Menthol versus tobacco e-liquid flavor: Impact on acute subjective effects, puff patterns, and intentions for use among Black and White menthol smokers.

BACKGROUND: The proposed FDA product standard to prohibit menthol as a characterizing flavor in combustible cigarettes has the potential to significantly reduce tobacco-related health disparities. Whether a menthol e-liquid product standard would improve or hinder public health is unknown. No known research has directly examined the impact of menthol vs. tobacco flavored e-liquid use on acute e-cigarette use patterns, subjective experience, behavioral intentions, and craving and withdrawal among menthol cigarette smokers. METHODS: Black (n = 47) and White (n = 4) nicotine-deprived menthol smokers with limited e-cigarette experience completed two counterbalanced in-laboratory 30-minute ad libitum vaping sessions with menthol and tobacco nicotine salt-based e-liquid in a randomized crossover pilot trial design. Questionnaires assessed reductions in craving and withdrawal and post-session subjective experience and behavioral intentions. Puff topography was measured continuously throughout each vaping session. RESULTS: Measures of puff topography did not differ significantly by e-liquid flavor (all p > .40). Similarly, menthol and tobacco flavored e-cigarettes were both rated positively in terms of subjective effects and behavioral intentions (all p > .10) and about 40 % of participants reported a preference for the tobacco-flavored e-liquid. Finally, participants showed comparable reductions in craving (p = .210) and withdrawal (p = .671) from pre- and post-session regardless of e-liquid flavor. CONCLUSIONS: Among menthol smokers in a lab-based setting, findings suggest that menthol vs tobacco e-liquid flavor has little impact on acute changes in puff patterns, subjective experience, behavioral intentions, or craving and withdrawal.

Nicotine Intake in Adult Pod E-cigarette Users: Impact of User and Device Characteristics.

INTRODUCTION: This study examined user behavior, e-cigarette dependence, and device characteristics on nicotine intake among users of pod-mod e-cigarettes. AIMS AND METHODS: In 2019-2020, people who use pod-mods in the San Francisco Bay Area completed questionnaires and provided a urine sample for analysis of total nicotine equivalents (TNE). The relationship between TNE and e-cigarette use, e-cigarette brands, e-liquid nicotine strength, e-cigarette dependence, and urine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), as a measure of combustible cigarette exposure, were examined. RESULTS: Of 100 participants (64% male, 71% in the 18-34 age group, 45% white), 53 used JUUL primarily, 12 used Puff Bar primarily, and 35 used other brands, including Suorin; 48 participants reported current cigarette smoking. Participants most often reported use of e-liquid with 4.5%-6.0% nicotine (68%), fruit (35%), tobacco (28%), and menthol or mint flavors (26%), used e-cigarettes on 25.5 (SD = 6.3) days a month, 10.2 (SD = 14.2) times a day, and 40% used 1-2 pods/cartridges per week. In bivariate analysis, urinary TNE was higher with greater frequency (days used) and intensity (number of pods used) of e-cigarette use, e-cigarette dependence, and combustible cigarette use. In multivariable analysis, days of e-cigarette use in the last 30 days, number of pods used per week, and NNAL levels were significantly associated with TNE. There was no significant impact of e-liquid nicotine strength on TNE. CONCLUSIONS: Nicotine intake among people who used pod-mod e-cigarettes increased with e-cigarette consumption and e-cigarette dependence, but not with e-liquid nicotine strength. Our findings may inform whether FDA adopts a nicotine standard for e-cigarettes. IMPLICATIONS: The study examined how device and user characteristics influence nicotine intake among pod-mod e-cigarette users. Nicotine intake increased with frequency (days of e-cigarette use in past 30 days) intensity of use (number of pods used per day) and e-cigarette dependence but not with the flavor or nicotine concentration of the e-liquids. Regulation of nicotine concentration of e-liquids is unlikely to influence nicotine exposure among adult experienced pod-mod users.

Cardiopulmonary Consequences of Vaping in Adolescents: A Scientific Statement From the American Heart Association.

