Introduction: Understanding exposures and potential health effects of e-cigarettes is complex. Users' puffing behavior, or topography, affects function of e-cigarette devices (eg, coil temperature) and composition of their emissions. Users with different topographies are likely exposed to different amounts of any harmful or potentially harmful constituents (HPHCs). In this study, we compare e-cigarette topographies of established cigarette smokers and nonestablished cigarette smokers. Methods: Data measuring e-cigarette topography were collected using a wireless hand-held monitoring device in users' everyday lives over 1 week. Young adult (aged 18-25) participants (N = 20) used disposable e-cigarettes with the monitor as they normally would and responded to online surveys. Topography characteristics of established versus nonestablished cigarette smokers were compared. Results: On average, established cigarette smokers in the sample had larger first puff volume (130.9 mL vs. 56.0 mL, p < .05) and larger puff volume per session (1509.3 mL vs. 651.7 mL, p < .05) compared with nonestablished smokers. At marginal significance, they had longer sessions (566.3 s vs. 279.7 s, p = .06) and used e-cigarettes more sessions per day (5.3 s vs. 3.5 s, p = .14). Established cigarette smokers also used e-cigarettes for longer puff durations (3.3 s vs. 1.8 s, p < .01) and had larger puff volume (110.3 mL vs. 54.7 mL, p < .05) compared with nonestablished smokers. At marginal significance, they had longer puff interval (38.1 s vs. 21.7 s, p = .05). Conclusions: Our results demonstrate that topography characteristics differ by level of established cigarette smoking. This suggests that exposure to constituents of e-cigarettes depends on user characteristics and that specific topography parameters may be needed for different user populations when assessing e-cigarette health effects. Implications: A user's topography affects his or her exposure to HPHCs. As this study demonstrates, user characteristics, such as level of smoking, can influence topography. Thus, it is crucial to understand the topography profiles of different user types to assess the potential for population harm and to identify potentially vulnerable populations. This study only looked at topography of cigarette smokers using disposable e-cigarettes. Further research is needed to better understand potential variation in e-cigarette topography and resulting exposures to HPHCs among users of different e-cigarette devices and liquids.
Introduction: Understanding exposures and potential health effects of e-cigarettes is complex. Users' puffing behavior, or topography, affects function of e-cigarette devices (eg, coil temperature) and composition of their emissions. Users with different topographies are likely exposed to different amounts of any harmful or potentially harmful constituents (HPHCs). In this study, we compare e-cigarette topographies of established cigarette smokers and nonestablished cigarette smokers. Methods: Data measuring e-cigarette topography were collected using a wireless hand-held monitoring device in users' everyday lives over 1 week. Young adult (aged 18-25) participants (N = 20) used disposable e-cigarettes with the monitor as they normally would and responded to online surveys. Topography characteristics of established versus nonestablished cigarette smokers were compared. Results: On average, established cigarette smokers in the sample had larger first puff volume (130.9 mL vs. 56.0 mL, p < .05) and larger puff volume per session (1509.3 mL vs. 651.7 mL, p < .05) compared with nonestablished smokers. At marginal significance, they had longer sessions (566.3 s vs. 279.7 s, p = .06) and used e-cigarettes more sessions per day (5.3 s vs. 3.5 s, p = .14). Established cigarette smokers also used e-cigarettes for longer puff durations (3.3 s vs. 1.8 s, p < .01) and had larger puff volume (110.3 mL vs. 54.7 mL, p < .05) compared with nonestablished smokers. At marginal significance, they had longer puff interval (38.1 s vs. 21.7 s, p = .05). Conclusions: Our results demonstrate that topography characteristics differ by level of established cigarette smoking. This suggests that exposure to constituents of e-cigarettes depends on user characteristics and that specific topography parameters may be needed for different user populations when assessing e-cigarette health effects. Implications: A user's topography affects his or her exposure to HPHCs. As this study demonstrates, user characteristics, such as level of smoking, can influence topography. Thus, it is crucial to understand the topography profiles of different user types to assess the potential for population harm and to identify potentially vulnerable populations. This study only looked at topography of cigarette smokers using disposable e-cigarettes. Further research is needed to better understand potential variation in e-cigarette topography and resulting exposures to HPHCs among users of different e-cigarette devices and liquids.
Authors: Matthew J Grainge; Lion Shahab; David Hammond; Richard J O'Connor; Ann McNeill Journal: Drug Alcohol Depend Date: 2009-05 Impact factor: 4.492
Authors: Alexa A Lopez; Marzena M Hiler; Eric K Soule; Carolina P Ramôa; Nareg V Karaoghlanian; Thokozeni Lipato; Alison B Breland; Alan L Shihadeh; Thomas Eissenberg Journal: Nicotine Tob Res Date: 2015-09-16 Impact factor: 4.244
Authors: Carolina P Ramôa; Marzena M Hiler; Tory R Spindle; Alexa A Lopez; Nareg Karaoghlanian; Thokozeni Lipato; Alison B Breland; Alan Shihadeh; Thomas Eissenberg Journal: Tob Control Date: 2015-08-31 Impact factor: 7.552
Authors: Tushar Singh; René A Arrazola; Catherine G Corey; Corinne G Husten; Linda J Neff; David M Homa; Brian A King Journal: MMWR Morb Mortal Wkly Rep Date: 2016-04-15 Impact factor: 17.586
Authors: Tory R Spindle; Marzena M Hiler; Alison B Breland; Nareg V Karaoghlanian; Alan L Shihadeh; Thomas Eissenberg Journal: Nicotine Tob Res Date: 2017-04-01 Impact factor: 4.244
Authors: Kelly R Smith; Faisal Hayat; Joel F Andrews; Marie E Migaud; Natalie R Gassman Journal: Chem Res Toxicol Date: 2019-08-02 Impact factor: 3.739
Authors: Shunsaku Goto; Robert M H Grange; Riccardo Pinciroli; Ivy A Rosales; Rebecca Li; Sophie L Boerboom; Katrina F Ostrom; Eizo Marutani; Hatus V Wanderley; Aranya Bagchi; Robert B Colvin; Lorenzo Berra; Olga Minaeva; Lee E Goldstein; Rajeev Malhotra; Warren M Zapol; Fumito Ichinose; Binglan Yu Journal: Arch Toxicol Date: 2022-10-04 Impact factor: 6.168
Authors: Evan Floyd; Toluwanimi Oni; Changjie Cai; Bilal Rehman; Jooyeon Hwang; Tyler Watson Journal: Int J Environ Res Public Health Date: 2022-06-29 Impact factor: 4.614
Authors: Afton Kechter; Kelsey A Simpson; Rachel Carmen Ceasar; Sara J Schiff; Naosuke Yamaguchi; Ricky N Bluthenthal; Sabrina L Smiley; Jessica L Barrington-Trimis Journal: Nicotine Tob Res Date: 2022-06-15 Impact factor: 5.825
Authors: Jessica Yingst; Jonathan Foulds; Susan Veldheer; Caroline O Cobb; Miao-Shan Yen; Shari Hrabovsky; Sophia I Allen; Christopher Bullen; Thomas Eissenberg Journal: Nicotine Tob Res Date: 2020-04-21 Impact factor: 4.244
Authors: Hanan Qasim; Zubair A Karim; Juan C Silva-Espinoza; Fadi T Khasawneh; José O Rivera; Cameron C Ellis; Stephanie L Bauer; Igor C Almeida; Fatima Z Alshbool Journal: J Am Heart Assoc Date: 2018-07-18 Impact factor: 5.501