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Exposure to e-cigarette advertisements and non-advertising content in relation to use behaviors and perceptions among US and Israeli adults

INTRODUCTION: As e-cigarette marketing strategies diversify, it is important to examine exposure to and impact of e-cigarette advertisements and non-advertising content (e.g. on social media) via multiple media channels among adults in different regulatory contexts. METHODS: Using 2021 cross-section...

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Detalles Bibliográficos
Autores principales: Duan, Zongshuan, Abroms, Lorien C., Cui, Yuxian, Wang, Yan, LoParco, Cassidy R., Levine, Hagai, Bar-Zeev, Yael, Khayat, Amal, Berg, Carla J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: European Publishing on behalf of the European Network for Smoking and Tobacco Prevention (ENSP) 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10685321/
https://www.ncbi.nlm.nih.gov/pubmed/38033881
http://dx.doi.org/10.18332/tpc/173558
Descripción
Sumario:INTRODUCTION: As e-cigarette marketing strategies diversify, it is important to examine exposure to and impact of e-cigarette advertisements and non-advertising content (e.g. on social media) via multiple media channels among adults in different regulatory contexts. METHODS: Using 2021 cross-sectional data among 2222 adults in the US (n=1128) and Israel (n=1094), multivariable regression examined past-month e-cigarette advertisement and non-advertising content exposure in relation to past-month e-cigarette use (logistic regression), as well as use intentions and risk perceptions (linear regressions), controlling for sociodemographics and tobacco use. RESULTS: Overall, 20.3% reported past-month e-cigarette use (15.5% US, 25.2% Israel), 46.1% any advertisement exposure (28.7% digital media, 25.2% traditional media, 16.8% retail settings), and 34.1% any non-advertising exposure (19.4% social media, 13.6% websites, 12.3% movie/television/theater, 5.8% radio/podcasts). Exposure to digital media advertisements (AOR=1.95; 95% CI: 1.42–2.66), traditional media advertisements (AOR=2.00; 95% CI=1.49–2.68), and social media non-advertising (AOR=1.72; 95% CI: 1.25–2.36) correlated with e-cigarette use. Exposure to traditional media advertisements (β=0.23; 95% CI: 0.08–0.38) and social media non-advertising (β=0.26; 95% CI: 0.09–0.43) correlated with use intentions. Exposure to digital media advertisements (β= -0.32; 95% CI: -0.57 – -0.08), retail setting advertisements (β= -0.30; 95% CI: -0.58 – -0.03), and radio/podcast non-advertising (β= -0.44; 95% CI: -0.84 – -0.03) correlated with lower perceived addictiveness. Radio/podcast non-advertising exposure (β= -0.50; 95% CI: -0.84 – -0.16) correlated with lower perceived harm. However, retail setting advertisement exposure was associated with e-cigarette non-use (AOR=0.61; 95% CI: 0.42–0.87), and traditional media advertisement (β=0.38; 95% CI: 0.15–0.61) and social media non-advertising exposure (β=0.40; 95% CI: 0.14–0.66) correlated with greater perceived addictiveness. CONCLUSIONS: E-cigarette-related promotional content exposure across media platforms impacts perceptions and use, thus warranting regulation.