Although the US Food and Drug Administration has not approved e-cigarettes as a cessation aid, industry has at times positioned their products in that way for adults trying to quit traditional cigarettes; however, their novelty and customizability have driven them into the hands of unintended users, particularly adolescents. Most new users of e-cigarette products have never smoked traditional cigarettes; therefore, understanding the respiratory and cardiovascular consequences of e-cigarette use has become of increasing interest to the research community. Most studies have been performed on adult e-cigarette users, but the majority of these study participants are either former traditional smokers or smokers who have used e-cigarettes to switch from traditional smoking. Therefore, the respiratory and cardiovascular consequences in this population are not attributable to e-cigarette use alone. Preclinical studies have been used to study the effects of naive e-cigarette use on various organ systems; however, almost all of these studies have used adult animals, which makes translation of health effects to adolescents problematic. Given that inhalation of any foreign substance can have effects on the respiratory and cardiovascular systems, a more holistic understanding of the pathways involved in toxicity could help to guide researchers to novel therapeutic treatment strategies. The goals of this scientific statement are to provide salient background information on the cardiopulmonary consequences of e-cigarette use (vaping) in adolescents, to guide therapeutic and preventive strategies and future research directions, and to inform public policymakers on the risks, both short and long term, of vaping.

Biomarkers of nicotine exposure correlate with the Hooked on Nicotine Checklist among adolescents in California, United States.

BACKGROUND: The Hooked on Nicotine Checklist (HONC) has been used to assess nicotine dependence (loss of autonomy over tobacco) among adolescents. Existing HONC validation studies for non-cigarette products, such as electronic cigarettes (e-cigarettes), have generally not considered biomarkers of nicotine exposure. METHODS: Within a cross-sectional sample of California (USA) high school students (total N = 1396; mean age 15.2 years; 56% female; 54% Hispanic/Latinx), self-reported past 30-day users of any tobacco (including e-cigarettes) completed a modified 10-item HONC questionnaire and provided saliva samples (N = 318 samples, including N = 234 exclusive past 30-day e-cigarette users). Samples were analyzed for cotinine using liquid chromatography-tandem mass spectrometry (lower limit of quantification: 1.0 ng/mL). RESULTS: Across four categories of HONC score corresponding to an increasing number of reported dependence symptoms (scores: 0, 1, 2-4, 5-10), the prevalence of quantifiable salivary cotinine increased among past 30-day tobacco users (20%, 21%, 38%, 55%, respectively, P-for-trend < 0.001) and among past 30-day exclusive e-cigarette users (15%, 22%, 31%, 42%, respectively, P-for-trend = 0.001). Among participants with quantifiable cotinine levels, HONC total score and cotinine were positively correlated among past 30-day tobacco users (n = 89; Spearman rho = 0.449; P < 0.001) and past 30-day exclusive e-cigarette users (n = 49; Spearman rho = 0.520; P < 0.001). HONC score was also associated with past 30-day frequency of tobacco product use and reported use of tobacco within 30 min of waking. CONCLUSIONS: These results support the validity of HONC to assess nicotine dependence among adolescents. Dependence symptoms may be experienced at low levels of nicotine exposure.

Clinical Pharmacology of Electronic Nicotine Delivery Systems (ENDS): Implications for Benefits and Risks in the Promotion of the Combusted Tobacco Endgame.

Electronic nicotine delivery systems (ENDS) such as e-cigarettes and heated tobacco products are novel battery-operated devices that deliver nicotine without combustion of tobacco. Because cigarette smoking is sustained by nicotine addiction and the toxic combustion products are mainly responsible for the harmful effects of smoking, ENDS could be used to promote smoking cessation while exposing users to lower levels of toxicants compared with conventional cigarettes. The currently available evidence from clinical and observational studies indicates a potential role of e-cigarettes as smoking cessation aids, although many continue to use e-cigarettes long after quitting smoking. Nicotine and toxicant delivery vary considerably by device and depend on the characteristics of the e-liquid formulation. Because smokers tend to titrate their nicotine intake to maintain their desired pharmacologic effects, device and liquid characteristics need to be considered when using ENDS as an aid to quit smoking. Factors potentially limiting their use are the currently still unknown long-term safety of these products and concerns regarding widespread use among youth. Implications of clinical pharmacology data on ENDS for the cigarette endgame and regulation by the U.S. Food and Drug administration are discussed.

