BACKGROUND: Sex and racial/ethnic identity specific cut-points for validating tobacco use using Wave 1 (W1) of the PATH Study were published in 2020. The current study establishes predictive validity of the W1 (2014) urinary cotinine and Total Nicotine Equivalents-2 (TNE-2) cut-points on estimating Wave 4 (W4; 2017) tobacco use. METHODS: For exclusive and polytobacco cigarette use, weighted prevalence estimates based on W4 self-report alone and with exceeding the W1 cut-point were calculated to identify the percentage missed without biochemical verification. Sensitivity and specificity of W1 cut-points on W4 self-reported tobacco use status were examined. Receiver Operating Characteristic curves were used to determine the optimal W4 cut-points to distinguish P30D users from non-users, and evaluate if the cut-points significantly differed from W1. RESULTS: Agreement between W4 self-reported use and exceeding the W1 cut-points was high overall and when stratified by demographic subgroups (0.7- 4.4% of use was missed if relying on self-report alone). The predictive validity of using the W1 cut-points to classify exclusive cigarette and polytobacco cigarette use at W4 was high (>90% sensitivity and specificity, except among polytobacco Hispanic smokers). Cut-points derived using W4 data did not significantly differ from the W1 derived cut-points (e.g., W1 exclusive= 40.5 ng/mL cotinine [95% CI: 26.1-62.8], W4 exclusive = 29.9 ng/ml cotinine [95% CI: 13.5-66.4]), among most demographic subgroups. CONCLUSION: The W1 cut-points remain valid for biochemical verification of self-reported tobacco use in W4. IMPACT: Findings from can be used in clinical and epidemiological studies to reduce misclassification of cigarette smoking status.

Obesity is a common, complex, and often persistent chronic disease associated with serious health and social consequences if not treated.1 Yet, despite the disease’s complexity, treatment of obesity can be successful.2–4 The current and long-term health of 14.4 million children and adolescents is affected by obesity,5,6 making it one of the most common pediatric chronic diseases in the United States.5,7,8 | | Obesity has long been stigmatized as a reversible consequence of personal choices but has, in reality, complex genetic, physiologic, socioeconomic, and environmental contributors. An increased understanding of the impact of social determinants of health (SDoHs) on the chronic disease of obesity—along with heightened appreciation of the impact of the chronicity and severity of obesity-related comorbidities—has enabled broader and deeper understanding of the complexity of both obesity risk and treatment.9,10

You have in your hands, or at your fingertips, the first edition of the American Academy of Pediatrics clinical practice guideline for evaluation and management of children and adolescents with overweight and obesity. Putting together this guideline was no small task, and the Academy is grateful to the efforts of all the professionals who contributed to the production of this document. This work is a true testament to their passion and dedication to combatting childhood and adolescent overweight and obesity.

INTRODUCTION: The Population Assessment of Tobacco and Health (PATH) Study is a longitudinal cohort study on tobacco use behavior, attitudes and beliefs, and tobacco-related health outcomes, including biomarkers of tobacco exposure in the U.S. population. In this report we provide a summary of urinary nicotine metabolite measurements among adult users and non-users of tobacco from Wave 1 (2013-2014) of the PATH Study. METHODS: Total nicotine and its metabolites including cotinine, trans-3'-hydroxycotinine (HCTT), and other minor metabolites were measured in more than 11 500 adult participants by liquid chromatography tandem mass spectrometry methods. Weighted geometric means (GM) and least square means from statistical modeling were calculated for non-users and users of various tobacco products. RESULTS: Among daily users, the highest GM concentrations of nicotine, cotinine and HCTT were found in exclusive smokeless tobacco users, and the lowest in exclusive e-cigarette users. Exclusive combustible product users had intermediate concentrations, similar to those found in users of multiple products (polyusers). Concentrations increased with age within the categories of tobacco users, and differences associated with gender, race/ethnicity and educational attainment were also noted among user categories. Recent (past 12 months) former users had GM cotinine concentrations that were more than threefold greater than never users. CONCLUSIONS: These urinary nicotine metabolite data provide quantification of nicotine exposure representative of the entire US adult population during 2013-2014 and may serve as a reference for similar analyses in future measurements within this study. IMPLICATIONS: Nicotine and its metabolites in urine provide perhaps the most fundamental biomarkers of recent nicotine exposure. This report, based on Wave 1 of the Population Assessment of Tobacco and Health (PATH) Study, provides the first nationally representative data describing urinary nicotine biomarker concentrations in both non-users, and users of a variety of tobacco products including combustible, e-cigarette and smokeless products. These data provide a urinary biomarker concentration snapshot in time for the entire US population during 2013-2014, and will provide a basis for comparison with future results from continuing, periodic evaluations in the PATH Study.

