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. Author manuscript; available in PMC: 2025 Aug 15.
Published before final editing as: Sex Res Social Policy. 2024 Nov 8:10.1007/s13178-024-01056-6. doi: 10.1007/s13178-024-01056-6

Associations Between Alcohol Delivery Policy and Pandemic Alcohol Use Among Sexual and Gender Minority Youth and Young Adults

Megan M Ruprecht 1, Jiayi Xu 1, Michael G Curtis 1, Ysabel Beatrice Floresca 1, Dylan Felt 1, Gregory Phillips II 1,2
PMCID: PMC12352502  NIHMSID: NIHMS2054197  PMID: 40823323

Abstract

Introduction

In an effort to promote social distancing as a response to the COVID-19 pandemic, many jurisdictions altered policies surrounding alcohol delivery, newly allowing both on-premises (i.e., from restaurants) and off-premises (i.e., from liquor stores) to deliver alcohol directly to consumers in many places. However, it is unknown how these changing delivery policies impact alcohol use among youth and young adults (YYA), especially sexual and gender minority youth and young adults (SGMY) population.

Methods

Using alcohol use data from a national, cross-sectional study of youth and young adults with ages 14–24 (n = 736) between February 2021 and March 2022 and policy data from the Alcohol Policy Information System (APIS), we used multinomial logistic regression to test associations between current drinking and binge drinking and the presence of different alcohol delivery policies, as well as to measure disparities between different subpopulations.

Results

Results indicate that off-premises delivery policy was associated with binge drinking as well as current light alcohol use. However, on-premises delivery policy was associated with lower rates of binge drinking. Younger populations and transgender populations reported lower levels of alcohol use.

Conclusions

Findings indicate that, as many of these policy changes become permanent, novel prevention strategies may be needed to prevent harmful alcohol use, especially in states that allow off-premises alcohol delivery.

Policy Implications

Results of the present study support the development of future research scrutinizing the long-term effects of increased alcohol accessibility among YYA and increased binge drinking among YYA as a tertiary consequence of the COVID-19 pandemic.

Keywords: Alcohol use, Binge drinking, Policy, Youth and young adults, LGBT, COVID-19

Introduction

Alcohol use among youth and young adults (YYA) continues to be a widespread problem; according to the Center for Disease Control and Prevention’s Youth Risk Behavior Survey (YRBS), in 2021, 22.7% of high school students reported current alcohol use and 10.5% reported binge drinking (Hoots et al., 2023). Alcohol use in YYA populations has pronounced social, psychological, and physical effects. For example, binge drinking in adolescence has been associated with decreased executive and cognitive functioning (Lees et al., 2020) as well as worsened performance in school (Patte et al., 2017). It has been further associated with mental health consequences, including anxiety (Pakula et al., 2016), depression (Archie et al., 2012), non-suicidal self-injury (Swannell et al., 2014), and suicidality (Phillips et al., 2020). Furthermore, disparities exist for sexual and gender minority youth and young adults (SGMY), with SGMY populations reporting both higher levels of recent alcohol use and heavy episodic use (Talley et al., 2014; Watson et al., 2019). Disparities also exist for racial and ethnic minority YYA, as Latinx and Native American YYA may also be particularly vulnerable to negative outcomes related to alcohol use (Friese & Grube, 2008; Metz et al., 2022). These disparities can be explained using minority stress theory, which indicates that populations experiencing stigma may use alcohol to cope with the overloaded stress burden experienced due to their minoritized identity (Lehavot & Simoni, 2011). Physical health concerns, including increased HIV vulnerability and higher rates of chronic disease, also remain notable (Phillips et al., 2018; Rehm, 2011).

As a result of the COVID-19 pandemic, widespread policy changes, including those related to alcohol use, were introduced in an attempt to curb disease spread. One such change to promote social distancing and quarantine was alterations in state alcohol policy, intended to minimize congregation at bars, restaurants, and liquor distributors. Specifically, home delivery of alcohol became more widely available. Home delivery policies can broadly be defined by the type of establishment: places where alcohol is sold but cannot be consumed are considered “off premises” and places where alcohol can be both purchased and consumed are considered “on premises” (Chinman et al., 2011). Customers may order alcohol either directly or through third party delivery services in most states. As of 1/1/2020, 18 states allowed home delivery from on-premises establishments (i.e., restaurants and bars), and 34 states + Washington, DC, allowed home delivery from off-premises establishments (e.g., liquor stores and grocery stores) with rules of how home delivery must be done varying by state. Some examples of specific home delivery requirements are as follows: (1) restrictions on the type of alcohol that can be delivered, (2) restrictions on quantity and packaging, (3) requiring that alcohol cannot be delivered without food, (4) restrictions on whether or not third party delivery is allowed (e.g., GrubHub and Uber Eats), (5) time constraints as to when alcohol can be delivered, and (6) requiring permits or licenses from the participating establishment. More states allowing for home delivery from off-premise establishments may be because many states deemed off-premise establishments as essential services during the COVID-19 lockdowns. As of 1/1/2022, 38 states allowed home delivery from on-premises establishments and 39 states allowed home delivery from off-premises establishments (National Institute of Alcohol Abuse and Alcoholism, 2022). As such, the COVID-19 pandemic prompted a major shift in alcohol policy which remained permanent in many jurisdictions, especially regarding delivery from on-premises establishments. Due to the sudden shift in policies, the effects of increased access to alcohol during the COVID-19 pandemic (March 2020–May 2023) are unknown. Therefore, it is essential to understand how these policies may impact alcohol use in order to effectively prevent harmful consumption, particularly among populations most vulnerable to the consequences of alcohol use, including youth and young adults.

