E-cigarette Users Research Articles

Association between E-Cigarette Smoking and Insulin Resistance Using the Triglyceride-Glucose Index in Korean Adults: Korea National Health and Nutrition Examination Survey.

Insulin resistance contributes to the development of cardiovascular disease and type 2 diabetes mellitus. Smoking leads to an increase in triglyceride levels, which, in turn, increases insulin resistance. Although the number of e-cigarette users has increased in recent years, few studies have investigated the association between ecigarette use and insulin resistance. Therefore, this study aimed to determine the association between e-cigarette use and insulin resistance using the triglyceride-glucose (TyG) index in Korean adults. This study included 4,404 healthy adults aged ≥20 years who participated in the Korea National Health and Nutrition Examination Survey between 2019 and 2020. Participants were categorized as never-smokers or ecigarette users, and the TyG index was categorized into low- and high-TyG index groups according to the median value (9.22). A logistic regression analysis was performed to determine the association between e-cigarette smoking and insulin resistance. E-cigarette users had a higher TyG index than never smokers (e-cigarette: mean=3.95; never: mean=9.18; P<0.001). The e-cigarette users had a higher risk of being in the high TyG index group than never-smokers (odds ratio [OR], 1.38; 95% confidence interval [CI], 1.03-1.84). In the subgroup analysis stratified by sex, age, and body mass index, a higher OR for a high TyG index was observed in men (OR, 1.46; 95% CI, 1.03-2.08) and individuals aged 60 years or older (OR, 3.74; 95% CI, 1.14-12.30). Our findings suggest that e-cigarette use is significantly associated with insulin resistance.

Evaluation and comparison of DNA alkylation and oxidative damage in e-cigarette and heated tobacco users

Objectives This study, aimed to determine and compare DNA damage in e-cigarette and HTP (IQOS) users by assessing DNA-adducts, which are biomarkers of various DNA alkylation and oxidation. Methods For the evaluation of DNA alkylation, N3-Ethyladenine (N3-EtA) and N3-Methyladenine (N3-MeA) adducts were used. DNA oxidation was assessed using, 8-hydroxy-2’-deoxyguanosine(8-OHdG). The urinary cotinine, N3-MeA, N3-EtA, and 8-OHdG concentrations of the cigarette smokers (n:39), e-cigarette users (n:28), IQOS users (n:20), passive smokers (n:32), and nonsmokers(n:41) who lived Ankara, Turkiye were determined using, liquid chromatography–tandem mass spectrometry (LC–MS/MS). Results In light of the detected 8-OHdG levels, e-cigarette (3.19 ng/g creatinine) and IQOS (4.38 ng/g creatinine) users had higher oxidative DNA damage than healthy nonsmokers (2.51 ng/g creatinine). Alkylated DNA-adducts were identified in the urine of e-cigarette (N3-MeA: 3.92 ng/g creatinine; N3-EtA: 0.23 ng/g creatinine) and IQOS (N3-MeA: 7.54 ng/g creatinine; N3-EtA: 0.29 ng/g creatinine) users. In the generation of N3-MeA adducts, a significant difference was found between IQOS users and e-cigarette users (p < 0.05). Also, DNA alkylation in flavored e-cigarette users (N3-MeA: 4.51 ng/g creatinine; N3-EtA: 0.27 ng/g creatinine) was higher than in non-flavored e-cigarette users (N3-MeA: 2.27 ng/g creatinine; N3-EtA: 0.06 ng/g creatinine). The highest cotinine levels were found in cigarette smokers (16.1316 ng/g creatinine). No significant difference was found when e-cigarette (1163.02 ng/g creatinine) and IQOS smokers were compared (1088.3 ng/g creatinine). Conclusion People who use e-cigarettes and IQOS may be at higher risk of genotoxicity than those who do not use and are not exposed to any tobacco products. Furthermore, the usage of flavoring additives in e-cigarettes contributed to additional genotoxic damage risks.

