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Edwards KC, St Helen G, Jacob P, Ozga JE, Stanton CA. Urinary anatalline and nicotelline cut-points to distinguish between exclusive and dual use of tobacco products. Biomarkers 2024:1-9. [PMID: 39105562 DOI: 10.1080/1354750x.2024.2389047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Accepted: 07/31/2024] [Indexed: 08/07/2024]
Abstract
OBJECTIVE This study measured anatalline and nicotelline, two minor tobacco alkaloids, to discriminate between exclusive smokeless tobacco (SLT) use, exclusive electronic nicotine delivery systems (ENDS) use, exclusive cigarette use, dual SLT and cigarette use, and dual ENDS and cigarette use. METHODS N = 664 urine samples from participants in the Population Assessment of Tobacco and Health Study were analyzed for anatalline and nicotelline. Geometric means and 95% confidence intervals were calculated for biomarker levels and their ratios. Non-parametric Receiver Operating Characteristic analyses were used to determine optimal cut-points of natural log-transformed biomarker ratios for distinguishing between tobacco use groups. RESULTS The anatalline/nicotelline ratio distinguished exclusive cigarette from exclusive SLT use (threshold = 18.1, sensitivity = 89.3%, specificity = 86.4%, AUC = 0.90), and exclusive SLT from exclusive ENDS use (threshold = 12.8, sensitivity = 96.4%, specificity = 76.3%, AUC = 0.90) very well, but had reduced sensitivity and specificity when distinguishing exclusive cigarette from exclusive ENDS or any dual use with cigarettes. CONCLUSIONS This research fills a gap in understanding the public health consequences of SLT and ENDS use by providing objective measures that can signal use of these products alone or in combination with cigarettes.
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Affiliation(s)
| | - Gideon St Helen
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Peyton Jacob
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Jenny E Ozga
- Behavioral Health and Health Policy, Westat, Rockville, MD, USA
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Chang CM, Thakur S, de Oca RM, Rostron BL, Cheng YC, Wright MJ, van Bemmel DM, Wang L, Hatsukami DK. Assessing the Relationship between Biomarkers of Exposure and Biomarkers of Potential Harm: PATH Study Wave 1 (2013 to 2014). Cancer Epidemiol Biomarkers Prev 2024; 33:1083-1090. [PMID: 38861317 PMCID: PMC11293985 DOI: 10.1158/1055-9965.epi-23-1471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 03/10/2024] [Accepted: 06/07/2024] [Indexed: 06/13/2024] Open
Abstract
BACKGROUND The adequacy of biomarkers of potential harm (BOPH) for assessing tobacco products was explored based on their ability to distinguish tobacco use from non-use, change with cessation, and to show biological gradient. METHODS The sample included individuals with biomarker data in wave 1 of the Population Assessment of Tobacco Health study who never used tobacco, currently smoke cigarettes exclusively, used to smoke cigarettes exclusively (quit in past 12 months), currently use smokeless tobacco exclusively, and currently use e-cigarettes exclusively. We compared BOPH levels between groups and assessed the relationships between log-transformed biomarkers of exposure [BOE; total nicotine equivalents including seven nicotine metabolites (TNE-7), 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanonol (NNAL), N-acetyl-S-(2-cyanoethyl)-L-cysteine, 1-hydroxypyrene, cadmium, and serum cotinine (SCOT)], and BOPH [high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), fibrinogen, soluble intercellular adhesion molecule-1 (sICAM-1), and 8-isoprostane]. RESULTS Among people who smoke, both sICAM-1 and 8-isoprostane distinguished smoking from non-use and were associated with all six BOE. Among people who use smokeless tobacco, 8-isoprostane was associated with TNE-7 and NNAL whereas hs-CRP was associated with SCOT. Among people who use e-cigarettes, no associations between BOPH and BOE were observed. CONCLUSIONS Both sICAM-1 and 8-isoprostane may be useful for assessing the use or changes in use of some tobacco products. Studies examining their predictive validity could further strengthen our understanding of these two biomarkers. IMPACT We found that two biomarkers of potential harm, soluble intercellular adhesion molecule-1 and 8-isoprostane, may have utility in studies assessing the potential harm of tobacco use in absence of long-term epidemiological studies.
