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Electronic cigarette advertising and teen smoking initiation
Journal Pre-proofs Electronic cigarette advertising and teen smoking initiation Julia Hansen, Reiner Hanewinkel, Matthis Morgenstern PII: DOI: Reference:
S0306-4603(19)30589-1 https://doi.org/10.1016/j.addbeh.2019.106243 AB 106243
To appear in:
Addictive Behaviors Addictive Behaviors
Received Date: Revised Date: Accepted Date:
14 May 2019 14 November 2019 20 November 2019
Please cite this article as: J. Hansen, R. Hanewinkel, M. Morgenstern, Electronic cigarette advertising and teen smoking initiation, Addictive Behaviors Addictive Behaviors (2019), doi: https://doi.org/10.1016/j.addbeh. 2019.106243
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© 2019 Elsevier Ltd. All rights reserved.
Title: Electronic cigarette advertising and teen smoking initiation
Author names and affiliations: Julia Hansen, PhD a , Reiner Hanewinkel, PhD a, Matthis Morgenstern, PhD a a Institute
for Therapy and Health Research, Harmsstrasse 2, 24114 Kiel, Germany
Corresponding author: Julia Hansen Institute for Therapy and Health Research, Harmsstrasse 2, 24114 Kiel, Germany Email: [email protected]
Abstract Introduction: The objective of this study was to investigate the associations between recall of exposure to e-cigarette advertisements and initial use of e-cigarettes, conventional cigarettes and hookahs one year later among German adolescents. Methods: Longitudinal school-based survey with a sample of 4,529 German adolescents (mean age=12.5 years, SD=1.55). Baseline assessment took place in the fall/winter 2016/2017, and a follow-up assessment 12 months later. Exposure to e-cigarette advertisements was measured at baseline with self-rated contact frequency to three advertising images. Multilevel mixed-effect logistic regression models were used to assess associations between exposure to e-cigarette advertisements at baseline and adolescents’ initiation of ecigarette, smoking and hookah use one year later. Results: About 14% (N=472) baseline never-users initiated e-cigarette use within one year, about 11% (N=384) initiated cigarette use, and 12% (N=406) used a hookah for the first time within the observation period. After statistical control for age, gender, school type, subjective socioeconomic status, sensation seeking, lifetime smoking behavior and peer substance use, adolescents with higher contact to e-cigarette advertisements had higher proportion of subsequent e-cigarette (aOR=1.37 (CI=1.04-1.81) p=.024), cigarette (aOR= 1.44 (CI=1.091.91) p=.010), and hookah use (aOR=1.82 (CI=1.37-2.42) p<.001). Conclusions: This longitudinal study demonstrates that exposure to e-cigarette advertisements may increase the likelihood of initial use of e-cigarettes, cigarettes, and hookahs. Findings raise concerns about e-cigarette marketing regulations in Germany, and about the broader impact of e-cigarette advertising on traditional smoking.
Key words: electronic cigarettes, conventional cigarettes, e-cigarette advertising, adolescence, teen smoking initiation Abbreviations: electronic cigarette = e-cigarette; standard deviation=SD, adjusted odds ratio = aOR, confidence interval = CI, socioeconomic status = SES
1
Introduction The use of electronic cigarettes (e-cigarettes) is an emerging public health issue. E-
cigarettes have gained attractiveness among all age groups, but a number of studies have shown that the prevalence of use is especially high among young people (Krishnan-Sarin, et al., 2019; Loukas, et al., 2019; Schneider, Gorig, Schilling, & Diehl, 2017). New vaping devices are entering the market rapidly (Miech, Johnston, O'Malley, Bachman, & Patrick, 2019), but safety and long-term health effects are still a matter of considerable scientific debate (Bals, et al., 2019; Wills, Pagano, Williams, & Tam, 2019). About 97.2% of German adolescents aged 12 to 17 are aware of e-cigarettes (Orth & Merkel, 2019), and 20 percent of German adolescents aged 14 to 18 years have already used e-cigarettes (Schneider, et al., 2017). Lifetime prevalence of e-cigarette use among adolescents has surpassed conventional cigarette use which declined steadily since the beginning of the millennium (Isensee, Goecke, & Hanewinkel, 2018). The consumption of ecigarettes and hookahs is becoming increasingly important among adolescents and young adults in Germany, and lifetime prevalence of hookah use in adolescents aged 12 to 17 years is about 26.4 % (Orth & Merkel, 2019). Currently, several types of e-cigarette devices (e. g. JUUL, hookah pens, mods, cig-alikes) and a wide variety of flavors are easily accessible in retail and online shops. It is therefore not surprising that marketing has seen extraordinary growth in the past ten years (Collins, Glasser, Abudayyeh, Pearson, & Villanti, 2019; Jenssen & Wilson, 2019). Some of the products and related marketing strategies include kid-friendly flavors, products with a high tech shape/feature and the communication that e-cigarettes are less harmful (Padon, Lochbuehler, Maloney, & Cappella, 2018; Pokhrel, Herzog, Fagan, Unger, & Stacy, 2019). Even though Germany has signed and ratified the WHO Framework Convention on Tobacco Control (FCTC), only mild restrictions on advertising exist. To date, marketing for cigarettes and e-cigarettes is omnipresent, running in public places, bus shelters, and
billboards. Point of sale marketing is allowed as well as advertising in movie theaters after 6 pm. In addition, there is no regulation on public e-cigarette use and no special taxes on the products. There is substantial evidence that tobacco advertisements influence young people’s behavior and lead to initiation and maintenance of smoking (Hanewinkel, Isensee, Sargent, & Morgenstern, 2011; Lovato, Watts, & Stead, 2011). However, there is less evidence regarding the effects of e-cigarette marketing. Some cross-sectional studies suggest an association between exposure to e-cigarette marketing and lower harm perception, intention to use, experimentation with e-cigarettes and initial use, and lower odds of cigarette smoking cessation (Best, et al., 2016; Dai & Hao, 2016; Farrelly, et al., 2015; Hansen, Hanewinkel, & Morgenstern, 2018; Singh, et al., 2016). A limited number of longitudinal studies conducted in the U.S. have shown that exposure to marketing for e-cigarette products increased the likelihood to use e-cigarettes (Agaku, et al., 2017; Camenga, et al., 2018; Nicksic, Harrell, Perez, Pasch, & Perry, 2017; Villanti, et al., 2016), but evidence is scarce. It is also not known if there is a “spill-over” effect, i.e., if exposure to e-cigarette advertisements affects conventional cigarette use (Collins, et al., 2019), but there is concern that marketing of ecigarettes may contribute to a rise in cigarette smoking as well (Cruz, et al., 2019). Hansen et al. recently reported a relationship between e-cigarette marketing and smoking of conventional cigarettes, though this analysis was cross-sectional (Hansen, et al., 2018). Thus, the present study had two main objectives. First, to replicate the longitudinal association found between e-cigarette marketing and e-cigarette initiation of adolescents. Second, to examine the potential existence of a “spill-over” effect of e-cigarette advertising on the use of other tobacco products.
2 2.1
Methods Participants and Procedures Data were collected as part of an ongoing annual cohort health survey that started in
fall/winter 2016/2017 among students from six federal states of Germany (BadenWürttemberg, Mecklenburg-West-Pomerania, North-Rhine-Westphalia, Rhineland-Palatinate, Saxony, and Schleswig-Holstein). Baseline and follow-up assessment took place approximately 12 months apart (i.e., baseline in fall/winter 2016/2017, and 12-month- followup in fall/winter 2017/2018). Baseline and follow-up questionnaires were linked with a sevendigit individual code. These codes were generated by students directly prior to answering the questions. The procedure has been tested in previous studies and was slightly modified for this study (Galanti, et al., 2007). The study was approved by the state ministries of cultural affairs, and ethical approval was obtained from the Ethical Committee of the German Psychological Society. Each state was randomly selected from one of the six Nielsen regions, which represent areas with similar purchasing power and consumer behavior. A total of 627 secondary schools were identified in randomly selected sub-regions within each state, and all of them were invited to participate in the study. The German school system has several types of secondary schools (i.e., Hauptschule, Realschule, Oberschule, Gemeinschaftsschule, and Gymnasium) that mainly differ with regard to the academic skills of their students and graduation level. Students usually graduate from school after 10th – 13th grade (at age of 17–19), depending on school type. Gymnasiums (highest academic level) must be attended until 12th/13th grade. Forty-four secondary schools agreed to participate and registered classes from grades 5 to 10. Study participation was voluntary. However, only students with written parental consent were eligible. Participant’s verbal agreement and parents’ informed consent (forms were disseminated by class teachers two weeks prior to the baseline assessment) were obtained before conducting the study. Data were collected by trained research staff or
instructed school personnel through self-completed anonymous questionnaires (paper pencil or online version) during one school hour (45 min). Adolescents were assured that their individual information would not be seen by parents or school administrators.