Differences in exposure to toxic and/or carcinogenic volatile organic compounds between Black and White cigarette smokers.

OBJECTIVE: It is unclear why Black smokers in the United States have elevated risk of some tobacco-related diseases compared to White smokers. One possible causal mechanism is differential intake of tobacco toxicants, but results across studies are inconsistent. Thus, we examined racial differences in biomarkers of toxic volatile organic compounds (VOCs) present in tobacco smoke. METHOD: We analyzed baseline data collected from 182 Black and 184 White adult smokers who participated in a randomized clinical trial in 2013-2014 at 10 sites across the United States. We examined differences in urinary levels of ten VOC metabolites, total nicotine equivalents (TNE), and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), controlling for covariates such as cigarettes per day (CPD), as well as differences in VOCs per TNE to assess the extent to which tobacco exposure, and not metabolic factors, accounted for racial differences. RESULTS: Concentration of metabolites of acrolein, acrylonitrile, ethylene oxide, and methylating agents were significantly higher in Blacks compared to Whites when controlled for covariates. Other than the metabolite of methylating agents, VOCs per TNE did not differ between Blacks and Whites. Concentrations of TNE/CPD and VOCs/CPD were significantly higher in Blacks. Menthol did not contribute to racial differences in VOC levels. CONCLUSIONS: For a given level of CPD, Black smokers likely take in higher levels of acrolein, acrylonitrile, and ethylene oxide than White smokers. Our findings are consistent with Blacks taking in more nicotine and toxicants per cigarette smoked, which may explain their elevated disease risk relative to other racial groups.

Twenty-Four-Hour Cardiovascular Effects of Electronic Cigarettes Compared With Cigarette Smoking in Dual Users.

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.

The impact of e-cigarette and cigarette prices on e-cigarette and cigarette sales in California.

Although numerous studies have examined the impact of cigarette prices on cigarette demand, research examining the impact of e-cigarette and cigarette prices on e-cigarette demand is relatively limited. This study estimated the impact of e-cigarette and cigarette prices on e-cigarette and cigarette sales in California. Using the 2012-2017 Nielsen Retail Scanner Data, we constructed e-cigarette prices, cigarette prices, and per capita e-cigarette and cigarette sales by year, quarter, and Nielsen scantrack market in California. E-cigarettes were categorized as disposable or reusable. Separate fixed-effects models estimated the impact of e-cigarette and cigarette prices on per capita disposable e-cigarette, reusable e-cigarette, and cigarette sales controlling for year, quarter, market, and smoke-free air law coverage. Average prices were $5.86 per pack of 20 cigarettes, $9.80 per disposable e-cigarette, and $19.11 per reusable e-cigarette. When prices of disposable e-cigarettes, reusable e-cigarettes, and cigarettes increased by 1%, per capita sales of the products decreased by 0.37%, 0.20%, and 0.21% respectively. Cigarette prices were positively associated with per capita sales of reusable e-cigarettes, indicating reusable e-cigarettes are substitutes for cigarettes. Reusable e-cigarette prices were positively associated with per capita sales of disposable e-cigarettes, indicating disposable e-cigarettes are substitutes for reusable e-cigarettes. No statistically significant association was found between disposable/reusable e-cigarette prices and cigarette sales. Our results suggest that raising prices of disposable e-cigarettes, reusable e-cigarettes, and cigarettes such as via tobacco excise tax increases would result in reduced sales for the products. Policymakers should consider the substitution between e-cigarettes and cigarettes when designing tobacco control policies.

Relationships Between Race, Gender, and Spot Urine Levels of Biomarkers of Tobacco Exposure Vary Based on How Creatinine Is Handled in Analyses.

