Reinskje Talhout

Hazardous Compounds in Tobacco Smoke

Tobacco smoke is a toxic and carcinogenic mixture of more than 5,000 chemicals. The present article provides a list of 98 hazardous smoke components, based on an extensive literature search for known smoke components and their human health inhalation risks. An electronic database of smoke components containing more than 2,200 entries was generated. Emission levels in mainstream smoke have been found for 542 of the components and a human inhalation risk value for 98 components. As components with potential carcinogenic, cardiovascular and respiratory effects have been included, the three major smoke-related causes of death are all covered by the list. Given that the currently used Hoffmann list of hazardous smoke components is based on data from the 1990s and only includes carcinogens, it is recommended that the current list of 98 hazardous components is used for regulatory purposes instead. To enable risk assessment of components not covered by this list, thresholds of toxicological concern (TTC) have been established from the inhalation risk values found: 0.0018 μg day−1 for all risks, and 1.2 μg day−1 for all risks excluding carcinogenicity, the latter being similar to previously reported inhalation TTCs.

Role of acetaldehyde in tobacco smoke addiction.

This review evaluates the presumed contribution of acetaldehyde to tobacco smoke addiction. In rodents, acetaldehyde induces reinforcing effects, and acts in concert with nicotine. Harman and salsolinol, condensation products of acetaldehyde and biogenic amines, may be responsible for the observed reinforcing effect of acetaldehyde. Harman and salsolinol inhibit monoamine oxidase (MAO), and some MAO-inhibitors are known to increase nicotine self-administration and maintain behavioural sensitization to nicotine. Harman is formed in cigarette smoke, and blood harman levels appear to be 2-10 times higher compared to non-smokers. Since harman readily passes the blood-brain barrier and has sufficient MAO-inhibiting potency, it may contribute to the lower MAO-activity observed in the brain of smokers. In contrast, the minor amounts of salsolinol that can be formed in vivo most likely do not contribute to tobacco addiction. Thus, acetaldehyde may increase the addictive potential of tobacco products via the formation of acetaldehyde-biogenic amine adducts in cigarette smoke and/or in vivo, but further research is necessary to substantiate this hypothesis.

An inventory of methods suitable to assess additive-induced characterising flavours of tobacco products

BACKGROUND Products with strong non-tobacco flavours are popular among young people, and facilitate smoking initiation. Similar to the U.S. Food and Drug Administration Tobacco Control Act, the new European Tobacco Product Directive (TPD) prohibits cigarettes and roll-your-own tobacco with a characterising flavour other than tobacco. However, no methods are prescribed or operational to assess characterising flavours. This is the first study to identify, review and synthesize the existing peer-reviewed and tobacco industry literature in order to provide an inventory of methods suitable to assess characterising flavours. METHODS Authors gathered key empirical and theoretical papers examining methods suitable to assess characterising flavours. Scientific literature databases (PubMed and Scopus) and tobacco industry documents were searched, based on several keyword combinations. Inclusion criteria were relevance for smoked tobacco products, and quality of data. RESULTS The findings reveal that there is a wide variation in natural tobacco flavours. Flavour differences from natural tobacco can be described by both expert and consumer sensory panels. Most methods are based on smoking tests, but odour evaluation has also been reported. Chemical analysis can be used to identify and quantify levels of specific flavour additives in tobacco products. CONCLUSIONS As flavour perception is subjective, and requires human assessment, sensory analysis in consumer or expert panel studies is necessitated. We recommend developing validated tests for descriptive sensory analysis in combination with chemical-analytical measurements. Testing a broad range of brands, including those with quite subtle characterizing flavours, will provide the concentration above which an additive will impart a characterising flavour.

Tobacco Smoke–Related Health Effects Induced by 1,3-Butadiene and Strategies for Risk Reduction

1,3-Butadiene (BD) is a smoke component selected by the World Health Organization (WHO) study group on Tobacco Product Regulation (TobReg) for mandated lowering. We examined the tobacco smoke–related health effects induced by BD and possible health impacts of risk reduction strategies. BD levels in mainstream smoke (MSS) from international and Canadian cigarettes and environmental tobacco smoke (ETS) were derived from scientific journals and international government reports. Dose-response analyses from toxicity studies from government reports were evaluated and the most sensitive cancer and noncancer endpoints were selected. The risks were evaluated by taking the ratio (margin of exposure, MOE) from the most sensitive toxicity endpoint and appropriate exposure estimates for BD in MSS and ETS. BD is a good choice for lowering given that MSS and ETS were at levels for cancer (leukemia) and noncancer (ovarian atrophy) risks, and the risks can be significantly lowered when lowering the BD concentrations in smoke. Several risk reduction strategies were analyzed including a maximum level of 125% of the median BD value per milligram nicotine obtained from international brands as recommended by the WHO TobReg, tobacco substitute sheets, dual and triple carbon filters, and polymer-derived carbon. The use of tobacco substitute sheet with a polymer-derived carbon filter resulted in the most significant change in risk for cancer and noncancer effects. Our results demonstrate that MOE analysis might be a practical way to assess the impact of risk reduction strategies on human health in the future.

