alcohol policy environments. Inclusive nondiscrimination laws are an indicator of less structural stigma directed at lesbian and bisexual women.

Keywords: alcohol policy environment, Behavioral Risk Factor Surveillance System, binge drinking, bisexual, legal epidemiology, lesbian, structural stigma

Graphical Abstract

graphic file with name nihms-1706852-f0001.jpg

■ States without inclusive laws

◊ States with inclusive laws

NDL denotes associations for states with nondiscrimination laws inclusive of sexual orientation; Error bars represent 95% confidence intervals around the odds ratio estimate

1. Introduction

Binge drinking is a major public health issue that results in individual and societal costs to health and well-being in the United States (Bouchery et al., 2011; Mokdad, 2004; Stahre et al., 2014). A substantial literature documents the higher prevalence of binge drinking and alcohol-related harms among lesbian, gay, and bisexual (LGB) women while evidence regarding the extent of binge drinking by sexual identity among men is more mixed (Drabble et al., 2005; Fish et al., 2018; Gonzales et al., 2016; Gonzales and Henning-Smith, 2017; Medley et al., 2016). These longstanding disparities among LGB adults are posited to result from sexual minority stress in the form of identity concealment, prejudice, discrimination, and violence (Meyer, 2003). Reducing binge drinking disparities among LGB populations is important for reducing binge drinking and alcohol-related harms at the population level and for achieving health equity.

Alcohol control policies reduce population-level binge drinking by controlling when, where, and by whom alcohol can be consumed (Nelson et al., 2013). Evidence shows that specific policies (e.g., increasing alcohol taxes, reducing alcohol outlet density, limiting days/hours of sale, and holding outlets liable for overserving intoxicated customers) are associated with lower rates of binge drinking, alcohol-impaired motor vehicle crashes, interpersonal violence, and liver cirrhosis (Campbell et al., 2009; Elder et al., 2010; Hahn et al., 2010; Middleton et al., 2010; Rammohan et al., 2011). Alcohol control policies likely interact with one another to produce public health benefits, and measuring their combined impact facilitates a better understanding of the alcohol policy environment.

The Alcohol Policy Scale (APS) score is a comprehensive tool for measuring the strength of alcohol policies enacted in a jurisdiction. As is the case for individual policies, a stronger alcohol policy environment (as measured by the APS score) correlate with lower levels of binge drinking among adults and youth accounting for individual demographic (e.g., age, sex, race-ethnicity, income, education) characteristics, state-level characteristics, and geography. (Xuan et al., 2015a, 2015b).

While these universal approaches have the same correlation with binge drinking for LGB and heterosexual populations, they do not appear to lower binge drinking disparities between these groups (Greene et al., 2021). Both lesbian and bisexual women have significantly higher odds of binge drinking compared with heterosexual women even in the presence of stronger alcohol policy environments (Greene et al., 2021). One possible explanation for this phenomenon is that alcohol policy environments influence the economic reasons that people drink, but not the structural factors that underlie binge drinking disparities between LGB and heterosexual populations.

Disparities in the prevalence and severity of mental health and substance use problems among LGB populations are driven by fundamental differences in the way LGB people are treated in society. Previous studies show that the lack of legal protections on the basis of sexual orientation increases psychiatric disorders, mental distress, and alcohol use disorders among LGB people (Hatzenbuehler et al., 2010, 2009; Raifman et al., 2018). Structural stigma is the theoretical framework that describes the mechanisms whereby these fundamental societal differences manifest as differences in health and well-being for the stigmatized group (Hatzenbuehler et al., 2013). Lesbian, gay, bisexual and other sexual minority people become stigmatized through processes that label these groups as ‘other,’ produce negative and harmful stereotypes, and separate these groups from those considered to have a ‘normal’ sexual orientation (Link and Phelan, 2001). This stigmatization is embedded in laws and policies (i.e., structural discrimination) that perpetuate the labelling, stereotyping, and separation and thus continue the stigmatization of these groups (Link and Phelan, 2001).

While the lack of legal protections is associated with worse mental health and substance use outcomes among LGB people, the presence of protections on the basis of sexual orientation is associated with reductions in disparities and improved health outcomes among LGB people (Everett et al., 2016; Hatzenbuehler et al., 2012; Raifman et al., 2017). In a cohort study of lesbian and bisexual women in Chicago, those recruited after the passage of a civil union law had lower baseline prevalence of perceived discrimination, depressive symptoms, and adverse drinking consequences compared with women recruited before the passage of the law (Everett et al., 2016). Most studies examining discrimination and alcohol consumption use interpersonal measures of discrimination (Gilbert and Zemore, 2016). Few studies of disparities in hazardous alcohol use across sexual identity incorporate a structural stigma perspective.

Given what is known about the protective effects of the alcohol policy environment on binge drinking among the general population and the ameliorative effects of legal protections on the basis of sexual orientation, we sought to explore how state-level alcohol policy environments interact with state-level nondiscrimination statutes that include protections on the basis of sexual orientation (i.e., inclusive nondiscrimination statutes) to contribute to disparities in binge drinking between LGB and heterosexual adults in the United States. We hypothesize that 1) stronger alcohol policy environments are linked to lower binge drinking by decreasing the availability, affordability, and accessibility of alcohol products; 2) inclusive nondiscrimination statutes are linked to lower substance use among LGB populations by reducing structural stigma; 3) for LGB men and women, living in states with stronger alcohol policy environments and inclusive nondiscrimination statutes is associated with lower binge drinking prevalence. Therefore, we tested whether inclusive nondiscrimination statutes strengthen the negative association between state-level alcohol policy environments and binge drinking among LGB adults and reduce binge drinking disparities because the combination of these policies address both the economic and social roots of binge drinking and binge drinking disparities. We conducted separate analyses for men and women (based on sex at birth) because of well-documented sex differences in the epidemiology of alcohol use; these differences are particularly salient at the intersection of sex and sexual orientation (Hughes et al., 2016). Like previous work in this area, several individual and state-level covariates have been included in the models to fully account for confounding between the primary exposure (i.e., the alcohol policy environment) and binge drinking.

