6 Current study Funded by National Institute of Alcohol Abuse and Alcoholism (R01AA11551). Purpose is to look at the effects of alcohol ads on youth.
7 Methods Computer-aided telephone survey of youth aged 15-26. Sampled from 24 United States cities, representing 75% of the population, which lives in metropolitan areas above 957,000 in population. Wave 1, N = 1872 May-July 1999 Wave 2, N = 1173 Dec-Jan 2000 Wave 3, N = 787 May-June, 2000 Wave 4, N = 588 Dec-Jan, 2001 Attrition higher among baseline drinkers; so conservative test. Sample weighted by city population, gender, & respondent age
8 Key measures Behavior: # drinks in the past month, computed from frequency of drinking, average quantity drunk per episode, & maximum drunk per episode. Self-report ad exposure in the past month: 8 item index for exposure to beer and liquor ad exposure on TV, radio, magazines, and billboards. Market-level advertising availability: sum of money spent on ads on TV, radio, billboards, & newspapers per market. Purchased industry data.
9 Are youth exposed to alcohol ads? Markets had between 285 (Tulsa) & 13,170 (Chicago) ads in 1999 & 2000, with a mean of 4314 ads. Ad amounts were stable over time. Youth reported exposure to 3 ads on average in past month.
10 How much do kids drink? 43% of underage youth 15-20 had at least 1 drink in the past month at baseline. Underage drinkers had an average of 28 drinks per month, and 4.3 drinks per drinking session. 53% of youth 15-26 had at least 1 drink in the past month at baseline. Drinkers had an average of 36 drinks per month, and 4.4 drinks per drinking session.
11 What is the relationship between alcohol advertising and drinking? H1: Youth living in markets with more ads drink more than youth in markets with fewer ads. H2: Youth exposed to more ads drink more than youth exposed to fewer ads. H3: Youth exposed to more ads increase their drinking over time.
12 Analysis Hierarchical linear modeling (HLM 5.04) Form of mixed modeling, with random & fixed effects. Accounts for clustered sample (markets). Allows partitioning of variance – observation, individual levels. Keeps all data on cases, including cases that drop out after baseline.
13 Model Alcohol use = intercept + time + ad exposure observation level + mean ad exposure individual level + market ad availability market level + market sales market level + prior alcohol use observation level + control variables (Time, Gender, Age, Whether in high school or not, African-Americans, Hispanics, Live with their parents or not, # hours worked per week.)
14 H1: Youth living in markets with more alcohol ads drink more than youth in markets with fewer ads. Market-level ad availability was positively related to alcohol use. The relationship held when controlling for amount of alcohol sales in the market. Results held for both underage youth 15-20 and youth 15-26.
15 H2: Youth exposed to more alcohol ads drink more than youth exposed to fewer ads. Alcohol use increased when a youth had higher mean level of ad exposure across all waves. Within-individual ad exposure was not statistically significant. Results held for both underage youth 15-20 and youth 15-26.
16 Youth drinking amounts by ad exposure & market-level ad availability
17 Example case Market ad availability Low Hi Ad exposure 0 36 10 1221 Number of drinks a 20 year old white male is predicted to have had in the past month
18 H3: Youth exposed to more alcohol ads increased their drinking over time. Statistically controlled for prior alcohol use & prior ad exposure. Individual-level ad exposure and market ad availability predicted changes in alcohol use.
19 Summary Youth drinking was greater than their peers and increased more over time when: youth reported more alcohol ad exposure than their peers and youth lived in markets with more ads.
20 Conclusions The amount of local alcohol advertising in the media environment and amount of advertising recalled matters to youth alcohol use. Underage youth displayed same pattern of effects as the entire age range.
21 Conclusions The results address the reverse causality question – can a correlation between youth ad exposure and drinking be due entirely to drinkers noticing more ads? No, because using the objective measure of market ad availability we still find a relationship with drinking, i.e. youth alcohol drinkers tend to live in places with more ads. and because increases in drinking over time are associated with higher levels of ad exposure.
22 Conclusions The results extend research on alcohol ad bans by linking # ads in market with individual youth behavior. The relationship between market-level ad availability & youth drinking was not due to market differences in alcohol sales.
23 Conclusions Conservative test of advertising availability effects because it measures the “added value” over & above the effects of national ads.
24 Conclusions Youth reporting greater amounts of long-term exposure to alcohol advertising drank more than youth who saw fewer ads, and were more likely to increase drinking over time. Results are consistent with theories of cumulative effects of advertising. For each person, the amount of alcohol consumption was not sensitive to short-term differences in alcohol advertising exposure.
25 Conclusions Some argue that advertising is unrelated to youth drinking and at best causes brand switching. If true, we would not have found positive relationships between alcohol advertising and changes over time in youth alcohol use.
26 Conclusion If current educational efforts by industry groups were enough to negate any effects of alcohol advertising on youth drinking, we would have found null effects. If alcohol ads only impact adults, we would not have found the effects of alcohol advertising on underage youth drinking. Alcohol advertising is a contributing factor to youth drinking quantities over time.
27 Contact information: Dr. Leslie Snyder Dept. of Communication Sciences University of Connecticut Storrs, CT 06269-1085 USA 860 486-4383 (o) leslie.snyder @uconn.edu