Globally, over 10 million youth use e-cigarettes; United States use, in particular, dramatically rose in the late 2010’s, exceeding year-over-year increases from any other substance in over four decades. This rise has been partially attributed to youth online e-cigarette marketing exposure, but has not been appropriately studied. We examined youth data from the Population Assessment of Tobacco and Health (PATH) spanning the dramatic increase period (Waves 4, 4.5, and 5; 2016-2019). We estimated average risk differences (RD) for Wave 5 e-cigarette harmfulness perception and use comparing all youth versus no youth reporting past-month online e-cigarette marketing exposure in Waves 4 and 4.5. We used a doubly robust, nonparametric targeted minimum loss-based estimator (TMLE) to estimate RD, incorporating PATH survey weights. Initial analyses adjusted for demographics, mental health issues, and other forms of e-cigarette marketing. Subsequent analyses adjusted for frequency of social media use, other substance use, and tobacco (non-e-cigarette) use. Initial analyses estimated that online marketing associated with a 9% decrease in e-cigarette harmfulness perception (RD=-0.09, 95% C-0.12, -0.05), or a Risk Ratio (RR) of 0.85 (95% CI=0.80, 0.91), as well as a 4% increase in current e-cigarette use (RD=0.04, 95% CI=0.02, 0.06; RR=1.36, 95% CI=1.15, 1.62). However, after adjusting for additional potential time-varying confounding variables, point estimates were close to null with 95% confidence intervals spanning the null. Frequency of social media use, other substance use, and/or tobacco use may be important confounding variables related to marketing and e-cigarette use that require further investigation. • U.S. youth e-cigarette use rose dramatically in the late 2010’s. • Fixed effects analysis supports online marketing (OM) as a cause. • Causal effect analysis (CEA) adjusts for time-varying exposure-confounder feedback. • Initial CEA indicated OM increased current e-cigarette use. • The effect was lost after adjusting for online activity and other substance use.
Harrell et al. (2026) studied this question.
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