2.2
Study sample The study flow is displayed in figure 1. The original baseline sample (N=6,902)
consisted of 5th to 10th graders (49% female, mean age 13.1 years, 51.3 % from “Gymnasium” schools). The 10th graders (n=692) were not followed up in this study, because many students graduate or change school after 10th grade in Germany. They were therefore excluded from all analyses. At follow-up assessment, 1,411 of these adolescents could not be reached again, either because of absence or because of a non-match of the individual code (response rate = 76.2%). A total of 4,529 were followed-up (mean age =12.5 years, SD= 1.55). About 88% (3,959) of the followed-up students were e-cigarette non-users at baseline, 88% (3,966) were cigarette non-users, and 87% (3,925) were hookah non-users.
***insert Figure 1 here***
2.3
Measures
2.3.1 Exposure measurement Exposure to advertisements has been operationalized in numerous ways across studies (Lovato, et al., 2011). Media report data (months February to April 2016) from an independent media monitoring agency (Ad Vision Digital, Germany) were used to provide detailed information on e-cigarette advertisements that were shown in Germany prior to baseline assessment. We selected three advertising campaigns (two television and one internet campaign) from brands with the largest amount of money spent for marketing actions. Fixedimages were extracted from each advertisement and presented to the students with all brand
names removed. The following e-cigarette brands were included in the survey: (1) vype (theme: two hands and a cig-a-like-product) and (2) Be posh (theme: attractive couple with actual use), and (3) ismoker (theme: banner with a cig-a-like device). We assessed individual advertising contact frequency of the adolescents at baseline by asking “How often have you seen this advertisement?”. Students answered on a four-point scale with a range from 1=“never”, 2=“1 to 4 times”, 3=“5 to 10 times” to 4=“more than 10 times”. For further details see Hansen et. al. (2018). Finally, a summative advertisement exposure scale was created. Every observation got a score, and the summative score was divided by the number of items over which the sum was calculated (range 1 to 4).
2.3.2 Lifetime e-cigarette, cigarette, and hookah use Adolescents were asked the following questions at baseline and follow-up assessment ‘How often have you ever vaped electronic cigarettes (smoked cigarettes, smoked hookah, respectively) in your life?’,(never smoked, just a few puffs, 1-19 times, 20-100 times, >100 times) (Bondy, Victor, & Diemert, 2009) Answers were recoded as 0=never and 1= all other options. Baseline never-users were classified as having initiated e-cigarette, cigarette, and/or hookah use if they reported anything else than non-smoking at follow-up.
2.3.3 Covariates To address possible confounding influences, baseline factors associated with smoking behavior (i.e., cigarettes, e-cigarettes, and hookah) were included as covariates. They were derived from studies that focused on risk factors concerning advertisement and smoking/ ‘vaping’ behavior (Perikleous, Steiropoulos, Paraskakis, Constantinidis, & Nena, 2018). Covariates were selected from the following three domains. Sociodemographic: Age, gender (male coded as 0, female coded as 1), migration background (0 = none, 1 = yes) and socioeconomic status (SES) were assessed. SES was
assessed by the MacArthur Scale of ‘Subjective Social Status’, which is represented as a picture of a "social ladder" (Goodman, et al., 2001). Range of the ladder is from 1 (low SES) to 10 (high SES). Environmental Factors: Potential environmental influences included the type of school participants attended. The German school system has different types of schools that differ regarding their academic level: ‘Gymnasiums’ (high academic level, graduation after 12/13th grade) were coded as 1 and other schools (lower academic level compared to ‘gymnasiums’, graduation after 9/10th grade) were coded as 0. Peer substance use was assessed by responses to the question, “How many of your friends use cigarettes /e-cigarettes or e-hookah/ hookah?” (Eleven-point scale, ranging from 0=none to 10=all, Cronbach’s alpha=.87). Answers were dichotomized into “none” (0) vs. all other responses (coded as 1). Personal characteristics: Sensation seeking is central to research on the prevention of risky health behaviors. We used the Sensation Seeking 2 Scale (SS2) that comprises two items (r=.71) ‘How often do you do dangerous things, just because to have fun?’, ‘How often do you do exciting things even though they are dangerous?’ respectively, with a five-pointscale from ‘never’ to ‘very often’(Slater, 2003; Stephenson, Hoyle, Palmgreen, & Slater, 2003). The two items were summed up and divided by two.
2.4
Statistical analysis For each binary outcome, we used multilevel mixed effect logistic regressions to
determine the association between exposure and initiation within one year after baseline. To allow for nested data, school and class level were included in the models. Adjusted odds ratios (aOR) and 95% confidence interval (CI) are reported. Prevalence was weighted to census data to account for offset nonresponse bias and to increase representativeness of the sample. Weighting factors were age, gender, migration background, and school type.
Weighted prevalence of smoking behavior, sensation seeking, socioeconomic status, and exposure to advertisements are reported. In the final models, all potentially confounding variables were included to obtain estimates for the exposure-behavior association after keeping other influencing factors constant. Lifetime smoking behaviors (e-cigarette use, cigarette use, and hookah use) were included in the models as confounders (none = 0, yes = 1).
3 3.1
Results Attrition analysis We analyzed attrition between the baseline and follow-up sample by using Chi-
Squared tests and t-Tests. Overall, 1,411 (23.8%) participants dropped out. They were slightly older (p<.001), less likely to be attending college-preparatory secondary schools (‘gymnasiums’, p=.007), were more likely to have vaped e-cigarettes before (p<.001), to have smoked conventional cigarettes (p<.002), and to have used hookah before (p<.001). Adolescents who dropped out were more likely to have reported exposure to e-cigarette advertisements (p<.001) and scored higher on sensation seeking scale (p<.001).
3.2
Sample characteristics and smoking behavior Demographic data of the analysis samples dependent on the initiation status is
presented in Table 1. Overall, about 38% (N=2,197) of the adolescents recalled exposure to ecigarette advertisements at baseline, 13.6% (N=472) began to vape within one year from baseline assessment. About 10.8% (N=384) of the students experimented with conventional cigarettes, and 12.4% (N=406) used a hookah for the first time within the observation period.
***insert Table 1 here***
3.3
Recall of exposure to e-cigarette advertisements and subsequent use of e-
cigarettes, cigarettes, and hookah To determine whether the recall of exposure to e-cigarette advertising was related to subsequent use of e-cigarettes, cigarettes, and hookah use, multilevel mixed effect logistic regressions were performed. As shown in Table 2, exposure to e-cigarette marketing messages was significantly associated with subsequent e-cigarette use (aOR=1.37 (95% CI 1.04-1.81) p=.024). Relatedly, adolescents who had never used conventional cigarettes at baseline were more likely to report using them one year later at follow-up assessment if they had been exposed to advertisements for e-cigarettes (aOR=1.44 (95% CI 1.09-1.91) p=.010). The odds for hookah initiation were 82% higher for exposed compared to unexposed never hookah users (aOR= 1.82 (95% CI 1.37-2.42) p<.001). In more detail, findings of the multilevel mixed effect logistic regressions revealed that 20.5% of the adolescents who reported being highly exposed to e-cigarette advertisements (exposure scale point=4) used e-cigarettes within the observation period for the first time. In the group of adolescents that reported non-exposure (exposure scale point=1), 11.1% of the adolescents reported initial use of e-cigarettes. Predicted frequencies for initial use of conventional cigarettes were 19.8% for highly exposed adolescents and 9.1% for the non-exposed group, respectively. Predicted frequencies for the initial use of hookah were 28.5% (highly exposed) and 9.2% (non-exposed). In addition, e-cigarette, cigarette and hookah use initiation were more frequently observed among those students who have friends that vape or smoke. Initial use of ecigarettes at follow-up was associated with cigarette and hookah use at baseline and initial use of cigarettes was associated with e-cigarette and hookah use. Experimentation with hookahs within the observation period was only linked to e-cigarette use at baseline, but not to cigarette use.
