BACKGROUND AND OBJECTIVES:

Non–cigarette tobacco marketing is less regulated and may promote cigarette smoking among adolescents. We quantified receptivity to advertising for multiple tobacco products and hypothesized associations with susceptibility to cigarette smoking.

METHODS:

Wave 1 of the nationally representative PATH (Population Assessment of Tobacco and Health) study interviewed 10 751 adolescents who had never used tobacco. A stratified random selection of 5 advertisements for each of cigarettes, e-cigarettes, smokeless products, and cigars were shown from 959 recent tobacco advertisements. Aided recall was classified as low receptivity, and image-liking or favorite ad as higher receptivity. The main dependent variable was susceptibility to cigarette smoking.

RESULTS:

CONCLUSIONS:

A large proportion of US adolescent never tobacco users are receptive to tobacco advertising, with television advertising for e-cigarettes having the highest recall. Receptivity to advertising for each non–cigarette tobacco product was associated with susceptibility to smoke cigarettes.

What’s Known on This Subject:

The consensus that cigarette marketing is 1 cause of adolescent smoking is the basis for marketing constraints imposed on these products in the United States and elsewhere. Little is known about the influence of marketing for non–cigarette tobacco products.

Advertising for non–cigarette tobacco products is reaching non–tobacco-using US adolescents, especially through television. High percentages of non–tobacco-using adolescents recognize tobacco ad images, including e-cigarette ads. Receptivity to these ads is associated with susceptibility to future cigarette smoking.

Susceptibility to smoking is a validated measure that predicts the risk of smoking initiation as many as 3 to 4 years before first experimentation.23,25 A series of questions identifies “committed never users” as those who have never been curious about use, have strong intentions not to use, and who would resist an offer to use from a best friend. All other never users are considered susceptible. Susceptibility and subsequent experimentation vary across sociodemographic variables, receptivity to tobacco marketing,16,17 exposure to other tobacco users,26 use of another psychoactive substance,27 use of another tobacco product,28 and psychosocial variables such as externalizing problem behaviors (eg, rule-breaking, aggression),29 internalizing problem behaviors (eg, depression, anxiety),30 and sensation-seeking.31

This study explores levels of receptivity to the marketing of e-cigarettes, cigarettes, cigars, and smokeless tobacco products among never-using 12 to 17 year olds, with the use of data from the national Population Assessment of Tobacco and Health (PATH) Study. The study design allowed us to assess adolescent receptivity to advertising for multiple tobacco products and to summarize this in a measure of receptivity to any tobacco advertising. We investigated whether this general receptivity to tobacco advertising was associated with susceptibility to use any tobacco product. Finally, we investigated the associations of advertising receptivity to each product with susceptibility to cigarette smoking.

Data are from wave 1 of the PATH study, which is a nationally representative sample of the civilian, noninstitutionalized US population, aged ≥12 years between September 2013 and December 2014.32,33 With oversight from the National Institute of Drug Abuse and the Food and Drug Administration, Westat collected data with the use of audio-computer–assisted self-interviews. Westat’s Institutional Review Board approved the study design/protocol, and the Office of Management and Budget approved the data collection. Households were identified by using an address-based, area-probability sampling method, and a screener survey enumerated household members (response rate = 54%). Generally, all youth aged 12 to 17 years (maximum 2 per household) were selected for interview, and parental consent and youth assent were obtained. Interviews were completed for 78.4% of selected youth. The data were weighted to adjust for the complex sample design and nonresponse to allow population estimates. If the respondent did not answer regarding their age, sex, race, or Hispanic ethnicity, these were obtained from the household screener (n = 704 or 6.6%) or, if not available, by using statistical imputation methods (n = 143 or 1.3%).34 In this article, our analyses were restricted to the 10 751 of the youth sample (N = 13 651) who reported that they had never used any tobacco product.

Following previous research,23,24 never users who had heard of the product were classified as either susceptible to use or committed never users on the basis of their responses to 3 questions assessing their curiosity about the product, intention to try it in the near future, and likely response if a best friend were to offer them the product (see Supplemental Information). Only those with the strongest rejection to all 3 questions were categorized as committed never users to each of the following 8 products (cigarettes, e-cigarettes, pipes, cigars, hookahs, smokeless tobacco, dissolvable tobacco, and bidis/kreteks). The strongest rejection to all questions for all products classified an individual as a committed never tobacco user; all others were considered to be susceptible to use ≥1 products. For this analysis, those who had never heard of a product were considered to be committed never users.

Respondents were asked “What is the brand of your favorite tobacco advertisement?” A list of brands was provided, with an option to nominate another brand. We assumed that identifying Marlboro or Camel as favorite referred to cigarettes, unless snus was specifically mentioned.

