Digital image analysis of cigarette filter staining to estimate smoke exposure

O’Connor, Richard J.; Kozlowski, Lynn T.; Hammond, David; Vance, Tammy T.; Stitt, Joseph P.; Cummings, K. Michael

doi:10.1080/14622200701485026

Cited by 26 publications

(20 citation statements)

References 11 publications

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“…The majority of studies (Ashare et al, 2012;Blank et al, 2009;Grainge et al, 2009;Hammond et al, 2005;June et al, 2011;June et al, 2012;McClure et al, 2012;McKee et al, 2006;McKee et al, 2011;O'Connor et al, 2007;O'Connor et al, 2010;Perkins et al, 2011;Rees et al, 2008;Veilleux et al, 2011;Williams et al, 2011) took an average of all puffs collected. This method offers the most complete representation of smoking behaviour and exposure to harmful elements of tobacco smoke, but is intolerant to the incorrect use of the device.…”

Section: Discussionmentioning

confidence: 99%

“…From the studies retained (n = 23), specific data reduction and exclusion criteria were provided in nine (Hammond, Fong, Cummings, & Hyland, 2005;King, McNamara, Conrad, & Cao, 2009;McKee et al, 2006;McKee et al, 2011;O'Connor et al, 2007;Perkins et al, 2011;Veilleux et al, 2011;Williams et al, 2011) and four (Grainge, Shahab, Hammond, O'Connor, & McNeill, 2009;McClure, Stitzer, & Vandrey, 2012;Muhammad-Kah et al, 2011;Williams et al, 2011) manuscripts, respectively. It was clearly stated in 11 (Blank, Disharoon, & Eissenberg, 2009;Faulkner et al, 2010;Grainge et al, 2009;Hammond et al, 2005;Hogarth, Dickinson, & Duka, 2010;June et al, 2011;June, Norton, Rees, & O'Connor, 2012;Matsumoto et al, 2013;McKee et al, 2006;Veilleux et al, 2011;Williams et al, 2011) manuscripts that an opportunity for familiarisation and instructions for the CReSS Pocket were provided to 4 articles excluded after reviewing methods section because CReSS Pocket was not employed 11 (of 23) articles stated whether an opportunity for participant familiarization was provided 9 (of 23) manuscripts provided clear, specific data reduction techniques 4 (of 23) manuscripts provided clear, specific data exclusion criteria 3 articles excluded after reviewing methods section because it was unclear what type of smoking topography instrument was employed 23 eligible studies and included in analysis 30 articles that met the following criteria: 1) Retrieved from MEDLINE, PubMed, and Scopus 2) Published between January 2001 and September 2012 3) Contained the following keywords "smoking topography", "puffing topography", and " CReSS"…”

Section: Description Of Included Studies and Data Reduction Techniquementioning

confidence: 99%

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A systematic review and analysis of data reduction techniques for the CReSS smoking topography device

et al. 2013

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I ntroduction: Characterising smoking behaviour in an objective and ecologically valid manner is integral to understanding health complications associated with tobacco use. Smoking topography (ST) provides a representation of the physical attributes of smoking. However, there is no clear guidance on ST data exclusion and reduction techniques and the impact of different techniques. Methods: A search was conducted using MEDLINE, PubMed, and Scopus and limited to studies published between 2001-2012. The search identified 23 studies using the CReSS device.Results: Few studies reported data reduction (n = 9) and exclusion (n = 4) criteria. Four data reduction techniques emerged and were applied to an existing dataset (n = 193, M age = 38.98, FTND = 5.19, mean 17.23 cigarettes/day). Using repeated measures ANOVA, there were significant (p < 0.05) differences among all techniques for puff volume, peak flow, puff duration and interpuff interval, which were attenuated upon controlling for puff count. Conclusions: This review highlights the inconsistency in the literature regarding the disclosure of smoking topography data treatment and provides clear evidence that outcomes vary depending on the technique used. Greater transparency is needed and consideration should be given by researchers to the potential impact of methodological decisions on study findings.