Sensation seeking, age, migrant background, and school type were also independent predictors of all three outcomes. Students with a migrant background were more likely to have used hookahs for the first time while students without migrant background were more likely to experiment with e-cigarettes and conventional cigarettes.
***insert Table 2 here*** 4
Discussion This longitudinal study provides information about the role of e-cigarette advertising
in e-cigarette, cigarette, and hookah initiation in a cohort of 4,529 German adolescents that were observed over a 12 months period. Among never e-cigarette users at baseline, 13.6 % of adolescents reported e-cigarette use at follow-up which is similar to the a recently published initiation rate of U.S students who attended grades 6 to 10 (Loukas, et al., 2019). Current data from German Federal Center of Health Education revealed that lifetime prevalence of ecigarette use among German adolescents has significantly increased from 2012 to 2018. The increase is primarily due to male adolescents’ use of e-cigarettes (Orth & Merkel, 2019), a trend that is also evident in the results of the present study. Overall, adolescents’ exposure to e-cigarette advertising was high. Our findings indicate that 37.1 % of adolescents who were 12.6 years old on average recalled exposure to e-cigarette marketing. Comparable estimates for exposure to e-cigarette advertising were found in the Eurobarometer survey (Filippidis, et al., 2017). There are two central findings from this study. First, an association between exposure to e-cigarette advertising at baseline and the experimental use of e-cigarettes during the observation period was still present after adjustment for numerous confounding variables (i.e., age, gender, sensation seeking, socioeconomic status, school type, migrant background, peer use, lifetime cigarette and hookah use). This result is in line with previous longitudinal studies on US cohorts (Agaku, et al., 2017; Camenga, et al., 2018; Loukas, et al., 2019).
The second central finding is related to the “spill-over” effect, i.e., if e-cigarette marketing is related to the experimentation with other tobacco products. There was also a significant independent association between baseline exposure to e-cigarette marketing and the initiation of conventional cigarettes and hookahs one year later. This implies that ecigarette advertisements could have a broader impact on adolescents’ health behavior than previously assumed. The finding is in contrast to a previous study examining a “spill-over” effect of e-cigarette advertising, which reported a null result (Villanti, et al., 2016). However, while the Villanti et al. study had a high internal validity due to an experimental design, the exposure measure was very different to our present analysis. Participants only had a brief laboratory exposure to e-cigarette marketing, making the results of the two studies hardly comparable. E-cigarette advertising contents have a striking similarity to conventional cigarette advertisements. For example, one advertisement depicts attractive people while holding a ciga-like product. There is evidence that the depiction of people using an e-cigarette in advertisements created more interest in trying e-cigarettes among adult smokers than ads with other images (Pepper, Emery, Ribisl, Southwell, & Brewer, 2014). Hence, e-cigarette advertisements with people using a cig-a-like product could be seen as the promotion of smoking behavior in general, creating interest for all kinds of smoking products. However, more longitudinal research is needed to examine the specificity of the relationship between ecigarette marketing and initial use of different kinds of smoking products in the group of nonusers. Another possible explanation for the found “spill-over” effect could be based on the gateway hypothesis that assumes a transition from one product to another (Kandel, 1975). There is empirical evidence that the use of e-cigarettes can motivate adolescents to start smoking conventional cigarettes (Glantz & Bareham, 2018; Morgenstern, Nies, Goecke, & Hanewinkel, 2018) and that the use of nicotine-containing liquids in e-cigarettes could be a
gateway to the use of conventional cigarettes (Etter, 2018; Schneider & Diehl, 2016). Thus, it is thinkable that exposure to e-cigarette advertisements and smoking behavior is related chronologically. Adolescents that were exposed to e-cigarette advertisements could be at higher risk to start using e-cigarettes. The ones who had used e-cigarettes could be in turn at higher risk to start smoking traditional tobacco cigarettes. More research is needed to address this potential chronological sequence, which considers the exposure to advertisements and the use of nicotine-containing liquids in e-cigarettes prior to the initial use of conventional cigarettes. Despite the significant findings, the current manuscript may even underestimate the magnitude of the effects of e-cigarette advertising. Attrition analyses indicated that higher risk adolescents (e.g., those more likely to have used e-cigarettes, conventional cigarettes, and hookah; more likely to have been exposed to advertisements; more likely to be willing to take a risk) were more likely to drop out of the study, and e-cigarette advertising would probably be more likely to affect these higher-risk adolescents.
4.1
Limitations For a proper interpretation of the results, some limitations have to be considered. First,
selected images of e-cigarette advertisement only covered a small variety of advertisements that ran in 2016, meaning that the implemented method did not use a representative sample of all e-cigarette marketing actions shown in Germany. It can therefore not be seen as a measure of overall exposure and does not allow for a precise estimation of the total amount of ecigarette ad exposure of adolescents in Germany. In the present study, only two sources of advertising (television and online media) were examined cumulatively. In addition, selected advertisement sources were banned in Germany later in 2016. Future research is needed that examines the marketing channels individually rather than cumulatively (Loukas, et al., 2019).
The use of tobacco products in association with advertisements could also be underestimated because of hidden advertisements in other channels, for instance cinemas and movies (Grana, Glantz, & Ling, 2011; Morgenstern, et al., 2013). Selected stimulus material included sources that have been prohibited since May 2016 (TV and internet ads), but were accessible for students before survey implementation. The models accounted for several important confounders but there may have been other confounding variables that were not integrated in the models; for instance, parental tobacco use, susceptibility to e-cigarettes or other tobacco advertising. Accounting for conventional cigarette advertising could strengthen the results because specific content-related effects could have been examined. Further, all variables were assessed by self-reports, and can only be regarded as a proxy of the actual behavior.
4.2
Conclusions This study adds to a limited number of longitudinal studies that examined the role of
e-cigarette advertisement in the later use of e-cigarettes. It supports previous cross-sectional analyses linking e-cigarette advertisement exposure with the use of e-cigarette products and other tobacco products. By using longitudinal data from German adolescents, this study fills the gap of missing evidence for a sample outside the U.S.. The reported “spill-over” effect raises serious concerns, but future research is needed to address a potential content-related effect of e-cigarette advertisements. Overall, the results of the present study support public health efforts to reduce exposure to marketing, including a comprehensive ban of all forms of tobacco and e-cigarette advertisements to protect youth from adverse health effects.
Conflict of interests: Julia Hansen, Reiner Hanewinkel, Matthis Morgenstern declare they have no conflict of interests.
Funding Source: The study is supported by DAK-Gesundheit (German Health Insurance Company). The funder had no role in the design and conduct of the study; no role in collection, management, analysis, and interpretation of the data; no role in preparation, review, or approval of the manuscript; and in the decision to submit the manuscript for publication.
Financial Disclosure: Julia Hansen, Reiner Hanewinkel, Matthis Morgenstern have nothing to disclose.
Acknowledgements The authors would like to thank Toska Jakob, Corinna Gutjahr, and Luise Rehermann for their support in data collection, Dr. Emeka W. Dumbili for his constructive criticism of the manuscript, and the DAK-Gesundheit for funding of the study, and all schools that have participated in the study.
