A Cross-Sectional Survey on Oral Nicotine Pouches: Characterizing Use-Motives, Topography, Dependence Levels, and Adverse Events.

INTRODUCTION: Oral nicotine pouches (ONPs) contain a crystalized nicotine powder instead of tobacco leaves. ONPs come in a variety of flavors and are often marketed as "tobacco-free," but research on ONP use-motivations and related experiences is limited. AIMS AND METHODS: This cross-sectional web-based survey collected self-report data on ONP use-characteristics (eg, frequency), brands and flavors used, use-motivations, dependence (Fagerström Test for Nicotine Dependence-Smokeless Tobacco [FTND-ST]), and ONP-related adverse events (AEs) experienced. RESULTS: The sample included 118 adults who reported current (past 30-day) ONP use. On average (SD), participants reported ONP use on 13 (6) days during the past month. Most participants (% of the sample) also reported the use of tobacco cigarettes (74%) and/or electronic cigarettes (53%) during the past month. Zyn (27%) and Lucy (19%) were the most currently used ONP brands with mint (23%) and tobacco (16%) as the most currently used flavors. The availability of preferred flavors was the most frequently reported (31%) ONP use-motivation. The sample demonstrated significant dependence levels (FTND-ST = 7, SD = 2). Reported AEs included mouth lesions (48%), upset stomach (39%), sore mouth (37%), sore throat (21%), and nausea (9%). Results should be interpreted in the context of study limitations, including using a relatively small and homogeneous online convenience sample. Acknowledging the limitations, this sample was deemed appropriate to include considering the novelty of the findings, the dearth of related research, and the necessity of examining foundational ONP use-characteristics (eg, topography, AEs); however, future research should consider recruiting larger and more generalizable samples. CONCLUSIONS: The availability of preferred flavors was a key ONP use-motivation in this sample. Mint and tobacco were the most currently used flavors, with Zyn and Lucy being the most currently used ONP brands. Participants reported dependence and a substantial number of ONP-related AEs. Nationally representative surveys should investigate ONP use along with outcomes included in the current study (eg, AEs) to inform ONP surveillance and policy development efforts. IMPLICATIONS: This study is among the first to assess reasons for initiating/maintaining ONP use as well as other relevant use-experiences (eg, AEs, dependence). These results highlight the role of flavors and nicotine dependence in ONP use, which are important considerations for informing ONP regulations.

Association of electronic nicotine delivery system (ENDS) and cigarette solo and dual use with alcohol-related consequences among US adults.

INTRODUCTION: Research reports a robust association between combustible cigarette use and alcohol use frequency and severity. Extension to the emerging landscape of electronic nicotine delivery system (ENDS) use is needed to inform prevention and treatment strategies. METHOD: We evaluated data from the 2020 National Survey on Drug Use and Health (NSDUH). Respondents included adults reporting cigarettes or ENDS solo or dual use. Multivariable logistic regression models evaluated associations with alcohol use disorder (AUD) and alcohol-related risky behavior (i.e., heavy drinking, binge alcohol use, and driving after drinking) compared to never use controls and respondents with a history, but not current, use of cigarettes or ENDS. RESULTS: Multivariable models showed greater odds of AUD for respondents with dual ENDS and cigarette use (AOR = 10.2), ENDS use (AOR = 6.27), cigarette use (AOR = 4.45), and a history, but not ongoing, use (AOR = 2.60) relative to respondents with no use history. Similarly, respondents with dual use (AOR = 3.94), ENDS use (AOR = 2.41), and cigarette use (AOR = 1.71) had greater odds of AUD relative to those with a history of, but not ongoing, use. The association between dual use and AUD was greater for adults ages 21-25 (AOR = 16.2) than for adults over 25 (AOR = 7.82). Cigarette and ENDS solo and dual-use were similarly associated with greater odds of alcohol-related risky behavior relative to control groups. CONCLUSION: These findings demonstrate that nicotine use and dual use may be associated with indicators of problematic drinking. These results offer insight into emerging licit polysubstance profiles and call for mechanistic research to inform prevention and intervention efforts.