Initial research suggests that those who had alcohol delivered during the COVID-19 pandemic reported heavier drinking than those who purchased alcohol in person (Huckle et al., 2021), including more binge drinking and more drinking days per month (Grossman et al., 2022). Furthermore, delivery may have led to increased alcohol use among young people. Pre-pandemic, one survey of 15 Midwestern communities found that 10% of 10th graders and 7% of 18–20 year olds had obtained alcohol through delivery services within the last year, indicating a major breach in YYA alcohol prevention strategies. Additionally, men, as well as heavier drinkers, were more likely to get alcohol delivered more frequently (U.S. Department of Health and Human Services (HHS), Health Services Administration (SAMHSA), & (ICCPUD) 2018). Binge drinking and more recent drinking were associated with at-home alcohol delivery among underage youth (Fletcher et al., 2000). While ID checks are still legally required for both on-premises and off-premises deliveries, the noncompliance rate has been extremely high, indicating that this may be a viable way for underage populations to obtain alcohol (Bargal, 2022; Jonathan K Noel & Rosenthal, 2023). However, no studies of which we are aware have investigated the impact of alcohol home delivery policies on SGM YYA under the legal drinking age of 21 years in the USA within the context of the COVID-19 pandemic.

This is especially pertinent as the COVID-19 pandemic has been shown to be associated with increased alcohol use among some YYA (Horigian et al., 2021; Veldhuis et al., 2021). Among college aged students, overall alcohol use has increased during the pandemic (Charles et al., 2021; Lechner et al., 2020), and among high school aged youth, the number of drinking days per week also increased (Dumas et al., 2020). Some subpopulations, in particular SGMY, may have been particularly affected (Salerno et al., 2021). Of note, results in this arena have been highly variable (Acuff et al., 2022), potentially due to rapid changes in environmental and social access. For example, one study found that alcohol use among high school aged youth decreased after the COVID-19 lockdown, possibly due to difficulty in accessing alcohol (J. K. Noel et al., 2023). Still, these rapid changes and disparities indicate an urgent need to evaluate existing policies to reduce and prevent harmful alcohol use among youth populations, especially SGMY populations, whose alcohol use patterns may have been particularly impacted. Further, policies such as those related to home delivery can have differential effects on particular sub-populations, which are critical to attend to in crafting policy and interventions (Giesbrecht et al., 2016). As such, it is important to firstly characterize alcohol use disparities among YYA populations during the pandemic and then explore how alcohol home delivery policies will impact alcohol use rates in SGMY populations, who already use alcohol at elevated rates, in order to prevent harmful alcohol use among YYA in the future.

Methods

Study Design

Data were collected as a part of the Youth and Young Adults COVID-19 Study—a prospective cohort of marginalized YYA—between February 2021 and March 2022. We defined age groups to be youth (14–17 years of age) and young adults (18–24 years of age). Eligibility criteria were (1) being 14 to 24 years of age, (2) residing in the USA/US territories, (3) having access to the internet, (4) being willing to complete a follow-up survey in 6 months, and (5) providing informed consent. We first sent out a screener to participants who were interested in the study, and then eligible participants who provided informed consent were invited to complete the survey. For participants under 18 years, ability to understand study procedures and decisional capacity was first assessed, based on the UCSD Task Force on Decisional Capacity’s procedures for determination of decisional capacity in persons participating in research (The UCSD Task Force on Decisional Capacity Team, 2003), using a modified version of the Evaluation to Consent Form (Dunn & Jeste, 2001; Moser et al., 2002; UCSD Task Force on Decisional Capacity, 2003). Informed consent for all participants was obtained electronically. Participants were recruited through paid social media advertisements, outreach with organizations that served LGBTQ +, Indigenous, and Latinx youth, and an existing participant registry. Participants who completed the baseline survey received a digital $30 VISA card. Study procedures were approved by < redacted for review > Institutional Review Board through expedited review.

Measures

Current Alcohol Use

Participants were asked, “During the past 30 days, on how many days have you had at least one drink of alcohol?” with response options ranging from 0 days to all 30 days (CDC, 2019). Extrapolating from National Health Interview Survey definitions, youth that reported 1 to 12 drinking days in the past month were classified as “Current Light Drinkers” and youth that reported more than 12 drinking days in the past month were classified as “Current Heavy Drinkers” (CDC, 2018).

Binge Drinking

Participants were asked, “During the past 30 days, on how many days did you have 4 or more drinks of alcohol in a row (if you are female) or 5 or more drinks of alcohol in a row (if you are male)?” with response options ranging from 0 to 20 or more days (CDC, 2019). Participants who answered > 0 days were classified as current binge drinkers (CDC, 2018).

