Behavioral Sciences Group, Sanford Research, Sioux Falls, SD, USA.
Department of Pediatrics, University of South Dakota Sanford School of Medicine, Sioux Falls, SD, USA.
Addiction. 2021 Jul;116(7):1848-1858. doi: 10.1111/add.15385. Epub 2021 Jan 19.
The impact of electronic cigarettes (ECs) on nicotine use is hotly debated: some fear that ECs are a 'catalyst' to conventional smoking, while others argue that they divert adolescents from the more harmful product. This study used simulation modeling to evaluate the plausibility of catalyst and diversion hypotheses against real-world data.
A simulation model represented life-time exclusive EC use, exclusive conventional smoking and dual use as separate subpopulations. The 'catalyst' effect was modeled as EC use increasing dual use initiation (i.e. EC users also start smoking). The 'diversion' effect was modeled as EC use decreasing exclusive cigarette initiation. The model was calibrated using data from the US National Youth Tobacco Survey (NYTS). The plausibility of each scenario was evaluated by comparing simulated trends with NYTS data. This is the first study, to our knowledge, to estimate the magnitude of a diversion effect through simulation.
United States.
Adolescents aged 12-17 years in NYTS, a cross-sectional study from 2000 to 2019 (n = 12 500 to 31 000 per wave). Exclusive cigarette use, exclusive EC use and dual use of both products were defined using cumulative life-time criteria (100+ cigarettes smoked and/or > 100 days vaped).
A null model (no catalyst or diversion) over-predicts NYTS smoking by up to 87%. Under the conservative assumption that the catalyst effect accounts for all dual use, an exponential decay constant of 19.6% EC users/year initiating smoking is required; however, this further over-predicts actual smoking by up to 109%. A diversion effect with an exponential decay constant of 55.4%/year or 65.4%/year, with the maximum possible opposing catalyst effect also active, is required optimally to match NYTS smoking trends (root mean square error = 286 632 versus 391 396 in the null model).
A simulation model shows that a substantial diversion effect is needed to explain observed nicotine use trends among US adolescents, and it must be larger than any possible opposing catalyst effect, if present.
电子烟 (EC) 对尼古丁使用的影响存在争议:一些人担心 EC 是传统吸烟的“催化剂”,而另一些人则认为它们使青少年远离更有害的产品。本研究使用模拟模型根据实际数据评估催化剂和转移假说的合理性。
模拟模型代表终生仅使用 EC、仅使用传统香烟和同时使用这两种产品的人群。“催化剂”效应被建模为 EC 使用增加双重使用的起始(即 EC 用户也开始吸烟)。“转移”效应被建模为 EC 使用减少了仅使用香烟的起始。该模型使用来自美国国家青少年烟草调查 (NYTS) 的数据进行校准。通过将模拟趋势与 NYTS 数据进行比较,评估了每种情况的合理性。据我们所知,这是第一项通过模拟估计转移效应程度的研究。
美国。
NYTS 中的 12-17 岁青少年,这是一项 2000 年至 2019 年的横断面研究(每波有 12500 至 31000 名参与者)。使用累积终生标准(吸烟 100 支以上或吸电子烟 100 天以上)定义了仅使用香烟、仅使用 EC 和同时使用这两种产品的情况。
无催化剂或转移的零模型(null model)预测 NYTS 的吸烟量最多高出 87%。在假设催化剂效应解释了所有双重使用的保守情况下,需要每年有 19.6%的 EC 用户开始吸烟的指数衰减常数;然而,这进一步预测了实际吸烟量,最多高出 109%。需要每年 55.4%或 65.4%的指数衰减常数的转移效应,同时最大可能的相反催化剂效应也处于活动状态,才能最佳地匹配 NYTS 的吸烟趋势(均方根误差分别为 286632 和 391396,在零模型中)。
模拟模型表明,需要有大量的转移效应才能解释美国青少年观察到的尼古丁使用趋势,如果存在的话,这种效应必须大于任何可能的相反催化剂效应。