Urinary Excretion Profile of Cannabinoid Analytes Following Acute Administration of Oral and Vaporized Cannabis in Infrequent Cannabis Users.

Traditionally, smoking has been the predominant method for administering cannabis, but alternative routes of administration have become more prevalent. Additionally, research examining urinary cannabinoid excretion profiles has primarily focused on 11-nor-9-carboxy-∆9-tetrahydrocannabinol (∆9-THC-COOH), a metabolite of ∆9-tetrahydrocannabinol (∆9-THC), as the primary analyte. The aim of the current study was to characterize the urinary excretion profile of ∆9-THC-COOH, ∆9-THC, ∆8-tetrahydrocannabinol (∆8-THC), 11-hydroxy-∆9-tetrahydrocannabinol (11-OH-∆9-THC), ∆9-tetrahydrocannabivarin (THCV), 11-nor-∆9-tetrahydrocannabivarin-9-carboxlic acid (THCV-COOH), cannabidiol (CBD), cannabinol (CBN) and 8,11-dihydroxytetrahydrocannabinol (8,11-diOH-∆9-THC) following controlled administration of both oral and vaporized cannabis. Participants (n = 21, 11 men/10 women) who were infrequent cannabis users ingested cannabis-containing brownies (0, 10 and 25 mg ∆9-THC) and inhaled vaporized cannabis (0, 5 and 20 mg ∆9-THC) across six double-blind outpatient sessions. Urinary concentrations of ∆9-THC analytes were measured at baseline and for 8 h after cannabis administration. Sensitivity, specificity and agreement between the three immunoassays (IAs) for ∆9-THC-COOH (cutoffs of 20, 50 and 100 ng/mL) and liquid chromatography-tandem mass spectrometry (LC-MS-MS) analyses (confirmatory cutoff concentrations of 15 ng/mL) were assessed. Urinary concentrations for ∆9-THC-COOH, ∆9-THC, 11-OH-∆9-THC, THCV, CBN and 8,11-diOH-∆9-THC all peaked at 5-6 h and 4 h following oral and vaporized cannabis administration, respectively. At each active dose, median maximum concentrations (Cmax) for detected analytes were quantitatively higher after oral cannabis administration compared to vaporized. Using current recommended federal workplace drug-testing criteria (screening via IA with a cutoff of ≥50 ng/mL and confirmation via LC-MS-MS at a cutoff of ≥15 ng/mL), urine specimens tested positive for ∆9-THC-COOH in 97.6% of oral sessions and 59.5% of vaporized sessions with active ∆9-THC doses. These data indicate that while ∆9-THC-COOH may serve as the most consistent confirmatory analyte under the current drug-testing guidelines, future work examining 11-OH-∆9-THC under similar parameters could yield an alternative analyte that may be helpful in distinguishing between licit and illicit cannabis products.

E-cigarette Solvent Ratio and Device Power Influence Ambient Air Particulate Matter.

OBJECTIVES: Electronic cigarette (ECIG)-generated aerosol contains particulate matter with a diameter less than 2.5 microns (PM2.5). Particles of this size may be injurious to the health of those who inhale them. Few studies have assessed the relationship between ECIG aerosol PM2.5 and ECIG liquid ingredients or ECIG device power. METHODS: Two studies were conducted in which participants generated aerosols with ECIGs: in one, ECIG liquids contained various vegetable glycerin/propylene glycol ratios and in the other, ECIG devices varied by electrical power output. RESULTS: Results indicate that, in general, PM2.5 increases as the ratio of vegetable glycerin to propylene glycol increases, or as device power increases. CONCLUSIONS: Regulating ECIG PM2.5 emissions to protect non-users requires an understanding of all the factors that influence these emissions.

Brain imaging of cannabinoid type I (CB1 ) receptors in women with cannabis use disorder and male and female healthy controls.

