BACKGROUND AND OBJECTIVES

The objective of the current study is to evaluate the temporal trends in the prevalence of cigarette and electronic cigarette (e-cigarette) advertisement exposure by venue and sociodemographic correlates among US adolescents from 2012 to 2020.

METHODS

We conducted a serial cross-sectional analysis of nationally representative samples of middle and high school youth from the 2012–2020 National Youth Tobacco Survey. Advertisement exposure was defined as self-report of seeing advertisements “sometimes,” “most of the time,” and “always.” The prevalence of cigarette (and other tobacco products) and e-cigarette advertisement exposure, including overall and at specific venues (Internet, press, screen, and retail stores), was estimated by survey year.

RESULTS

A total of 139 795 adolescents aged 11 to 19 years old were included in the analysis. The prevalence of exposure to combustible cigarette marketing remained high across all years (any venue ranging from 77.0% [2018] to 91.1% [2014]). An increasing trend for cigarette advertisement exposure was observed from 2017 to 2020 after a drop in 2015 (β2012–2015 = 2.8, P for trend < .001; β2017–2020 = .7, P for trend = .03), driven by retail store–based and Internet-based exposure. A similar increasing pattern in the estimated prevalence of e-cigarette marketing was observed (β2014–2016 = 4.6, P for trend < .001; β2017–2020 = 5.1, P for trend < .001).

CONCLUSIONS

Given the high estimated prevalence of cigarette and e-cigarette marketing exposure among US adolescents, further regulation efforts for both off-line and online tobacco marketing are needed to mitigate adolescent exposure to content regarding these products, reducing susceptibility to uptake.

What’s Known on This Subject:

Tobacco marketing exposure impacts adolescents’ receptivity to and curiosity about tobacco products, increasing risk for initiation and long-term use of nicotine. Further research is needed on tobacco product marketing strategies, which rapidly evolve across advertisement venues and types of products.

What This Study Adds:

The prevalence of tobacco marketing exposure during the study period remained elevated (cigarettes lowest prevalence: 77.0%; e-cigarettes lowest prevalence: 55.3%), led by in-store and Internet venues. Increased advertisement venue regulations may reduce adolescent exposure and risk of tobacco use.

Between 2017 and 2019 in the United States, past-30-day use of nicotine increased from 20% to 31% among high school students and from 6% to 11% among middle school students.15  Use of tobacco, specifically the use of electronic cigarettes (e-cigarettes), has become a public health epidemic,6  with 20% of high school and 5% of middle school students in the United States reporting current use of e-cigarettes in 2020.3,4,7  These trends are concerning because past research has demonstrated nearly all adults who smoke daily report use of their first cigarette by 18 years of age.8  Given the risk of long-term addiction, as well as the potential development of chronic health conditions (eg, cancer, lung disease, heart disease, and diabetes),9  identifying risk factors for use of nicotine among adolescents is critical for prevention.

Advertisements impact adolescents’ receptivity to and curiosity about tobacco products as well as increase risk for initiation and potential long-term use of nicotine.1012  In particular, exposure to online tobacco advertisements has been associated with increased risk for tobacco initiation and continued use, and individuals who view this content have a lower incidence of tobacco cessation than those who do not view this content.13  Traditional tobacco (ie, cigarette) and e-cigarette companies have increasingly and simultaneously shifted to marketing campaigns online, and this is concerning because there is evidence that such online marketing campaigns highlight characteristics that appeal to young people.14,15  For instance, the aesthetics of e-cigarettes, including their slim, easily concealable characteristics that appear similar to USB drives or other household products, as well as the availability of flavored e-cigarette products before 2019 regulations could likely contribute to the popularity of these products among youth.16 

Longitudinal investigations on adolescent tobacco advertisement exposure have primarily been focused on verifying and confirming susceptibility and risk for initiation of these products, with fewer studies investigating e-cigarettes specifically.17,18  Further research is needed to determine where adolescents are exposed to these advertisements, which subpopulations are most at risk for exposure, and how these factors have shifted over time. Determining settings where youth are disproportionately exposed to such advertisements and identifying subpopulations with greater vulnerability to these advertisements may allow for prevention and early intervention efforts targeted at those with the highest susceptibility for associated harms. Toward this aim, in the current study, we use nationwide data from the National Youth Tobacco Survey (NYTS) to determine the extent to which adolescents were exposed to cigarette (and other tobacco products) and e-cigarette advertisements across various platforms over multiple years, both online and off-line. Use of the NYTS data set allows for a comprehensive analysis of traditional tobacco (ie, cigarettes) and e-cigarette marketing trends from 2012 to 2020 to expand on existing studies,1,1921  developing an improved understanding of how tobacco advertisement exposure relates to tobacco use behaviors among adolescents. The current study is especially timely because we use data collected before the relatively widespread media coverage on vaping-related illnesses starting in summer 2019,22,23  allowing for the analyses of e-cigarette use risk factors independent of these potential confounders.

In the current study, we use data from the NYTS, which provides nationally representative data using a stratified 3-stage cluster sample design.24  Detailed information about the methodology of sampling and stratification can be found in previous research.18,25,26  The aim of the NYTS data set is to provide more comprehensive information on tobacco-related topics for both middle school (grades 6–8) and high school (grades 9–12) students in the United States compared with other existing surveys (eg, Youth Risk Behavior Surveillance System). The first NYTS study was conducted in 1999, and the study has been running annually since 2011. All information was collected via paper and pencil questionnaire until 2019, when the study team transitioned to an electronic data collection approach.

In the current study, 4 venues of exposure to tobacco advertisements among adolescents were assessed, including on the Internet, in press (newspapers and magazines), on screen (television [TV], movies, and streaming services [newly added to the survey in 2019]), and in retail stores (convenience stores, supermarkets, and gas stations).

Exposure to advertisements for both cigarettes and other tobacco products (referred to as cigarettes hereinafter; collected from 2012 to 2020; not available in 2016) and e-cigarettes (collected from 2014 to 2020) via different venues was examined, collectively and separately. Comparisons of the comprehensive wording from questionnaire items querying participant self-reported exposure to cigarette and e-cigarette advertisements are shown in Supplemental Table 4.

During each questionnaire year for both cigarettes and e-cigarettes, in separate portions of the questionnaire, participants were asked, “How often do you see advertisements or promotions for cigarettes or other tobacco products/e-cigarettes?” Venues of exposure were assessed and included the following: “using the Internet,” “reading newspapers or magazines,” “watching TV or streaming service or going to the movies,” and “going to a convenience store, supermarket, or gas station.” Respondents were asked to report their exposure to cigarette or e-cigarette advertisements for each of these items using the following: “I don’t use/visit [this venue],” “never,” “rarely,” “sometimes,” “most of the time,” and “always.” To be consistent with previous research,1,2  participants who answered “sometimes,” “most of the time,” and “always” for any venue were categorized as exposed to this type of tobacco advertising (ie, cigarettes or e-cigarettes). Participants who answered “I don’t use/visit [this venue],” “never,” and “rarely” were classified as not exposed. To assess general exposure level to tobacco product advertisements, participants who were classified as not exposed across all venues were considered not exposed overall. All other participants whose responses classified them as exposed to at least 1 venue were grouped as exposed overall. Our classification of exposure is consistent with that in previous studies.27 

Participant self-reported sociodemographic characteristics for this study included age range (≤12, 13–14, 15–16, and ≥17 years old), sex, and race and ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, Asian American, and other/multiple). We also included other factors that have been associated with tobacco advertisement exposure among youth, including tobacco use status and parental influence (ie, parental smoking status).18,28,29 

Tobacco use history (never versus ever) and whether participants currently lived with a tobacco user (yes versus no) were also included in sociodemographic covariates. Tobacco use history was assessed by participant self-reported use of tobacco products, including any cigarettes, cigars (including cigars, cigarillos, and little cigars, “even one or two puffs”), chewing tobacco (including snuff and dip, “even just a small amount”), e-cigarettes, and hookahs (or water pipes).

