Literature DB >> 25587199

The Pot Calling the Kettle Black? A Comparison of Measures of Current Tobacco Use.

Vidhura Tennekoon1, Robert Rosenman2.   

Abstract

Researchers often use the discrepancy between self-reported and biochemically assessed active smoking status to argue that self-reported smoking status is not reliable, ignoring the limitations of biochemically assessed measures and treating it as the gold standard in their comparisons. Here, we employ econometric techniques to compare the accuracy of self-reported and biochemically assessed current tobacco use, taking into account measurement errors with both methods. Our approach allows estimating and comparing the sensitivity and specificity of each measure without directly observing true smoking status. The results, robust to several alternative specifications, suggest that there is no clear reason to think that one measure dominates the other in accuracy.

Entities:  

Keywords:  biochemical assessments; measurement error; misclassification; smoking prevalence; social desirability

Year:  2015        PMID: 25587199      PMCID: PMC4289150          DOI: 10.1080/00036846.2014.972546

Source DB:  PubMed          Journal:  Appl Econ        ISSN: 0003-6846


  12 in total

1.  A pint a day raises a man's pay; but smoking blows that gain away.

Authors:  Jan C van Ours
Journal:  J Health Econ       Date:  2004-09       Impact factor: 3.883

2.  The validity of self-reported nicotine product use in the 2001-2008 National Health and Nutrition Examination Survey.

Authors:  David Scott Yeager; Jon A Krosnick
Journal:  Med Care       Date:  2010-12       Impact factor: 2.983

Review 3.  The accuracy of self-reported smoking: a systematic review of the relationship between self-reported and cotinine-assessed smoking status.

Authors:  Sarah Connor Gorber; Sean Schofield-Hurwitz; Jill Hardt; Geneviève Levasseur; Mark Tremblay
Journal:  Nicotine Tob Res       Date:  2009-01-27       Impact factor: 4.244

4.  Biochemical marker of use is a better predictor of outcomes than self-report metrics in a contingency management smoking cessation analog study.

Authors:  Sterling McPherson; Robert R Packer; Jennifer M Cameron; Donelle N Howell; John M Roll
Journal:  Am J Addict       Date:  2013-05-24

5.  Comprehensive evaluation of variability in nicotine metabolism and CYP2A6 polymorphic alleles in four ethnic populations.

Authors:  Miki Nakajima; Tatsuki Fukami; Hiroyuki Yamanaka; Eriko Higashi; Haruko Sakai; Ryoko Yoshida; Jun-Tack Kwon; Howard L McLeod; Tsuyoshi Yokoi
Journal:  Clin Pharmacol Ther       Date:  2006-09       Impact factor: 6.875

6.  Is serum cotinine a better measure of cigarette smoking than self-report?

Authors:  E J Pérez-Stable; N L Benowitz; G Marín
Journal:  Prev Med       Date:  1995-03       Impact factor: 4.018

7.  Determinants of smoking initiation among women in five European countries: a cross-sectional survey.

Authors:  Debora L Oh; Julia E Heck; Carolyn Dresler; Shane Allwright; Margaretha Haglund; Sara S Del Mazo; Eva Kralikova; Isabelle Stucker; Elizabeth Tamang; Ellen R Gritz; Mia Hashibe
Journal:  BMC Public Health       Date:  2010-02-17       Impact factor: 3.295

8.  Severe and differential underestimation of self-reported smoking prevalence in Chinese adolescents.

Authors:  Jin Ma; Jingfen Zhu; Na Li; Yaping He; Yong Cai; Jun Qiao; Pamela Redmon; Zhiqiang Wang
Journal:  Int J Behav Med       Date:  2014-08

9.  Optimal serum cotinine levels for distinguishing cigarette smokers and nonsmokers within different racial/ethnic groups in the United States between 1999 and 2004.

Authors:  Neal L Benowitz; John T Bernert; Ralph S Caraballo; David B Holiday; Jiantong Wang
Journal:  Am J Epidemiol       Date:  2008-11-19       Impact factor: 4.897

10.  Social determinants of smoking in low- and middle-income countries: results from the World Health Survey.

Authors:  Ahmad Reza Hosseinpoor; Lucy Anne Parker; Edouard Tursan d'Espaignet; Somnath Chatterji
Journal:  PLoS One       Date:  2011-05-31       Impact factor: 3.240

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  2 in total

1.  Assessing 30-day quantity-frequency of U.S. adolescent cigarette smoking as a predictor of adult smoking 14 years later.

Authors:  M L Saddleson; L T Kozlowski; G A Giovino; G G Homish; M C Mahoney; M L Goniewicz
Journal:  Drug Alcohol Depend       Date:  2016-03-09       Impact factor: 4.492

2.  The "Real" Number of Washington State Adolescents Using Marijuana, and Why: A Misclassification Analysis.

Authors:  Sean M Murphy; Robert Rosenman
Journal:  Subst Use Misuse       Date:  2018-10-26       Impact factor: 2.164

  2 in total

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