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Effect of Televised, Tobacco Company-Funded Smoking Prevention Advertising on Youth Smoking-Related Beliefs, Intentions, and Behavior I Melanie Wakefield, PhD, Yvonne Terry-McElrath, MSA, Sherry Emery, PhD, Henry Saffer, PhD, Frank J. Chaloupka, PhD, Glen Szczypka, BA,
Brian Flay, PhD, Patrick M. O'Malley, PhD, and Lloyd D. Johnston, PhD
The tobacco industry has actively attempted to remake its public image in response to ev- idence that it marketed products to youth and misled the public about smoking health risks.''^ This effort has included public edu- cation campaigns to communicate that youths should not smoke.'' In December of 1998, Philip Morris launched a national $tOO million television campEiign the com- pany described as targeted to youths aged 10-14 years.'' The primary message was that youths do not need to smoke to fit in socially with their peers, and the campaign delivers the slogan "Think. Don't Smoke." Although this campaign ended on US televi- sion in Jcinuary 2003, the ads continue to be broadcast in other countries.^ In October
1999, and with a budget of around $13 million,^ Lorillard Tobacco Company also launched a US-televised youth smoking pre- vention campaign with the slogan, "Tobacco is Whacko if You're a Teen.'"*
In mid-July 1999, Philip Mords launched a campaign that emphasized parental responsi- bility for talking to children about smoking; the slogan was "Talk. They'll Listen."^ This parent-focused youth smoking prevention campaign has featured a variety of television ads and continues today. The overt message of these ads is that parents should talk to their children about not smoking.
Few studies have examined the potential effect of youth-focused tobacco company- sponsored advertising. Of those, most have only assessed immediate appraisals of the ad- vertisements by youths,*'^'" or the relation between ads and attitudes thought to be pre- dictive of smoking behavior change," rather than smoking behavior itself. No studies have examined the effects of tobacco com- pany parent-focused advertising on youth. Because advertising that may influence youth
Objective. To relate exposure to televised youtb smoking prevention advertis- ing to youths' smoking beliefs, intentions, and behaviors.
Methods. We obtained commercial television ratings data from 75 US media markets to determine tbe average youth exposure to tobacco company youth-tar- geted and parent-targeted smoking prevention advertising. We merged these data witb nationally representative scbool-based survey data (n = 103172) gathered from 1999 to 2002. Multivariate regression models controlled for individual, geo- graphic, and tobacco policy factors, and otber televised antitobacco advertising.
Results. Tbere was little relation between exposure to tobacco company-sponsored, youtb-targeted advertising and youtb smoking outcomes. Among youths in grades 10 and 12, during tbe 4 montbs leading up to survey administration, eacb additional viewing of a tobacco company parent-targeted advertisement was, on average, as- sociated witb lower perceived barm of smoking (odds ratio [OR]=0.93; confidence interval [CI) = 0.88, 0.98), stronger approval of smoking (0R = 1.11; Cl = 1.03,1.20), stronger intentions to smoke in tbe future (0R= 1.12; Cl = 1.04,1.21), and greater like- lihood of having smoked in the past 30 days (0R = 1.12; Cl = 1.04,1.19).
Conclusions. Exposure to tobacco company youth-targeted smoking preven- tion advertising generally bad no beneficial outcomes for youths. Exposure to to- bacco company parent-targeted advertising may bave barmful effects on youtb, especially among youtbs in grades 10 and 12. {Am J Public Health. 2006;96: 2154-2160. doi:10.2105/AJPH.2005.083352)
smoking has also been broadcast at various times and intensities by tobacco control pro- grams,"^ it is a complicated matter to establish the relative influence of tobacco company- sponsored advertising.
The objective of this study was to assess the relation between exposure to tobacco company youth smoking prevention advertis- ing and youth smoking-related beliefs, inten- tions, and behavior in a representative sample of American secondary school students. The study includes youth-targeted and peirent- targeted advertising. The study sample in- cluded the primary target age group of the youth-targeted ads (grade 8, mean age 14 years), as well as older youths in grades 10 and 12 (mean ages 16 and 18 years, respec- tively). We used objective media monitoring data to meastire potential exposure of youths to different sources of advertising, as opposed to self-reported measures of exposure that
can be correlated with openness to change in smoking behavior.'^
METHODS
Advertising Data Nielsen Media Research provided data on
the occurrence of all smoking-related adver- tisements that appeared on network and cable television across the largest 75 US television media market areas during 1999-2002. These 75 markets accounted for 78% of American viewing households." A media mar- ket is defined by a group of nonoverlapping counties forming a major metropolitan area. Data are on the basis of individual ratings of television programs obtained by monitoring household audiences across media markets. Ratings provide an estimate of the percentage of households with televisions that watch a program or advertisement in a media market
2154 I Research and Practice | Peer Reviewed | Wakefield et al. American Journai of Pubiic i-iealth | December 2006, Voi 96, No. 12
mimm m refls^iE
over a specified time interval,'^ The advertising exposure measure used in our study is based on Target Rating Points (TRPs) for the popula- tion aged 12-17 years. In these analyses, TRPs were aggregated each month; 100 TRPs are equal to an average of 1 potential advertise- ment exposure per month for all youth aged 12-17 years within a media market, TRPs rep- resent potential average exposure; actual expo- sure for any given individual would vary on the basis of actual television viewing. In this study, all the tobacco company parent-targeted advertising was irom Philip Morris, However, tobacco company youth-targeted advertising was broadcast by Philip Morris cind Lorillard; Philip Morris made up 90,8% of the total TRPs in 1999, 93,0% in 2000, 85,2% in 2001, and 375% in 2002.
