| Literature DB >> 31582914 |
Samir Soneji1,2, Kristin E Knutzen1, Meghan Bridgid Moran3.
Abstract
INTRODUCTION: Engagement with online tobacco marketing among US adolescents increased from nearly 9% (2013-2014) to 21% (2014-2015). Such engagement increases the risk of tobacco use initiation. Despite the increase in the prevalence of and risks associated with engagement, the reasons why adolescents and young adults engage are not known.Entities:
Keywords: online tobacco marketing; tobacco ads; tobacco coupons
Year: 2019 PMID: 31582914 PMCID: PMC6751987 DOI: 10.18332/tid/99540
Source DB: PubMed Journal: Tob Induc Dis ISSN: 1617-9625 Impact factor: 2.600
Definitions of reasons for engagement with online tobacco marketing[1]
| Ads, exposure of ambiguous nature | Any response mentioning ads but not specifying nature of exposure | ‘It was an ad’ |
| Ad, incidental exposure | Respondent indicates they did not intend to watch the ad and/or it was forced upon them | ‘It was a pop-up ad that could not be exited that played during a video I was watching that was not related to tobacco’ |
| Ads, intentional exposure | Respondent indicates they watched the ad on purpose | ‘It popped up as an ad and looked interesting. So I watched the promotion then went to the website to check it out’ |
| Curiosity or general knowledge | Response indicating curiosity or seeking to know more, generally | ‘Boredom and curiosity’ |
| Product appeal | Respondent seeking more information about a specific product, looking to buy a product, or interested in a particular aspect of a product | ‘Wanted to buy a vape pen’ |
| Discounts, coupons, incentives, or contests | Respondent indicates seeking free and/or reduced product, or being otherwise incentivized to view and/or buy a product | ‘My mother and I are both smokers and it is a very expensive habit. I go to the websites for coupons and deals to try and save money for our lifestyle’ |
| Online content | Any response referencing online content, including unspecified video content, and social content such as Facebook, Instagram, Twitter, and YouTube | ‘I liked a Marlboro post and it pops up in my feed’ |
| Family or friends | Any response referencing family or friends, including seeking reduced products for family/friends or being exposed to online tobacco content by family/friends | ‘One of my friends promoted it on Twitter’ |
| School or research | Respondent specified engagement with online tobacco content was for school project or research purposes | ‘It was an ad I had to watch for a class’ |
| Adverse effects or anti-tobacco sentiment | Respondent specified engagement with online tobacco content was to understand negative health impact, or admitted bias against tobacco products | ‘There are always people who want to quit and don’t know how. I’m not addicted so I try to help’ |
| Particular brand | Respondents indicated a specific brand as their reason for engagement | ‘American Spirit was offering $2 packs of [sic] their cigarettes’ |
N=5244 US adolescents and young adults sampled in 2017.
Characteristics of sample
| Adolescent | 2619 | 49.9 |
| Young adult | 2625 | 50.1 |
| Female | 2794 | 53.3 |
| Male | 2373 | 45.3 |
| Genderqueer, gender non-conforming, or different identity | 40 | 0.8 |
| Trans male/trans man | 33 | 0.6 |
| Trans female/trans woman | 4 | 0.1 |
| Non-Hispanic white | 3056 | 59.4 |
| Hispanic | 1006 | 19.6 |
| Non-Hispanic black | 564 | 11.0 |
| Non-Hispanic Asian or Pacific Islander | 420 | 8.2 |
| Non-Hispanic American Indian or Alaskan Native | 96 | 1.9 |
| Never tobacco user, not susceptible | 1318 | 25.1 |
| Never tobacco user, susceptible | 1595 | 30.4 |
| Ever tobacco user | 1266 | 24.1 |
| Past 30-day tobacco user | 1065 | 20.3 |
Proportion of respondents do not sum to 100% because of rounding.
Prevalence (%) of any engagement with online tobacco marketing within past six months and specific reasons for engagement by age group[1]
| 12.0 | 28.3 | <0.01 | |
| Ads (Incidental exposure) | 2.6 | 5.0 | <0.01 |
| Curiosity or general knowledge | 2.2 | 5.5 | <0.01 |
| Online content | 1.7 | 3.0 | <0.01 |
| Discounts, coupons, incentives, or contests | 1.3 | 4.5 | <0.01 |
| Product appeal | 1.1 | 3.9 | <0.01 |
| Adverse effects or anti-tobacco sentiment | 0.8 | 1.5 | <0.01 |
| School or research | 0.4 | 0.9 | 0.01 |
| Family or friends | 0.4 | 1.4 | <0.01 |
| Particular brand | 0.4 | 1.6 | <0.01 |
| Ads (Intentional exposure) | 0.2 | 0.4 | 0.09 |
| Ads (Ambiguous exposure) | 0.8 | 1.7 | <0.01 |
N=5244 US adolescents and young adults sampled in 2017.
Sum of specific reasons for engagement do not equal the prevalence of any engagement because respondents could indicate multiple reasons.
