| Literature DB >> 33238559 |
Kristin Feltmann1, Johanna Gripenberg1, Tobias H Elgán1.
Abstract
Music festivals are often high-risk settings associated with large numbers of visitors and high alcohol intoxication levels, which contribute to a number of public health-related problems. According to the Swedish Alcohol Act, servers are responsible for not overserving alcohol to obviously intoxicated patrons. The aim of the current study was to examine compliance to the Swedish Alcohol Act at music festivals by assessing the rate of alcohol overserving to festival-goers. We conducted a study at a large music festival in Sweden hosting approximately 50,000 visitors. Professional actors, i.e., pseudo-patrons, enacted a standardized scene in which a highly intoxicated festival-goer attempted to buy beer at licensed premises inside the festival. Observers monitored each attempt. A total of 52 purchase attempts were conducted. The rate of overserving was 26.9% and was not influenced by the server's gender, the number of servers, or the level of crowdedness at the bar area. Overserving differed between server age groups, which was not statistically significant when controlling for other factors. Compliance to the Alcohol Act at the festival can be improved. Intoxication levels and related problems can be reduced by implementing a multicomponent intervention including staff training, policy work, and improved enforcement.Entities:
Keywords: alcohol policy; alcohol prevention; large events; pseudo-intoxication; pseudo-patron
Year: 2020 PMID: 33238559 PMCID: PMC7700124 DOI: 10.3390/ijerph17228699
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Rates of overserving across various characteristics.
| Characteristic | Proportion of Purchase Attempts % ( | Proportion of Overserving | x2(df) a, |
|---|---|---|---|
| Actor identity | |||
| Server’s gender | |||
| Server’s age | |||
| Time of purchase | |||
| Bar type c |
a df = degrees of freedom, b Fisher’s exact test since at least one cell had an expected count <5. c Small-sized bars had <3 counters, medium-sized bars had 3–10 counters, and large-sized bars had >10 counters.
Logistic regression analysis of factors influencing overserving.
| Independent Variables | Odds Ratio | 95% CI a |
|
|---|---|---|---|
| Server’s gender (ref: male) | |||
| Female | 0.82 | 0.17–3.89 | 0.806 |
| Server’s age (ref: 18–25 years old) | |||
| >25 years old | 3.46 | 0.56–21.33 | 0.181 |
| Bar type (ref: small sized) b | |||
| Medium sized | 0.57 | 0.08–4.13 | 0.575 |
| Large sized | 0.58 | 0.07–4.60 | 0.609 |
| Time of purchase (ref: 7:00–8:59 p.m.) | |||
| 9:00–10:59 p.m. | 0.37 | 0.07–2.04 | 0.252 |
| 11:00 p.m.–12:59 a.m. | 0.10 | 0.01–0.77 | 0.027 |
Nagelkerke R2 = 25.6%, a CI—confidence interval. b Small-sized bars had <3 counters, medium-sized bars had 3–10 counters, and large-sized bars had >10 counters.