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. Author manuscript; available in PMC: 2023 Nov 1.
Published in final edited form as: Alcohol Clin Exp Res. 2022 Sep 23;46(11):2068–2076. doi: 10.1111/acer.14937

A national assessment of on-premise drinking establishments near public universities: Drink prices, drink specials, indoor tobacco use, and state-level alcohol laws

C R LoParco 1, A Walker 2, M D Livingston 2, B Khoshhal 3, K M Gonzalez-Pons 4, E Soule 5, R Treffers 6, M E Rossheim 1
PMCID: PMC9743012  NIHMSID: NIHMS1848503  PMID: 36098371

Abstract

Background:

Inexpensive drinks and price promotions increase alcohol consumption and have been observed at on-premise drinking establishments near large colleges. Some bars may sell tobacco products and allow indoor tobacco use to encourage patrons to stay and drink more. This study examined drink prices/specials and associated practices of on-premise drinking establishments including tobacco sales and policies regarding tobacco use.

Methods:

In 2018, telephone calls about prices/practices were made to 403 randomly selected bars/nightclubs within 2 miles of large residential universities in each U.S. state. The Alcohol Policy Information System provided data on state-level alcohol laws. Multivariable linear and logistic regression models examined associations between alcohol prices/specials, state laws, and establishment practices.

Results:

The average price for the least expensive draft beer and a vodka shot at each location were $3.62 (SD=$1.15) and $4.77 (SD=$1.16), respectively. Most establishments (65%) had happy hour specials, 6% had 2-for-1 specials, 91% sold food, 9% sold cigarettes, 8% allowed smoking indoors, and 18% permitted electronic cigarette (e-cigarette) use indoors. Allowing e-cigarette use indoors (b=−0.54) and selling cigarettes (b=−0.79) were associated with lower vodka prices; allowing cigarette smoking indoors (b=−0.46) was associated with lower beer prices. Lower beer prices (OR=1.38), selling food (OR=2.97), and no state law banning happy hour specials altogether (OR=4.24) or with full day price reduction exemptions (OR=12.74) were associated with higher odds of having happy hour specials. Allowing e-cigarette use indoors was associated with having 2-for-1 specials (OR=6.38).

Conclusion:

In bars near large public universities, beers and shots were often available for less than $5 and drink specials were prevalent. Further, some establishments allowed tobacco use indoors and/or sold cigarettes. Laws that increase alcohol taxes, set minimum drink prices, and ban the sale and indoor use of tobacco products at on-premise drinking locations are important harm reduction tools.

Keywords: Alcohol, Price, Law, Happy Hour, Tobacco

Introduction

Young adults (18 – 22 years old), especially college students, frequently drink alcohol and engage in heavy episodic drinking (HED), i.e., drinking ≥ 5 drinks for males or ≥ 4 drinks for females on one occasion (Substance Abuse and Mental Health Services Administration (SAMHSA), 2020). Specifically, in 2019, one-third of college students engaged in HED during the past month, compared to 27% of their non-college peers (Substance Abuse and Mental Health Services Administration (SAMHSA), 2020). This prevalence represents cause for concern because of the many negative consequences associated with HED, including missed classes and lower grades, violence and physical injuries, regretted sex and sexual assaults, blackouts, and alcohol poisoning (Trangenstein et al., 2019, White and Hingson, 2013).

There have been numerous studies examining associations between on-premise drinking establishments and public health outcomes (e.g., alcohol use, violence; (Gruenewald et al., 2014, Gruenewald et al., 2006, Graham and Homel, 2012). On-premise drinking establishments (e.g., bars and restaurants) are places where people can both purchase and consume alcohol, and they are associated with heavy alcohol consumption and alcohol-related consequences, particularly among college students (Scribner et al., 2008, Toomey et al., 2007, Weitzman et al., 2003). Alcohol-related consequences resulting from HED in on-premise drinking establishments include neighborhood disruptions, vandalism, aggression, sexual assault, pedestrian injury, and an increased prevalence of driving while under the influence of alcohol (Stevenson, 1996, Toomey et al., 2007, Wechsler et al., 2002, Wilkinson and Livingston, 2012).

