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. 2020 Dec 21;56(4):500–509. doi: 10.1093/alcalc/agaa130

Support for Alcohol Policies in Marginalized Populations

Pamela J Trangenstein 1,✉, Nina Mulia 2, Camillia K Lui 2, Katherine J Karriker-Jaffe 2, Thomas K Greenfield 2, Rhonda Jones-Webb 3
PMCID: PMC8243274  PMID: 33341875

Abstract

Aim

Kingdon [(2014) Agendas, Alternatives, and Public Policies. Essex. United Kingdom: Pearson Education Limited] argues that windows of opportunity to pass policies emerge when problems, solutions and policy support co-occur. This study aims to identify a set of alcohol policies with the potential to reduce alcohol-related disparities given high levels of support from marginalized groups, such as racial/ethnic minorities and lower-income groups.

Methods

This study used data from five US National Alcohol Surveys, which were based on household probability samples of adults in 1995 (n = 4243), 2000 (n = 5736), 2005 (n = 1445), 2010 (n = 4164) and 2015 (n = 4041). We used multiple logistic regression to determine the odds of policy support by racial/ethnic group and income level, considering price, place and marketing policies as well as individual-level interventions.

Results

Overall a majority of Americans supported banning alcohol sales in corner stores (59.4%), banning alcohol advertisements on television (55.5%), and establishing universal health coverage for alcohol treatment (80.0%). Support was particularly high among Blacks, Hispanics/Latinos and lower-income persons. Multivariate models showed that compared with White people, foreign-born Hispanics/Latinos had the most robust levels of support, including raising alcohol taxes (aOR = 2.40, 95% CI: 2.00, 2.88, P < 0.0001), banning alcohol sales in corner stores (aOR = 2.85, 95% CI: 2.22, 3.65, P < 0.0001) and reducing retail sales hours (aOR = 2.91, 95% CI: 2.38, 3.55, P < 0.0001).

Conclusion

Of the policies examined, banning alcohol sales at corner stores is most likely to be in a “window of opportunity” for reducing alcohol-related disparities. By simultaneously reducing population-level consumption and harms from others’ drinking, place-based policies have the potential to reduce harms experienced by marginalized groups.

INTRODUCTION

In his seminal work, originally published in 1984, Agendas, Alternatives, and Public Policies, Kingdon (2014) argues that policymakers’ agendas depend on the convergence of three independent streams: problems, solutions and political will (see Fig. 1). Complex sets of rules govern how each of these streams emerges, evolves and interacts over time, but when the three converge, a “window of opportunity” opens and policy change is possible.

Fig. 1.

Fig. 1.

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Conceptual framework of Kingdon’s Three Streams Theory.

If they apply Kingdon’s framework to alcohol-related disparities in the United States, researchers can examine these three streams—problems, solutions and political will—to identify opportunities to advance alcohol policies that may reduce or prevent alcohol-related problems experienced by more marginalized populations. Starting with problems, Kingdon (2014) proposes two criteria: problems must describe conditions in which there are adverse consequences, and society must agree that we should fix those conditions. The extant literature on alcohol-related disparities clearly establishes this first criterion: Marginalized groups (such as racial/ethnic minorities and lower-income persons) have a disproportionately high risk for alcohol-related harms even though they drink less alcohol than their more advantaged peers (Chartier and Caetano, 2010; Vaeth et al., 2017). For example, compared with Whites, Blacks and Hispanics/Latinos face a greater risk of developing alcohol dependence (Chartier and Caetano, 2010; Vaeth et al., 2017), particularly after young adulthood (Grant et al., 2012; Witbrodt et al., 2014), as well as alcohol-attributable liver disease (Flores et al., 2008). Rates of recovery from alcohol dependence are also lower, and recurring alcohol use disorders more likely, in racial/ethnic minorities (Mulia and Jones-Webb, 2017). The “harms paradox” indicates that people who are socioeconomically disadvantaged tend to experience more alcohol-related harms (Herttua et al., 2015), even though they drink lower volumes of alcohol than more advantaged groups (Grittner et al., 2012). With regard to the second criterion, initiatives in the United States and abroad, such as Healthy People 2020, underscore the importance of combating health disparities (World Health Organization, 2017).

Moving on to the second stream, Kingdon (2014) defines solutions as accumulated knowledge and perspectives about how to fix emergent problems. Decades of research establishes which approaches most effectively reduce alcohol consumption, and this body of evidence consistently concludes that increasing the minimum drinking age, increasing alcohol taxes and other strategies for restricting the physical availability of alcohol are among policy options associated with the largest preventive potential (Babor et al., 2010; World Health Organization, 2010; Siegfried and Parry, 2019).

