Determination of Nicotine Protonation State in E-Liquids by Low-Resolution Benchtop NMR Spectroscopy.

Over several years, e-liquids with "nicotine salts" have gained considerable popularity. These e-liquids have a low pH, at which nicotine occurs mostly in its monoprotonated form. Manufacturers usually accomplish this by the addition of an organic acid, such as levulinic acid, benzoic acid, or lactic acid. Nicotine in its protonated form can be more easily inhaled, enhancing the addictiveness and attractiveness of products. Several techniques have been described for measuring the protonation state of nicotine in e-liquids. However, nuclear magnetic resonance (NMR) spectroscopy is particularly suited for this purpose because it can be performed on unaltered e-liquids. In this article, we demonstrate the suitability of a benchtop NMR (60 MHz) instrument for determining the protonation state of nicotine in e-liquids. The method is subsequently applied to measure the protonation state of 33 commercially available e-liquids and to investigate whether the vaping process alters the protonation state of nicotine. For this purpose, the protonation state in the condensed aerosol obtained by automated vaping of different e-liquids was compared with that of the original e-liquids. Two distinct populations were observed in the protonation state of nicotine in commercial e-liquids: free-base (fraction of free-base nicotine αfb > 0.80) and protonated (αfb < 0.40). For 30 e-liquids out of 33, the information on the packaging regarding the presence of nicotine salt was in agreement with the observed protonation state. Three e-liquids contained nicotine salt, even though this was not stated on the packaging. Measuring the protonation state of nicotine before and after (machine) vaping revealed that the protonation state of e-liquids is not affected by vaping. In conclusion, it is possible to determine the nicotine protonation state with the described method. Two clusters can be distinguished in the protonation state of commercial e-liquids, and the protonation state of nicotine remains unchanged after vaping.

Across the world availability of flavour accessories for tobacco products.

OBJECTIVE: This study aimed to provide an inventory of different types of flavour accessories for combustible tobacco products in eight countries varying in their approaches to flavour legislation and cultural aspects, including tobacco use. METHODS: A standardised search protocol was developed and shared with local informants to acquire information on the availability and marketing of flavour accessories in web shops accessible from Brazil, India, Italy, Singapore, South Africa, Switzerland, the UK and the USA. Characteristics of the products and web shops were reported, and flavours were categorised in a flavour wheel. RESULTS: Flavour accessories were available in all participating countries. Reported types are flavour capsules, cards, filter tips and tubes for make-your-own cigarettes, drops, sprays, rolling paper, aroma markers, a flavour stone and a flavour powder. In total, 118 unique flavours were reported, which were mostly fruity and sweet. Marketing of these products was often associated with (menthol) flavour bans. CONCLUSIONS: The wide availability and variety of flavour accessories raise significant public health concerns, as they have attractive flavours, and thus hinder the regulatory aim of flavour bans. Flavour accessories are not tobacco products and thus not regulated as such. Therefore, it is recommended that policymakers include these products in comprehensive flavour bans, to close this loophole in existing tobacco control measures.

Reducing attractiveness of e-liquids: proposal for a restrictive list of tobacco-related flavourings.

OBJECTIVE: Electronic cigarettes are addictive and harmful, and flavour is a key factor determining their abuse liability. Both adult smokers and young non-smokers like sweet and fruity flavours in particular. In order to discourage e-cigarette use among youth, the Dutch government announced in 2020 to only allow tobacco flavours in e-liquids. We propose a restrictive list of flavourings that will only enable the production of e-liquids with a tobacco flavour. METHODS: We used e-liquid ingredient data notified via the European Common Entry Gate system before the government's announcement. First, we classified all e-liquids into flavour categories, and continued with the set of flavourings present in tobacco e-liquids. Five selection criteria related to prevalence of use, chemical composition, flavour description and health effects were defined to compile a restrictive list of tobacco flavourings. RESULTS: E-liquids marketed as having tobacco flavour contained 503 different flavourings, some with tobacco flavour, but also other (such as sweet) flavours. We excluded (1) 330 flavourings used in <0.5% of e-liquids, (2) 77 used less frequently in tobacco than in all e-liquids, (3) 13 plant extracts, (4) 60 that are sweet or not associated with a tobacco flavour and (5) 7 flavourings with hazardous properties. This resulted in a final list of 16 flavourings. CONCLUSIONS: Implementing this restrictive list will likely discourage e-cigarette use among youth, but could also make e-cigarettes less attractive as smoking cessation aid.