Monthly TRP data were merged with na- tionally representative data collected during 1999-2002 from the Monitoring the Future school survey,'^ Data were collected from February to June each year fi-om samples of students in grades 8, 10, and 12, dravm to be representative of all students in the speci- fied grade for the 48 contiguous states. All surveys were self-completed and group- administered in school settings.
Dependent Variables
Separate analyses were conducted for each of the following self-reported depen- dent variables: recall of antitobacco advertis- ing at least weekly (1 = seeing antitobacco commercials on television or hearing them on the radio at least once a week in recent months); approval of smoking (1 =don't dis- approve of people smoking > 1 pack a day (grades 8 and 10), or don't disapprove of people (aged 18 years or older) smoking > 1 pack a day (grade 12); perceived enjoyment of life by smokers (1 = n o disagreement with tbe statement that smokers know how to enjoy life more than nonsmokers); prefer- ence for dating nonsmokers (1 =no prefer- ence for dating nonsmokers); perceived ex- aggeration of smoking harm (1 = n o disagreement with the statement that the harmful effects of smoking have been exag- gerated); perception tbat being a smoker re- flects poor judgment (1 =do not agree that being a smoker reflects poor judgment); per- ception that smoking is a dirty habit (1 =do
not agree that smoking is a dirty habit); perceived harm of smoking (1 = believe peo- ple risk "great harm" to themselves by smok- ing > 1 pack of cigeirettes a day); intentions to be smoking in 5 years time (0=definitely will not be smoking cigarettes in 5 years;
1 =other'^); smoking in the past 30 days (1 =any cigarette smoking in the past 30 days); and consumption among current smokers, as measured by a 6-point scale: less than 1 cigarette/day (0,5), 1-5 cigarettes/ day (3,0), about ,5 pack/day (10), about 1 pack/day (20), about 1,5 pack/day (30), and
2 or more packs/day (40), The natural log of this scale was used in all models,'*
The school survey randomly allocates stu- dents to several different forms of survey questionnaires to maximize the number of questions asked of students. Although all students are asked about smoking behavior (current smoking and consumption), only some forms contain questions on recall of advertising, cind smoking-related attitudes and intentions. For this reason, different numbers of students respond to each out- come measure. The total number of stu- dents included in each model is specified in table footnotes.
Independent Variables
Advertising exposure for eacb student was calculated to reflect the cumulative effect of repeated potential exposure to tobacco indus- try advertising and gave greater weight to more recent exposure,'^"^' Thus, in analyses, individual student potential exposure to to- bacco industry advertising was reflected by the sum of TRPs for the month in which the school survey was completed, plus the sum of depreciated TRPs from the 3 previous months. On the basis of the work of PoUay and colleagues,^' a depreciation value of 0,3 was specified as noted in the equation .
(1)
wbere Adstock is the total effective advertis- ing, X is set at tbe specified value of 0.3 as noted above, eind Ad indicates ad sponsor TRPs for time periods U - 1 , t-2, and t-3. A range of values for X were examined. Be- cause results were highly similar, X was set at
0,3, consistent with previously published data by Emery and colleagues ^̂ on the ef- fect of state tobacco control ads. The depreci- ated sum was scaled by dividing by 100, The resulting TRP exposure value represents the depreciated average number of times that ad- vertising from a particular sponsor was po- tentially seen by 100% of the youth aged 12—17 years in each media market over the 4 months leading up to each specific school's date of survey participation. Thus, students witbin tbe same media market were assigned different advertising exposures, depending on the month in which their school was sur- veyed. However, within media markets, stu- dents in each school were assigned the same advertising exposure values, because they completed the survey on the same date, Smoking-related outcomes were modeled using continuous versions of depredated TRPs for youth-targeted and parent-targeted advertising.
Statistical Analyses and Covariates
Our analyses used survey commands in Stata, version 8 (Stata Corp, College Station, Tex) for descriptive population estimates and multivariate regression models (SVYLOGISTIC for dichotomous outcomes; SVYREG for tbe models of cigarette consumption using the natural log of the consumption scale). The complex multistage sample design was ac- counted for by using sampling weights to ad- just for differential selection probabilities, and by using Taylor linearization-based variance estimators to adjust for clustering by school and compute robust stcindard errors.
Initially, for each type of tobacco company advertising, we tested several functional forms, including quadratic and threshold models, to explore whether the relations between exposure and outcomes were non- linear. The linear models fit the data best, cind cire reported here. Thus, odds ratios refer to change in the likelihood of each outcome measure, on the basis of each additional advertisement viewed, on average, in the 4 months leading up to the date of survey administration.
For tobacco company youth-targeted advertising, we first ran models for all stu- dents combined and controlled for (1) com- peting advertising exposure from 2 types of
December 2006, Vol 96, No, 12 I American Journal of Public Health Wakefield et al. \ Peer Reviewed | Research and Practice | 2155
campaigns: tobacco control (including state and national American Legacy Foundation campaigns) and tobacco company parent-tar- geted advertising; (2) individual sociodemo- graphics: gender, race/ethnicity, average pa- rental education, dual parent household, grade point average, 3 or more evenings out a week for fun/recreation, past-month tru- ancy, year, region, and student-earned in- come; and (3) state tobacco policy variables: average real price per pack of cigarettes^^ and a smoke-free air index measuring the comprehensiveness of state smoke-free laws. The smoke-free air index values depended on the number, type, and level of protection for smoke-free locations, and whether the state had the authority to preempt local smoke-free regulations,^^ On the basis that the primary target group of the tobacco com- pany youth-targeted advertising was youths aged 10-14 years and that middle- (grade 8, mean age 14 years) and high-school (grades 10 and 12, mean ages 16 and 18 years, re- spectively) students are at very different de- velopmental stages, we ran separate models for grade 8 versus grades 10 and 12, In the model for grades 10 and 12, a dummy vari- able for grade 12 was also included. This analysis process was repeated to examine the relation between tobacco company par- ent-targeted advertising and youth smoking outcomes (with the exception that competing advertising exposure for tobacco company youth-targeted advertising was included as a covariate).
