Policy-relevant differences between secondhand and thirdhand smoke: strengthening protections from involuntary exposure to tobacco smoke pollutants.

Starting in the 1970s, individuals, businesses and the public have increasingly benefited from policies prohibiting smoking indoors, saving thousands of lives and billions of dollars in healthcare expenditures. Smokefree policies to protect against secondhand smoke exposure, however, do not fully protect the public from the persistent and toxic chemical residues from tobacco smoke (also known as thirdhand smoke) that linger in indoor environments for years after smoking stops. Nor do these policies address the economic costs that individuals, businesses and the public bear in their attempts to remediate this toxic residue. We discuss policy-relevant differences between secondhand smoke and thirdhand smoke exposure: persistent pollutant reservoirs, pollutant transport, routes of exposure, the time gap between initial cause and effect, and remediation and disposal. We examine four policy considerations to better protect the public from involuntary exposure to tobacco smoke pollutants from all sources. We call for (a) redefining smokefree as free of tobacco smoke pollutants from secondhand and thirdhand smoke; (b) eliminating exemptions to comprehensive smoking bans; (c) identifying indoor environments with significant thirdhand smoke reservoirs; and (d) remediating thirdhand smoke. We use the case of California as an example of how secondhand smoke-protective laws may be strengthened to encompass thirdhand smoke protections. The health risks and economic costs of thirdhand smoke require that smokefree policies, environmental protections, real estate and rental disclosure policies, tenant protections, and consumer protection laws be strengthened to ensure that the public is fully protected from and informed about the risks of thirdhand smoke exposure.

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.

Thirdhand tobacco smoke exposure increases the genetic background-dependent risk of pan-tumor development in Collaborative Cross mice.

Increasing evidence has shown that thirdhand smoke (THS) exposure is likely to induce adverse health effects. An important knowledge gap remains in our understanding of THS exposure related to cancer risk in the human population. Population-based animal models are useful and powerful in investigating the interplay between host genetics and THS exposure on cancer risk. Here, we used the Collaborative Cross (CC) mouse population-based model system, which recapitulates the genetic and phenotypic diversity observed in the human population, to assess cancer risk after a short period of exposure, between 4 and 9 weeks of age. Eight CC strains (CC001, CC019, CC026, CC036, CC037, CC041, CC042 and CC051) were included in our study. We quantified pan-tumor incidence, tumor burden per mouse, organ tumor spectrum and tumor-free survival until 18 months of age. At the population level, we observed a significantly increased pan-tumor incidence and tumor burden per mouse in THS-treated mice as compared to the control (p = 3.04E-06). Lung and liver tissues exhibited the largest risk of undergoing tumorigenesis after THS exposure. Tumor-free survival was significantly reduced in THS-treated mice compared to control (p = 0.044). At the individual strain level, we observed a large variation in tumor incidence across the 8 CC strains. CC036 and CC041 exhibited a significant increase in pan-tumor incidence (p = 0.0084 and p = 0.000066, respectively) after THS exposure compared to control. We conclude that early-life THS exposure increases tumor development in CC mice and that host genetic background plays an important role in individual susceptibility to THS-induced tumorigenesis. Genetic background is an important factor that should be taken into account when determining human cancer risk of THS exposure.

Respiratory Exposure to Thirdhand Cigarette Smoke Increases Concentrations of Urinary Metabolites of Nicotine.