Cannabis effects are predominantly mediated by pharmacological actions on cannabinoid type 1 (CB1 ) receptors. Prior positron emission tomography (PET) studies in individuals who use cannabis included almost exclusively males. PET studies in females are needed because there are sex differences in cannabis effects, progression to cannabis use disorder (CUD), and withdrawal symptom severity. Females with CUD (N = 10) completed two double-blind cannabis smoking sessions (Session 1: placebo; Session 2: active), and acute cannabis effects were assessed. After Session 2, participants underwent 3 days of monitored cannabis abstinence; mood, craving, and withdrawal symptoms were assessed and a PET scan (radiotracer: [11 C]OMAR) followed. [11 C]OMAR Distribution volume (VT ) from these participants was compared with VT of age/BMI-similar female non-users of cannabis ("healthy controls"; N = 10). VT was also compared between female and male healthy controls (N = 7). Females with CUD displayed significantly lower VT than female healthy controls in specific brain regions (hippocampus, amygdala, cingulate, and insula). Amygdala VT was negatively correlated with mood changes (anger/hostility) during abstinence, but VT was not correlated with other withdrawal symptoms or cannabis effects. Among healthy controls, females had significantly higher VT than males in all brain regions examined. Chronic cannabis use appears to foster downregulation of CB1 receptors in women, as observed previously in men, and there are inherent sex differences in CB1 availability. Future studies should elucidate the time course of CB1 downregulation among females who use cannabis and examine the relation between CB1 availability and cannabis effects among other populations (e.g., infrequent users; medicinal users).

The failings of per se limits to detect cannabis-induced driving impairment: Results from a simulated driving study.

OBJECTIVE: Many jurisdictions use per se limits to define cannabis-impaired driving. Previous studies, however, suggest that THC concentrations in biological matrices do not reliably reflect cannabis dose and are poorly correlated with magnitude of driving impairment. Here, we first review a range of concerns associated with per se limits for THC. We then use data from a recent clinical trial to test the validity of a range of extant blood and oral fluid THC per se limits in predicting driving impairment during a simulated driving task. METHODS: Simulated driving performance was assessed in 14 infrequent cannabis users at two timepoints (30 min and 3.5 h) under three different conditions, namely controlled vaporization of 125 mg (i) THC-dominant (11% THC; <1% CBD), (ii) THC/CBD equivalent (11% THC; 11% CBD), and (iii) placebo (<1% THC & CBD) cannabis. Plasma and oral fluid samples were collected before each driving assessment. We examined whether per se limits of 1.4 and 7 ng/mL THC in plasma (meant to approximate 1 and 5 ng/mL whole blood) and 2 and 5 ng/mL THC in oral fluid reliably predicted impairment (defined as an increase in standard deviation of lateral position (SDLP) of >2 cm relative to placebo). RESULTS: For all participants, plasma and oral fluid THC concentrations were over the per se limits used 30 min after vaporizing THC-dominant or THC/CBD equivalent cannabis. However, 46% of participants failed to meet SDLP criteria for driving impairment. At 3.5 h post-vaporization, 57% of participants showed impairment, despite having low concentrations of THC in both blood (median = 1.0 ng/mL) and oral fluid (median = 1.0 ng/mL). We highlight two individual cases illustrating how (i) impairment can be minimal in the presence of a positive THC result, and (ii) impairment can be profound in the presence of a negative THC result. CONCLUSIONS: There appears to be a poor and inconsistent relationship between magnitude of impairment and THC concentrations in biological samples, meaning that per se limits cannot reliably discriminate between impaired from unimpaired drivers. There is a pressing need to develop improved methods of detecting cannabis intoxication and impairment.

E-cigarette use is prospectively associated with initiation of cannabis among college students.