We conducted sensitivity analyses to ex- plore the robustness of findings for outcomes of greatest concem. Because advertising and policy variables were correlated, we excluded each tobacco policy variable and tobacco con- trol campaign exposure, to explore if ob- served relations changed in a systematic way. In addition, we were able to include informa- tion on student-reported frequency of televi- sion watching as a covariate in models of smoking prevalence and consumption, be- cause these questions occurred on the same survey form as television watching questions for all 3 grades. In this set of analyses, the school survey item measured self-reported av- erage weekday television viewing as a contin- uous variable (a 7-point scale ranging from 0 to 5-1- hours).
RESULTS
After retaining cases that had no missing data for eovariates and at least 1 of the speci- fied dependent variables, 103 172 students remained in the analytic sample; 36% were students in grade 8 and 64% were students in grades 10 and 12, Table 1 shows that 20,8% of the sample population had smoked in the last 30 days and average daily consumption for these smokers was 5,43 cigarettes.
On average, students had been exposed to 4,77 depreciated potential viewings of tobacco company youth-targeted advertising and 1,13 potential viewings of tobacco company parent-targeted advertising in the 4-month period leading up to the survey. As expected from the diverse timing and inten- sity of these campaigns, there was variation between students, with a range of 0 to 14,51 viewings of tobacco company youth-targeted ads, and a reinge of 0 to 4,13 viewings of to- bacco company parent-targeted ads. There was also variation in exposure to tobacco con- trol campaigns (mean 6,88 viewings; for state antitobacco campaigns, mean= 1,66 [range= 0-19,14]; for the American Legacy Founda- tion, mean=5,23 [range=0-21,85]).
After we controlled for eovariates, in- creased exposure to tobacco company youth- targeted advertising among all students was generally unrelated to recall of televised anti- tobacco advertising or to smoking beliefs or behavior (Table 2), However, on average, each additional ad viewed was associated with a 3 % stronger intention to smoke in the future (OR=1,03; CI= 1,01, 1,05), When analyzed separately for middle- and high-school stu- dents, higher exposure to tobacco company youth-tat^eted advertising was unrelated to any outcome for students in grades 10 and 12, For students in grade 8, higher exposure was associated with stronger intentions to smoke in the future (OR=1,04; CI=1,O1, 1,08), Inclusion of self-reported frequency of television watching as a covariate did not change the finding that there was no relation between increased tobacco company youth- targeted advertising and smoking in the past 30 days, or consumption among smokers, (Data for students who smoked in the past 30 days: all students OR=0,99; CI= 0,96, 1,01; grade 8 OR=0,99; CI=0,95, 1,04; grades 10
and 12 OR=0,99; CI=0,96, 1,01, Data for consumption among smokers: all students Parameter estimate=-,008, P>.05; grade 8 Parameter estimate=-,014, P>.05; grades 10 and 12 Parameter estimate=-,004, P>.05.)
After adjusting for eovariates. Table 2 shows that among all students combined, each additional tobacco industry parent-targeted ad was associated with a lower likelihood of re- calling antitobacco advertising (OR=0,87; CI=0,82, 0,92), lower perceived harm of smoking (OR=0,95; CI=0,92, 1,00), stronger intentions to smoke in future (0R = 1,12; CI= 1,05, 1,19), and a greater likelihood of smoking in the past 30 days (0R= 1,10; CI= 1,03, 1,17),
Separate models for middle- and high- school students indicated that, among stu- dents in grade 8, greater tobacco company parent-targeted advertising exposure was re- lated to lower odds of recalling antitobacco advertising (OR=0,86; CI=0,78, 0,94), a greater likelihood of perceiving the harms as- sociated with smoking have been exaggerated (0R= 1,07; CI= 1,01, 1,13), and stronger in- tentions to smoke in the future (0R= 1,10; CI= 1,00, 1,21), Among students in grades 10 and 12, higher advertising exposure was also associated with less likelihood of recall- ing antitobacco advertising (OR=0,86; CI= 0,80, 0,94), stronger approval of smoking (0R= 1,11; CI= 1,03, 1,20), lower perceived harm of smoking (OR=0,93; CI=0,88, 0,98), stronger intentions to smoke in future (0R= 1,12; CI= 1,04,1,21), and a greater like- lihood of smoking in the past 30 days (0R= 1,12; CI=l,04, 1,19), Each additional ad ex- posure during the 4 months leading up to survey administration, on average, was associ- ated with a 12% increase in the likelihood that students in grades 10 and 12 had smoked in the past 30 days.