By comparison, the question of which alcohol control policies are most effective in reducing alcohol-related disparities is less clear. There is scant literature on alcohol policy effects by socioeconomic position and even less by race/ethnicity. To our knowledge, there are no empirical studies on whether and which alcohol policies reduce or exacerbate alcohol-related disparities (Mulia and Jones-Webb, 2017). Reviews suggest that certain universal approaches such as those that remove barriers to services are more promising for improving health equity. The question of how alcohol prevention strategies can reduce disparities is an area of active inquiry. A small body of research has found changes in alcohol taxes are associated with larger reductions in alcohol consumption and related harms among marginalized groups; for example, state-level beer and spirits taxes are associated with larger reductions in annual volume of consumption for racial/ethnic minority women and Hispanic/Latino men than among Whites (Subbaraman et al., 2020). In addition, relative to Whites, an Illinois alcohol tax increase was associated with larger reductions in chlamydia rates (as a measure of intoxication-related harm) among Blacks (Staras et al., 2014). With regard to income, recent US, Finnish and British studies suggest that lower-SES groups (where SES is defined using income, educational attainment, and occupational status) are more sensitive to alcohol price changes. For example, evaluations of a large reduction in alcohol prices in Finland documented subsequent growth in alcohol-related hospitalizations and mortality, particularly in lower-SES groups (Herttua et al., 2015; Mäkelä et al., 2015).

Kingdon’s third stream, political will, is shaped by public opinion, election results and administration priorities. Although public support alone cannot solve problems, public opinion drives which problems and solutions appear on the political agenda and when political will waxes and wanes. For example, politicians who are up for re-election may give priority to solutions that are highly supported among their constituents.

In concert, Kingdon’s theory and the extant research about alcohol-related disparities suggests that one way to combat disparities is to identify popular and effective solutions that address distinctive and prevalent risk factors of marginalized groups who are disproportionately burdened by alcohol problems. In other words, greater levels of public support for these policies would mean they have a higher likelihood of a “window of opportunity” opening. Communities that seize these windows to pass effective and equity-oriented policies may reduce alcohol-related disparities. Assessing the level of support among disadvantaged groups for different policy options is vitally important, otherwise acceptable policy interventions could exacerbate inequalities if they were to benefit certain groups more than the groups most impacted by alcohol problems.

Given this, the present study examines support for a range of alcohol policies in the United States overall, as well as by race/ethnicity and income, to identify effective approaches with high public support. To do so, we draw upon the last five waves of the National Alcohol Survey (NAS) to permit both subgroup comparisons of policy support and consideration of trends over time. We also examine policy support among high- and lower-income persons separately to disentangle associations with race/ethnicity and income. We then interpret our findings in combination with the literature on alcohol policy effectiveness to recommend strategies for reducing alcohol-related disparities that could result from the enactment of those policies during a window of opportunity.

METHODS

Data sources

Policy support, demographic and alcohol consumption data are from the NAS series, a repeated cross-sectional general population survey of US adults aged 18 years or older. We pooled survey data from five waves of the NAS: 1995 (n = 4925), 2000 (n = 7612), 2005 (n = 6919), 2010 (n = 7969) and 2015 (n = 7071). NAS 1995 was an in-person interview that utilized a multi-stage clustered sampling frame. In 2000, NAS became a computer-assisted telephone interview that used a list-assisted random digit dialed sampling frame. Extensive methodological work established minimal differences between in-person and telephone estimates for alcohol-related behaviors (Greenfield et al., 2000; Midanik and Greenfield, 2003). The NAS 2010 and 2015 added a cellular phone sample. The Institutional Review Boards at the Public Health Institute and the fieldwork agencies approved these surveys, and all participants provided informed consent.

The response rate in 1995 was 77%, while the cooperation rates in the telephone surveys were 58% (2000), 56% (2005), 52% (2010) and 56% (2015), consistent with contemporary telephone surveys (Curtin et al., 2005). In all years, Blacks and Hispanics/Latinos were oversampled. In 2005, the policy support questions were asked of approximately 25% of participants. Weights adjust for unequal selection probabilities, non-response and demographics. The final weighted sample is representative of the noninstitutionalized US adult population during the periods of data collection. Detailed information about the NAS series is available elsewhere (Kerr et al., 2013; Greenfield et al., 2019).

Sample

The final sample comprised 19,629 participants for whom complete data were available (4243 from 1995, 5736 from 2000, 1445 from 2005; 4164 from 2010; 4041 from 2015). The NAS only asked about support for some policies in some years (e.g. banning alcohol sales in corner stores was not asked in 2010), and we only used survey data from the years in which a given approach was included. Thus, our sample size included 12,588 participants for the retail hours of the sale, television advertising and sports sponsorship policies (not asked in 2010 or 2015), and 17,188 for the corner store sales policy (not asked in 2010).

Measures

Dependent variables (policy support)

We selected six of the eight items used to measure support for alcohol policies assessed between 1995 and 2015. We excluded items on warning labels and education because they were not asked in 2015 and alcohol education is not an effective population-level prevention strategy (Babor et al., 2010). Most items were adapted from prior Canadian and US surveys (Giesbrecht and Greenfield, 1999). The survey included one universal price policy (“Do you think taxes on alcoholic beverages should be increased, decreased or remain the same?”). It also included two universal marketing policies, including a ban on television advertising (“Should the government prohibit or stop wine, liquor, and beer advertising on TV?”) and banning alcohol industry sponsorship of sporting events (“Should the government prohibit or stop wine, liquor, and beer companies from sponsoring sporting or cultural events?”). We also included two community-level place policies: banning alcohol sales in corner stores (“Should alcoholic beverages be available in corner stores?”) and reducing alcohol retail hours (“Should beer and liquor store hours be increased, decreased, or remain the same?”). Lastly, we included one strategy that assessed support for a universal health insurance policy to increase access to alcohol treatment (“Do you think alcohol treatment programs should be covered in everyone’s health care insurance?”). All responses were dichotomized to indicate support for approaches that could reduce alcohol consumption and/or related problems (yes/no). Thus, responses favoring increased alcohol taxes, decreased liquor store hours and restricting sales of alcoholic beverages in corner stores would each be coded as policy support (yes).