INTRODUCTION: We illustrate the differential impact of common analysis approaches to handling urinary creatinine, a measure for urine dilution, on relationships between race, gender, and biomarkers of exposure measured in spot urine. METHODS: In smokers, spot urine levels of total nicotine equivalents (TNE, sum of total nicotine, total cotinine, and total 3'-hydroxycotinine) and total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) overall and per cigarette were examined. Relationships between race (African Americans [AA] n = 373, Whites n = 758) or gender (males n = 629, females n = 502) and TNE or NNAL were examined using the following approaches to handling creatinine: (1) unadjusted/unstandardized; (2) standardization; (3) adjustment as a covariate. Significance was considered at p < .05. RESULTS: Creatinine was higher in AA versus Whites (1.19 vs. 0.96 mg/mL; p < .0001) and in males versus females (1.21 vs. 0.84 mg/mL; p < .0001). Independent of how creatinine was handled, TNE was lower among AA than Whites (TNE ratios AA vs. Whites: 0.67-0.84; p's < .05). Unadjusted TNE per cigarette was higher among AA versus Whites (ratio 1.12; p = .0411); however, the relationship flipped with standardization (ratio 0.90; p = .0360) and adjustment (ratio 0.95; p = .3165). Regarding gender, unadjusted TNE was higher among males versus females (ratio 1.13; p = .0063), but the relationship flipped with standardization (ratio 0.79; p < .0001) or adjustment (ratio 0.89; p = .0018). Unadjusted TNE per cigarette did not differ across gender (ratio 0.98; p = .6591), but lower levels were found in males versus females with standardization (ratio 0.68; p < .0001) and adjustment (ratio 0.74; p < .0001). NNAL displayed similar patterns. CONCLUSIONS: Relationships between race, gender, and spot urine levels of biomarkers of exposure can vary greatly based on how creatinine is handled in analyses. IMPLICATIONS: Lack of appropriate methods can lead to discrepancies across reports on variability of urinary biomarkers by race and gender. We recommend that for any analyses of biomarkers of exposure measure in spot urine samples across race, gender, or other population subgroups that differ in urinary creatinine levels, sensitivity analyses comparing the different methods for handling urinary creatinine should be conducted. If methods result in discrepant findings, this should be clearly noted and discussed.

Comprehensive Parent-Metabolite PBPK/PD Modeling Insights into Nicotine Replacement Therapy Strategies.

BACKGROUND: Nicotine, the pharmacologically active substance in both tobacco and many electronic cigarette (e-cigarette) liquids, is responsible for the addiction that sustains cigarette smoking. With 8 million deaths worldwide annually, smoking remains one of the major causes of disability and premature death. However, nicotine also plays an important role in smoking cessation strategies. OBJECTIVES: The aim of this study was to develop a comprehensive, whole-body, physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model of nicotine and its major metabolite cotinine, covering various routes of nicotine administration, and to simulate nicotine brain tissue concentrations after the use of combustible cigarettes, e-cigarettes, nicotine gums, and nicotine patches. METHODS: A parent-metabolite, PBPK/PD model of nicotine for a non-smoking and a smoking population was developed using 91 plasma and brain tissue concentration-time profiles and 11 heart rate profiles. Among others, cytochrome P450 (CYP) 2A6 and 2B6 enzymes were implemented, including kinetics for CYP2A6 poor metabolizers. RESULTS: The model is able to precisely describe and predict both nicotine plasma and brain tissue concentrations, cotinine plasma concentrations, and heart rate profiles. 100% of the predicted area under the concentration-time curve (AUC) and maximum concentration (Cmax) values meet the twofold acceptance criterion with overall geometric mean fold errors of 1.12 and 1.15, respectively. The administration of combustible cigarettes, e-cigarettes, nicotine patches, and nicotine gums was successfully implemented in the model and used to identify differences in steady-state nicotine brain tissue concentration patterns. CONCLUSIONS: Our PBPK/PD model may be helpful in further investigations of nicotine dependence and smoking cessation strategies. As the model represents the first nicotine PBPK/PD model predicting nicotine concentration and heart rate profiles after the use of e-cigarettes, it could also contribute to a better understanding of the recent increase in youth e-cigarette use.

Comparison of Systemic Exposure to Toxic and/or Carcinogenic Volatile Organic Compounds (VOC) during Vaping, Smoking, and Abstention.