In sensitivity analyses among students in grades 10 and 12, where relations of most concem were found, exclusion of cigarette price or strength of smoke-free air index gen- erally did not systematically influence the re- lation between increasing tobacco company parent-targeted advertising and stronger ap- proval of smoking, lower perceived heirm of smoking, stronger intentions to smoke in the future, or greater likelihood of smoking in the past 30 days (Table 3), When tobacco-control
2156 I Research and Practice | Peer Reviewed | Wakefield et al. American Journal of Public Health | December 2006, Voi 96, No, 12
TABLE 1-Sample Characteristics of US School Students in 8th, 10th, and 12th Grade:
1 9 9 9 - 2 0 0 2
Weighted No.
independent control variabies (N=103172)'
Middle school (grade 8)
High school (grades 10 and 12)
iVIaie
Race/elhnicity
White
African American
Hispanic
Other
lives with both parents
Regulariyout>3nights/wk
Skipped or cut school in the past month
Eamed income, $
Parental education (range: 1-6)'
Average schooi grade (range: 1-9)'
Real price/pack of cigarettes, $ (range: $1.32-$2.86)
Smoke-free air index (range: -22.50-51.00) Dprfj nn ncglUI 1
Northeast
Midwest
West
South
independentvariabies(N
Average tobacco industiy parent-targeted exposure* (range: 0.00- 4.13)
Average tobacco industiy youth-targeted exposure" (range: 0.09-14.51)
Average tobacco controi exposure" (range: 0.00-23.90)
= 103172)'
Dependent variabies'
Recall antitobacco ads on TV or radio at ieast weekly (1 =yes)
Approve of others/aduits smoking > 1 pack per day (1=yes)'
Do not prefer to date nonsmokers (l=yes)
Feel that smokers know how to enjoy life more than nonsmokers (1=yes)
Feel the hamiful effects of cigarettes have been exaggerated (1 -yes)
Do not feel that being a smoker reflects poor judgment (1 =yes)
Do not feel that smoking is a dirty habit (1=yes)
f^rceive great hann in smoking > 1 packs/day (1 =yes)
Intend to smoke in 5 years (l=yes)
Smoked in the past 30 days (1 =yes)
Consumption frequency among current smokers (.5,3,10,20,30,40)*
28768
65388
37645
37685
37240
37343
37320
95952
34047
101720
19581
Percentage
36.0
64.0
47.3
71.6
12.0
10.9
5.5
75.0
44.5
19.4
21.5
28.0
18.8
31.7
62.4
22.7
22.6
16.2
34.2
39.6
27.5
69.6
39.1
20.8
Mean
1-15/wk (median)
3.99
6.22
1.92
13.15
1.13
4.77
6.88
5.43
'Number of students was obtained by retaining only cases with valid data for ail independent control variables, and valid data on at least 1 of the specified dependent variables.
'Parental education was a scaied vaiue ranging from 1 to 6, and was a combined average of mother's and father's highest
level of education, where 1 - grade schooi or iess, 2 - some high school, 3 - high school completion, 4 - some coilege, 5'College completion, and 6'graduate school. 'Average schooi grade was a 9-item scale where 1 = 0 and 9-A. A mean of 6 indicates a B. "Exposure to specific ads during the 4 months before the school survey. Advertising exposure data reported at the student level and not at the media market level, because students within the same media market wili have different average exposures on the basis of their schooi survey date.
'Possible Ns for dependent variables varied, because not ail items were asked of all students.
'students in grades8 and 10 were asked about disapproval of others' smoking; students in grade 12 were asked about disapproval of adults' smoking.
^Consumption was measured by a 6-point scale: iess than 1 cigarette/day (0.5), 1-5 cigarettes/day (3.0), about 0.5
pack/day (10), about 1 pack/day (20), about 1.5 pack/day (30), and 2 or more packs/day (40).The naturai iog of this scaie was used in all models.
ad exposure was removed, relations persisted between increasing tobacco company parent- targeted ad exposure and stronger approval of smoking as well as smoking in the past 30 days, but were weakened for perceived harm of smoking and intention to smoke in the future.
When self-reported frequency of television watching was included as a covariate, the relation between tobacco company parent- targeted ad exposure and current smoking was tinchanged for students in grade 8 (OR=1.11; CI=0.99, 1.25, not significant) but was strengthened among students in grades 10 and 12 (0R=1.14; CI=1.05, 1.25, PK.Ol). Control for television watching did not change the previously nonsignificant re- sults for cigarette consumption (grade 8: Pa- rameter estimate=-.O68, P>0.5; grades 10 and 12: Parameter estimate=-.O16, P>.05).
In models of students in all 3 grade levels, higher cigarette price was associated with lower consumption among current smokers (Parameter estimate=-.OO2, SE = 0.001, P< .05), and stronger smoke-free laws were asso- ciated with a lower likelihood of smoking in the past 30 days (OR=0.99; CI=0.99, 1.00, P=.O1 [data not shown]). In addition, consis- tent with previous studies, "'̂ ^ we observed expected relations between increasing expo- sure to tobacco control campaign advertising and higher recall of antitobacco advertising (OR=1.04; CI=1.03, 1.04, PK.OOl), more protective beliefs about smoking (e.g., in- creased perceived harm of smoking) (0R= 1.01; CI= 1.00, 1.02, P<.01), weakened in- tentions to smoke in future (OR=0.98; CI= 0.97, 0.99, P<.001), and a lower likelihood of smoking in the past 30 days {OR = 0.99; CI=0.98, 1.00, P<.01).