E-cigarettes have dramatically increased in popularity among youth. Coincident with expanded legalization, young adults' use of cannabis (marijuana) has also steadily increased in recent years. Use of tobacco products can increase the chances of later cannabis initiation among youth. However, most longitudinal investigations of tobacco and cannabis use patterns have focused on tobacco cigarettes, included adolescents as opposed to young adults, and have only employed two timepoints. The current study examined prospective associations between e-cigarette and cannabis use in a large, diverse college sample assessed over four timepoints (freshman - senior year; N = 4,670). E-cigarette use and cannabis use were modelled in a four-wave cross-lagged model. The results showed significant bidirectional associations between both substances, even after controlling for time-varying levels of depressive symptoms, alcohol use, and polysubstance use, sensation seeking, demographic variables, concurrent associations and previous levels of use. Moreover, the significance of the predictive path from e-cigarette use to later cannabis use remained unchanged when we ran the same model, but restricted the sample to e-cigarette-only users (i.e., never cigarette smokers), whereas only one prospective path from cannabis to e-cigarette use was significant in this subsample. The current findings suggest that the association of e-cigarette use and cannabis use is likely bidirectional, with stronger support for the link from e-cigarette use to later cannabis use, above and beyond cigarette use. As e-cigarettes gain further hold of the tobacco product market share and cannabis legalization continues to expand, data such as these will be critical for informing regulatory decisions for e-cigarettes and cannabis, particularly involving their accessibility to youth and young adults.

Reasons for Transition From Electronic Cigarette Use to Cigarette Smoking Among Young Adult College Students.

PURPOSE: Longitudinal studies indicate that e-cigarette use among youth and young adults is associated with cigarette smoking initiation. The purpose of this study was to identify reasons why nonsmoking young adults transition from e-cigarette use to cigarette smoking. METHODS: The study used concept mapping (CM), a mixed-method participatory approach. Fifty-five college students who endorsed initiation of e-cigarettes before cigarettes (lifetime e-cigarette uses ≥ 100 and ≥ 100 cigarettes in lifetime) completed at least one part of the study. In an online program, participants brainstormed (n = 54) statements describing reasons for transition from e-cigarette use to cigarette smoking, sorted statements (n = 46) into conceptually similar categories, and rated (n = 47) how true each statement was for them. RESULTS: Participants generated 60 unique statements, and multidimensional scaling analysis generated eight thematic clusters characterizing reasons for transition which included the following: "Sharing with Others," "Psychological Coping," "Cigarette Appeal," "Reinforcing Effects of Cigarettes," "Accessibility," "Social Influence," "Vaping Stigma," and "Vaping Deficiencies." Participants rated "Sharing with Others" and "Psychological Coping" highest (most true) and "Vaping Deficiencies" lowest (least true). For college students, the ability to share cigarettes with peers and access cigarettes from peers and smoking for stress/anxiety management were among the top reasons for transition. CONCLUSIONS: Results suggest that tailored prevention efforts aimed at reducing cigarette smoking uptake among college students who use tobacco as a means for psychological coping or social facilitation may be warranted. Furthermore, regulatory decisions aimed at limiting cigarette appeal, reinforcing effects, and accessibility may be relevant to reducing transition.

What factors reliably predict electronic cigarette nicotine delivery?

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.

Urinary Pharmacokinetic Profile of Cannabinoids Following Administration of Vaporized and Oral Cannabidiol and Vaporized CBD-Dominant Cannabis.

Cannabis products in which cannabidiol (CBD) is the primary chemical constituent (CBD-dominant) are increasingly popular and widely available. The impact of CBD exposure on urine drug testing has not been well studied. This study characterized the urinary pharmacokinetic profile of 100-mg oral and vaporized CBD, vaporized CBD-dominant cannabis (100-mg CBD; 3.7-mg ∆9-THC) and placebo in healthy adults (n = 6) using a within-subjects crossover design. Urine specimens were collected before and for 5 days after drug administration. Immunoassay (IA) screening (cutoffs of 20, 50 and 100 ng/mL) and LC-MS-MS confirmatory tests (cutoff of 15 ng/mL) for 11-nor-9-carboxy-∆9-tetrahydrocannabinol (∆9-THCCOOH) were performed; urine was also analyzed for CBD and other cannabinoids. Urinary concentrations of CBD were higher after oral (mean Cmax: 776 ng/mL) versus vaporized CBD (mean Cmax: 261 ng/mL). CBD concentrations peaked 5 h after oral CBD ingestion and within 1 h after inhalation of vaporized CBD. After pure CBD administration, only 1 out of 218 urine specimens screened positive for ∆9-THCCOOH (20-ng/mL IA cutoff) and no specimens exceeded the 15-ng/mL confirmatory cutoff. After inhalation of CBD-dominant cannabis vapor, nine samples screened positive at the 20-ng/mL IA cutoff, and two of those samples screened positive at the 50-ng/mL IA cutoff. Four samples that screened positive (two at 20 ng/mL and two at 50 ng/mL) confirmed positive with concentrations of ∆9-THCCOOH exceeding 15 ng/mL. These data indicate that acute dosing of pure CBD will not result in a positive urine drug test using current federal workplace drug testing guidelines (50-ng/mL IA cutoff with 15-ng/mL confirmatory cutoff). However, CBD products that also contain ∆9-THC may produce positive urine results for ∆9-THCCOOH. Accurate labeling and regulation of ∆9-THC content in CBD/hemp products are needed to prevent unexpected positive drug tests and unintended drug effects.

