Literature DB >> 8265764

Saliva cotinine and recent smoking--evidence for a nonlinear relationship.

G E Swan1, K Habina, B Means, J B Jobe, J L Esposito.   

Abstract

Cotinine concentration in various body fluids is considered to be among the most useful markers of nicotine exposure currently available. Despite the prevailing consensus concerning cotinine's usefulness, cotinine's large intrasubject variability has led some to question the value of a single-point measurement. Several individual differences (for example, age, race, sex, and so forth) may affect cotinine excretion, and a peculiar nonlinearity between the number of cigarettes smoked and cotinine concentration has been reported previously in the literature. The purpose of this investigation was to examine the nature of the association between cotinine and reported number of cigarettes smoked after adjustment for the relationship between cotinine and age, a key individual difference known to affect drug absorption, distribution, metabolism, excretion, and tissue sensitivity. The authors examined the relationship between saliva cotinine and daily cigarette consumption in 116 smokers (mean age = 37.4 years; average number of cigarettes smoked daily = 20.1) who logged each cigarette into a hand-held computer as part of a study on the accuracy of recall. The Pearson correlation between saliva cotinine and the logged number of cigarettes smoked in the previous 17 hours (the time window corresponding to the half-life of cotinine) accounted for significantly more of the variance in cotinine than did the average logged number of cigarettes smoked daily during 5 days. Age was also significantly associated with cotinine levels. Further examination of the relationship between cotinine and amount smoked in the previous 17 hours revealed evidence for a significant nonlinear component. Inclusion of both age and a cubic nonlinear component of daily cigarette consumption resulted in further significant improvement in the amount of variance accounted for in cotinine levels. These results suggest that adjustments forage and the inclusion of a nonlinear component for cigarette consumption will result in more precise use of cotinine as a validation tool for existing differences in smoking levels.

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Year:  1993        PMID: 8265764      PMCID: PMC1403462     

Source DB:  PubMed          Journal:  Public Health Rep        ISSN: 0033-3549            Impact factor:   2.792


  13 in total

1.  Cotinine in the serum, saliva, and urine of nonsmokers, passive smokers, and active smokers.

Authors:  M A Wall; J Johnson; P Jacob; N L Benowitz
Journal:  Am J Public Health       Date:  1988-06       Impact factor: 9.308

2.  Can genetic constitution affect the 'objective' diagnosis of nicotine dependence?

Authors:  J E Henningfield
Journal:  Am J Public Health       Date:  1990-09       Impact factor: 9.308

Review 3.  Titrating exposure to tobacco smoke using cotinine--a minefield of misunderstandings.

Authors:  J R Idle
Journal:  J Clin Epidemiol       Date:  1990       Impact factor: 6.437

Review 4.  Drug therapy. Pharmacologic aspects of cigarette smoking and nicotine addiction.

Authors:  N L Benowitz
Journal:  N Engl J Med       Date:  1988-11-17       Impact factor: 91.245

5.  Gas chromatographic determination of trans-3'-hydroxycotinine, a major metabolite of nicotine in smokers.

Authors:  G B Neurath; F G Pein
Journal:  J Chromatogr       Date:  1987-04-10

6.  Properties of saliva cotinine in young adult light smokers.

Authors:  K B Carey; D B Abrams
Journal:  Am J Public Health       Date:  1988-07       Impact factor: 9.308

7.  Saliva cotinine as a measure of smoking status in field settings.

Authors:  D B Abrams; M J Follick; L Biener; K B Carey; J Hitti
Journal:  Am J Public Health       Date:  1987-07       Impact factor: 9.308

8.  Cigarette smoking: carboxyhemoglobin, plasma nicotine, cotinine and thiocyanate vs self-reported smoking data and cardiovascular disease.