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Affiliation(s)
- Cindy M. Chang
- Center for Tobacco Products, Food and Drug Administration, MD, USA
| | - Sapna Thakur
- Center for Tobacco Products, Food and Drug Administration, MD, USA
| | | | - Brian L. Rostron
- Center for Tobacco Products, Food and Drug Administration, MD, USA
| | - Yu-Ching Cheng
- Center for Tobacco Products, Food and Drug Administration, MD, USA
| | - M. Jerry Wright
- Center for Tobacco Products, Food and Drug Administration, MD, USA
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Fakunle AG, Okekunle AP, Asowata OJ, Akpa O, Sarfo FS, Akpalu A, Wahab K, Obiako R, Komolafe M, Owolabi L, Osaigbovo GO, Adeoye AM, Tiwari HK, Uvere EO, Akinyemi J, Jenkins C, Arulogun O, Ibinaiye P, Appiah LT, Bello T, Singh A, Yaria J, Calys-Tagoe B, Ogbole G, Chukwuonye I, Melikam C, Adebayo P, Mensah Y, Adebayo O, Adeniyi S, Oguike W, Donna A, Akinyemi R, Ovbiagele B, Owolabi M. Non-cigarette Tobacco Use and Stroke Among West Africans: Evidence From the SIREN Study. Nicotine Tob Res 2024; 26:589-596. [PMID: 38015428 DOI: 10.1093/ntr/ntad239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 09/27/2023] [Accepted: 11/21/2023] [Indexed: 11/29/2023]
Abstract
INTRODUCTION Non-cigarette tobacco (NCT) represents a form of tobacco use with a misperceived significance in chronic disease events. Whether NCT use is sufficient to promote stroke events, especially among Africans, is yet to be understood. This study assessed the relationship between NCT use and stroke among indigenous Africans. METHODS A total of 7617 respondents (NCT users: 41 vs. non-NCT: 7576) from the Stroke Investigative Research and Educational Network (SIREN) study were included in the current analysis. NCT use was defined as self-reported use of smoked (cigars or piper) or smokeless (snuff or chewed) tobacco in the past year preceding stroke events. Stroke was defined based on clinical presentation and confirmed with a cranial computed tomography/magnetic resonance imaging. Multivariable-adjusted logistic regression was applied to estimate the odds ratio (OR) and 95% confidence interval (CI) for the relationship of NCT with stroke at a two-sided p < .05. RESULTS Out of the 41 (0.54%) who reported NCT use, 27 (65.9%) reported using smokeless NCT. NCT users were older than non-NCT users (62.8 ± 15.7 vs. 57.7 ± 14.8 years). Overall, NCT use was associated with first-ever stroke (OR: 2.08; 95% CI: 1.02, 4.23) in the entire sample. Notably, smokeless NCT use was independently associated with higher odds of stroke (OR: 2.74; 95% CI: 1.15, 6.54), but smoked NCT use (OR: 0.16; 95% CI: 0.02, 1.63) presented a statistically insignificant association after adjusting for hypertension and other covariates. CONCLUSIONS NCT use was associated with higher odds of stroke, and public health interventions targeting NCT use might be promising in reducing the burden of stroke among indigenous Africans. IMPLICATIONS A detailed understanding of the relationship between NCT use and stroke will likely inform well-articulated policy guidance and evidence-based recommendations for public health prevention and management of stroke on the African continent.
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Affiliation(s)
- Adekunle Gregory Fakunle
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Department of Public Health, Osun State University, Osogbo, Nigeria
| | - Akinkunmi Paul Okekunle
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Department of Food and Nutrition, Seoul National University, Seoul, Korea
| | - Osahon Jeffery Asowata
- Department of Epidemiology and Medical Statistics, University of Ibadan, Ibadan, Nigeria
| | - Onoja Akpa
- Department of Epidemiology and Medical Statistics, University of Ibadan, Ibadan, Nigeria
- Institute of Cardiovascular Diseases, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Fred S Sarfo
- Department of Medicine, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Albert Akpalu
- Department of Medicine, University of Ghana Medical School, Accra, Ghana
| | - Kolawole Wahab
- Department of Medicine, University of Ilorin Teaching Hospital, Ilorin, Nigeria
| | - Reginald Obiako
- Department of Radiology, Ahmadu Bello University, Zaria, Nigeria
| | - Morenikeji Komolafe
- Department of Medicine, Obafemi Awolowo University Teaching Hospital, Ile-Ife, Nigeria
| | - Lukman Owolabi
- Department of Medicine, Aminu Kano Teaching Hospital, Kano, Nigeria
| | | | - Abiodun M Adeoye
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Hemant K Tiwari
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Ezinne O Uvere
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Joshua Akinyemi
- Department of Epidemiology and Medical Statistics, University of Ibadan, Ibadan, Nigeria
| | - Carolyn Jenkins
- Department of Nursing, Medical University of South Carolina, Charleston, SC, USA
| | - Oyedunni Arulogun
- Department of Health Promotion and Education, University of Ibadan, Ibadan, Nigeria
| | - Philip Ibinaiye
- Department of Radiology, Ahmadu Bello University, Zaria, Nigeria
| | - Lambert T Appiah
- Department of Medicine, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Temilade Bello
- Department of Public Health, Osun State University, Osogbo, Nigeria
| | - Arti Singh
- Department of Medicine, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Joseph Yaria
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Benedict Calys-Tagoe
- Department of Community Health, University of Ghana Medical School, Accra, Ghana
| | - Godwin Ogbole
- Department of Radiology, University of Ibadan, Ibadan, Nigeria
| | | | - Chidinma Melikam
- Department of Radiology, Ahmadu Bello University, Zaria, Nigeria
| | - Philip Adebayo
- Department of Internal Medicine, Aga-Khan University, Dar es Salaam, Tanzania
| | - Yaw Mensah
- Department of Radiology, University of Ghana Medical School, Accra, Ghana
| | - Oladimeji Adebayo
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Institute of Cardiovascular Diseases, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Sunday Adeniyi
- Department of Medicine, University of Ilorin Teaching Hospital, Ilorin, Nigeria