2. Material and Methods

2.1. Study sample

We pooled data from the 2015–2018 Behavioral Risk Factor Surveillance System (BRFSS). The BRFSS is a repeated cross-sectional survey conducted by the Centers for Disease Control and Prevention used to estimate national and state-level prevalence of health outcomes and behaviors. Eligible individuals include adults 18+ years in the noninstitutionalized civilian population. BRFSS samples both landline and mobile telephone numbers. Through multistage sampling, the BRFSS produces a representative sample of the target population (Centers for Disease Control and Prevention, 2013). Our sample includes the 35 states that used the Sexual Orientation and Gender Identity (SOGI) module between 2015 and 2018, which includes an unweighted sample of 435,921 women and 339,660 men.

2.2. Measures

2.2.1. Primary exposure

The primary exposure in this analysis is the strength of the alcohol policy environment measured using the Alcohol Policy Scale (APS) score. This measure captures both the presence of individual alcohol policies enacted within a state and the degree to which these policies have been implemented. Development of the APS score has been fully explained elsewhere (Naimi et al., 2014; Nelson et al., 2013). Briefly, the scale developers convened a Delphi panel of alcohol policy experts who created a list of idealized alcohol policies (e.g., alcohol taxes) shown to reduce population-level binge drinking. The Delphi panel rated the efficacy of each policy in reducing binge drinking on a scale of 1 (low efficacy) to 5 (high efficacy). Separately, the scale developers created an implementation rating for each policy to represent the degree to which a state fully implemented each alcohol policy. The APS score is created by summing the products of the efficacy rating and implementation rating for all individual alcohol policies enacted in a state within a given year. Higher APS scores reflect stronger alcohol policy environments in which alcohol products may be more difficult to acquire and alcohol-related harms (e.g., drinking and driving) have more severe civil or criminal sanctions. We used APS scores calculated for 2014–2017 so that scores could be lagged by one year in the statistical models.

2.2.2. Primary outcome measure

The primary outcome for this analysis was binge drinking within the past 30 days. The National Institute on Alcohol Abuse and Alcoholism (NIAAA) defines binge drinking as 4+/5+ alcoholic beverages on a single occasion (about 2 hours) for women/men (National Institute on Alcohol Abuse and Alcoholism, 2020). This amount of alcohol in this amount of time causes substantial impairment and, on average, raises a person’s blood alcohol level to 0.08 mg/dL, the legal limit in most US states.

2.2.3. Moderators

Sexual identity and presence of nondiscrimination laws inclusive of sexual orientation were treated as moderators in the association between the alcohol policy environment and binge drinking. Sexual identity is collected in the BRFSS using the optional Sexual Orientation and Gender Identity module. The module asks the question: “Do you consider yourself to be?” with response options: Straight (i.e., heterosexual), Lesbian or Gay, Bisexual, or Something Else. We restricted this analysis to individuals who identified as heterosexual, lesbian or gay, or bisexual.

Information on inclusive statutes was extracted from reports produced by the Movement Advancement Project on the current state of inclusive legislation in employment, housing, and public accommodations in US states between 2015–2018 (Movement Advancement Project, 2019). During this period, states included in this analysis that had inclusive employment nondiscrimination laws also had inclusive housing and public accommodations laws. We used a binary indicator of whether a state’s nondiscrimination laws explicitly include sexual orientation (i.e., inclusive nondiscrimination statutes).

2.2.4. Covariates

Binge drinking prevalence can be affected by both individual and state-level factors. Therefore, we adjusted for several individual-level and state-level covariates to fully account for confounding between the alcohol policy environment and binge drinking. Individual covariates come from the BRFSS and include: age category (i.e.,18–24, 25–34, 35–44, 45–54, 55–64, 65+ years), race-ethnicity (categories included Hispanic/Latino, any race; and Non-Hispanic White, Black, Multi-racial, and Other race), educational attainment (less than high school, high school graduate, some college, college graduate), annual household income (<$15K; $15–24,999; $25–34,999; $35–49,999; $50K plus), and relationship status (married, divorced, widowed, separated, never married, member of unmarried couple).

State-level covariates were chosen a priori based on studies of the association between the alcohol policy environment and binge drinking (Xuan et al., 2015b, 2015a). These included population composition (i.e., proportion in the state who are 21+ years, adult males, Non-Hispanic White adults, and LGB adults), number of law enforcement officers per capita, the number of Catholics per 1,000 population, median household income, proportion of the population living in urban areas, and the state’s Census region (i.e., Northeast, South, Midwest, West). The number of Catholics in the population has been included in other studies because a higher proportion of Catholics in a state is associated with higher binge drinking prevalence (Holt et al., 2006). Law enforcement officers per capita is a proxy for a state’s ability to enforce alcohol policies. The proportion of LGB adults for each state is a proxy for access to LGB community. Each of these variables measures an aspect of a state’s environment that is hypothesized to be associated with both population-level binge drinking and whether a state passes stronger alcohol policies.