Sensory methods to evaluate perception of flavours in tobacco and other nicotine-containing products: a review.

OBJECTIVES: Sensory methods use human senses to evaluate product attributes. This review provides an overview of the types of sensory methods used to evaluate the perception of flavour in tobacco and other nicotine-containing (ToNic) products and to discuss how sensory data could inform flavoured ToNic product policy. DATA SOURCES: PubMed, Embase and Web of Science. STUDY SELECTION: All peer-reviewed studies evaluating ToNic products using a sensory method published before 23 May 2020. DATA EXTRACTION: Two independent coders completed title/abstract and full-text screening to choose articles for inclusion (Cohen's kappa=0.85, strong agreement). Each coder completed data extraction on half the articles, recording relevant information (eg, sensory methods used, results). The coders categorised sensory methods and generated overarching themes. DATA SYNTHESIS: Of 110 articles identified, we included 29 articles containing 35 studies that used sensory methods to investigate ToNic products. The sensory methods included analytic methods such as discrimination and descriptive tests and hedonic methods such as liking tests. Six themes emerged regarding how sensory methods can be used to understand consumer perception and liking of ToNic products and to inform ToNic product policy. CONCLUSIONS: The identified studies highlight that sensory data can inform ToNic product policy. Analytic and sensory hedonic ratings can be used to assess a ToNic product's ability to promote addiction in the user (ie, abuse liability). Lastly, hedonic ratings can provide information to assess potential use behaviours.

Flavours and flavourings in waterpipe products: a comparison between tobacco, herbal molasses and steam stones.

ObjectivesFlavoured products are especially appealing to youth and contribute to the onset of waterpipe smoking and continued use of waterpipe tobacco. The goal of database and chemical analysis was to provide a clear overview of commonly used flavours and flavourings in tobacco and related waterpipe products, that is, herbal molasses and steam stones. METHODS: In 2019, 249 waterpipe tobacco products were registered in the European Common Entry Gate by manufacturers to be marketed in The Netherlands. Flavour categories were assigned to the registered products based on their brand names and product descriptions. Nicotine and eleven 1111 flavourings were identified and quantified in waterpipe tobacco (n=8), herbal molasses (n=7) and steam stones (n=4) by extraction and gas chromatography-mass spectrometry (GC-MS) analysis. RESULTS: Flavour categories could be assigned to 237 of 249 registered waterpipe tobacco products. Eight flavour main categories and 48 unique subcategories were identified and presented in a flavour wheel. All registered waterpipe tobacco products were flavoured, and the majority (78%) was fruit flavoured. Herbal molasses contained similar median flavouring levels, and steam stones contained lower median levels compared with waterpipe tobacco. Flavourings in waterpipe products were almost exclusively fruity and sweet, often in combination with menthol/mint flavourings. CONCLUSIONS: This study is the first to present a waterpipe tobacco flavour wheel, providing a quick overview of waterpipe tobacco flavours and thereby aiding communication among experts around the globe. GC-MS analysis revealed that the most prevalent flavourings are present in similar levels in herbal and tobacco waterpipe products. Banning flavourings in all waterpipe products would be a good strategy to reduce waterpipe smoking among youth.

Exploring the gateway hypothesis of e-cigarettes and tobacco: a prospective replication study among adolescents in the Netherlands and Flanders.

