Electronic cigarette use intensity measurement challenges and regulatory implications.

Assessing tobacco use intensity allows researchers to examine tobacco use in greater detail than assessing ever or current use only. Tobacco use intensity measures have been developed that are specific to tobacco products, such as asking smokers to report number of cigarettes smoked per day. However, consensus on electronic cigarette use intensity measures that can be used for survey research has yet to be established due to electronic cigarette product and user behavior heterogeneity. While some survey measures that attempt to assess electronic cigarette use intensity exist, such as examining number of 'times' using an electronic cigarette per day, number of puffs taken from an electronic cigarette per day, volume of electronic cigarette liquid consumed per day, or nicotine concentration of electronic cigarette liquid, most measures have limitations. Challenges in electronic cigarette measurement often stem from variations across electronic cigarette device and liquid characteristics as well as the difficulty that many electronic cigarette users have regarding answering questions about their electronic cigarette device, liquid, or behavior. The inability for researchers to measure electronic cigarette use intensity accurately has important implications such as failing to detect unintended consequences of regulatory policies. Development of electronic cigarette use intensity measures, though not without its challenges, can improve understanding of electronic cigarette use behaviors and associated health outcomes and inform development of regulatory policies.

Cigarette Brand Use and Sexual Orientation: Intersections With Gender and Race or Ethnicity.

INTRODUCTION: Lesbian, gay, and bisexual (LGB) populations have higher cigarette smoking rates than heterosexual populations. The tobacco industry has leveraged LGB, gender, and racial or ethnic identities to establish cigarette brand preference. We examined cigarette brand use among smokers by sexual orientation and the implications of gender and race or ethnicity for brand use. METHODS: We used the National Survey on Drug Use and Health (NSDUH; 2015-2017) to conduct weighted bivariate analyses in 2019-2020 of the prevalence of 5 commonly used cigarette brands among adult smokers (N = 24,310) by sexual orientation. We conducted weighted regressions to test relationships between sexual orientation and brand use and interactions between sexual orientation, gender (defined in NSDUH as male or female), and race or ethnicity. RESULTS: LGB smokers were more likely to use Camel (lesbian/gay, OR = 1.7 [95% CI, 1.2-2.3], bisexual, OR = 1.8 [95% CI, 1.5-2.2]) and American Spirit cigarettes (lesbian/gay, OR = 2.8 [95% CI, 1.9-4.1], bisexual, OR = 3.2 [95% CI, 2.5-4.1]) than heterosexual smokers. Lesbian/gay smokers had higher odds of Marlboro cigarette use (OR = 1.2; 95% CI, 1.0-1.4) than heterosexual smokers. Bisexual smokers were more likely to smoke Newport cigarettes (OR = 1.7; 95% CI, 1.4-2.1) than heterosexual smokers. Interactions between LGB and female identities (vs gay or bisexual male) were positively associated with Camel, Marlboro, and Newport use. The interaction between lesbian/gay and Hispanic/Latino ethnicity (vs lesbian/gay White) was also positively associated with Newport use. CONCLUSION: LGB smokers may be more likely to smoke some commonly used cigarette brands than heterosexual smokers, and gender and race or ethnicity may have implications for brand preference. Future research could examine specific contributors to brand use among LGB smokers (eg, tobacco marketing).

Host-agent-vector-environment measures for electronic cigarette research used in NIH grants.