Prevalence (%) of reasons for engagement with online tobacco marketing by tobacco use status[1]
| 20.1 | 3.6 | 15.3 | 20.7 | 47.0 | <0.01 | ||
| 1 & 2; 1 & 3, 1 & 4; 2 & 3, 2 & 4; 3 & 4 | |||||||
| Curiosity or general knowledge | 3.9 | 0.5 | 3.1 | 4.7 | 8.2 | <0.01 | 1 & 2; 1 & 3, 1 & 4; 2 & 4; 3 & 4 |
| Ads (Incidental exposure) | 3.8 | 1.2 | 4.5 | 5.8 | 3.8 | <0.01 | 1 & 2; 1 & 3, 1 & 4 |
| Discounts, coupons, incentives, or contests | 2.9 | 0.1 | 0.7 | 1.7 | 11.1 | <0.01 | 1 & 2; 1 & 3, 1 & 4 |
| Product appeal | 2.5 | 0.1 | 0.6 | 2.1 | 8.9 | <0.01 | 1 & 3, 1 & 4; 2 & 4; 3 & 4 |
| Online content | 2.3 | 0.4 | 2.3 | 3.7 | 3.2 | <0.01 | 1 & 2; 1 & 3, 1 & 4 |
| Adverse effects or anti-tobacco sentiment | 1.2 | 0.2 | 1.8 | 1.4 | 1.1 | <0.01 | 1 & 2; 1 & 3 |
| Ads (Ambiguous exposure) | 1.2 | 0.4 | 1.4 | 1.0 | 2.2 | <0.01 | 1 & 4 |
| Particular brand | 1.0 | 0.2 | 0.3 | 0.6 | 3.5 | <0.01 | 1 & 2; 1 & 3, 1 & 4 |
| Family or friends | 0.9 | 0.1 | 1.0 | 1.2 | 1.5 | <0.01 | 1 & 3; 1 & 4 |
| School or research | 0.6 | 0.2 | 0.8 | 0.7 | 0.8 | 0.17 | —[ |
| Ads (Intentional exposure) | 0.3 | 0.0 | 0.2 | 0.6 | 0.6 | 0.02 | —[ |
N=5244 US adolescents and young adults sampled in 2017.
Sum of specific reasons for engagement do not equal the prevalence of any engagement because respondents could indicate multiple reasons.
Lack of significantly different pairs possible, despite significance of ANOVA, because the comparison between specific pairs of groups used t-tests adjusted for multiple comparisons while the ANOVA assesses difference among group means.
Logistic regression of any engagement with online tobacco marketing within the past six months and specific reasons of engagement[1]
| 1.98 (1.69–2.33) | 1.74 (1.27–2.38) | 1.79 (1.29–2.48) | 2.06 (1.36–3.13) | 1.91 (1.23–2.97) | |
| Female | 0.75 (0.65–0.87) | 0.86 (0.64–1.15) | 0.89 (0.67–1.19) | 1.15 (0.82–1.63) | 0.60 (0.42–0.88) |
| Other[ | 0.74 (0.39–1.38) | 1.39 (0.54–3.55) | 0.92 (0.28–3.02) | 0.57 (0.08–4.32) | 0.41 (0.05–3.07) |
| Non-Hispanic black | 1.89 (1.50–2.38) | 1.14 (0.70–1.84) | 2.24 (1.51–3.32) | 0.42 (0.22–0.82) | 1.37 (0.79–2.37) |
| Hispanic | 1.43 (1.18–1.72) | 1.35 (0.94–1.94) | 1.32 (0.92–1.90) | 0.42 (0.26–0.70) | 1.19 (0.76–1.88) |
| Non-Hispanic Asian or Pacific Islander | 1.81 (1.39–2.37) | 1.98 (1.27–3.10) | 1.65 (1.00–2.72) | 0.62 (0.29–1.32) | 1.30 (0.65–2.62) |
| Non-Hispanic American Indian or Alaskan Native | 1.64 (0.98–2.76) | 2.45 (1.10–5.47) | 0.91 (0.28–2.96) | 0.44 (0.10–1.86) | 2.56 (1.03–6.38) |
| Susceptive never tobacco user | 4.63 (3.35–6.38) | 3.68 (2.12–6.37) | 6.81 (2.91–15.95) | 9.52 (1.23–73.81) | 8.05 (1.03–62.98) |
| Ever tobacco user, not past 30-day | 5.86 (4.24–8.10) | 4.22 (2.42–7.35) | 9.40 (4.02–21.97) | 19.28 (2.58–143.94) | 22.78 (3.07–168.74) |
| Past 30-day tobacco user | 19.27 (14.02–26.50) | 2.55 (1.40–4.64) | 16.09 (6.95–37.22) | 136.94 (19.01–986.28) | 97.67 (13.53–704.87) |
N=5244 US adolescents and young adults sampled in 2017.
Genderqueer, gender non-conforming, different identity, trans male/trans man, or trans female/trans woman.
AOR: adjusted odds ratio, CI: confidence interval.