TY - JOUR
T1 - What factors reliably predict electronic cigarette nicotine delivery?
AU - Blank, Melissa D.
AU - Pearson, Jennifer
AU - Cobb, Caroline O.
AU - Felicione, Nicholas J.
AU - Hiler, Marzena M.
AU - Spindle, Tory R.
AU - Breland, Alison
N1 - Funding Information:
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).
Funding Information:
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).
Publisher Copyright:
© 2020 BMJ Publishing Group. All rights reserved.
PY - 2020/11/1
Y1 - 2020/11/1
N2 - 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.
AB - 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.
KW - electronic cigarettes
KW - nicotine
KW - regulation
KW - topography
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U2 - 10.1136/tobaccocontrol-2019-055193
DO - 10.1136/tobaccocontrol-2019-055193
M3 - Article
C2 - 31685583
AN - SCOPUS:85074797330
SN - 0964-4563
VL - 29
SP - 644
EP - 651
JO - Tobacco control
JF - Tobacco control
IS - 6
ER -