E-Cigarette Use Behavior and Expectancies Among Sexual Minority and Heterosexual College Student E-Cigarette Users

Background: College students who identify as a sexual minority (i.e., lesbian, gay, bisexual, or other sexual orientation) are at higher risk for e-cigarette use than their heterosexual or “straight” peers. However, little is known about factors, such as e-cigarette outcome expectancies, that might influence these differences in prevalence rates. Therefore, the current study examined differences between heterosexual and sexual minority college student e-cigarette users in terms of days of past-month e-cigarette use, e-cigarette dependence, and e-cigarette outcome expectancies. A secondary aim of the study was to examine whether outcome expectancies served as an explanatory mechanism in the association between sexual minority status and e-cigarette use frequency and dependence. Methods: Participants were heterosexual (n = 90; Mage = 19.65, SD = 2.70; 76.7% female; 77.8% White) and sexual minority (n = 44; Mage = 20.02, SD = 2.18; 68.2% female; 90.9% White) college student e-cigarette users who completed self-report measures. Results: Students who identified as a sexual minority reported greater e-cigarette dependence, more frequent past 30-day use, and greater negative consequences and positive reinforcement e-cigarette outcome expectancies. Follow-up mediation analyses indicated a significant indirect effect of sexual minority status on both days of past-month e-cigarette use and e-cigarette dependence through expectancies for negative consequences and positive reinforcement. Conclusions: These findings suggest that positive reinforcement and negative consequences outcome expectancies may be contributing to the disparities in e-cigarette use among college students who identify as a sexual minority and could be useful targets for cessation interventions for this population.

Aerosolized e-liquid base constituents induce cytotoxicity and genotoxicity in oral keratinocytes.

Electronic cigarette (e-cigarette) use among adults in the United States continues to rise. Particularly concerning is the impact of e-cigarette aerosol inhalation on the oral mucosa. Aerosols are derived from a heated e-liquid base of propylene glycol/glycerin (PG/G) often mixed with nicotine and chemical flavors. Of note, harmful and potentially harmful constituents (HPHCs), including metals and volatile organic compounds, have been detected in e-cigarette aerosols. It remains unknown, however, whether aerosols exclusively derived from e-liquid PG/G are detrimental to oral keratinocytes. The present study analyzed toxicological outcomes in normal oral keratinocytes exposed to model nicotine-free, unflavored PG/G e-liquid aerosols. Cell viability/cytotoxicity, genotoxicity, and immunoblotting assays were conducted in NOKSI, a gingiva-derived oral keratinocyte cell line, following exposure to model e-liquid aerosols or non-aerosolized controls. The HPHC acrolein, reported to form DNA adducts in the buccal mucosa from e-cigarette users, was also used in similar assays. PG/G e-liquid aerosol extracts significantly enhanced cytotoxic and DNA damaging responses in NOKSI cells when compared to non-aerosolized e-liquid treatment. Acrolein treatment led to similar results. The aerosolization process of PG/G e-liquid is a critical determinant of marked cytotoxic and genotoxic stimuli in oral keratinocytes.

Comparative Analysis of Pulmonary Health Among Traditional Smokers, Non-Smokers, and E-Cigarette Users: A Cross Sectional Study

Comparative Analysis of Pulmonary Health Among Traditional Smokers, Non-Smokers, and E-Cigarette Users: A Cross Sectional Study

Association between the use of electronic cigarettes and myocardial infarction in U.S. adults

BackgroundCompared with conventional cigarettes, electronic cigarettes are less harmful in some studies. However, recent research may indicate the opposite. This study aimed to determine whether e-cigarette use is related to myocardial health in adults in the U.S.MethodsThis study used data from the 2020 Behavioral Risk Factor Surveillance System (BRFSS), a cross-sectional survey of adult US residents aged 18 years or older. We examined whether e-cigarette use was related to myocardial infarction byapplying a logistic regression model to calculate odds ratios (ORs) and 95% confidence intervals (CIs).ResultsThe final analytical sample included 198,530 adults in the U.S. Logistic regression indicated that U.S. adults who reported being former and some days of e-cigarette use had 23% and 52% greater odds of ever having an MI, respectively, than did those who reported never using e-cigarettes (OR = 1.23, 95% CI 1.08–1.40, p = 0.001; OR = 1.52, 95% CI 1.10–2.09, p = 0.010).ConclusionsThe results suggest that former and someday users of e-cigarettes probably have increased odds of myocardial infarction in adults in the U.S. Further research is needed, including long-term follow-up studies on e-cigarettes, since it is still unknown whether they should be discouraged.