Limited data are available for how biomarkers of tobacco exposure (BOE) change when cigarette smokers transition to using electronic nicotine delivery systems (ENDS). Using biomarker data from Waves 1 (20132014) and 2 (20142015) of the PATH Study, we examined how mean BOE concentrations, including metabolites of nicotine, tobacco-specific nitrosamines (TSNA), polycyclic aromatic hydrocarbons (PAH), and volatile organic compounds (VOCM) and metals, changed when 2475 adult smokers transitioned to using ENDS or quit tobacco products. Exclusive smokers who transitioned to dual use had a significant decrease in NNAL (4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol), but not nicotine metabolites, most PAHs, metals, or VOCMs. Exclusive smokers who became dual users had significant reductions in total nicotine equivalents, NNAL, and 2CyEMA (acrylonitrile metabolite), but only in those who reduced cigarettes per day (CPD) by >=50%. Smokers who transitioned to exclusive ENDS use had significant reductions in most TSNAs, PAHs, and VOCMs; however, nicotine metabolites did not decrease in dual users who became exclusive ENDS users. Smokers who quit tobacco use had significant decreases in nicotine metabolites, all TSNAs, most PAHs, and most VOCMs. Cigarette smokers who became dual users did not experience significant reductions in most BOEs. Reductions were impacted by changes in CPD. However, transitioning from smoking to no tobacco or exclusive ENDS use was associated with reduced exposure to most BOEs measured. Future analyses could incorporate additional waves of PATH data and examine changes in biomarker exposure by ENDS device type and CPD. 2022 by the authors. Licensee MDPI, Basel, Switzerland.

INTRODUCTION: The Population Assessment of Tobacco and Health (PATH) Study is a nationally representative cohort of tobacco product users and nonusers. The study's main purpose is to obtain longitudinal epidemiologic data on tobacco use and exposure among the US population. AIMS AND METHODS: Nicotine biomarkers-cotinine (COT) and trans-3'-hydroxycotinine (HCT)-were measured in blood samples collected from adult daily tobacco users and nonusers during Wave 1 of the PATH Study (2013-2014; n = 5012; one sample per participant). Participants' tobacco product use and exposure to secondhand smoke were categorized based on questionnaire responses. Nonusers were subdivided into never users and recent former users. Daily tobacco users were classified into seven tobacco product use categories: exclusive users of cigarette, smokeless tobacco, electronic cigarette, cigar, pipe, and hookah, as well as polyusers. We calculated sample-weighted geometric mean (GM) concentrations of cotinine, HCT, and the nicotine metabolite ratio (NMR) and evaluated their associations with tobacco use with adjustment for potential confounders. RESULTS: The GMs (95% confidence intervals) of COT and HCT concentrations for daily tobacco users were 196 (184 to 208) and 72.5 (67.8 to 77.4) ng/mL, and for nonusers they were 0.033 (0.028 to 0.037) and 0.021 (0.018 to 0.023) ng/mL. Exclusive smokeless tobacco users had the highest COT concentrations of all user groups examined. The GM NMR in daily users was 0.339 (95% confidence interval: 0.330 to 0.350). CONCLUSIONS: These nationally representative estimates of serum nicotine biomarkers could be the basis for reference ranges characterizing nicotine exposure for daily tobacco users and nonusers in the US adult population. IMPLICATIONS: This report summarizes the serum nicotine biomarker measurements in Wave 1 of the PATH Study. We are reporting the first estimates of HCT in serum for daily tobacco users and nonusers in the noninstitutionalized, civilian US adult population; the first nationally representative serum COT estimates for daily exclusive users of different tobacco products and daily polyusers; and the first nationally representative estimate of the serum NMR in daily tobacco users by age, race/ethnicity, and sex.

