Effects of electronic cigarettes and hookah (waterpipe) use on home air quality.

INTRODUCTION: A major site of secondhand smoke exposure for children and adults is the home. Few studies have evaluated the impact of e-cigarette or hookah use on home air quality, despite evidence finding toxic chemicals in secondhand e-cigarette aerosols and hookah smoke. We assessed the effect of e-cigarette and hookah use on home air quality and compared it with air quality in homes where cigarettes were smoked and where no smoking or e-cigarette use occurred. METHODS: Non-smoking homes and homes where e-cigarettes, hookah or cigarettes were used were recruited in the New York City area (n=57) from 2015 to 2019. Particulate matter with diameter less than 2.5 µm (PM2.5), black carbon and carbon monoxide (CO) were measured during a smoking or vaping session, both in a 'primary' smoking room and in an adjacent 'secondary' room where no smoking or vaping occurred. Log transformed data were compared with postanalysis of variance Tukey simultaneous tests. RESULTS: Use of hookah significantly increased PM2.5 levels compared with non-smoking homes, in both the primary and secondary rooms, while use of e-cigarettes increased PM2.5 levels only in primary rooms. Additionally, in-home use of hookah resulted in greater CO concentrations than the use of cigarettes in primary rooms. CONCLUSIONS: Use of e-cigarettes or hookah increases air pollution in homes. For hookah, increases in PM2.5 penetrated even into rooms adjacent to where smoking occurs. Extending smoke-free rules inside homes to include e-cigarette and hookah products is needed to protect household members and visitors from passive exposure to harmful aerosols and gases.

The Mediating Effect of E-Cigarette Harm Perception in the Relationship between E-Cigarette Advertising Exposure and E-Cigarette Use.

Exposure to e-cigarette advertising is associated with e-cigarette use among young people. This study examined the mediating effect of e-cigarette harm perception on the above relationship. Cross-sectional survey data were collected from 2112 college students in New York City in 2017-2018. The analytic sample comprised 2078 participants (58.6% females) who provided completed data. Structural equal modeling was performed to examine if e-cigarette harm perception mediated the relationship between e-cigarette advertising exposure (via TV, radio, large signs, print media, and online) and ever e-cigarette use and susceptibility to e-cigarette use. About 17.1% of participants reported ever e-cigarette use. Of never users, 17.5% were susceptible to e-cigarette use. E-cigarette advertising exposure was mainly through online sources (31.5%). Most participants (59.4%) perceived e-cigarettes as equally or more harmful than cigarettes. Advertising exposure showed different effects on e-cigarette harm perception depending on the source of the advertising exposure, but perceiving e-cigarettes as less harmful than cigarettes was consistently associated with e-cigarette use and susceptibility. Low harm perception mediated the association between advertising exposure (via online, TV, and radio) and ever e-cigarette use and between online advertising exposure and e-cigarette use susceptibility. Regulatory actions are needed to address e-cigarette marketing, particularly on the Internet.

Supragingival microbiome alternations as a consequence of smoking different tobacco types and its relation to dental caries.

This study aimed to assess the effect of smoking different tobacco types on the supragingival microbiome and its relation to dental caries. Forty supragingival plaque samples were collected from smokers of a single tobacco type and non-smokers seeking treatment at the University Dental Hospital Sharjah, UAE. DMFT (decayed, missing and filled teeth) was determined for all participants who were divided into two groups: no-low caries (NC-LC: DMFT = 0-4; n = 18) and moderate-high caries (MC-HC: DMFT = 5-20; n = 22). 16S rRNA gene was sequenced using third-generation sequencing with Nanopore technology. Microbiome composition and diversity were compared. Caries was most common among cigarette smokers. Supragingival microbiota were significantly altered among smokers of different tobacco types. In cigarette smokers, cariogenic bacteria from genus Streptococcus (including S. mutans) were significantly more among subjects with NC-LC, while Lactobacilli (including L. fermentum) were more among subjects with MC-HC. In medwakh smokers, several periodontopathogens were significantly elevated in subjects with NC-LC, while other pathogenic bacteria (as Klebsiella pneumoniae) were more in those with MC-HC. Cigarette and alternative tobacco smoking had a significant impact on the supragingival microbiome. Indeed, further studies are required to unravel the consequences of oral dysbiosis triggered by smoking. This could pave the way for microbiota-based interventional measures for restoring a healthy oral microbiome which could be a promising strategy to prevent dental caries.

Benzene emissions from gas station clusters: a new framework for estimating lifetime cancer risk.