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Hanewinkel, R., Isensee, B., Sargent, J. D., & Morgenstern, M. (2011). Cigarette advertising and teen smoking initiation. Pediatrics, 127, e271-278. Hansen, J., Hanewinkel, R., & Morgenstern, M. (2018). Electronic cigarette marketing and smoking behaviour in adolescence: a cross-sectional study. ERJ Open Res, 4. Isensee, B., Goecke, M., & Hanewinkel, R. (2018). Zigarette, Shisha, E-Zigarette und Tabakerhitzer: Häufigkeit und Muster des Konsums unterschiedlicher Nikotinprodukte im Jugendalter. Suchtmedizin, 20. Jenssen, B. P., & Wilson, K. M. (2019). What is new in electronic-cigarettes research? Curr Opin Pediatr, 31, 262-266. Kandel, D. (1975). Stages in adolescent involvement in drug use. Science, 190, 912-914. Krishnan-Sarin, S., Jackson, A., Morean, M., Kong, G., Bold, K. W., Camenga, D. R., Cavallo, D. A., Simon, P., & Wu, R. (2019). E-cigarette devices used by high-school youth. Drug Alcohol Depend, 194, 395-400. Loukas, A., Paddock, E. M., Li, X., Harrell, M. B., Pasch, K. E., & Perry, C. L. (2019). Electronic Nicotine Delivery Systems Marketing and Initiation Among Youth and Young Adults. Pediatrics, 144. Lovato, C., Watts, A., & Stead, L. F. (2011). Impact of tobacco advertising and promotion on increasing adolescent smoking behaviours. Cochrane Database Syst Rev, CD003439. Miech, R., Johnston, L., O'Malley, P. M., Bachman, J. G., & Patrick, M. E. (2019). Adolescent Vaping and Nicotine Use in 2017-2018 - U.S. National Estimates. N Engl J Med, 380, 192-193. Morgenstern, M., Nies, A., Goecke, M., & Hanewinkel, R. (2018). E-Cigarettes and the Use of Conventional Cigarettes. Dtsch Arztebl Int, 115, 243-248. Morgenstern, M., Sargent, J. D., Engels, R., Scholte, R. H. J., Florek, E., Hunt, K., Sweeting, H., Mathis, F., Faggiano, F., & Hanewinkel, R. (2013). Smoking in movies and adolescent smoking initiation: longitudinal study in six European countries. Am J Prev Med, 44, 339-344. Nicksic, N. E., Harrell, M. B., Perez, A., Pasch, K. E., & Perry, C. L. (2017). Recall of E-cigarette Advertisements and Adolescent E-cigarette Use. Tob Regul Sci, 3, 210-221. Orth, B., & Merkel, C. (2019). Rauchen bei Jugendlichen und jungen Erwachsenen in Deutschland. Ergebnisse des Alkoholsurveys 2018 und Trends. BZgA-Forschungsbericht. Köln: Bundeszentrale für gesundheitliche Aufklärung. Padon, A. A., Lochbuehler, K., Maloney, E. K., & Cappella, J. N. (2018). A Randomized Trial of the Effect of Youth Appealing E-Cigarette Advertising on Susceptibility to Use E-Cigarettes Among Youth. Nicotine Tob Res, 20, 954-961. Pepper, J. K., Emery, S. L., Ribisl, K. M., Southwell, B. G., & Brewer, N. T. (2014). Effects of advertisements on smokers' interest in trying e-cigarettes: the roles of product comparison and visual cues. Tob Control, 23 Suppl 3, iii31-36. Perikleous, E. P., Steiropoulos, P., Paraskakis, E., Constantinidis, T. C., & Nena, E. (2018). ECigarette Use Among Adolescents: An Overview of the Literature and Future Perspectives. Front Public Health, 6, 86.
Pokhrel, P., Herzog, T. A., Fagan, P., Unger, J. B., & Stacy, A. W. (2019). E-cigarette Advertising Exposure, Explicit and Implicit Harm Perceptions, and E-cigarette Use Susceptibility Among Nonsmoking Young Adults. Nicotine Tob Res, 21, 127-131. Schneider, S., & Diehl, K. (2016). Vaping as a Catalyst for Smoking? An Initial Model on the Initiation of Electronic Cigarette Use and the Transition to Tobacco Smoking Among Adolescents. Nicotine Tob Res, 18, 647-653. Schneider, S., Gorig, T., Schilling, L., & Diehl, K. (2017). [E-Cigarettes on Everyone's Lips - Current Representative Data on Use Among Adolescents and Adults]. Dtsch Med Wochenschr, 142, e156-e166. Singh, T., Agaku, I. T., Arrazola, R. A., Marynak, K. L., Neff, L. J., Rolle, I. T., & King, B. A. (2016). Exposure to Advertisements and Electronic Cigarette Use Among US Middle and High School Students. Pediatrics, 137, e20154155. Slater, M. D. (2003). Alienation, Aggression, and Sensation Seeking as Predictors of Adolescent Use of Violent Film, Computer, and Website Content. Journal of Communication, 53, 105-121. Stephenson, M. T., Hoyle, R. H., Palmgreen, P., & Slater, M. D. (2003). Brief measures of sensation seeking for screening and large-scale surveys. Drug Alcohol Depend, 72, 279-286. Villanti, A. C., Rath, J. M., Williams, V. F., Pearson, J. L., Richardson, A., Abrams, D. B., Niaura, R. S., & Vallone, D. M. (2016). Impact of Exposure to Electronic Cigarette Advertising on Susceptibility and Trial of Electronic Cigarettes and Cigarettes in US Young Adults: A Randomized Controlled Trial. Nicotine Tob Res, 18, 1331-1339. Wills, T. A., Pagano, I., Williams, R. J., & Tam, E. K. (2019). E-cigarette use and respiratory disorder in an adult sample. Drug Alcohol Depend, 194, 363-370.
Figure 1. Flowchart
Table 1. Characteristics of the analysis samples by follow-up initiation status.
Characteristics of the analysis samples e-cigarette non-users at followup
e-cigarette initiators at followup
cigarette non-users at followup
cigarette initiators at followup
hookah non-users at followup
hookah initiators at followup
Total N (%)
3,463 (86.4)
472 (13.6)
3,560 (89.2)
384 (10.8 )
3.461 (87.6)
406 (12.4)
Demographics
N (%)/ M (SD)
N (%)/ M (SD)
N (%)/ M (SD)
N (%)/ M (SD)
N (%)/ M (SD)
N (%)/ M (SD)
12.2 (1.51) (3,455)
13.0 (1.28) (471)
12.2 (1.49) (3,552)
12.9 (1.43) (384)
12.2 (1.49) (3,453)
12.9 (1.34) (404)
Gender (female)
1,772 (51.2)
188 (39.8)
1,752 (49.3)
185 (48.2)
1,755 (50.8)
178 (44.0)
Migration (yes)
543 (15.7)
77 (16.3)
609 (17.1)
61 (15.9)
492 (14.2)
85 (21.0)
Socioeconomic status (high)a
980 (28.2)
136 (27.3)
1,007 (28.1)
113 (27.8)
968 (27.7)
123 (28.6)
Type of school (gymnasiums)
2,001 (57.8)
187 (39.6)
2,041 (57.3)
140 (36.5)
2,000 (57.8)
158 (38.9)
Sensation seeking (high) a
706 (21.2)
223 (46.0)
743 (21.9)
163 (41.7)
702 (20.8)
177 (43.8)
Peer use b (yes)
944 (32.4)
319 (71.4)
1.043 (35.2)
232 (64.4)
947 (32.1)
266 (69.2)
Exposure to ecigarette advertising (yes)
1,065 (32.1)
216 (51.1)
1,132 (33.3)
163 (42.9)
1,055 (31.5)
192 (45.3)
Age
a
tertile split least one friend uses e-cigarettes/cigarettes/hookah
b At
Table 2. Associations of the recall of exposure to e-cigarette advertisements and initiation of e-cigarettes, cigarettes, and hookah use within 12-months from baseline.
