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What factors reliably predict electronic cigarette nicotine delivery?
  1. Melissa D Blank1,
  2. Jennifer Pearson2,3,
  3. Caroline O Cobb4,
  4. Nicholas J Felicione1,
  5. Marzena M Hiler4,
  6. Tory R Spindle5,
  7. Alison Breland4
  1. 1 Department of Psychology, West Virginia University, Morgantown, West Virginia, USA
  2. 2 Division of Social and Behavioral Science/Health Administration and Policy, University of Nevada Reno, Reno, Nevada, USA
  3. 3 Department of Health, Behavior, and Society, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
  4. 4 Department of Psychology, Virginia Commonwealth University, Richmond, Virginia, USA
  5. 5 Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, Maryland, USA
  1. Correspondence to Dr Melissa D Blank, Psychology, West Virginia University, Morgantown, WV 26506-6040, USA; mdblank{at}


Background The ability of an electronic cigarette (e-cigarette) to deliver nicotine effectively may be dependent on features of the device, the liquid and the user. Some of these features have been examined in previous work (eg, liquid nicotine concentration and puff topography), while others have not (eg, nicotine dependence and demographic characteristics). The purpose of this secondary analysis is to examine such features as predictors of e-cigarette nicotine delivery using a relatively large sample.

Methods Four studies were combined in which e-cigarette-experienced users (n=63; 89% men; 75% white) and e-cigarette-naïve cigarette smokers (n=67; 66% men; 54% white) took 10 puffs from an eGo-style e-cigarette (~7.3 watts) filled with liquid that had a nicotine concentration of 18, 25 or 36 mg/mL. Thus, held constant across all studies were device features of battery/cartomiser style and power level and the topography parameters of puff number and interpuff interval. Blood was sampled before and after use, and puff topography was measured. Three general linear models were conducted to predict plasma nicotine concentrations (pre–post increase) for: (1) e-cigarette users only, (2) smokers only and (3) both groups combined. Predictor variables included puff duration, puff volume, liquid nicotine concentration, presession plasma nicotine concentration, nicotine dependence score (smokers only), gender and race.

Results In all models tested, longer puff durations and higher liquid nicotine concentrations were associated significantly with increased nicotine delivery (ps<0.05). For e-cigarette users only, higher presession nicotine concentration was associated significantly with increased nicotine delivery (p<0.05).

Conclusions Puff duration and liquid nicotine concentration may be among the more important factors to consider as regulators attempt to balance e-cigarette safety with efficacy. These findings should be interpreted in the context of devices with relatively low power output, a variable not studied here but likely also directly relevant to product regulation.

  • electronic cigarettes
  • topography
  • nicotine
  • regulation

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  • Presented at This secondary data analysis was presented at the 25th annual meeting of the Society for Research on Nicotine and Tobacco (February 2019; San Francisco, California, USA). Data for the individual studies also have been presented at various conferences, including Society for Research on Nicotine and Tobacco (2015, 2016 and 2017), College on Problems of Drug Dependence (2015), and National Institutes of Health Tobacco Regulatory Science Meeting (2016).

  • Contributors MB and JP conceptualised the project, drafted the introduction and discussion sections and reviewed and edited drafts of the manuscript. COC and AB conceptualised the project, conducted statistical analyses, drafted the methods and/or results sections and reviewed and edited drafts of the manuscript. NJF assisted with literature review and summary and reviewed and edited drafts of the manuscript. MMH and TS were lead on the two published studies included in these analyses and reviewed and edited drafts of the manuscript.

  • Funding Financial supported provided by the National Institute on Drug Abuse of the National Institutes of Health and the Centre for Tobacco Products of the US Food and Drug Administration under Award Numbers U54 DA036105 (PIs Thomas Eissenberg, PhD, and AB), P50DA036105 (PI Thomas Eissenberg, PhD) and K01DA037950 (JP) and by the WVU Prevention Research Centre under Cooperative Agreement Number 1-U48-DP-005004 (MB) from the Centers for Disease Control and Prevention (CDC).

  • Disclaimer The content is solely the responsibility of the authors and does not necessarily represent the views of the NIH, FDA or CDC.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Ethics approval Ethical approval was provided by the Institutional Review Board at Virginia Commonwealth University for all studies included.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available on reasonable request.