PURPOSE: During gas station operation, unburned fuel can be released to the environment through distribution, delivery, and storage. Due to the toxicity of fuel compounds, setback distances have been implemented to protect the general population. However, these distances treat gasoline sales volume as a categorical variable and only account for the presence of a single gas station and not clusters, which frequently occur. This paper introduces a framework for recommending setback distances for gas station clusters based on estimated lifetime cancer risk from benzene exposure. METHODS: Using the air quality dispersion model AERMOD, we simulated levels of benzene released to the atmosphere from single and clusters of generic gas stations and the associated lifetime cancer risk under meteorological conditions representative of Albany, New York. RESULTS: Cancer risk as a function of distance from gas station(s) and as a continuous function of total sales volume can be estimated from an equation we developed. We found that clusters of gas stations have increased cancer risk compared to a single station because of cumulative emissions from the individual gas stations. For instance, the cancer risk at 40 m for four gas stations each dispensing 1 million gal/year is 9.84 × 10-6 compared to 2.45 × 10-6 for one gas station. CONCLUSION: The framework we developed for estimating cancer risk from gas station(s) could be adopted by regulatory agencies to make setback distances a function of sales volume and the number of gas stations in a cluster, rather than on a sales volume category. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40201-020-00601-w.

The impact of smoking different tobacco types on the subgingival microbiome and periodontal health: a pilot study.

Smoking is a risk factor for periodontal disease, and a cause of oral microbiome dysbiosis. While this has been evaluated for traditional cigarette smoking, there is limited research on the effect of other tobacco types on the oral microbiome. This study investigates subgingival microbiome composition in smokers of different tobacco types and their effect on periodontal health. Subgingival plaques were collected from 40 individuals, including smokers of either cigarettes, medwakh, or shisha, and non-smokers seeking dental treatment at the University Dental Hospital in Sharjah, United Arab Emirates. The entire (~ 1500 bp) 16S rRNA bacterial gene was fully amplified and sequenced using Oxford Nanopore technology. Subjects were compared for the relative abundance and diversity of subgingival microbiota, considering smoking and periodontal condition. The relative abundances of several pathogens were significantly higher among smokers, such as Prevotella denticola and Treponema sp. OMZ 838 in medwakh smokers, Streptococcus mutans and Veillonella dispar in cigarette smokers, Streptococcus sanguinis and Tannerella forsythia in shisha smokers. Subgingival microbiome of smokers was altered even in subjects with no or mild periodontitis, probably making them more prone to severe periodontal diseases. Microbiome profiling can be a useful tool for periodontal risk assessment. Further studies are recommended to investigate the impact of tobacco cessation on periodontal disease progression and oral microbiome.

Hookah use patterns, social influence and associated other substance use among a sample of New York City public university students.

BACKGROUND: Most hookah use studies have not included racial and ethnic minorities which limits our understanding of its use among these growing populations. This study aimed to investigate the individual characteristics of hookah use patterns and associated risk behaviors among an ethnically diverse sample of college students. METHODS: A cross-sectional survey of 2460 students (aged 18-25) was conducted in 2015, and data was analyzed in 2017. Descriptive statistics were used to present the sociodemographic characteristics, hookah use-related behavior, and binge drinking and marijuana use according to the current hookah use group, including never, exclusive, dual/poly hookah use. Multivariate logistic regression was conducted to examine how hookah related behavior and other risk behaviors varied by sociodemographics and hookah use patterns. RESULTS: Among current hookah users (n = 312), 70% were exclusive hookah users and 30% were dual/poly hookah users. There were no statistically significant differences in sociodemographic characteristics except for race/ethnicity (p < 0.05). Almost half (44%) of the exclusive hookah users reported having at least five friends who also used hookah, compared to 30% in the dual/poly use group. Exclusive users were less likely to report past year binge drinking (17%) and past year marijuana use (25%) compared to those in the dual/poly use group (44 and 48% respectively); p < 0.001. CONCLUSIONS: The socialization aspects of hookah smoking seem to be associated with its use patterns. Our study calls for multicomponent interventions designed to target poly tobacco use as well as other substance use that appears to be relatively common among hookah users.

Evaluating State-Level Differences in E-cigarette and Cigarette Use Among Adults in the United States Between 2012 and 2014: Findings From the National Adult Tobacco Survey.