Descriptive statistics on participant characteristics were examined by exposure to any tobacco advertisement in the most recent survey year (2020, n = 14 362). To assess the yearly average percentage change in prevalence of tobacco advertising exposures, weighted linear regressions were conducted to obtain estimates on crude prevalence and 95% confidence intervals (CIs) for cigarettes and e-cigarettes separately.

Weighted logistic regressions were conducted to assess the change over time in exposure to cigarette advertising (2012–2020, sample size ranging from 100 157 to 139 376) and e-cigarette advertising (2014–2020, sample size ranging from 118 338 to 118 613), accounting for sociodemographic covariates. P for trend was estimated by using the survey year or age as a continuous variable.

Only complete cases (no missing data across all variables in each model) were included in the analyses. All analyses were performed by using SAS version 9.4 (SAS Institute, Inc, Cary, NC), with SURVEY procedures used to account for the complex survey design and to generate nationally representative estimates. All the statistical analyses were 2-sided, and P values <.05 were considered statistically significant.

A total of 139 795 US middle and high school students aged 11 to 19 years old (weighted population = 213 436 174) were included in the analysis (from 2012 to 2020). The unweighted sample size per cycle ranged from 14 362 to 24 362 adolescents. Unweighted frequencies and weighted percentages of sociodemographic characteristics in the 2020 survey year are presented in Table 1.

TABLE 1

Sample Size for Tobacco Advertising Exposure in the US Youth Population by Sociodemographic Characteristics, NYTS 2020

All (Weighted %)No. Participants by Tobaccoa Advertising Exposure (Weighted %)
NoYes
Overall 14 362 (100) 2385 (100) 11 977 (100) 
Age range, y    
 ≤12 3465 (21.7) 782 (27.9) 2683 (20.5) 
 13–14 4398 (29.1) 692 (29.2) 3706 (29.1) 
 15–16 3750 (28.8) 511 (24.3) 3239 (29.7) 
 ≥17 2721 (20.4) 390 (18.5) 2331 (20.8) 
Sex    
 Female 7281 (49.5) 1035 (41.7) 6246 (51.1) 
 Male 7045 (50.5) 1342 (58.3) 5703 (48.9) 
Race and ethnicity    
 Non-Hispanic White 6468 (48.8) 842 (40.1) 5626 (50.5) 
 Non-Hispanic Black 1512 (11.6) 247 (12.0) 1265 (11.6) 
 Hispanic 4272 (26.4) 753 (30.3) 3519 (25.6) 
 Asian American 820 (5.5) 274 (10.6) 546 (4.6) 
 Other or multiple races 935 (7.7) 153 (7.2) 782 (7.8) 
Ever used tobaccob    
 No 9807 (66.9) 1807 (73.6) 8000 (65.6) 
 Yes 4555 (33.1) 578 (26.4) 3977 (34.4) 
Lived with a tobacco userc    
 None 9083 (64.9) 1733 (75.7) 7350 (62.8) 
 At least 1 smoker 4947 (35.1) 552 (24.3) 4395 (37.2) 
All (Weighted %)No. Participants by Tobaccoa Advertising Exposure (Weighted %)
NoYes
Overall 14 362 (100) 2385 (100) 11 977 (100) 
Age range, y    
 ≤12 3465 (21.7) 782 (27.9) 2683 (20.5) 
 13–14 4398 (29.1) 692 (29.2) 3706 (29.1) 
 15–16 3750 (28.8) 511 (24.3) 3239 (29.7) 
 ≥17 2721 (20.4) 390 (18.5) 2331 (20.8) 
Sex    
 Female 7281 (49.5) 1035 (41.7) 6246 (51.1) 
 Male 7045 (50.5) 1342 (58.3) 5703 (48.9) 
Race and ethnicity    
 Non-Hispanic White 6468 (48.8) 842 (40.1) 5626 (50.5) 
 Non-Hispanic Black 1512 (11.6) 247 (12.0) 1265 (11.6) 
 Hispanic 4272 (26.4) 753 (30.3) 3519 (25.6) 
 Asian American 820 (5.5) 274 (10.6) 546 (4.6) 
 Other or multiple races 935 (7.7) 153 (7.2) 782 (7.8) 
Ever used tobaccob    
 No 9807 (66.9) 1807 (73.6) 8000 (65.6) 
 Yes 4555 (33.1) 578 (26.4) 3977 (34.4) 
Lived with a tobacco userc    
 None 9083 (64.9) 1733 (75.7) 7350 (62.8) 
 At least 1 smoker 4947 (35.1) 552 (24.3) 4395 (37.2) 

The sample size was weighted to be nationally represented. Weighted percentages may not sum to 100% because of rounding.

a

Participant characteristics were presented according to tobacco advertising exposure, including cigarettes and e-cigarettes.

b

Tobacco history assessment includes cigarettes, e-cigarettes, cigars (cigars, little cigars, and cigarillos), smokeless tobacco (chewing tobacco, snuff, dip, snus, and dissolvable tobacco), hookahs, pipe tobacco, and bidis (small brown cigarettes wrapped in a leaf).

c

The assessment includes cigarettes, e-cigarettes, cigars (cigars, little cigars, and cigarillos), smokeless tobacco (chewing tobacco, snuff, dip, snus, and dissolvable tobacco), hookahs, pipe tobacco, and bidis (small brown cigarettes wrapped in a leaf).

In the 2020 cycle, a large proportion of the participants reported being exposed to cigarette advertisements (11 977 of 14 362; 83.4%). The estimated prevalence of exposure to any cigarette advertisement was 78.9% (Table 2, Fig 1). Specifically, the estimated prevalence of exposure to cigarette advertisements in retail stores, on the Internet, on a screen-based device (on screen), and in press were 69.3% (95% CI, 67.3% to 70.8%), 40.8% (95% CI, 39.3% to 42.4%), 23.3% (95% CI, 21.8% to 24.7%), and 16.7% (95% CI, 15.6% to 17.9%), respectively.

FIGURE 1

Crude weighted trends in tobacco advertising exposure by cigarettes (and other tobacco products) and e-cigarettes, NYTS 2012–2020. Data were weighted to be nationally representative. Error bars indicated 95% CIs. Being exposed to seeing advertisements was defined as responding “sometimes,” “most of the time,” or “always” to each specific venue.