Initiation of e-cigarette use N=(3,839) aOR (95% CI)
cigarette use N=(3,848) aOR (95% CI)
hookah use (N=3,771) aOR (95% CI)
Recall of exposure to ecigarette advertisements (Range 1 – 4)
1.37 (1.04-1.81) p=.024
1.44 (1.09-1.91) p=.010
1.82 (1.37-2.42) p<.001
Age
1.25 (1.14-1.38) p<.001
1.28 (1.16-1.41) p<.001
1.28 (1.15-1.42) p<.001
Gender (male=0)
.71 (.56-.90) p=.004
1.29 (1.01-1.65) p=.039
.91 (.70-1.16) p=.441
Migration background (none=0)
.70 (.50-.98) p=.040
.50 (.35-.73) p<.001
1.49 (1.07-2.07) p=.017
Socioeconomic status (Range 1 = low to 10 = high)
1.03 (.95-1.12) p=.495
1.00 (.92-1.10) p=.927
1.06 (.97-1.16) p=.213
School type (other types than gymnasiums=0)
.51 (.35-.74) p<.001
.46 (.32-.67) p<.001
.62 (.42-.93) p=.021
Sensation Seeking
1.75 (1.55-1.98) p<.001
1.65 (1.45-1.87) p<.001
1.81 (1.59-2.06) p<.001
Peer Usea (none=0)
2.96 (2.28-3.85) p<.001
1.84 (1.39-2.42) p<.001
2.45 (1.85-3.24) p<.001
--
1.79 (1.16-2.75) p=.008
4.68 (3.04-7.21) p<.001
Lifetime cigarette use (none=0)
1.56 (1.08-2.27) p=.019
--
1.48 (.99-2.21) p=.056
Lifetime hookah use (none=0)
3.87 (2.64-5.68) p<.001
2.08 (1.39-3.11) p<.001
--
Lifetime e-cigarette use (none=0)
aOR= Adjusted Odds Ratio, CI =Confidence Interval a At least one friend uses e-cigarettes/cigarettes/hookah
Highlights
“Electronic cigarette advertising and teen smoking initiation”
Study examined the impact of e-cig marketing on smoking behavior. Exposure to e-cig advertisements increased the likelihood of future e-cigarette use. Exposure to e-cig marketing was associated with the use of conventional cigarettes.
We confirm that this work is original and has not been published elsewhere, nor is it currently under consideration for publication elsewhere. We have no conflicts of interest to disclose. The study is supported by DAK-Gesundheit (German Health Insurance Company). The funder had no role in the design and conduct of the study; no role in collection, management, analysis, and interpretation of the data; no role in preparation, review, or approval of the manuscript; and in the decision to submit the manuscript for publication. Dr Hansen drafted the manuscript, designed the data collection instruments, coordinated data collection, and carried out the initial analyses. Dr Hansen is taking final responsibility for the paper. Drs Hanewinkel and Morgenstern conceptualized and designed the study, and supervised data collection instruments, and data collection, and revised and critically reviewed the manuscript for important intellectual content. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.
Statement 1: Role of Funding Sources The study is supported by DAK-Gesundheit (German Health Insurance Company). The funder had no role in the design and conduct of the study; no role in collection, management, analysis, and interpretation of the data; no role in preparation, review, or approval of the manuscript; and in the decision to submit the manuscript for publication. Statement 2: Contributors Dr Hansen drafted the manuscript, designed the data collection instruments, coordinated data collection, and carried out the initial analyses. Dr Hansen is taking final responsibility for the paper. Drs Hanewinkel and Morgenstern conceptualized and designed the study, and supervised data collection instruments, and data collection, and revised and critically reviewed the manuscript for important intellectual content. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work. Statement 3: Conflict of Interest All authors declare they have no conflict of interests. Financial Disclosure: Julia Hansen, Reiner Hanewinkel, Matthis Morgenstern have nothing to disclose.
Statement 4: Acknowledgements The authors would like to thank Toska Jakob, Corinna Gutjahr, and Luise Rehermann for their support in data collection, Dr. Emeka W. Dumbili for his constructive criticism of the manuscript, and the DAK-Gesundheit for funding of the study, and all schools that have participated in the study.
S0306-4603(19)30589-1 https://doi.org/10.1016/j.addbeh.2019.106243 AB 106243
To appear in:
Addictive Behaviors Addictive Behaviors
Received Date: Revised Date: Accepted Date:
14 May 2019 14 November 2019 20 November 2019
Please cite this article as: J. Hansen, R. Hanewinkel, M. Morgenstern, Electronic cigarette advertising and teen smoking initiation, Addictive Behaviors Addictive Behaviors (2019), doi: https://doi.org/10.1016/j.addbeh. 2019.106243
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© 2019 Elsevier Ltd. All rights reserved.
Title: Electronic cigarette advertising and teen smoking initiation
Author names and affiliations: Julia Hansen, PhD a , Reiner Hanewinkel, PhD a, Matthis Morgenstern, PhD a a Institute
for Therapy and Health Research, Harmsstrasse 2, 24114 Kiel, Germany
Corresponding author: Julia Hansen Institute for Therapy and Health Research, Harmsstrasse 2, 24114 Kiel, Germany Email: [email protected]
Abstract Introduction: The objective of this study was to investigate the associations between recall of exposure to e-cigarette advertisements and initial use of e-cigarettes, conventional cigarettes and hookahs one year later among German adolescents. Methods: Longitudinal school-based survey with a sample of 4,529 German adolescents (mean age=12.5 years, SD=1.55). Baseline assessment took place in the fall/winter 2016/2017, and a follow-up assessment 12 months later. Exposure to e-cigarette advertisements was measured at baseline with self-rated contact frequency to three advertising images. Multilevel mixed-effect logistic regression models were used to assess associations between exposure to e-cigarette advertisements at baseline and adolescents’ initiation of ecigarette, smoking and hookah use one year later. Results: About 14% (N=472) baseline never-users initiated e-cigarette use within one year, about 11% (N=384) initiated cigarette use, and 12% (N=406) used a hookah for the first time within the observation period. After statistical control for age, gender, school type, subjective socioeconomic status, sensation seeking, lifetime smoking behavior and peer substance use, adolescents with higher contact to e-cigarette advertisements had higher proportion of subsequent e-cigarette (aOR=1.37 (CI=1.04-1.81) p=.024), cigarette (aOR= 1.44 (CI=1.091.91) p=.010), and hookah use (aOR=1.82 (CI=1.37-2.42) p<.001). Conclusions: This longitudinal study demonstrates that exposure to e-cigarette advertisements may increase the likelihood of initial use of e-cigarettes, cigarettes, and hookahs. Findings raise concerns about e-cigarette marketing regulations in Germany, and about the broader impact of e-cigarette advertising on traditional smoking.
Key words: electronic cigarettes, conventional cigarettes, e-cigarette advertising, adolescence, teen smoking initiation Abbreviations: electronic cigarette = e-cigarette; standard deviation=SD, adjusted odds ratio = aOR, confidence interval = CI, socioeconomic status = SES
1
Introduction The use of electronic cigarettes (e-cigarettes) is an emerging public health issue. E-
cigarettes have gained attractiveness among all age groups, but a number of studies have shown that the prevalence of use is especially high among young people (Krishnan-Sarin, et al., 2019; Loukas, et al., 2019; Schneider, Gorig, Schilling, & Diehl, 2017). New vaping devices are entering the market rapidly (Miech, Johnston, O'Malley, Bachman, & Patrick, 2019), but safety and long-term health effects are still a matter of considerable scientific debate (Bals, et al., 2019; Wills, Pagano, Williams, & Tam, 2019). About 97.2% of German adolescents aged 12 to 17 are aware of e-cigarettes (Orth & Merkel, 2019), and 20 percent of German adolescents aged 14 to 18 years have already used e-cigarettes (Schneider, et al., 2017). Lifetime prevalence of e-cigarette use among adolescents has surpassed conventional cigarette use which declined steadily since the beginning of the millennium (Isensee, Goecke, & Hanewinkel, 2018). The consumption of ecigarettes and hookahs is becoming increasingly important among adolescents and young adults in Germany, and lifetime prevalence of hookah use in adolescents aged 12 to 17 years is about 26.4 % (Orth & Merkel, 2019). Currently, several types of e-cigarette devices (e. g. JUUL, hookah pens, mods, cig-alikes) and a wide variety of flavors are easily accessible in retail and online shops. It is therefore not surprising that marketing has seen extraordinary growth in the past ten years (Collins, Glasser, Abudayyeh, Pearson, & Villanti, 2019; Jenssen & Wilson, 2019). Some of the products and related marketing strategies include kid-friendly flavors, products with a high tech shape/feature and the communication that e-cigarettes are less harmful (Padon, Lochbuehler, Maloney, & Cappella, 2018; Pokhrel, Herzog, Fagan, Unger, & Stacy, 2019). Even though Germany has signed and ratified the WHO Framework Convention on Tobacco Control (FCTC), only mild restrictions on advertising exist. To date, marketing for cigarettes and e-cigarettes is omnipresent, running in public places, bus shelters, and
billboards. Point of sale marketing is allowed as well as advertising in movie theaters after 6 pm. In addition, there is no regulation on public e-cigarette use and no special taxes on the products. There is substantial evidence that tobacco advertisements influence young people’s behavior and lead to initiation and maintenance of smoking (Hanewinkel, Isensee, Sargent, & Morgenstern, 2011; Lovato, Watts, & Stead, 2011). However, there is less evidence regarding the effects of e-cigarette marketing. Some cross-sectional studies suggest an association between exposure to e-cigarette marketing and lower harm perception, intention to use, experimentation with e-cigarettes and initial use, and lower odds of cigarette smoking cessation (Best, et al., 2016; Dai & Hao, 2016; Farrelly, et al., 2015; Hansen, Hanewinkel, & Morgenstern, 2018; Singh, et al., 2016). A limited number of longitudinal studies conducted in the U.S. have shown that exposure to marketing for e-cigarette products increased the likelihood to use e-cigarettes (Agaku, et al., 2017; Camenga, et al., 2018; Nicksic, Harrell, Perez, Pasch, & Perry, 2017; Villanti, et al., 2016), but evidence is scarce. It is also not known if there is a “spill-over” effect, i.e., if exposure to e-cigarette advertisements affects conventional cigarette use (Collins, et al., 2019), but there is concern that marketing of ecigarettes may contribute to a rise in cigarette smoking as well (Cruz, et al., 2019). Hansen et al. recently reported a relationship between e-cigarette marketing and smoking of conventional cigarettes, though this analysis was cross-sectional (Hansen, et al., 2018). Thus, the present study had two main objectives. First, to replicate the longitudinal association found between e-cigarette marketing and e-cigarette initiation of adolescents. Second, to examine the potential existence of a “spill-over” effect of e-cigarette advertising on the use of other tobacco products.
