Background: Volatile organic compounds (VOCs) are major components of air pollution and tobacco smoke, two known risk factors for cardiovascular diseases. VOCs are ubiquitous in the environment and originate from a wide range of sources, including the burning of biomass, fossil fuels, and consumer products. Direct evidence for associations between specific VOCs and ischemic heart disease (IHD) mortality in the general population is scarce. Methods: In a case-cohort study (stratified by age groups, sex, residence, and tobacco smoking), nested within the population-based Golestan cohort study (n = 50,045, 40–75 years, 58% women, enrollment: 2004–2008) in northeastern Iran, we measured urinary concentrations of 20 smoking-related VOC biomarkers using ultra high-performance liquid chromatography coupled with electrospray ionization tandem mass spectrometry. We calculated hazard ratio (HR) and 95% confidence interval (CI) for their associations with IHD mortality during follow-up to 2018, using Cox regression models adjusted for age, ethnicity, education, marital status, body mass index, physical activity, wealth, and urinary cotinine. Results: There were 575 non-cases from random subcohort and 601 participants who died from IHD, mean (standard deviation) age, 58.2 (9.3) years, with a median of 8.4 years follow-up. Significant associations [3rd vs. 1st tertile, HR (95% CI), P for trend] were observed between biomarkers of acrylamide [1.68(1.05,2.69), 0.025], acrylonitrile [2.06(1.14,3.72), 0.058], acrolein [1.98(1.30,3.01), 0.003 and 2.44(1.43,4.18), 0.002], styrene/ethylbenzene [1.83(1.19,2.84), 0.007 and 1.44(1.01,2.07), 0.046], dimethylformamide/methylisocyanate [2.15(1.33,3.50), 0.001], and 1,3butadiene [2.35(1.52,3.63),<0.001] and IHD mortality. These associations were independent of tobacco smoking, and they were only present in the non-smoking subgroup. Conclusion: Our findings provide direct evidence for associations between exposure to several VOCs with widespread household and commercial use and IHD mortality many years after these exposures. These results highlight the importance of VOC exposure in the general population as a risk factor for cardiovascular diseases and underline the importance of bio-monitoring non-tobacco VOC exposure. © 2024

Liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS-MS) with stable isotope-labeled internal standards (SIL-ISs) is the gold standard for quantitative analysis of drugs and metabolites in complex biological samples. Significant isotopic effects associated with deuterium labeling often cause the deuterated IS to elute at a different retention time from the target analyte, diminishing its capability to compensate for matrix effects. In this study, we systematically compared the analytical performance of deuterated (2H) SIL-IS to non-deuterated (13C and 15N) SIL-ISs for quantifying urinary 2-methylhippuric acid (2MHA) and 4-methylhippuric acid (4MHA), biomarkers of xylenes exposure, with an LC-ESI-MS-MS assay. Analytical method comparison between ISs demonstrated a quantitative bias for urinary 2MHA results, with concentrations generated with 2MHA-[2H7] on average 59.2% lower than concentrations generated with 2MHA-[13C6]. Spike accuracy, measured by quantifying the analyte-spiked urine matrix and comparing the result to the known spike concentration, determined that 2MHA-[2H7] generated negatively biased urinary results of -38.4%, whereas no significant bias was observed for 2MHA-[13C6]. Post-column infusion demonstrated that ion suppression experienced by 2MHA and 2MHA-[13C6] was not equally experienced by 2MHA-[2H7], explaining the negatively biased 2MHA results. The quantitation of urinary 4MHA results between ISs exhibited no significant quantitative bias. These results underscore the importance of the careful selection of ISs for targeted quantitative analysis in complex biological samples.

Nitrate levels are increasing in water resources across the United States and nitrate ingestion from drinking water has been associated with adverse health risks in epidemiologic studies at levels below the maximum contaminant level (MCL). In contrast, dietary nitrate ingestion has generally been associated with beneficial health effects. Few studies have characterized the contribution of both drinking water and dietary sources to nitrate exposure. The Agricultural Health Study is a prospective cohort of farmers and their spouses in Iowa and North Carolina. In 2018-2019, we assessed nitrate exposure for 47 farmers who used private wells for their drinking water and lived in 8 eastern Iowa counties where groundwater is vulnerable to nitrate contamination. Drinking water and dietary intakes were estimated using the National Cancer Institute Automated Self-Administered 24-Hour Dietary Assessment tool. We measured nitrate in tap water and estimated dietary nitrate from a database of food concentrations. Urinary nitrate was measured in first morning void samples in 2018-19 and in archived samples from 2010 to 2017 (minimum time between samples: 2 years; median: 7 years). We used linear regression to evaluate urinary nitrate concentrations in relation to total nitrate, and drinking water and dietary intakes separately. Overall, dietary nitrate contributed the most to total intake (median: 97 %; interquartile range [IQR]: 57-99 %). Among 15 participants (32 %) whose drinking water nitrate concentrations were at/above the U.S. Environmental Protection Agency MCL (10 mg/L NO(3)-N), median intake from water was 44 % (IQR: 26-72 %). Total nitrate intake was the strongest predictor of urinary nitrate concentrations (R(2) = 0.53). Drinking water explained a similar proportion of the variation in nitrate excretion (R(2) = 0.52) as diet (R(2) = 0.47). Our findings demonstrate the importance of both dietary and drinking water intakes as determinants of nitrate excretion.