Independent variables (marginalized group membership)

The first independent variable was self-reported race/ethnicity, which incorporated immigrant status for persons who identified as Hispanic/Latino. The five categories included White, Black, US-born Hispanic/Latino, foreign-born Hispanic/Latino and other. The second independent variable was income. We calculated total household income in the past year using two categories: income less than $40,000 or income of $40,001 or more. Income was adjusted for inflation and standardized to 2005 US dollar values, with the cutpoint representing the national median household income at the time of data collection.

Covariates

Demographics

Covariates included gender (male/female), age (continuous; scaled so one unit is 10 years), education (less than a high school degree, high school degree, or more than a high school degree) and marital status (single/never married, married/living with a partner, or divorced/separated/widowed). Previous research consistently shows that women and older adults tend to be more supportive of alcohol policies (Greenfield et al., 2004; Diepeveen et al., 2013; Callinan et al., 2014; Buykx et al., 2015; Parry et al., 2018). The research is less conclusive about the role of income, marital status and educational attainment in policy support (Diepeveen et al., 2013; Parry et al., 2018).

There is a positive association between religion and alcohol policy support, whereby more religious persons tend to have higher support for more restrictive policies (Greenfield et al., 2007; Lucchetti et al., 2014). Based on this, we included one covariate that captured the importance of religion to the respondent: “How important is religion in your life? Would you say very important, somewhat important, not really important, or not at all important?” We recorded this as a binary variable where 0 indicated less importance (not really important and not at all important) and 1 indicated more importance (very important and somewhat important).

Alcohol consumption

One of the strongest and most consistent predictors of alcohol policy support is the current drinking pattern; light drinkers and abstainers tend to show higher levels of support for alcohol policies that could reduce consumption or problems (Greenfield et al., 2007; Diepeveen et al., 2013; Parry et al., 2018). The NAS collects a past-year volume of alcohol consumption using a graduated quantity-frequency series (Greenfield, 2000; Greenfield et al., 2009). We calculated a three-category variable to capture past-year drinking status as abstainer, drinker or monthly heavy drinker (i.e. persons who consumed at least five alcoholic beverages during one occasion at least once a month over the past year, as defined by Greenfield, 2000).

Analysis

We used StataSE 14.2 (StataCorp, 2015) to conduct a multivariate logistic regression to determine the odds of policy support among demographic subgroups after adjusting for covariates. Focal independent variables were race/ethnicity and income. Covariates included age, gender, educational attainment, marital status, alcohol consumption and religion. We first tested one combined model with a racial/ethnic group and income as separate independent variables, and then we tested two additional models that stratified the sample by income. All analyses included the survey year as a covariate and used the survey weights. We used a Bonferroni correction to determine statistical significance within each set of analyses: The first set of regressions used P < 0.008 (0.05 divided by 6 tests), and the second set of analyses used P < 0.004 (0.05 divided by 12 tests).

Regression diagnostics included a link test for model specification, and these indicated no models were misspecified. We also examined variance inflation factors (VIFs), and all VIFs were less than two, indicating collinearity was not a problem (Sheather, 2009). Finally, we examined the models for outliers. We did not identify any points with undue influence, so all participants remained in the analysis.

RESULTS

Sample characteristics

Table 1 shows the participant distribution across the five survey administrations. Overall, the average age was 45.1 years (mean range: 43.0 years in 2000 to 49.6 years in 2010). In every year, approximately half the sample was female and half the sample was above the $40,000 threshold. Seventy-two percent of participants were White, 10.8% Black, 6.5% US-born Hispanic, 5.3% foreign-born Hispanic and 5.3% identified as other racial/ethnic groups. Still, the distribution of some demographic and drinking factors shows variation over time. In general, the survey samples tended to have a higher mean age in more recent years; this reflects the increasing difficulty of reaching younger populations using random digit dialing.

Table 1.