The Sensory Difference Threshold of Menthol Odor in Flavored Tobacco Determined by Combining Sensory and Chemical Analysis

Abstract Cigarettes are an often-used consumer product, and flavor is an important determinant of their product appeal. Cigarettes with strong nontobacco flavors are popular among young people, and may facilitate smoking initiation. Discriminating flavors in tobacco is important for regulation purposes, for instance to set upper limits to the levels of important flavor additives. We provide a simple and fast method to determine the human odor difference threshold for flavor additives in a tobacco matrix, using a combination of chemical and sensory analysis. For an example, the human difference threshold for menthol odor, one of the most frequently used tobacco flavors, was determined. A consumer panel consisting of 20 women compared different concentrations of menthol-flavored tobacco to unflavored cigarette tobacco using the 2-alternative forced choice method. Components contributing to menthol odor were quantified using headspace GC-MS. The sensory difference threshold of menthol odor corresponded to a mixture of 43 (37–50)% menthol-flavored tobacco, containing 1.8 (1.6–2.1) mg menthol, 2.7 (2.3–3.1) µg menthone, and 1.0 (0.9–1.2) µg neomenthyl acetate per gram of tobacco. Such a method is important in the context of the European Tobacco Product Directive, and the US Food and Drug Administration Tobacco Control Act, that both prohibit cigarettes and roll-your-own tobacco with a characterizing flavor other than tobacco. Our method can also be adapted for matrices other than tobacco, such as food.

Identification of flavour additives in tobacco products to develop a flavour library

Objectives This study combines chemical analysis and flavour descriptions of flavour additives used in tobacco products, and provides a starting point to build an extensive library of flavour components, useful for product surveillance. Methods Headspace gas chromatography-mass spectrometry (GC-MS) was used to compare 22 commercially available tobacco products (cigarettes and roll-your-own) expected to have a characterising flavour and 6 commercially available products not expected to have a characterising flavour with 5 reference products (natural tobacco leaves and research cigarettes containing no flavour additives). The flavour components naturally present in the reference products were excluded from components present in commercially available products containing flavour additives. A description of the remaining flavour additives was used for categorisation. Results GC-MS measurements of the 33 tobacco products resulted in an overview of 186 chemical compounds. Of these, 144 were solely present in commercially available products. These 144 flavour additives were described using 62 different flavour descriptors extracted from flavour databases, which were categorised into eight groups largely based on the definition of characterising flavours from the European Tobacco Product Directive: fruit, spice, herb, alcohol, menthol, sweet, floral and miscellaneous. Conclusions We developed a method to identify and describe flavour additives in tobacco products. Flavour additives consist of single flavour compounds or mixtures of multiple flavour compounds, and different combinations of flavour compounds can cause a certain flavour. A flavour library helps to detect flavour additives that are characteristic for a certain flavour, and thus can be useful for regulation of flavours in tobacco and related products.

An Inventory of Methods for the Assessment of Additive Increased Addictiveness of Tobacco Products

Background: Cigarettes and other forms of tobacco contain the addictive drug nicotine. Other components, either naturally occurring in tobacco or additives that are intentionally added during the manufacturing process, may add to the addictiveness of tobacco products. As such, these components can make cigarette smokers more easily and heavily dependent. Efforts to regulate tobacco product dependence are emerging globally. Additives that increase tobacco dependence will be prohibited under the new European Tobacco Product Directive. Objective: This article provides guidelines and recommendations for developing a regulatory strategy for assessment of increase in tobacco dependence due to additives. Relevant scientific literature is summarized and criteria and experimental studies that can define increased dependence of tobacco products are described. Conclusions: Natural tobacco smoke is a very complex matrix of components, therefore analysis of the contribution of an additive or a combination of additives to the level of dependence on this product is challenging. We propose to combine different type of studies analyzing overall tobacco product dependence potential and the functioning of additives in relation to nicotine. By using a combination of techniques, changes associated with nicotine dependence such as behavioral, physiological, and neurochemical alterations can be examined to provide sufficient information. Research needs and knowledge gaps will be discussed and recommendations will be made to translate current knowledge into legislation. As such, this article aids in implementation of the Tobacco Product Directive, as well as help enable regulators and researchers worldwide to develop standards to reduce dependence on tobacco products. Implications: This article provides an overall view on how to assess tobacco product constituents for their potential contribution to use and dependence. It provides guidelines that help enable regulators worldwide to develop standards to reduce dependence on tobacco products and guide researches to set research priorities on this topic.