In 2019, nearly 3000 U.S. residents developed severe lung injury associated with recent use of e-cigarette or vaping products. The Centers for Disease Control and Prevention responded to the outbreak, which was formally defined as e-cigarette, or vaping, product use-associated lung injury (EVALI). Centers for Disease Control and Prevention Laboratory rapidly developed assays to analyze potentially harmful and addictive substances in bronchoalveolar lavage (BAL) fluid collected from EVALI case patients. This report describes the development and validation of a high-throughput isotope-dilution high performance liquid chromatography-tandem mass spectrometry method for measuring two nicotine biomarkers, cotinine (COT) and trans-3'-hydroxycotinine (HCT), in bronchoalveolar lavage fluid samples. COT and HCT are the major metabolites of nicotine, the addictive alkaloid presents in tobacco products. This method had good specificity and sensitivity. The limit of detection is 0.033 and 0.0165 ng/mL for COT and HCT, respectively, using only 200 µL of sample volume. The within-run and between-run precision were 2-10%. The overall accuracy, calculated from recovery in three different sample matrices spiked at three concentrations, was 94.8% and 93.6% for COT and HCT, respectively. This novel HPLC-MS-MS method was utilized to characterize recent tobacco exposure in EVALI case patients. This method is useful for characterizing tobacco exposure that may be related to acute and chronic lung injury.

Tobacco use is a major cause of preventable morbidity and mortality globally. Tobacco products, including smokeless tobacco (ST), generally contain tobacco-specific N-nitrosamines (TSNAs), such as N′-nitrosonornicotine (NNN) and 4-(methylnitrosamino)-1-(3-pyridyl)-butanone (NNK), which are potent carcinogens that cause mutations in critical genes in human DNA. This review covers the series of biochemical and chemical transformations, related to TSNAs, leading from tobacco cultivation to cancer initiation. A key aim of this review is to provide a greater understanding of TSNAs: their precursors, the microbial and chemical mechanisms that contribute to their formation in ST, their mutagenicity leading to cancer due to ST use, and potential means of lowering TSNA levels in tobacco products. TSNAs are not present in harvested tobacco but can form due to nitrosating agents reacting with tobacco alkaloids present in tobacco during certain types of curing. TSNAs can also form during or following ST production when certain microorganisms perform nitrate metabolism, with dissimilatory nitrate reductases converting nitrate to nitrite that is then released into tobacco and reacts chemically with tobacco alkaloids. When ST usage occurs, TSNAs are absorbed and metabolized to reactive compounds that form DNA adducts leading to mutations in critical target genes, including the RAS oncogenes and the p53 tumor suppressor gene. DNA repair mechanisms remove most adducts induced by carcinogens, thus preventing many but not all mutations. Lastly, because TSNAs and other agents cause cancer, previously documented strategies for lowering their levels in ST products are discussed, including using tobacco with lower nornicotine levels, pasteurization and other means of eliminating microorganisms, omitting fermentation and fire-curing, refrigerating ST products, and including nitrite scavenging chemicals as ST ingredients. ©, This work was authored as part of the Contributor's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.

BACKGROUND: Studying carcinogens in tobacco and non-tobacco sources may be key to understanding the pathogenesis and geographic distribution of esophageal cancer. METHODS: Golestan Cohort Study (GCS) has been conducted since 2004 in a region with high rates of esophageal squamous cell carcinoma (ESCC). For this nested study, the cases comprised of all incident cases by Jan 1, 2018; controls were matched to the case by age, sex, residence, time in cohort, and tobacco use. We measured urinary concentrations of 33 exposure biomarkers of nicotine, polycyclic aromatic hydrocarbons (PAHs), volatile organic compounds (VOCs), and tobacco-specific nitrosamines (TSNAs). We used conditional logistic regression to calculate odds ratios (OR) and 95% confidence intervals (95%CI) for associations between the 90th versus the 10th percentiles of the biomarker concentrations and incident ESCC. RESULTS: Among individuals who did not currently use tobacco (148 cases/163 controls), two acrolein metabolites, two acrylonitrile metabolites, one propylene oxide metabolite and one 1,3-butadiene metabolite were significantly associated with incident ESCC (adjusted ORs between 1.8 and 4.3). Among tobacco users (57 cases/63 controls), metabolites of two other VOCs (styrene and xylene) were associated with ESCC (ORs= 6.2 and 9.0). In tobacco users, two TSNAs (NNN and N'-Nitrosoanatabine) were also associated with ESCC. Suggestive associations were seen with some PAHs (especially 2-hydroxynaphthalene) in non-users of tobacco products and other TSNAs in tobacco users. CONCLUSION: These novel associations based on individual-level data and samples collected many years before cancer diagnosis, from a population without occupational exposure, have important public health implications.