#### Aided Recall and Liking of Contemporary Ads

The above sampling scheme allowed some respondents to see >1 ad for a brand within a category, particularly for the little cigars and cigarillos set in P2. When >1 ad was shown for a brand, aided recall was assessed only on the first ad that was displayed. We computed the estimated recall rate as the weighted proportion of respondents who recalled seeing an ad for the brand out of the total number of respondents who were shown an ad for the brand. Before ranking brands on the frequency of recall, we removed brands with advertisements that were shown to <500 participants. Thus, for the rank order of aided recall, we considered a total of 55 tobacco brands (9 cigarette brands, 9 e-cigarette brands with television ads, 14 e-cigarette brands with print ads, 9 smokeless brands, and 14 cigar brands).

#### Exposure to Tobacco Use

All respondents were asked: “Does anyone who lives with you now use any of the following: [list of tobacco products]” and “During the past 7 days, about how many hours were you around others who were smoking? Include time in your home, in a car, at school or outdoors.” We report 2 binary variables: 1 for household exposure (no users of tobacco in the household versus any) and 1 for general exposure (no exposure to smoking by others in the past 7 days versus any).

#### Use of Other Drugs or Alcohol

Ever use was ascertained for alcohol, marijuana, as well as for misuse of prescription drugs (ie, Ritalin/Adderall, painkillers, sedatives, tranquilizers), cocaine or crack, methamphetamine or speed, heroin, inhalants, solvents, and hallucinogens by a series of questions: “Have you ever used [substance]?” (See Supplemental Information for the full list of questions). Adolescents who reported ever use of any of these were classified as “any use”; all others were classified as “no use.”

#### Psychosocial Predictors of Tobacco Use

We adjusted for mental health and substance use problems by using scales from the Global Appraisal of Individual Needs–Short Screener.35 The internalizing subscale (α = .81) included 4 items of depressive and anxiety symptoms. The externalizing subscale (α = .70) included experience with 5 conduct and behavioral items. The substance use problems subscale (α = .67) asked 7 questions about problems associated with alcohol or drug use. Adolescents were scored on how many items they had experienced in the past month or past 2 to 12 months (see Supplemental Information for questions). In addition, sensation seeking (α = .74) was assessed by 3 items modified from the Brief Sensation Seeking Scale.36 On all scales, respondents were scored as having no symptoms (0), low to moderate symptom levels (1–2), or high symptom levels (≥3).

Analyses were performed by using SAS Software, version 9.3 (SAS Institute, Cary, NC).37 We used the survey weights supplied with the data, and computed variances and P values by using the recommended Balanced Repeated Replication method with Fay = 0.3.27,33,38 Weighted percentages were calculated with SAS version 9.3 PROC SURVEYFREQ. Modified Wilson confidence limits for proportions were calculated on the weighted estimates by using PROC SURVEYFREQ. Separate logistic regression models tested the association of receptivity to any tobacco advertising with susceptibility to any tobacco product, as well as with susceptibility to cigarette smoking. These models controlled for the above-mentioned covariates. χ2 Tests were also conducted to test for significant differences between percentage recall of pairs of selected ad brands or modes. Odds ratios, confidence limits, and P values are reported from the weighted, adjusted model (calculated via PROC SURVEYLOGISTIC).

This sample of adolescent never tobacco users was balanced on sex and had a high proportion of younger adolescents (12–13 years: 39.5%; 14–15 years: 34.1%; 16–17 years: 26.4%) (Table 1). Just over half were non-Hispanic white (53.6%), 22.4% were Hispanic, 14.4% were non-Hispanic African American, 5.2% were Asian, and 4.5% were other races/ethnicities. Most adolescents (82.0%) had parents who completed high school, and 60.7% had parents with at least some college education. Never tobacco users who were not receptive to any tobacco advertising (54%) had the lowest susceptibility to any tobacco use (34.3%; 95% confidence interval [CI]: 32.9%–35.6%). Among never users with low receptivity (34%), 50.4% (95% CI: 48.5%–52.2%) were susceptible. Among the 10% of never users who had a moderate receptivity, 65.4% (95% CI: 62.2%–68.4%) were susceptible. Among the <2% of never users with high receptivity to tobacco advertising, 87.7% (95% CI: 81.2%–92.2%) were susceptible to any tobacco product.

TABLE 1

Logistic Regression Predicting Susceptibility to Any Tobacco Product Among Never-Using Adolescents