State-level covariates came from the 2010 US Census, the American Community Survey, the U.S. Religion Census Religious Congregations and Membership Study, and the Federal Bureau of Investigation Uniform Crime Reporting Statistics (Federal Bureau of Investigation, 2020; Grammich et al., 2018; U.S. Census Bureau, 2019, 2012).

2.3. Statistical analysis

The goal for this analysis was to examine whether the way in which inclusive nondiscrimination laws interact with the alcohol policy environment differs for LGB compared with heterosexual adults. Therefore, we built nested models that included a 2-way interaction between APS score and the binary indicator for the presence of inclusive nondiscrimination laws; 3-way interaction terms between APS score, inclusive nondiscrimination law, and sexual identity; and all other 2-way interactions between these three variables (Jaccard and Turrisi, 2011). We used logistic regression with backward stepwise selection to simultaneously account for confounding and test for effect measure modification. Stepwise selection also produces the most parsimonious model. Interaction terms with alpha > 0.05 were removed and the models re-run with a smaller number of interactions and main effects. In the final step, we removed nonsignificant covariates. For ease of interpretation, we stratified the final models on the variables in these significant interactions. All models were built in SAS 9.4 using PROC SURVEYLOGISTIC to account for the BRFSS complex survey design.

3. Results

3.1. Alcohol policy scores and inclusive nondiscrimination statutes

Among the 35 states included in the sample, 16 states had nondiscrimination statutes that included sexual orientation and 19 states had nondiscrimination statutes that did not include sexual orientation. Among states with inclusive nondiscrimination statutes, APS scores ranged from 43.1 to 69.5, with a mean of 56.7 (±8.18). Among states without inclusive nondiscrimination laws, APS scores ranged from 44.8 to 83.8, with a mean of 61.8 (±10.3) (Table 1). Oklahoma, Tennessee, Pennsylvania, and Florida were outliers in states without inclusive nondiscrimination laws. There was not a statistically significant difference in mean APS score between states with and without inclusive nondiscrimination statutes (p=0.11).

TABLE 1:

Summary statistics for alcohol policy scores among states with and without inclusive nondiscrimination protections, 2014–2017

N Mean (SD) Min Q25 Median Q75 Max
States with inclusive statutes1 16 56.7 (8.18) 43.1 50.5 58.0 63.5 69.5
States without inclusive statutes2 19 61.8 (10.3) 44.8 57.8 59.3 64.7 83.8
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1

California, Colorado, Connecticut, Delaware, Hawaii, Illinois, Iowa, Maryland, Massachusetts, Minnesota, Nevada, New York, Rhode Island, Vermont, Washington, Wisconsin

2

Florida, Georgia, Idaho, Indiana, Kansas, Kentucky, Louisiana, Mississippi, Missouri, Montana, North Carolina, Ohio, Oklahoma, Pennsylvania, South Carolina, Tennessee, Texas, Virginia, West Virginia

3.2. Interactions between sexual identity, alcohol policy scores, and presence of inclusive nondiscrimination statutes among women and men

Among women, the three-way interaction term was not statistically significant in the nested model with main effects, two-way and three-way interactions, and covariates (Table 2: Model 1). The only significant interaction was between presence of inclusive nondiscrimination statutes and bisexual identity (Table 2: Model 3.2). This model was stratified by the presence of inclusive nondiscrimination statutes.

TABLE 2:

Logistic regression interaction effects between alcohol policy score, sexual identity, and presence of nondiscrimination laws associated with binge drinking among women and men, 2015–2018

WOMEN MEN
Model 1b Model 2b Model 3.1b Model 3.2c Model 1b
Terma B p B p B p B p B p
APS score −0.003 0.68 −0.003 0.63 −0.004 0.0040 −0.004 0.0052 −0.006 0.2775
Nondiscrimination law (Yes) −0.236 0.56 −0.146 0.14 −0.158 0.0084 −0.147 0.0125 0.385 0.2744
APS score × Nondiscrimination law (Yes) interaction 0.001 0.83 −0.000 0.90 - NA - NA −0.007 0.2537
Lesbian vs Heterosexual (Ref) 0.234 0.50 0.211 0.57 0.177 0.0004 0.177 0.0004 0.091 0.6474
Bisexual vs Heterosexual (Ref) 0.085 0.69 0.143 0.50 0.228 <.0001 0.229 <.0001 0.238 0.4246
APS score × Lesbian interaction −0.001 0.85 −0.001 0.92 - NA - NA −0.002 0.5649
APS score × Bisexual interaction 0.003 0.47 0.001 0.67 - NA - NA −0.004 0.4395
Nondiscrimination law (Yes) × Lesbian interaction −0.043 0.90 −0.092 0.09 −0.091 0.07 −0.091 0.07 0.518 0.0089
Nondiscrimination law (Yes) × Bisexual interaction −0.228 0.29 −0.074 0.02 −0.078 0.0098 −0.078 0.0098 −0.173 0.5598
APS score × Nondiscrimination law (Yes) × Lesbian interaction −0.001 0.87 - NA - NA - NA −0.008 0.0119
APS score × Nondiscrimination law (Yes) × Bisexual interaction 0.003 0.44 - NA - NA - NA 0.002 0.6223
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a

: The joint test for an effect is a test that all the parameters associated with that effect are zero.

b

: Models adjusted for individual variables (age, race-ethnicity, education level, income level, relationship status) and state-level factors (population age 21+ years; population adult male; population Non-Hispanic white; population lesbian, gay, bisexual; law enforcement officers per capita; median household income; population living in urban areas; Catholics per 1,000 pop; census region)

c

: Model adjusted for individual variables (age, race-ethnicity, education level, income level, relationship status) and significant state level factors (population age 21+ years; population adult male; population Non-Hispanic white; population lesbian, gay, bisexual; Catholics per 1,000 pop; census region)

Among men, the 3-way interaction term between APS score, presence of inclusive nondiscrimination statutes, and sexual identity for gay men was statistically significant in the largest nested model among men (Table 2: Model 1). The 2-way interaction between presence of inclusive nondiscrimination statutes and sexual identity for gay men was statistically significant. Therefore, we stratified this model on both sexual identity and presence of inclusive nondiscrimination statutes.