DISCUSSION
Overall, we found no systematic associa- tions between increased exposure to tobacco company youth-targeted smoking prevention advertising and smoking outcomes among American youths. We found that increased ex- posure to tobacco company parent-targeted smoking prevention advertising was associated with lower recall of antitobacco advertising and stronger intentions to smoke in the future for all students. Among students in grade 8,
December 2006, Vol 96. No. 12 | American Journal of Public Health Wakefield et al. | Peer Reviewed | Research and Practice | 2157
TABLE 2-Odds Ratios for Each Unit increase in Number of Ads Viewed, With 95% Confidence intervais (Cis), for
Smoking-Reiated Beiiefs and Behavior and Tobacco industry Smoi(ing Prevention Advertising Exposure: 1 9 9 9 - 2 0 0 2
Exposure, All Students' Exposure, 8th Grade Students Exposure, 10th and 12th Grade Students'
Youth-Targeted" Parent-Targeted' Youth-Targeted" Parent-Targeted' Youth-Targeted" Parent-Targeted'
Recall antitobacco ads on TV or radio at least weekly
Approve of others/adults smoking > 1 pack/day'
Do not prefer to date nonsmokers
Feel that smokers know how to enjoy life more
than nonsmokers
Feel the harmful effects of cigarettes have
been exaggerated
Do not feel that being a smoker reflects poor judgment
Do not feel that smoking is a dirty habit
Perceive great harm In smoking > 1 packs/day
Intend to smoke in 5 years
Smoked in past 30 days
Consumption frequency among current smokers,*
parameter estimate (SE)
1.00 (0.98,1.02)
0.98 (0.95,1.00)
1.00 (0.97,1.02)
1.00 (0.98,1.03)
0.87"* (0.82,0.92)
1.06 (0.99,1.13)
1.04(0.97,1.11)
1.00 (0.94,1.07)
0.99 (0.96,1.02)
0.98 (0.95,1.01)
1.00 (0.96,1.04)
1.02 (0.98,1.06)
0 . 8 6 " (0.78,0.94)
1.03 (0.96,1.12)
1.05 (0.94,1.18)
1.07 (0.96,1.19)
1.01 (0.98,1.03)
0.98 (0.96,1.01)
0.99 (0.97,1.02)
0.99 (0.97,1.02)
0 . 8 6 " (0.80,0.94)
1 . 1 1 " (1.03,1.20)
1.03 (0.96,1.11)
0.94 (0.87,1.01)
1.00(0.98,1.02) 1.03(0.99,1.08) 1.01(0.98,1.03) 1.07* (1.01,1.13) 0.99(0.96,1.01) 0.99(0.93,1.06)
0.99 (0.97,1.01)
1.00 (0.98,1.02)
0.99 (0.98,1.01)
1.03" (1.01,1.05)
0.99 (0.97,1.01)
-.014; (.008)
0.99 (0.94,1.04)
1.00 (0.94,1.07)
0.95' (0.92,1.00)
1.12" (1.05,1.19)
1.10" (1.03,1.17)
.019 (.025)
0.98(0.95,1.01)
1.00 (0.96,1.03)
0.99 (0.97,1.01)
1.04* (1.01,1.08)
0.99 (0.95,1.04)
-.014 (.015)
1.02 (0.95,1.09)
1.01 (0.92,1.10)
0.98 (0.93,1.04)
1.10* (1.00,1.21)
1.11 (0.99,1.25)
.069 (.044)
0.99 (0.97,1.02)
1.01 (0.98,1.03)
1.00(0.98,1.02)
1.01 (0.99,1.04)
0.99 (0.97,1.01)
-.012 (.009)
0.96 (0.90,1.03)
0.99 (0.91,1.07)
0 . 9 3 " (0.88,0.98)
1.12" (1.04,1.21)
1.12" (1.04,1.19)
.018 (.028)
Note. All models controlled for tobacco control advertising exposure, either tobacco company parent-targeted or youth-targeted advertising exposure, year, gender, race/ethnicity, earned income, average parental education, whether both parents live in the home, grade point average, evenings out, truancy, region, state cigarette price, and state smoke-free air index values. 'All students model Ns (weighted): smoked in last 30 days 101720; perceived harm 95952; disapproval 65388; recall 28768; consumption 21138; remaining perception models range from 34047 to 37685. "Grade 8 model Ns (weighted): smoked in last 30 days 36382; perceived harm 36236; disapproval 23305; recall 12136; consumption 4,621; remaining perception models range from 12287 to 16688. 'Grades 10 and 12 model Ns (weighted): smoked in last 30 days 65 338; perceived harm 59 716; disapproval 42 083; recall 16 632; consumption 16 517; remaining perception models range from 20827 to 21760. A dummy variable identifying students in grade 12 was included in these models. "Tobacco company youth-targeted ads sponsored primarily by Philip Morris, and by Lorillard Tobacco Company. 'Tobacco company parent-targeted ads sponsored by Philip Morris. 'students in grades8 and 10 asked about disapproval of others' smoking; 12th grade students asked about disapproval of adults' smoking. 'Consumption measured by a 6-point scale: less than 1 cigarette/day (0.5), 1-5 cigarettes/day (3.0), about 0.5 pack/day (10), about 1 pack/day (20), about 1.5 pack/day (30), and 2 or more packs/day (40). The natural log of this scale was used in all models. *P<.05;"/'<.01;"*P<.001.
TABLE 3-Odds Ratios and 95% Confidence intervais for Tobacco Company Parent-Targeted Advertising
Exposure and Seiected Smolcing Outcomes Among Students in Grades 10 and 1 2 : 1 9 9 9 - 2 0 0 2
Model'
Approve of others/adults smoking > 1 pack/day*
Perceive great harm in smoking > 1 packs/day
Intend to smoke in 5 years
Smoked in past 30 days
Weighted No.