VariablePopulationSusceptible
n%95% CI%95% CIaOR95% CIP
Age, y
12–13 4312 39.5 38.6–40.5 34.9 33.5–36.4 Ref — —
14–15 3689 34.1 33.2–35.0 47.7 45.9–49.5 1.38 1.25–1.53 <.001
16–17 2750 26.4 25.6–27.2 52.1 50.1–54.1 1.44 1.28–1.61 <.001
Sex
Male 5422 50.4 49.5–51.4 43.5 42.1–44.9 1.12 1.02–1.24 .02
Female 5329 49.6 48.6–50.5 44.1 42.7–45.7 Ref — —
Race/ethnicity
NH white 5107 53.6 52.6–54.5 41.5 39.9–43.2 Ref — —
NH African American 1538 14.4 13.8–15.1 48.3 45.4–51.2 1.46 1.25–1.70 <.001
Hispanic 3132 22.4 21.6–23.2 46.7 44.9–48.5 1.63 1.47–1.81 <.001
Asian 318 5.2 4.8–5.6 36.8 31.5–42.4 1.14 0.87–1.49 .34
Other 656 4.5 4.1–4.9 50.1 45.8–54.5 1.32 1.07–1.63 .009
School performance
Mostly A’s 3003 30.0 29.0–31.0 37.2 35.5–39.0 0.72 0.63–0.82 <.001
A’s and B’s 3796 34.8 33.9–35.7 44.2 42.4–46.3 0.89 0.78–1.01 .08
Other 3952 35.2 34.1–36.3 49.0 47.3–50.7 Ref — —
Parental educationa
Less than HS graduate 2184 17.2 16.1–18.5 43.5 41.5–45.6 Ref — —
HS graduate 2408 21.3 20.2–22.5 42.2 40.2–44.2 0.92 0.81–1.05 .21
Some college 2876 26.9 25.6–28.3 44.4 42.4–46.5 1.00 0.89–1.13 .97
College graduate 3205 33.8 31.6–36.0 44.5 42.5–46.4 1.25 1.09–1.43 .001
No data 78 0.8 0.06–1.0 45.2 34.0–56.9 1.08 0.67–1.74 .77
Tobacco user in HH
No 7427 70.3 68.6–72.0 41.0 39.6–42.4 — — —
Yes 3324 29.7 28.0–31.4 50.5 48.6–52.5 1.19 1.06–1.34 .003
Exposure to smoking
Some exposure 3834 35.0 33.8–36.3 53.5 51.8–55.1 1.39 1.26–1.54 <.001
No exposure 6917 65.0 63.7–66.2 38.6 37.3–39.9 Ref — —
None 5762 54.1 53.0–55.3 34.3 32.9–35.6 Ref — —
Low 3741 34.1 33.0–35.3 50.4 48.5–52.2 1.38 1.24–1.53 <.001
Moderate 1070 10.1 9.5–10.7 65.4 62.2–68.4 2.39 2.02–2.84 <.001
High 178 1.7 1.4–2.0 87.7 81.2–92.2 6.73 3.90–11.61 <.001
Internalizing problems
None 3627 33.5 32.4–34.5 28.9 27.3–30.5 Ref — —
Low–moderate 3606 33.8 32.7–34.9 43.4 41.8–45.1 1.34 1.19–1.51 <.001
High 3518 32.8 31.6–34.0 59.4 57.3–61.5 1.62 1.42–1.84 <.001
Externalizing problems
None 3767 35.0 33.8–36.1 26.2 24.6–27.8 Ref — —
Low–moderate 4198 38.9 37.9–39.9 46.9 45.2–48.6 1.55 1.39–1.73 <.001
High 2786 26.1 25.1–27.1 62.8 60.6–65.0 2.07 1.81–2.37 <.001
Sensation seeking
None 6536 61.0 60.0–62.0 34.3 33.1–35.5 Ref — —
Low–moderate 3678 34.0 33.1–34.9 56.3 54.4–58.1 1.58 1.43–1.76 <.001
High 537 5.0 4.6–5.4 75.2 70.5–79.3 2.52 1.92–3.29 <.001
Substance use problems
None 10 251 95.5 95.1–95.9 42.3 41.3–43.4 Ref — —
Low–moderate 426 3.9 3.5–4.3 74.5 69.7–78.8 0.99 0.74–1.32 .95
High 74 0.6 0.5–0.8 82.8 72.7–89.8 1.41 0.74–2.69 .30
Used other substances
No 7269 66.8 65.5–68.1 32.0 30.9–33.1 Ref — —
Yes 3482 33.2 31.9–34.5 67.6 66.0–69.2 2.99 2.69–3.33 <.001