3.3. Association between alcohol policy score and binge drinking among women stratified by presence of inclusive nondiscrimination statutes

In states with inclusive nondiscrimination statutes, a 10-percentage point higher APS score was associated with a 7% lower odds of individual-level binge drinking (OR: 0.93 [95% CI: 0.89–0.97; p=0.0003]) among women controlling for sexual identity, individual demographic characteristics, and state-level factors (Table 3). The odds of binge drinking were not significantly different comparing lesbian and heterosexual women (OR: 1.19 [95% CI: 0.92–1.54; p=0.1777]). The odds of binge drinking among bisexual women were 1.34 [95% CI: 1.13–1.60; p=0.0008] times that of heterosexual women.

TABLE 3:

Association between alcohol policy score and binge drinking among women stratified by presence of inclusive nondiscrimination statutes, 2015–2018

States without inclusive statutes (n=19) States with inclusive statutes (n=16)
OR 95% CI p-value OR 95% CI p-value
APS (10 units) 0.98 [0.93 – 1.03] 0.4781 0.93 [0.89 – 0.97] 0.0003
Lesbian 1.71 [1.27 – 2.31] 0.0004 1.19 [0.92 – 1.54] 0.1777
Bisexual 1.84 [1.55 – 2.18] <.0001 1.34 [1.13 – 1.60] 0.0008
Heterosexual Ref Ref Ref Ref Ref Ref
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Adjusted for: age, race, education, income, marital status, population 21+, population male, population white, percent LGB, Catholic rate, region

In states without inclusive nondiscrimination statutes, there was not a significant association (OR: 0.98 [95% CI: 0.93–1.03] p=0.4781) between APS score and individual-level binge drinking controlling for individual demographic characteristics and state-level factors. In these states, lesbian and bisexual women were more likely to engage in binge drinking. Lesbian women had 1.71 [95% CI: 1.27–2.31; p=0.0004] times the odds of binge drinking compared to heterosexual women. Bisexual women had 1.84 [95% CI: 1.55–2.18; p <.0001] times the odds of binge drinking compared to heterosexual women.

3.3. Association between alcohol policy score and binge drinking among men stratified by presence of inclusive nondiscrimination statutes and sexual identity

After stratifying on the presence of inclusive nondiscrimination statutes and sexual identity, we did not find a significant association between APS score and individual-level binge drinking for heterosexual, gay, or bisexual men living in states with or without inclusive nondiscrimination statutes (Table 4). Among heterosexual men, the association between APS score and binge drinking was similar in states with versus without inclusive nondiscrimination statutes (OR: 1.00 [95% CI: 0.97–1.05] vs OR: 0.99 [95% CI: 0.95–1.03]) controlling for all individual and state-level factors. Among gay men, the association between APS score and binge drinking was also similar in states with versus without inclusive nondiscrimination statutes (OR: 0.92 [95% CI: 0.71–1.12] vs OR: 0.85 [95% CI: 0.64–1.12]). However, among bisexual men, the association between APS score and binge drinking was in opposite directions, but not statistically significant. In states with inclusive nondiscrimination statutes, the association between APS score and binge drinking was negative (OR: 0.95 [95% CI: 0.68–1.32]) among bisexual men; in states without inclusive nondiscrimination statutes, the association between APS score and binge drinking was positive (OR: 1.08 [95% CI: 0.76–1.53]) among bisexual men.

TABLE 4:

Association between alcohol policy score and binge drinking stratified by presence of nondiscrimination law and sexual identity among men, 2015–2018

States with inclusive statutesa
Heterosexual Gay Bisexual
ORb 95% CI p ORb 95% CI p ORb 95% CI p
APS score (10 units) 1.00 [0.97 – 1.05] 0.72 0.92 [0.71 – 1.12] 0.54 0.95 [0.68 – 1.32] 0.74
States without inclusive statutesa
Heterosexual Gay Bisexual
ORb 95% CI p ORb 95% CI p ORb 95% CI p
APS score (10 units) 0.99 [0.95 – 1.03] 0.56 0.85 [0.64 – 1.12] 0.25 1.08 [0.76 – 1.53] 0.69
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a

Model adjusted for individual variables (age, race-ethnicity, education level, income level, relationship status) and state-level factors (population age 21+ years; population adult male; population Non-Hispanic white; population lesbian, gay, bisexual; law enforcement officers per capita; median household income; population living in urban areas; Catholics per 1,000 pop; census region)

b

Odds ratio

4. Discussion

Our study examined how the association between the strength of the alcohol policy environment and binge drinking disparities by sexual identity differ by the presence of nondiscrimination laws inclusive of sexual orientation. Leveraging the BRFSS, we used data from men and women in 35 US states. We did not observe any associations between the alcohol policy environment and binge drinking among men regardless of whether they lived in states with or without inclusive nondiscrimination statutes. Among women, stronger alcohol policy environments were associated with lower binge drinking prevalence in states with inclusive statutes. There was no difference in binge drinking between lesbian and heterosexual women in states with inclusive statutes. Binge drinking disparities between bisexual and heterosexual women were lower in states with inclusive statutes compared to states without inclusive statutes.