Sample characteristics across NAS years 1995–2015, n = 19,629

1995 2000 2005 2010 2015 Total
n = 4243 n = 5736 n = 1445 n = 4164 n = 4041 n = 19,629
% % % % % %
Age (mean) 43.78 43.01 44.28 49.60 45.92 45.08
Gender
Female 51.1 49.9 50.9 55.2 52.2 51.7
Male 48.9 50.1 49.2 44.9 47.8 48.3
Race/Ethnicity
White 76.0 73.1 72.0 73.8 65.8 72.1
Black 11.3 11.4 11.4 8.0 11.5 10.8
US-born Hispanic 4.7 6.2 6.1 6.4 9.0 6.5
Foreign-born Hispanic 4.7 4.8 5.7 5.9 6.0 5.3
Other 3.2 4.6 4.9 6.0 7.7 5.3
Income
Less than $40,000 48.3 55.7 44.3 45.4 50.1 50.1
$40,001+ 51.7 44.3 55.7 54.6 49.9 49.9
Education
Less than high school degree 19.2 13.5 10.0 14.0 11.4 14.1
High school degree 35.9 31.0 28.1 30.9 24.6 30.4
More than high school degree 45.0 55.5 62.0 55.2 64.0 55.6
Marital status
Single/never married 16.8 19.8 18.2 15.3 23.4 19.0
Married/living with a partner 66.9 64.7 66.7 68.3 58.2 64.5
Divorced/separated/widowed 16.3 15.6 15.1 16.5 18.4 16.5
Religious importance
Less important 44.4 43.4 48.1 43.8 49.7 45.4
Very important 55.6 56.6 52.0 56.2 50.4 54.6
Current drinking status
Abstainer 34.2 36.9 31.1 34.2 30.6 33.9
Current drinker 53.7 51.9 57.1 56.3 58.3 54.9
Current monthly heavy drinker 12.2 11.2 11.8 9.6 11.2 11.2
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Descriptive analyses

We first examined annual changes in policy support (Table 2). Each year, a majority favored prohibiting alcohol sales in corner stores (59.4%), banning alcohol advertisements on television (55.5%) and establishing universal health coverage for alcohol treatment (80.0%). On the other hand, a minority supported raising alcohol taxes (36.6%), reducing the hours of alcohol retail sales (33.0%) and banning alcohol sports sponsorship (40.9%). Policy support fluctuated over time. Overall, support decreased from 1995 to 2015 for all of the policies (all P < 0.02) except universal health insurance coverage for alcohol treatment, which increased from 76.6% to 81.9% (F = 5.84, P < 0.001) and banning alcohol industry sponsorship of sporting events, which was stable around 40% over time (F = 1.82, P = 0.16).

Table 2.

Proportion supporting alcohol control policies by type of policy, overall and by marginalized group membership

Taxesa (n = 19,629) Corner storesb (n = 15,465) Hoursc (n = 11,424) TV Adsd (n = 11,424) Sponsore (n = 11,424) Treatmentf (n = 19,629)
% 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI
Overall 36.6 35.6, 37.5 59.4 58.3, 60.5 33.0 31.8, 34.1 55.5 54.2, 56.7 40.9 39.7, 42.1 80.0 79.1, 80.8
Race/Ethnicity
White (ref) 34.5 33.4, 35.6 57.2 55.9, 58.5 29.5 28.2, 30.9 53.5 52.0, 54.9 38.5 37.1, 40.0 79.1 78.1, 80.0
Black 36.2 34.3, 38.2 68.4*** 66.3, 70.4 39.7*** 37.5, 41.9 62.8*** 60.5, 65.0 47.1*** 44.8, 49.3 85.4*** 83.9, 86.8
US-born Hispanic 39.2** 36.4, 42.2 59.8 56.5, 62.9 38.8*** 35.5, 42.2 59.2** 55.8, 62.6 46.3** 42.8, 49.7 82.2* 79.7, 84.4
Foreign-born Hispanic 57.3*** 54.0, 60.5 81.5*** 78.4, 84.3 62.0*** 58.5, 65.3 69.7*** 66.4, 72.8 63.5*** 60.1, 66.8 69.6*** 66.4, 72.7
Other 39.3** 35.0, 43.7 58.9 53.8, 63.8 45.9*** 40.1, 51.9 56.5 50.6, 62.1 46.3** 40.4, 52.2 80.1 76.4, 83.4
Income
Less than $40,000 39.6*** 38.3, 40.9 65.0*** 63.6, 66.5 37.8*** 36.3, 39.4 61.3*** 59.8, 62.9 46.8*** 45.2, 48.4 78.4* 77.3, 79.5
$40,001+ 33.5 32.1, 34.8 53.4 52.8, 55.0 27.8 26.1, 29.4 49.3 47.4, 51.2 34.6 32.9, 36.4 81.5 80.3, 82.6
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* P < 0.05.

** P < 0.01.

*** P < 0.001.

CI: confidence interval; US: United States; TV: television.

aFavor increased taxes. Question asked, “Do you think taxes on alcoholic beverages should be increased, decreased or remain the same?”

bFavor ban on corner store sales. Question asked, “Should alcoholic beverages be available in corner stores?”

cFavor reduced liquor store hours. Question asked, “Should beer and liquor store hours be increased, decreased, or remain the same?”

dFavor ban on alcohol advertising. Question asked, “Should the government prohibit or stop wine, liquor, and beer advertising on TV?”

eFavor ban on sports sponsorship. Question asked, “Should the government prohibit or stop wine, liquor, and beer companies from sponsoring sporting or cultural events?”

fFavor universal coverage of alcohol treatment. Question asked, “Do you think alcohol treatment programs should be covered in everyone’s health care insurance?”