VariablePopulationSusceptible
n%95% CI%95% CIaOR95% CIP
Age, y
12–13 4312 39.5 38.6–40.5 34.9 33.5–36.4 Ref — —
14–15 3689 34.1 33.2–35.0 47.7 45.9–49.5 1.38 1.25–1.53 <.001
16–17 2750 26.4 25.6–27.2 52.1 50.1–54.1 1.44 1.28–1.61 <.001
Sex
Male 5422 50.4 49.5–51.4 43.5 42.1–44.9 1.12 1.02–1.24 .02
Female 5329 49.6 48.6–50.5 44.1 42.7–45.7 Ref — —
Race/ethnicity
NH white 5107 53.6 52.6–54.5 41.5 39.9–43.2 Ref — —
NH African American 1538 14.4 13.8–15.1 48.3 45.4–51.2 1.46 1.25–1.70 <.001
Hispanic 3132 22.4 21.6–23.2 46.7 44.9–48.5 1.63 1.47–1.81 <.001
Asian 318 5.2 4.8–5.6 36.8 31.5–42.4 1.14 0.87–1.49 .34
Other 656 4.5 4.1–4.9 50.1 45.8–54.5 1.32 1.07–1.63 .009
School performance
Mostly A’s 3003 30.0 29.0–31.0 37.2 35.5–39.0 0.72 0.63–0.82 <.001
A’s and B’s 3796 34.8 33.9–35.7 44.2 42.4–46.3 0.89 0.78–1.01 .08
Other 3952 35.2 34.1–36.3 49.0 47.3–50.7 Ref — —
Parental educationa
Less than HS graduate 2184 17.2 16.1–18.5 43.5 41.5–45.6 Ref — —
HS graduate 2408 21.3 20.2–22.5 42.2 40.2–44.2 0.92 0.81–1.05 .21
Some college 2876 26.9 25.6–28.3 44.4 42.4–46.5 1.00 0.89–1.13 .97
College graduate 3205 33.8 31.6–36.0 44.5 42.5–46.4 1.25 1.09–1.43 .001
No data 78 0.8 0.06–1.0 45.2 34.0–56.9 1.08 0.67–1.74 .77
Tobacco user in HH
No 7427 70.3 68.6–72.0 41.0 39.6–42.4 — — —
Yes 3324 29.7 28.0–31.4 50.5 48.6–52.5 1.19 1.06–1.34 .003
Exposure to smoking
Some exposure 3834 35.0 33.8–36.3 53.5 51.8–55.1 1.39 1.26–1.54 <.001
No exposure 6917 65.0 63.7–66.2 38.6 37.3–39.9 Ref — —
None 5762 54.1 53.0–55.3 34.3 32.9–35.6 Ref — —
Low 3741 34.1 33.0–35.3 50.4 48.5–52.2 1.38 1.24–1.53 <.001
Moderate 1070 10.1 9.5–10.7 65.4 62.2–68.4 2.39 2.02–2.84 <.001
High 178 1.7 1.4–2.0 87.7 81.2–92.2 6.73 3.90–11.61 <.001
Internalizing problems
None 3627 33.5 32.4–34.5 28.9 27.3–30.5 Ref — —
Low–moderate 3606 33.8 32.7–34.9 43.4 41.8–45.1 1.34 1.19–1.51 <.001
High 3518 32.8 31.6–34.0 59.4 57.3–61.5 1.62 1.42–1.84 <.001
Externalizing problems
None 3767 35.0 33.8–36.1 26.2 24.6–27.8 Ref — —
Low–moderate 4198 38.9 37.9–39.9 46.9 45.2–48.6 1.55 1.39–1.73 <.001
High 2786 26.1 25.1–27.1 62.8 60.6–65.0 2.07 1.81–2.37 <.001
Sensation seeking
None 6536 61.0 60.0–62.0 34.3 33.1–35.5 Ref — —
Low–moderate 3678 34.0 33.1–34.9 56.3 54.4–58.1 1.58 1.43–1.76 <.001
High 537 5.0 4.6–5.4 75.2 70.5–79.3 2.52 1.92–3.29 <.001
Substance use problems
None 10 251 95.5 95.1–95.9 42.3 41.3–43.4 Ref — —
Low–moderate 426 3.9 3.5–4.3 74.5 69.7–78.8 0.99 0.74–1.32 .95
High 74 0.6 0.5–0.8 82.8 72.7–89.8 1.41 0.74–2.69 .30
Used other substances
No 7269 66.8 65.5–68.1 32.0 30.9–33.1 Ref — —
Yes 3482 33.2 31.9–34.5 67.6 66.0–69.2 2.99 2.69–3.33 <.001

