Andy S L Tan1, Chul-Joo Lee2, Cabral A Bigman3. 1. Dana-Farber Cancer Institute, Population Sciences Division, Center for Community Based Research, Boston, MA, USA; Harvard TH Chan School of Public Health, Department of Social and Behavioral Sciences, Boston, MA, USA. Electronic address: andy_tan@dfci.harvard.edu. 2. Seoul National University, Department of Communication, Seoul, South Korea. 3. University of Illinois at Urbana-Champaign, Department of Communication, Urbana, IL, USA.
Abstract
OBJECTIVE: We assessed public support for six e-cigarette regulations and examined whether self-reported exposure to e-cigarette information and contradictory e-cigarette information were associated with support. METHOD: We conducted an online survey among a nationally representative sample of 527 U.S. adults in July 2014. Weighted, fully adjusted multinomial logistic regression models predicted support for banning e-cigarettes in smoke-free areas, prohibiting e-cigarette sales to youth, requiring addiction warnings, banning flavors, requiring labeling nicotine and harmful ingredients, and banning youth-targeted marketing. RESULTS: Between 34% and 72% supported these six policies (disagreed 6-24%; no opinion 18-38%). We found higher support for policies to protect youth (prohibit sales to youth and youth-targeted marketing) and to require labeling e-cigarette constituents (nicotine and harmful ingredients). Banning the use of flavors in e-cigarettes was the least supported. Overall information exposure predicted lower relative risk of support for three policies (prohibit sales to youth, nicotine and harmful ingredient labeling, addiction warnings). In comparison, contradictory information exposure predicted lower relative risk of support for two policies (prohibit sales to youth, nicotine and harmful ingredient labeling). CONCLUSIONS: Exposure to overall and conflicting information about e-cigarettes in the public sphere is associated with reduced support for certain proposed e-cigarette policies. These findings are important for policymakers and tobacco control advocates involved in promulgation of e-cigarette policies. The results provide insights on which policies may meet some public resistance and therefore require efforts to first gain public support.
OBJECTIVE: We assessed public support for six e-cigarette regulations and examined whether self-reported exposure to e-cigarette information and contradictory e-cigarette information were associated with support. METHOD: We conducted an online survey among a nationally representative sample of 527 U.S. adults in July 2014. Weighted, fully adjusted multinomial logistic regression models predicted support for banning e-cigarettes in smoke-free areas, prohibiting e-cigarette sales to youth, requiring addiction warnings, banning flavors, requiring labeling nicotine and harmful ingredients, and banning youth-targeted marketing. RESULTS: Between 34% and 72% supported these six policies (disagreed 6-24%; no opinion 18-38%). We found higher support for policies to protect youth (prohibit sales to youth and youth-targeted marketing) and to require labeling e-cigarette constituents (nicotine and harmful ingredients). Banning the use of flavors in e-cigarettes was the least supported. Overall information exposure predicted lower relative risk of support for three policies (prohibit sales to youth, nicotine and harmful ingredient labeling, addiction warnings). In comparison, contradictory information exposure predicted lower relative risk of support for two policies (prohibit sales to youth, nicotine and harmful ingredient labeling). CONCLUSIONS: Exposure to overall and conflicting information about e-cigarettes in the public sphere is associated with reduced support for certain proposed e-cigarette policies. These findings are important for policymakers and tobacco control advocates involved in promulgation of e-cigarette policies. The results provide insights on which policies may meet some public resistance and therefore require efforts to first gain public support.
Authors: Lauren Collins; Allison M Glasser; Haneen Abudayyeh; Jennifer L Pearson; Andrea C Villanti Journal: Nicotine Tob Res Date: 2019-01-01 Impact factor: 4.244
Authors: Allison M Glasser; Lauren Collins; Jennifer L Pearson; Haneen Abudayyeh; Raymond S Niaura; David B Abrams; Andrea C Villanti Journal: Am J Prev Med Date: 2016-11-30 Impact factor: 5.043