| | - Wisdom Oguike
- Department of Radiology, Ahmadu Bello University, Zaria, Nigeria
| | - Arnett Donna
- College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Rufus Akinyemi
- Department of Medicine, Federal Medical Centre, Abeokuta, Nigeria
- Neuroscience and Ageing Research Unit, Institute for Advanced Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Center for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Bruce Ovbiagele
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Mayowa Owolabi
- Department of Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Center for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Lebanese American University, Beirut, Lebanon
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Edwards KC, Ozga JE, Reyes-Guzman C, Smith D, Hatsukami D, Hart JL, Jackson A, Goniewicz M, Stanton CA. Associations between biomarkers of nicotine/tobacco exposure and respiratory symptoms among adults who exclusively smoke cigarettes in the U.S.: Findings from the PATH Study Waves 1-4 (2013-2017). Addict Behav Rep 2023; 17:100487. [PMID: 37008740 PMCID: PMC10060600 DOI: 10.1016/j.abrep.2023.100487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 03/08/2023] [Accepted: 03/20/2023] [Indexed: 04/04/2023] Open
Abstract
Significance Determining if tobacco-related biomarkers of exposure (BOE) are associated with respiratory symptoms is an important public health tool that can be used to evaluate the potential harm of different tobacco products. Methods Adult data from people who exclusively smoked cigarettes (N = 2,438) in Waves 1-4 (2013-2017) of the Population Assessment of Tobacco and Health Study were stacked to examine associations between baseline and follow-up within wave pairs (W1-W2, W2-W3, W3-W4). Weighted generalized estimating equation models were used to evaluate associations between biomarkers of nicotine, tobacco-specific nitrosamines, acrolein, acrylonitrile, cadmium, and lead at baseline/follow-up and respiratory symptom(s) (wheezing/whistling in the chest, wheezing during exercise, and/or dry cough in the past 12 months) at follow-up. Results Higher acrolein metabolite (CEMA) levels at follow-up were associated with increased odds of respiratory symptoms at follow-up for people who exclusively smoked cigarettes (aOR = 1.34; 95% CI = 1.06, 1.70), including when limited to those without a diagnosed respiratory disease (aOR = 1.46; 95% CI = 1.12, 1.90) and those who smoked daily (aOR = 1.40; 95% CI = 1.06, 1.84). Higher cadmium levels at baseline (while controlling for follow-up levels) were associated with reduced odds of respiratory symptoms at follow-up (aOR = 0.80; 95% CI = 0.65, 0.98) among people who exclusively smoked cigarettes without a respiratory disease. There were no significant associations between baseline/follow-up BOE and follow-up respiratory symptoms for people who smoked cigarettes non-daily. Conclusions This research supports measuring biomarkers of acrolein, such as CEMA, as a potential intermediate measurement for increased respiratory symptom development. Measuring these biomarkers could help alleviate the clinical burden of respiratory disease.
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Affiliation(s)
| | | | | | - Danielle Smith
- Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | | | - Joy L. Hart
- University of Louisville, Louisville, KY, USA
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Wu G, Gong S, He Y, Liu D. Smoking is associated with elevated blood level of volatile organic compounds: a population-based analysis of NHANES 2017-2018. Arch Public Health 2023; 81:55. [PMID: 37055810 PMCID: PMC10103525 DOI: 10.1186/s13690-023-01070-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Accepted: 03/23/2023] [Indexed: 04/15/2023] Open
Abstract
BACKGROUND The study aims to explore the association between cigarette smoking with blood exposure to volatile organic compounds using population data from the National Health and Nutrition Examination Survey (NHANES) 2017-2018. METHODS Based on the data of NHANES 2017-2018, we identified 1117 participants aged 18 to 65 years, who had complete VOCs testing data and filled out the Smoking-Cigarette Use and Volatile Toxicant questionnaires. The participants consisted of 214 dual-smoking persons, 41 E-cigarette smokers, 293 combustible-cigarette smokers and 569 non-smokers. We used One-way ANOVA and Welch's ANOVA to compare differences of VOCs concentration among 4 groups and multivariable regression model to confirm the factors associated with VOCs concentration. RESULTS In dual-smoking and combustible-cigarette smokers, blood concentration of 2,5-Dimethylfuran, Benzene, Benzonitrile, Furan, Isobutyronitrile were higher than non-smokers. When compared with people who never smoked, E-cigarette smokers had similar blood concentrations of VOCs. Blood concentrations of Benzene, Furan, and Isobutyronitrile were significant higher in combustible-cigarette smokers than in E-cigarette smokers. In the multivariable regression model, dual-smoking and combustible-cigarette smoking were associated with elevated blood concentrations of several VOCs except 1,4-Dichlorobenzene, while E-cigarette smoking was only associated with elevated 2,5-Dimethylfuran concentration. CONCLUSIONS Smoking, mainly dual-smoking and combustible-cigarette smoking, is associated with elevated blood concentration of VOCs, while the effect is weak in E-cigarette smoking.
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Affiliation(s)
- Guangjie Wu
- Department of pharmacy, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1095 Jiefang Avenue, Wuhan, Hubei provinve, China
| | - Shiwei Gong
- School of pharmacy, Tongji Medical College, Huzhong University of Science and Technology, No.13 Hangkong Road, Jiefang Avenue, Wuhan, Hubei province, China
| | - Yan He
- Department of pharmacy, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1095 Jiefang Avenue, Wuhan, Hubei provinve, China.
| | - Dong Liu
- Department of pharmacy, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1095 Jiefang Avenue, Wuhan, Hubei provinve, China.