Percentages, confidence limits, odds ratios, and P values are all weighted estimates. Other categories presented in the table may include respondents who did not provide data for the question. HH, household; HS, high school; NH, non-Hispanic; Ref, reference.

a

There were 78 records that did not include information on parental educational level.

Overall, 41.0% of 12 to 13 year olds and approximately half of both 14 to 15 year olds and 16 to 17 year olds were classified as being receptive to any tobacco advertising (Table 2). Approximately one-third of each age group had a low level of receptivity. There were significantly fewer 12 to 13 year olds with moderate or high receptivity (8.8%) compared with 16- to 17-year-old adolescents (15.0%) (P < .001).

TABLE 2

Receptivity to Tobacco Advertising by Product Type Among Never Tobacco Users

Product Type and Age, yReceptivity
LowModerateHighAnya
%95% CI%95% CI%95% CI%95% CI
Any product
12–13 32.2 30.8–33.8 7.6 6.7–8.5 1.2 0.9–1.6 41.0 39.5–42.6
14–15 36.0 34.2–37.8 11.2 10.0–12.4 1.6 1.2–2.1 48.7 46.8–50.6
16–17 34.5 32.6–36.5 12.5 11.1–13.9 2.5 1.9–3.3 49.5 47.4–51.6
E-cigarettes
12–13 24.2 22.9–25.6 3.3 2.7–3.9 0.3 0.2–0.6 27.8 26.5–29.2
14–15 28.0 26.4–29.7 4.2 3.5–5.1 0.5 0.3–0.8 32.8 31.0–34.5
16–17 27.2 25.5–28.9 4.9 4.1–6.0 0.6 0.3–1.0 32.7 30.6–34.8
Cigarettes
12–13 18.2 17.0–19.5 3.1 2.5–3.7 0.2 0.1–0.4 21.5 20.2–22.8
14–15 19.5 18.1–21.0 5.2 4.3–6.2 0.3 0.2–0.5 25.0 23.36–26.8
16–17 17.7 16.0–19.4 6.4 5.6–7.4 0.9 0.6–1.4 25.0 23.3–26.8
Smokeless tobacco
12–13 12.2 11.2–13.3 2.4 2.0–3.0 0.1 0.1–0.3 14.8 13.5–16.1
14–15 16.1 14.7–17.6 3.5 2.9–4.2 0.2 0.1–0.4 19.8 18.2–21.5
16–17 15.6 14.1–17.2 4.8 4.0–5.7 0.1 0.1–0.4 20.5 18.9–22.2
Cigarsb
12–13 6.6 5.8–7.4 1.4 1.0–1.8 0.0 0.0–0.2 7.9 7.1–8.9
14–15 8.8 7.9–9.7 1.9 1.4–2.6 0.1 0.0–0.4 10.8 9.8–11.9
16–17 8.8 7.7–10.0 3.7 3.0–4.5 0.1 0.0–0.2 12.6 11.3–14.0
Product Type and Age, yReceptivity
LowModerateHighAnya
%95% CI%95% CI%95% CI%95% CI
Any product
12–13 32.2 30.8–33.8 7.6 6.7–8.5 1.2 0.9–1.6 41.0 39.5–42.6
14–15 36.0 34.2–37.8 11.2 10.0–12.4 1.6 1.2–2.1 48.7 46.8–50.6
16–17 34.5 32.6–36.5 12.5 11.1–13.9 2.5 1.9–3.3 49.5 47.4–51.6
E-cigarettes
12–13 24.2 22.9–25.6 3.3 2.7–3.9 0.3 0.2–0.6 27.8 26.5–29.2
14–15 28.0 26.4–29.7 4.2 3.5–5.1 0.5 0.3–0.8 32.8 31.0–34.5
16–17 27.2 25.5–28.9 4.9 4.1–6.0 0.6 0.3–1.0 32.7 30.6–34.8
Cigarettes
12–13 18.2 17.0–19.5 3.1 2.5–3.7 0.2 0.1–0.4 21.5 20.2–22.8
14–15 19.5 18.1–21.0 5.2 4.3–6.2 0.3 0.2–0.5 25.0 23.36–26.8
16–17 17.7 16.0–19.4 6.4 5.6–7.4 0.9 0.6–1.4 25.0 23.3–26.8
Smokeless tobacco
12–13 12.2 11.2–13.3 2.4 2.0–3.0 0.1 0.1–0.3 14.8 13.5–16.1
14–15 16.1 14.7–17.6 3.5 2.9–4.2 0.2 0.1–0.4 19.8 18.2–21.5
16–17 15.6 14.1–17.2 4.8 4.0–5.7 0.1 0.1–0.4 20.5 18.9–22.2
Cigarsb
12–13 6.6 5.8–7.4 1.4 1.0–1.8 0.0 0.0–0.2 7.9 7.1–8.9
14–15 8.8 7.9–9.7 1.9 1.4–2.6 0.1 0.0–0.4 10.8 9.8–11.9
16–17 8.8 7.7–10.0 3.7 3.0–4.5 0.1 0.0–0.2 12.6 11.3–14.0

Percentages and confidence limits are weighted estimates. N = 10 751.

a

Any receptivity is the sum of low, moderate, and high receptivity levels. No receptivity is not shown but is equal to 100 − any. For all products, the age differences are significant (P < .001), as determined by χ2 tests.

b

Cigars include traditional cigars, cigarillos, and filtered cigars.

In multivariable logistic regression (Table 1) controlling for potential confounding variables, even low receptivity to any tobacco ads was significantly associated with increased concurrent susceptibility to use any tobacco product (adjusted odds ratio [aOR]: 1.38; 95% CI: 1.25–1.53). Moderate and high receptivity levels had higher and significant odds ratios (moderate: aOR = 2.39, P < .001; high: aOR = 6.73, P < .001).