Increased alcohol consumption in on-premise drinking establishments and associated negative consequences are likely facilitated by the frequent drink specials offered at on-premise drinking establishments (Kuo et al., 2003, Thombs et al., 2008). Previous research suggests that inexpensive alcohol and drink specials are offered at on-premise drinking establishments near college campuses (O’Mara et al., 2009, Thombs et al., 2008, Thombs et al., 2009). However, these data were limited to a single college bar district and were collected in 2006 and 2007. Other research demonstrates the presence of drink specials in both on- and off-premise drinking establishments using a sample of colleges across 38 states, however these data are more than two decades old (Kuo et al., 2003). Thus, more recent data on drink prices and drink specials in on-premise drinking establishments near colleges across the U.S. is needed.

Drink specials reduce drink prices, thereby promoting heavy alcohol consumption, particularly among college students who have relatively little disposable income (Chaloupka, 1996, Chaloupka et al., 2002, Kuo et al., 2003, O’Mara et al., 2009, Österberg, 1995, Thombs et al., 2008, Thombs et al., 2009). Several research reviews suggest that policies restricting drinking specials may reduce alcohol use (Toomey et al., 2007, Toomey and Wagenaar, 1999) and that these restrictions on drink specials may be supported by public opinion (Wagenaar et al., 2000). However, there is limited research examining the associations between laws restricting drinking specials and the presence of drink specials. One study conducted in a small sample of pubs and clubs in Australia indicated that many of these venues breached the happy hour restrictions (Jones and Lynch, 2007). It is essential to understand the associations between laws restricting drink specials and the presence of these drink specials in the U.S. to inform future policy development, implementation, and enforcement.

At the population-level, systematic reviews and meta-analyses have shown that higher alcohol prices (and taxes) are associated with reduced alcohol consumption and alcohol-related morbidity and mortality (Wagenaar et al., 2009, Wagenaar et al., 2010). Despite their effectiveness at reducing population-level alcohol consumption and related harm, federal and state taxes on alcohol are generally low and their impact is diminished over time because they infrequently increase and do not adjust for inflation (Xu and Chaloupka, 2011). Regardless of the public health importance of alcohol prices and related drinking behaviors and outcomes, there is limited information on the price of drinks sold at on-premise drinking establishments, including bars, restaurants, and nightclubs. This may be due to the notable challenges in documenting the prices of drinks sold at on-premise drinking establishments, including a lack of barcodes, fluctuations through the day, and changes due to drink specials (Ruhm et al., 2012).

Numerous studies show associations between alcohol consumption and tobacco use among college students (Dierker et al., 2006, Reed et al., 2007, Samuolis et al., 2021, Rossheim, 2013, Hiler et al., 2020). These associations have also been observed in on-premise drinking locations (Jiang and Ling, 2013, Rossheim, 2013). Specifically, studies utilizing convenience samples have indicated that bar attendance and alcohol intoxication levels are associated with increased odds of same-night smoking and lower odds of quitting smoking among young adults (Rossheim, 2013, Jiang and Ling, 2013), potentially due to cravings for smoking while drinking (Hiler et al., 2020). Fewer studies have examined electronic cigarette (e-cigarette) use (i.e., vaping) in the context of on-premise drinking establishments. Limited research indicates that while drinking alcohol, college students report greater cravings for, and pleasure from, smoking than from using e-cigarettes (Hiler et al., 2020). However, there is scant research examining establishment-level associations between cigarette sales or permissive indoor tobacco use and drink pricing or specials. This is an important consideration for public health, as permissive tobacco use may be an important risk factor for heavy drinking in on-premise establishments (Rossheim, 2013, Picone et al., 2004, Gallet and Eastman, 2007, Jiang and Ling, 2013).

Given that college students often have limited disposable incomes, low prices for food and alcohol generally appeal to college students (Montalto et al., 2019). On-premise drinking establishments may sell food to 1) supplement low revenue from selling inexpensive alcohol or 2) capitalize on expectancies. For example, patrons may have expectancies of needing to consume more alcohol to obtain their desired intoxication level after consuming food, which affects alcohol metabolism (Ramchandani et al., 2001). However, college students often restrict caloric intake when drinking, either for concerns about weight gain or to get drunk faster (Giles et al., 2009). Thus, not all patrons of these establishments may decide to consume food but instead may take advantage of the drink specials.