OBJECTIVE: The purpose of this study is to describe the focus and comprehensiveness of domains measured in e-cigarette research. METHODS: A portfolio analysis of National Institutes of Health grants focusing on e-cigarette research and funded between the fiscal years 2007 and 2015 was conducted. Grant proposals were retrieved using a government database and coded using the Host-Agent-Vector-Environment (HAVE) model as a framework to characterise the measures proposed. Eighty-one projects met the criteria for inclusion in the analysis. RESULTS: The primary HAVE focus most commonly found was Host (73%), followed by Agent (21%), Vector (6%) and Environment (0%). Intrapersonal measures and use trajectories were the most common measures in studies that include Host measures (n=59 and n=51, respectively). Product composition was the most common area of measurement in Agent studies (n=24), whereas Marketing (n=21) was the most common (n=21) area of Vector measurement. When Environment measures were examined as secondary measures in studies, they primarily focused on measuring Peer, Occupation and Social Networks (n=18). Although all studies mentioned research on e-cigarettes, most (n=52; 64%) did not specify the type of e-cigarette device or liquid solution under study. CONCLUSIONS: This analysis revealed a heavy focus on Host measures (73%) and a lack of focus on Environment measures. The predominant focus on Host measures may have the unintended effect of limiting the evidence base for tobacco control and regulatory science. Further, a lack of specificity about the e-cigarette product under study will make comparing results across studies and using the outcomes to inform tobacco policy difficult.

Measuring waterpipe tobacco smoking in survey research.

Waterpipe tobacco (WT) smoking remains a significant public health problem. However, few validated measures exist, presenting challenges for obtaining accurate prevalence estimates and making comparisons across studies. We identified items used to measure several WT smoking behaviours in eight US national surveys of youth and adults and two international studies, including the National Youth Tobacco Survey, National Adult Tobacco Survey, Population Assessment of Tobacco and Health Adult and Youth Surveys, Monitoring the Future, National Health Interview Survey, Health Styles, Tobacco Use Supplement: Current Population Survey, Global Adult Tobacco Survey and Global Youth Tobacco Survey. We also identified WT survey items across the first 14 Food and Drug Administration-funded Tobacco Centers of Regulatory Science. Constructs included product description and terminology, ever and current use, quantity and frequency, use of flavours and reasons for use. There was little consistency in WT measurement, highlighting the need for validated measures.

Psychometric Evaluation of the E-cigarette Dependence Scale.

INTRODUCTION: Psychometrically sound measures of e-cigarette dependence are lacking. METHODS: We modified the PROMIS Item Bank v1.0-Smoking: Nicotine Dependence for All Smokers for use with e-cigarettes and evaluated the psychometrics of the 22-, 8-, and 4-item adapted versions, referred to as The E-cigarette dependence scale (EDS). Adults (1009) who reported using e-cigarettes at least weekly completed an anonymous survey in summer 2016 (50.2% male, 77.1% White, mean age 35.81 [10.71], 66.4% daily e-cigarette users, 72.6% current cigarette smokers). Psychometric analyses included confirmatory factor analysis, internal consistency, measurement invariance, examination of mean-level differences, convergent validity, and test-criterion relationships with e-cigarette use outcomes. RESULTS: All EDS versions had confirmable, internally consistent latent structures that were scalar invariant by sex, race, e-cigarette use (nondaily/daily), e-liquid nicotine content (no/yes), and current cigarette smoking status (no/yes). Daily e-cigarette users, nicotine e-liquid users, and cigarette smokers reported being more dependent on e-cigarettes than their counterparts. All EDS versions correlated strongly with one another, evidenced convergent validity with the Penn State E-cigarette Dependence Index and time to first e-cigarette use in the morning, and evidenced test-criterion relationships with vaping frequency, e-liquid nicotine concentration, and e-cigarette quit attempts. Similar results were observed when analyses were conducted within subsamples of exclusive e-cigarette users and duals-users of cigarettes and e-cigarettes. CONCLUSIONS: Each EDS version evidenced strong psychometric properties for assessing e-cigarette dependence in adults who either use e-cigarette exclusively or who are dual-users of cigarettes and e-cigarettes. However, results indicated little benefit of the longer versions over the 4-item EDS, which provides an efficient assessment of e-cigarette dependence. IMPLICATIONS: The availability of the novel, psychometrically sound EDS can further research on a wide range of questions related to e-cigarette use and dependence. In addition, the overlap between the EDS and the original PROMIS that was developed for assessing nicotine dependence to cigarettes provides consistency within the field.

Advancing Tobacco Product Warning Labels Research Methods and Theory: A Summary of a Grantee Meeting Held by the US National Cancer Institute.