Although our primary analyses addressed any binge drinking, we explored high-frequency binge drinking (i.e., 5 or more occasions of binge drinking) to see if the policy landscape had a stronger association for individuals with more problematic drinking (Supplemental Tables 1 & 2). Among women, there was no association between the alcohol policy environment and high-frequency binge drinking in states with and without nondiscrimination statutes. Findings for men did not suggest any links between policy and high-frequency binge drinking. Given documented differences in high-intensity binge drinking by sexual orientation (Fish, 2019), future studies may consider examining whether the strength of the alcohol policy environment is associated with high-frequency binge drinking and whether this association differs across sexual identity and presence of inclusive statutes.

Previous studies have shown that stronger alcohol policy environments are associated with reduced odds of binge drinking among women, men, and the general population (Xuan et al., 2015a); however, they were unclear as to whether stronger alcohol policy environments had the same effect for LGB subgroups or whether they could reduce binge drinking disparities. Our study expands what is known by exploring how the strength of the alcohol policy environment is associated with binge drinking disparities in the presence of other public policies. Our findings suggest that stronger alcohol policy environments are linked with lower binge drinking disparities between LGB and heterosexual adults in the presence of inclusive nondiscrimination protections because 1) inclusive nondiscrimination statutes are an indicator of lower structural discrimination against LGB people; 2) the combination of strong alcohol policies and nondiscrimination laws correlate with the economic and social factors that underpin binge drinking and binge drinking disparities across sexual identity.

Similar to previous studies, this study found a significantly higher odds of binge drinking for bisexual women compared with heterosexual women even in states with inclusive nondiscrimination statutes. Negative attitudes towards bisexual people are held by both lesbian/gay and heterosexual people, though these attitudes are less prevalent among lesbian and gay individuals (Friedman et al., 2014). In a qualitative study, young bisexual women reported challenges at the macro, meso, and micro-levels (Flanders et al., 2015). These challenges included finding inclusive community, individuals denying the reality of their sexual orientation, and internalizing stereotypes about bisexual people (Flanders et al., 2015). At least one study has shown that greater involvement in the LGBT community is associated with increased problematic alcohol use among bisexual women, but not lesbian women and this association is mediated by experiences of discrimination (Feinstein et al., 2017). Thus, it is important to look to other public policies at the macro and meso levels as additional levers for reducing population-level binge drinking.

Previous work has hypothesized several social and cultural differences at the intersection of sexual identity and gender that can help contextualize the significant associations found for women but not men. First, increases in hazardous alcohol use in the United States has been driven by increased consumption among women rather than men (Dawson et al., 2015). Second, Hughes et al. propose that the social construction of gender and the differences in expected social roles for women and men are linked with differences in drinking behavior between women and men (Hughes et al., 2016). Excessive alcohol use is constructed as a masculine behavior while temperance is a feminine behavior, partially due to women’s expected roles as wives and mothers (Hughes et al., 2016). However, sexual minority people may eschew these expected gender roles while discrimination and stigma hinder the choices that sexual minority people can make regarding creation of families (Hughes et al., 2016). While an analysis of social and cultural factors is beyond the scope of this paper, it is critical to acknowledge structural factors outside of public policies that influence individual alcohol use.

This study contributes to the growing literature on the impact of public policy on the health and well-being of LGB people in two important ways (Everett et al., 2016; Hatzenbuehler et al., 2010, 2009; Raifman et al., 2018). First, our study brings a structural perspective to the examination of binge drinking disparities. As previously discussed, the epidemiology of binge drinking by sexual identity has revealed stark differences between LGB and heterosexual people, particularly among women (Drabble et al., 2005; Drabble and Trocki, 2005; Fish, 2019; Fish et al., 2018; Gonzales et al., 2016; Gonzales and Henning-Smith, 2017; Hughes et al., 2016). In general, women are less likely to binge drink than men. However, lesbian, bisexual, and other sexual minority women are more likely to binge drink than heterosexual women whereas gay, bisexual, and other sexual minority men binge drink at the same or only slightly more than heterosexual men. Studies examining the underlying causes for these differences have relied on measuring interpersonal experiences of discrimination, homophobia, and other minority stressors (Gilbert and Zemore, 2016; Wilson et al., 2016; Wray et al., 2016). Importantly, structural stigma pervades every part of society and can have negative effects on health outcomes even if individuals do not experience personally-mediated discrimination or homophobia (Hatzenbuehler et al., 2013). Our study reveals how public policy contributes to these documented disparities even in places where the availability, accessibility, and affordability of alcohol is low. Therefore, it is not only important to understand the role of individual, interpersonal, and community-level exposures on binge drinking disparities, but also policy-level exposures. As more US states continue to collect information about sexual orientation and gender identity, future research should continue to examine how structural factors contribute to health disparities for sexual and gender minority populations.

Our study also reveals the importance of taking a health equity approach when examining how public policies impact population-level binge drinking and binge drinking disparities. Few studies examining the effect of alcohol policy on binge drinking and alcohol-related harms include a health equity approach (Roche et al., 2015). Yet, crafting public policy with health equity in mind is critical for improving population health (Pollack Porter et al., 2018). Alcohol policies included in the APS score such as taxes and state monopolies reduce excessive alcohol consumption through economic forces. However, these polies may not account for other reasons (e.g., cultural) that people drink.