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Ohara H, Ito S, Takanami Y. Binary classification of users of electronic cigarettes and smokeless tobacco through biomarkers to assess similarity with current and former smokers: machine learning applied to the population assessment of tobacco and health study. BMC Public Health 2023; 23:589. [PMID: 36991369 PMCID: PMC10061900 DOI: 10.1186/s12889-023-15511-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 03/23/2023] [Indexed: 03/31/2023] Open
Abstract
BACKGROUND Exposure to harmful and potentially harmful constituents in cigarette smoke is a risk factor for cardiovascular and respiratory diseases. Tobacco products that could reduce exposure to these constituents have been developed. However, the long-term effects of their use on health remain unclear. The Population Assessment of Tobacco and Health (PATH) study is a population-based study examining the health effects of smoking and cigarette smoking habits in the U.S. POPULATION Participants include users of tobacco products, including electronic cigarettes and smokeless tobacco. In this study, we attempted to evaluate the population-wide effects of these products, using machine learning techniques and data from the PATH study. METHODS Biomarkers of exposure (BoE) and potential harm (BoPH) in cigarette smokers and former smokers in wave 1 of PATH were used to create binary classification machine-learning models that classified participants as either current (BoE: N = 102, BoPH: N = 428) or former smokers (BoE: N = 102, BoPH: N = 428). Data on the BoE and BoPH of users of electronic cigarettes (BoE: N = 210, BoPH: N = 258) and smokeless tobacco (BoE: N = 206, BoPH: N = 242) were input into the models to investigate whether these product users were classified as current or former smokers. The disease status of individuals classified as either current or former smokers was investigated. RESULTS The classification models for BoE and BoPH both had high model accuracy. More than 60% of participants who used either one of electronic cigarettes or smokeless tobacco were classified as former smokers in the classification model for BoE. Fewer than 15% of current smokers and dual users were classified as former smokers. A similar trend was found in the classification model for BoPH. Compared with those classified as former smokers, a higher percentage of those classified as current smokers had cardiovascular disease (9.9-10.9% vs. 6.3-6.4%) and respiratory diseases (19.4-22.2% vs. 14.2-16.7%). CONCLUSIONS Users of electronic cigarettes or smokeless tobacco are likely to be similar to former smokers in their biomarkers of exposure and potential harm. This suggests that using these products helps to reduce exposure to the harmful constituents of cigarettes, and they are potentially less harmful than conventional cigarettes.
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Affiliation(s)
- Hiromi Ohara
- Scientific Product Assessment Center, Japan Tobacco Inc, 6-2 Umegaoka, Aoba-ku, Yokohama, 227-8512, Kanagawa, Japan.
| | - Shigeaki Ito
- Scientific Product Assessment Center, Japan Tobacco Inc, 6-2 Umegaoka, Aoba-ku, Yokohama, 227-8512, Kanagawa, Japan
| | - Yuichiro Takanami
- Scientific Product Assessment Center, Japan Tobacco Inc, 6-2 Umegaoka, Aoba-ku, Yokohama, 227-8512, Kanagawa, Japan
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Holme JA, Valen H, Brinchmann BC, Vist GE, Grimsrud TK, Becher R, Holme AM, Øvrevik J, Alexander J. Polycyclic aromatic hydrocarbons (PAHs) may explain the paradoxical effects of cigarette use on preeclampsia (PE). Toxicology 2022; 473:153206. [PMID: 35550401 DOI: 10.1016/j.tox.2022.153206] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 04/29/2022] [Accepted: 05/05/2022] [Indexed: 11/21/2022]
Abstract
Tobacco smoking and use of snus (smokeless tobacco) are associated with adverse effects on pregnancy and neonatal outcomes. Nicotine is considered a key toxicant involved in effects caused by both smoking and snus, while pyrolysis products including polycyclic aromatic hydrocarbons (PAHs) in cigarette smoke represents the constituents most unequally divided between these two groups of tobacco products. The aim of this review was: i) to compare the impact, in terms of relative effect estimates, of cigarette smoking and use of Swedish snus on pregnancy outcomes using similar non-tobacco user controls, and ii) to examine whether exposure to PAHs from smoking could explain possible differences in impact on pregnancy outcomes. We systematically searched MEDLINE, Embase, PsycInfo, Web of Science and the Cochrane Database of Systematic Reviews up to October 2021 and identified studies reporting risks for adverse pregnancy and neonatal outcomes associated with snus use and with smoking relative to pregnant women with no use of tobacco. Both snus use and smoking were associated with increased risk of stillbirth, preterm birth, and oral cleft malformation, with comparable point estimates. These effects were likely due to comparable nicotine exposure. We also found striking differences. While both smoking and snus increased the risk of having small for gestational age (SGA) infants, risk from maternal smoking was markedly higher as was the reduction in birthweight. In contrast, the risk of preeclampsia (PE) was markedly lower in smokers than in controls, while snus use was associated with a slightly increased risk. We suggest that PAHs acting via AhR may explain the stronger effects of tobacco smoking on SGA and also to the apparent protective effect of cigarette smoking on PE. Possible mechanisms involved include: i) disrupted endocrine control of fetal development as well as placental development and function, and ii) stress adaption and immune suppression in placenta and mother.
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Affiliation(s)
- Jørn A Holme
- Division of Climate and Health, Norwegian Institute of Public Health, Oslo, Norway.
| | - Håkon Valen
- Division of Climate and Health, Norwegian Institute of Public Health, Oslo, Norway.
| | - Bendik C Brinchmann
- Division of Climate and Health, Norwegian Institute of Public Health, Oslo, Norway; Department of Occupational Medicine and Epidemiology, National Institute of Occupational Health, Oslo, Norway.
| | - Gunn E Vist
- Division for Health Services, Norwegian Institute of Public Health, Oslo, Norway.
| | - Tom K Grimsrud
- Department of Research, Cancer Registry of Norway, Oslo, Norway.
| | - Rune Becher
- Division of Climate and Health, Norwegian Institute of Public Health, Oslo, Norway.
| | - Ane M Holme
- Department of Obstetrics and Gynecology, Oslo University Hospital, Oslo, Norway.
| | - Johan Øvrevik
- Division of Climate and Health, Norwegian Institute of Public Health, Oslo, Norway; Department of Biosciences, University of Oslo, Oslo, Norway.
| | - Jan Alexander
- Division of Climate and Health, Norwegian Institute of Public Health, Oslo, Norway.