FIGURE 1

Crude weighted trends in tobacco advertising exposure by cigarettes (and other tobacco products) and e-cigarettes, NYTS 2012–2020. Data were weighted to be nationally representative. Error bars indicated 95% CIs. Being exposed to seeing advertisements was defined as responding “sometimes,” “most of the time,” or “always” to each specific venue.

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TABLE 2.

Crude Weighted Trends in Tobacco Advertising Exposed by venue, NYTS 2012 – 2020a

2012201320142015201620172018201920201st available year - 20162017 - 20202020 vs 1st Cycle Difference (95% CI)e
β (95% CI)dP for trenddβ (95% CI)dP for trendd
Cigarette (and other tobacco productsb), Weighted % (95% CI)c 
Any venues 
 82.8 86.4 91.1 89.4 NA 77.9 77.0 81.1 78.9 2.8* <.001* 0.7* 0.03* -3.9* 
 (81.7, 83.8) (85.1, 87.8) (90.4, 91.8) (88.3, 90.5)  (76.5, 79.2) (75.8, 78.3) (80.1, 82.1) (77.6, 80.2) (2.3, 3.3)*  (0.1, 1.3)*  (-5.7, -2.1)* 
Retail stores 
 76.2 76.7 80.6 76.5 NA 65.5 64.1 71.0 69.3 0.5 0.13 1.8* <.001* -6.9* 
 (74.9, 77.5) (75.1, 78.3) (79.5, 81.8) (75.0, 77.9)  (63.9, 67.2) (62.6, 65.6) (69.5, 72.5) (67.3, 70.8) (-0.2, 1.1)  (1.0, 2.6)*  (-9.1, -4.7)* 
Internet 
 43.0 43.5 46.8 48.6 NA 39.8 40.8 42.1 40.8 2.0* <.001* 0.4 0.23 -2.2* 
 (41.8, 44.2) (42.3, 44.6) (45.6, 48.1) (47.1, 50.2)  (38.4, 41.2) (39.3, 42.4) (40.6, 43.6) (39.3, 42.4) (1.4, 2.6)*  (-0.3, 1.1)  (-4.2, -0.1)* 
Screen 
 NA NA 69.0 67.0 NA 33.5 32.9 25.7 23.3 NA NA -3.8* <.001* -45.8* 
   (67.9, 70.1) (65.6, 68.5)  (31.6, 35.4) (31.6, 34.3) (24.1, 27.4) (21.8, 24.7)   (-4.6, -3.0)*  (-47.6, -43.9)* 
Press 
 36.9 36.3 34.3 34.1 NA 20.3 18.7 20.5 16.7 -1.0* <.001* -0.9* 0.002* -20.2* 
 (35.8, 38.1) (35.0, 37.6) (33.2, 35.5) (32.9, 35.3)  (19.1, 21.5) (17.8, 19.5) (19.3, 21.7) (15.6, 17.9) (-1.6, -0.5)*  (-1.4, -0.3)*  (-21.9, -18.5)* 
E-cigarette, Weighted % (95% CI)c 
Any venues 
 NA NA 68.9 73.0 78.2 55.3 55.7 68.6 68.0 4.6* <.001* 5.1* <.001* -0.8 
   (67.7, 70.0) (71.3, 74.6) (77.1, 79.2) (54.0, 56.6) (54.5, 56.9) (67.1, 70.1) (66.3, 69.8) (3.8, 5.5)*  (4.4, 5.8)*  (-3.0, 1.4) 
Retail stores 
 NA NA 54.8 59.9 68.0 43.6 43.3 57.0 59.2 6.6* <.001* 6.0* <.001* 4.5* 
   (53.6, 56.0) (58.2, 61.6) (66.9, 69.1) (42.3, 45.0) (42.0, 44.6) (55.1, 58.8) (57.3, 61.2) (5.7, 7.6)*  (5.2, 6.9)*  (2.0, 6.9)* 
Internet 
 NA NA 39.8 42.6 40.6 27.9 30.8 43.5 40.6 0.4 0.37 5.0* <.001* -0.8 
   (38.5, 41.1) (40.8, 44.4) (39.4, 41.8) (26.8, 29.1) (29.8, 31.8) (42.3, 44.6) (39.0, 42.2) (-0.5, 1.3)  (4.4, 5.7)*  (-1.3, 2.9) 
Screen 
 NA NA 36.5 44.5 37.7 27.4 26.0 25.1 23.0 0.6 0.35 -1.4* <.001* -13.5* 
   (35.3, 37.7) (42.7, 46.2) (36.0, 39.3) (26.2, 28.6) (24.8, 27.3) (23.9, 26.4) (21.6, 24.4) (-0.7, 1.8)  (-2.0, -0.8)*  (-15.5, -11.6)* 
Press 
 NA NA 30.4 31.0 23.9 17.0 16.4 19.2 16.7 -3.3* <.001* 0.2 0.74 -13.7* 
   (29.3, 31.5) (29.9, 32.1) (22.9, 24.9) (15.9, 18.1) (15.5, 17.3) (18.3, 20.1) (15.5, 17.9) (-4.0, -2.5)*  (-0.3, 0.7)  (-15.5, -12.0)* 
2012201320142015201620172018201920201st available year - 20162017 - 20202020 vs 1st Cycle Difference (95% CI)e
β (95% CI)dP for trenddβ (95% CI)dP for trendd
Cigarette (and other tobacco productsb), Weighted % (95% CI)c 
Any venues 
 82.8 86.4 91.1 89.4 NA 77.9 77.0 81.1 78.9 2.8* <.001* 0.7* 0.03* -3.9* 
 (81.7, 83.8) (85.1, 87.8) (90.4, 91.8) (88.3, 90.5)  (76.5, 79.2) (75.8, 78.3) (80.1, 82.1) (77.6, 80.2) (2.3, 3.3)*  (0.1, 1.3)*  (-5.7, -2.1)* 
Retail stores 
 76.2 76.7 80.6 76.5 NA 65.5 64.1 71.0 69.3 0.5 0.13 1.8* <.001* -6.9* 
 (74.9, 77.5) (75.1, 78.3) (79.5, 81.8) (75.0, 77.9)  (63.9, 67.2) (62.6, 65.6) (69.5, 72.5) (67.3, 70.8) (-0.2, 1.1)  (1.0, 2.6)*  (-9.1, -4.7)* 
Internet 
 43.0 43.5 46.8 48.6 NA 39.8 40.8 42.1 40.8 2.0* <.001* 0.4 0.23 -2.2* 
 (41.8, 44.2) (42.3, 44.6) (45.6, 48.1) (47.1, 50.2)  (38.4, 41.2) (39.3, 42.4) (40.6, 43.6) (39.3, 42.4) (1.4, 2.6)*  (-0.3, 1.1)  (-4.2, -0.1)* 
Screen 
 NA NA 69.0 67.0 NA 33.5 32.9 25.7 23.3 NA NA -3.8* <.001* -45.8* 
   (67.9, 70.1) (65.6, 68.5)  (31.6, 35.4) (31.6, 34.3) (24.1, 27.4) (21.8, 24.7)   (-4.6, -3.0)*  (-47.6, -43.9)* 
Press 
 36.9 36.3 34.3 34.1 NA 20.3 18.7 20.5 16.7 -1.0* <.001* -0.9* 0.002* -20.2* 
 (35.8, 38.1) (35.0, 37.6) (33.2, 35.5) (32.9, 35.3)  (19.1, 21.5) (17.8, 19.5) (19.3, 21.7) (15.6, 17.9) (-1.6, -0.5)*  (-1.4, -0.3)*  (-21.9, -18.5)* 
E-cigarette, Weighted % (95% CI)c 
Any venues 
 NA NA 68.9 73.0 78.2 55.3 55.7 68.6 68.0 4.6* <.001* 5.1* <.001* -0.8 
   (67.7, 70.0) (71.3, 74.6) (77.1, 79.2) (54.0, 56.6) (54.5, 56.9) (67.1, 70.1) (66.3, 69.8) (3.8, 5.5)*  (4.4, 5.8)*  (-3.0, 1.4) 
Retail stores 
 NA NA 54.8 59.9 68.0 43.6 43.3 57.0 59.2 6.6* <.001* 6.0* <.001* 4.5* 
   (53.6, 56.0) (58.2, 61.6) (66.9, 69.1) (42.3, 45.0) (42.0, 44.6) (55.1, 58.8) (57.3, 61.2) (5.7, 7.6)*  (5.2, 6.9)*  (2.0, 6.9)* 
Internet 
 NA NA 39.8 42.6 40.6 27.9 30.8 43.5 40.6 0.4 0.37 5.0* <.001* -0.8 
   (38.5, 41.1) (40.8, 44.4) (39.4, 41.8) (26.8, 29.1) (29.8, 31.8) (42.3, 44.6) (39.0, 42.2) (-0.5, 1.3)  (4.4, 5.7)*  (-1.3, 2.9) 
Screen 
 NA NA 36.5 44.5 37.7 27.4 26.0 25.1 23.0 0.6 0.35 -1.4* <.001* -13.5* 
   (35.3, 37.7) (42.7, 46.2) (36.0, 39.3) (26.2, 28.6) (24.8, 27.3) (23.9, 26.4) (21.6, 24.4) (-0.7, 1.8)  (-2.0, -0.8)*  (-15.5, -11.6)* 
Press 
 NA NA 30.4 31.0 23.9 17.0 16.4 19.2 16.7 -3.3* <.001* 0.2 0.74 -13.7* 
   (29.3, 31.5) (29.9, 32.1) (22.9, 24.9) (15.9, 18.1) (15.5, 17.3) (18.3, 20.1) (15.5, 17.9) (-4.0, -2.5)*  (-0.3, 0.7)  (-15.5, -12.0)* 