We also tested changes in policy support during the 20-year period by race/ethnicity and income. These results followed similar patterns, except changes by income over time were often no longer significant after stratifying by race/ethnicity (data not shown). The only significant change among racial/ethnic and income groups that differed from the overall pattern was that foreign-born Hispanics/Latinos decreased their support for universal coverage for alcohol treatment (from 78.7% to 59.0%, F = 5.79, P < 0.01) and persons of other racial/ethnic groups decreased their support for banning sponsorship of sporting events (58.2–49.7%, F = 3.27, P = 0.04). Based on these findings of mostly non-significant over-time changes, we pooled data across years.

Bivariate analyses consistently showed racial/ethnic minorities (compared to Whites) and lower-income (compared to higher-income) groups tended to have higher levels of support for alcohol policies, with a few exceptions for universal coverage for alcohol treatment (Table 2).

Adjusted models

Policy support among marginalized groups generally persisted after adjusting for covariates (Table 3). In these models, the more advantaged subgroup (i.e. Whites, higher-income people) served as a reference to compare with the more disadvantaged subgroup. The most consistent and pronounced differences were observed among the two groups of Hispanics/Latinos. Compared with Whites, foreign-born Hispanics/Latinos had two to three times greater odds (100–200% higher odds) of support for raising alcohol taxes (140% higher odds), banning alcohol sales in corner stores (185% higher odds), reducing alcohol retail sales hours (191% higher odds) and banning alcohol industry sponsorship of sporting events (143% higher odds). US-born Hispanics/Latinos also had higher odds of support for most of the alcohol policies than Whites, though the differences were smaller in magnitude than those seen for foreign-born Hispanics/Latinos. Compared to Whites, US-born Hispanics/Latinos had roughly 57% higher odds of supporting banning sports sponsorship, 46% higher odds of supporting raising alcohol taxes, and 44% higher odds of banning alcohol sales in corner stores.

Table 3.

Results of adjusted logistic regression models for alcohol control policy support by age, gender, race/ethnicity and income level, United States 1995–2015

Taxesa (n = 19,629) Corner storesb (n = 15,465) Hoursc (n = 11,424) TV Adsd (n = 11,424) Sponsore (n = 11,424) Treatmentf (n = 19,629)
aOR 95% CI aOR 95% CI aOR 95% CI aOR 95% CI aOR 95% CI aOR 95% CI
Age (years)g 1.05*** 1.02, 1.08 1.17*** 1.13, 1.22 0.98 0.94, 1.02 1.11*** 1.07, 1.16 1.13*** 1.08, 1.17 0.91*** 0.88, 0.95
Gender
Male (ref) (ref) (ref) (ref) (ref) (ref)
Female 1.24*** 1.13, 1.35 1.83*** 1.65, 2.03 1.28*** 1.14, 1.45 1.64*** 1.47, 1.83 1.68*** 1.50, 1.87 1.88*** 1.69, 2.10
Race/Ethnicity
White (ref) (ref) (ref) (ref) (ref) (ref)
Black 0.88** 0.78, 1.00 1.38*** 1.20, 1.58 1.17** 1.01, 1.34 1.17** 1.02, 1.34 1.18** 1.03, 1.35 1.73*** 1.49, 2.00
US-born Hispanic 1.46*** 1.24, 1.71 1.44*** 1.20, 1.72 1.67*** 1.38, 2.02 1.41*** 1.19, 1.69 1.57*** 1.31, 1.87 1.27** 1.05, 1.54
Foreign-born Hispanic 2.40*** 2.00, 2.88 2.85*** 2.22, 3.65 2.91*** 2.38, 3.55 1.46*** 1.18, 1.80 2.43*** 1.98, 2.98 0.69*** 0.57, 0.83
Other 1.30** 1.05, 1.60 1.08 0.85, 1.37 1.94*** 1.43, 2.62 1.13 0.85, 1.50 1.42** 1.07, 1.88 1.08 0.83, 1.39
Income
Less than $40,000 1.00 0.90, 1.11 1.17*** 1.04, 1.31 1.19** 1.04, 1.35 1.29*** 1.14, 1.46 1.25*** 1.10, 1.41 0.91 0.81, 1.03
$40,001+ (ref) (ref) (ref) (ref) (ref) (ref)
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Asterisk and bolding indicates P < 0.008.

aOR: adjusted odds ratio; CI: confidence interval; US: United States.

Note: Models also adjusted for year of survey administration, drinker category (abstainer, current drinker, and current heavy drinker), education (high school or less versus more than high school), marital status (married; separated, divorced, or widowed; never married), and importance of religion (high/low).

aFavor increased taxes. Question asked, “Do you think taxes on alcoholic beverages should be increased, decreased or remain the same?”

bFavor ban on corner store sales. Question asked, “Should alcoholic beverages be available in corner stores?”

cFavor reduced liquor store hours. Question asked, “Should beer and liquor store hours be increased, decreased, or remain the same?”

dFavor ban on alcohol advertising. Question asked, “Should the government prohibit or stop wine, liquor, and beer advertising on TV?”

eFavor ban on sports sponsorship. Question asked, “Should the government prohibit or stop wine, liquor, and beer companies from sponsoring sporting or cultural events?”

fFavor universal coverage of alcohol treatment. Question asked, “Do you think alcohol treatment programs should be covered in everyone’s health care insurance?”

gA one-unit increase in age is 10 years.

