Literature DB >> 17164388

Digital image analysis of cigarette filter stains as an indicator of compensatory smoking.

Andrew A Strasser1, Richard J O'Connor, Marc E Mooney, E Paul Wileyto.   

Abstract

OBJECTIVE: Cigarette filters trap a significant portion of carcinogen-containing smoke particulate and may provide an indication of cigarette constituent exposure. A technique for quantifying filter tar staining with digital imaging has shown predictive value between typical total puff volume and filter tar stain intensity. The current study uses smoking topography data acquired during an examination of compensatory smoking of Quest cigarettes and digital analyses of the tar stains of the spent Quest cigarette filters. Due to reduced nicotine levels, we hypothesized compensatory smoking to occur. The purposes of the current study were to describe the physical characteristics of the Quest cigarettes, to further validate the effect of puff volume on filter tar staining, and to examine the effect of compensatory smoking on changes in filter tar staining, hypothesizing that compensatory smoking would result in more intense tar staining.
METHODS: Physical characteristics of the Quest cigarettes were measured to characterize the product. Spent cigarette filters were digitally analyzed for color intensity features, matched to smoking topography measures, and examined in regression models. Difference scores for digital imaging and smoking topography were used in a regression model to identify the effect of compensatory smoking on tar stain.
RESULTS: Total puff volume was a significant predictor of a*center (redness) [beta = 0.003 (SE, 0.0004), R2 = 0.42, t = 7.87, P < 0.001] and L*center (lightness) [beta = -0.015 (SE, 0.002), R2 = 0.45, t = -8.18, P < 0.001] for Quest cigarettes and a significant predictor of a*center [beta = 0.003 (SE, 0.0005), R2 = 0.37, t = 5.27, P < 0.001] and L*center [beta = -0.009 (SE, 0.002), R2 = 0.35, t = -5.05, P < 0.001] for own preferred brand. Regression models indicate total puff volume difference was a significant predictor of L*center difference [beta = -0.01 (SE, 0.003), R2 = 0.171, t = -3.15, P = 0.003] and approached significance for a*center difference [beta = 0.002 (SE, 0.001), R2 = 0.057, t = 1.99, P = 0.053].
CONCLUSION: Results suggest that compensatory smoking may be detectable by darkening and reddening of the tar stain. This type of measure could be useful in quantifying the extent to which human smokers smoke differently than standard testing protocols and in assessing the prevalence of compensatory smoking in population samples.

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Year:  2006        PMID: 17164388     DOI: 10.1158/1055-9965.EPI-06-0623

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  7 in total

1.  Effect of cigarette smoke on acrylic resin teeth.

Authors:  Seema S Patil; Dhakshaini M R; Anil Kumar Gujjari
Journal:  J Clin Diagn Res       Date:  2013-09-10

2.  Transdisciplinary Tobacco Use Research Centers: research achievements and future implications.

Authors:  Timothy B Baker; K Michael Cummings; Dorothy K Hatsukami; C Anderson Johnson; Caryn Lerman; Raymond Niaura; Stephanie S O'Malley
Journal:  Nicotine Tob Res       Date:  2009-07-24       Impact factor: 4.244

Review 3.  Role of cigarette sensory cues in modifying puffing topography.

Authors:  Vaughan W Rees; Jennifer M Kreslake; Geoffrey Ferris Wayne; Richard J O'Connor; K Michael Cummings; Gregory N Connolly
Journal:  Drug Alcohol Depend       Date:  2012-02-25       Impact factor: 4.492

4.  Nicotine metabolite ratio predicts smoking topography and carcinogen biomarker level.

Authors:  Andrew A Strasser; Neal L Benowitz; Angela G Pinto; Kathy Z Tang; Stephen S Hecht; Steve G Carmella; Rachel F Tyndale; Caryn E Lerman
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2011-01-06       Impact factor: 4.254

Review 5.  Cigarette filter-based assays as proxies for toxicant exposure and smoking behavior--a literature review.

Authors:  John L Pauly; Richard J O'Connor; Geraldine M Paszkiewicz; K Michael Cummings; Mirjana V Djordjevic; Peter G Shields
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2009-12       Impact factor: 4.254

6.  PREP advertisement features affect smokers' beliefs regarding potential harm.

Authors:  A A Strasser; K Z Tang; M D Tuller; J N Cappella
Journal:  Tob Control       Date:  2008-09       Impact factor: 7.552

7.  Do non-daily smokers compensate for reduced cigarette consumption when smoking very-low-nicotine-content cigarettes?

Authors:  Saul Shiffman; Jason M Mao; Brenda F Kurland; Sarah M Scholl
Journal:  Psychopharmacology (Berl)       Date:  2018-10-05       Impact factor: 4.530

  7 in total

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