Understanding the price of alcohol sold at on-premise locations is important. Price is a modifiable risk factor that is strongly associated with alcohol consumption and related harms and can be a powerful policy lever for harm reduction (Wagenaar et al., 2009, Wagenaar et al., 2010). Given the associations between alcohol outlet density and alcohol consumption, alcohol consumption is likely to be higher in areas with a greater outlet density due, in part, to increased competition driving down prices (Chen et al., 2009, Treno et al., 2013, Gruenewald et al., 1993, Gruenewald et al., 2014). The purpose of this study was to describe drink prices and specials at on-premise drinking establishments near large public universities in the U.S. This study also aimed to examine associations between statewide laws on drink specials, establishment practices (i.e., indoor tobacco use and food and cigarette sales), and drink prices/specials in on-premise drinking locations. In line with the theoretical model described in (Gruenewald, 2007), niche markets exist which utilize social stratification processes; these niche markets (e.g., bars) may increase alcohol-related problems. Moreover, the regulatory environment in these bars (e.g., restrictions on drink specials) are associated with alcohol-related outcomes (Graham and Homel, 2012). As such, it is important to understand factors of these niche markets, such as indoor tobacco use and retail of other products, that may affect drink prices and therefore patrons’ risk of becoming heavily intoxicated.

Materials and Methods

Study Sample

The current study focused on on-premise drinking establishments near the three largest in-person residential four-year public colleges in each U.S. state (n = 145 because some states did not have three four-year public colleges). Public universities were chosen because of the distinct experiences (Aries and Seider, 2007) as well as the less expensive financial costs compared to private universities (Baum and Ma, 2010). Thus, it is plausible that on-premise drinking locations surrounding public universities offer less expensive alcohol compared to those near private universities. Between October 2017 and January 2018, trained research assistants used Google Maps to search for “bars and nightclubs near [University name]”. Similar to (Kuo et al., 2003, Wagoner et al., 2018), inclusion criteria included being within two miles of one of the 145 college campuses. In addition, establishments were required to be open past midnight at least one day of the week and have a phone number listed. Given the inclusion criteria, restaurants could have been included in the sample; however, the search terms used in Google likely resulted in fewer restaurants relative to other on-premise drinking establishments.

The number of on-premise drinking establishments within two miles of a college ranged from one (e.g., Bismarck State College, ND) to 70 (e.g., The University of Texas at Austin, TX). Three colleges were excluded because they did not have any bars listed within two miles (Castleton University and Vermont Technical College, VT; University of Rhode Island, RI). The final sampling frame consisted of 2,297 on-premise drinking establishments. For each college, four on-premise drinking establishments were randomly selected using a random number generator. If there were four or fewer establishments near a college, all were selected. This sampling mechanism was chosen to aim to have a similar representation of on-premise drinking locations near large universities in each state. Randomly selected establishments (n = 542) were called between February 12th and 25th, 2018. Each establishment was called a maximum of 3 times. Calls typically lasted between 1 and 5 minutes. Of the 542 bars that were called, 422 (77.9%) answered the phone; overall, 403 (74.4%) of the 542 bars that were called answered the phone, sold alcohol and provided answers to questions relating to drink prices, drink specials, and establishment practices, thus comprising the analytic sample. This study was considered “not human subjects research” by the University’s Institutional Review Board because all survey questions pertained to business practices (i.e., drinks specials and prices, indoor tobacco use, and sale of food and cigarettes).

Measures

On-Premise Alcohol Establishment Prices and Practices.

During phone calls with on-premise establishments, researchers first verified the name of the drinking establishments that they contacted. Next, researchers asked a series of standardized questions pertaining to vodka prices, beer prices, indoor tobacco use, and whether they had happy hour drink specials, 2-for-1 drink specials, and food or cigarettes for sale. Drink prices were recorded in dollars. Responses to all other questions were coded as Yes = 1 or No = 0. Vodka and beer prices were assessed by asking “When you don’t have a drink special going, how much does a shot of your least expensive vodka cost?” and “When you don’t have a drink special going, how much does your least expensive draft beer cost?”, respectively. The price of vodka shots was assessed because these are sold in relatively consistent volume (1.5 oz) and proof (80) compared to other alcoholic beverage types (O’Mara et al., 2009, Clapp et al., 2007), which helps provide a more consistent indicator of price between establishments.