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8
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Mazumder S, Shia W, Bendik PB, Achilihu H, Sosnoff CS, Alexander JR, Luo Z, Zhu W, Pine BN, Feng J, Blount BC, Wang L. Nicotine Exposure in the U.S. Population: Total Urinary Nicotine Biomarkers in NHANES 2015-2016. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:3660. [PMID: 35329347 PMCID: PMC8955498 DOI: 10.3390/ijerph19063660] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 03/15/2022] [Accepted: 03/17/2022] [Indexed: 02/01/2023]
Abstract
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 < 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.
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Affiliation(s)
- Shrila Mazumder
- Tobacco and Volatiles Branch, Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA; (W.S.); (P.B.B.); (H.A.); (C.S.S.); or (J.R.A.); (Z.L.); (W.Z.); (B.N.P.); (J.F.); (B.C.B.); (L.W.)
| | - Winnie Shia
- Tobacco and Volatiles Branch, Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA; (W.S.); (P.B.B.); (H.A.); (C.S.S.); or (J.R.A.); (Z.L.); (W.Z.); (B.N.P.); (J.F.); (B.C.B.); (L.W.)
- Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN 37830, USA
| | - Patrick B. Bendik
- Tobacco and Volatiles Branch, Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA; (W.S.); (P.B.B.); (H.A.); (C.S.S.); or (J.R.A.); (Z.L.); (W.Z.); (B.N.P.); (J.F.); (B.C.B.); (L.W.)
- Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN 37830, USA
| | - Honest Achilihu
- Tobacco and Volatiles Branch, Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA; (W.S.); (P.B.B.); (H.A.); (C.S.S.); or (J.R.A.); (Z.L.); (W.Z.); (B.N.P.); (J.F.); (B.C.B.); (L.W.)
| | - Connie S. Sosnoff
- Tobacco and Volatiles Branch, Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA; (W.S.); (P.B.B.); (H.A.); (C.S.S.); or (J.R.A.); (Z.L.); (W.Z.); (B.N.P.); (J.F.); (B.C.B.); (L.W.)
| | - Joseph R. Alexander
- Tobacco and Volatiles Branch, Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA; (W.S.); (P.B.B.); (H.A.); (C.S.S.); or (J.R.A.); (Z.L.); (W.Z.); (B.N.P.); (J.F.); (B.C.B.); (L.W.)
| | - Zuzheng Luo
- Tobacco and Volatiles Branch, Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA; (W.S.); (P.B.B.); (H.A.); (C.S.S.); or (J.R.A.); (Z.L.); (W.Z.); (B.N.P.); (J.F.); (B.C.B.); (L.W.)
| | - Wanzhe Zhu
- Tobacco and Volatiles Branch, Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA; (W.S.); (P.B.B.); (H.A.); (C.S.S.); or (J.R.A.); (Z.L.); (W.Z.); (B.N.P.); (J.F.); (B.C.B.); (L.W.)
| | - Brittany N. Pine
- Tobacco and Volatiles Branch, Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA; (W.S.); (P.B.B.); (H.A.); (C.S.S.); or (J.R.A.); (Z.L.); (W.Z.); (B.N.P.); (J.F.); (B.C.B.); (L.W.)
- Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN 37830, USA
| | - June Feng
- Tobacco and Volatiles Branch, Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA; (W.S.); (P.B.B.); (H.A.); (C.S.S.); or (J.R.A.); (Z.L.); (W.Z.); (B.N.P.); (J.F.); (B.C.B.); (L.W.)
| | - Benjamin C. Blount
- Tobacco and Volatiles Branch, Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA; (W.S.); (P.B.B.); (H.A.); (C.S.S.); or (J.R.A.); (Z.L.); (W.Z.); (B.N.P.); (J.F.); (B.C.B.); (L.W.)
| | - Lanqing Wang
- Tobacco and Volatiles Branch, Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA; (W.S.); (P.B.B.); (H.A.); (C.S.S.); or (J.R.A.); (Z.L.); (W.Z.); (B.N.P.); (J.F.); (B.C.B.); (L.W.)
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Nahhas GJ, Cummings KM, Halenar MJ, Sharma E, Alberg AJ, Hatuskami D, Bansal-Travers M, Hyland A, Gaalema DE, Morris PB, Duffy K, Chang JT, Lagaud G, Vivar JC, Marshall D, Blanco C, Taylor KA. Smokeless Tobacco Use and Prevalence of Cardiovascular Disease Among Males in the Population Assessment of Tobacco and Health (PATH) Study, Waves 1–4. Prev Med Rep 2022; 25:101650. [PMID: 35127346 PMCID: PMC8800067 DOI: 10.1016/j.pmedr.2021.101650] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 11/25/2021] [Indexed: 11/26/2022] Open
Abstract
Oral smokeless tobacco (SLT) products are non-combusted forms of tobacco that can be dependence producing. SLT use may pose health risks to users such as cardiovascular disease (CVD) through various pathways including influencing hemodynamics, endothelial dysfunction, inflammation, insulin resistance, hyperlipidemia, and arrhythmogenesis. Past studies have suggested a small, elevated risk of CVD among SLT users compared to never tobacco users. This study advances the literature by exploring how the duration of regular SLT use relates to CVD prevalence. In this study of ≥ 40-year-old men only, we did not find a consistent dose–response trend for years of SLT use and prevalence of CVD.
