E-cigarette use has become widespread, and its effects on airway inflammation and disease are not fully delineated. E-cigarette vapor extract (EVE) profoundly affects neutrophil function. We hypothesized that EVE also alters eosinophil function and thus could impact allergic airways disease. We employed RNA-sequencing to measure the ex vivo effect of EVE components on human eosinophil transcription. Blood eosinophils from 9 non-vaping subjects without asthma were isolated by negative selection. Cells were incubated for 48 hours with EVE consisting of glycerin, propylene glycol and nicotine (EVE+), EVE without nicotine (\"EVE-\"), air-exposed media termed Extract Buffer (EB), or untreated media. Bulk RNA-sequencing was performed. Transcriptomic analysis revealed that the EB, EVE-, and EVE+ conditions showed highly variable gene expression with respect to No Treatment and each other. Differential gene expression analysis comparing a combination of EVE+, EVE-, and EB revealed 3,030 differentially expressed genes (DEG) with adjusted p value < 0.05 and log2 fold change >0.5 or <0.5. There were 645 DEG between EB and EVE-, 1,713 between EB and EVE+, and 404 between EVE- and EVE+. Gene set enrichment analysis demonstrated that DEG between both EVE+ and EVE- and the EB control were positively enriched for heme metabolism and apoptosis and negatively enriched TNFα signaling, IFNγ signaling, and inflammatory response. Thus, EVE significantly alters eosinophil metabolic and inflammatory pathways, mediated by propylene glycol and glycerin with both enhancing and unique effects of nicotine. This study motivates further research into the pathogenic effects of vaping on airway eosinophils and allergic airways disease.

Because of the increasing popularity of e-cigarettes, monitoring the e-cigarette market has become important for national health authorities to guarantee safety and quality. In the EU, the Tobacco Products Directive requires emission studies for e-cigarette products. The absence of industry guidelines for studying these emissions and the lack of proper validation in the literature led us to develop and validate a method using the total error approach for the determination of nicotine in e-cigarette aerosols. A commercial vaping device was used to generate aerosols, which were then collected on Cambridge filter pads and measured for nicotine concentration by UHPLC-DAD after extraction. The method was successfully validated by generating accuracy profiles, which show that the β-expectation tolerance intervals remained below the acceptance limits of ±20%. Within-run repeatability and intermediate precision were considered acceptable since the highest RSD value obtained was below 5%. The method was applied to 15 commercial e-liquids. A complete validation of a method for the analysis of e-cigarette emissions is presented, including several parameters that impact the accuracy and reproducibility. Similar systematic approaches for method development and validation could be used for other e-cigarette emission analysis methods to ensure the reliability of the measurements.

OBJECTIVE: The impacts of passive (i.e., browsing) versus active (i.e., engagement) use of social media on e-cigarette use among youth have been understudied in existing literature. This study examines how passive and active use of social media are differentially associated with e-cigarette use among youth and how risk perceptions mediate these associations.
METHODS: Pooled data from the 2021 and 2022 National Youth Tobacco Survey (N=48,704, aged 11-19) were used. Weighted structural equation models were employed to estimate the associations between passive and active social media use and youth e-cigarette use.
RESULTS: Both passive and active social media use were associated with higher odds and more days of e-cigarette use among youth. E-cigarette risk perceptions mediated the associations between active use and both the likelihood of ever using e-cigarettes and the number of days of use. Risk perceptions mediated the association between active, but not passive, use and the number of days of e-cigarette use. Compared to passive use, active use was overall associated with higher odds and more days of youth e-cigarette use.
CONCLUSIONS: The findings suggest that public health efforts should distinguish between passive and active social media use when designing and executing interventions. Attention and efforts should also be directed towards understanding the distinct indirect effects of passive and active social media use through risk perceptions. These findings advance our theoretical understanding of the role of different types of social media use and offer significant practical insights for interventions.

Electronic cigarettes (vapes) are actively used, and their use is growing globally, especially among young people. Its spread is rapid due to the presence of unproven rumors that it is used to treat smoking addiction as it aids in smoking cessation. However, E.C has a negative impact on dental health by affecting the oral microbiome and salivary components. The goal of this study was to evaluate the impact of electronic cigarettes on dental caries in relation to glucosyltransferase B and secretory immunoglobulin in the saliva of electronic cigarette users. Ninety active males were divided into two groups: 45 electronic-cigarette smokers in addition to 45 non-electronic-cigarette smokers as a control group. An oral examination was performed on the studied groups, and decayed missing filling tooth surfaces (DMFS) were documented. Additionally, unstimulated saliva was collected to evaluate salivary glucosyltransferase B and secretory immunoglobulin A by using a sandwich enzyme-linked immune-sorbent assay (ELISA). The obtained outcomes showed that decayed, missing, and filled Surfaces values(DMFS), salivary glucosyltransferase B, and salivary secretory immunoglobulin A were greater in the study group than in control group. Additionally, a correlation between glucosyltransferase B, secretory immunoglobulin A, and DMFS was positive and significant. It was concluded that e-cigarettes may have an effect on saliva components and dental caries.