Changing landscape of cannabis: novel products, formulations, and methods of administration.

Laws regulating cannabis have changed radically in the U.S. and abroad. Historically, users smoked dried cannabis flowers that contained Δ9-tetrahydrocannabinol (THC), the primary psychoactive component of cannabis, as the principal product constituent. Coincident with cannabis legalization and increased interest in medicinal use of the plant, there is now an expansive retail cannabis marketplace with novel cannabis products, formulations, and methods of administration. In this review, we describe emergent cannabis product chemotypes (e.g. THC-dominant, CBD-dominant, balanced or 'hybrid' with high concentrations of THC and CBD), product formulations (e.g. edibles, concentrates), and methods of administration (e.g. smoked, vaporized, orally ingested). Psychologists can play a pivotal role in studying the health impact of cannabis legalization and conducting research to inform product regulation.

Acute Pharmacokinetic Profile of Smoked and Vaporized Cannabis in Human Blood and Oral Fluid.

Currently, an unprecedented number of individuals can legally access cannabis. Vaporization is increasingly popular as a method to self-administer cannabis, partly due to perception of reduced harm compared with smoking. Few controlled laboratory studies of cannabis have used vaporization as a delivery method or evaluated the acute effects of cannabis among infrequent cannabis users. This study compared the concentrations of cannabinoids in whole blood and oral fluid after administration of smoked and vaporized cannabis in healthy adults who were infrequent users of cannabis. Seventeen healthy adults, with no past-month cannabis use, self-administered smoked or vaporized cannabis containing Δ9-tetrahydrocannabinol (THC) doses of 0, 10 and 25 mg in six double-blind outpatient sessions. Whole blood and oral fluid specimens were obtained at baseline and for 8 h after cannabis administration. Cannabinoid concentrations were assessed with enzyme-linked immunosorbent assay (ELISA) and liquid chromatography-tandem mass spectrometry (LC-MS-MS) methods. Sensitivity, specificity and agreement between ELISA and LC-MS-MS results were assessed. Subjective, cognitive performance and cardiovascular effects were assessed. The highest concentrations of cannabinoids in both whole blood and oral fluid were typically observed at the first time point (+10 min) after drug administration. In blood, THC, 11-OH-THC, THCCOOH and THCCOOH-glucuronide concentrations were dose-dependent for both methods of administration, but higher following vaporization compared with smoking. THC was detected longer in oral fluid compared to blood and THCCOOH detection in oral fluid was rare and highly erratic. For whole blood, greater detection sensitivity for ELISA testing was observed in vaporized conditions. Conversely, for oral fluid, greater sensitivity was observed in smoked sessions. Blood and/or oral fluid cannabinoid concentrations were weakly to moderately correlated with pharmacodynamic outcomes. Cannabis pharmacokinetics vary by method of inhalation and biological matrix being tested. Vaporization appears to be a more efficient method of delivery compared with smoking.

Effects of electronic cigarette liquid solvents propylene glycol and vegetable glycerin on user nicotine delivery, heart rate, subjective effects, and puff topography.