BACKGROUND: Studies demonstrated that adolescent e-cigarette use is associated with subsequent tobacco smoking, commonly referred to as the gateway effect. However, most studies only investigated gateways from e-cigarettes to tobacco smoking. This study replicates a cornerstone study revealing a positive association between both adolescent e-cigarette use and subsequent tobacco use; and tobacco and subsequent e-cigarette use in the Netherlands and Flanders. DESIGN: The longitudinal design included baseline (n=2839) and 6-month (n=1276) and 12-month (n=1025) follow-up surveys among a school-based cohort (mean age: 13.62). Ten high schools were recruited as a convenience sample. The analyses involved (1) associations of baseline e-cigarette use and subsequent tobacco smoking among never smokers; (2) associations of e-cigarette use frequency at baseline and tobacco smoking frequency at follow-up; and (3) the association of baseline tobacco smoking and subsequent e-cigarette use among non-users of e-cigarettes. FINDINGS: Consistent with prior findings, baseline e-cigarette use was associated with higher odds of tobacco smoking at 6-month (OR=1.89; 95% CI 1.05 to 3.37) and 12-month (OR=5.63; 95% CI 3.04 to 10.42) follow-ups. More frequent use of e-cigarettes at baseline was associated with more frequent smoking at follow-ups. Baseline tobacco smoking was associated with subsequent e-cigarette use (OR=3.10; 95% CI 1.58 to 6.06 at both follow-ups). CONCLUSION: Our study replicated the positive relation between e-cigarette use and tobacco smoking in both directions for adolescents. This may mean that the gateway works in two directions, that e-cigarette and tobacco use share common risk factors, or that both mechanisms apply.

Variations in cigarette brand characteristics: can consumers tell the difference?

OBJECTIVES: Sensory experience is an important determinant of smoking initiation, brand choice and harm perception, but little is known about how cigarette design shapes sensory experience. This study reports which variations in tobacco blend and design characteristics available on the market are likely to be perceived as different by consumers. METHODS: Truth Tobacco Industry Documents was reviewed for studies showing noticeable sensory differences resulting from variations in tobacco blend and design characteristics. These differences were compared with tobacco product data as available in the Dutch section of the European Common Entry Gate (EU-CEG) system on 30 April 2020. RESULTS: Industry documents identified discrimination thresholds for ventilation, pressure drop, tobacco weight, filter length, and tar and nicotine levels in smoke while evidence for other design characteristics was less conclusive. In the 103 different cigarette varieties in the EU-CEG database, five main types of cigarettes could be identified by principal component analysis, differing in (combinations of) design characteristics. The most significant differences between brand varieties were tar, nicotine and carbon monoxide emissions and associated parameters filter ventilation, filter length, cigarette length and tobacco weight. CONCLUSIONS: While some clusters of brand varieties provided a noticeably different product for consumers, in many cases design differences within these clusters did not exceed the expected discrimination threshold. This indicates that many products on the market are not discernibly different for consumers, and that proliferation of brand varieties has a non-sensory purpose, such as marketing. Policy makers should consider limiting available brand varieties and regulating design characteristics to reduce product appeal.

Comprehensive Dutch market data analysis shows that e-liquids with nicotine salts have both higher nicotine and flavour concentrations than those with free-base nicotine.

