| Literature DB >> 30987643 |
Kristin Feltmann1, Tobias H Elgán2, Johanna Gripenberg2.
Abstract
BACKGROUND: Alcohol intoxication is associated with problems such as violence, injuries, drunk driving and sexual risk-taking, and music festivals are considered a high-risk setting for high levels of alcohol consumption. This study investigates intoxication levels, drinking habits, and opinions on alcohol use and alcohol policies among visitors at one of the largest music festivals in Sweden in 2017.Entities:
Keywords: AUDIT-C; Alcohol drinking habits; Alcohol intoxication; Alcohol prevention; Blood alcohol concentration (BAC); Gender effects; Large music event; Opinions on alcohol
Mesh:
Substances:
Year: 2019 PMID: 30987643 PMCID: PMC6466660 DOI: 10.1186/s13011-019-0203-8
Source DB: PubMed Journal: Subst Abuse Treat Prev Policy ISSN: 1747-597X
Demographic characteristics
| % (n) | |
|---|---|
| Gender | |
| Male | 63.7 (898) |
| Female | 34.9 (492) |
| Other | 0.1 (2) |
| Age (years) | |
| 16–17 | 4.9 (69) |
| 18–20 | 23.1 (326) |
| 21–25 | 37.5 (529) |
| 26–30 | 15.2 (214) |
| ≥ 31 | 19.0 (268) |
| Occupation | |
| No occupation | 2.1 (29) |
| Working full-time | 64.3 (906) |
| Working part-time | 7.9 (111) |
| University | 10.9 (154) |
| High school | 7.0 (98) |
| Working & studying | 7.4 (104) |
| Ticket type | |
| 1-day | 10.1 (142) |
| 4-day | 14.9 (210) |
| 4-day with camping | 74.5 (1050) |
| Entering | 66.5 (937) |
| Exiting | 32.4 (457) |
| Thursday | 50.7 (715) |
| Friday | 49.3 (695) |
| Main entrance | 47.8 (674) |
| Camping entrance | 52.2 (736) |
Demographic characteristics of the 1410 participants are presented as percentages of all participants and in total numbers (n). Data is missing for the following variables and number of participants: gender (n = 18), age (n = 4), occupation (n = 8), ticket type (n = 8) and entering/exiting (n = 16)
BAC levels among different groups and factors
| BAC (%) of all participants ( | BAC (%), participants with BAC > 0% ( | |||||
|---|---|---|---|---|---|---|
| median | (IQ range) | median | (IQ range) | |||
| Total | 0.068 | (0.019–0.110) | 0.082 | (0.046–0.120) | ||
| Gender | ||||||
| Male | 0.076 | (0.035–0.117) | < 0.001 | 0.085 | (0.051–0.120) | 0.002 |
| Female | 0.048 | (0.002–0.094) | 0.071 | (0.033–0.110) | ||
| Age (years) | ||||||
| < 18 | 0.000 | (0.000–0.058) | < 0.001 | 0.064 | (0.039–0.089) | 0.001 |
| 18–20 | 0.060 | (0.018–0.102) | 0.076 | (0.042–0.111) | ||
| 21–25 | 0.071 | (0.029–0.113) | 0.081 | (0.047–0.116) | ||
| 26–30 | 0.079 | (0.034–0.124) | 0.093 | (0.055–0.131) | ||
| ≥ 31 | 0.068 | (0.018–0.118) | 0.086 | (0.046–0.127) | ||
| Occupation | ||||||
| No occupation | 0.068 | (0.023–0.113) | < 0.001 | 0.082 | (0.048–0.117) | < 0.001 |
| Working full-time | 0.074 | (0.029–0.119) | 0.087 | (0.050–0.124) | ||
| Working part-time | 0.050 | (0.000–0.100) | 0.081 | (0.041–0.122) | ||
| University | 0.066 | (0.021–0.111) | 0.084 | (0.051–0.117) | ||
| High school | 0.030 | (0.000–0.072) | 0.064 | (0.040–0.088) | ||
| Working & studying | 0.043 | (0.006–0.080) | 0.063 | (0.027–0.100) | ||
| Ticket type | ||||||
| 1-day | 0.048 | (0.002–0.093) | < 0.001 | 0.076 | (0.045–0.107) | 0.300 |
| 4-day | 0.055 | (0.002–0.109) | 0.083 | (0.046–0.121) | ||
| 4-day with camping | 0.070 | (0.026–0.114) | 0.082 | (0.045–0.120) | ||
| Entering | 0.070 | (0.025–0.115) | < 0.001 | 0.084 | (0.047–0.122) | 0.007 |
| Exiting | 0.055 | (0.010–0.100) | 0.077 | (0.039–0.115) | ||