BACKGROUND: Biomarkers of exposure are tools for understanding the impact of tobacco use on health outcomes if confounders like demographics, use behavior, biological half-life and other sources of exposure are accounted for in the analysis. METHODS: We performed multiple regression analysis of longitudinal measures of urinary biomarkers of alkaloids, tobacco-specific nitrosamines, polycyclic aromatic hydrocarbons, volatile organic compounds (VOC), and metals to examine the sample-to-sample consistency in Waves 1 and 2 of the Population Assessment of Tobacco and Health Study including demographic characteristics and use behavior variables of persons who smoked exclusively. Regression coefficients, within- and between-person variance, and intra-class correlation coefficients were compared to biomarker smoking-nonsmoking population mean ratios and biological half-lives. RESULTS: Most biomarkers were similarly associated with sex, age, race/ethnicity, and product use behavior. The biomarkers with larger smoking-nonsmoking population mean ratios had greater regression coefficients related to recency of exposure. For VOC and alkaloid metabolites, longer biological half-life was associated with lower within-person variance. For each chemical class studied, there were biomarkers that demonstrated good intra-class correlation coefficients. CONCLUSIONS: For most of the biomarkers of exposure reported in the PATH Study, for people who smoke cigarettes exclusively, associations are similar between urinary biomarkers of exposure and demographic and use behavior covariates. Biomarkers of exposure within-subject consistency is likely associated with non-tobacco sources of exposure and biological half-life. IMPACT: Biomarkers measured in the PATH Study provide consistent sample-to-sample measures from which to investigate the association of adverse health outcomes with the characteristics of cigarettes and their use.

Assessing benzene exposure is a public health priority due to its deleterious health effects and ubiquitous industrial and environmental sources of exposure. Phenyl mercapturic acid (PhMA) is a commonly used urinary biomarker to assess benzene exposure. However, recent work has identified significant interlaboratory variation in urinary PhMA concentrations related to methodological differences. In this study, we present urinary 6-hydroxy-2,4-cyclohexadienyl mercapturic acid (pre-PhMA), a metabolite that undergoes acid-catalyzed dehydration to form PhMA, as a novel and specific urinary biomarker for assessing benzene exposure. We developed and validated the first quantitative liquid chromatography-tandem mass spectrometry assay for measuring urinary concentrations of pre-PhMA. The pH effect on the method of ruggedness testing determined that pre-PhMA is stable across the normal human urine pH range and that neutral conditions must be maintained throughout quantification for robust and accurate measurement of urinary pre-PhMA concentrations. The method exhibited below 2 ng/mL sensitivity for pre-PhMA, linearity over three orders of magnitude, and precision and accuracy within 10%. Urinary pre-PhMA concentrations were assessed in 369 human urine samples. Smoking individuals exhibited elevated levels of pre-PhMA compared to non-smoking individuals. Furthermore, the relationship between benzene exposure and urinary pre-PhMA levels was explored by examining the correlation of pre-PhMA with 2-cyanoethyl mercapturic acid, a smoke exposure biomarker. The urinary biomarkers exhibited a positive correlation (r = 0.720), indicating that pre-PhMA levels increased with benzene exposure. The results of this study demonstrate that urinary pre-PhMA is a rugged and effective novel biomarker of benzene exposure that can be widely implemented for future biomonitoring studies.

OBJECTIVE: Volatile organic compounds (VOCs) are used in the sterilization and manufacture of medical equipment. These compounds have high vapor pressures with low water solubility and are emitted as gases from solids or liquids. They can be mutagenic, neurotoxic, genotoxic, and/or carcinogenic. Safe limits of exposure are not known for neonates. This study examined determinants of exposure in newborns undergoing cardiac surgery. METHODS: Twenty metabolites of 16 VOCs (e.g., xylene, cyanide, acrolein, acrylonitrile, N, N-dimethylformamide, 1,3-butadiene, styrene, and benzene) were measured as metabolites in daily urine samples collected from 10 neonates undergoing cardiac operations (n = 150 samples). Metabolites were quantified using reversed-phase ultra-high performance liquid chromatography and electrospray ionization tandem mass spectrometry. Repeated measures ANOVA was performed for each metabolite to examine associations with use of medical devices. RESULTS: At least 3 metabolites were detected in every sample. The median number of metabolites detected in each sample was 14 (range: 3-15). In a model controlling for other factors, the use of extracorporeal membrane oxygenation was associated with significantly (p ≤ 0.05) higher metabolite levels of acrolein, acrylonitrile, ethylene oxide, propylene oxide, styrene, and ethylbenzene. Patients breathing ambient air had higher levels of metabolites of acrolein, xylene, N,N-dimethylformamide, methyl isocyanate, cyanide, 1,3-butadiene (all p≤ 0.05). CONCLUSIONS: Exposure to volatile organic compounds is pervasive in newborns undergoing cardiac surgery. Sources of exposure likely include medical devices and inhalation from the air in the intensive care unit. The contribution of VOC exposure during cardiac surgery in newborns to adverse outcomes warrants further evaluation.