Off-Premises Delivery Policy

As previously described, off-premises alcohol retailers are places where alcohol is sold but cannot be consumed (e.g., it is meant to be consumed off site). As such, off-premises delivery includes delivery from grocery stores, liquor stores, and similar retailers (Chinman et al., 2011). Delivery policy changes throughout the pandemic were retrieved from the Alcohol Policy Information System (APIS), which maintained a database of alcohol-related laws during the COVID-19 emergency month by month (National Institute on Alcohol Abuse and Alcoholism, 2022). Each participant was assigned a “1” or “0,” depending on whether or not off-premises alcohol delivery was permitted in the state where that participant lives on the date they completed the baseline survey. Additional policy details can be found in Table 1.

Table 1.

On-premises and off-premises alcohol delivery policy, pre- and post-pandemic (NIAAA, 2022a, 2022b)

Delivery from on-premises establishments Delivery from off-premises establishment
Pre-COVID During the pandemic Pre-COVID During the pandemic
Alabama Not permitted Permitted starting 10/1/2021 with delivery permit Not permitted Permitted starting 10/1/21
Alaska Not permitted Permitted starting 4/16/20. Now permanent Permitted Permitted
Arizona Permitted for bars only As of 10/1//21, bars can deliver cocktails, restaurants must apply for permit Permitted Permitted
Arkansas Permitted for beer only Permitted for beer and wine starting 3/19/20, with food delivery, excluding third-party delivery services. Expanded to include mixed drinks 4/14/21 Not permitted Permitted starting 3/20/20
California Beer and wine only Permitted with food sale from 3/19/20 to 12/31/21. As of 1/1/22, beer and wine only Permitted Permitted
Colorado Not permitted Permitted delivery of sealed beverages purchased with food 3/20/20–7/10/20 Permitted Permitted
Connecticut Beer and wine only Permitted to deliver sealed alcohol with existing permit; must include food as of 4/2/20. As of 6/4/21, delivery must be by a direct employee or a third party that holds a permit Permitted Permitted
Delaware Not permitted Not permitted Not permitted Not permitted
Florida Not permitted Bars and restaurants can sell alcohol for delivery if food included as of 3/20/20 Permitted Permitted
Georgia Not permitted Delivery of beer and wine permitted as of 8/3/20 Permitted Permitted
Hawaii Not specifically allowed Establishments with a liquor license permitted to sell unopened beer/wine or pre-packaged cocktails with food for delivery from 4/16/20 to 8/5/21 Not permitted Not permitted
Idaho Permitted for beer and wine only Permitted for beer and wine only Permitted Permitted
Illinois Subject to approval of the Local Liquor Control Commission Permitted for mixed drinks as of 6/2/20, use of third party delivery services prohibited, expanded to include wine and allow for use of third party delivery services as of 6/2/21 Beer and wine only Beer and wine only
Indiana Permitted for select bars and restaurants with permit Permitted, though state imposed limits for delivery exist Permitted Permitted
Iowa Permitted for beer As of 7/1/21, third party services permitted to deliver alcohol from licensed establishments with an agreement between the establishment and the third party service Permitted Permitted
Kansas Not permitted Not permitted Not permitted Not permitted
Kentucky Not permitted As of 3/15/20, delivery sales are permitted by any licensed establishment Permitted Permitted
Louisiana Permitted for restaurants with additional license Delivery by third-party permitted 6/9/20. Restaurants with permit can use employees to delivery beer or wine, with food Permitted Permitted
Maine Not permitted Beer and wine delivery permitted with food 3/18/20. Cocktail delivery allowed 4/27/20 Not permitted Not permitted
Maryland Permitted, depending on county As of 3/19/20, allowed to deliver to homes, subject to local licensing boards Permitted Permitted
Massachusetts Not permitted As of 4/3/20, allowed to deliver malt beverages and wine with food. Expanded to include mixed drinks as of 7/20/20, to continue until the end of the state of emergency Permitted, though vehicle used must have a permit Permitted though May starting 11/6/20
Michigan Not permitted Permitted with carry out license, as of 7/1/20 Permitted Permitted
Minnesota Not permitted Not permitted Permitted Permitted
Mississippi Not permitted As of 7/1/21, restaurants are permitted to delivery beer, wine, and “light spirit products” within wet counties, but they must have a delivery permit Not permitted Permitted as of 7/1/21
Missouri Permitted for bars and restaurants Permitted for bars and restaurants Permitted Permitted
Montana Not permitted As of 3/20/20, restaurants can sell alcohol for delivery with food. Bars can sell alcohol without restriction. as of 10/1/21, both restaurants and bars can sell only beer and wine with food; must also have a delivery endorsement from the Department of Revenue Permitted Permitted
Nebraska Permitted with license Permitted as of 3/19/20; law rescinded as of 6/1/21 Permitted Permitted
Nevada Not permitted Not permitted Not permitted Not permitted
New Hampshire Permitted for wine only From 3/18/20 to 5/7/21, beer and wine delivery allowed if accompanied by a food order Permitted Permitted
New Jersey Permitted with license Permitted as of 3/30/20 Permitted Permitted
New Mexico Not permitted As of 7/1/21, restaurants and bars can deliver alcohol with a delivery permit Not permitted Not permitted
New York Not permitted As of 3/16/20, restaurants and bars can sell alcohol for delivery. Food required to be sold with alcohol 7/17/20–4/28/21. As of 6/25/21, cocktail delivery no longer permitted Permitted Permitted
North Carolina Permitted for beer and wine only Beer and wine delivery allowed, mixed beverage delivery allowed 12/21/20–6/1/21 Beer and wine only Beer and wine only
North Dakota Not permitted Not permitted Not permitted Not permitted
Ohio Not permitted As of 4/7/20, establishments with existing on-premises permits could deliver beer, wine, mixed beverages, or spirituous liquor, with food. Made into law on 10/13/20 Not permitted Not permitted
Oklahoma Not permitted 3/24/20–5/15/20, beer and wine delivery permitted by temporary order, third-parties not allowed. Made into law 8/26/21 when mixed drink delivery also became permitted Not permitted Permitted as of 3/24/20
Oregon Permitted for beer and wine only, with a shipper’s permit As of 6/8/21, can deliver malt beverages, wine and cider without permit. Could delivery mixed drinks and wine without a permit as of 6/11/21 Beer and wine only Distilleries, beer, wine starting 4/20
Pennsylvania Beer and wine only Beer and wine delivery permitted Not permitted Not permitted
Rhode Island Not permitted Not permitted Permitted Permitted
South Carolina Not permitted Permitted from 3/21/20 to 6/6/21—third party delivery not allowed Not permitted Not permitted
South Dakota Not specifically permitted Not specifically permitted Permitted Permitted
Tennessee Permitted for bars and restaurants who have a licensed delivery service Permitted from 3/23/20 to 5/31/21 if alcohol is purchased with food. As of 5/31/21, delivery permitted only for bars and restaurants via a licensed delivery service Permitted Permitted
Texas Only permitted for bars and restaurants that hold a food and beverage certificate As of 3/20/20, restaurants and bars with a mixed drink permit can deliver beer, wine or mixed drinks with food. Could apply to permanently sell mixed drinks as of 6/27/20. As of 5/12/21, select permittees can deliver with food orders and use third party services Permitted Permitted
Utah Not permitted Not permitted Not permitted Not permitted
Vermont Not permitted Delivery temporarily permitted 3/19/20 to 7/1/21 Permitted Permitted
Virginia Not permitted, unless they hold a special delivery permit As of 4/10/20, restaurants can deliver beer, wine, and mixed drinks either directly or through a third-party. Expanded into law 7/1/21, with delivery permit required Wine and beer only, with a four case limit Permitted
Washington Permitted for beer and wine only As of 5/6/20, delivery was expanded to include spirits. Made law through July 1st, 23 Permitted Permitted
West Virginia Not permitted As of 4/3/20, beer and wine delivery permitted with food. As of 5/10/21, delivery is allowed with permit, cocktails included, as long as it accompanies a food purchase Permitted Permitted 5/10/21
Wisconsin Not permitted Not permitted Not permitted Permitted 3/20–5/13/20
Wyoming Not permitted Not permitted Permitted Permitted
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On-Premises Delivery Policy