UNASSIGNED: Youth e-cigarette (EC) use has rapidly increased in the last few years. It is crucial to identify the susceptible youth and prevent them from EC uptake. This study was conducted to investigate factors that affect youth susceptibility to EC use.
UNASSIGNED: This study employed a cross-sectional survey design, utilizing multi-center stratified cluster sampling method to select two junior high schools and two senior high schools in Shanghai, Guangzhou, and Chengdu. One-third of classes of each grade in the selected schools were involved in this survey. After obtaining the informed consent of parents, an anonymous and self-administered questionnaire was distributed to students. Questionnaire was designed based on the Ecological Models of Health Behavior. Associations between EC susceptibility and covariates were identified using multivariate logistic regression.
UNASSIGNED: Among 2,270 students who had never vaped, 38.0% were susceptible to ECs. Logistic regression analysis identified factors on different levels affecting the susceptibility. Individual factors included senior high school students (OR = 1.34, 95% CI: 1.08-1.65), sensation seeker (OR = 1.11, 95%CI: 1.08-1.14), poor academic performance (OR = 1.24, 95% CI: 1.01-1.54), ever cigarette user (OR = 2.27, 95% CI: 1.29-4.01), unaware of the second-hand smoke from vaping (OR = 1.56, 95% CI: 1.25-1.96), agreeable with \"I do not want to hang around vapers\" (OR = 0.79, 95% CI: 0.64-0.97), agreeable with \"ECs are more fashionable than cigarette\" (OR = 2.50, 95% CI: 1.72-3.62) and favorable attitudes toward vaping (OR = 5.09, 95% CI: 3.78-6.85) were significantly associated with susceptibility to ECs. At interpersonal level, students who believe they would not be punished by parents for vaping increased susceptibility (OR = 1.27, 95% CI:1.01-1.59). At community level, exposure of EC advertising (OR = 1.81, 95% CI:1.46-2.25), exposure to hazard information (OR = 0.76, 95% CI: 0.59-0.97) and seeing vaping in daily life (OR = 2.11, 95% CI: 1.62-2.74), were statistically significantly associated with youth susceptibility to ECs.
UNASSIGNED: EC susceptibility was observed in a substantial proportion of adolescents who had never vaped, influenced by factors on different levels. This research underscores the urgent need for comprehensive intervention strategies to prevent the youth susceptibility to ECs.

BACKGROUND: While public health efforts have made tobacco smoking near obsolete among adolescents, vaping products are quickly taking their place. With the negative health consequences looming ahead of young vapers, there is a desperate need to curb youth vaping. Adolescents want to be actively engaged in their health which creates space to educate on vaping in this population segment.
METHODS: From January to May 2023, 35 adolescents aged 11-18 participated in interviews to assess the investigator-developed Teen E-cigarette and Vaping Educational Resource (T-EVER). All the interviews were recorded and transcribed for independent analysis by two study team members.
RESULTS: The participants liked the T-EVER, indicating they were engaged in the content. However, some participants wanted more information. The participants wanted health professionals to educate them on vaping but were worried about the potential barriers facing the implementation in community pharmacy settings.
CONCLUSIONS: Adolescents want to learn about vaping, but there are limited opportunities to do so. The T-EVER is designed to educate youth about vaping. This tool was well received and has the potential to be used by pharmacists as a vaping prevention and cessation intervention. More research is required to discern the true scope of the pharmacist\'s role in using an educational tool to address adolescent vaping.

Although the effects of cigarette smoke (CS) on the development of several intestinal diseases is well documented, the impact of e-cigarette aerosol (e-cig) on digestive health is largely unknown. To compare the effects of e-cig and CS on mouse ileum and colon, animals were chronically exposed for 6 months by nose-only inhalation to e-cig at 18 or 30 W power, or to 3R4F CS. Results showed that e-cig exposure decreased colon cell proliferation. Several other proliferative defects were observed in response to both e-cig and CS exposure, including up- and down-regulation of cyclin D1 protein levels in the ileum and colon, respectively. E-cig and CS exposure reduced myeloperoxidase activity in the ileum. In the colon, both exposures disrupted gene expression of cytokines and T cell transcription factors. For tight junction genes, ZO-1- and occludin-protein expression levels were reduced in the ileum and colon, respectively, by e-cig and CS exposure. The 16S sequencing of microbiota showed specific mild dysbiosis, according to the type of exposure. Overall, e-cig exposure led to altered proliferation, inflammation, and barrier function in both the ileum and colon, and therefore may be a gut hazard on par with conventional CS.