OBJECTIVES: Recent years have seen an increase in e-liquids containing nicotine salts. Nicotine salts are less harsh and bitter than free-base nicotine and therefore can facilitate inhalation. Because inhalation-facilitating ingredients are banned in the European Union, we assessed the occurrence and characteristics of nicotine salt-containing e-liquids notified for the Netherlands. METHODS: We analysed data for 39 030 products, submitted by manufacturers in the European Union Common Entry Gate system, as extracted on 30 June 2020. RESULTS: Nicotine salts were present in 13% of e-liquids, especially in pod-related e-liquids (73%) and e-liquids registered from 2018 onwards (over 25%). We found six nicotine salt ingredients (NSIs): nicotine lactate, salicylate, benzoate, levulinate, ditartrate and malate. Nicotine salts also occurred as nicotine-organic acid ingredient combination (NAIC), like nicotine and benzoic acid. Nicotine concentrations were twofold higher in e-liquids with NSI (median 14 mg/mL) and NAIC (11 mg/mL) than for free-base nicotine (6 mg/mL). E-liquids with NSI contained a fourfold higher number (median n=17) and concentration (median 31.0 mg/mL) of flavour ingredients than e-liquids with free-base nicotine (n=4, 7.4 mg/mL). In NAIC-containing e-liquids, these were threefold higher (n=12, 21.5 mg/mL). E-liquids with nicotine salts were less often tobacco flavoured but more often had fruity or sweet flavours. CONCLUSIONS: A substantial and increasing share of e-liquids in the Netherlands contains nicotine salts. Their characteristics can make such e-liquids more addictive and more attractive, especially to young and beginning users. Policymakers are advised to consider regulating products containing nicotine salts.

Neuromodulatory and neurotoxic effects of e-cigarette vapor using a realistic exposure method.

The most direct effects of inhaled harmful constituents are the effects on the airways. However, inhaled compounds can be rapidly absorbed and subsequently result in systemic effects. For example, e-cigarette vapor has been shown to evoke local effects in the lung, although little is known about subsequent effects in secondary target organs such as the brain. Traditionally, such effects are tested using in vivo models. As an alternative, we have combined two in vitro systems, which are Air-Liquid-Interface (ALI) cultured alveolar cells (A549) and rat primary cortical cultures grown on multi-well microelectrode arrays. This allows us to assess the neurological effects of inhaled compounds. We have used exposure to e-cigarette vapor, containing nicotine, menthol, or vanillin to test the model. Our results show that ALI cultured A549 cells respond to the exposure with the production of cytokines (IL8 and GROalpha). Furthermore, nicotine, menthol, and vanillin were found on the basolateral side of the cell culture, which indicates their translocation. Upon transfer of the basolateral medium to the primary cortical culture, exposure-related changes in spontaneous electrical activity were observed correlating with the presence of e-liquid components in the medium. These clear neuromodulatory effects demonstrate the feasibility of combining continuous exposure of ALI cultured cells with subsequent exposure of neuronal cells to assess neurotoxicity. Although further optimization steps are needed, such a combination of methods is important to assess the neurotoxic effects of inhaled compounds realistically. As such, an approach like this could play a role in future mechanism-based risk assessment strategies.

Evolution of tobacco products: recent history and future directions.

Declines in cigarette smoking prevalence in many countries and the consolidation of the tobacco industry have prompted the introduction of other forms of nicotine delivery. These include electronic nicotine delivery systems (ENDS), heated tobacco products (HTPs) and oral nicotine products (ONPs). Evolving over time, some of these products now deliver nicotine at levels comparable to cigarettes and may serve as effective substitutes for smokers. However, certain products, especially ENDS like JUUL, have also appealed to youth and non-smokers, prompting concerns about expanding nicotine use (and potentially nicotine addiction). The tobacco industry could shift away from primarily promoting cigarettes to promoting ENDS, HTPs and/or ONPs, though at this time it continues to heavily promote cigarettes in low and middle-income countries. Differing regulatory regimes may place upward and downward pressures on both cigarettes and these newer products in terms of population use, and may ultimately drive the extent to which cigarettes are or are not displaced by ENDS, HTPs and/or ONPs in the coming decade.

Both Nonsmoking Youth and Smoking Adults Like Sweet and Minty E-liquid Flavors More Than Tobacco Flavor.