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Section: Discussionmentioning

confidence: 99%

Section: Description Of Included Studies and Data Reduction Techniquementioning

confidence: 99%

A systematic review and analysis of data reduction techniques for the CReSS smoking topography device

et al. 2013

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“…17 Changes in smoke topographydthat is, the way in which a cigarette is smoked including puff volume, puff time, dwell time and number of puffs per cigarettedall have profound effects on toxin exposure. 18 Even within a single individual, cigarettes are smoked differently and yields of toxin will vary, and it is likely that there will be differential exposure among the many toxins contained in smoke. 19 At present there are limited means of measuring exposure to specific smoke-derived toxins, but methodologies in this regard are advancing.…”

Section: Discussionmentioning

confidence: 99%

The Impact Of Nonlinear Smoking Effects In The Identification Of Gene-by-Smoking Interactions In COPD Genetics Studies

Castaldi

DeMeo

Hersh

et al. 2010

D17. Gene Environment Interactions

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BackgroundThe identification of gene-by-environment interactions is important for understanding the genetic basis of chronic obstructive pulmonary disease (COPD). Many COPD genetic association analyses assume a linear relationship between pack-years of smoking exposure and forced expiratory volume in 1 s (FEV 1 ); however, this assumption has not been evaluated empirically in cohorts with a wide spectrum of COPD severity. Methods The relationship between FEV 1 and pack-years of smoking exposure was examined in four large cohorts assembled for the purpose of identifying genetic associations with COPD. Using data from the Alpha-1 Antitrypsin Genetic Modifiers Study, the accuracy and power of two different approaches to model smoking were compared by performing a simulation study of a genetic variant with a range of gene-by-smoking interaction effects. Results Non-linear relationships between smoking and FEV 1 were identified in the four cohorts. It was found that, in most situations where the relationship between pack-years and FEV 1 is non-linear, a piecewise linear approach to model smoking and gene-by-smoking interactions is preferable to the commonly used total pack-years approach. The piecewise linear approach was applied to a genetic association analysis of the PI*Z allele in the Norway CaseeControl cohort and a potential PI*Z-by-smoking interaction was identified (p¼0.03 for FEV 1 analysis, p¼0.01 for COPD susceptibility analysis). Conclusion In study samples of subjects with a wide range of COPD severity, a non-linear relationship between pack-years of smoking and FEV 1 is likely. In this setting, approaches that account for this non-linearity can be more powerful and less biased than the more common approach of using total pack-years to model the smoking effect.Chronic obstructive pulmonary disease (COPD) is well suited to the study of gene-by-environment interactions since the major environmental risk factor for COPDdcigarette smokingdis known and quantifiable. With the advent of large wellpowered genome-wide association studies in COPD, the identification of such interactions may be feasible. However, there are a number of challenges to the identification of gene-by-smoking interactions in COPD: (1) the principal genetic risk factors for COPD are still in the process of being identified; (2) a variety of approaches have been used to model smoking effects; and (3) there is no empirical knowledge of the nature, extent or functional form of gene-by-smoking interactions in COPD.While cigarette smoking is easily quantifiable in terms of pack-years ((average daily number of cigarettes smoked/20 cigarettes per pack) 3 years of smoking), previous work has shown that packyears alone may be an overly simplistic means of modelling smoking exposure, and non-linear relations may be present.1 2 Many COPD genetic association analyses model smoking effects by including a pack-years term in a regression model, which assumes a linear relation between pack-years and forced expiratory volume in 1 s (FEV 1 ) or, in...

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“…Participants, Quest cigarettes, smoking topography measures, and CIELAB data were characterized using descriptive statistics. We hypothesized that L*center score, a measure of lightness, and a*center, a measure of redness to greenness, would be most responsive to total puff volume, as observed previously (17,23). We addressed these questions using (linear) regression methods, using the robust variance estimate to account for the repeated measures.…”

Section: Methodsmentioning

confidence: 99%

“…The specifics of the imaging system and technique are described in greater detail elsewhere (22,23). In brief, the system involves using a color CCD digital camera (DFW-x710, Sony USA, New York, NY) to capture a 1024 Â 768 pixel resolution image of a cigarette butt (mouth end) and then processing that image to extract color information from the center of the spent filter, as well as a 7-pixel-wide ring around the outside of the filter.…”

Section: Methodsmentioning

confidence: 99%

Digital Image Analysis of Cigarette Filter Stains as an Indicator of Compensatory Smoking

Strasser

O’Connor

Mooney

et al. 2006

Cancer Epidemiology, Biomarkers &Amp; Prevention

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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. 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. (Cancer Epidemiol Biomarkers Prev 2006;15(12):2565 -9)

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Digital image analysis of cigarette filter staining to estimate smoke exposure

Cited by 26 publications

References 11 publications

A systematic review and analysis of data reduction techniques for the CReSS smoking topography device

A systematic review and analysis of data reduction techniques for the CReSS smoking topography device

The Impact Of Nonlinear Smoking Effects In The Identification Of Gene-by-Smoking Interactions In COPD Genetics Studies

Digital Image Analysis of Cigarette Filter Stains as an Indicator of Compensatory Smoking

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