Background and aims

Relative pharmacological effects of e-cigarettes and cigarettes during 24 hours of ad-libitum use have not been described. In this study, 24-hour blood plasma nicotine concentrations and 48-hour subjective effects with use of cigarettes and e-cigarettes were measured among dual users.

Design

Two-arm within-subject cross-over design with preferred e-cigarette or cigarette ad-libitum use over 48 hours.

Setting

Hospital research ward in San Francisco, California, USA.

Participants

Thirty-six healthy dual users of e-cigarettes and cigarettes (n = 8, 25% females).

Measurements

Twenty-four-hour blood plasma nicotine and cotinine concentrations and 48-hour self-reported nicotine withdrawal symptoms and rewarding effects.

Findings

Analyses used analysis of variance (ANOVA)-based mixed models with order of product (e-cigarette or cigarette) and product type (combustible cigarette or type of e-cigarette) as fixed effects, and subject as a repeated effect. During a 24-hour period, e-cigarettes produced lower nicotine exposure than cigarettes for the majority of users, although 25% received more nicotine from e-cigarettes, which was predicted by more frequent e-cigarette use or greater dependence. Compared to cigarette smoking, nicotine exposure for variable-power tank users was similar, while cig-a-like (t₍₃₀₎  = 2.71, P = 0.011, d = 0.745) and fixed-power tank users (t₍₃₀₎  = 3.37, P = 0.002, d = 0.993) were exposed to less nicotine. Cigarettes were rated higher than e-cigarettes on some desirable subjective effects (e.g. psychological reward, t₍₃₂₂₎  = 7.24 P < 0.001, d = 0.432), but withdrawal symptom reduction was comparable. No differences were found between e-cigarette types, but Bayes factors indicate that these measures were insensitive.

Conclusions

During a 24-hour period in a hospital setting in the United States, nicotine exposure for dual users of e-cigarettes and cigarettes was similar when using cigarettes or variable-power tank devices only but was lower for those using cig-a-like or fixed-power devices only. Despite lower nicotine levels, all types of e-cigarette were effective in preventing withdrawal symptoms. E-cigarettes were rated less rewarding than cigarettes.

Background and aims

Relative pharmacological effects of e-cigarettes and cigarettes during 24 hours of ad-libitum use have not been described. In this study, 24-hour blood plasma nicotine concentrations and 48-hour subjective effects with use of cigarettes and e-cigarettes were measured among dual users.

Design

Two-arm within-subject cross-over design with preferred e-cigarette or cigarette ad-libitum use over 48 hours.

Setting

Hospital research ward in San Francisco, California, USA.

Participants

Thirty-six healthy dual users of e-cigarettes and cigarettes (n = 8, 25% females).

Measurements

Twenty-four-hour blood plasma nicotine and cotinine concentrations and 48-hour self-reported nicotine withdrawal symptoms and rewarding effects.

Findings

Analyses used analysis of variance (ANOVA)-based mixed models with order of product (e-cigarette or cigarette) and product type (combustible cigarette or type of e-cigarette) as fixed effects, and subject as a repeated effect. During a 24-hour period, e-cigarettes produced lower nicotine exposure than cigarettes for the majority of users, although 25% received more nicotine from e-cigarettes, which was predicted by more frequent e-cigarette use or greater dependence. Compared to cigarette smoking, nicotine exposure for variable-power tank users was similar, while cig-a-like (t₍₃₀₎  = 2.71, P = 0.011, d = 0.745) and fixed-power tank users (t₍₃₀₎  = 3.37, P = 0.002, d = 0.993) were exposed to less nicotine. Cigarettes were rated higher than e-cigarettes on some desirable subjective effects (e.g. psychological reward, t₍₃₂₂₎  = 7.24 P < 0.001, d = 0.432), but withdrawal symptom reduction was comparable. No differences were found between e-cigarette types, but Bayes factors indicate that these measures were insensitive.

Conclusions

During a 24-hour period in a hospital setting in the United States, nicotine exposure for dual users of e-cigarettes and cigarettes was similar when using cigarettes or variable-power tank devices only but was lower for those using cig-a-like or fixed-power devices only. Despite lower nicotine levels, all types of e-cigarette were effective in preventing withdrawal symptoms. E-cigarettes were rated less rewarding than cigarettes.

Introduction

Many electronic cigarette manufacturers have begun offering liquids containing "nicotine salts," which are formed when an acid is mixed in a solution with free-base nicotine. Type of salt could play a significant role in the abuse liability of electronic cigarette liquids. As a first step to understanding nicotine salts, this study sought to identify the types of acids present in 23 commercially available electronic cigarette liquids.

Aims and methods

Twenty-three electronic cigarette liquids advertised as containing nicotine salts were purchased for analysis. These liquids were tested for the presence of 11 different organic acids that were deemed likely to be used in a nicotine salt formulation. Liquids were analyzed using a combination of liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry methods, then compared to authentic acid standards for identification.

Results

Six of the 11 possible acids were identified in the liquids, from most to least common: lactic, benzoic, levulinic, salicyclic, malic, and tartaric acid. Acid(s) could not be identified in one of the liquids. Though most liquids contained only one type, three of the liquids contained multiple acids.

Conclusions

These data demonstrate that several types of salts/acids are currently being used in electronic cigarette liquids. The type and concentration of salt(s) used in these liquids may differentially alter sensations in the throat and upper airway, and overall pharmacology of the aerosols by altering liquid pH and from flavor and sensory characteristics of the acids themselves.

Implications

This study demonstrates that at least six different types of acids are being used to create the nicotine salts in electronic cigarette liquids, with the acids lactic, benzoic, and levulinic being the most frequently identified. Identification of these acids can serve as the foundation for future research to determine if type of nicotine salt alters pharmacological and toxicological effects of electronic cigarettes.

Background Cardiovascular safety is an important consideration regarding the benefits versus risks of electronic cigarette use (EC) for public health. The single-use cardiovascular effects of EC have been well studied but may not reflect effects of ad libitum use throughout the day. We aimed to compare the circadian hemodynamic effects as well as 24-hour biomarkers of oxidative stress, and platelet aggregation and inflammation, with ad libitum cigarette smoking (CS) versus EC versus no tobacco product use. Methods and Results Thirty-six healthy dual CS and EC users participated in a crossover study in a confined research setting. Circadian heart rate, blood pressure and plasma nicotine levels, 24-hour urinary catecholamines, 8-isoprostane and 11-dehydro-thromboxane B2, and plasma interleukin-6 and interleukin-8 were compared in CS, EC, and no nicotine conditions. Over 24 hours, and during daytime, heart rate and blood pressure were higher in CS and EC compared with no tobacco product conditions (P<0.01). Heart rate on average was higher with CS versus EC. Urinary catecholamines, 8-isoprostane, and 11-dehydro-thromboxane B2 were not significantly different, but plasma IL-6 and IL-8 were higher with both CS and EC compared with no tobacco product (P<0.01). Conclusions CS and EC had similar 24-hour patterns of hemodynamic effects compared with no tobacco product, with a higher average heart rate with CS versus EC, and similar effects on biomarkers of inflammation. EC may pose some cardiovascular risk, particularly to smokers with underlying cardiovascular disease, but may also provide a harm reduction opportunity for smokers willing to switch entirely to EC. Registration URL: https://www.clinicaltrials.gov; Unique Identifier: NCT02470754.