Smokers may reduce their health risk by switching to electronic cigarette (e-cigarette) use. As e-cigarettes are not harmless, concerns exist about e-cigarette use by nonsmokers and youth. E-liquids are available in many different flavors that increase sensory appeal. Flavor preferences may differ between user groups, which could open doors for product regulation. We investigated which e-liquid flavors are attractive to specific user groups by comparing liking between adolescent nonsmokers (n = 41; mean age 16.9 ± 0.8), young adult nonsmokers (n = 42; mean age 22.7 ± 1.7), and adult smokers (n = 56; mean age 39.7 ± 11.1). Participants smelled tobacco- (n = 6) and nontobacco (n = 24)-flavored e-liquids and rated liking on a 9-point labeled hedonic scale, and familiarity, overall intensity, perceived sweetness, perceived bitterness, and irritation of the odors on a 100-unit Visual Analog Scale. Mean liking ranged from 2.3 (whiskey) to 6.7 (peppermint). Within all groups, the typically sweet and minty flavors (e.g., wine gum, watermelon, peppermint, menthol) were liked significantly more than the tobacco-flavored e-liquids. The set of tobacco-flavored e-liquids was significantly, but slightly, less disliked by adult smokers (3.9 ± 0.2) than adolescent (3.1 ± 0.3) and young adult (3.4 ± 0.3) nonsmokers (P < 0.001). No between-group differences were observed for sweet and minty flavors. Liking correlated significantly positively with odor sweetness (R = 0.49) and familiarity (R = 0.48) and negatively with odor bitterness (R = -0.58), irritation (R = -0.47), and overall intensity (R = -0.27). Thus, sweet- and minty-flavored e-liquids are liked equally by young nonsmokers and adult smokers, and more than tobacco flavors. Banning all flavors except tobacco will likely reduce e-cigarette appeal; potentially more for young nonsmokers than adult smokers.

Nearly 20 000 e-liquids and 250 unique flavour descriptions: an overview of the Dutch market based on information from manufacturers.

OBJECTIVES: Flavours increase attractiveness of electronic cigarettes and stimulate use among vulnerable groups such as non-smoking adolescents. It is important for regulators to monitor the market to gain insight in, and regulate the range of e-liquid flavours that is available to consumers. E-liquid manufacturers are required to report key product information to authorities in the European Member States in which they plan to market their products. This information was used to provide an overview of e-liquid flavour descriptions marketed in the Netherlands in 2017. METHODS: Two researchers classified 19 266 e-liquids into the 16 main categories of the e-liquid flavour wheel, based on information from four variables in the European Common Entry Gate system. Flavour descriptions were further specified in subcategories. RESULTS: For 16 300 e-liquids (85%), sufficient information was available for classification. The categories containing the highest number of e-liquids were fruit (34%), tobacco (16%) and dessert (10%). For all e-liquids, excluding unflavoured ones, 245 subcategories were defined within the main categories. In addition to previously reported subcategories, various miscellaneous flavours such as sandwich, buttermilk and lavender were identified. CONCLUSIONS: In 2017, ~20 000 e-liquids were reported to be marketed in the Netherlands, in 245 unique flavour descriptions. The variety of marketed flavour descriptions reflects flavour preference of e-cigarette users as described in literature. Our systematic classification of e-liquids by flavour description provides a tool for organising the huge variety in market supply, serves as an example for other countries to generate similar overviews and can support regulators in developing flavour regulations.

Comprehensive overview of common e-liquid ingredients and how they can be used to predict an e-liquid's flavour category.

