Literature DB >> 34383052

Validation of the Wave 1 and Wave 2 Population Assessment of Tobacco and Health (PATH) Study Indicators of Tobacco Dependence Using Biomarkers of Nicotine Exposure Across Tobacco Products.

David R Strong1,2, Eric Leas1,2, Madison Noble1,2, Martha White1,2, Allison Glasser3, Kristie Taylor4, Kathryn C Edwards4, Kevin C Frissell4, Wilson M Compton5, Kevin P Conway5, Elizabeth Lambert5, Heather L Kimmel5, Marushka L Silveira5,6, Lynn C Hull7, Dana van Bemmel7, Megan J Schroeder7, Kenneth Michael Cummings8, Andrew Hyland9, June Feng10, Benjamin Blount10, Lanqing Wang10, Ray Niaura3.   

Abstract

INTRODUCTION: This study examined the predictive relationships between biomarkers of nicotine exposure and 16-item self-reported level of tobacco dependence (TD) and subsequent tobacco use outcomes. AIMS AND METHODS: The Population Assessment of Tobacco and Health (PATH) Study surveyed adult current established tobacco users who provided urine biospecimens at Wave 1 (September 2013-December 2014) and completed the Wave 2 (October 2014-October 2015) interview (n = 6872). Mutually exclusive user groups at Wave 1 included: Cigarette Only, E-cigarette Only, Cigar Only, Hookah Only, Smokeless Tobacco Only, Cigarette Plus E-cigarette, multiple tobacco product users who smoked cigarettes, and multiple tobacco product users who did not smoke cigarettes. Total Nicotine Equivalents (TNE-2) and TD were measured at Wave 1. Approximate one-year outcomes included frequency/quantity used, quitting, and adding/switching to different tobacco products.
RESULTS: For Cigarette Only smokers and multiple tobacco product users who smoked cigarettes, higher TD and TNE-2 were associated with: a tendency to smoke more, smoking more frequently over time, decreased likelihood of switching away from cigarettes, and decreased probability of quitting after one year. For other product user groups, Wave 1 TD and/or TNE-2 were less consistently related to changes in quantity and frequency of product use, or for adding or switching products, but higher TNE-2 was more consistently predictive of decreased probability of quitting.
CONCLUSIONS: Self-reported TD and nicotine exposure assess common and independent aspects of dependence in relation to tobacco use behaviors for cigarette smokers. For other product user groups, nicotine exposure is a more consistent predictor of quitting than self-reported TD. IMPLICATIONS: This study suggests that smoking cigarettes leads to the most coherent pattern of associations consistent with a syndrome of TD. Because cigarettes continue to be prevalent and harmful, efforts to decrease their use may be accelerated via conventional means (eg, smoking cessation interventions and treatments), but also perhaps by decreasing their dependence potential. The implications for noncombustible tobacco products are less clear as the stability of tobacco use patterns that include products such as e-cigarettes continue to evolve. TD, nicotine exposure measures, and consumption could be used in studies that attempt to understand and predict product-specific tobacco use behavioral outcomes.
© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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Year:  2022        PMID: 34383052      PMCID: PMC8666120          DOI: 10.1093/ntr/ntab162

Source DB:  PubMed          Journal:  Nicotine Tob Res        ISSN: 1462-2203            Impact factor:   5.825


  22 in total

Review 1.  Measuring nicotine dependence among youth: a review of available approaches and instruments.

Authors:  S M Colby; S T Tiffany; S Shiffman; R S Niaura
Journal:  Drug Alcohol Depend       Date:  2000-05-01       Impact factor: 4.492

2.  A Nicotine-Focused Framework for Public Health.

Authors:  Scott Gottlieb; Mitchell Zeller
Journal:  N Engl J Med       Date:  2017-08-16       Impact factor: 91.245

3.  Nicotine Dependence and Urinary Nicotine, Cotinine and Hydroxycotinine Levels in Daily Smokers.

Authors:  Ilse P I Van Overmeire; Tom De Smedt; Paul Dendale; Kristiaan Nackaerts; Hilde Vanacker; Jan F A Vanoeteren; Danny M G Van Laethem; Joris Van Loco; Koen A J De Cremer
Journal:  Nicotine Tob Res       Date:  2016-04-15       Impact factor: 4.244

Review 4.  Nicotine addiction.

Authors:  Neal L Benowitz
Journal:  N Engl J Med       Date:  2010-06-17       Impact factor: 91.245

5.  Multi-rule quality control for the age-related eye disease study.

Authors:  Samuel P Caudill; Rosemary L Schleicher; James L Pirkle
Journal:  Stat Med       Date:  2008-09-10       Impact factor: 2.373

6.  Design and methods of the Population Assessment of Tobacco and Health (PATH) Study.

Authors:  Andrew Hyland; Bridget K Ambrose; Kevin P Conway; Nicolette Borek; Elizabeth Lambert; Charles Carusi; Kristie Taylor; Scott Crosse; Geoffrey T Fong; K Michael Cummings; David Abrams; John P Pierce; James Sargent; Karen Messer; Maansi Bansal-Travers; Ray Niaura; Donna Vallone; David Hammond; Nahla Hilmi; Jonathan Kwan; Andrea Piesse; Graham Kalton; Sharon Lohr; Nick Pharris-Ciurej; Victoria Castleman; Victoria R Green; Greta Tessman; Annette Kaufman; Charles Lawrence; Dana M van Bemmel; Heather L Kimmel; Ben Blount; Ling Yang; Barbara O'Brien; Cindy Tworek; Derek Alberding; Lynn C Hull; Yu-Ching Cheng; David Maklan; Cathy L Backinger; Wilson M Compton
Journal:  Tob Control       Date:  2016-08-08       Impact factor: 7.552

7.  The nicotine dependence syndrome scale: a multidimensional measure of nicotine dependence.

Authors:  Saul Shiffman; Andrew Waters; Mary Hickcox
Journal:  Nicotine Tob Res       Date:  2004-04       Impact factor: 4.244

8.  Nicotine dependence in cigarette smoking: an empirically-based, multivariate model.

Authors:  O F Pomerleau; J B Fertig; S O Shanahan
Journal:  Pharmacol Biochem Behav       Date:  1983-08       Impact factor: 3.533

Review 9.  Monitoring the tobacco use epidemic II: The agent: Current and emerging tobacco products.

Authors:  Steven D Stellman; Mirjana V Djordjevic
Journal:  Prev Med       Date:  2008-09-20       Impact factor: 4.018

Review 10.  Pharmacology of nicotine: addiction, smoking-induced disease, and therapeutics.

Authors:  Neal L Benowitz
Journal:  Annu Rev Pharmacol Toxicol       Date:  2009       Impact factor: 13.820

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  1 in total

1.  Understanding heterogeneity among individuals who smoke cigarettes and vape: assessment of biomarkers of exposure and potential harm among subpopulations from the PATH Wave 1 Data.

Authors:  Pavel N Lizhnyak; Brendan Noggle; Lai Wei; Jeffery Edmiston; Elizabeth Becker; Ryan A Black; Mohamadi Sarkar
Journal:  Harm Reduct J       Date:  2022-08-17
  1 in total

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