BACKGROUND: Electronic cigarettes (ECIGs) are a class of tobacco products that produce different effects (e.g., nicotine delivery), depending on the device, liquid, and behavioral factors. However, the influence of the two primary ECIG liquid solvents, propylene glycol (PG) and vegetable glycerin (VG), on ECIG acute effects is unknown. METHODS: Thirty ECIG-experienced, ≥12-h nicotine- abstinent participants completed four conditions consisting of two ECIG-use bouts (10 puffs, 30 s interpuff-interval) differing only by liquid PG:VG ratio (2PG:98VG, 20PG:80VG, 55PG:45VG, 100PG). Device power (7.3 W) and liquid nicotine concentration (18 mg/ml) remained constant. Nicotine delivery, subjective effects, heart rate (HR), and puff topography were assessed. RESULTS: In the 100PG condition, participants took shorter and smaller puffs but obtained significantly more nicotine relative to the two VG-based conditions. Total nicotine exposure (i.e., area under the curve) was also significantly higher during use of the two PG-based liquids. However, participants reported that the 100 PG liquid was significantly less "pleasant" and "satisfying" relative to the other liquids (all ps < .05). Increases in HR and decreases in abstinence symptoms (e.g., "craving") did not differ across conditions. CONCLUSIONS: PG:VG ratio influenced nicotine delivery, some subjective effects, and puff topography. Lower overall product satisfaction associated with the 100PG liquid suggests factors other than nicotine delivery (e.g., aerosol visibility) may play a role in maintaining ECIG use. Regulating ECIG acute effects such as nicotine delivery and subjective effects may require simultaneous attention to liquid PG:VG ratio as well as device, liquid, and behavioral factors known to influence these outcomes.

Nicotine emissions from electronic cigarettes: Individual and interactive effects of propylene glycol to vegetable glycerin composition and device power output.

INTRODUCTION: The power output of e-cigarettes varies considerably, as does the composition of liquids used with these products. Most e-cigarette liquids contain two primary solvents: propylene glycol (PG) and vegetable glycerin (VG). The primary aim of this study was to examine the extent to which PG and VG composition and device power interact with each other to influence e-cigarette nicotine emissions. METHODS: Aerosols were generated using a 2nd generation e-cigarette and an automatic smoking machine. Nicotine was measured in aerosols, via gas chromatography, produced from three solutions containing pure PG, pure VG, or a mixture of both solvents (50:50) across three different power settings (4.3, 6.7, and 9.6 W). RESULTS: At the lowest power setting, nicotine yield increased significantly as more PG was added to the solution. However, as device power was increased, differences in nicotine yield across liquids became less pronounced. At the highest power setting (9.6 W), nicotine yields did not differ across the three liquids examined. CONCLUSIONS: The present study demonstrated that the extent to which e-cigarette liquid PG and VG composition influences nicotine emissions is dependent on device power. Thus, device power may influence e-cigarette nicotine emissions to a greater degree relative to solvent concentrations.

Acute Effects of Smoked and Vaporized Cannabis in Healthy Adults Who Infrequently Use Cannabis: A Crossover Trial.

Importance: Vaporization is an increasingly popular method for cannabis administration, and policy changes have increased adult access to cannabis drastically. Controlled examinations of cannabis vaporization among adults with infrequent current cannabis use patterns (>30 days since last use) are needed. Objective: To evaluate the acute dose effects of smoked and vaporized cannabis using controlled administration methods. Design, Setting, and Participants: This within-participant, double-blind, crossover study was conducted from June 2016 to January 2017 at the Behavioral Pharmacology Research Unit, Johns Hopkins University School of Medicine, and included 17 healthy adults. Six smoked and vaporized outpatient experimental sessions (1-week washout between sessions) were completed in clusters (order counterbalanced across participants); dose order was randomized within each cluster. Interventions: Cannabis containing Δ9-tetrahydrocannabinol (THC) doses of 0 mg, 10 mg, and 25 mg was vaporized and smoked by each participant. Main Outcomes and Measures: Change from baseline scores for subjective drug effects, cognitive and psychomotor performance, vital signs, and blood THC concentration. Results: The sample included 17 healthy adults (mean [SD] age, 27.3 [5.7] years; 9 men and 8 women) with no cannabis use in the prior month (mean [SD] days since last cannabis use, 398 [437] days). Inhalation of cannabis containing 10 mg of THC produced discriminative drug effects (mean [SD] ratings on a 100-point visual analog scale, smoked: 46 [26]; vaporized: 69 [26]) and modest impairment of cognitive functioning. The 25-mg dose produced significant drug effects (mean [SD] ratings, smoked: 66 [29]; vaporized: 78 [24]), increased incidence of adverse effects, and pronounced impairment of cognitive and psychomotor ability (eg, significant decreased task performance compared with placebo in vaporized conditions). Vaporized cannabis resulted in qualitatively stronger drug effects for most pharmacodynamic outcomes and higher peak concentrations of THC in blood, compared with equal doses of smoked cannabis (25-mg dose: smoked, 10.2 ng/mL; vaporized, 14.4 ng/mL). Blood THC concentrations and heart rate peaked within 30 minutes after cannabis administration and returned to baseline within 3 to 4 hours. Several subjective drug effects and observed cognitive and psychomotor impairments persisted for up to 6 hours on average. Conclusions and Relevance: Vaporized and smoked cannabis produced dose-orderly drug effects, which were stronger when vaporized. These data can inform regulatory and clinical decisions surrounding the use of cannabis among adults with little or no prior cannabis exposure. Trial Registration: ClinicalTrials.gov Identifier: NCT03676166.

