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 - Funding Information:
This manuscript is supported with federal funds from the National Institute on Drug Abuse , National Institutes of Health , and the and the Center for Tobacco Products , Food and Drug Administration , Department of Health and Human Services, under contract to Westat (Contract # HHSN271201100027C ).
Funding Information:
This manuscript is supported with federal funds from the National Institute on Drug Abuse, National Institutes of Health, and the and the Center for Tobacco Products, Food and Drug Administration, Department of Health and Human Services, under contract to Westat (Contract # HHSN271201100027C).
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 -