TABLE 3

Ads for Tobacco Brands With the Highest Aided Recall by Age Group Among US Never Tobacco Users

12–13 y14–15 y16–17 yTotal
%95% CI%95% CI%95% CI%95% CI
Blu cig (TV) E-cigarette 5668 27.2 25.2–29.2 35.0 32.6–37.6 31.8 28.8–34.9 31.0 29.5–32.5
Blu cig (print) E-cigarette 6125 20.2 18.5–22.0 23.4 21.4–25.6 24.2 21.9–26.5 22.3 21.1–23.6
Grizzly Oral dip 10 545 8.9 7.9–10.0 11.5 10.2–12.8 11.5 10.2–12.9 10.5 9.7–11.2
Camel Cigarette 10 751 10.4 9.5–11.4 10.5 9.5–11.5 9.3 8.1–10.6 10.1 9.5–10.8
Vapor Shark (TV) E-cigarette 1335 11.6 8.6–15.3 8.6 6.0–12.2 10.0 7.3–13.7 10.1 8.3–12.3
NJOY (TV) E-cigarette 1848 9.1 7.0–11.6 9.9 7.6–12.8 8.7 6.3–11.9 9.2 7.7–11.1
NJOY (print) E-cigarette 6100 8.5 7.4–9.7 9.3 8.0–10.7 8.6 7.2–10.3 8.8 8.0–9.6
Marlboro Cigarette 10 751 8.6 7.8–9.5 9.0 8.0–10.0 7.6 6.5–8.9 8.4 7.9–9.0
Newport Cigarette 10 751 6.7 5.8–7.7 8.3 7.4–9.5 8.7 7.6–9.9 7.8 7.1–8.5
10 VUSE (TV) E-cigarette 1485 7.1 5.0–9.8 6.8 4.9–9.3 6.7 4.5–9.7 6.9 5.6–8.4
11 V4L Vapor4Life (print) E-cigarette 1000 4.5 2.9–7.1 4.9 3.1–7.6 10.0 6.6–15.0 6.1 4.7–7.9
12 NEO (print) E-cigarette 528 5.1 2.7–9.4 6.5 3.4–11.9 6.7 3.1–14.0 6.0 4.1–8.8
13 VUSE (print) E-cigarette 755 6.3 4.0–9.7 6.4 4.0–10.0 5.0 2.7–9.0 6.0 4.3–8.2
14 Zig Zag Cigarillo/little cigar 841 4.9 3.0–7.8 5.4 3.3–8.9 7.4 4.5–12.0 5.8 4.4–7.6
15 Camel Snus 7832 4.7 4.0–5.6 6.5 5.5–7.8 5.4 4.2–7.0 5.5 4.9–6.2
16 Gold Cigarillo/little cigar 853 3.9 2.3–6.7 4.9 2.7–8.8 6.4 3.7–10.7 4.9 3.7–6.6
17 Marlboro Snus 683 4.4 2.3–8.2 5.9 3.3–10.1 4.5 2.4–8.3 4.9 3.4–7.0
18 Skoal Oral dip 1211 3.5 2.0–6.0 5.9 4.0–8.5 5.1 2.7–9.3 4.7 3.5–6.3
19 L&M Cigarette 5022 4.6 3.7–5.6 4.9 3.8–6.2 4.2 3.1–5.6 4.6 3.9–5.3
20 Apollo (print) E-cigarette 739 4.2 2.4–7.3 4.9 2.6–9.0 4.3 2.2–8.2 4.4 3.2–6.2
12–13 y14–15 y16–17 yTotal
%95% CI%95% CI%95% CI%95% CI
Blu cig (TV) E-cigarette 5668 27.2 25.2–29.2 35.0 32.6–37.6 31.8 28.8–34.9 31.0 29.5–32.5
Blu cig (print) E-cigarette 6125 20.2 18.5–22.0 23.4 21.4–25.6 24.2 21.9–26.5 22.3 21.1–23.6
Grizzly Oral dip 10 545 8.9 7.9–10.0 11.5 10.2–12.8 11.5 10.2–12.9 10.5 9.7–11.2
Camel Cigarette 10 751 10.4 9.5–11.4 10.5 9.5–11.5 9.3 8.1–10.6 10.1 9.5–10.8
Vapor Shark (TV) E-cigarette 1335 11.6 8.6–15.3 8.6 6.0–12.2 10.0 7.3–13.7 10.1 8.3–12.3
NJOY (TV) E-cigarette 1848 9.1 7.0–11.6 9.9 7.6–12.8 8.7 6.3–11.9 9.2 7.7–11.1
NJOY (print) E-cigarette 6100 8.5 7.4–9.7 9.3 8.0–10.7 8.6 7.2–10.3 8.8 8.0–9.6
Marlboro Cigarette 10 751 8.6 7.8–9.5 9.0 8.0–10.0 7.6 6.5–8.9 8.4 7.9–9.0
Newport Cigarette 10 751 6.7 5.8–7.7 8.3 7.4–9.5 8.7 7.6–9.9 7.8 7.1–8.5
10 VUSE (TV) E-cigarette 1485 7.1 5.0–9.8 6.8 4.9–9.3 6.7 4.5–9.7 6.9 5.6–8.4
11 V4L Vapor4Life (print) E-cigarette 1000 4.5 2.9–7.1 4.9 3.1–7.6 10.0 6.6–15.0 6.1 4.7–7.9
12 NEO (print) E-cigarette 528 5.1 2.7–9.4 6.5 3.4–11.9 6.7 3.1–14.0 6.0 4.1–8.8
13 VUSE (print) E-cigarette 755 6.3 4.0–9.7 6.4 4.0–10.0 5.0 2.7–9.0 6.0 4.3–8.2
14 Zig Zag Cigarillo/little cigar 841 4.9 3.0–7.8 5.4 3.3–8.9 7.4 4.5–12.0 5.8 4.4–7.6
15 Camel Snus 7832 4.7 4.0–5.6 6.5 5.5–7.8 5.4 4.2–7.0 5.5 4.9–6.2
16 Gold Cigarillo/little cigar 853 3.9 2.3–6.7 4.9 2.7–8.8 6.4 3.7–10.7 4.9 3.7–6.6
17 Marlboro Snus 683 4.4 2.3–8.2 5.9 3.3–10.1 4.5 2.4–8.3 4.9 3.4–7.0
18 Skoal Oral dip 1211 3.5 2.0–6.0 5.9 4.0–8.5 5.1 2.7–9.3 4.7 3.5–6.3
19 L&M Cigarette 5022 4.6 3.7–5.6 4.9 3.8–6.2 4.2 3.1–5.6 4.6 3.9–5.3
20 Apollo (print) E-cigarette 739 4.2 2.4–7.3 4.9 2.6–9.0 4.3 2.2–8.2 4.4 3.2–6.2