OBJECTIVES: Flavours increase e-cigarette attractiveness and use and thereby exposure to potentially toxic ingredients. An overview of e-liquid ingredients is needed to select target ingredients for chemical analytical and toxicological research and for regulatory approaches aimed at reducing e-cigarette attractiveness. Using information from e-cigarette manufacturers, we aim to identify the flavouring ingredients most frequently added to e-liquids on the Dutch market. Additionally, we used flavouring compositions to automatically classify e-liquids into flavour categories, thereby generating an overview that can facilitate market surveillance. METHODS: We used a dataset containing 16 839 e-liquids that were manually classified into 16 flavour categories in our previous study. For the overall set and each flavour category, we identified flavourings present in more than 10% of the products and their median quantities. Next, quantitative and qualitative ingredient information was used to predict e-liquid flavour categories using a random forest algorithm. RESULTS: We identified 219 unique ingredients that were added to more than 100 e-liquids, of which 213 were flavourings. The mean number of flavourings per e-liquid was 10±15. The most frequently used flavourings were vanillin (present in 35% of all liquids), ethyl maltol (32%) and ethyl butyrate (28%). In addition, we identified 29 category-specific flavourings. Moreover, e-liquids' flavour categories were predicted with an overall accuracy of 70%. CONCLUSIONS: Information from manufacturers can be used to identify frequently used and category-specific flavourings. Qualitative and quantitative ingredient information can be used to successfully predict an e-liquid's flavour category, serving as an example for regulators that have similar datasets available.

Risk assessment of components in tobacco smoke and e-cigarette aerosols: a pragmatic choice of dose metrics.

BACKGROUND: Risk assessment of individual tobacco smoke components is important for the purpose of prioritization or selecting chemicals for monitoring products. Smoking is characterized by a highly varying, intermittent exposure and the challenge is to choose the most appropriate dose metric. METHODS: Generally, average daily exposure estimates are used as dose metric, without considering temporal determinants. The applicability hereof is discussed in the context of choosing dose metrics for local respiratory tract effects and for systemic effects in a smoking scenario or for the use of e-cigarettes. RESULTS: Using average daily exposure estimates for the smoking scenario can lead to erroneous risk evaluations for several reasons. Inhaled peak air concentrations during a puff can be two to three orders of magnitude higher than the calculated average daily inhaled concentration, which may impact the assessment of both systemic and local health effects. A pragmatic risk assessment is proposed, based on the Margin of Exposure (MoE) approach. The choice of an appropriate dose metric, such as inhaled concentration, inhaled dose or absorbed dose, depends on the type of effect. Temporal characteristics should be considered in the final step of the MoE approach, as is illustrated by two cases, glycerol and benzene. CONCLUSION: The choice of an appropriate dose metric and inclusion of temporal determinants are important aspects in the risk assessment of individual smoke components. The proposed MoE approach provides the opportunity to weigh smoking-related exposure characteristics during the final step of the risk evaluation.

Conceptual model for the evaluation of attractiveness, addictiveness and toxicity of tobacco and related products: The example of JUUL e-cigarettes.

Many new tobacco and related products (nTRP) have emerged on the market, with unknown health risks. Here, we present a conceptual model containing the factors and relations between them that contribute to the nTRP's health effects. Factors that determine attractiveness, addictiveness and toxicity of nTRP were defined based on previous assessments, literature, and expert discussions. Our model will aid in identifying key risk factors contributing to increased risk of adverse health effects for a product in a qualitative manner. Additionally, it can gauge attractiveness for specific user groups, as a determinant for population prevalence of use. Our model can be used to identify aspects of nTRP that require attention for public information or product regulation. As an example, we applied this to JUUL, a popular e-cigarette in the US. Aspects of concern for JUUL are its attractive and discrete shape, user-friendly prefilled pods, flavors, high aerosol nicotine levels, and liquids containing nicotine salts instead of free-based nicotine. The addictiveness and especially attractiveness are sufficiently high to have a large potential impact on population health due to its contribution to use and hence exposure. Products and their use can change over time; therefore market research and monitoring are crucial.

Aldehyde and Volatile Organic Compound Yields in Commercial Cigarette Mainstream Smoke Are Mutually Related and Depend on the Sugar and Humectant Content in Tobacco.