NYTS, the National Youth Tobacco Survey; NA, Not Available; CI, Confidence Interval.

a

Sample size for each cell (unweighted N) ranged from 14 531 to 24 362.

b

The assessment of other tobacco products includes: cigars (cigars, little cigars, and cigarillos), smokeless tobacco (chewing tobacco, snuff, dip, snus, and dissolvable tobacco), hookahs, pipe tobacco, and bidis (small brown cigarettes wrapped in a leaf).

c

Weighted % and 95% CI were calculated on each survey cycle. All estimates were weighted to be national reprehensive.

d

The β, 95 CI, and P for trend were estimated by using unadjusted linear regression that included the National Youth Tobacco Study survey year as a continuous variable. The estimate (β) can be interpreted as the average percentage point change in prevalence annually.

e

A decrease corresponds to difference below zero. An increase corresponds to difference above zero.

*

Estimates indicate statistically significant.

From 2012 to 2015, increasing trends in exposure to cigarette advertisements from any venue, the Internet, and the press were observed (all P for trend < .001; Table 2). Exposure from retail stores was an exception, staying high and stable during the same period (P = .13). The relevant data from 2016 were not available, and substantial drops were observed from 2015 to 2017 across all venues. From 2017 to 2020, estimated prevalence of exposure to cigarette advertisements from any venue and retail stores increased (any venue: β2017–2020 = .7; retail store: β2017–2020 = 1.8; all P for trend ≤ .03). In contrast, screen- and press-based exposure decreased (on screen: β2017–2020 = −3.8; in press: β2017–2020 = −.9; all P for trend ≤ .002). Overall, a reduction in prevalence of cigarette advertisement exposure from any venue was observed from 2012 to 2020 (difference, −3.9% [95% CI, −5.7% to −2.1%]). Of note, prevalence of exposure to screen-based cigarette advertisements declined significantly from 69% (95% CI, 67.9% to 70.1%) in 2014 to 23.3% (95% CI, 21.8% to 24.7%) in 2020 (difference, −45.8% [95% CI, −47.6% to −43.9]), as did prevalence of exposure to cigarette advertisements in press (difference, −20.2% [95% CI, −21.9% to −18.5%]).

After adjusting for sociodemographic covariates, significantly higher odds of being exposed to any cigarette advertisement were consistently observed among older adolescents, female youth, and those who ever used tobacco and lived with a tobacco user (Table 3, Fig 2). In addition, apparent racial disparities in exposure to cigarette advertisements were observed. From any venue, racial and ethnic minority individuals, including those of non-Hispanic Black (adjusted odds ratio [aOR], 0.79 [95% CI, 0.73 to 0.84]), Hispanic (aOR, 0.76 [95% CI, 0.72 to 0.80]), Asian American (aOR, 0.55 [95% CI, 0.50 to 0.61]), and other or multiple races and ethnicities (aOR, 0.91 [95% CI, 0.84 to 0.99]), were less likely to be exposed to cigarette advertisements from 2012 to 2020 (Table 3, Fig 2) compared with non-Hispanic White individuals. African American adolescents were more likely to report being exposed to cigarette screen-based (aOR, 1.34 [95% CI, 1.24 to 1.44]), Internet (aOR, 1.18 [95% CI, 1.12 to 1.24]), and press (aOR, 1.05 [95% CI, 1.00 to 1.12]) advertisements compared with non-Hispanic White adolescents.

FIGURE 2

Crude weighted trends in cigarette advertising exposure by race and ethnicity, sex, and tobacco use history, NYTS 2012–2020. Data were weighted to be nationally representative. Error bars indicated 95% CIs. Being exposed to seeing advertisements was defined as responding “sometimes,” “most of the time,” or “always” to each specific venue. A, Race and ethnicity. B, Sex. C, Tobacco use history.

FIGURE 2

Crude weighted trends in cigarette advertising exposure by race and ethnicity, sex, and tobacco use history, NYTS 2012–2020. Data were weighted to be nationally representative. Error bars indicated 95% CIs. Being exposed to seeing advertisements was defined as responding “sometimes,” “most of the time,” or “always” to each specific venue. A, Race and ethnicity. B, Sex. C, Tobacco use history.

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TABLE 3.

