Krysten W Bold1, Grace Kong2, Meghan Morean2, Ralitza Gueorguieva3, Deepa R Camenga4, Patricia Simon2, Danielle R Davis2, Asti Jackson2, Suchitra Krishnan-Sarin2. 1. Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States. Electronic address: krysten.bold@yale.edu. 2. Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States. 3. Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States; Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States. 4. Department of Emergency Medicine, Yale University School of Medicine, New Haven, CT, United States.
Abstract
BACKGROUND: Adolescent e-cigarette use has increased recently; however, little is known about trends in use of specific devices by youth. This study aims to 1) compare rates of e-cigarette device use over time, 2) examine changes in frequency of device use, and 3) identify predictors of device use. METHODS: Cross-sectional surveys were distributed school-wide across 4 diverse Connecticut high-schools in 2017, 2018, 2019 and assessed current (i.e., past-30-day) use of various e-cigarette devices: disposables/cig-a-likes, vape pens, mods, JUULs, and other rechargeable pod devices (added in 2018 and 2019). Analyses compared rates of device use and frequency (i.e., number of days used in past 30) over time. Multivariable logistic regression models examined demographic and tobacco use characteristics (e.g., age first trying e-cigarettes) as predictors of current use of each device type in 2019. RESULTS: From 2017-2019, rates of using JUUL, disposables/cig-a-likes, and vape pens increased significantly, while use of mods and other pod devices decreased (ps<.001). Over 59 % of youth reported using more than one e-cigarette device in 2019. Over time, more youth were frequent users (using ≥20 out of 30 days) of disposable/cig-a-likes (32 % to >46 %) and JUUL (28 % to >35 %) devices. In multivariable models, first trying e-cigarettes at a younger age was associated with current use of disposable/cig-a-like, vape pens, mods, and other rechargeable pod devices. CONCLUSIONS: From 2017-2019, JUUL, disposable/cig-a-like, and vape pens increased in popularity and were used frequently. Tobacco regulations designed to reduce youth use should consider various device types.
BACKGROUND: Adolescent e-cigarette use has increased recently; however, little is known about trends in use of specific devices by youth. This study aims to 1) compare rates of e-cigarette device use over time, 2) examine changes in frequency of device use, and 3) identify predictors of device use. METHODS: Cross-sectional surveys were distributed school-wide across 4 diverse Connecticut high-schools in 2017, 2018, 2019 and assessed current (i.e., past-30-day) use of various e-cigarette devices: disposables/cig-a-likes, vape pens, mods, JUULs, and other rechargeable pod devices (added in 2018 and 2019). Analyses compared rates of device use and frequency (i.e., number of days used in past 30) over time. Multivariable logistic regression models examined demographic and tobacco use characteristics (e.g., age first trying e-cigarettes) as predictors of current use of each device type in 2019. RESULTS: From 2017-2019, rates of using JUUL, disposables/cig-a-likes, and vape pens increased significantly, while use of mods and other pod devices decreased (ps<.001). Over 59 % of youth reported using more than one e-cigarette device in 2019. Over time, more youth were frequent users (using ≥20 out of 30 days) of disposable/cig-a-likes (32 % to >46 %) and JUUL (28 % to >35 %) devices. In multivariable models, first trying e-cigarettes at a younger age was associated with current use of disposable/cig-a-like, vape pens, mods, and other rechargeable pod devices. CONCLUSIONS: From 2017-2019, JUUL, disposable/cig-a-like, and vape pens increased in popularity and were used frequently. Tobacco regulations designed to reduce youth use should consider various device types.
Authors: Jeffrey G Willett; Morgane Bennett; Elizabeth C Hair; Haijuan Xiao; Marisa S Greenberg; Emily Harvey; Jennifer Cantrell; Donna Vallone Journal: Tob Control Date: 2018-04-18 Impact factor: 7.552
Authors: Paul T Harrell; Syeda Mahrukh Hussnain Naqvi; Andrew D Plunk; Ming Ji; Silvia S Martins Journal: Am J Drug Alcohol Abuse Date: 2016-09-26 Impact factor: 3.829
Authors: Andrea S Gentzke; MeLisa Creamer; Karen A Cullen; Bridget K Ambrose; Gordon Willis; Ahmed Jamal; Brian A King Journal: MMWR Morb Mortal Wkly Rep Date: 2019-02-15 Impact factor: 17.586
Authors: Grace Kong; Benjamin W Chaffee; Ran Wu; Suchitra Krishnan-Sarin; Feifei Liu; Adam M Leventhal; Rob McConnell; Jessica Barrington-Trimis Journal: Drug Alcohol Depend Date: 2022-01-11 Impact factor: 4.852