TY - JOUR
T1 - Associations of risk factors of e-cigarette and cigarette use and susceptibility to use among baseline PATH study youth participants (2013–2014)
AU - Sawdey, Michael D.
AU - Day, Hannah R.
AU - Coleman, Blair
AU - Gardner, Lisa D.
AU - Johnson, Sarah E.
AU - Limpert, Jean
AU - Hammad, Hoda T.
AU - Goniewicz, Maciej L.
AU - Abrams, David B.
AU - Stanton, Cassandra A.
AU - Pearson, Jennifer L.
AU - Kaufman, Annette R.
AU - Kimmel, Heather L.
AU - Delnevo, Cristine D.
AU - Compton, Wilson M.
AU - Bansal-Travers, Maansi
AU - Niaura, Raymond S.
AU - Hyland, Andrew
AU - Ambrose, Bridget K.
N1 - Publisher Copyright:
© 2018
PY - 2019/4
Y1 - 2019/4
N2 - Introduction: Improved understanding of the distribution of traditional risk factors of cigarette smoking among youth who have ever used or are susceptible to e-cigarettes and cigarettes will inform future longitudinal studies examining transitions in use. Methods: Multiple logistic regression analysis was conducted using data from youth (ages 12–17 years) who had ever heard of e-cigarettes at baseline of the PATH Study (n = 12,460) to compare the distribution of risk factors for cigarette smoking among seven mutually exclusive groups based on ever cigarette/e-cigarette use and susceptibility status. Results: Compared to committed never users, youth susceptible to e-cigarettes, cigarettes, or both had increasing odds of risk factors for cigarette smoking, with those susceptible to both products at highest risk, followed by cigarettes and e-cigarettes. Compared to e-cigarette only users, dual users had higher odds of nearly all risk factors (aOR range = 1.6–6.8) and cigarette only smokers had higher odds of other (non-e-cigarette) tobacco use (aOR range = 1.5–2.3), marijuana use (aOR = 1.9, 95%CI = 1.4–2.5), a high GAIN substance use score (aOR = 1.9, 95%CI = 1.1–3.4), low academic achievement (aOR range = 1.6–3.4), and exposure to smoking (aOR range = 1.8–2.1). No differences were observed for externalizing factors (depression, anxiety, etc.), sensation seeking, or household use of non-cigarette tobacco. Conclusions: Among ever cigarette and e-cigarette users, dual users had higher odds of reporting traditional risk factors for smoking, followed by single product cigarette smokers and e-cigarette users. Understanding how e-cigarette and cigarette users differ may inform youth tobacco use prevention efforts and advise future studies assessing probability of progression of cigarette and e-cigarette use.
AB - Introduction: Improved understanding of the distribution of traditional risk factors of cigarette smoking among youth who have ever used or are susceptible to e-cigarettes and cigarettes will inform future longitudinal studies examining transitions in use. Methods: Multiple logistic regression analysis was conducted using data from youth (ages 12–17 years) who had ever heard of e-cigarettes at baseline of the PATH Study (n = 12,460) to compare the distribution of risk factors for cigarette smoking among seven mutually exclusive groups based on ever cigarette/e-cigarette use and susceptibility status. Results: Compared to committed never users, youth susceptible to e-cigarettes, cigarettes, or both had increasing odds of risk factors for cigarette smoking, with those susceptible to both products at highest risk, followed by cigarettes and e-cigarettes. Compared to e-cigarette only users, dual users had higher odds of nearly all risk factors (aOR range = 1.6–6.8) and cigarette only smokers had higher odds of other (non-e-cigarette) tobacco use (aOR range = 1.5–2.3), marijuana use (aOR = 1.9, 95%CI = 1.4–2.5), a high GAIN substance use score (aOR = 1.9, 95%CI = 1.1–3.4), low academic achievement (aOR range = 1.6–3.4), and exposure to smoking (aOR range = 1.8–2.1). No differences were observed for externalizing factors (depression, anxiety, etc.), sensation seeking, or household use of non-cigarette tobacco. Conclusions: Among ever cigarette and e-cigarette users, dual users had higher odds of reporting traditional risk factors for smoking, followed by single product cigarette smokers and e-cigarette users. Understanding how e-cigarette and cigarette users differ may inform youth tobacco use prevention efforts and advise future studies assessing probability of progression of cigarette and e-cigarette use.
KW - Cigarettes
KW - E-cigarettes
KW - Risk factors of tobacco use
KW - Susceptibility
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U2 - 10.1016/j.addbeh.2018.11.027
DO - 10.1016/j.addbeh.2018.11.027
M3 - Article
C2 - 30473246
AN - SCOPUS:85057063278
SN - 0306-4603
VL - 91
SP - 51
EP - 60
JO - Addictive Behaviors
JF - Addictive Behaviors
ER -