Authors:  P Hill; N J Haley; E L Wynder
Journal:  J Chronic Dis       Date:  1983

9.  Cotinine validation of self-reported smoking in commercially run community surveys.

Authors:  J P Pierce; T Dwyer; E DiGiusto; T Carpenter; C Hannam; A Amin; C Yong; G Sarfaty; J Shaw; N Burke
Journal:  J Chronic Dis       Date:  1987

10.  Smokers of low-yield cigarettes do not consume less nicotine.

Authors:  N L Benowitz; S M Hall; R I Herning; P Jacob; R T Jones; A L Osman
Journal:  N Engl J Med       Date:  1983-07-21       Impact factor: 91.245

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  9 in total

1.  Quality of measurement of smoking status by self-report and saliva cotinine among pregnant women.

Authors:  N R Boyd; R A Windsor; L L Perkins; J B Lowe
Journal:  Matern Child Health J       Date:  1998-06

2.  Pharmacologic characterization of a nicotine-discriminative stimulus in rhesus monkeys.

Authors:  Colin S Cunningham; Martin A Javors; Lance R McMahon
Journal:  J Pharmacol Exp Ther       Date:  2012-03-21       Impact factor: 4.030

3.  Attenuated nicotine-like effects of varenicline but not other nicotinic ACh receptor agonists in monkeys receiving nicotine daily.

Authors:  Colin S Cunningham; Megan J Moerke; Martin A Javors; F Ivy Carroll; Lance R McMahon
Journal:  Br J Pharmacol       Date:  2016-11-06       Impact factor: 8.739

4.  Utility and relationships of biomarkers of smoking in African-American light smokers.

Authors:  Man Ki Ho; Babalola Faseru; Won S Choi; Nicole L Nollen; Matthew S Mayo; Janet L Thomas; Kolawole S Okuyemi; Jasjit S Ahluwalia; Neal L Benowitz; Rachel F Tyndale
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2009-12       Impact factor: 4.254

5.  How many cigarettes did you smoke? Assessing cigarette consumption by global report, Time-Line Follow-Back, and ecological momentary assessment.

Authors:  Saul Shiffman
Journal:  Health Psychol       Date:  2009-09       Impact factor: 4.267

6.  Genetic polymorphisms in 15q25 and 19q13 loci, cotinine levels, and risk of lung cancer in EPIC.

Authors:  Maria N Timofeeva; James D McKay; George Davey Smith; Mattias Johansson; Graham B Byrnes; Amélie Chabrier; Caroline Relton; Per Magne Ueland; Stein Emil Vollset; Øivind Midttun; Ottar Nygård; Nadia Slimani; Isabelle Romieu; Françoise Clavel-Chapelon; Marie-Christine Boutron-Ruault; Guy Fagherazzi; Rudolf Kaaks; Birgit Teucher; Heiner Boeing; Cornelia Weikert; H Bas Bueno-de-Mesquita; Carla van Gils; Petra H M Peeters; Antonio Agudo; Aurelio Barricarte; Jose-Maria Huerta; Laudina Rodríguez; Maria-José Sánchez; Nerea Larrañaga; Kay-Tee Khaw; Nick Wareham; Naomi E Allen; Ruth C Travis; Valentina Gallo; Teresa Norat; Vittorio Krogh; Giovanna Masala; Salvatore Panico; Carlotta Sacerdote; Rosario Tumino; Antonia Trichopoulou; Pagona Lagiou; Dimitrios Trichopoulos; Torgny Rasmuson; Göran Hallmans; Elio Riboli; Paolo Vineis; Paul Brennan
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2011-08-23       Impact factor: 4.254

7.  Investigating the added value of biomarkers compared with self-reported smoking in predicting future e-cigarette use: Evidence from a longitudinal UK cohort study.

Authors:  Jasmine N Khouja; Marcus R Munafò; Caroline L Relton; Amy E Taylor; Suzanne H Gage; Rebecca C Richmond
Journal:  PLoS One       Date:  2020-07-14       Impact factor: 3.240

8.  Salivary cotinine concentrations in daily smokers in Barcelona, Spain: a cross-sectional study.

Authors:  Marcela Fu; Esteve Fernandez; Jose M Martínez-Sánchez; José A Pascual; Anna Schiaffino; Antoni Agudo; Carles Ariza; Josep M Borràs; Jonathan M Samet
Journal:  BMC Public Health       Date:  2009-09-03       Impact factor: 3.295

9.  Applying Tobacco, Environmental, and Dietary-Related Biomarkers to Understand Cancer Etiology and Evaluate Prevention Strategies.

Authors:  Lisa A Peterson; Silvia Balbo; Naomi Fujioka; Dorothy K Hatsukami; Stephen S Hecht; Sharon E Murphy; Irina Stepanov; Natalia Y Tretyakova; Robert J Turesky; Peter W Villalta
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2020-02-12       Impact factor: 4.254

  9 in total

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