No description available.

Electronic cigarettes (ECIGs) aerosolize an often nicotine-containing solution for user inhalation. ECIG nicotine delivery may depend on liquid nicotine concentration and user puffing behavior (topography). This study examined the relationship among liquid nicotine concentration, puff topography, and plasma nicotine concentration. Thirty-three ECIG-experienced and 31 ECIG-naïve individuals completed four laboratory sessions that differed by ECIG liquid nicotine concentration (0, 8, 18, or 36 mg/ml). A 3.3 volt “eGo” ECIG battery attached to a 1.5 Ohm dual coil “cartomizer” filled with 1 ml of 70% propylene glycol/30% vegetable glycerin nicotine liquid was used in two ECIG-bouts (10 puffs; 30 s IPI). Plasma nicotine concentration, puff topography, and HR were evaluated. Some ECIG/liquid combinations can deliver physiologically active doses of nicotine to users, and nicotine delivery depends on liquid nicotine concentration and user puffing behavior. Liquid contents, device characteristics, and user behavior should be considered when regulating ECIGs.

Electronic cigarettes (ECIGs) are a class of tobacco products that use a heating element to aerosolize a liquid, typically containing nicotine, allowing for user inhalation. Despite their rapid growth in popularity, little is known about ECIGs including how certain device and liquid factors influence nicotine delivery, user physiological and subjective responses, and puffing behavior (puff topography). Limited pre-clinical research has demonstrated that the ratio of two solvents commonly found in ECIG liquids, propylene glycol (PG) and vegetable glycerin (VG), may have an influence on the nicotine content of ECIG aerosols. However, the extent to which PG:VG ratio in ECIG liquids influences acute effects experienced by ECIG users is unknown. The primary purpose of this clinical laboratory study was to examine the influence of PG:VG ratio on plasma nicotine concentration, heart rate (HR), subjective effects, and puff topography in experienced ECIG users. Thirty ECIG-experienced individuals participated in four independent laboratory conditions that differed only by the PG:VG ratio in the ECIG liquid (100:0, 55:45, 20:80, and 2:98). In each condition, participants used a 3.3 volt “eGo” ECIG battery attached to a 1.5 Ohm dual coil “cartomizer” loaded with 1 ml of ECIG liquid (nicotine concentration: 18 mg/ml). Participants completed two ECIG use bouts (10 puffs with 30 sec inter-puff-interval) in each study condition. ECIG PG:VG ratio had a direct influence on nicotine delivery, subjective effects, and puff topography. Nicotine delivery and overall nicotine intake were highest following the use of the liquids containing mostly PG, despite participants taking significantly shorter and smaller puffs in these conditions, suggesting PG may be a more efficient nicotine-delivery vehicle than VG. Abstinence symptoms were suppressed similarly across all PG:VG ratios, and HR also increased in a similar fashion in all conditions following ECIG use. Participants reported significantly lower scores on items assessing sensory ECIG effects following use of the 100PG:0VG liquid, indicating a lower overall satisfaction with this liquid. Further evaluating the influence of PG and VG and other ECIG device and liquid characteristics on ECIG acute effects using clinical laboratory methodologies could inform regulations of these products.

This dissertation presents three papers applying health economics to the study of risky behaviors. The first uses data from the 1979 National Longitudinal Survey of Youth to examine the relationship between adverse events and risky behaviors among adolescents. Substance use responses to experiencing either of two adverse events--violent crime victimization or death of a non-family member one felt close to--explain 6.7 percent of first cigarette use, and 14.3 percent of first use of illegal drugs other than marijuana. Analyses of exercise, a positive coping mechanism, find shock-responses consistent with a coping-response, but not with rational, time-inconsistent, or non-rational drivers considered here. I conclude that distressing events lead to risky behaviors, with a coping response contributing to this effect.