The purpose of this period prevalence study is to compare the prevalence of cardiovascular disease (CVD) in current/former established smokeless tobacco (SLT) users (ever SLT users who have used the product fairly regularly) to those who were: 1) never established cigarette smokers and SLT users, and 2) current/former established exclusive cigarette smokers (have smoked at least a 100 or more cigarettes in lifetime) only, adjusting for known risk factors for CVD. Analyses included 4,703 men ≥ 40 years of age who participated in the Population Assessment of Tobacco and Health (PATH) Study, Waves: 1–4, conducted between 2013 and 2017. Current users were those using SLT products daily or on some days, whereas former users had not used SLT and/or cigarettes in the past 12 months. CVD prevalence was defined as a self-reported diagnosis of congestive heart failure, stroke, or myocardial infarction. Among current/former established SLT users, years of use defined exposure history, while pack-years defined exposure history for smokers. Adjusted odds ratios (AOR) and 95% confidence intervals (CI) were reported with trend tests to examine dose–response associations. Current/former established exclusive SLT users were not significantly more likely to have had any CVD compared to never established cigarette and SLT users (OR = 1.7 [0.8–3.7]), or current/former established exclusive cigarette smokers (OR = 0.9 [0.5–1.8]). Current/former established exclusive cigarette smokers were more likely to have had any CVD compared to those who were never established cigarette and SLT users (OR = 1.6 [1.1–2.3]).
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10
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Chang JT, Vivar JC, Tam J, Hammad HT, Christensen CH, van Bemmel DM, Das B, Danilenko U, Chang CM. Biomarkers of Potential Harm among Adult Cigarette and Smokeless Tobacco Users in the PATH Study Wave 1 (2013-2014): A Cross-sectional Analysis. Cancer Epidemiol Biomarkers Prev 2021; 30:1320-1327. [PMID: 33947655 DOI: 10.1158/1055-9965.epi-20-1544] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 02/22/2021] [Accepted: 04/28/2021] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND While smokeless tobacco (ST) causes oral cancer and is associated with cardiovascular diseases, less is known about how its effects differ from other tobacco use. Biomarkers of potential harm (BOPH) can measure short-term health effects such as inflammation and oxidative stress. METHODS We compared BOPH concentrations [IL6, high-sensitivity C-reactive protein, fibrinogen, soluble intercellular adhesion molecule-1 (sICAM-1), and F2-isoprostane] across 3,460 adults in wave 1 of the Population Assessment of Tobacco and Health study (2013-2014) by tobacco use groups: primary ST users (current exclusive ST use among never smokers), secondary ST users (current exclusive ST use among former smokers), exclusive cigarette smokers, dual users of ST and cigarettes, former smokers, and never tobacco users. We estimated geometric mean ratios using never tobacco users, cigarette smokers, and former smokers as referents, adjusting for demographic and health conditions, creatinine (for F2-isoprostane), and pack-years in smoker referent models. RESULTS BOPH levels among primary ST users were similar to both never tobacco users and former smokers. Most BOPH levels were lower among ST users compared with current smokers. Compared with never tobacco users, dual users had significantly higher sICAM-1, IL6, and F2-isoprostane. However, compared with smokers, dual users had similar biomarker levels. Former smokers and secondary ST users had similar levels of all five biomarkers. CONCLUSIONS ST users have lower levels of inflammatory and oxidative stress biomarkers than smokers. IMPACT ST use alone and in combination with smoking may result in different levels of inflammatory and oxidative stress levels.
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Affiliation(s)
- Joanne T Chang
- Center for Tobacco Products, U.S. Food and Drug Administration, Silver Spring, Maryland.
| | - Juan C Vivar
- Center for Tobacco Products, U.S. Food and Drug Administration, Silver Spring, Maryland
| | - Jamie Tam
- Center for Tobacco Products, U.S. Food and Drug Administration, Silver Spring, Maryland.,Department of Health Policy and Management, Yale University School of Public Health, New Haven, Connecticut
| | - Hoda T Hammad
- Center for Tobacco Products, U.S. Food and Drug Administration, Silver Spring, Maryland
| | - Carol H Christensen
- Center for Tobacco Products, U.S. Food and Drug Administration, Silver Spring, Maryland
| | - Dana M van Bemmel
- Center for Tobacco Products, U.S. Food and Drug Administration, Silver Spring, Maryland
| | - Babita Das
- Center for Tobacco Products, U.S. Food and Drug Administration, Silver Spring, Maryland
| | - Uliana Danilenko
- Division of Laboratory Science, National Center for Environmental Health, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Cindy M Chang
- Center for Tobacco Products, U.S. Food and Drug Administration, Silver Spring, Maryland
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11
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Xia B, Blount BC, Guillot T, Brosius C, Li Y, Van Bemmel DM, Kimmel HL, Chang CM, Borek N, Edwards KC, Lawrence C, Hyland A, Goniewicz ML, Pine BN, Xia Y, Bernert JT, De Castro BR, Lee J, Brown JL, Arnstein S, Choi D, Wade EL, Hatsukami D, Ervies G, Cobos A, Nicodemus K, Freeman D, Hecht SS, Conway K, Wang L. Tobacco-Specific Nitrosamines (NNAL, NNN, NAT, and NAB) Exposures in the US Population Assessment of Tobacco and Health (PATH) Study Wave 1 (2013-2014). Nicotine Tob Res 2021; 23:573-583. [PMID: 32716026 PMCID: PMC7885786 DOI: 10.1093/ntr/ntaa110] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 06/19/2020] [Indexed: 12/12/2022]
Abstract
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.