Firefighters are at an increased risk of cancer due to their occupational exposure to combustion byproducts, especially when those compounds penetrate the firefighter personal protective equipment (PPE) ensemble. This has led to questions about the impact of base layers (i.e., shorts vs. pants) under PPE ensembles. This study asked 23 firefighters to perform firefighting activities while wearing one of three different PPE ensembles with varying degrees of protection. Additionally, half of the firefighters unzipped their jackets after the scenario while the other half kept their jackets zipped for five additional minutes. Several volatile organic compound (VOC) and naphthalene air concentrations outside and inside of hoods, turnout jackets, and turnout pants were evaluated; biological (urinary and exhaled breath) samples were also collected. VOCs and naphthalene penetrated the three sampling areas (hoods, jackets, pants). Significant (p-value < 0.05) increases from pre- to post-fire for some metabolites of VOCs (e.g., benzene, toluene) and naphthalene were found. Firefighters wearing shorts and short sleeves absorbed higher amounts of certain compounds (p-value < 0.05), and the PPE designed with enhanced interface control features appeared to provide more protection from some compounds. These results suggest that firefighters can dermally absorb VOCs and naphthalene that penetrate the PPE ensemble.

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.

BACKGROUND: Cigarette smoking increases the risk of cancer, cardiovascular diseases, and premature death. Aromatic amines (AA) are found in cigarette smoke and are well-established human bladder carcinogens. METHODS: We measured and compared total urinary levels of 1-aminonaphthalene (1AMN), 2-aminonaphthalene (2AMN), and 4-aminobiphenyl (4ABP) in adults who smoked cigarettes exclusively and in adult nonusers of tobacco products from a nationally representative sample of non-institutionalized U.S. population in the 2013-2014 National Health and Nutrition Examination Survey. RESULTS: Sample-weighted geometric mean concentrations of AAs in adults who smoked cigarettes exclusively compared with adult nonusers were 30 times higher for 1AMN and 4 to 6 times higher for 2AMN and 4ABP. We evaluated the association of tobacco-smoke exposure with urinary AAs using sample-weighted multiple linear regression models to control for age, sex, race/ethnicity, diet, and urinary creatinine. Secondhand smoke exposure status was categorized using serum cotinine (SCOT) among adult nonusers (SCOT ≤ 10 ng/mL). The exposure for adults who smoked cigarettes exclusively (SCOT > 10 ng/mL) was categorized on the basis of the average number of self-reported cigarettes smoked per day (CPD) in the five days prior to urine collection. The regression models show AAs concentration increased with increasing CPD (P < 0.001). Dietary-intake variables derived from the 24-hours recall questionnaire were not consistently significant predictors of urinary AAs. CONCLUSIONS: This is the first characterized total urinary AA concentrations of the U.S. adult non-institutionalized population. Our analyses show that smoking status is a major contributor to AA exposures. IMPACT: These data provide a crucial baseline for exposure to three AAs in U.S. non-institutionalized adults.

While the thirdhand smoke (THS) residue from tobacco smoke has been recognized as a distinct public health hazard, there are currently no gold standard biomarkers to differentiate THS from secondhand smoke (SHS) exposure. This study used machine learning algorithms to assess which combinations of biomarkers and reported tobacco smoke exposure measures best differentiate children into three groups: no/minimal tobacco smoke exposure (NEG); predominant THS exposure (TEG); and mixed SHS and THS exposure (MEG). Participants were 4485 nonsmoking 3-17-year-olds from the National Health and Nutrition Examination Survey 2013-2016. We fitted and tested random forest models, and the majority (76%) of children were classified in NEG, 16% were classified in TEG, and 8% were classified in MEG. The final classification model based on reported exposure, biomarker, and biomarker ratio variables had a prediction accuracy of 95%. This final model had prediction accuracies of 100% for NEG, 88% for TEG, followed by 71% for MEG. The most important predictors were the reported number of household smokers, serum cotinine, serum hydroxycotinine, and urinary 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL). In the absence of validated biomarkers specific to THS, comprehensive biomarker and questionnaire data for tobacco smoke exposure can distinguish children exposed to SHS and THS with high accuracy.

Little filtered cigars are tobacco products with many cigarette-like characteristics. However, despite cigars falling under the U.S. Food and Drug Administration regulatory authority, characterizing flavors, which are still allowed in little filtered cigars, and filter design may influence how people use the products and the resulting exposure to harmful and potentially harmful constituents. We estimated nicotine mouth level intake (MLI) from analyses of little cigar filter butt solanesol levels, brand characteristics, carbon monoxide boost, and puff volume in 48 dual cigarette/cigar users during two repeat bouts of ad lib smoking of three little filtered cigar brands. Mean nicotine MLI for the three brands was significantly different with Swisher Sweets (0.1% ventilation) Cherry at 1.20 mg nicotine, Cheyenne Menthol (1.5%) at 0.63 mg, and Santa Fe unflavored (49%) at 0.94 mg. The association between nicotine MLI and puff volume was the same between Cheyenne Menthol and Santa Fe unflavored. However, these were different from Swisher Sweets Cherry. At least five main factors─flavor, ventilation, filter design, nicotine delivery related to tar, and user puff volume─may directly or indirectly impact MLI and its association with other measures. We found that users of little filtered cigars that have different filter ventilation and flavor draw dissimilar amounts of nicotine from the product, which may be accompanied by differences in exposure to other harmful smoke constituents.