Background and Aims: Prior cross-sectional research finds that electronic cigarette (e-cigarette) use clusters with higher rates of harmful alcohol consumption in the United States adult population. The current study examined prospectively the association between e-cigarette use, cigarette use and the combined use of e-cigarettes and tobacco cigarettes and alcohol use outcomes. Design: A nationally representative multi-wave cohort survey (wave 1: September 2013–December 2014, wave 2: October 2014–October 2015). Setting: United States. Participants: A representative sample of civilian, non-institutionalized adults who completed waves 1 and 2 of the Population Assessment of Tobacco and Health survey (n = 26 427). Measurements: Participants were categorized into exposure groups according to their e-cigarette and cigarette use during wave 1. Past 30-day alcohol use outcomes were (1) National Institute on Alcohol Abuse and Alcoholism (NIAAA)-defined hazardous alcohol use, (2) total alcohol drinks consumed and (3) alcohol-related consequences. Findings: After controlling for socio-demographic risk factors and alcohol use at wave 1, all exposure groups showed higher odds of hazardous alcohol use [adjusted odds ratios (aORs) = 2.05–2.12, all P < 0.001] and reported higher past-month total drinks (B = 0.46–0.70, all P < 0.001) and more alcohol consequences (B = 0.63–0.89, all P ≤ 0.10) at wave 2 compared with non-users. Cigarette users (B = 0.24, P = 0.038) and dual e-cigarette/cigarette users (B = 0.32, P = 0.038) reported higher past-month total drinks compared with e-cigarette users. There was no conclusive evidence that non-daily use of e-cigarettes or cigarettes predicted poorer alcohol use outcomes compared with daily use. Conclusions: In the United States between 2013 and 2015, after adjustment for socio-demographic characteristics, cigarette and e-cigarette use were associated with alcohol use 1 year later.

No description available.

Current methods for the risk assessment of environmental exposures commonly involve questionnaires, stationary monitoring, and personal air sampling. However, as these approaches do not capture the body's internal response, they lend minimal understanding to the biologic consequence of exposure. In order to address the unmet need of connecting external exposure measurements with signatures of internal exposure, this thesis examines the overarching hypothesis that transcriptomic changes in the human airway epithelium can serve as indicators of physiologic responses to inhaled pollutants. This is an extension of previous work that has demonstrated an airway ''field of injury'' effect where cigarette smoke exposure alters gene-expression in epithelial cells lining the respiratory tract. Specifically, I examine transcriptomic changes and the biologic responses associated with exposure to the following pollutants: environmental tobacco smoke (Aim 1), household air pollution from smoky coal combustion (Aim 2), and electronic cigarette vapor (Aim 3). First, I performed whole-genome transcriptional profiling of the nasal epithelium in children and adults and detected gene-expression changes associated with exposure to environmental tobacco smoke. Next, I employed similar approaches to detect a signature of coal smoke exposure in the buccal epithelium of healthy, non-smoking females exposed to household air pollution Xuanwei, China. The findings from these studies suggest that upper airway gene-expression can reflect the host response to prolific sources of environmental exposures that are major risk factors for chronic lung disease. Lastly, I examine the cellular and physiologic consequences of electronic cigarette (ECIG) aerosol exposure by analyzing transcriptomic profiles of human bronchial epithelial cells that have either been (1) differentiated and exposed in vitro or (2) acquired via bronchoscopy from the airway epithelium of ECIG users. The studies detailed in this dissertation offer valuable insight that will accelerate the efforts to evaluate the health effects of both well-established and emerging types of inhaled exposures in large-scale population studies. Furthermore, the transcriptomic strategies woven throughout the following chapters push for a novel assessment paradigm that may enable the public health community to rapidly characterize the physiologic host response to inhalation exposures of different sources, and to evaluate the biologic consequences of exposure-reduction initiatives. / 2017-05-01T00:00:00Z

The human body encounters a number of chemical exposures on a daily basis, which may have short- or long-term health implications. Previously it has been demonstrated that the entire respiratory tract of an individual reacts to exposures like tobacco smoke in a similar manner, and that common molecular changes can be measured in airway epithelium. I propose that cataloguing the exposure of airway epithelial cells to tobacco cigarette (TCIG) smoke and its constituents, electronic cigarette (ECIG) aerosol and other drugs and small molecules can significantly increase the understanding of chemical exposure and identify common gene expression alterations. First, I determined the molecular impact of ECIG aerosol exposure on human airway epithelium in vitro, including alterations in genes related to xenobiotic metabolism, oxidative stress, and ciliated cells. These changes were generally less pronounced than the effects of TCIG exposure, and were more pronounced in ECIG products containing nicotine than those without nicotine. Furthermore, gene expression differences observed in vitro were concordant with differences observed in airway epithelium collected from ECIG users. Second, I examined the impact of TCIG exposure and TCIG constituents on premalignant airway cells, to better understand the progression or regression of precancerous lesions. These data could also identify the constituents of TCIGs and the precancerous mutations that increase the risk for malignancy. Third, in an effort to build a high-throughput methodology for chemical exposures, I exposed primary lung cell lines to small molecule therapeutics and identified lung-specific and lung cell-type-specific effects of exposure, suggesting that profiling additional cell lines would further inform airway gene expression in response to exposure and that organ-specific exposure profiling may provide valuable insight into drug discovery for common diseases. Overall, transcriptomic profiles from the airway epithelium reflect exposure to various inhaled and chemical perturbations. These gene expression profiles indicate common changes across a multitude of airway exposures as well as unique alterations specific to a given perturbation. Gene expression profiling can therefore be used to detail the potential response to a compendium of chemical exposures including those that are either well-established or potential risk factors for chronic lung diseases. / 2019-07-09T00:00:00Z