| Thursday | 0.065 | (0.016–0.115) | 0.346 | 0.084 | (0.046–0.123) | 0.127 |
| Friday | 0.069 | (0.028–0.111) | 0.080 | (0.048–0.123) | ||
| Main entrance | 0.068 | (0.021–0.116) | 0.453 | 0.085 | (0.048–0.122) | 0.087 |
| Camping entrance | 0.068 | (0.024–0.112) | 0.078 | (0.042–0.115) | ||
Median and interquartile (IQ) range of blood alcohol concentration (BAC) levels are presented. Differences in BAC levels across the categories of gender, age, occupational activity, ticket type, status of entering/exiting, day of measurement and entrance were measured using the Mann-Whitney U-test or the Kruskal-Wallis test. Data is missing for the following variables and number of participants: BAC levels (n = 2), gender (n = 18), age (n = 4), occupation (n = 8), ticket type (n = 8) and entering/exiting (n = 16)
Fig. 1BAC level distribution across gender. Blood alcohol concentration (BAC) levels were measured using breath analyzers. BAC data were divided into the following categories: no alcohol (0) or low alcohol (0.001–0.049%) consumption, intoxication (0.050–0.099%) and high intoxication (≥0.10%). The data represent the distribution across these categories and are presented as numbers of people (bar) and percentages (above bars). This distribution across categories is also presented for each gender separately as numbers of people (bar) and percentages (within bars). Chi-squared tests showed a significant effect of the distribution of gender across BAC category (Χ2(4) = 49.64, p < 0.001). Z-tests revealed significant gender differences in all categories except the category 0.001–0.049%
Self-reported drinking habits across gender using AUDIT-C and calculated frequencies of risky alcohol consumption using 3 different cut-off levels
| AUDIT-C | Male % (n) | Female % (n) | Total % (n) | Gender Χ2 (df), |
|---|---|---|---|---|
| Question 1: Frequency of alcohol use | ||||
| Never | 0.9 (8) | 4.1 (20)* | 2.0 (28) | 49.99 (4), |
| Monthly | 16.7 (150) | 25.7 (126)* | 19.9 (276) | |
| 2–4 times a month | 58.0 (520) | 57.0 (280) | 57.6 (800) | |
| 2–3 times a week | 21.2 (190) | 12.4 (61)* | 18.1 (252) | |
| ≥4 times a week | 3.2 (29) | 0.8 (4)* | 2.4 (34) | |
| Question 2: Reported alcohol use on a typical day | ||||
| ≤4 units | 23.5 (210) | 47.4 (225)* | 31.8 (435) | 81.10 (1), |
| ≥5 units | 76.5 (682) | 52.6 (250)* | 68.2 (934) | |
| Question 3: Frequency of binge drinking (≥6 units) | ||||
| Never | 2.7 (24) | 12.6 (61)* | 6.1 (85) | 114.69 (4), |
| <Once a month | 26.0 (233) | 42.2 (205)* | 31.7 (438) | |
| Monthly | 47.2 (422) | 33.3 (162)* | 42.2 (584) | |
| Weekly | 23.5 (210) | 11.5 (56)* | 19.4 (268) | |
| Daily or almost daily | 0.7 (6) | 0.2 (1) | 0.5 (7) | |
| AUDIT-C score: Risky alcohol use | ||||
| > 4 for men, 3 for women | 81.0 (726) | 73.5 (361)* | 78.4 (1087) | 10.54 (1), |
| > 5 for men, 4 for women | 68.5 (614) | 53.8 (264)* | 63.3 (878) | 29.74 (1), |
| ≥6 for men & women | 68.5 (614) | 37.1 (182)* | 57.4 (796) | 128.37 (1), |
Frequencies in percent and number (n) of people across the categories of questions of the Alcohol Use Disorder Identification Test-Consumption (AUDIT-C) are shown. The frequencies of risky alcohol use according to different cut-offs used in research are presented. The effects of gender were analyzed using Pearson’s chi-squared test followed by the z-test
*Column proportions differ significantly (p < 0.05) between men and women. Data is missing for the following variables and number of participants: BAC (n = 2); AUDIT-C question 1 (n = 2), question 2 (n = 8) and question 3 (n = 11)