INTRODUCTION: This study examined the predictive relationships between biomarkers of nicotine exposure and 16-item self-reported level of tobacco dependence (TD) and subsequent tobacco use outcomes. METHODS: The Population Assessment of Tobacco and Health (PATH) Study surveyed adult current established tobacco users who provided urine biospecimens at Wave 1 (September 2013-December 2014) and completed the Wave 2 (October 2014-October 2015) interview (n=6872). Mutually exclusive user groups at Wave 1 included: Cigarette Only, E-cigarette Only, Cigar Only, Hookah Only, Smokeless Tobacco Only, Cigarette Plus E-cigarette, multiple tobacco product users who smoked cigarettes, and multiple tobacco product users who did not smoke cigarettes. Total Nicotine Equivalents (TNE-2) and TD were measured at Wave 1. Approximate one-year outcomes included frequency/quantity used, quitting, and adding/switching to different tobacco products. RESULTS: For Cigarette Only smokers and multiple tobacco product users who smoked cigarettes, higher TD and TNE-2 were associated with: a tendency to smoke more, smoking more frequently over time, decreased likelihood of switching away from cigarettes, and decreased probability of quitting after one year. For other product user groups, Wave 1 TD and/or TNE-2 were less consistently related to changes in quantity and frequency of product use, or for adding or switching products, but higher TNE-2 was more consistently predictive of decreased probability of quitting. CONCLUSIONS: Self-reported TD and nicotine exposure assess common and independent aspects of dependence in relation to tobacco use behaviors for cigarette smokers. For other product user groups, nicotine exposure is a more consistent predictor of quitting than self-reported TD. IMPLICATIONS: This study suggests that smoking cigarettes leads to the most coherent pattern of associations consistent with a syndrome of TD. Because cigarettes continue to be prevalent and harmful, efforts to decrease their use may be accelerated via conventional means (e.g., smoking cessation interventions and treatments), but also perhaps by decreasing their dependence potential. The implications for noncombustible tobacco products are less clear as the stability of tobacco use patterns that include products such as e-cigarettes continue to evolve. TD, nicotine exposure measures, and consumption could be used in studies that attempt to understand and predict product-specific tobacco use behavioral outcomes.

BACKGROUND: Former smokers who currently use e-cigarettes have lower concentrations of biomarkers of tobacco toxicant exposure than current smokers. It is unclear whether tobacco toxicant exposure reductions may lead to health risk reductions. METHODS: We compared inflammatory biomarkers (high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), fibrinogen, soluble intercellular adhesion molecule-1 (sICAM-1)) and an oxidative stress marker (F2-isoprostane) among 3,712 adult participants in Wave 1 (2013-2014) of the Population Assessment of Tobacco and Health Study by tobacco user groups: dual users of cigarettes and e-cigarettes; former smokers who currently use e-cigarettes-only; current cigarette-only smokers; former smokers who do not currently use any tobacco; and never tobacco users. We calculated geometric means (GMs) and estimated adjusted geometric mean ratios (GMRs). RESULTS: Dual users experienced greater concentration of F2-isoprostane than current cigarette-only smokers (GMR 1.09 [95%CI 1.03, 1.15]). Biomarkers were similar between former smokers who currently use e-cigarettes and both former smokers who do not use any tobacco and never tobacco users, but among these groups most biomarkers were lower than those of current cigarette-only smokers. The concentration of F2-isoprostane decreased by time since smoking cessation among both exclusive e-cigarette users (p-trend=0.03) and former smokers who do not currently use any tobacco (p-trend=0.0001). CONCLUSIONS: Dual users have greater concentration of F2-isoprostane than smokers. Exclusive e-cigarette users have biomarker concentrations that are similar to those of former smokers who do not currently use tobacco, and lower than those of exclusive cigarette smokers. IMPACT: This study contributes to an understanding of the health effects of e-cigarettes.