On-premises alcohol retailers include those where alcohol is both sold and consumed. Therefore, on-premises delivery includes delivery from restaurants and bars. Similar to off-premises delivery, participants were assigned a “1” or “0,” depending on whether or not on-premises alcohol delivery was permitted in the state where that participant lives on the date they completed the baseline survey, according to APIS (National Institute on Alcohol Abuse and Alcoholism, 2022). In a small number of cases, delivery is allowed from restaurants but not bars, or vice versa (Table 1). Because of this, specific policies about whether or not on-premises home delivery was allowed from restaurants were used in analyses.

Age

Age was assessed by asking participants, “How old are you right now?” Participants were placed into one of three age group categories: (a) 14–17 years old, (b) 18–21 years old, and (c) 22–24 years old.

Race/Ethnicity

Participant’s race was collected via the following question: “How do you describe your race? [Choose all that apply].” Response options included (1) American Indian or Alaska Native, (2) Black or African American, (3) Asian, (4) Native Hawaiian or Other Pacific Islander, (5) White, (6) Not listed, and (7) Prefer not to answer. Participants who selected more than one option were categorized as (8) Multiracial (Cheng & Lee, 2009; Holmes, 1997). Due to the small sample size, those who selected (4) and (6) were dropped from the analytic sample. Latinx Ethnicity was assessed with the question “Are you of Hispanic, Latinx, or Spanish origin?” Response options included (1) Yes, (2) No, and (3) Prefer not to answer. Participants who responded “Yes” to the Latinx ethnicity question were categorized as “Hispanic/Latinx” regardless of which options they selected for the race question. Thus, race/ethnicity was collapsed into six analytic groups: (1) White, (2) American Indian/Alaska Native, (3) Asian, (4) Black or African American, (5) Hispanic/Latinx, and (6) Multiracial.