Association Between Initial Use of e-Cigarettes and Subsequent Cigarette Smoking Among Adolescents and Young Adults: A Systematic Review and Meta-analysis.

Importance: The public health implications of e-cigarettes depend, in part, on whether e-cigarette use affects the risk of cigarette smoking. Objective: To perform a systematic review and meta-analysis of longitudinal studies that assessed initial use of e-cigarettes and subsequent cigarette smoking. Data Sources: PubMed, EMBASE, Cochrane Library, Web of Science, the 2016 Society for Research on Nicotine and Tobacco 22nd Annual Meeting abstracts, the 2016 Society of Behavioral Medicine 37th Annual Meeting & Scientific Sessions abstracts, and the 2016 National Institutes of Health Tobacco Regulatory Science Program Conference were searched between February 7 and February 17, 2017. The search included indexed terms and text words to capture concepts associated with e-cigarettes and traditional cigarettes in articles published from database inception to the date of the search. Study Selection: Longitudinal studies reporting odds ratios for cigarette smoking initiation associated with ever use of e-cigarettes or past 30-day cigarette smoking associated with past 30-day e-cigarette use. Searches yielded 6959 unique studies, of which 9 met inclusion criteria (comprising 17 389 adolescents and young adults). Data Extraction and Synthesis: Study quality and risk of bias were assessed using the Newcastle-Ottawa Scale and the Risk of Bias in Non-randomized Studies of Interventions tool, respectively. Data and estimates were pooled using random-effects meta-analysis. Main Outcomes and Measures: Among baseline never cigarette smokers, cigarette smoking initiation between baseline and follow-up. Among baseline non-past 30-day cigarette smokers who were past 30-day e-cigarette users, past 30-day cigarette smoking at follow-up. Results: Among 17 389 adolescents and young adults, the ages ranged between 14 and 30 years at baseline, and 56.0% were female. The pooled probabilities of cigarette smoking initiation were 30.4% for baseline ever e-cigarette users and 7.9% for baseline never e-cigarette users. The pooled probabilities of past 30-day cigarette smoking at follow-up were 21.5% for baseline past 30-day e-cigarette users and 4.6% for baseline non-past 30-day e-cigarette users. Adjusting for known demographic, psychosocial, and behavioral risk factors for cigarette smoking, the pooled odds ratio for subsequent cigarette smoking initiation was 3.62 (95% CI, 2.42-5.41) for ever vs never e-cigarette users, and the pooled odds ratio for past 30-day cigarette smoking at follow-up was 4.28 (95% CI, 2.52-7.27) for past 30-day e-cigarette vs non-past 30-day e-cigarette users at baseline. A moderate level of heterogeneity was observed among studies (I2 = 60.1%). Conclusions and Relevance: e-Cigarette use was associated with greater risk for subsequent cigarette smoking initiation and past 30-day cigarette smoking. Strong e-cigarette regulation could potentially curb use among youth and possibly limit the future population-level burden of cigarette smoking.