Objective: To examine the association between state-level tobacco control measures and current use estimates of both e-cigarettes and cigarettes, while accounting for socio-demographic correlates. Methods: Using the 2012-2013 and 2013-2014 National Adult Tobacco Survey (NATS), we assessed prevalence estimates of US adults' e-cigarette and cigarette current use. Four state groups were created based on the combined state-specific prevalence of both products: low cigarette/e-cigarette (n = 15), high cigarette/e-cigarette (n = 16), high cigarette/low e-cigarette (n = 11), and low cigarette/high e-cigarette) (n = 9). To evaluate the implementation of state-level tobacco control measures, Tobacco Control Index (TCI) was calculated using the State of Tobacco Control annual reports for 2012 and 2013. Multinomial logistic regression models were used to examine differences among the four groups on socio-demographic factors and TCI. Low cigarette/e-cigarette group was used as the referent group. Results: Current use estimates of each product varied substantially by state; current e-cigarette use was highest in Oklahoma (10.3%) and lowest in Delaware (2.7%), and current cigarette use was highest in West Virginia (26.1%), and lowest in Vermont (12.6%). Compared to low cigarette/e-cigarette, all other US-state categories had significantly lower TCI scores (high cigarette/e-cigarette: adjusted Relative Risk Ratio [aRRR] = 0.61; 95% confidence interval [CI]: 0.60-0.61, high cigarette/low e-cigarette: aRRR = 0.74; 95% CI: 0.73-0.74, and low cigarette/high e-cigarette: aRRR = 0.72; 95% CI: 0.71-073). Conclusions: Enforcing existing tobacco control measures likely interacts with e-cigarette use despite being cigarette-focused. Continuing to monitor e-cigarette use is critical to establish baseline use and evaluate future e-cigarette specific federal and state-level tobacco regulatory actions while accounting for the existing tobacco control environment. Implications: This study investigates state-level current use estimates of e-cigarettes and cigarettes among US adults; and their association with four existing tobacco control measures. The overall score of these measures was negatively associated with state-level current use estimates such that states with low current e-cigarette and cigarette use had the highest mean overall score. This study assesses the potential relationship between existing state-level tobacco control measures and e-cigarette use and calls for improving the enforcement of the known-to-work tobacco control measures across all US states, while developing evidence-based regulations and interventions specific to e-cigarettes within the existing US tobacco use environment.

Nonmedical Opioid Use in Relation to Recency of Heroin Use in a Nationally Representative Sample of Adults in the United States.

Nonmedical opioid use has been linked to lifetime heroin use; however, research is needed to examine associations between nonmedical opioid use and current or recent heroin use, as current users appear to be at highest risk for harm. Data were from a nationally representative sample of non-institutionalized adults (age 18-64) in households participating in the National Survey of Drug Use and Health who reported lifetime heroin use (2005-2014, N = 7,111). We examined associations between frequency and recency of nonmedical opioid use and recency of heroin use. Most (86.7%) lifetime heroin users reported no heroin use in the last 12 months, while 6.1% reported current use (use in the last 30 days). The majority of the sample (69.3%) reported lifetime nonmedical opioid use; 14.3% reported nonmedical use in the last 30 days. Adjusted odds for current heroin use increased as frequency of past-year nonmedical opioid use increased, with a quarter (24.7%) of current heroin users reporting nonmedical opioid use on 157-365 days in the last year. Over half (54.7%) of current heroin users reported current nonmedical opioid use. Prevention efforts should consider that high-frequency and current nonmedical opioid use is a robust correlate of continued heroin use.

Dental, Dental Hygiene, and Advanced Dental Students' Use, Knowledge, and Beliefs Regarding Tobacco Products.

Using cigarettes and alternative tobacco products (ATPs) is associated with negative oral health outcomes, and dental health professionals are poised to help patients quit. The aim of this study was to determine dental, dental hygiene, and advanced dental students' use, knowledge, and beliefs about cigarettes and ATPs, including perceptions about their education in tobacco dependence treatment and counseling experience. All 1,783 students enrolled in the dental, dental hygiene, and postdoctoral dental programs at the New York University College of Dentistry were invited to participate in the survey in 2016. A total of 708 students at least partially completed the survey, for a response rate of 39.7%. In the results, 146 of the students (20.1%) reported ever using cigarettes, while 253 (35.7%) reported ever using any ATP. Regarding tobacco use intervention, the students reported they had not received enough training on ATPs, were neutral about cigarettes, and were somewhat confident and not so confident counseling a cigarette smoker or ATP user, respectively. By their fourth year, 77.8% of the dental students reported they had counseled someone to stop smoking cigarettes, but only 40.7% had counseled someone to stop using ATPs. Overall, all groups of students reported feeling more confident and had received more education on interventions for cigarettes than for ATPs (p<0.001). These students reported low confidence in helping people quit tobacco and did not perceive they had received enough training on intervening with patients on use of cigarettes and ATPs. These findings call for a revised tobacco education curriculum for dental, dental hygiene, and advanced dental students, focused on building knowledge and confidence for promoting tobacco dependence treatment.

