An exploration into "do-it-yourself" (DIY) e-liquid mixing: Users' motivations, practices and product laboratory analysis. (June 2019) - Cox, Sharon; Leigh, Noel J.; Vanderbush, Taylor S.; Choo, Emma; Goniewicz, Maciej L.; Dawkins, Lynne
Abstract: Background: E-liquids are commercially available and manufactured, however some users of e-cigarettes prefer to prepare them at home (Do-it-Yourself; DIY) using individual ingredients. To date there is a paucity of research on how and why users make their own e-liquids. Methods: Forty-one European and US based exclusive users of e-cigarettes (ex-smokers) were individually interviewed. Structured interviews focused on motivations for home-mixing, practices, buying habits and broader themes around reasons for long-term vaping. We also measured nicotine and solvent concentrations and analysed 33 DIY e-liquids collected from 16 participants for nicotine, solvents, flavourings, and potentially harmful chemicals. Results: There were four main reasons for DIY: 1) economical (financial savings), 2) self-control over manufacturing process, 3) novelty, fun and 4) higher nicotine concentrations. Twelve out of 16 participants achieved nicotine concentration within 20% of their intended limit. Samples from five participants were above the EU Tobacco Products Directive's (TPD) 20 mg/ml nicotine concentration upper limit. Most samples contained more vegetable glycerine (VG) than propylene glycol (PG) and the most commonly used flavourings were dessert, e.g., vanilla and caramel. Chemical analysis also revealed presence of several potentially harmful chemicals and respiratory irritants, including cinnamaldehyde, benzaldehyde, and acetoin. Conclusion: DIY may offer users of e-cigarettes a long-term affordable practical method of vaping. Recommended safety advice needs to reflect actual and fast moving user behaviour. Highlights: First study investigating motivations and practices of DIY e-liquid mixing First known chemical analysis of e-cigarette DIY liquid Majority achieved nicotine concentration within 20% of the intended limit There is a need for research to track actual real-life user behaviour