Presence of a happy hour special was measured by asking “Do you have happy hour on any days of the week?” where happy hour refers to having reduced prices during certain hours. Availability of 2-for-1 specials was measured by asking “Do you have two-for-one drink specials on any days of the week?” meaning selling multiple servings for the price of a single serving. Retail of food and/or tobacco were assessed by asking “Do you sell food?” and “Do you sell cigarettes or have a cigarette vending machine?” Indoor tobacco use practices were assessed by asking “Is smoking cigarettes allowed inside?” and “What about electronic cigarettes, can those be used inside?”

State-Level Drink Special Laws.

State-level laws for restrictions on happy hour and 2-for-1 drink specials were taken from the ‘Drink Specials’ topic in the Alcohol Policy Information System (Alcohol Policy Information System, 2018). In keeping with the timing of survey data collection, these variables were coded based on state laws in 2018. State restrictions on happy hours were coded as: none, restricted, banned but full day price reductions allowed, or completely banned. State restrictions on 2-for-1 drink specials were coded as Yes or No.

Analyses

First, descriptive analyses of drinking establishment practices were conducted. Specifically, the mean price for the cheapest vodka and cheapest beer were calculated. The proportion of drinking establishments with happy hours, 2-for-1 drink specials, retail sale of food and/or tobacco, allowance of indoor cigarette smoking, and allowance of indoor e-cigarette smoking were calculated. SAS survey procedures were used to cluster the standard errors at the university level.

Next, a series of multivariable linear regression models were used to estimate the associations between drinking establishment practices and vodka and beer prices. All drinking establishment practices were entered into the model simultaneously. In addition to the predictors of interest, state fixed effects were included in the models for price to account for state-specific laws (taxation, on-premise alcohol regulations, etc.) that may drive price independent of establishment characteristics.

Similar logistic regression models estimated the associations between drinking establishment practices and the presence of happy hour or 2-for-1 drink specials. Models for drink specials included the price of beer and vodka as predictors since the baseline price of alcohol may drive establishment choices with respect to drink specials. State fixed effects were not able to be included in the models for drink specials due to convergence issues. As an alternative, models controlled for the corresponding state-specific laws most likely to impact the presence of each type of drink special: restrictions on happy hour specials and restrictions on 2-for-1 drink specials. Refer to Appendix 1 for specific model equations. To account for non-independence, all regression models were estimated as generalized estimating equations, clustering the standard error at the university level. To test the robustness of our findings, we performed a series of sensitivity analyses. While the number of sampled outlets per university was unrelated to our outcomes, to account for potential endogeneity due to outlet density, we re-ran all analyses controlling for the number of outlets per university. To account for potential bias due to missingness of our outcomes and predictors (0%–9%), we performed multiple imputation analyses using 100 imputations.

Results

The average price for a drinking establishment’s least expensive draft beer was $3.62, while the least expensive shot of vodka was $4.77. Most drinking establishments (65%) had happy hour specials, while relatively few (6%) had 2-for-1 drinking specials. Most drinking establishments (91%) sold food, while a minority (9%) sold cigarettes on-premise. Most establishments did not allow smoking or e-cigarette use indoors, however permissive indoor e-cigarette use (18%) was more common than permissive indoor cigarette use (8%) (Table 1). Tables 2 and 3 provide information on reported drink specials by state laws.

Table 1.

Drinking Establishment Practices and Alcohol Prices

Average Cost (SE) or N (%) Range
Drink Prices (least expensive)
Draft Beer (n = 397) $3.62 ($1.15) $1.25 – $7.50
Shot of Vodka (n = 382) $4.77 ($1.16) $1.83 – $10.00
Drink Specials
Happy hour (n = 403) 261 (64.76%)
2-for-1 (n = 402) 25 (6.22%)
Establishment Practices
Served food (n = 402) 365 (90.80%)
Allowed smoking indoors (n = 401) 31 (7.73%)
Allowed e-cigarettes (n = 396) 71 (17.93%)
Sold cigarettes on premise (n = 396) 36 (9.09%)
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Note: 82% of locations had draft beer for < $5; 44% of locations had a shot of vodka for < $5; 41% had both draft beer and a shot of vodka for < $5.