BACKGROUND: The World Health Organization's Framework Convention on Tobacco Control recommends prominent pictorial health warnings on tobacco products. To advance research methods, theory and understanding of how tobacco product warning labels (TPWLs) work, the US National Cancer Institute convened a grantee meeting. Our article describes the key insights that emerged from the meeting, situated within the context of the scientific literature. RESULTS & RECOMMENDATIONS: First, presentations confirmed that large, pictorial TPWLs motivate people to try to quit and encourage smoking cessation. Second, pictorial TPWLs increase attention, knowledge, negative affect, and thinking about the warning. Third, TPWL studies have primarily used brief-exposure laboratory studies and observational studies of sustained exposure through national policy implementation, with a few randomized trials involving several weeks of exposure-with generally consistent results found across study designs. Fourth, novel assessment methods include brain imaging, eye tracking and "best-worst" discrete choice experiments. To make TPWL even more effective, research is needed to confirm the mechanisms of their influence, their impact across vulnerable populations, and their effect on social media posts about tobacco products. Research is also needed on the effect of trial design choices, the predictive validity of new measurement approaches, and warning labels for non-cigarette tobacco products. IMPLICATIONS: To improve scientific understanding of TPWL effects, this grantee meeting summary describes emerging research methods, theory and study results. Directions for future research include examination of the mechanisms of how warning labels work across diverse tobacco products and across different populations and contexts.

The association between perceived e-cigarette and nicotine addictiveness, information-seeking, and e-cigarette trial among U.S. adults.

Perceptions of harm and addictiveness are associated with smoking combusted cigarettes, but these factors have not been fully explored for e-cigarettes. Specifically, little is known about the perceived harm and addictiveness of e-cigarettes, or whether information-seeking about e-cigarettes is related to trying e-cigarettes. We aimed to determine the relationship between (1) perceived e-cigarette harm and addictiveness and trying e-cigarettes; (2) nicotine perceptions and trying e-cigarettes; and (3) e-cigarette information-seeking, Internet use, and trying e-cigarettes. We used data from the nationally representative 2015 Health Information National Trends Survey-FDA (HINTS-FDA 2015). Weighted multivariable logistic regression models assessed independent associations between perceived e-cigarette harm, perceived e-cigarette addictiveness, nicotine perceptions, e-cigarette information-seeking, personal Internet use, and trying e-cigarettes, among 3195 adults. Compared to people who believed e-cigarettes were equally or more addictive than combusted cigarettes, those who believed e-cigarettes were less addictive had 2.49 times the odds of trying e-cigarettes (95% confidence interval [CI]: 1.30, 4.74). Perceived e-cigarette harm and nicotine perceptions were not associated with trying e-cigarettes. The positive association between e-cigarette addictiveness and trying e-cigarettes coupled with the lack of an association between nicotine perceptions and trying e-cigarettes suggests people do not fully understand that e-cigarettes contain nicotine and therefore could be addictive. People most frequently reported searching for information about potential health effects of e-cigarettes (37.9%), indicating that people are interested in learning about the potential impact of e-cigarette use on their health. People who searched for information about e-cigarettes had 10.23 higher odds of trying e-cigarettes (CI: 5.41, 19.33).

Development and psychometric validation of a novel measure of sensory expectancies associated with E-cigarette use.