Percentages and confidence limits are weighted estimates. In cases in which a respondent saw >1 ad for a brand, only the response to the first presentation of the ad was tallied. Modified Wilson confidence limits are reported. TV, television.

a

Rank order is from the Total column for ages 12–17 y.

In our multivariable logistic regression controlling for potential covariates, moderate to high receptivity to cigarettes (aOR: 1.57; 95% CI: 1.25–1.98), e-cigarettes (aOR: 1.53; 95% CI: 1.21–1.94), and smokeless tobacco (aOR: 1.58; CI: 1.23–2.03) was significantly associated with concurrent susceptibility to smoke cigarettes (Table 4), which was not the case for moderate to high receptivity to cigar advertising. A low level of receptivity to any of the 4 forms of tobacco advertising was not associated with concurrent susceptibility to smoke cigarettes.

TABLE 4

Variables Associated With Susceptibility to Cigarette Smoking Among Adolescent Never Tobacco Users

Receptivity toPopulationSusceptible to Cigarette Smoking
n%95% CI% Susceptible95% CIaOR95% CIP
No receptivity 8158 76.4 75.38–77.36 26.9 25.88–28.00 Ref — —
Low receptivity 2054 18.5 17.64–19.42 37.3 35.12–39.58 1.08 0.96–1.22 .20
Moderate–high receptivity 539 5.1 4.60–5.67 51.6 46.71–56.41 1.57 1.25–1.98 <.001
No receptivity 8822 82.0 81.04–82.92 27.8 26.81–28.80 Ref — —
Low receptivity 1560 14.4 13.61–15.30 38.1 35.38–40.85 1.03 0.88–1.22 .70
Moderate–high receptivity 369 3.6 3.20–3.96 51.2 45.97–56.34 1.58 1.23–2.03 <.001
No receptivity 9617 89.9 89.28–90.42 28.5 27.51–29.44 Ref — —
Low receptivity 890 7.9 7.37–8.45 41.9 38.32–45.49 1.13 0.94–1.36 .20
Moderate–high receptivity 244 2.2 1.95–2.58 54.6 47.65–61.41 1.15 0.81–1.63 .42
No receptivity 7384 69.2 68.13–70.27 26.2 25.14–27.32 Ref — —
Low receptivity 2890 26.3 25.28–27.35 36.3 34.49–38.11 1.11 0.99–1.25 .06
Moderate–high receptivity 477 4.5 4.07–4.94 54.0 48.79–59.17 1.53 1.21–1.94 <.001
Receptivity toPopulationSusceptible to Cigarette Smoking
n%95% CI% Susceptible95% CIaOR95% CIP
No receptivity 8158 76.4 75.38–77.36 26.9 25.88–28.00 Ref — —
Low receptivity 2054 18.5 17.64–19.42 37.3 35.12–39.58 1.08 0.96–1.22 .20
Moderate–high receptivity 539 5.1 4.60–5.67 51.6 46.71–56.41 1.57 1.25–1.98 <.001
No receptivity 8822 82.0 81.04–82.92 27.8 26.81–28.80 Ref — —
Low receptivity 1560 14.4 13.61–15.30 38.1 35.38–40.85 1.03 0.88–1.22 .70
Moderate–high receptivity 369 3.6 3.20–3.96 51.2 45.97–56.34 1.58 1.23–2.03 <.001
No receptivity 9617 89.9 89.28–90.42 28.5 27.51–29.44 Ref — —
Low receptivity 890 7.9 7.37–8.45 41.9 38.32–45.49 1.13 0.94–1.36 .20
Moderate–high receptivity 244 2.2 1.95–2.58 54.6 47.65–61.41 1.15 0.81–1.63 .42
No receptivity 7384 69.2 68.13–70.27 26.2 25.14–27.32 Ref — —
Low receptivity 2890 26.3 25.28–27.35 36.3 34.49–38.11 1.11 0.99–1.25 .06
Moderate–high receptivity 477 4.5 4.07–4.94 54.0 48.79–59.17 1.53 1.21–1.94 <.001