Anabasine and anatabine are minor alkaloids in tobacco products and are precursors for tobacco-specific nitrosamines (TSNAs). The levels of these two compounds have been used to differentiate tobacco product sources, monitor compliance with smoking cessation programs, and for biomonitoring in TSNA-related studies. The concentrations of urinary anabasine and anatabine were measured in a representative sample of U.S. adults who smoked cigarettes (N = 770) during the 2013-2014 National Health and Nutrition Examination Survey (NHANES) study cycle, which was the first cycle where urinary anabasine and anatabine data became available. Weighted geometric means (GM) and geometric least squares means (LSM) with 95% confidence intervals were calculated for urinary anabasine and anatabine categorized by tobacco-use status [cigarettes per day (CPD) and smoking frequency] and demographic characteristics. Smoking 20 CPD was associated with 3.6 higher anabasine GM and 4.8 higher anatabine GM compared with smoking &lt;10 CPD. Compared with non-daily smoking, daily smoking was associated with higher GMs for urinary anabasine (1.41 ng/mL vs. 6.28 ng/mL) and anatabine (1.62 ng/mL vs. 9.24 ng/mL). Urinary anabasine and anatabine concentrations exceeded the 2 ng/mL cut point in 86% and 91% of urine samples from people who smoke (PWS) daily, respectively; in comparison, 100% of them had serum cotinine concentrations greater than the established 10 ng/mL cut point. We compared these minor tobacco alkaloid levels to those of serum cotinine to assess their suitability as indicators of recent tobacco use at established cut points and found that their optimal cut point values would be lower than the established values. This is the first time that anabasine and anatabine are reported for urine collected from a U.S. population-representative sample of NHANES study participants, providing a snapshot of exposure levels for adults who smoked during 2013-2014. The results of this study serve as an initial reference point for future analysis of NHANES cycles, where changes in the national level of urinary anabasine and anatabine can be monitored among people who smoke to show the effect of changes in tobacco policy.

BACKGROUND: The epidemiological evidence regarding the carcinogenicity of nitrate and sodium in drinking water is limited, partly because measuring the exposure at the individual level is complex. Most studies have used nitrate in water supplies as a proxy for individual exposure, but dietary intakes and other factors may contribute to the exposure. The present study investigates the factors associated with urinary nitrate and sodium in a high-risk area for esophageal and gastric cancers. METHODS: For this cross-sectional study, we used data and samples collected in 2004-2008 during the enrollment phase of the Golestan Cohort Study from a random sample of 349 participants (300 individuals from 24 rural villages and 49 from the city of Gonbad), stratified by average water nitrate in their district, the source of drinking water, and the usual dietary intake of nitrate and sodium. Nitrate, sodium, and creatinine were measured in a spot urine sample collected at the time of interview. We used the provincial cancer registry data to calculate the cumulative incidence rates of esophageal and gastric cancers for each location through June 1, 2020, and used weighted partial Pearson correlation to compare the incidence rates with median urinary nitrate and sodium in each village or the city. RESULTS: Among 349 participants (mean age±SD: 50.7 ± 8.6 years), about half (n = 170) used groundwater for drinking, and the use of ground water was significantly more common in high-elevation locations (75.8%). The geometric mean of the creatinine-corrected urinary nitrate concentration was 68.3 mg/g cr (95%CI: 64.6,72.3), and the corresponding geometric mean for urinary sodium was 150.0 mmoL/g cr (95%CI: 139.6161.1). After adjusting for confounders, urinary nitrate was associated with being a woman, drinking groundwater, and living in high-elevation locations, but not with estimated dietary intake. Urinary sodium concentration was significantly associated with monthly precipitation at the time of sampling but not with elevation or drinking water source. There were significant positive correlations between both median urinary nitrate and sodium in each location and esophageal cancer incidence rates adjusted for sex and age (r = 0.65 and r = 0.58, respectively, p < 0.01), but not with gastric cancer incidence. CONCLUSION: In a rural population at high risk for esophageal and gastric cancers, nitrate excretion was associated with living at a higher elevation and using groundwater for drinking. The associations between nitrate and sodium excretion with esophageal cancer incidence warrant future investigation.

The objective of this study was to examine long-term trends in serum cotinine (COT) concentrations, as a measure of secondhand smoke (SHS) exposure, in U.S. nonsmokers using data from the National Health and Nutrition Examination Surveys (NHANES) from 2003 to 2018. We analyzed NHANES serum COT results from 8 continuous NHANES 2 year cycles from 2003 to 2018 using a liquid chromatography–tandem mass spectrometry assay that has been maintained continuously at the Centers for Disease Control and Prevention (CDC) since 1992. Serum COT concentrations (based on the geometric means) among nonsmokers in the U.S. decreased by an average of 11.0% (95% confidence interval (CI) [8.8%, 13.1%]; p < 0.0001) every 2 year cycle. From 2003 to 2018, serum COT concentrations in U.S. nonsmokers declined by 55.0%, from 0.065 ng/mL in 2003–2004 to 0.029 ng/mL in 2017–2018 (p < 0.0001). Significant decreases in serum COT concentrations were observed in all demographic groups. While disparities between these groups seems to be shrinking over time, several previously observed disparities in SHS exposure remain in 2017–2018. Serum COT concentrations of the non-Hispanic Black population remained higher than those of non-Hispanic Whites and Mexican Americans (p < 0.0001). Additionally, serum COT concentrations were significantly higher for children aged 3–5 years than other age groups (p ≤ 0.0002), and men continued to have significantly higher serum COT concentrations than women (p = 0.0384). While there is no safe level of exposure to SHS, the decrease in serum COT concentrations in the U.S. population as well as across demographic groupings represents a positive public health outcome and supports the importance of comprehensive smoke-free laws and policies for workplaces, public places, homes, and vehicles to protect nonsmokers from SHS exposure. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