Weighted logistic regressions models of tobacco advertising exposure, adjusted for sociodemographic characteristics, NYTS 2012 – 2020a

Adjusted Odds Ratio (95% CI)b
Cigarette (& other tobacco productsa)E-cigarettes
Any venuesRetail storesInternetScreenPressAny venuesRetail storesInternetScreenPress
Unweighted number of cases(N = 139 795)(N = 139 004)(N = 139 376)(N = 100 157)(N = 139 044)(N = 119 289)(N = 118 338)(N = 118 613)(N = 118 514)(N = 118 369)
Age (y) 
≤ 12 1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
13 - 14 1.31
(1.24-1.39)* 
1.30
(1.24-1.37)* 
1.13
(1.08-1.18)* 
1.18
(1.12-1.24)* 
1.24
(1.17-1.30)* 
1.20
(1.15-1.26)* 
1.19
(1.14-1.25)* 
1.24
(1.18-1.30)* 
1.17
(1.11-1.23)* 
1.26
(1.18-1.34)* 
15 - 16 1.39
(1.30-1.48)* 
1.42
(1.34-1.50)* 
1.07
(1.02-1.12)* 
1.23
(1.16-1.31)* 
1.43
(1.36-1.51)* 
1.32
(1.25-1.40)* 
1.28
(1.21-1.35)* 
1.33
(1.26-1.40)* 
1.24
(1.18-1.31)* 
1.54
(1.45-1.64)* 
≥ 17 1.31
(1.22-1.40)* 
1.42
(1.34-1.51)* 
0.93
(0.88-0.97)* 
1.19
(1.12-1.27)* 
1.53
(1.45-1.62)* 
1.23
(1.16-1.30)* 
1.25
(1.18-1.33)* 
1.28
(1.21-1.34)* 
1.20
(1.14-1.27)* 
1.70
(1.60-1.80)* 
P for trendc <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 
Sex 
Female 1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
Male 0.72
(0.69-0.75)* 
0.78
(0.76-0.81)* 
0.71
(0.69-0.73)* 
0.75
(0.72-0.78)* 
0.82
(0.79-0.85)* 
0.87
(0.84-0.90)* 
0.87
(0.85-0.90)* 
0.79
(0.76-0.82)* 
0.85
(0.82-0.88)* 
0.82
(0.79-0.86)* 
Race 
White 1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
Black 0.79
(0.73-0.84)* 
0.63
(0.60-0.67)* 
1.18
(1.12-1.24)* 
1.34
(1.24-1.44)* 
1.05
(1.00-1.12)* 
0.88
(0.83-0.93)* 
0.71
(0.68-0.76)* 
0.97
(0.92-1.02) 
1.32
(1.26-1.40)* 
1.02
(0.96-1.09) 
Hispanic 0.76
(0.72-0.80)* 
0.67
(0.64-0.70)* 
1.04
(1.00-1.07)* 
1.09
(1.04-1.15)* 
0.96
(0.92-1.01) 
0.86
(0.82-0.89)* 
0.78
(0.75-0.81)* 
0.96
(0.93-1.00) 
1.09
(1.05-1.14)* 
0.97
(0.93-1.02) 
Asian 0.55
(0.50-0.61)* 
0.50
(0.46-0.54)* 
0.82
(0.75-0.89)* 
0.76
(0.69-0.84)* 
0.81
(0.75-0.88)* 
0.60
(0.55-0.65)* 
0.56
(0.51-0.60)* 
0.73
(0.67-0.80)* 
0.64
(0.59-0.70)* 
0.73
(0.67-0.80)* 
Otherd 0.91
(0.84-0.99)* 
0.85
(0.79-0.91)* 
1.07
(1.01-1.14)* 
1.04
(0.97-1.12) 
1.04
(0.98-1.11) 
0.95
(0.89-1.01) 
0.90
(0.84-0.96)* 
1.04
(0.98-1.11) 
1.04
(0.97-1.11) 
0.98
(0.91-1.06) 
Ever used tobaccoe 
No 1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
Yes 1.14
(1.09-1.19)* 
1.07
(1.03-1.11)* 
1.13
(1.09-1.16)* 
1.07
(1.02-1.11)* 
1.15
(1.11-1.19)* 
1.37
(1.32-1.42)* 
1.30
(1.26-1.35)* 
1.36
(1.31-1.41)* 
1.20
(1.16-1.25)* 
1.30
(1.25-1.35)* 
Lives with a tobacco userf 
None 1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
Yes 1.49
(1.43-1.56)* 
1.31
(1.26-1.36)* 
1.31
(1.27-1.34)* 
1.27
(1.22-1.32)* 
1.16
(1.12-1.20)* 
1.34
(1.29-1.39)* 
1.24
(1.20-1.28)* 
1.29
(1.24-1.33)* 
1.27
(1.23-1.32)* 
1.17
(1.13-1.21)* 
Questionnaire year 
2012 1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
NA 1.00
(Ref) 
NA NA NA NA NA 
2013 1.07
(0.96-1.19) 
1.06
(0.95-1.17) 
1.02
(0.95-1.09) 
NA 0.98
(0.90-1.06) 
NA NA NA NA NA 
2014 2.25
(2.01-2.51)* 
1.32
(1.21-1.45)* 
1.15
(1.07-1.24)* 
1.00
(Reference) 
0.89
(0.83-0.95)* 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
2015 1.85
(1.65-2.08)* 
1.03
(0.94-1.13) 
1.25
(1.16-1.35)* 
0.92
(0.84-0.99)* 
0.88
(0.82-0.94)* 
1.24
(1.13-1.35)* 
1.25
(1.15-1.36)* 
1.14
(1.05-1.23)* 
1.43
(1.31-1.55)* 
1.03
(0.96-1.10) 
2016 NA NA NA NA NA 1.69
(1.56-1.83)* 
1.84
(1.71-1.97)* 
1.06
(0.99-1.14) 
1.07
(0.98-1.17) 
0.72
(0.68-0.78)* 
2017 0.74
(0.66-0.82)* 
0.60
(0.55-0.66)* 
0.88
(0.82-0.95)* 
0.22
(0.20-0.24)* 
0.43
(0.40-0.47)* 
0.57
(0.53-0.62)* 
0.65
(0.61-0.70)* 
0.60
(0.56-0.65)* 
0.68
(0.63-0.73)* 
0.48
(0.44-0.52)* 
2018 0.70
(0.63-0.77)* 
0.56
(0.51-0.60)* 
0.92
(0.85-0.99)* 
0.21
(0.20-0.23)* 
0.39
(0.36-0.42)* 
0.57
(0.53-0.61)* 
0.63
(0.59-0.68)* 
0.68
(0.64-0.73)* 
0.63
(0.58-0.68)* 
0.44
(0.41-0.48)* 
2019 0.88
(0.80-0.97)* 
0.76
(0.69-0.83)* 
0.95
(0.88-1.03) 
0.15
(0.13-0.16)* 
0.43
(0.39-0.47)* 
0.99
(0.91-1.07) 
1.09
(1.00-1.18)* 
1.17
(1.10-1.25)* 
0.59
(0.54-0.64)* 
0.53
(0.49-0.57)* 
2020 0.80
(0.73-0.89)* 
0.73
(0.67-0.80)* 
0.92
(0.85-0.99)* 
0.13
(0.12-0.14)* 
0.34
(0.31-0.38)* 
1.01
(0.93-1.10) 
1.26
(1.15-1.38)* 
1.08
(1.00-1.17)* 
0.54
(0.49-0.59)* 
0.47
(0.42-0.52)* 