4.1. Strengths and limitations

Our study has several strengths and limitations to consider. First, the study was guided by a structural stigma theoretical framework to place binge drinking in a larger population-level context. Second, the measure used to capture the alcohol policy environment accounts for all the alcohol laws enacted at the state level as well as the degree of implementation of these laws. Moreover, lagging the alcohol policy scale score reduces the possibility of reverse causation in which stricter policies are enacted in states with lower binge drinking prevalence because they face fewer political challenges. Finally, our models adjust for several individual and state-level factors to rule out alternative explanations for the association between the alcohol policy environment, nondiscrimination statutes, and binge drinking disparities.

However, the findings must be carefully considered in the context of the following limitations. The BRFSS underestimates binge drinking prevalence which may bias these results towards the null (Nelson et al., 2010). The SOGI module was used in 35 of the 50 US states during the period and some states used the module in more years than others. While our results are not representative of the US population, they are representative of the target populations of the included states due to the sampling design. Exploratory analyses showed no association between the presence of inclusive nondiscrimination laws and a state’s use of the SOGI module.

Government surveys may undercount sexual minority populations (Ferlatte et al., 2017). Discomfort with disclosing sexual identity on a government administered survey may lead to misclassification of sexual minority people. This misclassification may be greater in states that offer no protection against discrimination on the basis of sexual orientation which could bias these results.

These results may not be applicable to some sexual and gender minority groups. The BRFSS collects only sexual identity; however, alcohol use also varies across sexual attraction and behavior (Fish, 2019). More research is also needed on the link between public policies and alcohol use among transgender and gender diverse populations. Future research should examine hazardous alcohol use patterns by gender identity across facets of sexual orientation and how public policies are associated with these patterns.

4.2. Conclusions

The association between the alcohol policy environment and binge drinking disparities differs in states with inclusive nondiscrimination laws for US women. These laws are a signal of less structural discrimination targeted at sexual minority groups and work in tandem to lower binge drinking disparities between sexual minority and heterosexual women. Future studies should continue to interrogate which laws might be helpful for reducing binge drinking among men. These findings not only provide clues to a structural source of binge drinking disparities, but also possible avenues for advocacy in reducing these disparities and improving the overall health and well-being of LGB women in the United States. Examining public policy may reveal important information about the roots of binge drinking disparities among LGB populations and aid in developing interventions.

Supplementary Material

Supp.tables 1&2

Highlights.

  • We evaluate links between alcohol policy, legal protections, and binge drinking.

  • Overall for women, stronger alcohol policy is associated with lower binge drinking.

  • This association is significant in states with legal protections for LGB people.

  • LGB binge drinking disparities are lower in states with these legal protections.

Acknowledgements

The authors would like to thank Dr. Tim Naimi, Jason Blanchette, and Dr. Ziming Xuan at Boston University for the APS score data.

Funding:

Naomi Greene was supported by NCI National Research Service Award T32 CA009314 and the Drug Dependence Epidemiology Training Program funded by the National Institute on Drug Abuse, National Institutes of Health grant number T32DA007292.

Role of funding source

The authors are solely responsible for the conception, design, and findings presented.

Footnotes

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Conflict of Interest

The authors have no conflicts of interest to disclose.

Declaration of Interest: The authors have no financial interests to disclose.