Percentages, odds ratios, confidence limits, and P values are all from weighted estimates. The logistic regression model controlled for the variables listed in Table 1: age, sex, race-ethnicity, parental education, school performance, and tobacco use in the household as well as exposure to smoking, the psychosocial risk factor summary measure (none versus any externalizing, internalizing, sensation seeking, or substance use problems), and use of other substances. An indicator for receptivity to each of the product categories was included in the model; thus, a respondent might be receptive to multiple products. Ref, reference.

a

Cigars include traditional cigars, cigarillos, and filtered cigars.

Despite marketing restrictions on cigarettes and other products, tobacco advertising continues to reach one-third to one-half of adolescents, depending on age. E-cigarette advertising generated the highest reach. This dominance of e-cigarettes is in stark contrast to the advertising expenditures for each product over the study period: >$9 billion/year for cigarettes,39$415 million/year for smokeless products,40 and only \$60 million/year for e-cigarettes4 (although this latter amount appears to be growing substantially each year). One explanation for receptivity being highest for the product with the lowest marketing budget4 is that the product with minimal marketing restrictions may have a significant advantage. Products with less-restricted marketing can use marketing synergies across multiple media channels, which are likely more cost-effective than campaigns for products with significant marketing restrictions.41 It has been noted that television is still among the most effective advertising platforms in the United States.42 In this study, 4 of the top 10 ads recalled were e-cigarette television ads, which made up only a portion of the e-cigarette marketing expenditures, a budget that was 2 orders of magnitude below the cigarette marketing budget.4,39 Our results suggest that, even though cigarettes are not allowed to be advertised on television, interest in them may be increased through observing ads for other tobacco products. This topic, along with how receptivity may affect harm perceptions, will be explored in separate longitudinal analyses of PATH study data.

Two major study strengths are its large nationally representative sample of adolescents and the use of a stratified random sample from a near census of recent tobacco advertising images to gauge reach and receptivity. A limitation is that our findings are cross-sectional and the directionality of associations cannot be determined. However, susceptibility has been a consistent precursor of risk of smoking initiation2 and, in the PATH study wave 1, susceptibility to use tobacco among 12 to 17 year olds appears to be equivalent to the prevalence of experimentation for those aged a few years older.43 Moreover, this sample will be followed longitudinally, allowing us to confirm whether both low and moderate/high receptivity to tobacco advertising predicts later tobacco use behavior among these never smokers.

In this survey, 41% of US 12 to 13 year olds, as well as half of older adolescents who had never used tobacco, were receptive to tobacco adverting and this receptivity was associated with increased susceptibility to cigarette smoking, regardless of the type of tobacco product advertised. Indeed, there was no difference in the association between receptivity for advertising for the different tobacco products and susceptibility to cigarette smoking. E-cigarette advertising was the most recalled by US adolescents, particularly ads that were shown on television. This high level of recall was achieved despite e-cigarette advertising expenditures being a fraction of those for cigarette marketing.

• CI

confidence interval

•
• aOR

•
• P1

period 1

•
• P2

period 2

•
• PATH

Population Assessment of Tobacco and Health

Dr Pierce conceptualized and designed the study and drafted the initial manuscript; Dr Sargent conceptualized and designed the study including the study instruments and critically reviewed the manuscript; Ms White carried out the initial analyses and reviewed and revised the manuscript; Dr Messer designed the analyses and reviewed and revised the manuscript; Drs Carusi and Hyland lead the PATH project, including the design of survey instruments, and reviewed and revised the manuscript; and Drs Borek, Portnoy, Kaufman, Stanton, Bansal-Travers, Strong, Pearson, Coleman, Trinidad, and Moran and Ms Green, Ms Noble, and Mr Leas reviewed and approved the initial proposed analyses and reviewed and revised the manuscript; and all authors approved the final manuscript as submitted.

The views and opinions expressed in this presentation are those of the authors only and do not necessarily represent the views, official policy, or position of the US Department of Health and Human Services or any of its affiliated institutions or agencies.

FUNDING: This study is supported with federal funds from the National Institute on Drug Abuse, National Institutes of Health, and the Food and Drug Administration, Department of Health and Human Services, under a contract to Westat (contract HHSN271201100027C). Funded by the National Institutes of Health (NIH).

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## Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.