A method to achieve accurate measurement of unmetabolized volatile organic compounds (VOCs) in urine was developed and characterized. The method incorporates a novel preanalytical approach of adding isotopically labeled internal standard (ISTD) analogues directly to the collection container at the point of collection to compensate for analyte loss to the headspace and the collection container surfaces. Using this approach, 45 toxic VOCs ranging in water solubility and boiling point were evaluated and analyzed by headspace solid-phase microextraction/gas chromatography-mass spectrometry. Results show that urine VOCs could be equally lost to the container headspace as to the container surface suggesting similarity of these two regions as partition phases. Surface adsorption loss was found to trend with compound water solubility. In particular, with no headspace, more nonpolar VOCs experienced substantial losses (e.g., 48% for hexane) in a standard 120 mL urine cup at concentrations in the low- and sub-ppb range. The most polar VOCs evaluated (e.g., tetrahydrofuran) showed no significant loss. Other commonly practiced methods for urine sample collection and analysis such as aliquoting, specimen freezing, and use of surrogate ISTD were found to significantly bias results. With this method, we achieved errors ranging from -8.0 to 4.8% of spiked urine specimens. Paired urine and blood specimens from cigarette smokers were compared to assess this method.

BACKGROUND: Determine the overall, sex-, and racially/ethnically-appropriate population-level cotinine and total nicotine equivalents (TNE-2, the molar sum of the two major nicotine metabolites) cut-points to distinguish tobacco users from non-users across multiple definitions of use (e.g., exclusive vs. polytobacco, and daily vs. non-daily). METHODS: Using Wave 1 (2013-2014) of the U.S. Population Assessment of Tobacco and Health (PATH) Study, we conducted weighted Receiver Operating Curve (ROC) analysis to determine the optimal urinary cotinine and TNE-2 cut-points, stratified by sex and race/ethnicity. RESULTS: For past 30-day exclusive cigarette users, the cotinine cut-point that distinguished them from non-users was 40.5 ng/mL, with considerable variation by sex (male: 22.2 ng/mL; female: 43.1 ng/mL) and between racial/ethnic groups (non-Hispanic other: 5.2 ng/mL; non-Hispanic black: 297.0 ng/mL). A similar, but attenuated, pattern emerged when assessing polytobacco cigarette users (overall cut-point= 39.1 ng/mL, range= 5.5 ng/mL- 80.4 ng/mL) and any tobacco users (overall cut-point= 39.1 ng/mL, range= 4.8 ng/mL- 40.0 ng/mL). Using TNE-2, which is less impacted by racial differences in nicotine metabolism, produced a comparable pattern of results although reduced the range magnitude. CONCLUSIONS: Due to similar frequency of cigarette use among polytobacco users, overall cut-points for exclusive cigarette use were not substantially different from cut-points that included polytobacco cigarette use or any tobacco use. Results revealed important differences in sex and race/ethnicity appropriate cut-points when evaluating tobacco use status and established novel urinary TNE-2 cut-points. IMPACT: These cut-points may be used for biochemical verification of self-reported tobacco use in epidemiologic studies and clinical trials.