Comparisons of systemic exposure to toxicants during monitored cigarette smoking, electronic cigarette (e-cigarette) use, and abstention are needed to enhance our understanding of the risks of e-cigarette use (vaping). In a cross-over study, we measured 10 mercapturic acid metabolites of volatile organic compounds (VOCs) in 24-hour urine samples collected from 36 dual users (8 women) of e-cigarettes and cigarettes during 2 days of ad libitum vaping or cigarette-only use, and 2 days of enforced abstention. Concentrations of VOC metabolites were higher during smoking compared with vaping, except for the methylating agents' metabolite. The fold-difference in concentrations when smoking relative to vaping ranged from 1.31 (1.06-1.61; geometric mean, 95% confidence interval; 1,3-butadiene) to 7.09 (5.88-8.54; acrylonitrile). Metabolites of acrylamide [fold difference of 1.21 (1.03-1.43)] and benzene [1.46 (1.13-1.90)] were higher during vaping compared with abstention. The 1,3-butadiene and propylene oxide metabolites were higher in variable-power tank users compared with users of cig-a-likes. E-cigarettes expose users to lower levels of toxic VOCs compared with cigarette smoking, supporting their harm reduction potential among smokers. However, some e-cigarettes expose users to VOCs such as acrylamide, benzene, and propylene oxide, and may pose health risks to nonsmoking users. The results of our study will inform regulators in assessing e-cigarettes with respect to the balance between its potential harm reduction for adult smokers and risk to nonsmoking users.

Urine Metabolites for Estimating Daily Intake of Nicotine From Cigarette Smoking.

INTRODUCTION: Accurate measurement of nicotine exposure from cigarette smoke is important in studying disease risk and level of dependence. Urine total nicotine equivalents, the molar sum of nicotine and six metabolites (NE7), accounts for more than 90% of a nicotine dose and is independent of individual metabolic differences. However, measuring NE7 is technically difficult and costly. We compared NE7, the gold standard of nicotine intake, with different combinations of fewer urinary nicotine metabolites. We also examined the impact of individual differences in nicotine metabolic rate, sex, and race on strength of association with NE7. METHODS: Urine samples from 796 daily smokers, who participated across five clinical studies, were assayed for nicotine and/or metabolites. Associations with NE7 were assessed by regression and Bland-Altman analyses. RESULTS: Overall, the molar sum of urine [cotinine + 3'-hydroxycotinine (3HC)] (NE2) and [nicotine + cotinine + 3HC] (NE3) were strongly correlated with NE7 (r = .97 and .99, respectively). However, in slow metabolizers NE2 was less predictive of NE7, whereas NE3 was equally robust. Urine total cotinine was also strongly correlated with NE7 (r = .87). CONCLUSIONS: Urine NE3 is a robust biomarker of daily nicotine intake, independently of individual metabolic differences, whereas NE2 is less accurate in slow metabolizers. Our findings inform the selection of more rigorous and cost-effective measures to assess nicotine exposure in tobacco research studies. IMPLICATIONS: The molar sum of urine total nicotine, cotinine and 3HC (NE3) is a robust biomarker of daily nicotine intake, independently of individual metabolic differences, and performs as well as measuring seven nicotine metabolites (NE7). The sum of cotinine and 3HC (NE2) is less accurate in slow metabolizers. Our findings inform the selection of more rigorous and cost-effective measures to assess nicotine exposure in tobacco research studies.

Biomarkers of Exposure for Dual Use of Electronic Cigarettes and Combustible Cigarettes: Nicotelline, NNAL, and Total Nicotine Equivalents.