INTRODUCTION: E-cigarette dependence measures largely focus on e-cigarette use ("vaping") that is linked to nicotine use, and measures assessing sensory aspects of vaping that may influence use (e.g., taste) are limited in scope. Thus, we developed the novel Sensory E-cigarette Expectancies Scale (SEES). METHODS: In Summer 2017, 610 adult e-cigarette users (48.7% male, 84.9% White, 37.41[±12.15] years old) completed an online survey that included 23 SEES items. Psychometric analyses included evaluating latent structure, internal consistency, measurement invariance, mean differences, and test-criterion relationships. RESULTS: Factor analyses supported a 9-item, 3-subscale structure (taste/smell, pleasure/satisfaction, vapor cloud production). Subscales evidenced internal consistency and scalar invariance by sex, race, smoking status (current/not), vaping status (daily/not), e-liquid nicotine content (yes/no), and device type (cig-a-likes/vape-pens/Advanced Personal Vaporizers [APVs]/Mods). Women and daily e-cigarette users reported stronger SEEs for taste/smell and pleasure than their counterparts. Non-white participants reported stronger SEEs for cloud production than White participants. Cig-a-like users reported the weakest SEEs for taste/smell and weaker SEEs linked to cloud production than APV/mod users. SEES scores evidenced convergence with nicotine dependence (mean r = .36). Finally, SEES scores predicted vaping frequency and habitual vaping concurrently and incrementally beyond nicotine dependence. CONCLUSIONS: The SEES evidenced good psychometric properties, suggesting that the measure can be used to assess sensory vaping expectancies in adults. Importantly, SEES scores indicated that sensory expectancies are related, yet distinct, from nicotine dependence. Future research should evaluate how SEEs relate to product characteristic preferences and patterns of vaping including the development and maintenance of addiction.

Measuring E-cigarette dependence: Initial guidance.

E-cigarette use rates are increasing among youth and adults, despite limited knowledge about the safety, risks, and potential for this product in substituting for or reducing other tobacco use. Understanding how to characterize and assess e-cigarette dependence will be important for evaluating the public health impact of e-cigarettes and considering prevention and intervention strategies. To provide an initial review of constructs to consider when assessing e-cigarette dependence, a content expert group within the Tobacco Center for Regulatory Science (TCORS) Measurement Workgroup engaged in a review of published manuscripts and 12 tobacco dependence measures, followed by review of suggested dependence domains by a 10-person external subject-matter expert panel. The final domains selected to be considered in the development of a measure of e-cigarette dependence included: 1) Quantity and frequency of use, 2) Tolerance, 3) Perceived benefits, 4) Withdrawal symptoms, 5) Craving/urge to use, 6) Use despite harm, 7) Impaired control, 8) Automaticity, 9) Preferred over competing rewards, and 10) Sensory dependence. Similarities and differences in potential features of e-cigarette dependence compared with dependence on other tobacco products is discussed. Future work will evaluate these dependence items and constructs in a sample of e-cigarette users with a goal of developing a valid, brief, standardized measure of e-cigarette dependence.

Electronic Nicotine Delivery Systems and Acceptability of Adult Cigarette Smoking Among Florida Youth: Renormalization of Smoking?

PURPOSE: There is a dearth of research into whether electronic nicotine delivery systems (ENDS) promote acceptance of cigarette smoking. Therefore, we aimed to assess the association between ENDS exposure, acceptance of cigarette smoking, and susceptibility to cigarette smoking. METHODS: Data from the 2014 Florida Youth Tobacco Survey with a state representative sample of middle and high school students (n = 68,928) were analyzed. Own ENDS use, exposure to ENDS advertising, living with ENDS users, acceptance of adult cigarette smoking, demographics, and known predictors of cigarette smoking were assessed. Susceptibility to cigarette smoking was assessed among never smokers. Weighted multiple logistic regression models and mediation analyses were conducted, stratified by middle/high school and never/ever smoking. Analyses were conducted in 2016. RESULTS: Own ENDS use, exposure to ENDS advertising, and living with ENDS users were associated with acceptance of adult cigarette smoking even among never smokers, after accounting for covariates (p < .05). In a mediation analysis, own ENDS use, exposure to ENDS advertising, and living with ENDS users were indirectly associated with susceptibility to cigarette smoking among never smokers through acceptance of adult cigarette smoking (p < .05). CONCLUSIONS: Youth ENDS exposure may contribute to normalizing adult cigarette smoking and may in turn heighten susceptibility to cigarette smoking. If confirmed by longitudinal studies, these findings suggest that ENDS policy interventions may help prevent youth cigarette smoking.

Philip Morris research on precursors to the modern e-cigarette since 1990.