INTRODUCTION: The World Health Organization (WHO) Framework Convention on Tobacco control recognizes the need for tobacco product regulation. In line with that, the WHO Study Group on Tobacco Product Regulation (TobReg) proposed to regulate nine toxicants in mainstream cigarette smoke, including aldehydes, volatile organic compounds (VOCs), and carbon monoxide (CO). We analyzed their relations in 50 commercially available cigarette brands, using two different smoking regimes, and their dependence on sugar and humectant concentrations in tobacco filler. METHODS: We measured sugar and humectant in tobacco filler and aldehydes, VOCs, and tar, nicotine, and CO (TNCO) in mainstream smoke. The general statistics, correlations between emission yields, and correlations between contents and emissions yields were determined for these data. RESULTS: For aldehydes, several significant correlations were found with precursor ingredients in unburnt tobacco when smoked with the Intense regime, most prominently for formaldehyde with sucrose, glucose, total sugars, and glycerol. For VOCs, 2,5-dimethylfuran significantly correlates with several sugars under both International Standards Organization (ISO) and Intense smoking conditions. A correlation network visualization shows connectivity between a sugar cluster, an ISO cluster, and an Intense cluster, with Intense formaldehyde as a central highest connected hub. CONCLUSIONS: Our multivariate analysis showed several strong connections between the compounds determined. The toxicants proposed by WHO, in particular, formaldehyde, can be used to monitor yields of other toxicants under Intense conditions. Emissions of formaldehyde, acetaldehyde, acrolein, and 2,5-dimethylfuran may decrease when sugar and humectants contents are lowered in tobacco filler. IMPLICATIONS: Our findings suggest that the aldehydes and VOCs proposed by TobReg are a representative selection for smoke component market monitoring purposes. In particular, formaldehyde yields may be useful to monitor emissions of other toxicants under Intense conditions. Since the most and strongest correlations were observed with the Intense regime, policymakers are advised to prescribe this regime for regulatory purposes. Policymakers should also consider sugars and humectants contents as targets for future tobacco product regulations, with the additional advantage that consumer acceptance of cigarette smoke is proportional to their concentrations in the tobacco blend.

Advice to the European Commission as Regards Type and Criteria for Comprehensive Studies to Be Requested From Manufacturers: The Opinion of the Scientific Committee on Health, Environmental, and Emerging Risks (SCHEER).

The European Commission has established a priority list of 15 additives contained in cigarettes and roll-your-own tobacco subject to enhanced reporting obligations. The European Union (EU) Tobacco Products Directive (TPD) prescribes that Member States shall require manufacturers and importers of tobacco products to carry out comprehensive studies on these additives to assess their contribution to any of the properties listed in Article 6 of the TPD: toxicity or addictiveness, characterizing flavor, inhalation facilitation, nicotine uptake, and carcinogenic, mutagenic, or toxic for reproduction. The Scientific Committee on Health, Environmental, and Emerging Risks (SCHEER) has provided guidance on the type and criteria for comprehensive studies, and on the most suitable methodologies to test these 15 tobacco additives as well as additives on future updated lists. The SCHEER proposes a stepwise strategy as the most pragmatic and efficient way to assess the effects of tobacco additives. In addition to proposing specific steps and tests to be considered by industry, some general criteria were also identified such as no comparative testing (testing cigarettes with and without the additive) and no animal studies. As tobacco additives have no benefits for health, but rather may promote use of and addiction to an extremely toxic product, a risk-benefit analysis is not the appropriate paradigm for assessing the additive. When comprehensive studies confirm that additives have any of the properties listed in Article 6 of the TPD, regulatory actions should be considered. If uncertainties cannot be solved by comprehensive studies, the SCHEER recommends that the assessors consider the worst-case evaluation. IMPLICATIONS: In this article, the SCHEER proposes a stepwise strategy to assess (1) the toxic and addictive effects, (2) the characterizing flavor, and (3) facilitating inhalation properties of tobacco additives. The proposed steps and tests provide guidance to (1) Member State on which comprehensive studies should be requested and (2) tobacco industry on which strategy of testing should be applied to address the request and to prepare reports to be sent to the relevant authorities for the evaluation of tobacco additives "safety" to comply with the Tobacco Products Directive 2014/40/EU.