Sexual Orientation

Sexual orientation was assessed by asking participants, “Which of the following best describes your sexual orientation at this time? [Choose all that apply].” Response options included (1) Asexual or asexual spectrum, (2) Bisexual or pansexual, (3) Gay or lesbian, (4) Straight (heterosexual), (5) Queer, (6) Questioning my sexual orientation, (7) Not listed, and (8) Prefer not to respond. Individuals who responded “Not listed” were asked to provide a write-in response. For individuals who selected more than one option, we then asked “If you could only pick one term to describe your sexual orientation, which would you pick?” and assigned their sexual orientation based on their specified selection among the first seven options listed above.

Gender Identity

Gender identity was assessed by asking, “Which of the following terms best describes your gender at this time? [Choose all that apply].” Response options included (1) Woman/Girl, (2) Man/Boy, (3) Two-spirit, (4) Non-binary, (5) Agender, (6) Genderqueer, (7) Questioning my gender identity, (8) Not listed, and (9) Prefer not to respond. Individuals who responded “Not listed” were asked to provide a write-in response and placed in another gender identity group based on their response where possible (n = 18).

Gender Modality

First, participants were asked “Some people use the term transgender to describe themselves when their gender does not align with the sex they were assigned at birth. Do you identify as transgender?” Response options included (1) Yes, (2) No, (3) Prefer not to respond, (4) I’m not sure if I identify as transgender, and (5) I’m not sure what this question is asking. Using responses to this question and the Gender Identity question, we constructed the Gender Modality variable including (1) Cisgender, (2) Trans and gender diverse, and (3) Not sure. Specifically, individuals who reported their Gender Identity as “man/boy” and “women/girl” and did not report a transgender gender modality were categorized as cisgender.

Data Cleaning and Analytic Sample

In total, 2395 eligible individuals provided informed consent. After thorough data cleaning procedures were implemented: participants who missed attention check questions, provided inconsistent demographic identities between the screening and main survey, or duplicate or invalid email addresses (n = 1191), and those who did not complete the survey (n = 149) were excluded, resulting a final sample of 1055. For this study, we excluded participants who reported never having at least one drink of alcohol in their life (n = 298); missing values (n = 7); response options of “Not listed” (n = 12), “Prefer not to answer” or “Don’t know” (n = 49); “Native Hawaiian or other Pacific Islander” for race/ethnicity (n = 4); and “Two-spirit” for gender identity (n = 3), resulting in a final analytic sample of 736.

Statistical Analyses

Data cleaning, recoding, and statistical analyses were conducted in RStudio version 4.2.1 (RStudio, Boston, MA). Frequencies and percentages were calculated for categorical variables (Table 2). Multinomial logistic regression models were developed to estimate the associations between predictor variables (off-premises and on-premises delivery policy) and each of categorical outcomes: (1) current alcohol use and (2) binge drinking (Tables 3 and 4). p-values, X2, and McFadden R2 were reported to determine the goodness of fit for models. Demographics including age, race/ethnicity, sexual identity, gender identity, and gender modality were adjusted for each of the models. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were calculated for all regression models.

Table 2.

Participant characteristics

Demographics (n = 736) n (%)
Age, years
 14–17 68 (9.2)
 18–21 345 (46.9)
 22–24 323 (43.9)
Race/ethnicity
 White 176 (23.9)
 American Indian or Alaska Native 69 (9.4)
 Asian 47 (6.4)
 Black 120 (16.3)
 Hispanic/Latinx 250 (34.0)
 Multiracial 74 (10.1)
Sexual identity
 Straight 145 (19.7)
 Asexual/ace spectrum 27 (3.7)
 Bisexual/pansexual 264 (35.9)
 Gay/lesbian 164 (22.3)
 Queer 120 (16.3)
 Questioning 16 (2.2)
Gender
 Woman/girl 365 (49.6)
 Agender 6 (0.8)
 Gender queer 26 (3.5)
 Man/boy 191 (26.0)
 Non-binary 122 (16.6)
 Questioning 26 (3.5)
Gender modality
 Cisgender 469 (63.7)
 Not sure 30 (4.1)
 Trans and gender diverse 237 (32.2)
Alcohol policies
 On-premises delivery 621 (84.4)
 Off-premises delivery 577 (78.4)
Outcomes
  Alcohol use in 30 days
 No alcohol use 30 days 228 (31.0)
 Current heavy drinking 83 (11.3)
 Current light drinking 425 (57.7)
 Binge drink in 30 days
 Current binge drinking 263 (35.7)
 Not current drinking 228 (31.0)
 Not current binge drinking 245 (33.3)
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Table 3.

Multinomial logistic regression: associations between current alcohol use and alcohol delivery policies