References

  1. Bouchery EE, Harwood HJ, Sacks JJ, Simon CJ, Brewer RD, 2011. Economic costs of excessive alcohol consumption in the U.S., 2006. Am. J. Prev. Med 41, 516–524. 10.1016/j.amepre.2011.06.045 [DOI] [PubMed] [Google Scholar]
  2. Campbell CA, Hahn RA, Elder R, Brewer R, Chattopadhyay S, Fielding J, Naimi TS, Toomey T, Lawrence B, Middleton JC, 2009. The effectiveness of limiting alcohol outlet density as a means of reducing excessive alcohol consumption and alcohol-related harms. Am. J. Prev. Med 37, 556–569. 10.1016/j.amepre.2009.09.028 [DOI] [PubMed] [Google Scholar]
  3. Centers for Disease Control and Prevention, 2013. BRFSS Data User Guide [WWW Document]. URL https://www.cdc.gov/brfss/data_documentation/pdf/UserguideJune2013.pdf (accessed 9.14.20).
  4. Dawson DA, Goldstein RB, Saha TD, Grant BF, 2015. Changes in alcohol consumption: United States, 2001–2002 to 2012–2013. Drug Alcohol Depend 148, 56–61. 10.1016/j.drugalcdep.2014.12.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Drabble L, Midanik LT, Trocki K, 2005. Reports of alcohol consumption and alcohol-related problems among homosexual, bisexual and heterosexual respondents: results from the 2000 National Alcohol Survey. J. Stud. Alcohol 66, 111–120. [DOI] [PubMed] [Google Scholar]
  6. Drabble L, Trocki K, 2005. Alcohol consumption, alcohol-related problems, and other substance use among lesbian and bisexual women. J. Lesbian Stud 9, 19–30. 10.1300/J155v09n03_03 [DOI] [PubMed] [Google Scholar]
  7. Elder RW, Lawrence B, Ferguson A, Naimi TS, Brewer RD, Chattopadhyay SK, Toomey TL, Fielding JE, 2010. The effectiveness of tax policy interventions for reducing excessive alcohol consumption and related harms. Am. J. Prev. Med 38, 217–229. 10.1016/j.amepre.2009.11.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Everett BG, Hatzenbuehler ML, Hughes TL, 2016. The impact of civil union legislation on minority stress, depression, and hazardous drinking in a diverse sample of sexual-minority women: A quasi-natural experiment. Soc. Sci. Med 169, 180–190. 10.1016/j.socscimed.2016.09.036 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Federal Bureau of Investigation, 2020. Uniform Crime Reporting (UCR) [WWW Document]. URL https://ucr.fbi.gov/crime-in-the-u.s (accessed 9.10.20).
  10. Feinstein BA, Dyar C, London B, 2017. Are outness and community involvement risk or protective factors for alcohol and drug abuse among sexual minority women? Arch. Sex. Behav 46, 1411–1423. 10.1007/s10508-016-0790-7 [DOI] [PubMed] [Google Scholar]
  11. Ferlatte O, Hottes TS, Trussler T, Marchand R, 2017. Disclosure of sexual orienation by gay and bisexual men in government-administered probability surveys. LGBT Health 4, 68–71. 10.1089/lgbt.2016.0037 [DOI] [PubMed] [Google Scholar]
  12. Fish JN, 2019. Sexual orientation related disparities in high-intensity binge drinking: findings from a nationally representative sample. LGBT Health 6, 242–249. 10.1089/lgbt.2018.0244 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Fish JN, Hughes TL, Russell ST, 2018. Sexual identity differences in high-intensity binge drinking: findings from a US national sample. Addiction 113, 1–10. 10.1111/add.14041 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Flanders CE, Dobinson C, Logie C, 2015. “I’m never really my full self”: young bisexual women’s perceptions of their mental health. J. Bisex. 15, 454–480. 10.1080/15299716.2015.1079288 [DOI] [Google Scholar]
  15. Friedman MR, Dodge B, Schick V, Herbenick D, Hubach RD, Bowling J, Goncalves G, Krier S, Reece M, 2014. From bias to bisexual health disparities: attitudes toward bisexual men and women in the United States. LGBT Health 1, 309–318. 10.1089/lgbt.2014.0005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Gilbert PA, Zemore SE, 2016. Discrimination and drinking: A systematic review of the evidence. Soc. Sci. Med 161, 178–194. 10.1016/j.socscimed.2016.06.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Gonzales G, Henning-Smith C, 2017. Health disparities by sexual orientation: results and implications from the Behavioral Risk Factor Surveillance System. J. Community Health 42, 1–10. 10.1007/s10900-017-0366-z [DOI] [PubMed] [Google Scholar]
  18. Gonzales G, Przedworski J, Henning-Smith C, 2016. Comparison of health and health risk factors between lesbian, gay, and bisexual adults and heterosexual adults in the United States. JAMA Intern. Med 176, 1344. 10.1001/jamainternmed.2016.3432 [DOI] [PubMed] [Google Scholar]
  19. Grammich C, Hadaway K, Houseal R, Jones DE Krindatch A, Stanley R, Taylor RH, 2018. U.S. Religion Census Religious Congregations and Membership Study, 2010 (State File). 10.17605/OSF.IO/X8D69 [DOI]
  20. Greene N, Johnson RM, German D, Rosen J, Cohen JE, 2021. State-level alcohol enviornments and sexual identity disparities in binge drinking in the Behavioral Risk Factor Surveillance System. LGBT Health. 10.1089/lgbt.2020.0182 [DOI] [PMC free article] [PubMed]
  21. Hahn RA, Kuzara JL, Elder R, Brewer R, Chattopadhyay S, Fielding J, Naimi TS, Toomey T, Middleton JC, Lawrence B, 2010. Effectiveness of policies restricting hours of alcohol sales in preventing excessive alcohol consumption and related harms. Am. J. Prev. Med 39, 590–604. 10.1016/j.amepre.2010.09.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Hatzenbuehler ML, Keyes KM, Hasin DS, 2009. State-level policies and psychiatric morbidity in lesbian, gay, and bisexual populations. Am. J. Public Health 99, 2275–2281. 10.2105/AJPH.2008.153510 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Hatzenbuehler ML, McLaughlin KA, Keyes KM, Hasin DS, 2010. The impact of institutional discrimination on psychiatric disorders in lesbian, gay, and bisexual populations: a prospective study. Am. J. Public Health 100, 452–459. 10.2105/AJPH.2009.168815 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Hatzenbuehler ML, O’Cleirigh C, Grasso C, Mayer K, Safren S, Bradford J, 2012. Effect of same-sex marriage laws on health care use and expenditures in sexual minority men: a quasi-natural experiment. Am. J. Public Health 102, 285–291. 10.2105/AJPH.2011.300382 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Hatzenbuehler ML, Phelan JC, Link BG, 2013. Stigma as a fundamental cause of population health inequalities. Am. J. Public Health 103, 813–821. 10.2105/AJPH.2012.301069 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Hughes TL, Wilsnack SC, Kantor LW, 2016. The influence of gender and sexual orientation on alcohol use and alcohol-related problems: toward a global perspective. Alcohol Res. Curr. Rev 38, 121–132. [PMC free article] [PubMed] [Google Scholar]