INTRODUCTION: The aims of this study were to characterize particle size in a thirdhand smoke (THS) aerosol and measure the effects of controlled inhalational exposure to THS on biomarkers of tobacco smoke exposure, inflammation, and oxidative stress in human subjects. Secondhand cigarette smoke changes physically and chemically after release into the environment. Some of the resulting chemicals persist indoors as thirdhand cigarette smoke. THS that is sorbed to surfaces can emit particles back into the air. AIMS AND METHODS: Smoke particle size was measured with a scanning mobility particle sizer and condensation particle counter. Using a crossover study design, 18 healthy nonsmokers received a 3-hour inhalational exposure to THS and to filtered, conditioned air. THS was generated with a smoking machine and aged overnight in a chamber. The chamber was flushed with clean air to create the THS aerosol. The tobacco smoke metabolites cotinine, 3-hydroxycotinine and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) were measured in urine. Vascular endothelial growth factor and interleukin-6 in plasma, and 8-isoprostane in urine, were measured using enzyme-linked immunosorbent assay kits. RESULTS: Mean smoke particle size increased with aging (171 to 265 nm). We found significant increases in urinary cotinine and 3-hydroxycotinine after 3 hours of exposure to THS and no significant increases in NNAL, interleukin-6, vascular endothelial growth factor or 8-isoprostane. CONCLUSIONS: Acute inhalational exposure to 22-hour old tobacco smoke aerosol caused increases in the metabolites of nicotine but not the metabolites of the tobacco-specific nitrosamine NNK (4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone). This corroborates the utility of cotinine and NNAL for secondhand and THS exposure screening. IMPLICATIONS: This study shows that a 3-hour inhalational exposure to the tobacco smoke aerosol that forms in a room that has been smoked in and left unventilated overnight causes increases in urinary metabolites of nicotine, but not of the tobacco-specific nitrosamine NNK. This suggests that cleaning personnel and others who live and work in rooms polluted with aged or thirdhand cigarette smoke regularly may have inhalational exposures and potential health effects related to their exposure to nicotine and other smoke toxicants.

Minor Tobacco Alkaloids as Biomarkers to Distinguish Combusted Tobacco Use From Electronic Nicotine Delivery Systems Use. Two New Analytical Methods.

Biomarkers for the use of electronic nicotine delivery systems (ENDS) are desirable for studies of the health effects of electronic cigarettes and related devices. However, the aerosols inhaled from these devices do not contain substances that are unique to this class of products, i.e., substances that are not present in cigarette smoke or those that do not have common environmental or dietary sources. Consequently, identifying selective biomarkers for ENDS use remains a challenge. If co-use of conventional tobacco products can be definitively ruled out, then nicotine and its metabolites are suitable for assessing exposure. Self-reports from questionnaires are often used to obtain information on product use. But self-reports may not always be accurate, and are not amenable to obtaining quantitative information on exposure. An alternative approach is to use selective biomarkers for conventional tobacco products to definitively rule out their use. In this article, we describe two new LC-MS/MS methods for the minor tobacco alkaloids anabasine, anatabine, nicotelline, anatalline, and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), a tobacco-specific nitrosamine metabolite, all biomarkers that are selective for the use of conventional tobacco products. Applications of these biomarkers in studies of ENDS use and dual use of ENDS and conventional tobacco products are also discussed.

Tobacco-specific and combustion pollutants in settled house dust in Malta.

Aim: Most of the carcinogenic pollutants coming from tobacco smoking or other combustion processes tend to accumulate in settled house dust (SHD) over time. This study evaluated the load of these pollutants in smokers and non-smokers' houses from relatively fresh SHD collected in five different districts on the island of Malta. Methods: An improved, efficient extraction method to obtain three fractions from a 200 mg of SHD was developed. It was validated for the analysis of nicotine and polycyclic aromatic hydrocarbons (PAH) by GC-MS/MS and nicotelline and TSNA by LC-MS/MS. Kruskal-Wallis H tests were used to evaluate differences across districts, while a Mann-Whitney U test was used to check differences between smokers and non-smokers' houses. Diagnostic ratios were used to evaluate the carcinogenicity of PAH in SHD in Malta. Results: For all analytes, no statistical difference was observed across different districts, but, in smokers' houses, 97.9% of the total concentration of all target analytes found in SHD is nicotine, 0.1% is TSNA, and 2.0% is PAH. In non-smokers' houses, nicotine represents 16.8% of the load, while 0.4% and 82.8% are TSNA and PAH, respectively. The carcinogenicity of the PAH mixture in Maltese SHD, expressed as the mean benzo(a)pyrene equivalent (BaPeq) is 371 ng/g. Conclusion: Indoor activities, ventilation practices, and infiltration of outdoor pollutants contribute to a complex SHD composition. Although the BaPeq is on the lower end of carcinogenicity, the effects of a mixture including tobacco-related potent carcinogens in SHD are largely unknown. In view of indoor, continuous exposure to SHD through several pathways, further research is warranted.