2 2.1
Methods Participants and Procedures Data were collected as part of an ongoing annual cohort health survey that started in
fall/winter 2016/2017 among students from six federal states of Germany (BadenWürttemberg, Mecklenburg-West-Pomerania, North-Rhine-Westphalia, Rhineland-Palatinate, Saxony, and Schleswig-Holstein). Baseline and follow-up assessment took place approximately 12 months apart (i.e., baseline in fall/winter 2016/2017, and 12-month- followup in fall/winter 2017/2018). Baseline and follow-up questionnaires were linked with a sevendigit individual code. These codes were generated by students directly prior to answering the questions. The procedure has been tested in previous studies and was slightly modified for this study (Galanti, et al., 2007). The study was approved by the state ministries of cultural affairs, and ethical approval was obtained from the Ethical Committee of the German Psychological Society. Each state was randomly selected from one of the six Nielsen regions, which represent areas with similar purchasing power and consumer behavior. A total of 627 secondary schools were identified in randomly selected sub-regions within each state, and all of them were invited to participate in the study. The German school system has several types of secondary schools (i.e., Hauptschule, Realschule, Oberschule, Gemeinschaftsschule, and Gymnasium) that mainly differ with regard to the academic skills of their students and graduation level. Students usually graduate from school after 10th – 13th grade (at age of 17–19), depending on school type. Gymnasiums (highest academic level) must be attended until 12th/13th grade. Forty-four secondary schools agreed to participate and registered classes from grades 5 to 10. Study participation was voluntary. However, only students with written parental consent were eligible. Participant’s verbal agreement and parents’ informed consent (forms were disseminated by class teachers two weeks prior to the baseline assessment) were obtained before conducting the study. Data were collected by trained research staff or
instructed school personnel through self-completed anonymous questionnaires (paper pencil or online version) during one school hour (45 min). Adolescents were assured that their individual information would not be seen by parents or school administrators.
2.2
Study sample The study flow is displayed in figure 1. The original baseline sample (N=6,902)
consisted of 5th to 10th graders (49% female, mean age 13.1 years, 51.3 % from “Gymnasium” schools). The 10th graders (n=692) were not followed up in this study, because many students graduate or change school after 10th grade in Germany. They were therefore excluded from all analyses. At follow-up assessment, 1,411 of these adolescents could not be reached again, either because of absence or because of a non-match of the individual code (response rate = 76.2%). A total of 4,529 were followed-up (mean age =12.5 years, SD= 1.55). About 88% (3,959) of the followed-up students were e-cigarette non-users at baseline, 88% (3,966) were cigarette non-users, and 87% (3,925) were hookah non-users.
***insert Figure 1 here***
2.3
Measures
2.3.1 Exposure measurement Exposure to advertisements has been operationalized in numerous ways across studies (Lovato, et al., 2011). Media report data (months February to April 2016) from an independent media monitoring agency (Ad Vision Digital, Germany) were used to provide detailed information on e-cigarette advertisements that were shown in Germany prior to baseline assessment. We selected three advertising campaigns (two television and one internet campaign) from brands with the largest amount of money spent for marketing actions. Fixedimages were extracted from each advertisement and presented to the students with all brand
names removed. The following e-cigarette brands were included in the survey: (1) vype (theme: two hands and a cig-a-like-product) and (2) Be posh (theme: attractive couple with actual use), and (3) ismoker (theme: banner with a cig-a-like device). We assessed individual advertising contact frequency of the adolescents at baseline by asking “How often have you seen this advertisement?”. Students answered on a four-point scale with a range from 1=“never”, 2=“1 to 4 times”, 3=“5 to 10 times” to 4=“more than 10 times”. For further details see Hansen et. al. (2018). Finally, a summative advertisement exposure scale was created. Every observation got a score, and the summative score was divided by the number of items over which the sum was calculated (range 1 to 4).
2.3.2 Lifetime e-cigarette, cigarette, and hookah use Adolescents were asked the following questions at baseline and follow-up assessment ‘How often have you ever vaped electronic cigarettes (smoked cigarettes, smoked hookah, respectively) in your life?’,(never smoked, just a few puffs, 1-19 times, 20-100 times, >100 times) (Bondy, Victor, & Diemert, 2009) Answers were recoded as 0=never and 1= all other options. Baseline never-users were classified as having initiated e-cigarette, cigarette, and/or hookah use if they reported anything else than non-smoking at follow-up.
2.3.3 Covariates To address possible confounding influences, baseline factors associated with smoking behavior (i.e., cigarettes, e-cigarettes, and hookah) were included as covariates. They were derived from studies that focused on risk factors concerning advertisement and smoking/ ‘vaping’ behavior (Perikleous, Steiropoulos, Paraskakis, Constantinidis, & Nena, 2018). Covariates were selected from the following three domains. Sociodemographic: Age, gender (male coded as 0, female coded as 1), migration background (0 = none, 1 = yes) and socioeconomic status (SES) were assessed. SES was
assessed by the MacArthur Scale of ‘Subjective Social Status’, which is represented as a picture of a "social ladder" (Goodman, et al., 2001). Range of the ladder is from 1 (low SES) to 10 (high SES). Environmental Factors: Potential environmental influences included the type of school participants attended. The German school system has different types of schools that differ regarding their academic level: ‘Gymnasiums’ (high academic level, graduation after 12/13th grade) were coded as 1 and other schools (lower academic level compared to ‘gymnasiums’, graduation after 9/10th grade) were coded as 0. Peer substance use was assessed by responses to the question, “How many of your friends use cigarettes /e-cigarettes or e-hookah/ hookah?” (Eleven-point scale, ranging from 0=none to 10=all, Cronbach’s alpha=.87). Answers were dichotomized into “none” (0) vs. all other responses (coded as 1). Personal characteristics: Sensation seeking is central to research on the prevention of risky health behaviors. We used the Sensation Seeking 2 Scale (SS2) that comprises two items (r=.71) ‘How often do you do dangerous things, just because to have fun?’, ‘How often do you do exciting things even though they are dangerous?’ respectively, with a five-pointscale from ‘never’ to ‘very often’(Slater, 2003; Stephenson, Hoyle, Palmgreen, & Slater, 2003). The two items were summed up and divided by two.
2.4
Statistical analysis For each binary outcome, we used multilevel mixed effect logistic regressions to
determine the association between exposure and initiation within one year after baseline. To allow for nested data, school and class level were included in the models. Adjusted odds ratios (aOR) and 95% confidence interval (CI) are reported. Prevalence was weighted to census data to account for offset nonresponse bias and to increase representativeness of the sample. Weighting factors were age, gender, migration background, and school type.