UNASSIGNED: E-cigarettes are the most-used nicotine product among adolescents, but limited psychometrically-sound, e-cigarette-relevant measures exist for adolescents. We examined psychometric properties of the Self-Report Habit Index (SRHI) for assessing adolescents\' habitual e-cigarette use.
UNASSIGNED: During Fall 2022, 4855 students from eight Connecticut high schools completed an anonymous survey. The analytic sample comprised 491 students who reported past-month e-cigarette use and completed the SRHI (Age M=15.94, SD=1.24 years, 56 % female, 37.1 % Hispanic, 57.6 % White). We examined the SRHI\'s latent factor structure; internal reliability; measurement invariance and between-groups differences (e.g., nicotine vs. nicotine-free vaping); and associations with total e-cigarette flavors used in the past month, past-30-day vaping frequency, and e-cigarette dependence.
UNASSIGNED: The SRHI\'s 6-item, 1-factor structure was confirmed. Internal reliability was excellent. The SRHI was scalar invariant for all subgroups tested. Nicotine (vs. nicotine-free) and daily (vs. non-daily) e-cigarette use were associated with greater habitual e-cigarette use behavior. In adjusted models, habitual e-cigarette use was associated with using more e-cigarette flavors, vaping more frequently, and greater e-cigarette dependence. Habitual e-cigarette use incrementally accounted for variance in past-month flavors used and vaping frequency beyond dependence.
UNASSIGNED: The SRHI evidenced solid psychometric properties for assessing habitual e-cigarette use behavior among high school students. Relationships between habitual use and frequency of use, e-cigarette flavors, and dependence might be expected as these constructs are associated with the three characterizing features of habitual behaviors: frequent repetition, cue-driven elicitation, and automaticity. Future prospective research can clarify the temporal ordering of habitual e-cigarette use and dependence in adolescents.

BACKGROUND: If US adults who smoke cigarettes are switching to e-cigarettes, the effect may be observable at the population level: smoking prevalence should decline as e-cigarette prevalence increases, especially in sub-populations with highest e-cigarette use. This study aimed to assess such effects in recent nationally-representative data.
METHODS: We updated a prior analysis with the latest available National Health Interview Survey data through 2022. Data were cross-sectional estimates of the yearly prevalence of smoking and e-cigarette use, respectively, among US adults and among specific age, race/ethnicity, and sex subpopulations. Non-linear models were fitted to observed smoking prevalence in the pre-e-cigarette era, with a range of \'cut-off\' years explored (i.e., between when e-cigarettes were first introduced to when they became widely available). These trends were projected forward to predict what smoking prevalence would have been if pre-e-cigarette era trends had continued uninterrupted. The difference between actual and predicted smoking prevalence (\'discrepancy\') was compared to e-cigarette use prevalence in each year in the e-cigarette era to investigate whether the observed decline in smoking was statistically associated with e-cigarette use.
RESULTS: Observed smoking prevalence in the e-cigarette era was significantly lower than expected based on pre-e-cigarette era trends; these discrepancies in smoking prevalence grew as e-cigarette use prevalence increased, and were larger in subpopulations with higher e-cigarette use, especially younger adults aged 18-34. Results were robust to sensitivity tests varying the analysis design.
CONCLUSIONS: Population-level data continue to suggest that smoking prevalence has declined at an accelerated rate in the last decade in ways correlated with increased uptake of e-cigarette use.

OBJECTIVE: To identify risk factors for relaxing a strict e-cigarette ban in households with adolescents.
METHODS: Youth (ages 12-17) in the Population Assessment of Tobacco and Health (PATH) Study whose parents held a strict vaping ban in 2016 (n = 6,514; 51.5% male) and their parents provided follow-up data on up to four occasions through 2020 on whether the ban was relaxed.
RESULTS: 13.5% of households with strict vaping bans relaxed them in a subsequent wave. Results from a logistic regression model showed that the odds of relaxing strict bans were higher if, at baseline, parents vaped (OR = 2.20; 95% CI: 1.22-3.97; p < .01), parents smoked tobacco (OR = 2.55; CI: 2.00-3.26; p < .001), youth smoked tobacco (OR = 2.27; CI: 1.29-4.00; p < .01), parents reported no smoking ban (OR = 2.68; CI: 1.88-3.81; p < .001), youth did not know that their household had a vaping ban (OR = 1.95; CI: 1.50-2.54; p < .001), and parents perceived low harm from vaping (OR = 1.60; CI: 1.16-2.19; p < .01). Although most sociodemographic controls were not independently associated, parents were less likely to relax bans if they had a college degree (OR = 0.71; CI: 0.51-0.998; p < .05), graduate degree (OR = 0.50; CI: 0.43-0.72; p < .001), or children who were non-Hispanic Black (OR = 0.69; CI: 0.49-0.96; p < .05) or Hispanic (OR = 0.62; CI: 0.47-0.81; p < .001).
CONCLUSIONS: While most households with adolescents prohibited e-cigarette use indoors, nearly one in seven relaxed prior strict vaping bans. Parents need support to maintain clear, consistent, and continuous restrictions that communicate that vaping is not safe or permissible for youth.