Associations of risk factors of e-cigarette and cigarette use and susceptibility to use among baseline PATH study youth participants (2013-2014)

Michael D Sawdey, Hannah R Day, Blair Coleman, Lisa D Gardner, Sarah E Johnson, Jean Limpert, Hoda T Hammad, Maciej L Goniewicz, David B Abrams, Cassandra A Stanton, Jennifer L Pearson, Annette R Kaufman, Heather L Kimmel, Cristine D Delnevo, Wilson M Compton, Maansi Bansal-Travers, Raymond S Niaura, Andrew Hyland, Bridget K Ambrose, Michael D Sawdey, Hannah R Day, Blair Coleman, Lisa D Gardner, Sarah E Johnson, Jean Limpert, Hoda T Hammad, Maciej L Goniewicz, David B Abrams, Cassandra A Stanton, Jennifer L Pearson, Annette R Kaufman, Heather L Kimmel, Cristine D Delnevo, Wilson M Compton, Maansi Bansal-Travers, Raymond S Niaura, Andrew Hyland, Bridget K Ambrose

Abstract

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.

Keywords: Cigarettes; E-cigarettes; Risk factors of tobacco use; Susceptibility.

Published by Elsevier Ltd.

References

    1. Jamal A, Gentzke A, Hu S, et al. Tobacco use among middle and high school students-United States, 2011-2016. MMWR Morbidity and mortality weekly report. 2017;66(23):597 10.15585/mmwr.mm6623a1.
    1. Miech RA, Johnston LD, O’malley PM, Bachman JG, Schulenberg JE. Monitoring the future national survey results on drug use, 1975-2015: Volume I, secondary school students. 2016.
    1. Kozlowski LT, Warner KE. Adolescents and e-cigarettes: Objects of concern may appear larger than they are. Drug & Alcohol Dependence. 2017;174:209–214. 10.1016/j.drugalcdep.2017.01.001.
    1. Barrington-Trimis JL, Berhane K, Unger JB, et al. Psychosocial factors associated with adolescent electronic cigarette and cigarette use. Pediatrics. 2015;136(2):308–317. 10.1542/peds.2015-0639.
    1. Soneji S, Barrington-Trimis JL, Wills TA, et al. Association between initial use of e-cigarettes and subsequent cigarette smoking among adolescents and young adults: A systematic review and meta-analysis. JAMA Pediatrics. 2017;171(8):788–797. 10.1001/jamapediatrics.2017.1488.
    1. Wills TA, Knight R, Sargent JD, Gibbons FX, Pagano I, Williams RJ. Longitudinal study of e-cigarette use and onset of cigarette smoking among high school students in Hawaii. Tob Control. 2017;26(1):34–39. 10.1136/tobaccocontrol-2015-052705.
    1. Soneji SS, Sung H-Y, Primack BA, Pierce JP, Sargent JD. Quantifying population-level health benefits and harms of e-cigarette use in the United States. PLOS ONE. 2018;13(3):e0193328 10.1371/journal.pone.0193328.
    1. National Academies of Sciences, Engineering, and Medicine. Public health consequences of e-cigarettes. Washington, DC: The National Academies Press;2018. 978-0-309-46831-2 .
    1. Hampson SE, Andrews JA, Severson HH, Barckley M. Prospective predictors of novel tobacco and nicotine product use in emerging adulthood. Journal of Adolescent Health. 2015;57(2):186–191. 10.1016/j.jadohealth.2015.04.015.
    1. Kwon E, Seo D-C, Lin H-C, Chen Z. Predictors of youth e-cigarette use susceptibility in a U.S. Nationally representative sample. Addictive Behaviors. 2018;82:79–85. 10.1016/j.addbeh.2018.02.026.
    1. Wills TA, Knight R, Williams RJ, Pagano I, Sargent JD. Risk factors for exclusive e-cigarette use and dual e-cigarette use and tobacco use in adolescents. Pediatrics. 2015;135(1):E43–E51. 10.1542/peds.2014-0760.
    1. Leventhal AM, Strong DR, Sussman S, et al. Psychiatric comorbidity in adolescent electronic and conventional cigarette use. J Psychiatr Res. 2016;73(Supplement C):71–78. 10.1016/j.jpsychires.2015.11.008.
    1. Hyland A, Ambrose BK, Conway KP, et al. Design and methods of the Population Assessment of Tobacco and Health (PATH) study. Tob Control. 2017;26(4):371–378. 10.1136/tobaccocontrol-2016-052934.
    1. U.S. Department of Health and Human Services, National Institutes of Health. National Institute on Drug Abuse, United States Department of Health Human Services, Food Drug Administration, Center for Tobacco Products. Population Assessment of Tobacco and Health (PATH) study restricted-use files. 2017. 10.3886/ICPSR36231.v13.
    1. Pierce JP, Choi WS, Gilpin EA, Farkas AJ, Merritt RK. Validation of susceptibility as a predictor of which adolescents take up smoking in the United States. Health psychology : official journal of the Division of Health Psychology, American Psychological Association. 1996;15(5):355–361.
    1. Pierce JP, Sargent JD, White MM, et al. Receptivity to tobacco advertising and susceptibility to tobacco products. Pediatrics. 2017;139(6). 10.1542/peds.2016-3353.
    1. U.S. Department of Health and Human Services. E-cigarette use among youth and young adults. A report of the Surgeon general. 2016. .
    1. Dennis ML, Chan YF, Funk RR. Development and validation of the Gain Short Screener (GSS) for internalizing, externalizing and substance use disorders and crime/violence problems among adolescents and adults. The American Journal on Addictions 2006;15(s1).
    1. Hoyle RH, Stephenson MT, Palmgreen P, Lorch EP, Donohew RL. Reliability and validity of a brief measure of sensation seeking. Personality and Individual Differences. 2002;32(3):401–414. 10.1016/S0191-8869(01)00032-0.
    1. Conway KP, Green VR, Kasza KA, et al. Co-occurrence of tobacco product use, substance use, and mental health problems among youth: Findings from wave 1 (2013–2014) of the Population Assessment of Tobacco and Health (PATH) study. Addictive Behaviors. 2018;76:208–217. 10.1016/j.addbeh.2017.08.009.
    1. Neff LJ, Arrazola RA, Caraballo RS, et al. Frequency of tobacco use among middle and high school students - United States, 2014. Mmwr-Morbid Mortal W. 2015;64(38):1061–1065.
    1. U.S. Department of Health and Human Services. Preventing tobacco use among youth and young adults: A report of the Surgeon General. 2012. .
    1. Wong SL, Shields M, Leatherdale S, Malaison E, Hammond D. Assessment of validity of self-reported smoking status. Health reports. 2012;23(1):47–53.
    1. Brener ND, Billy JO, Grady WR. Assessment of factors affecting the validity of self-reported health-risk behavior among adolescents: Evidence from the scientific literature. The Journal of adolescent health : official publication of the Society for Adolescent Medicine. 2003;33(6):436–457.

Source: PubMed

Sponsors and Collaborators

Medical Conditions

Drug Interventions

3
Subscribe