INTRODUCTION: Concurrent use of tobacco cigarettes and e-cigarettes ("dual use") is common among tobacco users. Little is known about differences in demographics and toxicant exposure among subsets of dual users. AIMS AND METHODS: We analyzed data from adult dual users (current every/some day users of tobacco cigarettes and e-cigarettes, n = 792) included in the PATH Study Wave 1 (2013-2014) and provided urine samples. Samples were analyzed for biomarkers of exposure to nicotine and selected toxicants (tobacco-specific nitrosamine NNK [NNAL], lead, cadmium, naphthalene [2-naphthol], pyrene [1-hydroxypyrene], acrylonitrile [CYMA], acrolein [CEMA], and acrylamide [AAMA]). Subsets of dual users were compared on demographic, behavioral, and biomarker measures to exclusive cigarette smokers (n = 2411) and exclusive e-cigarette users (n = 247). RESULTS: Most dual users were predominant cigarette smokers (70%), followed by daily dual users (13%), non-daily concurrent dual users (10%), and predominant vapers (7%). Dual users who smoked daily showed significantly higher biomarker concentrations compared with those who did not smoke daily. Patterns of e-cigarette use had little effect on toxicant exposure. Dual users with high toxicant exposure were generally older, female, and smoked more cigarettes per day. Dual users who had low levels of biomarkers of exposure were generally younger, male, and smoked non-daily. CONCLUSIONS: In 2013-2014, most dual users smoked cigarettes daily and used e-cigarettes occasionally. Cigarette smoking appears to be the primary driver of toxicant exposure among dual users, with little-to-no effect of e-cigarette use on biomarker levels. Results reinforce the need for dual users to stop smoking tobacco cigarettes to reduce toxicant exposure. IMPLICATIONS: With considerable dual use of tobacco cigarettes and e-cigarettes in the United States, it is important to understand differences in toxicant exposure among subsets of dual users, and how these differences align with user demographics. Findings suggest most dual users smoke daily and use e-cigarettes intermittently. Low exposure to toxicants was most common among younger users, males, and intermittent smokers; high exposure to toxicants was most common among older users, females, and heavier cigarette smokers. Results underscore the heterogeneity occurring within dual users, and the need to quit smoking cigarettes completely in order to reduce toxicant exposure.

INTRODUCTION: The tobacco-specific nitrosamines (TSNAs) are an important group of carcinogens found in tobacco and tobacco smoke. To describe and characterize the levels of TSNAs in the Population Assessment of Tobacco and Health (PATH) Study Wave 1 (2013-2014), we present four biomarkers of TSNA exposure: N'-nitrosonornicotine, N'-nitrosoanabasine, N'-nitrosoanatabine, and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) which is the primary urinary metabolite of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone. METHODS: We measured total TSNAs in 11 522 adults who provided urine using automated solid-phase extraction coupled to isotope dilution liquid chromatography-tandem mass spectrometry. After exclusions in this current analysis, we selected 11 004 NNAL results, 10 753 N'-nitrosonornicotine results, 10 919 N'-nitrosoanatabine results, and 10 996 N'-nitrosoanabasine results for data analysis. Geometric means and correlations were calculated using SAS and SUDAAN. RESULTS: TSNA concentrations were associated with choice of tobacco product and frequency of use. Among established, every day, exclusive tobacco product users, the geometric mean urinary NNAL concentration was highest for smokeless tobacco users (993.3; 95% confidence interval [CI: 839.2, 1147.3] ng/g creatinine), followed by all types of combustible tobacco product users (285.4; 95% CI: [267.9, 303.0] ng/g creatinine), poly tobacco users (278.6; 95% CI: [254.9, 302.2] ng/g creatinine), and e-cigarette product users (6.3; 95% CI: [4.7, 7.9] ng/g creatinine). TSNA concentrations were higher in every day users than in intermittent users for all the tobacco product groups. Among single product users, exposure to TSNAs differed by sex, age, race/ethnicity, and education. Urinary TSNAs and nicotine metabolite biomarkers were also highly correlated. CONCLUSIONS: We have provided PATH Study estimates of TSNA exposure among US adult users of a variety of tobacco products. These data can inform future tobacco product and human exposure evaluations and related regulatory activities.