Table 2.

Happy Hour Laws versus Reported Happy Hour Drink Specials

Reported No Happy Hour Drink Special Reported Having a Happy Hour Drink Special Total
No Happy Hour Restriction 83 (20.60%) 184 (45.66%) 267 (66.25%)
Happy Hour Restriction 17 (4.22%) 59 (14.64%) 76 (18.86%)
Happy Hours Banned, Full Day Reduction Permitted 25 (6.20%) 6 (1.49%) 31 (7.69%)
Happy Hours Completely Banned 17 (4.22%) 12 (2.98%) 29 (7.20%)
Total 142 (35.24%) 261 (64.76%) 403
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Table 3.

2-for-1 Laws versus Reported 2-for-1 Drink Specials

Reported No 2-for-1 Drink Special Reported Having a 2-for-1 Drink Special Total
No Legal Restriction on 2-for-1 Sales 229 (56.97%) 21 (5.22%) 250 (62.19%)
2-for-1 Sales Legally Restricted 148 (36.82%) 4 (1%) 152 (37.81%)
Total 377 (93.78%) 25 (6.22%) 402
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Note: One location was missing information regarding the presence of 2-for-1 specials, thus the sample size is 402.

Tobacco-related practices were significantly associated with alcohol price. The price of the least expensive shot of vodka was, on average, lower in establishments that allowed the use of e-cigarettes indoors (b = −0.54, 95% CI [−1.02, −0.06]) or that sold cigarettes (b = −0.79, 95% CI [−1.15, −0.42]). The price of the least expensive draft beer was lower in establishments that allowed cigarette smoking indoors (b = −0.46, 95% CI [−0.91, −0.01]). However, there were no statistically significant associations between either vodka or beer prices and whether an establishment sold food (Table 4).

Table 4.

Multivariable Logistic and Linear Regression Models

Vodka Price
(n = 382)		 Beer Price
(n=397)		 Happy Hour Special
(n = 403)		 2-for-1 special
(n = 402)
β (95% CI) β (95% CI) AOR (95% CI) AOR (95% CI)
Drinking Establishment Practices
Served food −.33 (−.81, .15) −.35 (−.80, .10) 2.97 (1.37, 6.45) * 1.66 (.34, 8.13)
Allowed smoking indoors .50 (−.08, 1.08) −.46 (−.91, −.01) * .33 (.09, 1.17) .58 (.12, 2.76)
Allowed e-cigarettes −.54 (−1.02, −.06) * −.28 (−.62, .05) 2.07 (.82, 5.24) 6.38 (2.45, 16.63) *
Sold cigarettes on premise −.79 (−1.15, −.42) * −.17 (−.51, .18) 1.23 (.54, 2.79) .85 (.25, 2.92)
State Laws
No Happy Hour Restriction - - Referent -
Happy Hours Restricted - - 1.44 (.66, 3.14) -
Happy Hours Banned, Full Day Reduction Permitted - - .08 (.04, .17) * -
Happy Hours Completely Banned - - .24 (.07, .76) * -
No Restriction on 2-for-1 Sales - - - Referent
2-for-1 Sales Restricted - - - .36 (.12, 1.10)
Drink Prices
Vodka Price ($1 increase) - - .83 (.65, 1.06) .83 (.57, 1.23)
Beer Price ($1 increase) - - .72 (.58, .90) * .15 (.73, 1.81)
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Note: Adjusted Odds Ratios (95%CI) or Regression Coefficients (95% CI)