INTRODUCTION: In response to reducing cigarette nicotine content, people who smoke could attempt to compensate by using more cigarettes or by puffing on individual cigarettes with greater intensity. Such behaviors may be especially likely under conditions where normal nicotine content (NNC) cigarettes are not readily accessible. The current within-subject, residential study investigated whether puffing intensity increased with very low nicotine content (VLNC) cigarette use, relative to NNC cigarette use, when no other nicotine products were available. METHODS: Sixteen adults who smoke daily completed two 4-night hotel stays in Charleston, South Carolina (U.S.) in 2018 during which only NNC or only VLNC cigarettes were accessible. We collected the filters from all smoked cigarettes and measured the deposited solanesol to estimate mouth-level nicotine delivery per cigarette. These estimates were averaged within and across participants, per each 24-hour period. We then compared the ratio of participant-smoked VLNC and NNC cigarette mouth-level nicotine to the ratio yielded by cigarette smoking machines (when puffing intensity is constant). RESULTS: Average mouth-level nicotine estimates from cigarettes smoked during the hotel stays indicate participants puffed VLNC cigarettes with greater intensity than NNC cigarettes in each respective 24-hour period. However, this effect diminished over time (p<0.001). Specifically, VLNC puffing intensity was 40.0% (95% CI: 29.9, 53.0) greater than NNC puffing intensity in the first period, and 16.1% (95% CI: 6.9, 26.0) greater in the fourth period. CONCLUSION: Average puffing intensity per cigarette was elevated with exclusive VLNC cigarette use, but the extent of this effect declined across four days. IMPLICATIONS: In an environment where no other sources of nicotine are available, people who smoke daily may initially attempt to compensate for cigarette nicotine reduction by puffing on individual cigarettes with greater intensity. Ultimately, the compensatory behavior changes required to achieve usual nicotine intake from VLNC cigarettes are drastic and unrealistic. Accordingly, people are unlikely to sustain attempts to compensate for very low cigarette nicotine content.

Chemicals of unknown inhalational toxicity are present in electronic cigarette and vaping products. E-cigarettes typically contain nicotine and other relatively hydrophilic chemicals while vaping products typically contain cannabinoids and other hydrophobic chemicals. For example, vaping products can include hydrophobic terpenes such as squalane (SQA) and squalene (SQE). However, little is known about the SQA and SQE transmission from liquid to aerosol. SQA and SQE are used in commercial products that are applied dermally and ingested orally, but limited information is available on their inhalational exposure and toxicity. We developed and validated a quantitative method to measure SQE and SQA in bronchoalveolar lavage fluid to assess if these chemicals accumulate in lung epithelial lining fluid after inhalation. Calibration curves spanned a range of 0.50-30.0 µg analyte per mL bronchoalveolar lavage fluid. Recoveries were found to be 97-105% for SQE and 81-106% for SQA. Limits of detection were 0.50 μg/ml for both SQE and SQA. The method was applied to bronchoalveolar lavage fluid samples of patients from the 2019 outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI) and a comparison group. Neither SQA nor SQE was detected above the method LOD for any samples analyzed; conversely, SQA or SQE were reproducibly measured in spiked quality control BAL fluids (relative standards deviations <15% for both analytes). Further applications of this method may help to evaluate the potential toxicity of SQA and SQE chronically inhaled from EVPs.

INTRODUCTION: Firefighters are exposed to volatile organic compounds (VOCs) during structural fire responses and training fires, several of which (e.g., benzene, acrolein, styrene) are known or probable carcinogens. Exposure studies have found that firefighters can absorb chemicals like benzene even when self-contained breathing apparatus (SCBA) are worn, suggesting that dermal absorption contributes to potentially harmful exposures. However, few studies have characterized VOC metabolites in urine from firefighters. OBJECTIVES: We quantified VOC metabolites in firefighters' urine following live firefighting activity across two field studies. METHODS: In two separate controlled field studies, spot urine was collected before and 3 h after firefighters and firefighter students responded to simulated residential and training fires. Urine was also collected from instructors from the training fire study before the first and 3 h after the last training scenario for each day (instructors led three training scenarios per day). Samples were analyzed for metabolites of VOCs to which firefighters may be exposed. RESULTS: In the residential fire study, urinary metabolites of xylenes (2MHA), toluene (BzMA), and styrene (MADA) increased significantly (at 0.05 level) from pre- to post-fire. In the training fire study, MADA concentrations increased significantly from pre- to post-fire for both firefighter students and instructors. Urinary concentrations of benzene metabolites (MUCA and PhMA) increased significantly from pre- to post-fire for instructors, while metabolites of xylenes (3MHA+4MHA) and acrolein (3HPMA) increased significantly for firefighter students. The two highest MUCA concentrations measured post-shift from instructors exceeded the BEI of 500 μg/g creatinine. CONCLUSIONS: Some of the metabolites that were significantly elevated post-fire are known or probable human carcinogens (benzene, styrene, acrolein); thus, exposure to these compounds should be eliminated or reduced as much as possible through the hierarchy of controls. Given stringent use of SCBA, it appears that dermal exposure contributes in part to the levels measured here.