42083
59716
21760
65338
Excluding State Cigarette Price
1.10*(1.02,1.18)
0.95 (0.90,1.01)
1 . 1 2 " (1.04,1.20)
1 . 1 0 " (1.03,1.18)
Excluding State Smoke-Free
Air Index Value
1 . 1 1 " (1.03,1.21)
0 . 9 3 " (0.88,0.98)
1 . 1 3 " (1.05,1.22)
1 . 1 2 " (1.05,1.20)
Excluding Tobacco Control
Ad Exposure
1 . 1 0 " (1.04,1.17)
0.97 (0.93,1.01)
1.04 (0.98,1.10)
1 . 0 7 " (1.02,1.12)
'Tobacco company parent-targeted ads sponsored by Philip Morris. All models controlled for year, gender, race/ethnicity, earned income, average parental education, whether both parents live in the home, average school grade, evenings out, truancy, region, and dummy variable for students in grade 12. Unless specified above, models also controlled for tobacco control advertising exposure, either tobacco company parent-directed or youth-targeted advertising exposure, state cigarette price, and state smoke-free air index values. ' Students in grade 10 were asked about disapproval of others' smoking; students in grade 12 were asked about disapproval of adults' smoking. • P < . 0 5 ; " P < . 0 1 .
tobacco company parent-targeted advertising was related to stronger beliefs that tbe barms assodated witb smoking have been exagger- ated, and among students in grades 10 and 12, was associated with lower perceived harm
of smoking, stronger approval of smoking, and a higher likelihood of baving smoked in tbe past 30 days. Importantly, tbe results for smoking prevalence among students in grades 10 and 12 were not systematically influenced
by correlations between price and strengtb of smoke-free air laws, or tobacco control adver- tising exposure, altbougb some models were less robust wben tobacco control ad exposure was removed as a covadate.
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Our study did have limitations. Our use of cross-sectional survey data reduced our abil- ity to make direct causal inferences about whether potential exposure to tobacco com- pany parent-targeted advertising resulted in changes to youth smoking behavior, or whether an unmeasured factor may better ex- plain the relations we observed. However, our ability to adjust for competing advertising ex- posures, our use of regional and year dummy variables, our sensitivity analyses, and the fact that we observed results for tobacco pol- jĵ 23,24 ^^j other advertising covariates"'^^ that were largely consistent with those found in previous studies, lead us to believe that it is unlikely that we are misrepresenting the rela- tion between exposure to tobacco company youth-targeted or parent-targeted advertising and youth smoking outcomes. An alternate hypothesis is that tobacco companies may have purposefully purchased parent-tcirgeted advertising in media markets that have higher youth smoking rates. This seems unlikely, however, given that the vast majority of their television time was bought through national network and cable channels and was not sup- plemented by the purchase of local media market television time. In addition, although the study had a large sample size, which makes differences between groups more likely to achieve statistical significance, the overall consistency in the pattern and robust- ness of findings leads one to conclude that the detected relations are reed.
As previously mentioned, another study limitation is that because TRPs measure aver- age exposure for the overall population in a media market, individual youths may have more or less actual exposure, depending upon their own viewing habits. However, when we adjusted for self-reported television watching, the relations between tobacco company youth- targeted and parent-targeted advertising and smoking in the past 30 days did not change for students in grade 8 and strengthened for students in grades 10 and 12, Previous studies of antitobacco and antidrug advertising have found a strong correlation between advertising recall and TRP measures,"'^'
Studies that use controlled exposure have indicated that tobacco company youth- targeted advertisements are less likely than those from state tobacco control programs to
make youths stop and think about smoking'" and are of less interest to youths,^^ In 1 na- tional study, Philip Morris "Think, Don't Smoke" advertisements were associated with increased intention to smoke and more favor- able feelings towards the tobacco industry,^ Massachusetts youths aged 14-17 who re- called seeing Philip Morris' "Think, Don't Smoke" ads perceived them to be less effec- tive them ads that featured the serious conse- quences of smoking,* Our finding of no relation between tobacco company youth- targeted advertising and youth smoking sub- stantiates these previous results. Although to- bacco company youth-targeted advertising was withdrawn from US television in early 2003, ads continue to be broadcast in other countries, contributing "clutter" to other public health-sponsored advertising efforts'̂ that have been shown to be effective, "'̂ '̂̂ ^
Our finding of potentially harmful relations between tobacco company parent-targeted smoking prevention advertising emd youth smoking is a source of concern. Our observa- tion of adverse relations associated with par- ent-targeted advertising is not simply an arti- fact of our methodological approach: we have previously reported beneficial relations be- tween exposure to state-sponsored antito- bacco advertising and youth smoking beliefs and behavior using the same methods.^^
Why might such advertising have harmful relations, espedally for older teens? Although parents are the overt target group of tobacco company parent-targeted advertising, youths are exposed to them, on average, at levels al- most equivalent to those of state-sponsored antitobacco campaigns. The overt message of the parent-targeted campaign is that parents should talk to their children about smoking, but no reason beyond simply being a teen- ager is offered as to why youths should not smoke.
Theories in developmental psychology sug- gest that authority messages specific to teen- agers invite rejection by those who have mi- grated to a domincint peer group orientation as they make the transition to adulthood, typi- cally between ages 15 to 17 years,̂ *'̂ ^ As ado- lescents age toward adulthood, they are more inclined to perceive themselves as independent and self-reliant and less likely to report that they rely on their parents for guidance or
assistance,̂ * Evaluations of the US National Anti-Drug Media Campaign, which used messages encouraging parents to talk to their children about ilMcit drugs, have also reported unfavorable effects on adolescents,^"'" Facili- tating productive interaction between parents and adolescents about substance use may re- quire more intensive intervention approaches than simple encouragement through the mass media, which may do more harm than good.