INTRODUCTION: Dual use of electronic cigarettes (e-cigarettes) and combustible cigarettes is a major public health issue. It is generally accepted that exclusive e-cigarette use is less harmful than exclusive combustible cigarette use, but most e-cigarette users continue to smoke combustible cigarettes as well. To what extent the use of e-cigarettes reduces harm in people who continue to smoke combustible cigarettes has been debated. The aim of this study was to explore the utility of biomarkers as measures of dual use. METHODS: In two human studies of participants who used e-cigarettes only or both combustible cigarettes and e-cigarettes, we measured urine concentrations of the metabolites of nicotine (total nicotine equivalents) as well as two biomarkers of tobacco exposure: 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), a tobacco-specific carcinogen metabolite, and nicotelline, a tobacco alkaloid not found in significant concentrations in e-cigarette products. RESULTS: The presence of nicotine metabolites indicates either e-cigarette or combustible cigarette use. Nicotelline (half-life of 2-3 hours) indicates recent combustible cigarette use and NNAL (half-life of 10 days or more), indicates combustible cigarette use occurring within several weeks prior to sample collection. CONCLUSIONS: Nicotelline and NNAL are useful biomarkers for combustible tobacco use in users e-cigarettes. The application of these biomarkers provides a tool to help assess whether, or to what extent, dual use of e-cigarettes and combustible cigarettes reduces harm compared to sole use of combustible cigarettes. These biomarkers can also verify exclusive use of e-cigarettes over short (24 hour) or long (several week) time periods. IMPLICATIONS: To what extent dual use of e-cigarettes and combustible cigarettes reduce harm compared to smoking combustible cigarettes only is of considerable public health interest. We show that the levels of the minor tobacco alkaloid nicotelline and the nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) are extremely low in electronic cigarette fluids. The urine biomarkers nicotelline and the NNK metabolite 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) are indicative of cigarette smoking and can be used to assess recent and past smoking in dual users.

Twenty-four-hour subjective and pharmacological effects of ad-libitum electronic and combustible cigarette use among dual users.

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.

Sources and Biomarkers of Secondhand Tobacco Smoke Exposure in Urban Adolescents.

OBJECTIVE: In an urban adolescent population, we evaluated sources of exposure to secondhand smoke exposure (SHS), examined differences in exposure by race/ethnicity, age and sex, and determined the relationship between exposure source(s) and the biomarkers cotinine and NNAL. METHODS: Participants were recruited from a public hospital-based outpatient clinic in San Francisco, CA, USA. RESULTS: Of a sample of N = 298 adolescents screened, 235 were biologically confirmed to be exposed to tobacco smoke. Of those, N = 16 were active smokers and N = 219 were exposed to SHS; 91 (39%) were heavily SHS exposed (median cotinine = 0.76 ng/mL) and 128 (54%) had light SHS exposure (median cotinine = 0.11 ng/mL). Within those SHS exposed, the most common source of exposure was in a public area. No significant racial/ethnic differences were found, although African American adolescents were more likely to live in a home that allowed smoking. Older adolescents were more likely to be exposed across several difference sources, and females more likely to be exposed in a car and in public areas. Past 7-day exposure in the home, in a car, and current blunt use were significantly related to biomarkers of exposure. CONCLUSIONS: Urban adolescents are exposed to SHS across a variety of sources. Although exposure in a public area is most common, exposure in the home and in cars significantly influences tobacco biomarker levels. Interventions to reduce exposure would have the greatest impact in this population if they focused on reducing exposure in the home and in cars. History of blunt use is a strong determinant of tobacco exposure.

Effects of Nicotine Metabolic Rate on Cigarette Reinforcement.

INTRODUCTION: The rate of nicotine metabolism, estimated by the nicotine metabolite ratio (NMR), is an important determinant of tobacco dependence. This study investigated the effect of NMR on smoking behavior due to nicotine reinforcement during ad libitum smoking. AIMS AND METHODS: As part of a larger study, participants were stratified based on saliva NMR as fast and slow metabolizers. After smoking a cigarette and measuring nicotine blood concentrations, participants smoked as desired over a 90-minute period. Analysis included time to first cigarette, total number of cigarettes, total number of puffs, and weight of tobacco consumed. RESULTS: Sixty-one (48%) participants were fast metabolizers and 66 (52%) slow metabolizers by NMR. No significant differences were found regarding the smoking topography variables by NMR. Normal metabolizers by genotype (n = 79) had a shorter time to first cigarette than reduced metabolizers (n = 39; p = .032). Blacks smoked fewer cigarettes (p = .008) and took fewer total puffs (p = .002) compared with Whites. Among Whites, fast metabolizers by NMR had a shorter time to first cigarette compared with slow metabolizers (p = .014). Among fast metabolizers, Whites had, compared with Blacks, shorter latency to first cigarette (p = .003) and higher number of total puffs (p = .014) and cigarettes smoked (p = .014). Baseline cigarettes per day and nicotine elimination half-life significantly predicted topography outcomes. CONCLUSIONS: Saliva NMR did not predict cigarette reinforcement during a relatively brief period of ad libitum smoking. Differences were seen by race, with White fast metabolizers by NMR having shorter time to first cigarettes compared with slow metabolizers. IMPLICATIONS: After a 90-minute period of nicotine abstinence, NMR was not significantly associated with smoking reinforcement. Slow and fast metabolizers had similar time to first cigarette, number of cigarettes smoked, total number of puffs, and tobacco consumed; however, within-race differences show that within Whites, fast metabolizers had a faster time to first cigarette than slow metabolizers.

