University of Southern California, Department of Population and Public Health Sciences, Institute for Addiction Science, Los Angeles, CA, USA.
Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
Addiction. 2022 Dec;117(12):3129-3139. doi: 10.1111/add.16009. Epub 2022 Aug 12.
To estimate the association of longitudinal patterns of e-cigarette use with cigarette smoking abstinence, after accounting for time-dependent confounding and selection bias.
Secondary analysis of longitudinal national cohort data. Using marginal structural models and four waves of the population assessment of tobacco and health (wave 1, 2013-14; wave 2, 2014-15; wave 3, 2015-16; wave 4, 2016-18), we estimated the association of vaping frequency across waves 2 and 3 with 12-month sustained cigarette smoking abstinence at wave 4, adjusting for time-dependent confounders at waves 1 and 2 and selection bias due to drop-out with inverse probability of treatment and censoring weights.
United States.
PARTICIPANTS/CASES: A total of 5699 adults (18+ years) who smoked cigarettes and did not vape at wave 1.
The exposure was vaping frequency at waves 2 and 3 (non-use, non-daily use, daily use), representing nine possible combinations of vaping frequency across two waves. Non-use at both waves was the exposure reference group. The primary outcome was sustained 12-month cigarette smoking abstinence at wave 4.
Among 5699 adults who smoked cigarettes at wave 1, a total of 560 (9.8%) reported smoking abstinence at wave 4. Compared with nonuse at both waves, daily vaping at both waves [risk ratio (RR) = 3.82, 95% confidence interval (CI) = 2.59-5.64] and non-use at wave 2 followed by daily vaping at wave 3 (RR = 2.50, 95% CI = 1.66-3.77) were positively associated with smoking abstinence; non-daily vaping at both waves was inversely associated with smoking abstinence (RR = 0.28, 95% CI = 0.11-0.75). Results persisted after accounting for misclassification of e-cigarette use and cigarette smoking abstinence and after restricting to participants with plans to quit smoking.
In a US cohort of adult smokers, longitudinal patterns of vaping frequency appear to predict smoking abstinence, even after accounting for several sources of systematic error. Consistent daily vaping is associated with increased chances of cigarette smoking abstinence, while consistent non-daily vaping is associated with decreased chances of smoking abstinence.
在考虑时间依赖性混杂因素和选择偏差的情况下，估计电子烟使用的纵向模式与戒烟的关联。
对纵向全国队列数据进行二次分析。使用边缘结构模型和四次人群烟草和健康评估（第 1 波，2013-14 年；第 2 波，2014-15 年；第 3 波，2015-16 年；第 4 波，2016-18 年），我们估计了第 2 波和第 3 波的电子烟使用频率与第 4 波的 12 个月持续戒烟之间的关联，在第 1 波和第 2 波调整了时间依赖性混杂因素，并通过逆概率治疗和删失权重处理了因辍学导致的选择偏差。
美国。
参与者/病例：共有 5699 名成年人（18 岁以上）在第 1 波时吸烟且不吸电子烟。
暴露于第 2 波和第 3 波的电子烟使用频率（不使用、非日常使用、日常使用），代表两个波之间电子烟使用频率的九个可能组合。两次均不使用是暴露的参照组。主要结局是第 4 波的持续 12 个月戒烟。
在第 1 波时吸烟的 5699 名成年人中，共有 560 人（9.8%）在第 4 波时报告戒烟。与两次均不使用相比，两次均每日使用电子烟[风险比（RR）=3.82，95%置信区间（CI）=2.59-5.64]和第 2 波不使用而第 3 波每日使用电子烟（RR=2.50，95%CI=1.66-3.77）与戒烟呈正相关；两次均非日常使用电子烟与戒烟呈负相关（RR=0.28，95%CI=0.11-0.75）。在考虑电子烟使用和戒烟的错误分类以及限制在有戒烟计划的参与者后，结果仍然存在。
在一项美国成年吸烟者队列中，纵向电子烟使用模式似乎可以预测戒烟，即使在考虑了多种系统性误差源后也是如此。一致的每日使用电子烟与增加戒烟的机会相关，而一致的非日常使用电子烟与降低戒烟的机会相关。