E-cigarette use and respiratory illnesses among U.S. adults: An analysis of the Population Assessment of Tobacco and Health Study

IntroductionElectronic cigarettes (e-cigarette) entered the United States marketplace in 2007. Because of the chemical composition of e-cigarette liquid, there are concerns related to its effects on respiratory illnesses. MethodsUsing Wave 4 (2016–2018) of the adult (≥18 years of age) Population Assessment of Tobacco and Health study, logistic regression was used to quantify the association between e-cigarette use and any respiratory illness (asthma, chronic bronchitis, COPD, emphysema, or other lung or respiratory conditions). Age, gender, and the use of other tobacco products were assessed as modifiers of this relationship via interactions on the additive and multiplicative scales. ResultsAfter adjustment, ever e-cigarette use was associated with a 1.32 (95 % confidence intervals [CI]:1.03, 1.69) greater odds of any respiratory illness compared with never e-cigarette users among U.S. adults. When comparing ever and never e-cigarette users, older adults (Odds Ratio [OR] = 1.65, 95 %CI:1.20, 2.26), and ever users of other tobacco products (OR = 1.77, 95 %CI:1.37, 2.29) had greater odds of reporting any respiratory illness than younger adults and those who never used other tobacco products. Among never e-cigarette users, men (OR = 1.51, 95 %CI:1.12, 2.04) were less likely to report any respiratory illness than women. Only the joint effect of age and e-cigarette use on any respiratory illness was statistically significant, suggesting this effect was greater than expected on the additive and multiplicative scales. ConclusionThese findings suggest that the relationship between e-cigarette use and any respiratory illness varies with age. Interventions and policies to reduce e-cigarette use should target high-risk groups for any respiratory illness.

E-Cigarette Nicotine Delivery Among Young Adults by Nicotine Form, Concentration, and Flavor

Concerns have been raised about the abuse liability of modern e-cigarettes that use acidic additives to form nicotine salts, making the inhalation of nicotine smoother than freebase nicotine. To examine the effects of nicotine form and concentration and e-liquid flavor on subjective effects ratings, vaping behavior, and nicotine uptake among young adults who use e-cigarettes. In this single-blind, within-participant, crossover randomized clinical trial, a convenience sample of young adults aged 21 to 25 years who currently used e-cigarettes was recruited from December 2021 to August 2023, for in-person research laboratory visits in Columbus, Ohio. Participants completed up to 9 vaping sessions, starting with their usual e-cigarette brand in the first session followed by 1 of 8 laboratory-prepared e-liquids in a randomly assigned order in each subsequent session. Prepared e-liquids varied by nicotine form (salt-based vs freebase), nicotine concentration (5% vs 1% weight per weight), and flavor (menthol vs tobacco). Each session included a 5-minute, 10-puff standardized vaping period followed by 30 minutes of ad libitum vaping. At 4 time points (0, 5, 10, and 35 minutes) during each vaping session, plasma samples were collected for assessing nicotine uptake, and self-reports of urges, craving, and withdrawal were collected via questionnaires. Positive subjective effects were self-reported after 35 minutes of vaping using a visual analog scale; urges and cravings were reported using the Questionnaire of Smoking Urges (QSU). Puff topography data were collected throughout each vaping session. Seventy-two participants (mean [SD] age, 22.4 [1.4] years; 42 [58.3%] female) who sampled at least 1 laboratory-prepared e-liquid composed the analytic sample. Salt-based (vs freebase) nicotine e-liquids increased nicotine intake, with 5% salt-based e-liquids delivering the highest mean plasma levels of nicotine (11.2 ng/mL [95% CI, 9.3-13.2 ng/mL] at 5 minutes; 17.2 ng/mL [95% CI, 14.3-20.1 ng/mL] at 35 minutes) irrespective of flavors. Higher positive subjective effect ratings (eg, for liking) were received by salt-based (42.8; 95% CI, 39.4-46.1) vs freebase (32.0; 95% CI, 28.6-35.3) nicotine, 1% (43.4; 95% CI, 40.2-46.6) vs 5% (31.2; 95% CI, 27.7-34.6) nicotine, and menthol-flavored (43.2; 95% CI, 39.7-46.7) vs tobacco-flavored (31.5; 95% CI, 28.4-34.7) e-liquids. Salt-based and 1% but not menthol-flavored nicotine elicited more intense puffing (eg, 25% [95% CI, 12%-40%] more total puffs for nicotine salts vs freebase). All study e-liquids reduced urges and cravings, with 5% vs 1% nicotine being more effective (mean [SE] QSU-Desire score at 35 minutes, 15.4 [0.5] vs 16.7 [0.5]). In this crossover randomized clinical trial among young adult e-cigarette users, salt-based (vs freebase) nicotine e-liquids increased nicotine intake and yielded more positive subjective effects ratings and intense puffing behaviors, suggesting higher abuse potential. Restricting the level of acidic additives and menthol flavoring may reduce the addictiveness of e-cigarettes. ClinicalTrials.gov Identifier: NCT05458895.

