Evidence map›Paper›PMID 34383052›Full record

ArticleNicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco2022

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 Strong, Eric Leas, Madison Noble, Martha White, Allison Glasser, Kristie Taylor, Kathryn C Edwards, Kevin C Frissell, Wilson M Compton, Kevin P Conway and 12 more

Erratum issuedOpen access · greenAbstract read
In one paragraph

Article in Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.3field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 23 citations in OpenAlex.

  1. Urinary Tobacco and Nicotine Exposure Biomarkers as Predictors of Transitions between Cigarette and e-Cigarette Use in the Exhale Longitudinal Cohort Study.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2026
    Observational
  2. Article
  3. Article
  4. Article
  5. Indicators of Tobacco Dependence Among Youth: Findings From Wave 1 (2013-2014) of the Population Assessment of Tobacco and Health Study.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2023
    Article
  6. Article
  7. Article
  8. Measuring Nicotine Dependence Among Adolescent and Young Adult Cigarillo Users.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2022
    Article
  9. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

22 authors at 7 institutions in 1 country.

David R StrongCancer Prevention & Control Program, Moores Cancer Center University of California, San Diego, CA, USA.
Eric LeasCancer Prevention & Control Program, Moores Cancer Center University of California, San Diego, CA, USA.
Madison NobleCancer Prevention & Control Program, Moores Cancer Center University of California, San Diego, CA, USA.
Martha WhiteCancer Prevention & Control Program, Moores Cancer Center University of California, San Diego, CA, USA.
Allison GlasserDepartment of Social and Behavioral Sciences, College of Global Public Health, New York University, New York, NY, USA.ORCID 0000-0002-6582-2684
Kristie TaylorWestat, Rockville, MD, USA.
Kathryn C EdwardsWestat, Rockville, MD, USA.
Kevin C FrissellWestat, Rockville, MD, USA.
Wilson M ComptonNational Institute on Drug Abuse (NIDA/NIH), Bethesda, MD, USA.
Kevin P ConwayNational Institute on Drug Abuse (NIDA/NIH), Bethesda, MD, USA.
Elizabeth LambertNational Institute on Drug Abuse (NIDA/NIH), Bethesda, MD, USA.
Heather L KimmelNational Institute on Drug Abuse (NIDA/NIH), Bethesda, MD, USA.ORCID 0000-0001-8278-0095
Marushka L SilveiraNational Institute on Drug Abuse (NIDA/NIH), Bethesda, MD, USA.ORCID 0000-0002-4880-2550
Lynn C HullCenter for Tobacco Products, FDA, Silver Spring, MD, USA.
Dana van BemmelCenter for Tobacco Products, FDA, Silver Spring, MD, USA.
Megan J SchroederCenter for Tobacco Products, FDA, Silver Spring, MD, USA.
Kenneth Michael CummingsMedical University of South Carolina, Charleston, SC, USA.
Andrew HylandRoswell Park Cancer Institute, Buffalo, NY, USA.
June FengCenters for Disease Control and Prevention, Atlanta, GA, USA.
Benjamin BlountCenters for Disease Control and Prevention, Atlanta, GA, USA.
Lanqing WangCenters for Disease Control and Prevention, Atlanta, GA, USA.ORCID 0000-0001-6620-7096
Ray NiauraDepartment of Social and Behavioral Sciences, College of Global Public Health, New York University, New York, NY, USA.
National Institute on Drug Abuse · USUniversity of California San Diego · USCenters for Disease Control and Prevention · USWestat (United States) · USNew York University · USMedical University of South Carolina · USRoswell Park Comprehensive Cancer Center · US

Funding

CDC HHSFDA HHSNIDA NIH HHS HHSN271201100027CNIDA NIH HHS HHSN271201600001C
6 · The paper itself

Abstract

introductionThis 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

methodsThe 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.

resultsFor 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.

conclusionsSelf-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.

Indexed as

Electronic Nicotine Delivery SystemsTobacco ProductsTobacco Use DisorderAdultBiomarkersHumansNicotineTobacco UseBiomarkersNicotine

Identifiers

PMID34383052
PMCPMC8666120
OpenAlexW3190082415

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.