INTRODUCTION: To date, no studies have evaluated the consistency of biomarker levels in people who smoke over a long-time period in real-world conditions with a large number of subjects and included use behavior and measures of nicotine metabolism. We evaluated the variability of biomarkers of nicotine exposure over approximately a 1-year period in people who exclusively smoke cigarettes, including intensity and recency of use and brand switching to assess impact on understanding associations with product characteristics. AIMS AND METHODS: Multivariate regression analysis of longitudinal repeated measures of urinary biomarkers of nicotine exposure from 916 adults in the Population Assessment of Tobacco and Health (PATH) Study with demographic characteristics and use behavior variables. Intraclass correlation coefficients (ICCs) were calculated to examine individual variation of nicotine biomarkers and the uncertainty of repeat measures at two time points (Waves 1 and 2). RESULTS: Age, race, and urinary creatinine were significant covariates of urinary cotinine. When including use behavior, recency, and intensity of use were highly significant and variance decreased to a higher extent between than within subjects. The ICC for urinary cotinine decreased from 0.7530 with no use behavior variables in the model to 0.5763 when included. Similar results were found for total nicotine equivalents. CONCLUSIONS: Urinary nicotine biomarkers in the PATH Study showed good consistency between Waves 1 and 2. Use behavior measures such as time since last smoked a cigarette and number of cigarettes smoked in the past 30 days are important to include when assessing factors that may influence biomarker concentrations. IMPLICATIONS: The results of this study show that the consistency of the nicotine biomarkers cotinine and total nicotine equivalents in spot urine samples from Waves 1 to 2 of the PATH Study is high enough that these data are useful to evaluate the association of cigarette characteristics with biomarkers of exposure under real-world use conditions.

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.

We characterize nicotine exposure in the U.S. population by measuring urinary nicotine and its major (cotinine, trans-3′-hydroxycotinine) and minor (nicotine 1′-oxide, cotinine N-oxide, and 1-(3-pyridyl)-1-butanol-4-carboxylic acid, nornicotine) metabolites in participants from the 2015–2016 National Health and Nutrition Examination Survey. This is one of the first U.S. population-based urinary nicotine biomarker reports using the derived total nicotine equivalents (i.e., TNEs) to characterize exposure. Serum cotinine data is used to stratify tobacco non-users with no detectable serum cotinine (−sCOT), non-users with detectable serum cotinine (+sCOT), and individuals who use tobacco (users). The molar concentration sum of cotinine and trans-3′-hydroxycotinine was calculated to derive the TNE2 for non-users. Additionally, for users, the molar concentration sum of nicotine and TNE2 was calculated to derive the TNE3, and the molar concentration sum of the minor metabolites and TNE3 was calculated to derive the TNE7. Sample-weighted summary statistics are reported. We also generated multiple linear regression models to analyze the association between biomarker concentrations and tobacco use status, after adjusting for select demographic factors. We found TNE7 is positively correlated with TNE3 and TNE2 (r = 0.99 and 0.98, respectively), and TNE3 is positively correlated with TNE2 (r = 0.98). The mean TNE2 concentration was elevated for the +sCOT compared with the −sCOT group (0.0143 [0.0120, 0.0172] µmol/g creatinine and 0.00188 [0.00172, 0.00205] µmol/g creatinine, respectively), and highest among users (33.5 [29.6, 37.9] µmol/g creatinine). Non-daily tobacco use was associated with 50% lower TNE7 concentrations (p &lt; 0.0001) compared with daily use. In this report, we show tobacco use frequency and passive exposure to nicotine are important sources of nicotine exposure. Furthermore, this report provides more information on non-users than a serum biomarker report, which underscores the value of urinary nicotine biomarkers in extending the range of trace-level exposures that can be characterized. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

A quantitative method was developed to measure four harmful carbonyls (acetaldehyde, acrolein, crotonaldehyde, and formaldehyde) in aerosol generated from e-cigarette, or vaping, products (EVPs). The method uses a commercially available sorbent bed treated with a derivatization solution to trap and stabilize reactive carbonyls in aerosol emissions from EVPs to reduce reactive analyte losses and improve quantification. Analytes were extracted from the sorbent material using acetonitrile and analyzed via high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The method was applied to aerosols generated from products obtained from case patients with EVP use-associated lung injury (EVALI). The method accuracy ranged from 93.6 to 105% in the solvent and 99.0 to 112% in the matrix. Limits of detection (LODs) were in the low nanogram range at 0.735-2.10 ng for all analytes, except formaldehyde at 14.7 ng. Intermediate precision, as determined from the replicate measurements of quality-control (QC) samples, showed a relative standard deviation (RSD) of less than 20% for all analytes. The EVALI case-related products delivered aerosol containing the following ranges of carbonyls: acetaldehyde (0.0856-5.59 μg), acrolein (0.00646-1.05 μg), crotonaldehyde (0.00168-0.108 μg), and formaldehyde (0.0533-12.6 μg). At least one carbonyl analyte was detected in every product. Carbonyl deliveries from EVALI-associated products of all types are consistent with the previously published results for e-cigarettes, and levels are lower than those observed in smoke from combustible cigarettes. This method is rugged, has high throughput, and is well suited for quantifying four harmful carbonyls in aerosol emissions produced by a broad spectrum of devices/solvents, ranging from e-cigarette containing polar solvents to vaping products containing nonpolar solvents.