*

p is significant at < 0.05 value

There were also several drinking establishment practices associated with the presence of drink specials. The price of beer was negatively associated with the availability of happy hour specials. Specifically, for every $1 increase in the price of the least expensive draft beer, the odds of having a happy hour special decreased 28% (OR 0.72, 95% CI [0.58, 0.90]). Selling food was associated with approximately three times the odds of having a happy hour special (OR 2.97, 95% CI [1.37, 6.45]). Establishments in states that banned happy hours but allowed full day price reductions (OR 0.08, 95% CI [0.04, 0.17]) or completely banned happy hours (OR 0.24, 95% CI [0.07, 0.76]) had lower odds of reporting the presence of a happy hour special. Among the drinking establishment practices examined, only allowing the use of e-cigarettes indoors was associated with 2-for-1 drink specials. Establishments that reported allowing e-cigarette use indoors had more than 6 times the odds of reporting having a 2-for-1 drink special (OR 6.38, 95% CI [2.45, 16.63]) (Table 4).

Results from sensitivity analyses were largely similar to our primary model specifications. When controlling for the number of alcohol outlets sampled, no substantive differences were observed, with the exception of allowing cigarette use inside on beer prices. While the estimated relationship between allowance of indoor cigarette use and beer prices remained similar, the corresponding confidence interval widened to include the null (b = −0.42, 95% CI [−0.85, 0.01]). Compared to our primary complete-case analyses, estimates from multiple imputation models were also similar. Exceptions include further attenuating of the association between cigarette use inside and beer prices (b = −0.35, 95% CI [−0.78, 0.08]), and the association between restriction on 2-for-1 drink specials and reported 2-for-1 specials becoming statistically significant (OR=0.31 95%CI [0.10, 0.94]).

Discussion

This study described the presence of drink specials and the average drink prices of on-premise drinking establishments near Universities, as well as their associations with state laws and establishment practices. Results indicated that 44% of locations had vodka available for less than $5, 82% had beer available for less than $5, and 41% of locations had both vodka and beer available for less than $5. Many locations offered happy hour specials (65%), had multiple sources of revenue (e.g., food [91%] and cigarette [9%] retail), and several allowed indoor use of e-cigarettes (18%) or cigarettes (8%). Food/cigarette retail and allowing indoor tobacco use (i.e., cigarettes and e-cigarettes) were associated with lower alcohol prices, and previous research indicates that lower prices are associated with higher intoxication levels (Chaloupka, 1996, Chaloupka et al., 2002, O’Mara et al., 2009, Österberg, 1995). Given the known associations between intoxication levels and event-specific smoking (Rossheim, 2013), it is possible that low alcohol prices serve as a loss leader to attract consumers, while also selling and allowing indoor use of cigarettes to yield profit (Erickson, n.d., Rice and Drummond, 2012). These on-premise settings with low alcohol prices and permissive tobacco use may be high-risk settings for tobacco initiation or failed cessation efforts.

Laws that set minimum drink prices, increase drink taxes, or ban the retail and indoor consumption of tobacco products may be effective harm reduction tools to mitigate over-consumption of alcohol (Chaloupka, 1996, O’Mara et al., 2009, Thombs et al., 2008, Thombs et al., 2009, Wagenaar et al., 2009, Stockwell et al., 2012, Orbell et al., 2009). Importantly, the amount of taxation on alcoholic beverages is largely dependent on the pre-tax retail price (Alcohol Policy Information System, 2020). Given the observed low alcohol prices in on-premise settings, nominal increases in drink taxes may not result in a substantial increase in alcohol price. Rather, setting minimum drink prices may result in less heavy drinking due to the combination of higher base drink prices and the corresponding increase in taxes. Results from simulation models and natural experiments in Canada, Scotland, and Wales indicate that setting a minimum unit price of alcohol reduces alcohol purchase, alcohol consumption, alcohol-attributable deaths, and hospital stays (Anderson et al., 2021, O’Donnell et al., 2019, Sherk et al., 2020). These decreases in alcohol purchase and consumption tended to occur among individuals who consumed large quantities of alcohol (O’Donnell et al., 2019, Anderson et al., 2021). Thus, prohibiting the retail sale and indoor use of tobacco products, along with setting minimum drink prices, may be important harm reduction policies at on-premise drinking establishments for alcohol control purposes.