BACKGROUND: Use of electronic cigarettes (e-cigarettes) is increasing rapidly. Chinese pharmacist Hon Lik is frequently cited as inventing the modern e-cigarette in 2003. However, tobacco companies have developed electronic nicotine delivery systems since at least 1963. METHODS: We searched the University of California San Francisco Truth (formerly Legacy) Tobacco Industry Documents beginning with the terms 'electric cigarette' and 'electronic cigarettes', 'e-cigarette', 'smokeless cigarettes', 'nicotine aerosol', 'tobacco aerosol', and 'vaping' and then expanded the search using snowball sampling. We focused our analysis on Philip Morris (PM) documents discussing technology that aerosolised a nicotine solution because these devices resembled modern e-cigarettes. Over 1000 documents were reviewed; 40 were included in the final analysis. RESULTS: PM started developing a nicotine aerosol device in 1990 to address the health concerns and decreased social acceptability of smoking that were leading smokers to switch to nicotine replacement therapy. PM had developed a capillary aerosol generator that embodied basic e-cigarette technology in 1994, but in the mid-to-late 1990s focused on applying its aerosol technology to pharmaceutical applications because of uncertainty of how such products might affect potential Food and Drug Administration regulation of tobacco products. In 2001, PM resumed its work on a nicotine aerosol device, and in 2013, NuMark (a division of Altria, PM's parent company) released the MarkTen, a nicotine aerosol device. CONCLUSIONS: Rather than a disruptive technology, PM developed e-cigarette technology to complement, not compete with, conventional cigarettes and evade tobacco control regulations.

Developmental toxicity of nicotine: A transdisciplinary synthesis and implications for emerging tobacco products.

While the health risks associated with adult cigarette smoking have been well described, effects of nicotine exposure during periods of developmental vulnerability are often overlooked. Using MEDLINE and PubMed literature searches, books, reports and expert opinion, a transdisciplinary group of scientists reviewed human and animal research on the health effects of exposure to nicotine during pregnancy and adolescence. A synthesis of this research supports that nicotine contributes critically to adverse effects of gestational tobacco exposure, including reduced pulmonary function, auditory processing defects, impaired infant cardiorespiratory function, and may contribute to cognitive and behavioral deficits in later life. Nicotine exposure during adolescence is associated with deficits in working memory, attention, and auditory processing, as well as increased impulsivity and anxiety. Finally, recent animal studies suggest that nicotine has a priming effect that increases addiction liability for other drugs. The evidence that nicotine adversely affects fetal and adolescent development is sufficient to warrant public health measures to protect pregnant women, children, and adolescents from nicotine exposure.

Adolescent Smoking Cessation With Bupropion: The Role of Adherence.

INTRODUCTION: While many medications can be effective aids to quitting tobacco, real world adherence to smoking cessation medications may render a potentially effective medication ineffective. The present study investigated the role of adherence on treatment outcomes in a bupropion dose-response study among adolescent smokers trying to quit smoking. METHODS: Three hundred twelve adolescent boys (n = 143) and girls (n = 169) between the ages of 14-17 were enrolled in the study, and were randomly assigned to use either 300 mg, 150 mg or placebo bupropion to quit smoking. Among the eligibility criterion, participants had to smoke at least six cigarettes per day, be motivated to quit smoking (self report), have an exhaled carbon monoxide level greater than or equal to 10 ppm, and report at least two previous quit attempts. Adherence to medication was determined by both self-report and actual counts of unused medication and empty medication packaging. Smoking status was determined by a combination of self-report and biochemical verification (breath carbon monoxide and urine cotinine). RESULTS: Cotinine-confirmed quit rates were significantly higher as a function of high adherence (20.69%) relative to low adherence (0.00%) in the 300-mg Bupropion Sustained Release group. Overall adherence in all study conditions in this highly controlled study was high (74%), but was significantly lower in non-white participants. CONCLUSIONS: Effectiveness of bupropion for adolescent smoking cessation is contingent on achieving high rates of medication adherence, but considerable variations in adherence impacted outcomes. IMPLICATIONS: Few studies have assessed the safety and efficacy of medications to help adolescent smokers quit, and we conducted one such study assessing bupropion. In this analysis of that original study, we assess the role of adherence in use of medication and quit rates. We found that adherence was related to outcomes, particularly in the 300-mg dose of bupropion.