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Affiliation(s)
- Baoyun Xia
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - Benjamin C Blount
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - Tonya Guillot
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - Christina Brosius
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - Yao Li
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - Dana M Van Bemmel
- Office of Science, Center for Tobacco Products, U.S. Food and Drug Administration, Silver Spring, MD
| | - Heather L Kimmel
- Division of Epidemiology, Services and Prevention Research, National Institute of Drug Abuse, Bethesda, MD
| | - Cindy M Chang
- Office of Science, Center for Tobacco Products, U.S. Food and Drug Administration, Silver Spring, MD
| | - Nicolette Borek
- Office of Science, Center for Tobacco Products, U.S. Food and Drug Administration, Silver Spring, MD
| | | | | | - Andrew Hyland
- Roswell Park Comprehensive Cancer Center, Roswell Park Cancer Institute, Buffalo, NY
| | - Maciej L Goniewicz
- Roswell Park Comprehensive Cancer Center, Roswell Park Cancer Institute, Buffalo, NY
| | - Brittany N Pine
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - Yang Xia
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - John T Bernert
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - B Rey De Castro
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - John Lee
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - Justin L Brown
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - Stephen Arnstein
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - Diane Choi
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - Erin L Wade
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | | | - Gladys Ervies
- Office of Science, Center for Tobacco Products, U.S. Food and Drug Administration, Silver Spring, MD
| | - Angel Cobos
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - Keegan Nicodemus
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - Dana Freeman
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
| | - Stephen S Hecht
- Masonic Cancer Center, University of Minnesota, Minneapolis, MN
| | - Kevin Conway
- Division of Epidemiology, Services and Prevention Research, National Institute of Drug Abuse, Bethesda, MD
| | - Lanqing Wang
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA
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Luo X, Carmella SG, Chen M, Jensen JA, Wilkens LR, Le Marchand L, Hatsukami DK, Murphy SE, Hecht SS. Urinary Cyanoethyl Mercapturic Acid, a Biomarker of the Smoke Toxicant Acrylonitrile, Clearly Distinguishes Smokers From Nonsmokers. Nicotine Tob Res 2021; 22:1744-1747. [PMID: 32391548 DOI: 10.1093/ntr/ntaa080] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 05/05/2020] [Indexed: 12/22/2022]
Abstract
INTRODUCTION Cyanoethyl mercapturic acid (CEMA) is a urinary metabolite of acrylonitrile, a toxicant found in substantial quantities in cigarette smoke, but not in non-combusted products such as e-cigarettes or smokeless tobacco and rarely in the diet or in the general human environment. Thus, we hypothesized that CEMA is an excellent biomarker of combusted tobacco product use. AIMS AND METHODS We tested this hypothesis by analyzing CEMA in the urine of 1259 cigarette smokers (urinary cotinine ≥25 ng/mL) and 1191 nonsmokers. The analyses of CEMA and cotinine were performed by validated liquid chromatography-tandem mass spectrometry methods. Logistic regression was fit for log-transformed CEMA to construct the receiver operating characteristic curve. RESULTS We found that a CEMA cutpoint of 27 pmol/mL urine differentiated cigarette smokers from nonsmokers with sensitivity and specificity greater than 99%. The use of different cotinine cutpoints to define smokers (10-30 ng/mL) had little effect on the results. CONCLUSIONS CEMA is a highly reliable urinary biomarker to identify users of combusted tobacco products such as cigarettes as opposed to users of non-combusted products, medicinal nicotine, or nonusers of tobacco products. IMPLICATIONS CEMA can be used to distinguish users of combusted tobacco products from non-combusted products such as e-cigarettes, smokeless tobacco, and medicinal nicotine. Levels of CEMA in the urine of people who use these non-combusted products are extremely low, in contrast to cotinine.
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Affiliation(s)
- Xianghua Luo
- Masonic Cancer Center, University of Minnesota, Minneapolis, MN
| | | | - Menglan Chen
- Masonic Cancer Center, University of Minnesota, Minneapolis, MN
| | - Joni A Jensen
- Masonic Cancer Center, University of Minnesota, Minneapolis, MN
| | | | | | | | - Sharon E Murphy
- Masonic Cancer Center, University of Minnesota, Minneapolis, MN
| | - Stephen S Hecht
- Masonic Cancer Center, University of Minnesota, Minneapolis, MN
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Majeed B, Linder D, Eissenberg T, Tarasenko Y, Smith D, Ashley D. Cluster analysis of urinary tobacco biomarkers among U.S. adults: Population Assessment of Tobacco and Health (PATH) biomarker study (2013-2014). Prev Med 2020; 140:106218. [PMID: 32693174 PMCID: PMC7680301 DOI: 10.1016/j.ypmed.2020.106218] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 07/08/2020] [Accepted: 07/14/2020] [Indexed: 01/14/2023]
Abstract
Tobacco use delivers nicotine, tobacco-specific nitrosamines (TSNAs), volatile organic compounds (VOCs), and polycyclic aromatic hydrocarbons (PAHs), which are metabolized and excreted in urine offering useful biomarkers of exposure. Previous studies compared individual toxicants across tobacco users. Based on a group of biomarkers, cluster analysis was used to define tobacco toxicant exposure profiles. Clusters with distinct exposure profiles, were determined and described, based on levels of urinary biomarkers of exposure to nicotine, TSNAs, VOCs, and PAHs among a national sample of current, established, adult tobacco users, and examine the association of use behavior and cluster membership. The PATH Biomarker Wave 1 data were analyzed. Current established tobacco users with complete urinary biomarker data were included (N = 6724). User groups included cigarette smokers, users of electronic cigarette (ECIG), smokeless tobacco (SLT), and dual and poly tobacco users. Cluster analysis, pairwise comparisons, and multinomial logistic regression were conducted. Cigarette smokers were primarily in clusters with high biomarker concentrations across all groups, but actual concentrations were associated with smoking quantity. A cluster with high TSNAs but low levels of PAHs and VOCs was heavily populated by SLT users. Exclusive ECIG users, depending on use frequency, were predominantly in clusters with low biomarker concentrations, except for one cluster that had relatively high TSNAs. Clusters heavily populated by dual and poly tobacco users were the same as those heavily populated by cigarette smokers. Ten exposure profiles (clusters) were determined and linked to tobacco use behavior. Findings could inform future research and policy initiatives.