BACKGROUND: Monitoring population-level toxicant exposures from smokeless tobacco (SLT) use is important for assessing population health risks due to product use. In this study, we assessed tobacco biomarkers of exposure (BOEs) among SLT users from the Wave 1 (2013-14) of the Population Assessment of Tobacco and Health (PATH) Study. METHODS: Urinary biospecimens were collected from adults aged 18 and older. Biomarkers of nicotine, tobacco-specific nitrosamines (TSNAs), polycyclic aromatic hydrocarbons (PAHs), volatile organic compounds (VOCs), metals, and inorganic arsenic were analyzed and reported among exclusive current established SLT users in comparison to exclusive current established cigarette smokers, dual SLT and cigarette users, and never tobacco users. RESULTS: In general, SLT users (n=448) have significantly higher concentrations of biomarkers of exposure to nicotine, TSNAs and PAHs compared to never tobacco users; significant dose-response relationships between frequency of SLT use and biomarker concentrations were also reported among exclusive SLT daily users. Exclusive SLT daily users have higher geometric mean concentrations of total nicotine equivalent-2 (TNE2) and TSNAs than exclusive cigarette daily smokers. In contrast, geometric mean concentrations of PAHs and VOCs were substantially lower among exclusive SLT daily users than exclusive cigarette daily smokers. CONCLUSIONS: Our study produced a comprehensive assessment of SLT product use and 52 biomarkers of tobacco exposure. Compared to cigarette smokers, SLT users experience greater concentrations of some tobacco toxicants, including nicotine and TSNAs. IMPACT: Our data add information on the risk assessment of exposure to SLT-related toxicants. High levels of harmful constituents in SLT remain a health concern.

BACKGROUND: Given the diverse cigar market and limited data on biomarker patterns by cigar type, we compared biomarkers of nicotine and tobacco toxicants among cigar smokers and other groups. METHODS: Using Wave 1 urinary biomarker data from 5,604 adults in the Population Assessment of Tobacco and Health (PATH) Study, we compared geometric mean concentrations among cigar-only smokers (all cigars and separately for traditional, cigarillo, and filtered cigars), cigarette-only smokers, dual cigar/cigarette smokers, and never users of tobacco. We calculated geometric mean ratios (GMR) comparing groups with never users adjusting for sex, age, race/ethnicity, education and creatinine. RESULTS: Some day cigar-only smokers had lower biomarker concentrations than every day cigar-only smokers but higher than never users. Every day cigar-only smokers (n=61) had lower TNE-2 (cotinine+trans-3'-hydroxycotinine) compared to every day cigarette-only (n=2217;p<0.0001) and dual cigar/cigarette smokers (n=601;p<0.0001). Several biomarkers, including NNAL (NNK metabolite) and CYMA (metabolite of acrylonitrile), were comparable in these groups. In exploratory analyses, every day filtered cigar-only (n=7) smokers had higher biomarker concentrations compared to every day traditional cigar-only smokers (n=12) and cigarillo-only smokers (n=24). Every day smokers of each cigar type were similar to exclusive cigarette smokers. For some biomarkers, particularly for every day filtered cigar-only smokers, concentrations were higher. CONCLUSIONS: For some biomarkers, every day cigar-only smokers were comparable to every day cigarette-only smokers. Exploratory analyses suggest that biomarkers vary by cigar type with every day filtered cigar-only smokers having the highest concentrations. IMPACT: High exposure to harmful constituents among cigar smokers is a continuing health issue.