Current light drinking vs. no alcohol use in 30 days Current heavy drinking vs. no alcohol use in 30 days
Predictors aOR 95% CI aOR 95% CI
(Intercept) 3.34 1.56, 7.14 1.22 0.4, 3.67
Policies
 On-premises delivery 0.60 0.34, 1.06 0.51 0.22, 1.17
 Off-premises delivery 1.93 1.24, 3.01 1.96 0.97, 3.95
Demographics
Age, years
 22–24 Ref
 14–17 0.10 0.05, 0.19 0.03 0.01, 0.15
 18–21 0.47 0.32, 0.69 0.19 0.11, 0.35
Race/ethnicity
 White Ref
 American Indian or Alaska Native 0.76 0.36, 1.60 – –
 Asian 0.94 0.44, 2.03 1.37 0.62, 3.02
 Black 1.10 0.61, 1.97 1.34 0.55, 3.25
 Hispanic/Latinx 1.09 0.67, 1.75 1.67 0.58, 4.80
 Multiracial 0.90 0.46, 1.76 3.45 0.60, 19.92
Sexual identity
 Straight Ref
 Asexual/ace spectrum 0.25 0.09, 0.69 – –
 Bisexual/pansexual 1.31 0.78, 2.19 1.37 0.62, 3.02
Gay/lesbian 1.56 0.88, 2.76 1.34 0.55, 3.25
 Queer 1.95 0.98, 3.87 1.67 0.58, 4.80
 Questioning 1.45 0.38, 5.46 3.45 0.60, 19.92
Gender identity
 Woman/girl Ref
 Agender 2.51 0.31, 20.20 – –
 Gender queer 1.15 0.40, 3.30 2.53 0.44, 14.61
 Man/boy 0.80 0.50, 1.28 1.46 0.72, 2.94
 Non-binary 1.38 0.66, 2.88 2.10 0.58, 7.61
 Questioning 4.66 0.35, 62.72 1.84 0.09, 36.71
Gender modality
 Cisgender Ref
 Trans and gender diverse 0.51 0.28, 0.94 0.36 0.12, 1.06
 Not sure 0.11 0.01, 1.24 0.39 0.03, 5.74
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“–” Unstable estimates due to small sample cells. Log-likelihood: − 606.75; McFadden R2: 0.10997; likelihood ratio test: χ2 = 149.93 (p < 0.0001). aOR is adjusted odds ratio; 95% CI is 95% confidence intervals. Boldface indicates statistical significance at p < 0.05

Table 4.

Multinomial logistic regression: associations between binge drinking and alcohol delivery policies

Not current binge drinking vs. current binge drinking Not current drinking vs. current binge drinking
Predictors aOR 95% CI aOR 95% CI
(Intercept) 1.01 0.47, 2.18 0.46 0.2, 1.05
Policies
 On-premises delivery 1.31 0.74, 2.33 1.99 1.06, 3.71
 Off-premises delivery 0.80 0.49, 1.31 0.46 0.28, 0.77
Demographics
Age, years
 22–24 Ref Ref
 14–17 2.25 0.84, 6.03 18.70 7.63, 45.82
 18–21 1.14 0.79, 1.66 2.64 1.74, 4.02
Race/ethnicity
 White Ref Ref
 American Indian or Alaska Native 0.47 0.22, 1.03 0.92 0.41, 2.03
 Asian 1.23 0.53, 2.85 1.41 0.56, 3.54
 Black 0.61 0.34, 1.11 0.72 0.37, 1.37
 Hispanic/Latinx 0.63 0.38, 1.03 0.78 0.45, 1.33
 Multiracial 0.68 0.34, 1.36 0.88 0.41, 1.89
Sexual identity
 Straight Ref Ref
 Asexual/ace spectrum 0.73 0.17, 3.19 4.13 1.25, 13.62
 Bisexual/pansexual 1.35 0.79, 2.30 0.88 0.50, 1.56
 Gay/lesbian 0.87 0.48, 1.56 0.62 0.33, 1.15
 Queer 1.16 0.59, 2.29 0.56 0.26, 1.19
 Questioning 1.53 0.42, 5.58 0.74 0.17, 3.24
Gender identity
 Woman/girl Ref Ref
 Agender – – – –
 Gender queer 0.11 0.03, 0.47 0.32 0.10, 1.01
 Man/boy 0.65 0.40, 1.07 0.93 0.56, 1.55
 Non-binary 0.81 0.34, 1.90 0.63 0.26, 1.52
 Questioning – – – –
Gender modality
 Cisgender Ref Ref
 Trans and gender diverse 2.03 0.98, 4.17 2.98 1.45, 6.14
 Not sure – – – –
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“–” Unstable estimates due to small sample cells. Log-likelihood: − 726.32; McFadden R2: 0.10035; likelihood ratio test: χ2 = 162.03 (p < 0.0001). aOR is adjusted odds ratio; 95% CI is 95% confidence intervals. Boldface indicates statistical significance at p < 0.05

Results

The analytic sample was highly diverse (Table 2): by race/ethnicity, 34.0% of participants identified as Hispanic/Latinx, followed by 23.9% White, 16.3% Black/African American, 10.1% Multiracial, 9.4% American Indian/Alaska Native, and 6.4% Asian. By sexual identity, a plurality identified as bisexual/pansexual (35.9%), with 22.3% identifying as gay/lesbian, and 19.7% identifying as straight (n = 145). By gender modality, the majority of participants identified as cisgender (63.7%), with 32.2% identifying as transgender or gender diverse.

At the time of the survey, the majority of participants lived in states where on-premises delivery was allowed (84.4%), and 78.4% of participants lived where off-premises delivery was permitted. 48 states were represented in the sample, excluding Wyoming and Vermont.

Among those who reported lifetime alcohol use, 57.7% were current light drinkers and 11.3% were heavy drinkers. Further, 35.7% reported current binge drinking.