Differences in nicotine intake and effects from electronic and combustible cigarettes among dual users.

AIM: To describe systemic nicotine exposure and subjective effects of electronic cigarettes (e-cigarettes) in people who use both e-cigarettes and cigarettes (dual users), including within-subject comparisons of e-cigarette and cigarette use. DESIGN: Two-arm, counterbalanced cross-over study. Participants used their usual brand of e-cigarette or cigarette during a standardized session in a 2-week study. SETTING: Hospital research ward, San Francisco, CA, USA. PARTICIPANTS: Thirty-six healthy (eight women, 28 men) participants. MEASUREMENTS: Plasma nicotine was analyzed by gas chromatography-tandem mass spectrometry; nicotine withdrawal, urge to smoke and vape, affective states, craving, satisfaction and psychological reward were measured by standardized questionnaires. FINDINGS: Compared with cigarettes, average maximum plasma nicotine concentration (Cmax ) was lower with e-cigarettes [6.1 ± 5.5 ng/ml, mean ± standard deviation (SD) versus 20.2 ± 11.1 ng/ml, P < 0.001] and time of maximal concentration (Tmax ) was longer (6.5 ± 5.4 versus 2.7 ± 2.4 minutes, P < 0.001). Use of both products resulted in a reduction in the severity of withdrawal symptoms, negative affect and urge to use either product. E-cigarettes were less rewarding and satisfying and reduced craving to a lesser degree than cigarettes. We were not able to detect any differences in withdrawal symptoms, affective states and urge to smoke cigarettes between e-cigarette and cigarette use. CONCLUSION: Systemic nicotine exposure was, on average, lower with single use of e-cigarettes compared with cigarettes, and e-cigarettes were judged to be less satisfying and rewarding and reduced craving less than cigarettes.

Quantitative biochemical screening for marijuana use and concordance with tobacco use in urban adolescents.

BACKGROUND: Assessing the prevalence and level of exposure (dose) of tobacco and marijuana use is important in studies of harm from use of these substances. We used biochemical analysis of urine to quantitatively assess exposure to nicotine and delta 9-tetrahydrocannabinol (THC) in adolescents receiving medical care in a public hospital METHODS: Participants were 686 adolescents between 12 and 21 years old seen at Zuckerberg San Francisco General Hospital between 2012 and 2014. Urine samples were assayed using high sensitivity liquid chromatographic assays for cotinine, a major metabolite of nicotine, and 11-nor-9-carboxy-delta 9-THC (THC-COOH), a major metabolite of THC. A commonly used immunoassay screen for THC-COOH was also performed. RESULTS: The THC-COOH immunoassay substantially underestimated THC exposure, as measured with the high sensitivity assay. THC use was detected in 25% of participants, with higher prevalence with increasing age and in non-Hispanic blacks. Active tobacco smokers had an 80% prevalence of THC use (odds ratio for cigarette smoking predicting THC use 13.2). Urine cotinine and THC-COOH were significantly correlated (r = 0.60). CONCLUSIONS: The use of a high sensitivity chromatographic urine assay provides a much more complete picture of adolescent tobacco use compared to a commonly used immunoassay. The immunoassay provides high specificity but moderate sensitivity. We confirm high concordance of tobacco and marijuana use and the high predictive value of cigarette smoking in predicting marijuana use, and provide novel data on the quantitative correlation between level of exposure to nicotine and THC. Quantitative screening of nicotine and THC exposure may enhance our understanding of addiction and harm from single and dual product use.