Sensory Evaluation of E-Liquid Flavors by Smelling and Vaping Yields Similar Results.

INTRODUCTION: Sensory research on e-liquid flavors can be performed by means of smelling and vaping. However, data comparing smelling versus vaping e-liquid flavors are lacking. This study aims to investigate if smelling could be an alternative to vaping experiments by determining the correlation for hedonic flavor assessment between orthonasal smelling and vaping of e-liquids, for smokers and nonsmokers. METHODS: Twenty-four young adult smokers (mean age 24.8 ± 9.3) and 24 nonsmokers (mean age 24.9 ± 7.7) smelled and vaped 25 e-liquids in various flavors. Participants rated liking, intensity, familiarity, and irritation on a 100-mm Visual Analog Scale. Pearson correlations within and between smelling and vaping were calculated. Differences between user groups were calculated using t tests. RESULTS: Correlation coefficients between smelling and vaping based on mean group ratings were 0.84 for liking, 0.82 for intensity, 0.84 for familiarity, and 0.73 for irritation. Means of the within-subjects correlation coefficients were, respectively, 0.51, 0.37, 0.47, and 0.25. Correlations between smelling and vaping varied across individuals (ranging from -0.27 to 0.87) and flavors (-0.33 to 0.81). Correlations and mean liking ratings did not differ between smokers and nonsmokers. CONCLUSIONS: The strong group-level correlations between orthonasal smelling and vaping e-liquid flavors justify the use of smelling instead of vaping in future research. For example, smelling could be used to investigate differences in e-liquid flavor liking between (potential) user groups such as nicotine-naïve adolescents. The more modest within-subject correlations and variation across individuals and flavors merit caution in using smelling instead of vaping in other types of experiments. IMPLICATIONS: This study supports the use of orthonasal smelling (instead of vaping) e-liquids to measure hedonic flavor perception in some studies where vaping would be inappropriate or not feasible. Examples of research situations where smelling e-liquids may be sufficient are (1) investigating nicotine-naïve individuals (ie, nonusers), (2) investigating individuals under legal age for e-cigarette use (ie, youth and adolescents), (3) investigating brain responses to exposure of e-liquid flavors using functional magnetic resonance imaging or electroencephalogram, and (4) comparing hedonic flavor assessment between adolescent nonusers and current smokers to provide support for future regulations on e-liquid flavors.

A Method for Comparing the Impact on Carcinogenicity of Tobacco Products: A Case Study on Heated Tobacco Versus Cigarettes.

Comparing the harmful health effects related to two different tobacco products by applying common risk assessment methods to each individual compound is problematic. We developed a method that circumvents some of these problems by focusing on the change in cumulative exposure (CCE) of the compounds emitted by the two products considered. The method consists of six steps. The first three steps encompass dose-response analysis of cancer data, resulting in relative potency factors with confidence intervals. The fourth step evaluates emission data, resulting in confidence intervals for the expected emission of each compound. The fifth step calculates the change in CCE, probabilistically, resulting in an uncertainty range for the CCE. The sixth step estimates the associated health impact by combining the CCE with relevant dose-response information. As an illustrative case study, we applied the method to eight carcinogens occurring both in the emissions of heated tobacco products (HTPs), a novel class of tobacco products, and tobacco smoke. The CCE was estimated to be 10- to 25-fold lower when using HTPs instead of cigarettes. Such a change indicates a substantially smaller reduction in expected life span, based on available dose-response information in smokers. However, this is a preliminary conclusion, as only eight carcinogens were considered so far. Furthermore, an unfavorable health impact related to HTPs remains as compared to complete abstinence. Our method results in useful information that may help policy makers in better understanding the potential health impact of new tobacco and related products. A similar approach can be used to compare the carcinogenicity of other mixtures.

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

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.