Multinomial Logistic Regression Analyses

Current Alcohol Use

Current alcohol use was explored with three levels: no alcohol use (reference group), current light drinking, and current heavy drinking. Off-premises and on-premises delivery policies and demographics were used as independent variables (Table 3). Overall, the data fit the model well (X2 = 149.93, p < 0.01; McFadden R2 = 0.11).

The adjusted odds of light drinking among YYA who live in a state with an off-premises delivery policy were nearly twice that of YYA who have no off-premises delivery (aOR = 1.93; 95% CI = 1.24, 3.01). However, no association was found for YYA who reported current heavy drinking. Furthermore, YYA who reported current light alcohol use were less likely to be between the ages of 14–17 (aOR = 0.10; 95% CI = 0.05, 0.19) and 18–21 (aOR = 0.47; 95% CI = 0.32, 0.69), than between the ages of 22–24. Similarly, those categorized as current heavy drinkers were more likely to be older. Compared to non-users, current light drinkers were less likely to identify as asexual or on the ace spectrum (aOR = 0.25; 95% CI = 0.09, 0.69) and were less likely to identify as transgender or gender diverse (aOR = 0.51; 95% CI = 0.28, 0.94). These same associations did not appear for current heavy drinking compared to non-users. No statistically significant associations appeared based on race/ethnicity and current alcohol use rates.

Binge Drinking

Binge drinking was explored with three levels: current binge drinking (reference group), no current drinking, and not current binge drinking. Off-premises and on-premises delivery policies and demographics were used as independent variables (Table 4). Overall, the data fit the model well (X2 = 162.03, p < 0.01; McFadden R2 = 0.10).

Compared to YYA who reported current binge drinking, those who reported not current binge drinking were less likely to identify as gender queer (aOR = 0.11; 95% CI = 0.03, 0.47) compared to their woman/girl peers. No differences were found by policies.

Compared to YYA who reported current binge drinking, those who reported not current drinking were more likely to live in a state with on-premises delivery (aOR = 1.99; 95% CI = 1.06, 3.71) and less likely to live in a state with off-premises delivery (aOR = 0.46; 95% CI = 0.28, 0.77). Participants who identified as trans and gender diverse were more likely to report not current drinking compared to those who identified as cisgender (aOR = 2.98; 95% CI = 1.45, 6.14).

Compared to YYA who did not report current drinking, those who reported current binge drinking were more likely to live in a state with off-premises delivery (aOR = 2.16; 95% CI = 1.31, 3.59) and less likely to live in a state with on-premises delivery (aOR = 0.50; 95% CI = 0.27, 0.94). Those who reported current alcohol use, but did not report binge drinking, when compared to those who reported no current alcohol use at all, were more likely to live in a state with off-premises delivery only (aOR = 1.73; 95% CI = 1.06, 2.84). YYA who reported binge drinking were less likely to be in a younger age group. Similarly, those who reported current drinking but not binge drinking were also less likely to be in a younger age group. YYA who identified as asexual were less likely to report current binge drinking than those who identified as straight (aOR = 0.24; 95% CI = 0.07, 0.80) and less likely to report not current binge drinking than those who identified as straight (aOR = 0.18; 95% CI = 0.05, 0.65). YYA who identified as transgender/gender diverse were less likely to report current binge drinking when compared with those who identified as cisgender (aOR = 0.34; 95% CI = 0.16, 0.69).

Discussion

This study is one of the first to characterize the associations between alcohol policy change and alcohol use among youth and young adults during the COVID-19 pandemic. Results are critical, as many of these policies are likely to remain in effect post-pandemic, and therefore appropriate interventions to support populations disproportionately impacted by these policies may be needed.

Off-premises delivery (e.g., from a liquor store) appeared to be more influential on YYA’s alcohol use than on-premises delivery (e.g., from a restaurant). Specifically, on-premises delivery had few significant associations with alcohol consumption patterns in YYA: There were no significant associations found in the case of current alcohol use with on-premises delivery. Further, compared to YYA who did not report current drinking, those who reported current binge drinking were less likely to live in a state with on-premises delivery. One reason for this may be due to the details of some on-premises delivery policies. Many states with on-premises delivery policies require customers to order food (National Institute of Alcohol Abuse and Alcoholism, 2022). This may have promoted more responsible drinking habits: for example, ordering a bottle of wine to accompany dinner for delivery versus having a case of wine delivered directly from a retailer, as may occur in an off-premises delivery state. The high cost of food delivery in most areas also may have limited binge drinking in states with on-premises delivery. In this sense, on-premises delivery’s negative association with current binge drinking may indicate that the availability of on-premises delivery could lead to more moderate consumption habits. Further investigation which focuses on the effects of variation within on-premises delivery may help to elucidate these exact mechanisms.