Importance: Use of electronic cigarettes (e-cigarettes) is increasing. Measures of exposure to known tobacco-related toxicants among e-cigarette users will inform potential health risks to individual product users. Objectives: To estimate concentrations of tobacco-related toxicants among e-cigarette users and compare these biomarker concentrations with those observed in combustible cigarette users, dual users, and never tobacco users. Design, Setting, and Participants: A population-based, longitudinal cohort study was conducted in the United States in 2013-2014. Cross-sectional analysis was performed between November 4, 2016, and October 5, 2017, of biomarkers of exposure to tobacco-related toxicants collected by the Population Assessment of Tobacco and Health Study. Participants included adults who provided a urine sample and data on tobacco use (N = 5105). Exposures: The primary exposure was tobacco use, including current exclusive e-cigarette users (n = 247), current exclusive cigarette smokers (n = 2411), and users of both products (dual users) (n = 792) compared with never tobacco users (n = 1655). Main Outcomes and Measures: Geometric mean concentrations of 50 individual biomarkers from 5 major classes of tobacco product constituents were measured: nicotine, tobacco-specific nitrosamines (TSNAs), metals, polycyclic aromatic hydrocarbons (PAHs), and volatile organic compounds (VOCs). Results: Of the 5105 participants, most were aged 35 to 54 years (weighted percentage, 38%; 95% CI, 35%-40%), women (60%; 95% CI, 59%-62%), and non-Hispanic white (61%; 95% CI, 58%-64%). Compared with exclusive e-cigarette users, never users had 19% to 81% significantly lower concentrations of biomarkers of exposure to nicotine, TSNAs, some metals (eg, cadmium and lead), and some VOCs (including acrylonitrile). Exclusive e-cigarette users showed 10% to 98% significantly lower concentrations of biomarkers of exposure, including TSNAs, PAHs, most VOCs, and nicotine, compared with exclusive cigarette smokers; concentrations were comparable for metals and 3 VOCs. Exclusive cigarette users showed 10% to 36% lower concentrations of several biomarkers than dual users. Frequency of cigarette use among dual users was positively correlated with nicotine and toxicant exposure. Conclusions and Relevance: Exclusive use of e-cigarettes appears to result in measurable exposure to known tobacco-related toxicants, generally at lower levels than cigarette smoking. Toxicant exposure is greatest among dual users, and frequency of combustible cigarette use is positively correlated with tobacco toxicant concentration. These findings provide evidence that using combusted tobacco cigarettes alone or in combination with e-cigarettes is associated with higher concentrations of potentially harmful tobacco constituents in comparison with using e-cigarettes alone.

BACKGROUND: Polycyclic aromatic hydrocarbons (PAHs) are environmental pollutants formed from incomplete combustion of organic matter; some PAHs are carcinogens. Smoking, diet, and other activities contribute to exposure to PAHs. Exposure data to PAHs among combustible tobacco product users (e.g. cigarette smokers) exist; however, among non-combustible tobacco products users (e.g., e-cigarette users), such data are rather limited. OBJECTIVES: We sought to evaluate exposure to PAHs among participants in Wave 1 (2013-2014) of the Population Assessment of Tobacco and Health (PATH) Study based on the type of tobacco product (combustible vs non-combustible), and frequency and intensity of product use. METHODS: We quantified seven PAH urinary biomarkers in 11,519 PATH Study participants. From self-reported information, we categorized 8327 participants based on their use of tobacco products as never-tobacco user (never user, n=1700), exclusive current established combustible products user (combustible products user, n=5767), and exclusive current established non-combustible products user (non-combustible products user, n=860). We further classified tobacco users as exclusive cigarette user (cigarette user, n=3964), exclusive smokeless product user (SLT user, n=509), and exclusive e-cigarette user (e-cigarette user, n=280). Last, we categorized frequency of product use (everyday vs some days) and time since use (last hour, within 3days, over 3days). We calculated geometric mean (GM) concentrations, and evaluated associations between tobacco product user categories and PAH biomarkers concentrations. RESULTS: Combustible products users had significantly higher GMs of all biomarkers than non-combustible products users and never users; non-combustible products users had significantly higher GMs than never users for four of seven biomarkers. For all biomarkers examined, cigarette users had the highest GMs compared to other tobacco-product users. Interestingly, GMs of 2-hydroxyfluorene, 3-hydroxyfluorene and summation operator2,3-hydroxyphenanthrene were significantly higher in SLT users than in e-cigarette users; 3-hydroxyfluorene and 1-hydroxypyrene were also significantly higher in e-cigarette and SLT users than in never users. Everyday cigarette and SLT users had significantly higher GMs for most biomarkers than some days' users; cigarette and SLT users who used the product in the last hour had significantly higher GMs of most biomarkers than other occasional cigarette or SLT users respectively. By contrast, everyday e-cigarette users' GMs of most biomarkers did not differ significantly from those in some days' e-cigarette users; we did not observe clear trends by time of last use among e-cigarette users. CONCLUSIONS: Users of tobacco products had higher PAH urinary biomarker concentrations compared to never users, and concentrations differed by type and frequency of tobacco product use.