Prevalence, demographic, socio-economic, and lifestyle factors associated with cigarette, e-cigarette, and dual use: evidence from the 2017-2021 Scottish Health Survey.

Understanding the correlation between demographic, socio-economic, and lifestyle factors with e-cigarette use, cigarette smoking, and dual use is essential for targeted public health interventions. This study examines the prevalence of these behaviors in Scotland and identifies the associated factors. We conducted a repeated cross-sectional analysis of the Scottish Health Survey data from 2017 to 2021, leveraging data from 12,644 participants aged 16 and older: 2271 cigarette smokers, 687 e-cigarette users, 428 dual users, and 9258 never users. Weighted prevalences were calculated by age group, sex, and survey year, followed by weighted multinomial logistic regression to explore associated factors. The overall prevalences were 72.0% (95% CI 70.9-73.1) for never users, 18.9% (95% CI 17.9-19.9) for cigarette smokers, 5.5% (95% CI 5.0-6.1) for e-cigarette users, and 3.6% (95% CI 3.2-4.0) for dual users. From 2017 to 2021, cigarette smoking declined from 21.7% (95% CI 19.6-23.9) to 13.1% (95% CI 11.5-15.0), e-cigarette use from 6.5% (95% CI 5.4-7.8) to 4.8% (95% CI 3.6-6.4), and dual use from 3.7% (95% CI 2.9-4.6) to 2.7% (95% CI 1.9-3.7). Age was a critical factor, with the 25-34 age group more likely to use e-cigarettes (p = 0.007) and the 35-44 age group more likely to engage in dual use (p = 0.006) compared to the 16-24 age group. Males had higher odds of e-cigarette use than females (p = 0.031). White individuals had higher odds of using e-cigarettes (p = 0.023) and being dual users (p = 0.017) compared to non-whites. Previously married individuals had higher odds of dual use than singles (p = 0.031). Larger household sizes were linked to reduced odds of all three behaviors (p = 0.001). Rural residents were less likely to use e-cigarettes compared to urban residents (p = 0.025). Higher education correlated with lower odds of all three behaviors (p = 0.001). Manual occupation increased the likelihood of dual use (p = 0.042). Lower income and higher deprivation significantly increased the odds of all three behaviors (p < 0.001). Excessive alcohol consumption was associated with increased odds of the three behaviors (p < 0.001). Poor sleep quality correlated with increased odds of dual use (p = 0.002) and cigarette smoking (p < 0.001). Adherence to physical activity guidelines was associated with reduced odds of all three behaviors (cigarette smoking p < 0.001, e-cigarette use p = 0.031, dual use p = 0.016). In conclusion, this study showed a decline in the prevalence of cigarette smoking, e-cigarette use, and dual usage from 2017 to 2021 in Scotland. Significant associations with demographic, socio-economic, and lifestyle factors highlight the need for targeted public health interventions.

E-Cigarette Use, Cigarette Smoking, and Sex are Associated with Nasal Microbiome Dysbiosis.

Previous research suggests that e-cigarettes can alter immune function, including in the nasal mucosa, in unique ways. The respiratory microbiome plays a key role in respiratory host defense, but the effects of e-cigarettes on the respiratory or nasal microbiome, are not well understood. Using 16S rRNA gene sequencing on nasal samples from adult e-cigarette users, smokers, and nonsmokers, we determined that e-cigarette use and cigarette smoking are associated with differential respiratory microbiome dysbiosis and substantial sex-dependent differences in the nasal microbiome, particularly in e-cigarette users. Staphylococcus aureus, a common respiratory pathogen, was more abundant in both e-cigarette users and smokers in comparison with nonsmokers, while Lactobacillus iners, often consider a protective species, was more abundant in smokers but less abundant in e-cigarette users in comparison with nonsmokers. In addition, we identified significant dysbiosis of the nasal microbiome between e-cigarette users and smokers with high versus low serum cotinine levels, an indicator of tobacco product use and toxicant exposure. We also analyzed nasal lavage fluid for immune mediators associated with host-microbiota interactions. Our analysis identified disruption of immune mediators in the nose of e-cigarette users and smokers, which is indicative of disrupted respiratory mucosal immune responses. Taken together, our data identified unique, sex-dependent host immune dysfunction associated with e-cigarette use in the nasal mucosa. More broadly, our data highlight the need for continued inclusion and careful consideration of sex as an important variable in the context of toxicant exposures. This is the first study investigating the effects of e-cigarette use and sex on the nasal microbiome, which is considered an important gatekeeper for protecting the lower respiratory tract from pathogens. We found significant sex, exposure group, and serum cotinine level associated differences in the composition of the nasal microbiome, demonstrating the importance of considering sex in future nasal microbiome studies and warranting further investigation of the mechanisms by which e-cigarette use dysregulates nasal immune homeostasis.