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.

Secondhand smoke exposure in school children in Malta assessed through urinary biomarkers.

School children may be exposed to secondhand smoke (SHS) either at home, in transit or in social gatherings permitting smoking in their presence. Questionnaires about SHS often underestimate prevalence and extent of exposure. A more accurate tool is the use of biomarkers such as cotinine (COT) and trans-3'-hydrocycotinine (3HC) as biomarkers of SHS exposure, alongside 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), a reduction product in the body of the tobacco-specific nitrosamine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), both potent carcinogens. We measured urinary COT, 3HC and total NNAL using sensitive and specific high-performance LC-MS/MS methods. The limit of quantification (LOQ) for each assay were 0.05 ng/mL, 0.1 ng/mL and 0.25 pg/mL respectively. The aim of this study was to evaluate the exposure to SHS of school children (9-11 years), from five public schools in the island of Malta, from questionnaire information about smoking at home and verify it by urinary biomarker data of COT, 3HC and NNAL. These biomarkers were measurable in 99.4%, 95.4% and 98.3% of the participating children respectively. From the children reporting smoking at home, 11% had a history of asthma and had COT, 3HC and NNAL geometric mean concentrations double compared to the non-asthmatic group. In has been confirmed that non-smokers exposed to SHS and THS have a higher NNAL/COT ratio than the group identified as smokers according to specific and defined COT threshold levels (despite the fact that a priori, the entire study group was composed of non-smokers). The implication of high measured levels of urinary NNAL in children should be of concern given its potency. A main effects multifactor ANOVA model was developed and the children's house and school locations and the smoking frequency were statistically significant to predict the levels of the three metabolites. For 3HC only, the status of the employment of the mother was also an important predictor.

Genetic background influences the effect of thirdhand smoke exposure on anxiety and memory in Collaborative Cross mice.

Growing evidence indicates that thirdhand smoke (THS) exposure induces many adverse health effects. However, it is unclear how THS exposure affects behavior and how host genetic background modulates phenotypic changes. Here we used the Collaborative Cross (CC) mouse population-based model to assess behavioral alterations immediately after THS exposure from 4 to 9 weeks of age. We first measured anxiety-like behavior in six strains using light/dark box combined with a custom multivariate mouse tracking system. We developed an anxiety risk scoring system based on anxiety-related traits and then evaluated the THS impact on them. THS exposure significantly decreased anxiety risk in CC019 (P = 0.002) and CC051 (P = 0.009), but increased anxiety risk in CC036 (P < 0.001), while the other three strains did not show significant changes in anxiety-related traits. Such differences were driven by female mice for the six measures of anxiety-like behavior. Memory potential was measured in the same cohort of mice using the passive avoidance assay. Both THS-exposed male and female CC019 mice displayed significant memory loss compared to controls while no significant changes were found in the other five strains. This study provides strong evidence that THS exposure leads to strain-dependent changes in anxiety-like behavior and memory, suggesting that host genetic variations play a critical role in individual susceptibility to THS-induced effects.

3-Ethenylpyridine Measured in Urine of Active and Passive Smokers: A Promising Biomarker and Toxicological Implications.

In studies of tobacco toxicology, including comparisons of different tobacco products and exposure to secondhand or thirdhand smoke, exposure assessment using biomarkers is often useful. Some studies have indicated that most of the toxicity of tobacco smoke is due to gas-phase compounds. 3-Ethenylpyridine (3-EP) is a major nicotine pyrolysis product occurring in the gas phase of tobacco smoke. It has been used extensively as an environmental tracer for tobacco smoke. 3-EP would be expected to be a useful tobacco smoke biomarker as well, but nothing has been published about its metabolism and excretion in humans. In this Article we describe a solid-phase microextraction (SPME) GC-MS/MS method for determination of 3-EP in human urine and its application to the determination of 3-EP in the urine of smokers and people exposed to secondhand smoke. We conclude that 3-EP is a promising biomarker that could be useful in studies of tobacco smoke exposure and toxicology. We also point out the paucity of data on 3-EP toxicity and suggest that additional studies are needed.