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.

2-carbamoylethyl mercapturic acid (2CaEMA, N-Acetyl-S-carbamoylethyl-L-cysteine) is a urinary metabolite and exposure biomarker of acrylamide, which is a harmful volatile organic compound found in cigarette smoke and in some foods. The goal of this study was to determine the association between cigarette smoking and urinary 2CaEMA concentrations among the U.S. population while considering potential dietary sources of acrylamide intake and demographics. We measured 2CaEMA concentrations in urine specimens collected during the National Health and Nutrition Examination Survey 2011-2012, 2013-2014, and 2015-2016 cycles from eligible participants 18 years and older (n=5443) using liquid chromatography/tandem mass spectrometry. We developed multiple regression models with urinary 2CaEMA concentrations as the dependent variable and sex, age, race/Hispanic origin, reported primary sources of dietary acrylamide intake, and cigarette smoke exposure as independent variables. This study demonstrates that cigarette smoking is strongly associated with urinary 2CaEMA, suggests that cigarette smoking is likely a primary source of acrylamide exposure, and provides a baseline measure for 2CaEMA in the U.S. population.

In 2019, the Centers for Disease Control and Prevention responded to an outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI). Bronchoalveolar-lavage (BAL) fluid from EVALI patients was available for analysis to investigate a range of potential toxicants that might be present at the presumed site of lung injury. Our laboratory developed and validated a novel method to measure cannabinoids and their metabolites in BAL fluid to aid in the investigation of the toxicants that might be the cause of EVALI. In this paper, we describe a sensitive liquid chromatography-tandem mass spectrometry method to measure the following six cannabinoids: Δ(9)-tetrahydrocannabinol (THC), THC metabolites 11-nor-9-carboxy-THC and 11-hydroxy-THC, cannabinol, cannabidiol (CBD), and CBD metabolite 7-nor-7-carboxycannabidiol. Cannabinoids were extracted from BAL fluid using solid-phase extraction. Accuracy, precision, stability, and limits of detection were determined from replicate analyses of spiked BAL pools. The lower limits of detection ranged from 0.019 to 0.153 ng/mL for a sample volume of 150 μL. Overall accuracy ranged from 71.0 to 100.8%. Within-run imprecision (measured by the coefficient of variation) was below 8%, and between-run imprecision was below 21% for all analytes and concentrations tested. The method was applied to samples from 59 EVALI case patients. We identified THC, CBD, or their metabolites in 76% of EVALI patient samples. These findings support previous evidence that THC-containing products played a major role in the EVALI outbreak and help to inform public health recommendations.

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.

Numerous chemicals of unknown inhalational toxicity have been measured in electronic cigarette, or vaping, products (EVPs). In addition, little is known about the liquid-to-aerosol transmission and deliveries of these chemicals, including oil-like terpenes such as squalene (SQE) and squalane (SQA). To provide information on the aerosol deliveries of these compounds from EVPs, we developed and validated a quantitative method to measure squalene and squalane in EVP aerosol emissions. Validation parameters include measurement repeatability (SQA and SQE %RSD <6%), intermediate precision (SQA: %RSD 11%, SQE: %RSD 17%), accuracy (SQA: 86-107%, SQE: 104-113%), matrix effects, method robustness, and analyte stability. Limits of detection were 6.06 ng/mL puffed air volume for both squalene and squalane. The method was used to measure squalene and squalane in aerosol emissions of 153 EVPs associated with case patients from a recent outbreak of e-cigarette, or vaping, product use associated lung injury (EVALI). The EVPs analyzed were organized into nicotine, cannabidiol, and tetrahydrocannabinol products by the percentage of nicotine, cannabidiol, and tetrahydrocannabinol in total particulate matter after vaping. In case-associated tetrahydrocannabinol products the detection rates and mean concentrations were 82.4% and 33.0 ng/mL puffed air for squalene and 4.41% and 7.80 ng/mL puffed air for squalane.

Cannabis has certain health benefits, but some people may experience harms from use. Co-use of tobacco and cannabis is common. Smoke from cannabis contains many of the same carcinogens and toxicants as the smoke from tobacco, raising concerns that cannabis smoking may be a risk factor for cancer. With growing access to and acceptance of medical and nonmedical cannabis, there is an urgent need to understand the risks and benefits of the current modes of cannabis use and how cannabis may be associated with cancer risk. This monograph summarizes a session from a National Cancer Institute Symposium on nonmedical cannabis use and cancer risk. We had 3 objectives: describe the relation between nonmedical cannabis use and cancer risk, delineate patterns and correlates of cannabis co-use with tobacco, and document potentially harmful inhalational exposure resulting from smoked and vaped cannabis. Methodological limitations in the literature and future research recommendations are provided.