Previous research, including systematic reviews, indicate happy hour specials are associated with heavy alcohol use and experiencing negative consequences (Puac-Polanco et al., 2020). The current study’s findings indicated that state-wide restrictions or bans on happy hour specials were associated with lower odds of having a happy hour special. Importantly, in the current study, 41% of locations in states with happy hours completely banned still reported having happy hour specials (Table 2). These findings align with those of (Reynolds-Ramirez, 2004) which demonstrated that some on-premise drinking locations in two U.S. counties did not adhere to restrictions on drink specials. Noncompliance may be due to a lack of awareness of these laws, which may be increased by a public media campaign (National Highway Traffic Safety Administration, 2005, Edwards et al., 1994). Results indicate a need for increased surveillance such as through compliance checks (National Highway Traffic Safety Administration, 2005) and enforcement such as issuing warnings to violators and enhanced staff training (National Highway Traffic Safety Administration, 2005). In line with this, the National Institute on Alcohol Abuse and Alcoholism (NIAAA) CollegeAIM recommendations suggest that ending happy hour and other drink specials may be an important public health policy to limit over-consumption by college students (Cronce, 2018). Tools exist to facilitate this process of implementing and evaluating laws that restrict drink specials (Imm et al., 2007).

Strengths and Limitations

Data were collected from a large, geographically diverse sample using phone calls, resulting in unique data that are not routinely collected. However, data were limited to on-premise alcohol establishments near large colleges and therefore may not be generalizable to other settings. Moreover, locations were identified using Google Maps rather than data on license type or NAICS codes. Using Google searches to identify locations is not a validated strategy to identify a comprehensive list of bars, thus some bars may be missing from the sample. However, this method is likely how potential consumers identify these locations themselves, which may increase ecological validity. Estimates presented are designed to provide information about on-premise drinking establishments near large public universities across the U.S.; however, proportionate sampling and sampling weights were not used. Thus, on-premise drinking locations near the smaller universities in the sample over over-representative, whereas on-premise drinking establishments near the larger universities are under-represented. However, sensitivity analyses revealed the number of sampled outlets per university were unrelated to outcomes. In addition, the data collected were self-reported during a brief phone interview, resulting in possible measurement error. Accordingly, the reported promotions and prices could not be confirmed in-person, and some respondents may not have answered accurately if their practices were not in accordance with state law. Responses may also have differed based on who answered the phone and provided the information, such as bartenders versus managers. Furthermore, the volume and proof of alcoholic beverages may vary between establishments, thereby influencing the price per gram of ethanol. To achieve a high response rate, data could not be collected on the brands of beer on tap and the volume of containers, which would have allowed for precise calculations of the cost per gram of ethanol.

Conclusion

This was the first study to assesses associations between state alcohol laws, alcohol prices/promotions, indoor tobacco use, and tobacco retail sales at on-premise drinking establishments across the United States. Study findings indicated that selling other products (i.e., food, cigarettes), allowing tobacco use indoors, and offering drink specials were significantly associated with lower drink prices. Previous research indicates greater consumption of alcohol occurs when consumers take advantage of lower prices (O’Mara et al., 2009). As such, understanding establishment-level practices associated with low drink prices is important for informing interventions that may prevent heavy drinking and related negative consequences. Results suggest that laws that increase alcohol taxes, set minimum drink prices, and ban the retail sale and use of tobacco products indoors are likely important harm reduction tools to implement in on-premise drinking locations near large universities.

Supplementary Material

Appendix 1

Acknowledgements

We would like to acknowledge the following individuals for their assistance with conducting telephone interviews: Candace Nelson, Helen Zeraye, Joy Barua, Tammy Cavazos, Samantha Seballos, Kaylan Bullock, Abigail Trinidad, Talia Abdo, and Ogechi Emechebe.

Funding

ES is supported by grant numbers R15ES032138 from the National Institute of Environmental Health of the National Institutes of Health (NIH) and U54DA036105 from the National Institute on Drug Abuse of the NIH and the Center for Tobacco Products of the U.S. Food and Drug Administration (FDA). The content is solely the responsibility of the authors and does not necessarily represent the views of the NIH or the FDA.

Footnotes

Conflict of Interest

ES is named on a patent application for a smartphone app that determines electronic cigarette device and liquid characteristics.

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Appendix 1
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