In addition, Blacks and lower-income persons showed higher odds of support for a few policies. Specifically, Blacks had 38% greater odds of support for banning alcohol sales in corner stores and 88% greater odds of support for universal coverage for alcohol treatment compared with Whites. Compared with higher-income persons, lower-income persons had roughly 17% greater odds of support for banning alcohol sales in corner stores, 19% higher odds of reducing hours of alcohol sales, 29% higher odds of restricting alcohol ads on TV and 25% higher odds of banning alcohol sponsorship at sporting events.

Stratified models

When stratifying by income, both groups of foreign-born Hispanics/Latinos had roughly two to three times the odds of support (100–200% higher odds) for each policy than their White counterparts, except for banning alcohol ads on TV and universal health insurance coverage for alcohol treatment (Table 4). For the other subgroups, the stratified analyses revealed differences in support for some alcohol policies that had been obscured in the overall models, suggesting some of the differences observed in the full sample may have been driven by a particular income group. For example, only higher-income US-born Hispanics/Latinos showed greater support for the marketing policies (banning alcohol ads on TV and banning industry sponsorship at sporting events) than higher-income Whites. After stratifying by income, the greater odds of support for banning alcohol sales in corner stores among Blacks only persisted among higher-income Blacks (as compared with higher-income Whites); that is, there was no difference by race/ethnicity among lower-income people. In addition, although higher-income Blacks had 27% higher odds of supporting raising alcohol taxes like higher-income Whites in the stratified model, lower-income Blacks had 28% lower odds of support for this approach than lower-income Whites.

Table 4.

Results of multiple logistic regression for alcohol control policy support based on age, gender and race/ethnicity stratified by level of income, United States 1995–2015

Taxesa (n = 19,629) Corner storesb (n = 15,465) Hoursc (n = 11,424) TV Adsd (n = 11,424) Sponsore (n = 11,424) Treatmentf (n = 19,629)
aOR 95% CI aOR 95% CI aOR 95% CI aOR 95% CI aOR 95% CI aOR 95% CI
Lower-income (<$40,000 per year)
Age (years) 1.03 0.99, 1.07 1.15* 1.09, 1.21 0.95 0.90, 0.99 1.11* 1.06, 1.17 1.10* 1.05, 1.15 0.86* 0.82, 0.90
Gender
Male (ref) (ref) (ref) (ref) (ref) (ref)
Female 1.28* 1.13, 1.45 1.73* 1.49, 2.00 1.28* 1.09, 1.49 1.49* 1.28, 1.74 1.50* 1.30, 1.74 1.73* 1.50, 1.99
Race/Ethnicity
White (ref) (ref) (ref) (ref) (ref) (ref)
Black 0.72* 0.61, 0.83 1.18 0.99, 1.40 1.03 0.86, 1.23 1.05 0.89, 1.25 1.05 0.89, 1.24 1.48* 1.23, 1.77
US-born Hispanic 1.35* 1.11, 1.65 1.41* 1.12, 1.77 1.57* 1.25, 1.96 1.23 0.99, 1.53 1.29 1.04, 1.60 1.32 1.05, 1.68
Foreign-born Hispanic 2.20* 1.79, 2.71 3.09* 2.32, 4.13 2.89* 2.29, 3.66 1.31 1.03, 1.67 2.31* 1.82, 2.92 0.59* 0.48, 0.74
Other 1.16 0.88, 1.54 1.19 0.84, 1.68 1.83 1.21, 2.77 1.24 0.84, 1.82 1.57 1.08, 2.28 1.14 0.81, 1.61
Higher-income (≥$40,000 per year)
Age (years) 1.08* 1.02, 1.14 1.21* 1.14, 1.29 1.04 0.97, 1.12 1.10* 1.02, 1.17 1.17* 1.09, 1.26 1.01 0.95, 1.08
Gender
Male (ref) (ref) (ref) (ref) (ref) (ref)
Female 1.22* 1.07, 1.39 1.95* 1.68, 2.26 1.30* 1.08, 1.57 1.82* 1.55, 2.15 1.92* 1.62, 2.28 2.12* 1.80, 2.50
Race/Ethnicity
White (ref) (ref) (ref) (ref) (ref) (ref)
Black 1.27** 1.04, 1.54 1.82* 1.46, 2.27 1.48* 1.17, 1.87 1.36* 1.08, 1.71 1.41* 1.13, 1.76 2.22* 1.70, 2.90
US-born Hispanic 1.52* 1.17, 1.97 1.48* 1.11, 1.96 1.83* 1.30, 2.57 1.69* 1.24, 2.29 2.08* 1.52, 2.84 1.18 0.86, 1.60
Foreign-born Hispanic 2.73* 1.86, 4.00 2.21* 1.31, 3.71 2.58* 1.70, 3.91 1.96* 1.28, 3.03 2.26* 1.50, 3.41 0.96 0.60, 1.53
Other 1.43** 1.04, 1.96 0.97 0.69, 1.36 2.04* 1.33, 3.14 0.98 0.64, 1.48 1.21 0.79, 1.85 1.01 0.69, 1.48
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Asterisk and bolding indicates P < 0.004.

aOR: adjusted odds ratio; CI: confidence interval; US: United States.