During depositions and testimony in US- based tobacco trials, tobacco company wit- nesses put forward their youth smoking pre- vention efforts as evidence that they are concerned about youth smoking and that the campaigns are part of efforts to reduce youth smoking,''̂ However, during questioning at such a trial, Carolyn Levy, director of Philip Morris youth smoking prevention programs, admitted that the aim of their programs was to delay smoking until age 18,̂ ^ This con- trasts with the aims of public health-funded programs, which are to encourage people to never take up smoking.
In summary, our analysis suggests that to- bacco company youth- and parent-targeted smoking prevention advertising campaigns confer no benefit to youths, and especially for older teens, parent-targeted advertising may have harmful relations. In the United States, youths have the benefit of the national Amer- ican Legacy Foundation antitobacco cam- paign, as well as state antitobacco campaigns. The Legacy Foundation's budget cuts will force it to advertise less in the future,'''' and state antitobacco campaign advertising has begun to decline as a result of reduced state tobacco control funding,'̂ '̂ "̂ Many other countries of the world have limited or no public health-sponsored televised antitobacco advertising. Given a media environment that has fewer demonstrably beneficial advertising messages, it is conceivable that tobacco com- pany smoking prevention ads could have even greater adverse effects on youth smok- ing behavior than suggested by this study, •
About the Authors Melanie Wakefield is with the Center for Behavioral Research in Cancer, The Cancer Council Victoria, Melbourne, Aus- tralia Yvonne Terry-McElrath, Patrick M. O'Malley, and Lloyd D. Johnston are mth the Institute for Social Research, University of Michigan. Ann Arbor. Sherry Emery, Frank/. Chaloupka, and Glen Szczypka are with the Institute for
December 2006, Vol 96, No, 12 | American Journal of Public Health Wakefield et al. | Peer Reviewed | Research and Practice | 2159
Health Research and Policy, University of Illinois, Chicago. Henry Saffer is with the Department of Economics, Kean University, Union, Nf. Brian Flay is with the Department of Public Health, Oregon State University, Corvallis.
Requests for reprints should be sent to Melanie Wakefield, PhD, Center for Behavioral Research in Cancer, The Cancer Council Victoria, I Rathdowne Street, Carlton, Victoria, Australia, 3053 (e-mail: melanie.wakefield@cancervic. org.au).
Contributors M. Wakefield eonceived and led the study and the writ- ing of the article. Y. Terry-McElrath conducted the anal- ysis and assisted with writing. S. Emery, H. Saffer. F. Chaloupka, B. Flay, P.M. O'Malley, and L.D. Johnston contributed to conception of the study and the analysis and assisted with writing. G. Szczypka undertook data management for the study and assisted with writing.
Acknowledgments The study was supported the National Cancer Institute State and Community Tobacco Control Initiative (grant CA86273), the National Institute on Drug Abuse (grant DA01411), and The Robert Wood Johnson Foundation (grant 032 769). Melanie Wakefield was supported by a VicHealth Senior Research Fellowship.
Human Participant Protection This study was approved by the University of Illinois, Chicago, institutional review board. Use of data from the Monitoring the Future school surveys received ethi- cal approval by the University of Michigan Behavioral Sciences institutional review board.
References 1. Hirschhom N. Corporate social responsibility and the tobacco industry: hope or hype? Tobacco Control. 2004;13(4);447-453.
2. Smith EA, Malone RE. Thinking the "unthinkable": why Philip Morris considered quitting. Tobacco Control. 2003;12(2):208-213.
3. Landman A, Ling PM, Glantz SA. Tobacco indus- try youth smoking prevention programs: protecting the industry and hurting tobacco control. Amf Public Heatth. 2002;92(6):917-930.
4. Sussman S. Tobacco industry youth tobacco pre- vention programming: a review. Prevention Science. 2002;3(l):57-67.
5. World Health Organization. Youth smoking preven- tion activities: results of regional situation analysis. Manilla, Philippines: WHO Western Pacific Regional Office; 2 0 0 4 .
6. Farrelly MC, Niederdeppe J, Yarsevich J. Youth to- bacco prevention mass media campaigns: past, present, and future directions. Tobacco Control. 2003;12 (Suppl 1): i35-47.
7. Fairclough G. Study slams Philip Morris ads telling teens not to smoke: how a market researcher who dedi- cated years to cigarette sales came to create antismoking ads. Wall Street foumal. May 29, 2002:Bl, 2P, lC.
8. Biener L. Antitobacco advertisements by Massa- chusetts and Philip Morris: wbat teenagers think. To- bacco Control. 2002;n(Suppl 2):ii43-46.
9. Teenage Research Unlimited. Counter-tobacco
advertising exploratory summary report fanuary-March 1999. Northbrook, IL: Teenage Research Unlimited; 1999.
10. Terry-McElrath Y, Wakefield M, Ruel E, et al. The effect of anti-smoking advertisement executional char- acteristics on youth appraisal and engagement. / Health Commun. 2 0 0 5 ; 10:127-143.