Opinions on alcohol use and their relation to BAC levels
| Overall sample | Within BAC category: 0% 0.001–0.09 > 0.10% | Within gender: Male Female | ||||||
|---|---|---|---|---|---|---|---|---|
| agree | disagree | agree | agree | agree | agree | agree | Χ2 (df = 1) | |
| % (n) | % (n) | % (n) | % (n) | % (n) | % (n) | % (n) | ||
| S1 | 29.3 (411) | 48.3 (679) | 13.5 (35) | 29.7 (210) | 37.8 (165) | 31.6 (283) | 24.7 (121) | 7.35 |
| S2 | 15.2 (212) | 73.2 (1031) | 9.4 (24) | 16.1 (113) | 17.0 (74) | 19.0 (168) | 8.2 (40) | 28.39 |
| S3 | 75.2 (1055) | 9.3 (130) | 82.2 (212) | 75.9 (535) | 70.3 (306) | 70.8 (630) | 82.9 (406) | 24.60 |
| S4 | 19.8 (276) | 63.7 (898) | 15.2 (39) | 19.8 (139) | 22.6 (98) | 24.2 (215) | 11.9 (58) | 29.74 |
| S5 | 89.0 (1250) | 7.2 (102) | 95.0 (245) | 90.9 (643) | 82.4 (360) | 86.8 (777) | 93.0 (455) | 12.56 |
| S6 | 85.6 (1189) | 7.0 (99) | 87.6 (126) | 86.3 (606) | 83.2 (355) | 83.5 (735) | 89.6 (438) | 9.37 |
Opinions on alcohol use and alcohol policies were assessed through the following statements: S1) A good night out means getting drunk. S2) It is acceptable for people under 18 to buy or be bought alcohol. S3) Drunk people ruin a night out. S4) Drunk people should be able to enter the festival area. S5) People who are drunk should not be able to obtain more alcohol. S6) Not providing people who are already drunk with more alcohol would improve nights out. Frequencies of agreement are presented for the overall sample (left), within each blood alcohol concentration (BAC) level category (middle) and within each gender (right). Data represent the number of people (n) and percentage. The effects of gender were analyzed using Pearson’s chi-squared test
Factors influencing undetectable and high alcohol intoxication levels
| D.V. BAC | 0% | ≥0.10% | ||||||
|---|---|---|---|---|---|---|---|---|
| χ2 | O.R. | 95% C.I. |
| χ2 | O.R. | 95% C.I. |
| |
| Age | 6.97 | 0.97 | 0.95–0.99 | 0.008 | 7.70 | 1.03 | 1.00–1.04 | 0.006 |
| Gender (female vs. male) | 16.38 | 1.93 | 1.41–2.67 | < 0.001 | 2.16 | 0.81 | 0.61–1.07 | 0.142 |
| Risky alcohol use | 17.78 | 0.49 | 0.35–0.68 | < 0.001 | 8.96 | 1.58 | 1.17–2.12 | 0.003 |
| Camping ticket | 16.19 | 0.37 | 0.23–0.60 | < 0.001 | 1.74 | 1.38 | 0.86–2.23 | 0.187 |
| Entering the festival | 12.84 | 0.53 | 0.38–0.75 | < 0.001 | 3.40 | 1.30 | 0.99–1.74 | 0.065 |
| Agree with S1 | 10.15 | 0.49 | 0.32–0.76 | 0.001 | 3.57 | 1.31 | 0.99–1.74 | 0.059 |
| Agree with S2 | 0.55 | 0.82 | 0.49–1.38 | 0.457 | 0.001 | 0.99 | 0.70–1.41 | 0.973 |
| Agree with S3 | 1.39 | 1.28 | 0.85–1.93 | 0.238 | 1.41 | 0.84 | 0.62–1.12 | 0.235 |
| Agree with S4 | 0.15 | 1.09 | 0.70–1.71 | 0.695 | 0.93 | 0.85 | 0.61–1.19 | 0.335 |
| Agree with S5 | 0.68 | 1.34 | 0.67–2.70 | 0.408 | 10.20 | 0.53 | 0.36–0.78 | 0.001 |
Using multinomial logistic regression analysis, the influence of the following factors on blood alcohol concentration (BAC) levels were investigated: age, gender, self-reported risky alcohol use according to AUDIT-C (cut-off 4 for women, 5 for men), ticket type (camping ticket vs. 4-day or 1-day ticket without camping), entering versus exiting the festival, and agreeing with statements S1 to S5 (n = 1318). BAC categories of 0% and ≥ 0.10% were compared with the reference category 0.001–0.09%. All shown independent variables are dichotomous except for age (continuous)