Characteristics of Adults Who Switched From Cigarette Smoking to E-cigarettes.

INTRODUCTION: Because of the rapidly increasing use of electronic cigarettes (e-cigarettes), this study aimed to investigate the individual characteristics and state-level prevalence of U.S. adults who have switched to e-cigarettes from traditional cigarettes. METHODS: Data from the 2012-2013 and 2013-2014 National Adult Tobacco Surveys were analyzed in 2016. Relative percent change in switching was estimated, and the state-specific prevalence of adults who switched to e-cigarettes from traditional cigarettes was calculated and mapped. Multivariate logistic regression was conducted to examine how switching varied by sociodemographic subgroups and region. RESULTS: Overall, the number of individuals who switched from traditional cigarettes to e-cigarettes increased by approximately 100% over the 1-year interval. Significant increases were found among a number of sociodemographics and regions. Multivariate logistic regression analyses showed that young adults and those living in the South and West were more likely to switch to e-cigarettes, compared to former smokers who did not switch. Compared with current dual users, those with higher education and those who were not single were more likely to switch to e-cigarettes. The state with the highest prevalence of switching was New Mexico (7.3%), whereas Connecticut had the lowest prevalence (0.8 %) among former smokers. CONCLUSIONS: There is an increase in the progression from traditional cigarette use to e-cigarette use. Further research is warranted to determine whether this change continues and facilitates cigarette smoking cessation as a possible public health benefit and opportunity to save lives rather than constitutes a potential threat to public health.

Patterns of electronic cigarette use and level of psychological distress.

BACKGROUND: Psychological distress has been correlated with higher levels of nicotine dependence. To date, the possible association between individuals' levels of psychological distress and e-cigarette use has not been investigated, despite the dramatic growth of e-cigarette use in the US. We examined this possible association using a nationally representative sample of US adults. METHODS: A total of 36,697 adults from the 2014 National Health Interview Survey (NHIS) were included. The Kessler 6 scale was used to measure psychological distress. Multivariate logistic regression analysis was conducted to assess the association between level of psychological distress and e-cigarette use. RESULTS: Both e-cigarette and cigarette use varied according to level of psychological distress as well as multiple socio-demographic characteristics. In a multivariate model, psychological distress was significantly associated with the following groups: (a) exclusive e-cigarette ever-use (aOR = 3.7; 95% CI = 1.6, 8.6), (b) current dual use of e-cigarettes and cigarettes (aOR = 4.6; 95% CI = 3.1, 6.7), (c) former cigarette use and ever use of e-cigarette (aOR = 3.2; 95% CI = 2.2, 4.8) and (d) current use of cigarettes only (aOR = 2.1; 95% CI = 1.7, 2.6). CONCLUSION: These are the first data to demonstrate that, as is true for cigarettes, e-cigarette use is associated with increased levels of psychological distress. Further large-scale, longitudinal studies are needed to determine the direction of this relationship and to evaluate the long-term positive and negative consequences of such use.

Analysis of State-Specific Prevalence, Regional Differences, and Correlates of Hookah Use in U.S. Adults, 2012-2013.

OBJECTIVE: To investigate the state-specific prevalence, regional differences, and correlates of hookah use among U.S. adults. METHODS: We analyzed the most recent nationally representative data of adults from the National Adult Tobacco Survey (NATS) 2012-2013 (n = 60192). State-specific prevalence of lifetime and current hookah use was calculated and mapped. Multivariate logistic regression was performed to determine the association between sociodemographic characteristics, regional differences, and hookah use. RESULTS: Among U.S. adults (≥18 years), overall prevalence of lifetime hookah use was 12.3%, while current use was 3.9%. Mapping of state-specific prevalence revealed that the West tended to have higher rates of use, while the South tended to have lower ones. In the adjusted model, we observed that current hookah use was positively associated with younger adults, males, non-Hispanic adults, those with higher education and income statuses, being single, those living in the West, and current cigarette use. CONCLUSION: The prevalence of hookah use varies by state, region, and sociodemographic characteristics among adults. Future research, including longitudinal studies, are needed to identify geographic and sociodemographic characteristics and trends among hookah users, investigate hookah-related health outcomes, and evaluate targeted public health efforts aimed at this emerging threat. IMPLICATIONS: This study investigates state-level prevalence, regional differences, and sociodemographic characteristics of hookah use among U.S. adults, using the most recent NATS. Hookah use was positively associated with younger adults and those living in the West. This study adds to the understanding of the geographic and sociodemographic factors underlying hookah use, which can be used to develop much needed evidence-based regulations and programs that are responsive to the needs of different risk groups.