Reconciling human smoking behavior and machine smoking patterns: Implications for understanding smoking behavior and the impact on laboratory studies

Catalin Marian, Richard J. O'Connor, Mirjana V. Djordjevic, Vaughan W. Rees, Dorothy K. Hatsukami, Peter G. Shields

Research output: Contribution to journalReview article

63 Scopus citations

Abstract

Background: Recent Food and Drug Administration legislation enables the mandating of product performance standards for cigarette smoke and the evaluation of manufacturers' health claims for modified tobacco products. Laboratory studies used for these evaluations and also for understanding tobacco smoke toxicology use machines to generate smoke. The goal of this review is to critically evaluate methods to assess human smoking behavior and replicate this in the laboratory. Methods: Smoking behavior and smoking machine studies were identified using PubMed and publicly available databases for internal tobacco company documents. Results: The smoking machine was developed to generate smoke to allow for comparing cigarette tar and nicotine yields. The intent was to infer relative human disease risk, but this concept was flawed because humans tailor their smoking to the product, and chemical yields and toxicologic effects change with different smoking profiles. Although smoking machines also allow for mechanistic assessments of smoking-related diseases, the interpretations also are limited. However, available methods to assess how humans puff could be used to provide better laboratory assessments, but these need to be validated. Separately, the contribution of smoke mouth-holding and inhalation to dose need to be assessed, because these parts of smoking are not captured by the smoking machine. Better comparisons of cigarettes might be done by tailoring human puff profiles to the product based on human studies and comparing results across regimens. Conclusions: There are major research gaps that limit the use of smoking machine studies for informing tobacco control regulation and mechanistic studies.

Original languageEnglish (US)
Pages (from-to)3305-3320
Number of pages16
JournalCancer Epidemiology Biomarkers and Prevention
Volume18
Issue number12
DOIs
StatePublished - Dec 1 2009

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