Electronic cigarette use and indoor air quality in a natural setting.

INTRODUCTION: Secondhand smoke (SHS) from combustible cigarettes causes numerous diseases. Policies have been developed to prevent SHS exposure from indoor cigarette use to reduce health risks to non-smokers. However, fewer policies have been implemented to deter electronic cigarette (ECIG) use indoors, and limited research has examined the impact of secondhand exposure to ECIG aerosol. METHODS: Indoor air quality was measured at a 2-day ECIG event held in a large room at a hotel. Fine particulate matter (PM) was measured using 2 devices that measured concentrations of PM 2.5 µm aerodynamic diameter or smaller (PM2.5). Measurements were taken before the event, over 2 days when the event was ongoing, and the day after the event. PM2.5 measurements were also taken from the restaurant at the hotel hosting the event and a restaurant at a nearby hotel. RESULTS: During 6 time points when the event was ongoing, between 59 and 86 active ECIG users were present in the event room (room volume=4023 m3). While the event was ongoing, median PM2.5 concentrations in the event room increased from a baseline of 1.92-3.20 µg/m3 to concentrations that ranged from 311.68 µg/m3 (IQR 253.44-411.84 µg/m3) to 818.88 µg/m3 (IQR 760.64-975.04 µg/m3). CONCLUSIONS: PM2.5 concentrations observed at the ECIG event were higher than concentrations reported previously in hookah cafés and bars that allow cigarette smoking. This study indicates that indoor ECIG use exposes non-users to secondhand ECIG aerosol. Regulatory bodies should consider establishing policies that prohibit ECIG use anywhere combustible cigarette use is prohibited.

The Influence of a Mouthpiece-Based Topography Measurement Device on Electronic Cigarette User's Plasma Nicotine Concentration, Heart Rate, and Subjective Effects Under Directed and Ad Libitum Use Conditions.

INTRODUCTION: Electronic cigarettes e-cigarettes aerosolize a liquid solution often containing nicotine. e-cigarette nicotine delivery may be influenced by user puffing behaviors ("puff topography"). E-cigarette puff topography can be recorded using mouthpiece-based computerized systems. The present study sought to examine the extent to which these systems influence e-cigarette nicotine delivery and other e-cigarette associated acute effects under ad libitum use conditions. METHODS: Plasma nicotine concentration, heart rate, and subjective effects were assessed in 29 experienced e-cigarette users using their preferred e-cigarette battery and liquid (≥12mg/mL nicotine) in two sessions differing only by the presence of a mouthpiece-based device. In both sessions, participants completed a directed e-cigarette use bout (10 puffs, 30-s interpuff interval) and a 90-min ad libitum bout. Puff topography was recorded in the session with the topography mouthpiece. RESULTS: Plasma nicotine, heart rate, and subjective effects, aside from "Did the e-cigarette Taste Good?" were independent of topography measurement (higher mean taste ratings were observed in the no topography condition). Mean (SEM) plasma nicotine concentration following the ad libitum bout was 34.3ng/mL (4.9) in the no topography condition and 35.7ng/mL (4.3) in the topography condition. Longer puff durations, longer interpuff intervals, and larger puff volumes were observed in the ad libitum relative to the directed bout. CONCLUSIONS: E-cigarette use significantly increased plasma nicotine concentration and heart rate while suppressing abstinence symptoms. These effects did not differ when a topography mouthpiece was present. Future studies using ad libitum e-cigarette use bouts would facilitate understanding of e-cigarette toxicant yield. IMPLICATIONS: No prior study has examined whether mouthpiece-based topography recording devices influence e-cigarette associated nicotine delivery, heart rate, or subjective effects under ad libitum conditions or assessed ad libitum puff topography in experienced individuals using their preferred e-cigarette battery and liquid with a mouthpiece-based computerized device. E-cigarette use significantly increased plasma nicotine concentration and heart rate while suppressing abstinence symptoms. These effects did not differ when a topography mouthpiece was present. Ad libitum puff topography differed from puff topography recorded during directed puffing. These findings suggest that future studies using ad libitum use bouts would facilitate better understanding of e-cigarette toxicant yield.