Introduction: Cigarette smoking is associated with lung cancer, cardiovascular disease, and chronic respiratory conditions. It is responsible for high mortality and morbidity risk in the US population. Smokers find sudden quitting difficult and it is reported that a large number of unassisted quitting attempts are eventually unsuccessful. Electronic cigarette or e-cig is a novel battery-driven, nicotine delivery product, currently being used as a smoking cessation tool by current and former smokers. Since its resemblance to a conventional cigarette, and its non-combustible nature, e-cig use has risen exponentially in the last few years. To address such public health issues, the US FDA is working on formulating regulations to manufacture, market, and distribute e-cigs has called for research evidence on the long term use of e-cig use. Objective: The objective of this study was to develop and validate a Discrete Event Simulation model to simulate the electronic cigarette (e-cig) use behavior, and to estimate the long term e-cig use prevalence, in different groups of the US population. Methods: The model population was generated from analyzing the National Health Interview Survey data from 2011-2013. The population was categorized into current, recent former, late former and never smokers. Population birth rates and death rates were applied using the 2012 US Census Bureau data. Model parametrization, transition probabilities and e-cig related risks were obtained and applied using cross sectional survey and longitudinal e-cig studies done on US population. The model was run for the period of 15 years and e-cig use prevalence at the end of the simulation period was estimated. Each simulation was replicated 100 times using Monte Carlo simulation approach. Model validation was performed by the use of null and extreme input values (internal validation), examining programing codes (debugging), verification by tobacco science and system analysis experts (structural and technical validation), comparison of model’s first year results with CDC reports (external validation). Conclusion: Total projected e-cig prevalence in the US population at the end of simulation of period was found to be around 19%. The results showed a gradual reduction in the number of conventional cigarette smokers and an increase in the e-cig users over the simulation period. Highest e-cig users were old, male, white and had less than high school level education. Sensitivity analyses of various model parameters showed that the e-cig prevalence was most sensitive to the impact and timing of policy implementation. As a novel nicotine delivery system, e-cigs are rapidly gaining acceptance in the US and recent reports have shown an exponential rise in the popularity of e-cig among minors and young adults. Our research provides empirical evidence that can be used by the scientific community and regulatory bodies to formulate regulations for marketing and sales of e-cigs in various sections of the population, where the prevalence is expected to rise in future. Our study can also guide the policy makers to introduce relevant policies at specific time points when the e-cig use is expected to rise.

Submitted in full fulfilment of the requirements for the degree of MASTER OF COMMERCE (Marketing) at the UNIVERSITY OF THE WITWATERSRAND 2015 / With an increase in the concern over the harmful effects of smoking traditional tobacco cigarettes, there has been an increase in the use of a smoking alternative considered to be a healthier option, namely the e-cigarette. Thus, it is of interest to understand certain factors surrounding the novelty, and this research has been conducted in terms of evaluating the predictors of the diffusion of innovations on consumer resistance towards the e-cigarette among South African university students, with the primary purpose being to research a gap in the South African e-cigarette market, and to utilise the results to better understand the overall market. The gap in prior research has been identified as what appears to be a lack of information regarding the South African e-cigarette market, and in particular, the predictors of consumer resistance, including relative advantage, compatibility, complexity, trialability, observability, and perceived risk. The study undertook a quantitative methodology in which 400 students from the University of the Witwatersrand were asked to complete a self-administered questionnaire. Data analysis was conducted using SPSS 22 and AMOS for structural equation modelling. The results indicate that three of the six hypotheses are supported. Thus, indicating that marketers should focus on applying relative advantage, complexity, and perceived risk to marketing strategies. This study contributes to existing literature and contextual knowledge regarding consumer resistance and the diffusion of innovation. The results further provide marketing practitioners with a better understanding on how to limit consumer resistance and how to improve product diffusion of the e-cigarette, subsequently improving the rate of adoption. However, future research is necessary for corroboration. / MT2017