11. Farrelly MC, Healton CG, Davis KC, Messeri P, Haviland MH. Getting to the truth: evaluating national tobacco countermarketing campaigns. Amf Public Health. 2 0 0 2 ; 9 2 : 9 0 1 - 9 0 7
12. Wakefield M, Szczypka G, Terry-McElrath Y, et al. Mixed messages on tobacco: comparative exposure to public health, tobacco company and pharmaceutical company sponsored tobacco-related television cam- paigns in the United States, 1 9 9 9 - 2 0 0 3 . Addiction. 2005;100:1875-1883.
13. Borland R, Balmford J. Understanding how mass media campaigns impact on smokers. Tobacco Control. 2003;12 (Suppl 2):ii45-52.
14. Nielsen Media Research. DMA market and demo- graphic rank: September 2001. New York: Nielsen Media Research; 2 0 0 2 .
15. Szczypka G, Emery S, Wakefield M, Chaloupka F. The adaption and use of Nielsen Media Research commer- cial ratings data to measure potential exposure to televised smoking-related advertisements. Available at: http://www. impacteen.org/ab_RPNo29_2003.htm. Accessed Au- gust 15, 2 0 0 6 .
16. Johnston LD, O'Malley PM, Bachman JG. Monitor- ing the Future: national survey results on drug use, 1975- 2003. Volume 1: Secondary school students. Bethesda, MD: National Institute on Drug Abuse;2004. NIH Publication No. 0 4 - 5 5 0 7
17 Wakefield M, Kloska DD, O'Malley PM, et al. The role of smoking intentions in predicting future smoking among youth: findings from Monitoring the Future data. Addiction. 2004;99(7):914-922.
18. Duan NMW, Morris CN, Newhouse JP Choosing between the sample selection model and the multi-part model./BMsmess Fcon Stat. 1 9 8 4 ; 2 : 2 8 3 - 2 8 9 .
19. Bemdt E. The practice of econometrics: classic and contemporary. Reading, MA: Addison-Wesley Publishing Company; 1991.
20. Koyck LM. Distributed lags and investment analysis. Amsterdam: North Holland Publishers; 1959.
21. PoUay R, Siddarth S, Segal M, et al. The last straw? Cigarette advertising and realized market shares among youths and adults, 1 9 7 9 - 1 9 9 3 . / M a r f a m g . 1996; 60(2):l-16.
22. Emery S, Wakefield MA, Terry-McElrath Y, et al. Televised state-sponsored anti-tobacco advertising and youth smoking beliefs and bebavior in tbe United States, 1 9 9 9 - 2 0 0 0 . Arch Paediatr AdolescMed 2 0 0 5 ; 1 5 9 ; 6 3 9 - 6 4 5 .
2 3 . Chaloupka F, Warner K. The economics of smok- ing. In: Newhouse JP, Cuyler AJ, eds. The Handbook of Health Economics. New York: North Holland; 2 0 0 1 : 1539-1627.
24. Wakefield MA, Chaloupka FJ, Kaufman NJ, Or- leans CT, Barker DC, Ruel EE. Effect of restrictions on smoking at home, at school, and in public places on teenage smoking: cross sectional study. Br Medf. 2000; 3 2 1 ( 7 2 5 7 ) : 3 3 3 - 3 3 7
25. Southwell BG, Barmada CH, Homik RC, Maklan DM. Can we measure encoded exposure? Validation evidence from a national campaign. / Health Commun. 2002;7(5):445-453.
26. Wakefield M, Balch Gl, Ruel EE, et al. Youth re- sponses to anti-smoking advertisements from tobacco control agencies, tobacco companies and pharmaceuti- cal companies.//lpp/Soc ftycW. 2005;35:1894-1911.
27. Farrelly MC, Davis KC, Haviland ML, Messeri P, Healton CG. Evidence of a dose-response relationship between "truth" antismoking ads and youth smoking prevalence. Amf Public Health. 2005;95(3):425-431.
28. Crockett LJ, Petersen AC. Adolescent develop- ment: Health risks and opportunities for health promo- tion. In: Millstein SG, Petersen C, Nightingale EO, eds. Promoting the Health of Adolescents: New Directions for theTwenty-First Century, 1993, New York: Oxford Uni- versity Press; 1 9 9 3 ; 3 - 3 7
29. Ingra V, Irwin CE. Theories of adolescent risk taking behavior. In: Di Clemente RJ, Hansen WB, and Ponton LE, eds. Handbook of Adolescent Health Risk Be- havior, New York: Plenum Press; 1996.
30. Homik R, Maklan D, Cadell D, et al. Evaluation of the national youth anti-drug media campaign: fifth semi- annual report of findings. Available at: http://www.nida. nih.gov/DESPR/Westat/#reports. Accessed September 19, 2 0 0 5 .
31. Homik R, Maklan D, Cadell D, et al. Evaluation of the national youth antidrug media campaign: 2003 report of findings. Available at: http://www.nidajiih.gov/DESPR/ Westat/treports. Accessed September 19, 2 0 0 5 .
32. Wakefield M, Mcleod K, Perry CL. "Stay away from them until you're old enough to make a deci- sion": Tobacco company testimony about youtb smok- ing initiation. Tobacco Control. In press.
33. Schroeder SA. Tobacco control in the wake of the 1998 Master Settlement Agreement. New Engf Med. 2 0 0 4 ; 3 5 0 : 2 9 3 - 3 0 1 .
34. Szczypka G, Wakefield M, Emery S, et al. Esti- mated exposure of adolescents to state-funded anti- tobacco television advertisements - 37 states and the District of Columbia, 1 9 9 9 - 2 0 0 3 . MMWR. 2 0 0 5 ; 54(42): 1077-1080.
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