An E-liquid Flavor Wheel: A Shared Vocabulary based on Systematically Reviewing E-liquid Flavor Classifications in Literature.

Abstract Introduction E-liquids are available in a high variety of flavors. A systematic classification of e-liquid flavors is necessary to increase comparability of research results. In the food, alcohol, and fragrance industry, flavors are classified using flavor wheels. We systematically reviewed literature on flavors related to electronic cigarette use, to investigate how e-liquid flavors have been classified in research, and propose an e-liquid flavor wheel to classify e-liquids based on marketing descriptions. Methods The search was conducted in May 2017 using PubMed and Embase databases. Keywords included terms associated with electronic cigarette, flavors, liking, learning, and wanting in articles. Results were independently screened and reviewed. Flavor categories used in the articles reviewed were extracted. Results Searches yielded 386 unique articles of which 28 were included. Forty-three main flavor categories were reported in these articles (eg, tobacco, menthol, mint, fruit, bakery/dessert, alcohol, nuts, spice, candy, coffee/tea, beverages, chocolate, sweet flavors, vanilla, and unflavored). Flavor classifications of e-liquids in literature showed similarities and differences across studies. Our proposed e-liquid flavor wheel contains 13 main categories and 90 subcategories, which summarize flavor categories from literature to find a shared vocabulary. For classification of e-liquids using our flavor wheel, marketing descriptions should be used. Conclusions We have proposed a flavor wheel for classification of e-liquids. Further research is needed to test the flavor wheels’ empirical value. Consistently classifying e-liquid flavors using our flavor wheel in research (eg, experimental, marketing, or qualitative studies) minimizes interpretation differences and increases comparability of results. Implications We reviewed e-liquid flavors and flavor categories used in research. A large variation in the naming of flavor categories was found and e-liquid flavors were not consistently classified. We developed an e-liquid flavor wheel and provided a guideline for systematic classification of e-liquids based on marketing descriptions. Our flavor wheel summarizes e-liquid flavors and categories used in literature in order to create a shared vocabulary. Applying our flavor wheel in research on e-liquids will improve data interpretation, increase comparability across studies, and support policy makers in developing rules for regulation of e-liquid flavors.

Simple and Fast Determination of Ammonia in Tobacco

The presence of ammonia in tobacco is an important factor for the absorption of nicotine, and for product taste. The determination of ammonia in tobacco is usually performed by ion chromatography with conductivity detection devices. Here a new method is presented to measure the concentration of ammonia in tobacco based on an automated enzymatic method. This method is easy to perform and can be used on routine clinical analyzers. The enzymatic ammonia determination showed an intra-assay and inter-assay variation of 4-7 and 5-8%, respectively as determined with 3 brands of cigarettes. A comparison with the established HPLC-IC method gave similar results with respect to both concentrations in cigarettes and the reproducibility of the method. In one working day 50-60 samples of cigarettes or tobacco can be processed and analyzed.

Sensory analysis of characterising flavours: evaluating tobacco product odours using an expert panel

Objectives Tobacco flavours are an important regulatory concept in several jurisdictions, for example in the USA, Canada and Europe. The European Tobacco Products Directive 2014/40/EU prohibits cigarettes and roll-your-own tobacco having a characterising flavour. This directive defines characterising flavour as ‘a clearly noticeable smell or taste other than one of tobacco […]’. To distinguish between products with and without a characterising flavour, we trained an expert panel to identify characterising flavours by smelling. Methods An expert panel (n=18) evaluated the smell of 20 tobacco products using self-defined odour attributes, following Quantitative Descriptive Analysis. The panel was trained during 14 attribute training, consensus training and performance monitoring sessions. Products were assessed during six test sessions. Principal component analysis, hierarchical clustering (four and six clusters) and Hotelling’s T-tests (95% and 99% CIs) were used to determine differences and similarities between tobacco products based on odour attributes. Results The final attribute list contained 13 odour descriptors. Panel performance was sufficient after 14 training sessions. Products marketed as unflavoured that formed a cluster were considered reference products. A four-cluster method distinguished cherry-flavoured, vanilla-flavoured and menthol-flavoured products from reference products. Six clusters subdivided reference products into tobacco leaves, roll-your-own and commercial products. Conclusions An expert panel was successfully trained to assess characterising odours in cigarettes and roll-your-own tobacco. This method could be applied to other product types such as e-cigarettes. Regulatory decisions on the choice of reference products and significance level are needed which directly influences the products being assessed as having a characterising odour.