A content analysis of electronic cigarette manufacturer websites in China.

OBJECTIVE: The goal of this study was to summarise the websites of electronic cigarette (e-cigarette) manufacturers in China and describe how they market their products. METHODS: From March to April 2013, we used two search keywords 'electronic cigarette' (Dian Zi Xiang Yan in Chinese) and 'manufacturer' (Sheng Chan Chang Jia in Chinese) to search e-cigarette manufacturers in China on Alibaba, an internet-based e-commerce business that covers business-to-business online marketplaces, retail and payment platforms, shopping search engine and data-centric cloud computing services. A total of 18 websites of 12 e-cigarette manufacturers in China were analysed by using a coding guide which includes 14 marketing claims. RESULTS: Health-related benefits were claimed most frequently (89%), followed by the claims of no secondhand smoke (SHS) exposure (78%), and utility for smoking cessation (67%). A wide variety of flavours, celebrity endorsements and e-cigarettes specifically for women were presented. None of the websites had any age restriction on access, references to government regulation or lawsuits. Instruction on how to use e-cigarettes was on 17% of the websites. CONCLUSIONS: Better regulation of e-cigarette marketing messages on manufacturers' websites is needed in China. The frequent claims of health benefits, smoking cessation, strategies appealing to youth and women are concerning, especially targeting women. Regulators should prohibit marketing claims of health benefits, no SHS exposure and value for smoking cessation in China until health-related, quality and safety issues have been adequately addressed. To avoid e-cigarette use for initiation to nicotine addiction, messages targeting youth and women should be prohibited.

The importance of product definitions in US e-cigarette laws and regulations.

BACKGROUND: How electronic cigarettes and similar products (e-cigarettes) are defined affects how they are regulated, particularly whether existing laws for cigarettes apply, including sales and marketing, youth access, smoke-free and taxation laws. METHODS: We examined the text of 46 bills that define e-cigarettes enacted in 40 states and characterised how e-cigarettes and similar products were defined. RESULTS: States enact laws creating new product categories for e-cigarettes separate from the 'tobacco product' category (eg, 'alternative nicotine product,' 'vapour product,' 'electronic nicotine device'), with four states explicitly excluding e-cigarettes from 'tobacco products.' Twenty-eight states do not include e-cigarettes in their definitions of 'tobacco products' or 'smoking,' eight include e-cigarettes as 'tobacco products,' three include e-cigarettes in 'smoking.' Sixteen states' definitions of e-cigarettes require nicotine, and five states pre-empt more stringent local laws. Tobacco and e-cigarette industry representatives tried to shape laws that benefit their interests. CONCLUSIONS: Definitions separating e-cigarettes from other tobacco products are common. Similar to past 'Trojan horse' policies, e-cigarette policies that initially appear to restrict sales (eg, limit youth access) may actually undermine regulation if they establish local pre-emption or create definitions that divide e-cigarettes from other tobacco products. Comparable issues are raised by the European Union Tobacco Products Directive and e-cigarette regulations in other countries. Policymakers should carefully draft legislation with definitions of e-cigarettes that broadly define the products, do not require nicotine or tobacco, do not pre-empt stronger regulations and explicitly include e-cigarettes in smoke-free and taxation laws.

Dual use of smokeless tobacco or e-cigarettes with cigarettes and cessation.

OBJECTIVES: To evaluate predictors of dual use of cigarettes with smokeless tobacco or e-cigarettes. METHODS: Adult smokers (N = 1324) completed online cross-sectional surveys. Logistic regression evaluated predictors of dual use and cigarette quit attempts. RESULTS: Smokeless tobacco dual use was associated with past attempts to quit smoking by switching to smokeless products. E-cigarette dual use was associated with using stop-smoking medication and strong anti-tobacco industry attitudes. Ever use of stop-smoking medication was associated with quit attempts among dual e-cigarette users and cigarette-only users. CONCLUSIONS: Dual users are more likely than cigarette-only users to endorse certain cessation-related attitudes and behaviors. This may provide an opportunity for clinicians or others to discuss evidence-based strategies for smoking cessation.