Harmonization of acronyms for volatile organic compound metabolites using a standardized naming system.

Increased interest in volatile organic compound (VOC) exposure has led to an increased need for consistent, systematic, and informative naming of VOC metabolites. As analytical methods have expanded to include many metabolites in a single assay, the number of acronyms in use for a single metabolite has expanded in an unplanned and inconsistent manner due to a lack of guidance or group consensus. Even though the measurement of VOC metabolites is a well-established means to investigate exposure to VOCs, a formal attempt to harmonize acronyms amongst investigators has not been published. The aim of this work is to establish a system of acronym naming that provides consistency in current acronym usage and a foundation for creating acronyms for future VOC metabolites.

Thirdhand smoke associations with the gut microbiomes of infants admitted to a neonatal intensive care unit: An observational study.

INTRODUCTION: Microbiome differences have been found in adults who smoke cigarettes compared to non-smoking adults, but the impact of thirdhand smoke (THS; post-combustion tobacco residue) on hospitalized infants' rapidly developing gut microbiomes is unexplored. Our aim was to explore gut microbiome differences in infants admitted to a neonatal ICU (NICU) with varying THS-related exposure. METHODS: Forty-three mother-infant dyads (household member[s] smoke cigarettes, n = 32; no household smoking, n = 11) consented to a carbon monoxide-breath sample, bedside furniture nicotine wipes, infant-urine samples (for cotinine [nicotine's primary metabolite] assays), and stool collection (for 16S rRNA V4 gene sequencing). Negative binomial regression modeled relative abundances of 8 bacterial genera with THS exposure-related variables (i.e., household cigarette use, surface nicotine, and infant urine cotinine), controlling for gestational age, postnatal age, antibiotic use, and breastmilk feeding. Microbiome-diversity outcomes were modeled similarly. Bayesian posterior probabilities (PP) ≥75.0% were considered meaningful. RESULTS: A majority of infants (78%) were born pre-term. Infants from non-smoking homes and/or with lower NICU-furniture surface nicotine had greater microbiome alpha-diversity compared to infants from smoking households (PP ≥ 75.0%). Associations (with PP ≥ 75.0%) of selected bacterial genera with urine cotinine, surface nicotine, and/or household cigarette use were evidenced for 7 (of 8) modeled genera. For example, lower Bifidobacterium relative abundance associated with greater furniture nicotine (IRR<0.01 [<0.01, 64.02]; PP = 87.1%), urine cotinine (IRR = 0.08 [<0.01,2.84]; PP = 86.9%), and household smoking (IRR<0.01 [<0.01, 7.38]; PP = 96.0%; FDR p < 0.05). CONCLUSIONS: THS-related exposure was associated with microbiome differences in NICU-admitted infants. Additional research on effects of tobacco-related exposures on healthy infant gut-microbiome development is warranted.

Adhesion and Removal of Thirdhand Smoke from Indoor Fabrics: A Method for Rapid Assessment and Identification of Chemical Repositories.

Thirdhand smoke (THS) is an environmental contaminant that may cause adverse health effects in smokers and nonsmokers. Currently, time-consuming analytical methods are necessary to assess chemicals in THS repositories, like upholstered furniture and clothing. Our goal was to develop a rapid, accessible method that can be used to measure THS contamination in common household fabrics and to evaluate remediation. Cotton, terry cloth, polyester, and wool were exposed to THS for various times in a controlled laboratory environment and then extracted in various media at room temperature or 60 °C to develop an autofluorescent method to quantify THS. Concentrations of nicotine and related alkaloids in the extracts were determined using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and high-performance liquid chromatography (HPLC). The autofluorescence of extracts was proportional to the time and amount of THS exposure received by cotton and terry cloth. Extracts of polyester and wool did not show autofluorescence unless heat was applied during extraction. Nicotine, nicotine alkaloids, and TSNA concentrations were higher in THS extracts from cotton and terry cloth than extracts of polyester and wool carpet, in agreement with the autofluorescence data. For fabrics spiked with 10 mg of nicotine, extraction efficiency was much higher from terry cloth (7 mg) than polyester (0.11 mg). In high relative humidity, nicotine recovery from both cotton and polyester was 80% (~8 mg). Our results provide a simple, rapid method to assess THS contaminants in household fabrics and further show that THS extraction is influenced by fabric type, heat, and humidity. Thus, remediation of THS environments may need to vary depending on the fabric reservoirs being treated. Understanding the dynamics of THS in fabrics can help set up appropriate remediation policies to protect humans from exposure.