  27. Jaccard J, Turrisi R, 2011. Three-Way Interactions, in: Interaction Effects in Multiple Regression SAGE Publications, Inc, Thousand Oaks, pp. 44–60. 10.4135/9781412984522 [DOI] [Google Scholar]
  28. Link BG, Phelan JC, 2001. Conceptualizing stigma. Annu. Rev. Sociol 27, 363–385. 10.1146/annurev.soc.27.1.363 [DOI] [Google Scholar]
  29. Medley G, Lipari, Rachel N, Bose J, Cribb DS, Kroutil LA, Hedden SL, McHenry G, Lipari NR, Bose J, Cribb DS, Kroutil LA, McHenry G, 2016. Sexual orientation and estimates of adult substance use and mental health: Results from the 2015 National Survey on Drug Use and Health. NSDUH Data Rev 10. [Google Scholar]
  30. Meyer IH, 2003. Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: Conceptual issues and research evidence. Psychol. Bull 129, 674–697. 10.1037/0033-2909.129.5.674 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Middleton JC, Hahn RA, Kuzara JL, Elder R, Brewer R, Chattopadhyay S, Fielding J, Naimi TS, Toomey T, Lawrence B, 2010. Effectiveness of policies maintaining or restricting days of alcohol sales on excessive alcohol consumption and related harms. Am. J. Prev. Med 39, 575–589. 10.1016/j.amepre.2010.09.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Mokdad AH, 2004. Actual causes of death in the United States, 2000. JAMA 291, 1238. 10.1001/jama.291.10.1238 [DOI] [PubMed] [Google Scholar]
  33. Naimi TS, Blanchette J, Nelson TF, Nguyen T, Oussayef N, Heeren TC, Gruenewald P, Mosher J, Xuan Z, 2014. A new scale of the U.S. alcohol policy environment and its relationship to binge drinking. Am. J. Prev. Med 46, 10–16. 10.1016/j.amepre.2013.07.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. National Institute on Alcohol Abuse and Alcoholism, 2020. Drinking levels defined [WWW Document]. URL https://www.niaaa.nih.gov/alcohol-health/overview-alcohol-consumption/moderate-binge-drinking (accessed 9.14.20).
  35. Nelson DE, Naimi TS, Brewer RD, Roeber J, 2010. US state alcohol sales compared to survey data, 1993–2006. Addiction 105, 1589–1596. 10.1111/j.1360-0443.2010.03007.x [DOI] [PubMed] [Google Scholar]
  36. Nelson TF, Xuan Z, Babor TF, Brewer RD, Chaloupka FJ, Gruenewald PJ, Holder H, Klitzner M, Mosher JF, Ramirez RL, Reynolds R, Toomey TL, Churchill V, Naimi TS, 2013. Efficacy and the strength of evidence of U.S. alcohol control policies. Am. J. Prev. Med 45, 19–28. 10.1016/j.amepre.2013.03.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Pollack Porter KM, Rutkow L, McGinty EE, 2018. The importance of policy change for addressing public health problems. Public Health Rep 133, 9S–14S. 10.1177/0033354918788880 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Raifman J, Moscoe E, Austin SB, Hatzenbuehler ML, Galea S, 2018. Association of state laws permitting denial of services to same-sex couples with mental distress in sexual minority adults: a difference-in-difference-in-differences analysis. JAMA Psychiatry 75, 671–677. 10.1001/jamapsychiatry.2018.0757 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Raifman J, Moscoe E, Austin SB, McConnell M, 2017. Difference-in-differences analysis of the association between state same-sex marriage policies and adolescent suicide attempts. JAMA Pediatr. 171, 350–356. 10.1001/jamapediatrics.2016.4529 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Rammohan V, Hahn RA, Elder R, Brewer R, Fielding J, Naimi TS, Toomey TL, Chattopadhyay SK, Zometa C, 2011. Effects of dram shop liability and enhanced overservice law enforcement initiatives on excessive alcohol consumption and related harms. Am. J. Prev. Med 41, 334–343. 10.1016/j.amepre.2011.06.027 [DOI] [PubMed] [Google Scholar]
  41. Roche A, Kostadinov V, Fischer J, Nicholas R, O’Rourke K, Pidd K, Trifonoff A, 2015. Addressing inequities in alcohol consumption and related harms. Health Promot. Int 30, ii20–ii35. 10.1093/heapro/dav030 [DOI] [PubMed] [Google Scholar]
  42. Stahre M, Roeber J, Kanny D, Brewer RD, Zhang X, 2014. Contribution of excessive alcohol consumption to deaths and years of potential life lost in the United States. Prev. Chronic Dis 11, 130–293. 10.5888/pcd11.130293 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. U.S. Census Bureau, 2019. 2012–2016 American Community Survey 5-Year Estimates [WWW Document] URL https://www.census.gov/programs-surveys/acs/technical-documentation/table-and-geography-changes/2016/5-year.html (accessed 9.10.20).
  44. U.S. Census Bureau, 2012. 2010 Census Summary File — Technical Documentation [WWW Document]. URL https://www.census.gov/prod/cen2010/doc/sf1.pdf (accessed 9.14.20).
  45. Wilson SM, Gilmore AK, Rhew IC, Hodge KA, Kaysen DL, 2016. Minority stress is longitudinally associated with alcohol-related problems among sexual minority women. Addict. Behav 61, 80–83. 10.1016/j.addbeh.2016.05.017 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Wray TB, Pantalone DW, Kahler CW, Monti PM, Mayer KH, 2016. The role of discrimination in alcohol-related problems in samples of heavy drinking HIV-negative and positive men who have sex with men (MSM). Drug Alcohol Depend 166, 226–234. 10.1016/j.drugalcdep.2016.07.017 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Xuan Z, Blanchette J, Nelson TF, Heeren T, Oussayef N, Naimi TS, 2015a. The alcohol policy environment and policy subgroups as predictors of binge drinking measures among US adults. Am. J. Public Health 105, 816–822. 10.2105/AJPH.2014.302112 [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Xuan Z, Blanchette JG, Nelson TF, Nguyen TH, Hadland SE, Oussayef NL, Heeren TC, Naimi TS, 2015b. Youth drinking in the United States: relationships with alcohol polices and adult drinking. Pediatrics 136, 18–27. 10.1542/peds.2015-0537 [DOI] [PMC free article] [PubMed] [Google Scholar]

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