P for trendg <.001* <.001* <.001* <.001* <.001* <.001* .01* .69 <.001* <.001* 
Adjusted Odds Ratio (95% CI)b
Cigarette (& other tobacco productsa)E-cigarettes
Any venuesRetail storesInternetScreenPressAny venuesRetail storesInternetScreenPress
Unweighted number of cases(N = 139 795)(N = 139 004)(N = 139 376)(N = 100 157)(N = 139 044)(N = 119 289)(N = 118 338)(N = 118 613)(N = 118 514)(N = 118 369)
Age (y) 
≤ 12 1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
13 - 14 1.31
(1.24-1.39)* 
1.30
(1.24-1.37)* 
1.13
(1.08-1.18)* 
1.18
(1.12-1.24)* 
1.24
(1.17-1.30)* 
1.20
(1.15-1.26)* 
1.19
(1.14-1.25)* 
1.24
(1.18-1.30)* 
1.17
(1.11-1.23)* 
1.26
(1.18-1.34)* 
15 - 16 1.39
(1.30-1.48)* 
1.42
(1.34-1.50)* 
1.07
(1.02-1.12)* 
1.23
(1.16-1.31)* 
1.43
(1.36-1.51)* 
1.32
(1.25-1.40)* 
1.28
(1.21-1.35)* 
1.33
(1.26-1.40)* 
1.24
(1.18-1.31)* 
1.54
(1.45-1.64)* 
≥ 17 1.31
(1.22-1.40)* 
1.42
(1.34-1.51)* 
0.93
(0.88-0.97)* 
1.19
(1.12-1.27)* 
1.53
(1.45-1.62)* 
1.23
(1.16-1.30)* 
1.25
(1.18-1.33)* 
1.28
(1.21-1.34)* 
1.20
(1.14-1.27)* 
1.70
(1.60-1.80)* 
P for trendc <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 <.001 
Sex 
Female 1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
Male 0.72
(0.69-0.75)* 
0.78
(0.76-0.81)* 
0.71
(0.69-0.73)* 
0.75
(0.72-0.78)* 
0.82
(0.79-0.85)* 
0.87
(0.84-0.90)* 
0.87
(0.85-0.90)* 
0.79
(0.76-0.82)* 
0.85
(0.82-0.88)* 
0.82
(0.79-0.86)* 
Race 
White 1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
Black 0.79
(0.73-0.84)* 
0.63
(0.60-0.67)* 
1.18
(1.12-1.24)* 
1.34
(1.24-1.44)* 
1.05
(1.00-1.12)* 
0.88
(0.83-0.93)* 
0.71
(0.68-0.76)* 
0.97
(0.92-1.02) 
1.32
(1.26-1.40)* 
1.02
(0.96-1.09) 
Hispanic 0.76
(0.72-0.80)* 
0.67
(0.64-0.70)* 
1.04
(1.00-1.07)* 
1.09
(1.04-1.15)* 
0.96
(0.92-1.01) 
0.86
(0.82-0.89)* 
0.78
(0.75-0.81)* 
0.96
(0.93-1.00) 
1.09
(1.05-1.14)* 
0.97
(0.93-1.02) 
Asian 0.55
(0.50-0.61)* 
0.50
(0.46-0.54)* 
0.82
(0.75-0.89)* 
0.76
(0.69-0.84)* 
0.81
(0.75-0.88)* 
0.60
(0.55-0.65)* 
0.56
(0.51-0.60)* 
0.73
(0.67-0.80)* 
0.64
(0.59-0.70)* 
0.73
(0.67-0.80)* 
Otherd 0.91
(0.84-0.99)* 
0.85
(0.79-0.91)* 
1.07
(1.01-1.14)* 
1.04
(0.97-1.12) 
1.04
(0.98-1.11) 
0.95
(0.89-1.01) 
0.90
(0.84-0.96)* 
1.04
(0.98-1.11) 
1.04
(0.97-1.11) 
0.98
(0.91-1.06) 
Ever used tobaccoe 
No 1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
Yes 1.14
(1.09-1.19)* 
1.07
(1.03-1.11)* 
1.13
(1.09-1.16)* 
1.07
(1.02-1.11)* 
1.15
(1.11-1.19)* 
1.37
(1.32-1.42)* 
1.30
(1.26-1.35)* 
1.36
(1.31-1.41)* 
1.20
(1.16-1.25)* 
1.30
(1.25-1.35)* 
Lives with a tobacco userf 
None 1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
Yes 1.49
(1.43-1.56)* 
1.31
(1.26-1.36)* 
1.31
(1.27-1.34)* 
1.27
(1.22-1.32)* 
1.16
(1.12-1.20)* 
1.34
(1.29-1.39)* 
1.24
(1.20-1.28)* 
1.29
(1.24-1.33)* 
1.27
(1.23-1.32)* 
1.17
(1.13-1.21)* 
Questionnaire year 
2012 1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
NA 1.00
(Ref) 
NA NA NA NA NA 
2013 1.07
(0.96-1.19) 
1.06
(0.95-1.17) 
1.02
(0.95-1.09) 
NA 0.98
(0.90-1.06) 
NA NA NA NA NA 
2014 2.25
(2.01-2.51)* 
1.32
(1.21-1.45)* 
1.15
(1.07-1.24)* 
1.00
(Reference) 
0.89
(0.83-0.95)* 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
1.00
(Reference) 
2015 1.85
(1.65-2.08)* 
1.03
(0.94-1.13) 
1.25
(1.16-1.35)* 
0.92
(0.84-0.99)* 
0.88
(0.82-0.94)* 
1.24
(1.13-1.35)* 
1.25
(1.15-1.36)* 
1.14
(1.05-1.23)* 
1.43
(1.31-1.55)* 
1.03
(0.96-1.10) 
2016 NA NA NA NA NA 1.69
(1.56-1.83)* 
1.84
(1.71-1.97)* 
1.06
(0.99-1.14) 
1.07
(0.98-1.17) 
0.72
(0.68-0.78)* 
2017 0.74
(0.66-0.82)* 
0.60
(0.55-0.66)* 
0.88
(0.82-0.95)* 
0.22
(0.20-0.24)* 
0.43
(0.40-0.47)* 
0.57
(0.53-0.62)* 
0.65
(0.61-0.70)* 
0.60
(0.56-0.65)* 
0.68
(0.63-0.73)* 
0.48
(0.44-0.52)* 
2018 0.70
(0.63-0.77)* 
0.56
(0.51-0.60)* 
0.92
(0.85-0.99)* 
0.21
(0.20-0.23)* 
0.39
(0.36-0.42)* 
0.57
(0.53-0.61)* 
0.63
(0.59-0.68)* 
0.68
(0.64-0.73)* 
0.63
(0.58-0.68)* 
0.44
(0.41-0.48)* 
2019 0.88
(0.80-0.97)* 
0.76
(0.69-0.83)* 
0.95
(0.88-1.03) 
0.15
(0.13-0.16)* 
0.43
(0.39-0.47)* 
0.99
(0.91-1.07) 
1.09
(1.00-1.18)* 
1.17
(1.10-1.25)* 
0.59
(0.54-0.64)* 
0.53
(0.49-0.57)* 
2020 0.80
(0.73-0.89)* 
0.73
(0.67-0.80)* 
0.92
(0.85-0.99)* 
0.13
(0.12-0.14)* 
0.34
(0.31-0.38)* 
1.01
(0.93-1.10) 
1.26
(1.15-1.38)* 
1.08
(1.00-1.17)* 
0.54
(0.49-0.59)* 
0.47
(0.42-0.52)* 
P for trendg <.001* <.001* <.001* <.001* <.001* <.001* .01* .69 <.001* <.001* 