Effect of race and glucuronidation rates on the relationship between nicotine metabolite ratio and nicotine clearance.

OBJECTIVES: To investigate if the nicotine metabolite ratio (NMR, the ratio of nicotine metabolites 3'-hydroxycotinine/cotinine) is a reliable phenotypic biomarker for nicotine clearance across races, and as a function of differences in the rate of nicotine, cotinine and 3'-hydroxycotinine glucuronidation and UGT genotypes. METHODS: Participants [Caucasians (Whites), African Americans (Blacks) and Asian-Americans (Asians)] received an oral solution of deuterium-labeled nicotine and its metabolite cotinine. Plasma and saliva concentrations of nicotine and cotinine were used to determine oral clearances. Rates of glucuronidation were assessed from urine glucuronide/parent ratios, and UGT2B10 and UGT2B17 genotypes from DNA. RESULTS: Among the 227 participants, 96 (42%) were White, 67 (30%) Asian and 64 (28%) Black. Compared to the other two races, Whites had higher nicotine and cotinine total oral clearance, Blacks had lower nicotine and cotinine glucuronidation rates and Asians had lower 3'-hydroxycotinine glucuronidation rates. A strong positive correlation (correlations coefficients 0.77-0.84; P < 0.001) between NMR and nicotine oral clearance was found for all three races, and NMR remained a strong predictor for the nicotine oral clearance while adjusting for race, sex and age. Neither the metabolite glucuronidation ratios nor the UGT genotypes had significant effects on the ability of NMR to predict nicotine oral clearance. CONCLUSION: NMR appears to be a reliable phenotypic biomarker for nicotine clearance across races, glucuronidation phenotypes and genotypes. Racial differences in the relationships between NMR, smoking behaviors and addiction are unlikely to be related to an inadequate estimation of nicotine clearance on the basis of NMR.

Large Differences in Urinary Benzene Metabolite S-Phenylmercapturic Acid Quantitation: A Comparison of Five LC-MS-MS Methods.

Benzene is a known genotoxic carcinogen linked to many hematological abnormalities. S-phenylmercapturic acid (PHMA, N-acetyl-S-(phenyl)-L-cysteine, CAS# 4775-80-8) is a urinary metabolite of benzene and is used as a biomarker to assess benzene exposure. Pre-S-phenylmercapturic acid (pre-PHMA) is a PHMA precursor that dehydrates to PHMA at acidic pH. Published analytical methods that measure urinary PHMA adjust urine samples to a wide range of pH values using several types of acid, potentially leading to highly variable results depending on the concentration of pre-PHMA in a sample. Information is lacking on the variation in sample preparation among laboratories regularly measuring PHMA and the effect of those differences on PHMA quantitation in human urine samples. To investigate the differences in PHMA quantitation, we conducted an inter-laboratory comparison that included the analysis of 50 anonymous human urine samples (25 self-identified smokers and 25 self-identified non-smokers), quality control samples and commercially available reference samples in five laboratories using different analytical methods. Observed urinary PHMA concentrations were proportionally higher at lower pH, and results for anonymous urine samples varied widely among the methods. The method with the neutral preparation pH yielded results about 60% lower than the method using the most acidic conditions. Samples spiked with PHMA showed little variation, suggesting that the variability in results in human urine samples across methods is driven by the acid-mediated conversion of pre-PHMA to PHMA.

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.