Note: Models also adjusted for year of survey administration, drinker category (abstainer, current drinker, and current heavy drinker), education (high school or less versus more than high school), marital status (married; separated, divorced, or widowed; never married), and importance of religion (high/low).

aFavor increased taxes. Question asked, “Do you think taxes on alcoholic beverages should be increased, decreased or remain the same?”

bFavor ban on corner store sales. Question asked, “Should alcoholic beverages be available in corner stores?”

cFavor reduced liquor store hours. Question asked, “Should beer and liquor store hours be increased, decreased, or remain the same?”

dFavor ban on alcohol advertising. Question asked, “Should the government prohibit or stop wine, liquor, and beer advertising on TV?”

eFavor ban on sports sponsorship. Question asked, “Should the government prohibit or stop wine, liquor, and beer companies from sponsoring sporting or cultural events?”

fFavor universal coverage of alcohol treatment. Question asked, “Do you think alcohol treatment programs should be covered in everyone’s health care insurance?”

gA one-unit increase in age is 10 years.

Income did not appear to modify the associations between race/ethnicity and support for alcohol treatment for US-born Hispanics/Latinos or Blacks. Blacks’ greater odds of support for universal coverage for alcohol treatment remained significant after stratifying by income, and neither low- nor higher-income US-born Hispanics/Latinos differed from Whites in odds of supporting universal coverage for alcohol treatment. However, the odds of support for coverage of alcohol treatment differed among low- and higher-income foreign-born Hispanics/Latinos. Lower-income foreign-born Hispanics/Latinos had 41% lower odds of supporting universal coverage of alcohol treatment compared with lower-income Whites.

CONCLUSIONS

This study aimed to identify effective alcohol policies with substantial support in order to identify potential “windows of opportunity” for mitigating alcohol-related disparities. Our results show high levels of overall support for banning alcohol ads on TV, and marginalized groups showed particular support for bans on alcohol sales in corner stores and for universal health insurance coverage of alcohol treatment. In our view, the high levels of public support for banning alcohol sales in corner stores represent a particularly important “window of opportunity” that could help mitigate alcohol-related disparities. As noted earlier, restrictions on alcohol availability are among the most effective alcohol policies. In addition, these community-level policies can be selectively implemented in neighborhoods that are saturated with outlets and where support may be particularly high. Alcohol outlets often cluster in marginalized neighborhoods (Morrison et al., 2016) and those with a history of discriminatory lending practices (e.g. redlining) (Trangenstein et al., 2019), suggesting one root cause of these alcohol-related disparities may be an unequal implementation of beneficial alcohol policies. This would lead to downstream environmental disparities by placing marginalized groups in close contact with the risks associated with alcohol stores, such as violent crime, sexually transmitted infections and drink-driving crashes (Campbell et al., 2009; Sherk et al., 2018), which are the harms that some blame on the residents of the neighborhoods themselves, rather than on their unjust surroundings. Place-based approaches like banning alcohol sales in corner stores would help remove this environmental risk. Finally, because disparities in the distribution of alcohol outlets may arise from their exclusion from higher-income neighborhoods (Morrison et al., 2015), ensuring that economically diverse community members have a seat at the table when developing alcohol outlet zoning and licensing policies may help prevent disparities in the future.

Universal healthcare coverage for alcohol treatment may be a complementary approach to consider, as it had some of the highest levels of public support that were robust over time. Part of the appeal of coupling alcohol treatment with universal health insurance coverage is that it removes a common barrier (cost) that can create or exacerbate disparities. However, the universal coverage aspect also contains limitations. This option merely specifies a goal of universal coverage; it does not also identify a specific source of funds that would cover treatment costs so as to make this policy sustainable over time. Kingdon (2014) argues that viable solutions are most successful when they are cheap. In addition, while there is literature to support the short-term effectiveness of treatment (National Research Council, 1990; Miller et al., 2001), study authors could not find strong evidence that health insurance coverage or cost of treatment per se affect alcohol-related outcomes. This may reflect the unclear relationship between insurance and treatment entry in the context of public funding for treatment (Schmidt and Weisner, 2005; Bouchery et al., 2012), as well as high rates of treatment non-completion (Arndt et al., 2013).

While deemed very effective for reducing population-level consumption, raising alcohol taxes and reducing liquor store hours had among the lowest levels of existing support, and marginalized groups did not consistently show high levels of support for banning alcohol ads on TV. In multivariate models, higher-income Hispanics/Latinos and higher-income Blacks were the only subgroups with increased support for taxes and restrictive store hours and advertising policies. This is consistent with the larger alcohol policy support literature, which tends to find lower levels of support for population-wide approaches (Buykx et al., 2016; Parry et al., 2018), likely because people may be less likely to support policies that they believe will constrain their own behavior. This is consistent with the long-standing finding that drinkers, particularly heavy drinkers, have lower levels of support for alcohol policies (Diepeveen et al., 2013; Buykx et al., 2016), although other experiences, such as being harmed by others’ drinking, may mitigate this (Stanesby et al., 2017).