NYTS, the National Youth Tobacco Survey; CI, Confidence Interval; NA, Not Applicable.

a

Participant characteristics were presented by tobacco product (Cigarettes & other tobacco products vs. E-cigarettes) by advertising exposure venue (any venues, Internet, press, screen, and retail stores). Other tobacco products include: cigars (cigars, little cigars, and cigarillos), smokeless tobacco (chewing tobacco, snuff, dip, snus, and dissolvable tobacco), hookahs, pipe tobacco, and bidis (small brown cigarettes wrapped in a leaf). All estimates were weighted to be nationally representative.

b

For categorical variables, the adjusted odds ratios (AORs) represent the change in odds expected in each category compared with the reference group.

c

P for trend of age was calculated using age as a continuous variable.

d

Other/Multiple includes race/ethnicity other than Non-Hispanic White, Non-Hispanic Black, Hispanics, and Asians, including multiracial group.

e

The assessment of tobacco use includes: cigarette, E-cigarette, cigars (cigars, little cigars, and cigarillos), smokeless tobacco (chewing tobacco, snuff, dip, snus, and dissolvable tobacco), hookahs, pipe tobacco, and bidis (small brown cigarettes wrapped in a leaf).

f

The assessment of family members’ tobacco use includes: cigarette, E-cigarette, cigars (cigars, little cigars, and cigarillos), smokeless tobacco (chewing tobacco, snuff, dip, snus, and dissolvable tobacco), hookahs, pipe tobacco, and bidis (small brown cigarettes wrapped in a leaf).

g

P for trend over survey year was calculated using the National Youth Tobacco Study (NYTS) available questionnaire cycle as a continuous variable.

*

Estimates indicate statistically significant.

In 2020, 68.0% (95% CI, 66.3% to 69.8%) of participants reported exposure to any e-cigarette advertisements, which was mainly driven by exposure from retail stores (59.2% [95% CI, 57.3% to 61.2%]) and the Internet (40.6% [95% CI, 39.0% to 42.2%]). From 2014 to 2016, an increasing trend was observed in the prevalence of exposure to e-cigarette advertisements from any venue and retail stores (any venue: β2014–2016 = 4.6; retail stores: β2014–2016 = 6.6; all P for trend < .001). Decreases in reported exposures were observed between 2016 and 2017. From 2017 to 2020, the prevalence of exposure to e-cigarette advertisements significantly increased across all venues (all P for trend < .001), with a notable exception of exposure from the press (β2017–2020 = .2; P for trend = .74). Overall, compared with 2014, there was a lower prevalence of exposure to e-cigarette press- (difference, −13.7% [95% CI, −15.5% to −12.0%]) and screen-based (difference, −13.5% [95% CI, −15.5% to −11.6%]) advertisements, but there was a higher prevalence of exposure to e-cigarette advertisements from retail stores (difference, 4.5% [95% CI, 2.0% to 6.9%]) in 2020 compared with the prevalence in 2014.

Similar to cigarette advertisements, a significantly higher prevalence of exposure to any e-cigarette advertisement was found among participants who were older, female, ever used tobacco, and lived with a tobacco user (Table 3, Fig 3). Similarly, Asian American adolescents were less likely to report exposure to any e-cigarette advertisement (aOR, 0.60 [95% CI, 0.55 to 0.65]) compared with non-Hispanic White adolescents across all cycles (Table 3, Fig 3). Additionally, results suggested that African American (aOR, 1.32 [95% CI, 1.26 to 1.40]) and Hispanic (aOR, 1.09 [95% CI, 1.05 to 1.14]) adolescents were more likely to report being exposed to screen-based e-cigarette advertisements compared with non-Hispanic White adolescents.

FIGURE 3

Crude weighted trends in e-cigarette advertising exposure by race and ethnicity, sex, and tobacco use history, NYTS 2014–2020. Data were weighted to be nationally representative. Error bars indicated 95% CIs. Being exposed to seeing advertisements was defined as responding “sometimes,” “most of the time,” or “always” to each specific venue. A, Race and ethnicity. B, Sex. C, Tobacco use history.

FIGURE 3

Crude weighted trends in e-cigarette advertising exposure by race and ethnicity, sex, and tobacco use history, NYTS 2014–2020. Data were weighted to be nationally representative. Error bars indicated 95% CIs. Being exposed to seeing advertisements was defined as responding “sometimes,” “most of the time,” or “always” to each specific venue. A, Race and ethnicity. B, Sex. C, Tobacco use history.

Close modal

The purpose of the current study was to explore the trends in tobacco advertisement exposures from 2012 to 2020 among adolescents in the NYTS study. Primary findings indicate a high prevalence of exposure to cigarette advertisements (78.9% in 2020) and e-cigarette advertisements (68.0% in 2020) across all marketing venues. Additionally, the prevalence of cigarette advertisements (ranging from 77.0% [2018] to 91.1% [2014]) remained higher across all survey years compared with the prevalence e-cigarette advertisements (ranging from 55.3% [2017] to 78.2% [2016]). In addition, demographic differences, such as age, sex, or living situation, were associated with exposure to tobacco advertisements from both online and off-line venues, which could lead to disparities in tobacco-related negative consequences across certain vulnerable groups.

Findings reveal that exposure to cigarette and e-cigarette advertisements across all marketing venues increased from the first year analyzed (cigarettes, 2012; e-cigarettes, 2014) to 2016, decreased from 2016 to 2017, and increased again in 2017 before slightly dropping most recently in 2020. Overall, cigarette and e-cigarette advertisement exposure from any venue has ultimately decreased from 2012 and 2014 to 2020, with decreases in exposure to screen and press advertisements driving this trend. The drop in e-cigarette advertisement exposure from 2016 to 2017 is of particular importance because the US Food and Drug Administration released a ruling extending its authority to e-cigarettes in May 2016, including these products within the umbrella of tobacco product advertisement and sale regulations.30  This ruling and the additional requirements and restrictions placed on e-cigarette companies during this year (eg, reworking marketing strategies to meet US Food and Drug Administration requirements, registering products as tobacco products, listing ingredients, placing a health warning on packaging) could have contributed to this drop in advertisement exposure.31  Before May 2016, there were no restrictions surrounding the sale of e-cigarettes to minors, and requiring age verification and denying the distribution of free samples may have also reduced exposure to and interest in these products among youth from 2016 to 2017.31 

Our current results reveal that the prevalence of adolescent e-cigarette advertisement exposure was lower than the prevalence of regular cigarette advertisement exposure across all venues, except for on Internet-based platforms in 2019 (43.5% for e-cigarettes versus 42.1% for cigarettes). One possible explanation for this higher prevalence of exposure to e-cigarette advertisements on online venues may be the use of social media and the way youth interact with content on these platforms.32  User-generated posts on social media often portray e-cigarette use in a positive light, and social media platforms filter advertisements and recommend posts on the basis of content that users view and like.33  Thus, an initial interaction (eg, viewing or liking) with an e-cigarette advertisement and content on social media may trigger the social media platform to increase the frequency of the adolescent’s exposure to these advertisements, providing increased reinforcement and social norms surrounding e-cigarette use. For example, even passively interacting with posts (ie, viewing posts) on Twitter has a positive association with tobacco use.34  Starting in 2019, image- and video-based platforms, such as Instagram and TikTok, have become the most popular social media sites among youth,35  and influencers on these sites can visually depict and describe their use of e-cigarettes to millions of teenagers who follow their accounts.36  Although regulations prohibiting the promotion of tobacco products to youth on social media began to emerge in 2018, they did not extend to influencers’ ability to promote tobacco content on media platforms, which may be related to a gradual increase in tobacco advertisement exposure on Internet platforms from 2017 to 2019.