Weighted prevalence of smoking behavior, sensation seeking, socioeconomic status, and exposure to advertisements are reported. In the final models, all potentially confounding variables were included to obtain estimates for the exposure-behavior association after keeping other influencing factors constant. Lifetime smoking behaviors (e-cigarette use, cigarette use, and hookah use) were included in the models as confounders (none = 0, yes = 1).
3 3.1
Results Attrition analysis We analyzed attrition between the baseline and follow-up sample by using Chi-
Squared tests and t-Tests. Overall, 1,411 (23.8%) participants dropped out. They were slightly older (p<.001), less likely to be attending college-preparatory secondary schools (‘gymnasiums’, p=.007), were more likely to have vaped e-cigarettes before (p<.001), to have smoked conventional cigarettes (p<.002), and to have used hookah before (p<.001). Adolescents who dropped out were more likely to have reported exposure to e-cigarette advertisements (p<.001) and scored higher on sensation seeking scale (p<.001).
3.2
Sample characteristics and smoking behavior Demographic data of the analysis samples dependent on the initiation status is
presented in Table 1. Overall, about 38% (N=2,197) of the adolescents recalled exposure to ecigarette advertisements at baseline, 13.6% (N=472) began to vape within one year from baseline assessment. About 10.8% (N=384) of the students experimented with conventional cigarettes, and 12.4% (N=406) used a hookah for the first time within the observation period.
***insert Table 1 here***
3.3
Recall of exposure to e-cigarette advertisements and subsequent use of e-
cigarettes, cigarettes, and hookah To determine whether the recall of exposure to e-cigarette advertising was related to subsequent use of e-cigarettes, cigarettes, and hookah use, multilevel mixed effect logistic regressions were performed. As shown in Table 2, exposure to e-cigarette marketing messages was significantly associated with subsequent e-cigarette use (aOR=1.37 (95% CI 1.04-1.81) p=.024). Relatedly, adolescents who had never used conventional cigarettes at baseline were more likely to report using them one year later at follow-up assessment if they had been exposed to advertisements for e-cigarettes (aOR=1.44 (95% CI 1.09-1.91) p=.010). The odds for hookah initiation were 82% higher for exposed compared to unexposed never hookah users (aOR= 1.82 (95% CI 1.37-2.42) p<.001). In more detail, findings of the multilevel mixed effect logistic regressions revealed that 20.5% of the adolescents who reported being highly exposed to e-cigarette advertisements (exposure scale point=4) used e-cigarettes within the observation period for the first time. In the group of adolescents that reported non-exposure (exposure scale point=1), 11.1% of the adolescents reported initial use of e-cigarettes. Predicted frequencies for initial use of conventional cigarettes were 19.8% for highly exposed adolescents and 9.1% for the non-exposed group, respectively. Predicted frequencies for the initial use of hookah were 28.5% (highly exposed) and 9.2% (non-exposed). In addition, e-cigarette, cigarette and hookah use initiation were more frequently observed among those students who have friends that vape or smoke. Initial use of ecigarettes at follow-up was associated with cigarette and hookah use at baseline and initial use of cigarettes was associated with e-cigarette and hookah use. Experimentation with hookahs within the observation period was only linked to e-cigarette use at baseline, but not to cigarette use.
Sensation seeking, age, migrant background, and school type were also independent predictors of all three outcomes. Students with a migrant background were more likely to have used hookahs for the first time while students without migrant background were more likely to experiment with e-cigarettes and conventional cigarettes.
***insert Table 2 here*** 4
Discussion This longitudinal study provides information about the role of e-cigarette advertising
in e-cigarette, cigarette, and hookah initiation in a cohort of 4,529 German adolescents that were observed over a 12 months period. Among never e-cigarette users at baseline, 13.6 % of adolescents reported e-cigarette use at follow-up which is similar to the a recently published initiation rate of U.S students who attended grades 6 to 10 (Loukas, et al., 2019). Current data from German Federal Center of Health Education revealed that lifetime prevalence of ecigarette use among German adolescents has significantly increased from 2012 to 2018. The increase is primarily due to male adolescents’ use of e-cigarettes (Orth & Merkel, 2019), a trend that is also evident in the results of the present study. Overall, adolescents’ exposure to e-cigarette advertising was high. Our findings indicate that 37.1 % of adolescents who were 12.6 years old on average recalled exposure to e-cigarette marketing. Comparable estimates for exposure to e-cigarette advertising were found in the Eurobarometer survey (Filippidis, et al., 2017). There are two central findings from this study. First, an association between exposure to e-cigarette advertising at baseline and the experimental use of e-cigarettes during the observation period was still present after adjustment for numerous confounding variables (i.e., age, gender, sensation seeking, socioeconomic status, school type, migrant background, peer use, lifetime cigarette and hookah use). This result is in line with previous longitudinal studies on US cohorts (Agaku, et al., 2017; Camenga, et al., 2018; Loukas, et al., 2019).
The second central finding is related to the “spill-over” effect, i.e., if e-cigarette marketing is related to the experimentation with other tobacco products. There was also a significant independent association between baseline exposure to e-cigarette marketing and the initiation of conventional cigarettes and hookahs one year later. This implies that ecigarette advertisements could have a broader impact on adolescents’ health behavior than previously assumed. The finding is in contrast to a previous study examining a “spill-over” effect of e-cigarette advertising, which reported a null result (Villanti, et al., 2016). However, while the Villanti et al. study had a high internal validity due to an experimental design, the exposure measure was very different to our present analysis. Participants only had a brief laboratory exposure to e-cigarette marketing, making the results of the two studies hardly comparable. E-cigarette advertising contents have a striking similarity to conventional cigarette advertisements. For example, one advertisement depicts attractive people while holding a ciga-like product. There is evidence that the depiction of people using an e-cigarette in advertisements created more interest in trying e-cigarettes among adult smokers than ads with other images (Pepper, Emery, Ribisl, Southwell, & Brewer, 2014). Hence, e-cigarette advertisements with people using a cig-a-like product could be seen as the promotion of smoking behavior in general, creating interest for all kinds of smoking products. However, more longitudinal research is needed to examine the specificity of the relationship between ecigarette marketing and initial use of different kinds of smoking products in the group of nonusers. Another possible explanation for the found “spill-over” effect could be based on the gateway hypothesis that assumes a transition from one product to another (Kandel, 1975). There is empirical evidence that the use of e-cigarettes can motivate adolescents to start smoking conventional cigarettes (Glantz & Bareham, 2018; Morgenstern, Nies, Goecke, & Hanewinkel, 2018) and that the use of nicotine-containing liquids in e-cigarettes could be a
gateway to the use of conventional cigarettes (Etter, 2018; Schneider & Diehl, 2016). Thus, it is thinkable that exposure to e-cigarette advertisements and smoking behavior is related chronologically. Adolescents that were exposed to e-cigarette advertisements could be at higher risk to start using e-cigarettes. The ones who had used e-cigarettes could be in turn at higher risk to start smoking traditional tobacco cigarettes. More research is needed to address this potential chronological sequence, which considers the exposure to advertisements and the use of nicotine-containing liquids in e-cigarettes prior to the initial use of conventional cigarettes. Despite the significant findings, the current manuscript may even underestimate the magnitude of the effects of e-cigarette advertising. Attrition analyses indicated that higher risk adolescents (e.g., those more likely to have used e-cigarettes, conventional cigarettes, and hookah; more likely to have been exposed to advertisements; more likely to be willing to take a risk) were more likely to drop out of the study, and e-cigarette advertising would probably be more likely to affect these higher-risk adolescents.
4.1
Limitations For a proper interpretation of the results, some limitations have to be considered. First,
selected images of e-cigarette advertisement only covered a small variety of advertisements that ran in 2016, meaning that the implemented method did not use a representative sample of all e-cigarette marketing actions shown in Germany. It can therefore not be seen as a measure of overall exposure and does not allow for a precise estimation of the total amount of ecigarette ad exposure of adolescents in Germany. In the present study, only two sources of advertising (television and online media) were examined cumulatively. In addition, selected advertisement sources were banned in Germany later in 2016. Future research is needed that examines the marketing channels individually rather than cumulatively (Loukas, et al., 2019).
