Trajectories of switching from cigarette to E-Cigarettes amongst adult smokers in a NYC randomized controlled trial

Joint Event on 7^th International Conference on Advances in Skin, Wound Care and Tissue Science & 11^th International Conference on Epidemiology & Public HealthSurgery

September 25-26, 2019 Copenhagen, Denmark

Alexandra Guttentag, Tuo-Yen Tseng, Donna Shelley and Thomas Kirchner

NYU Global Public Health, USA
New York University School of Medicine, USA

Posters & Accepted Abstracts: J Tissue Sci Eng

Abstract :

Background: Electronic cigarettes may offer an intermediary step on the pathway to cessation for addicted, adult smokers.

Objective: Identify and describe common trajectories of smoking reduction after immediate introduction of e-cigarette device, using longitudinal data.

Methods: 99 adult smokers (>10 cigarettes per day) were assigned to either a placebo or nicotine-based e-cigarette device (NJOY King Bold) and instructed to use it to help them reduce their baseline smoking rate by 50%. Participants reported e-cigarette and cigarette usage daily, and 79 participants completed the 3-week end-of-intervention survey. A latent class analysis with a time-varying (longitudinal) outcome variable was run using the PROC TRAJ function in STATA.

Results: Four linear trajectory groups were identified among the participants based on reported CPD and study day (1-21). Classes were identified such that the smallest group included 18.9% of the total sample and the largest group included 33.5% of the total sample. Groups were designated with numbers 1-4; group 1 was the group with the highest “success” with the e-cigarette (largest negative slope in CPD over time with β=-0.07, and group 4 had the lowest success with the e-cigarette device (slightly positive slope of CPD, β=0.01). Based on preliminary results, those who were assigned to the placebo group were more likely to end up in group 1(RRRs for Groups 2-4: .16-.17, CI=.035-.77). Preliminary results show significant associations between class membership and intervention assignment.

Conclusions: The clustering of different groups may help health providers advise their patients on expectations for cessation and customization of switching/cessation plans. The presence or absence of nicotine may also play a role in how smokers use the e-cigarette to help them reduce smoking.