Despite overall decreases in exposure to cigarette and e-cigarette advertisements from 2012 and 2014 to 2020, it is concerning that the majority of US youth continue to report relatively high exposure to such marketing. In particular, our results indicate that most exposure comes from retail store–based advertisements, surpassing Internet, press, and other screen marketing avenues.37  Point-of-sale (POS) locations, such as convenience stores and gas stations, where adolescents frequently shop, often contain increased marketing materials for popular tobacco product brands.38,39  These increases in exposure could be a result of new e-cigarettes brands and types of products (eg, vape pens, pods, e-hookahs) that have recently entered the market and that have potentially increased the popularity and/or normalized the broad use of tobacco products among young people.40  Previous literature has emphasized the need for restrictions on tobacco POS advertising because youth who were frequently exposed to such advertisements were found to be twice as likely to try smoking than those who were not, and POS advertisements have been associated with youth brand preference and positive brand imagery.41,42  In Europe, the implementation of POS display bans was associated with a decrease in regular smoking among adolescents, showing promising results for such policies.43  This increase in retail advertisement exposure among adolescents, particularly within POS locations, should be closely monitored because any increase in advertisement restrictions within other venues may lead to further spikes in advertisements within those that are unmonitored.

Our findings highlight several demographic differences in tobacco advertisement exposure, with older adolescents, female youth, those who had ever used tobacco, and those who lived with an individual using tobacco having a higher prevalence of exposure to any tobacco advertisement. These findings are consistent with previous research that has revealed that among US youth, half of older adolescents (14–17 years old) were receptive to at least 1 tobacco advertisement and had higher receptivity compared with younger adolescents (12–13 years old).44  Although the advertisement and promotion of certain tobacco products has historically featured slim, attractive, and athletic models to appeal toward and target women,45,46  our results also contrast recent literature with other nationwide data sets demonstrating a higher prevalence of cigarette advertisement exposure among male youth.47  Exposure to cigarette or e-cigarette advertisements has been associated with significantly higher odds of current use of cigarettes and cigars or cigarillos among adolescents, and those who live with a tobacco user may be more receptive to these advertisements because of increased familiarity with the product.18,44  Adolescents reporting higher tobacco advertisement exposure and living with a tobacco user may be at an especially increased risk for the initiation and continued use of tobacco products because adolescents with nicotine-dependent parents and siblings are more susceptible to smoking initiation and more severe smoking patterns, and this risk increases with prolonged exposure.48,49  Thus, additional research into strategies to reduce disproportionate advertising and prevent subsequent tobacco use of members of these communities is greatly needed.

The strengths of this study include the use of a long-term nationally representative data set to investigate trends in the amount of exposure to nicotine advertisements and potential sociodemographic correlates, allowing for the results to be confidently generalized to the population of interest. Limitations of this study include the use of self-report measures to assess exposure to cigarette and e-cigarette marketing platforms. However, previous studies have found that self-report is a valid means for assessing for exposure and can provide a wider range of responses than many other data collection instruments.50  It should be noted that during the survey period analyzed, the data collection approach was changed from paper and pencil based to digital collection, and this new approach helped improve efficiency and remove inconsistent responses.51  The survey has also been updated since 2019 to include streaming services within the question assessing exposure from TV (eg, “watching TV or streaming service”), which may have changed responses across recent years, and 2020 survey results may differ because of the coronavirus disease 2019 pandemic, which could have impacted school participation rates.52  Additionally, the NYTS questionnaire did not provide a specific definition for “cigarettes and other tobacco products,” and this was taken to refer to conventional tobacco products (eg, cigars [cigars, little cigars, and cigarillos], smokeless tobacco [chewing tobacco, snuff, dip, snus, and dissolvable tobacco], hookahs, pipe tobacco, and bidis [small brown cigarettes wrapped in a leaf]) rather than e-cigarettes from the context provided. Finally, data support the notion that state and federal regulations prompted changes in adolescent nicotine use, but the data cannot confirm this causality, and our findings reported may not be generalizable to other youth who are homeschooled, attend alternative schools, are in detention centers, or have dropped out of school.

Although significant strides have been made to reduce exposure to tobacco advertisements, there is still a strong need to increase tobacco advertisement regulations, especially surrounding e-cigarette use and advertising within retail stores and on social media.53  With potential increases in negative health outcomes related to use of e-cigarettes and similar products among youth in 2019,9  our findings demonstrate an urgent need to reduce adolescent exposure to advertisements for e-cigarettes and other tobacco products. While considering free speech within the context of limiting tobacco advertisements,54,55  such a decrease in tobacco advertisement exposure, especially among youth, may be successful in reducing rates of initiation and improving risk awareness related to e-cigarette and conventional tobacco use, thereby preventing negative short- and long-term public health outcomes.

FUNDING: Funded by National Institutes of Health grant K02 DA043657 (principal investigator: Dr Cavazos-Rehg) and National Institute on Alcohol Abuse and Alcoholism grant F32 AA027941 (principal investigator: Dr Borodovsky). The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the National Institute on Alcohol Abuse and Alcoholism. Funded by the National Institutes of Health (NIH).

Ms Li conceptualized and designed the study, collected data, conducted the initial analyses, drafted the initial manuscript, and reviewed and revised the manuscript; Ms Kaiser, Ms Kasson, and Ms Riordan drafted the initial manuscript and reviewed and revised the manuscript; Mr Cao and Dr Borodovsky critically reviewed initial analyses and critically reviewed and revised the manuscript for important intellectual content; Dr Cavazos-Rehg conceptualized and designed the study, coordinated and supervised data collection, and critically reviewed and revised the manuscript for important intellectual content; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

Deidentified individual participant data will not be made available. Data included in the current analyses were conducted on the publicly accessible National Youth and Tobacco Survey data set.

     
  • aOR

    adjusted odds ratio

  •  
  • CI

    confidence interval

  •  
  • e-cigarette

    electronic cigarette

  •  
  • NYTS

    National Youth Tobacco Survey

  •  
  • POS

    point-of-sale

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Competing Interests

POTENTIAL CONFLICT OF INTEREST: Dr Borodovsky is a member of the board of directors and treasurer of MySafeRx Inc, a nonprofit scientific research organization. He receives no financial compensation from this organization; the other 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.

Supplementary data