The use of tobacco products in association with advertisements could also be underestimated because of hidden advertisements in other channels, for instance cinemas and movies (Grana, Glantz, & Ling, 2011; Morgenstern, et al., 2013). Selected stimulus material included sources that have been prohibited since May 2016 (TV and internet ads), but were accessible for students before survey implementation. The models accounted for several important confounders but there may have been other confounding variables that were not integrated in the models; for instance, parental tobacco use, susceptibility to e-cigarettes or other tobacco advertising. Accounting for conventional cigarette advertising could strengthen the results because specific content-related effects could have been examined. Further, all variables were assessed by self-reports, and can only be regarded as a proxy of the actual behavior.
4.2
Conclusions This study adds to a limited number of longitudinal studies that examined the role of
e-cigarette advertisement in the later use of e-cigarettes. It supports previous cross-sectional analyses linking e-cigarette advertisement exposure with the use of e-cigarette products and other tobacco products. By using longitudinal data from German adolescents, this study fills the gap of missing evidence for a sample outside the U.S.. The reported “spill-over” effect raises serious concerns, but future research is needed to address a potential content-related effect of e-cigarette advertisements. Overall, the results of the present study support public health efforts to reduce exposure to marketing, including a comprehensive ban of all forms of tobacco and e-cigarette advertisements to protect youth from adverse health effects.
Conflict of interests: Julia Hansen, Reiner Hanewinkel, Matthis Morgenstern declare they have no conflict of interests.
Funding Source: The study is supported by DAK-Gesundheit (German Health Insurance Company). The funder had no role in the design and conduct of the study; no role in collection, management, analysis, and interpretation of the data; no role in preparation, review, or approval of the manuscript; and in the decision to submit the manuscript for publication.
Financial Disclosure: Julia Hansen, Reiner Hanewinkel, Matthis Morgenstern have nothing to disclose.
Acknowledgements The authors would like to thank Toska Jakob, Corinna Gutjahr, and Luise Rehermann for their support in data collection, Dr. Emeka W. Dumbili for his constructive criticism of the manuscript, and the DAK-Gesundheit for funding of the study, and all schools that have participated in the study.
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Figure 1. Flowchart
Table 1. Characteristics of the analysis samples by follow-up initiation status.
Characteristics of the analysis samples e-cigarette non-users at followup
e-cigarette initiators at followup
cigarette non-users at followup
cigarette initiators at followup
hookah non-users at followup
hookah initiators at followup
Total N (%)
3,463 (86.4)
472 (13.6)
3,560 (89.2)
384 (10.8 )
3.461 (87.6)
406 (12.4)
Demographics
N (%)/ M (SD)
N (%)/ M (SD)
N (%)/ M (SD)
N (%)/ M (SD)
N (%)/ M (SD)
N (%)/ M (SD)
12.2 (1.51) (3,455)
13.0 (1.28) (471)
12.2 (1.49) (3,552)
12.9 (1.43) (384)
12.2 (1.49) (3,453)
12.9 (1.34) (404)
Gender (female)
1,772 (51.2)
188 (39.8)
1,752 (49.3)
185 (48.2)
1,755 (50.8)
178 (44.0)
Migration (yes)
543 (15.7)
77 (16.3)
609 (17.1)
61 (15.9)
492 (14.2)
85 (21.0)
Socioeconomic status (high)a
980 (28.2)
136 (27.3)
1,007 (28.1)
113 (27.8)
968 (27.7)
123 (28.6)
Type of school (gymnasiums)
2,001 (57.8)
187 (39.6)
2,041 (57.3)
140 (36.5)
2,000 (57.8)
158 (38.9)
Sensation seeking (high) a
706 (21.2)
223 (46.0)
743 (21.9)
163 (41.7)
702 (20.8)
177 (43.8)
Peer use b (yes)
944 (32.4)
319 (71.4)
1.043 (35.2)
232 (64.4)
947 (32.1)
266 (69.2)
Exposure to ecigarette advertising (yes)
1,065 (32.1)
216 (51.1)
1,132 (33.3)
163 (42.9)
1,055 (31.5)
192 (45.3)
Age
a
tertile split least one friend uses e-cigarettes/cigarettes/hookah
b At
Table 2. Associations of the recall of exposure to e-cigarette advertisements and initiation of e-cigarettes, cigarettes, and hookah use within 12-months from baseline.
Initiation of e-cigarette use N=(3,839) aOR (95% CI)
cigarette use N=(3,848) aOR (95% CI)
hookah use (N=3,771) aOR (95% CI)
Recall of exposure to ecigarette advertisements (Range 1 – 4)
1.37 (1.04-1.81) p=.024
1.44 (1.09-1.91) p=.010
1.82 (1.37-2.42) p<.001
Age
1.25 (1.14-1.38) p<.001
1.28 (1.16-1.41) p<.001
1.28 (1.15-1.42) p<.001
Gender (male=0)
.71 (.56-.90) p=.004
1.29 (1.01-1.65) p=.039
.91 (.70-1.16) p=.441
Migration background (none=0)
.70 (.50-.98) p=.040
.50 (.35-.73) p<.001
1.49 (1.07-2.07) p=.017
Socioeconomic status (Range 1 = low to 10 = high)
1.03 (.95-1.12) p=.495
1.00 (.92-1.10) p=.927
1.06 (.97-1.16) p=.213
School type (other types than gymnasiums=0)
.51 (.35-.74) p<.001
.46 (.32-.67) p<.001
.62 (.42-.93) p=.021
Sensation Seeking
1.75 (1.55-1.98) p<.001
1.65 (1.45-1.87) p<.001
1.81 (1.59-2.06) p<.001
Peer Usea (none=0)
2.96 (2.28-3.85) p<.001
1.84 (1.39-2.42) p<.001
2.45 (1.85-3.24) p<.001
--
1.79 (1.16-2.75) p=.008
4.68 (3.04-7.21) p<.001
Lifetime cigarette use (none=0)
1.56 (1.08-2.27) p=.019
--
1.48 (.99-2.21) p=.056
Lifetime hookah use (none=0)
3.87 (2.64-5.68) p<.001
2.08 (1.39-3.11) p<.001
--
Lifetime e-cigarette use (none=0)
aOR= Adjusted Odds Ratio, CI =Confidence Interval a At least one friend uses e-cigarettes/cigarettes/hookah
Highlights
“Electronic cigarette advertising and teen smoking initiation”
Study examined the impact of e-cig marketing on smoking behavior. Exposure to e-cig advertisements increased the likelihood of future e-cigarette use. Exposure to e-cig marketing was associated with the use of conventional cigarettes.
We confirm that this work is original and has not been published elsewhere, nor is it currently under consideration for publication elsewhere. We have no conflicts of interest to disclose. The study is supported by DAK-Gesundheit (German Health Insurance Company). The funder had no role in the design and conduct of the study; no role in collection, management, analysis, and interpretation of the data; no role in preparation, review, or approval of the manuscript; and in the decision to submit the manuscript for publication. Dr Hansen drafted the manuscript, designed the data collection instruments, coordinated data collection, and carried out the initial analyses. Dr Hansen is taking final responsibility for the paper. Drs Hanewinkel and Morgenstern conceptualized and designed the study, and supervised data collection instruments, and data collection, and revised and critically reviewed the manuscript for important intellectual content. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.
Statement 1: Role of Funding Sources The study is supported by DAK-Gesundheit (German Health Insurance Company). The funder had no role in the design and conduct of the study; no role in collection, management, analysis, and interpretation of the data; no role in preparation, review, or approval of the manuscript; and in the decision to submit the manuscript for publication. Statement 2: Contributors Dr Hansen drafted the manuscript, designed the data collection instruments, coordinated data collection, and carried out the initial analyses. Dr Hansen is taking final responsibility for the paper. Drs Hanewinkel and Morgenstern conceptualized and designed the study, and supervised data collection instruments, and data collection, and revised and critically reviewed the manuscript for important intellectual content. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work. Statement 3: Conflict of Interest All authors declare they have no conflict of interests. Financial Disclosure: Julia Hansen, Reiner Hanewinkel, Matthis Morgenstern have nothing to disclose.
Statement 4: Acknowledgements The authors would like to thank Toska Jakob, Corinna Gutjahr, and Luise Rehermann for their support in data collection, Dr. Emeka W. Dumbili for his constructive criticism of the manuscript, and the DAK-Gesundheit for funding of the study, and all schools that have participated in the study.