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Affiliation(s)
- Ban Majeed
- Department of Population Health Sciences, Medical College of Georgia, Augusta University, Augusta, GA, United States of America.
| | - Daniel Linder
- Department of Population Health Sciences, Medical College of Georgia, Augusta University, Augusta, GA, United States of America
| | - Thomas Eissenberg
- Center for the Study of Tobacco Products, Department of Psychology, Virginia Commonwealth University, Richmond, VA, United States of America
| | - Yelena Tarasenko
- Division of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA, United States of America
| | - Danielle Smith
- Department of Health Behavior, Roswell Park Comprehensive Cancer Center, Buffalo, NY, United States of America
| | - David Ashley
- Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA, United States of America
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Agaku I, Odani S, Nelson JR. U.S. Military Veteran Versus Nonveteran Use of Licit and Illicit Substances. Am J Prev Med 2020; 59:733-741. [PMID: 33012620 DOI: 10.1016/j.amepre.2020.04.027] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Revised: 04/16/2020] [Accepted: 04/17/2020] [Indexed: 11/16/2022]
Abstract
INTRODUCTION To provide up-to-date substance use surveillance data among U.S. military veterans versus nonveterans, this study assesses current use of tobacco products, alcohol, marijuana, prescription pain relievers, tranquilizers, sedatives, stimulants, cocaine, heroin, methamphetamines, inhalants, and hallucinogens. METHODS Pooled data were from the 2015-2017 National Survey on Drug Use and Health, a nationally representative, self-reported survey of the U.S. adult non-institutionalized population. Military veterans were those who had "ever been in the United States Armed Forces" and were "now separated/retired from reserves/active duty" (n=7,301). Nonveterans were those who had never been in the U.S. Armed forces (n=121,366). Age- and gender-stratified weighted prevalence estimates were calculated and compared with chi-square tests. All analyses were conducted in 2019. RESULTS Illicit substance use, including marijuana and cocaine, was generally lower among veterans than nonveterans, whereas use of licit substances such as tobacco and alcohol was higher among veterans than nonveterans. The most commonly used substances among veterans were tobacco and alcohol. Among male participants aged 18-25 years, 59.8% of veterans reported past-12-month cigarette/cigar smoking (vs 46.6% of nonveterans), whereas 17.6% reported heavy drinking (vs 12.2% of nonveterans). For both cigarette/cigar smoking and binge drinking, there was a marked narrowing of the male-female gap in prevalence with increasing age among veterans. Female veterans aged 18-25 years reported significantly higher opioid use than their nonveteran counterparts (54.7% vs 35.0%); they also had the highest prevalence of opioid misuse (15.3%) than any other group. CONCLUSIONS Intensified efforts are needed to reduce substance use among veterans and provide cessation and mental health services.
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Affiliation(s)
- Israel Agaku
- Department of Oral Health Policy and Epidemiology, Harvard School of Dental Medicine, Boston, Massachusetts.
| | - Satomi Odani
- School of Medicine, University of Crete, Heraklion, Greece
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Urinary Acrylonitrile Metabolite Concentrations Before and after Smoked, Vaporized, and Oral Cannabis in Frequent and Occasional Cannabis Users. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17186438. [PMID: 32899602 PMCID: PMC7558117 DOI: 10.3390/ijerph17186438] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 08/31/2020] [Accepted: 09/01/2020] [Indexed: 12/25/2022]
Abstract
Cannabis use through smoking, vaping, or ingestion is increasing, but only limited studies have investigated the resulting exposure to harmful chemicals. N-acetyl-S-(2-cyanoethyl)-L-cysteine (2CYEMA), a urinary metabolite of acrylonitrile, a possible carcinogen, is elevated in the urine of past-30-day cannabis users compared to non-cannabis users. Five frequent and five occasional cannabis users smoked and vaped cannabis on separate days; one also consumed cannabis orally. Urine samples were collected before and up to 72 h post dose and urinary 2CYEMA was quantified. We compared 2CYEMA pre-exposure levels, maximum concentration, time at maximum concentration for occasional versus frequent users following different exposure routes, and measured half-life of elimination. Smoking cannabis joints rapidly (within 10 min) increased 2CYEMA in the urine of occasional cannabis users, but not in frequent users. Urine 2CYEMA did not consistently increase following vaping or ingestion in either study group. Cigarette smokers had high pre-exposure concentrations of 2CYEMA. Following cannabis smoking, the half-lives of 2CYEMA ranged from 2.5 to 9.0 h. 2CYEMA is an effective biomarker of cannabis smoke exposure, including smoke from a single cannabis joint, however, not from vaping or when consumed orally. When using 2CYEMA to evaluate exposure in cannabis users, investigators should collect the details about tobacco smoking, route of consumption, and time since last use as possible covariates.
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