e-Cigarettes, Smoking Cessation, and Weight Change: Retrospective Secondary Analysis of the Evaluating the Efficacy of e-Cigarette Use for Smoking Cessation Trial

• Published in: JMIR public health and surveillance Vol. 10; p. e58260
• Main Authors: Lyzwinski, Lynnette, Dong, Meichen, Wolfinger, Russell D, Filion, Kristian B, Eisenberg, Mark J
• Format: Journal Article
• Language: English
• Published: Canada JMIR Publications 16.09.2024
• Subjects: Abstinence; Adult; Body Weight; Carbon monoxide; Counseling; Electronic cigarettes; Electronic Nicotine Delivery Systems - statistics & numerical data; Ethics; Female; Humans; Male; Middle Aged; Missing data; Mortality; Multimedia; Nicotine; Original Paper; Retrospective Studies; Secondary analysis; Smoking; Smoking cessation; Smoking Cessation - methods; Smoking Cessation - statistics & numerical data; Statistical methods; Weight Gain; Canada; nicotine; vaping; weight change; e-cigarettes; smoking cessation; weight gain
• ISSN: 2369-2960; 2369-2960
• DOI: 10.2196/58260

While smoking cessation has been linked to substantial weight gain, the potential influence of e-cigarettes on weight changes among individuals who use these devices to quit smoking is not fully understood. This study aims to reanalyze data from the Evaluating the Efficacy of e-Cigarette Use for Smoking Cessation (E3) trial to assess the causal effects of e-cigarette use on change in body weight. This is a secondary analysis of the E3 trial in which participants were randomized into 3 groups: nicotine e-cigarettes plus counseling, nonnicotine e-cigarettes plus counseling, and counseling alone. With adjustment for baseline variables and the follow-up smoking abstinence status, weight changes were compared between the groups from baseline to 12 weeks' follow-up. Intention-to-treat and as-treated analyses were conducted using doubly robust estimation. Further causal analysis used 2 different propensity scoring methods to estimate causal regression curves for 4 smoking-related continuous variables. We evaluated 5 different subsets of data for each method. Selection bias was addressed, and missing data were imputed by the machine learning method extreme gradient boosting (XGBoost). A total of 257 individuals with measured weight at week 12 (mean age: 52, SD 12 y; women: n=122, 47.5%) were included. Across the 3 treatment groups, of the 257 participants, 204 (79.4%) who continued to smoke had, on average, largely unchanged weight at 12 weeks, with comparable mean weight gain ranging from -0.24 kg to 0.33 kg, while 53 (20.6%) smoking-abstinent participants gained weight, with a mean weight gain ranging from 2.05 kg to 2.70 kg. After adjustment, our analyses showed that the 2 e-cigarette arms exhibited a mean gain of 0.56 kg versus the counseling alone arm. The causal regression curves analysis also showed no strong evidence supporting a causal relationship between weight gain and the 3 e-cigarette-related variables. e-Cigarettes have small and variable causal effects on weight gain associated with smoking cessation. In the E3 trial, e-cigarettes seemed to have minimal effects on mitigating the weight gain observed in individuals who smoke and subsequently quit at 3 months. However, given the modest sample size and the potential underuse of e-cigarettes among those randomized to the e-cigarette treatment arms, these results need to be replicated in large, adequately powered trials. ClinicalTrials.gov NCT02417467; https://www.clinicaltrials.gov/study/NCT02417467.