One final high-level finding is that higher levels of support for targeted policies (e.g. coverage for alcohol treatment) is consistent with an individualistic definition of alcohol problems (i.e. lack of personal responsibility or individual failing that results in excessive consumption and negative consequences) that is promulgated by the alcohol industry (Casswell et al., 2016). This stands in stark contrast to a public health definition of alcohol problems, which would define the product—alcohol—as the problem (e.g. Jahiel and Babor, 2007; Moodie et al., 2013). The second, more inclusive framing of alcohol problems supports policy approaches that would limit the availability, price and marketing of alcohol. Thus, if there is already a problem and a solution, advocates may help a “window of opportunity” open by using carefully crafted problem statements to boost public support for public health policy solutions.

This analysis has several limitations. Although the NAS uses identical wording in each iteration, not all policies support questions were asked each year. In particular, the marketing and place-based policies were not asked in the most recent iterations. Pooling data from several NAS surveys allowed us to examine many subgroup differences, although we were unable to examine all potentially relevant subgroup differences (e.g. among Asians or subgroups of Hispanics/Latinos beyond immigration status). Finally, the wording of some of the policy support questions may introduce other limitations. In particular, using a binary (yes/no) or three-category format (more, same, less) to measure policy attitudes produces less heterogeneity than Likert scale response options. In addition, the alcohol tax question asked, “Do you think taxes on alcoholic beverages should be increased, decreased or remain the same?” Previous research shows that public support for alcohol taxes is higher when the question references earmarking proceeds for a particular cause (Wright et al., 2017); earmarking tax revenue to fund universal treatment for alcohol may be a potentially viable strategy in the future. Finally, we did not examine whether the policies covered in this study are effective in reducing alcohol-related disparities. Research suggests that alcohol is more available in minority and lower-income communities (Morrison et al., 2016) and restricting the physical availability of alcohol leads to reductions in alcohol consumption and alcohol problems (Sherk et al., 2018). Future studies may wish to test the hypothesis that alcohol outlet density regulations can reduce or prevent alcohol-related disparities.

There is a wide array of effective approaches with widespread public support. In addition to identifying the policies with broad population support, researchers also can help shape the political agenda by strategically defining and surveilling problems. If researchers define problems in a way that suggests a specific solution that has public support, they can create “windows of opportunity.” Two prime examples include Philadelphia, Pennsylvania and Omaha, Nebraska. In Philadelphia, a researcher and reverend used research linking alcohol advertising exposure to underage drinking as evidence to enact a new ban on all new alcohol advertisements on public property (Haas and Sherman, 2020). In addition, they used grasstops organizing to get the Southeastern Pennsylvania Transportation Authority to commit to no longer displaying any alcohol ads on or in their bus shelters (Haas and Sherman, nd). This was a large victory because the School District of Philadelphia provided free bus tokens or reduced bus fares for 27,000+ students at the time (Haas and Sherman, nd). In Omaha, a neighborhood association filed a Supreme Court case against a nuisance alcohol outlet that was the site of a shooting and the epicenter of thousands of police calls for service (Jernigan et al., 2013). The Supreme Court ruled that the Nebraska Liquor License Control Commission must consider how environmental context can determine whether such outlets function legitimately or contribute to neighborhood disorganization (Jernigan et al., 2013). This court case paved the way for a subsequent land-use ordinance that granted the city (rather than the state) the authority to determine whether to approve new outlets within city limits and ultimately resulted in a deemed approved ordinance that established operational standards for outlets (Jernigan et al., 2013).

To quote the great philosopher Seneca, “luck is what happens when preparation meets opportunity.” If researchers and civil society prepare compelling evidence documenting the problem and showing support for effective interventions and policies, they will be better able to encourage legislators to seize these windows of opportunity when they arise (Johnson et al., 2004).

Data Availability

Datasets and codebooks from the U.S. National Alcohol Survey Series can be requested here: http://arg.org/nas-datasets/.

Funding

The project described was supported by Award Numbers T32AA007240 (Graduate Research Training in Alcohol Problems: Alcohol-Related Disparities) and P50AA005595 (Epidemiology of Alcohol Problems: Alcohol-Related Disparities) from the National Institute on Alcohol Abuse and Alcoholism. The content is solely the responsibility of the authors and does not necessarily represent the official view of the National Institute on Alcohol Abuse and Alcoholism or the National Institutes of Health. The supporting institutions had no role in the study design, collection, analysis or interpretation of the data, writing of the manuscript or the decision to submit the manuscript for publication.

Declarations

Drs Trangenstein and Greenfield have received research and/or travel support from the National Alcohol Beverage Control Association.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Datasets and codebooks from the U.S. National Alcohol Survey Series can be requested here: http://arg.org/nas-datasets/.

Articles from Alcohol and Alcoholism (Oxford, Oxfordshire) are provided here courtesy of Oxford University Press

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