Off-premises delivery policy, however, seems to have had a larger impact on YYA alcohol use. Compared to YYA who reported current binge drinking, those who did not report current drinking were less likely to live in a state with an off-premises delivery policy. This may reflect that the ease of bulk delivery enabled with off-premises delivery facilitates binge drinking. This corresponds with previous research that says that, while binge drinking was a largely social activity among YYA pre-pandemic (Chung et al., 2018), solitary binge drinking during COVID-19 became more common among this population (Jackson et al., 2021). In this sense, off-premises alcohol delivery may have been a highly feasible option for those looking to binge drink in isolation during a period of social distancing. YYA who live in a state with an off-premises delivery policy were also more likely to have reported being a current light drinker than those in states where off-premises delivery is not permitted. However, despite positive associations between both current light or heavy drinking and off-premises delivery policy compared to no alcohol use, this association was only statistically significant for the current light drinking group. Perhaps this could mean that YYA who already heavily drink had access to alcohol regardless of delivery policy, though those who only consumed alcohol lightly may have been more influenced by alcohol delivery. Further exploration with a more robust sample size, complemented by qualitative work, will be needed to fully understand this phenomenon.

Results confirmed that younger age groups were less likely to use alcohol. This makes sense given the legal drinking age. This also suggests that, while alcohol delivery services may not enforce age restrictions as tightly as on-premise sales do considering the challenges of online age verification (Colbert et al., 2021), this influence is not enough to remove the association of age and alcohol use altogether. Even requiring a debit/credit card in order to use a service may be a unique prevention barrier for youth who do not have this payment method, regardless of the legal drinking age. Ensuring that delivery agencies are transparent on billing services about alcohol sales may help strengthen this age-based prevention barrier. The cost and affordability of alcohol delivery services might be another factor that impacted drinking behavior, particularly among younger age groups (Laixuthai & Chaloupka, 1993; Xu & Chaloupka, 2011).

While many expected patterns were shown in the models, the lower rates of current binge drinking in transgender and gender diverse populations compared to those who identified as cisgender was unexpected, given known disparities (Andrzejewski et al., 2022). This initially appears to contradict existing research which finds a higher prevalence of binge drinking in this group (Day et al., 2017; Gilbert et al., 2018). However, pandemic-era research has found conflicting evidence of binge drinking (Some et al., 2022), perhaps related to changing social dynamics and reduced instances of group alcohol use events seen during COVID-19-related shut downs (Lundahl & Cannoy, 2021). In other words, with a lack of access to bars and clubs, some groups of YYA may have been isolated away from alcohol. This result may also be attributable to the nature of our sample: there was a higher proportion of transgender and gender diverse YYA represented in the youngest age group (12.2% were between 14 and 17 compared to 7% of cisgender YYA). As such, the lower rates of alcohol use in the 14–17 year age group may explain this discrepancy. Further longitudinal investigation into alcohol use patterns during and after the pandemic will be needed to fully characterize disparities.

Limitations

This study is not without limitations. We did not collect data on participants’ methods of alcohol purchase. We acknowledge that the availability of alcohol delivery services does not necessarily reflect actual utilization. Thus, we are limited in our ability to capture the impact of delivery policies on alcohol consumption among YYA. For example, delivery policies that required food purchases with alcohol were not considered in the study design. Further analyses should also include participants’ access to alcohol purchases, locations of alcohol use, and sources of alcohol. For example, for participants aged 21 or above, we should collect information on whether they engaged in self-purchase or received alcohol through others such as family members or friends.

Our analyses on the availability of off-premises and on-premises delivery policies across states were aggregative, potentially overlooking differences in rules and regulations by state. For example, online age verification was required for on-premise delivery policies; however, specific age verification systems varied by state, which would differentially impact YYA. Additionally, some states like Kansas and South Dakota only permit the delivery of wine from wineries, while others such as Indiana and Michigan allow the delivery of all categories of alcohol, which may have a differential impact on alcohol use behaviors (Colbert et al., 2021).

This is a cross-sectional study, and as such, we are unable to ascertain causation or temporality. Furthermore, while this sample is national, it is not necessarily representative of the U.S. population, and in fact, minoritized populations were oversampled. To ensure a diverse representation of demographic identities, we set a minimum cell size of 5 for each group in our analyses; however, that may have led to unstable estimates. This was a web-based survey, indicating that some populations, including those without access to the internet, were not included. Our online data collection tool may introduce recall and social desirability biases. Finally, because of some diversity in alcohol policy smaller than the state level (i.e., dry counties and townships with their own alcohol control commissions), it is possible that some participants are in a location with a policy different from the broader state in which they live, and therefore are incorrectly categorized. However, given the size of the sample, we are confident that this possibility would not affect overall results.

Conclusions

In conclusion, variations in alcohol control policy were associated with differential alcohol use patterns in a diverse sample of YYA. While off-premises delivery was associated with higher rates of current alcohol use and binge drinking, on-premises delivery policy may be associated with more moderation in consumption. Thoroughly characterizing potential methods to reduce alcohol misuse at a structural level is of the utmost importance, and further longitudinal investigation should be done to see if these associations hold true post-COVID-19 pandemic. Further research into the drivers of alcohol consumption among minoritized groups (e.g., LGBTQ + youth) is necessary to end temporary measures in favor of permanent, effective policy enactment to reduce the harms caused by alcohol to YYA populations.

Footnotes

Ethics Approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. All study procedures have been reviewed and approved by the Northwestern University Institutional Review Board.

Consent to Participate Informed consent was obtained for all research participants prior to their participation in this study, including consent to distribute deidentified results in a published journal article. A waiver of parental consent was obtained for participants under 18.

Conflict of Interest The authors declare no competing interests.

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