An adaptation and exploratory factor analysis of the smoking-related weight and eating episodes test (SWEET) for electronic cigarette users

IntroductionSmoking for weight control is a well-documented behavior. There is emerging evidence to suggest electronic cigarettes (e-cigarettes) may be used for similar motivations yet measure development for the use of e-cigarettes for weight control has received less attention. The objective of the current study was to adapt and explore the psychometric properties of The Smoking-Related Weight and Eating Episodes Test (SWEET) for e-cigarette users. MethodsYoung adult (N=1875) current cigarette, e-cigarette, and dual users completed the original SWEET (SWEET-C) and/or adapted SWEET for e-cigarette use (SWEET-EC) based on current tobacco product use. Demographics, associated e-cigarette characteristics, nicotine dependence, outcome expectancies, and eating disorder behaviors were also assessed. Participants were recruited online and measures were completed via self-report. ResultsFour exploratory factor analyses using principal components extraction and direct oblimin rotation methods were run to explore the SWEET-C and SWEET-EC. A one-factor solution explaining 66 % of the variance was retained for the SWEET-C, and a one-factor solution explaining 73 % of the variance was retained for the SWEET-EC. Both measures exhibited excellent internal consistency. Higher SWEET-EC scores were observed among dual users, and were associated with daily e-cigarette use, JUUL use, self-reported vaping for weight control, older age, higher body mass index, and problematic eating behaviors. ConclusionOur findings support the adaptation of the SWEET-EC to measure e-cigarette use for weight control. The SWEET-EC will help to better understand how individuals use e-cigarettes to curb eating behavior and for weight control.

Disposable e-cigarette use: Factors, frequency and cigarette smoking among United States high school students.

Disposable e-cigarette use has increased among United States (US)high school students in recent years. However, there is limited research on the profile of these users, how often they use these products, and whether they displace cigarette smoking. This study aimed to measure how disposable e-cigarette use among US youth varies according to demographic characteristics and whether there is any association between e-cigarette use and reduced use of traditional cigarettes. We used cross-sectional data from the 2022 National Youth Tobacco Survey and conducted a multinomial logistic regression to examine factors associated with the types of e-cigarette devices used in the prior 30 days, adjusting for sex, sexual identity, grade level and race/ethnicity. We also used a finite mixture model to account for unobserved differences among users and identify e-cigarette use patterns in different subgroups of users. United States. High school students in grades 9-12 (n = 14 389). Survey participants self-reported the type of e-cigarette device used, the frequency of e-cigarettes used and cigarettes smoked over the past 30 days. Disposable e-cigarettes were the most popular e-cigarette type. Sex, sexual orientation, grade level and race/ethnicity were associated with disposable e-cigarette use. The odds of disposable e-cigarette use were lower in male students than in female students (odds ratio [OR] = 0.78, 95% confidence interval [CI] = [0.64-0.96]), and higher in students who identified as gay or lesbian (OR = 1.70, 95% CI = [1.11-2.61]) or bisexual (OR = 1.52, 95% CI = [1.16-1.99]) than in heterosexual students. The odds of disposable use were higher among students in higher grades (10th, 11th and 12th) than in 9th graders (OR = 1.71, 2.24 and 2.52, respectively). Disposable e-cigarette users had a lower frequency of traditional cigarette use than other e-cigarette users, both in the low-frequency class (incidence rate ratio [IRR] = 0.33, 95% CI = [0.12-0.92]) and the high-frequency class (IRR = 0.27, 95% CI = [0.08-0.92]). Disposable e-cigarette use appears to be higher among United States high school students who are female, older and/or identify as gay, lesbian or bisexual. Disposable e-cigarettes appear to be associated with reduced traditional cigarette use.

A pilot study on oral microbiome in electronic cigarettes consumers versus traditional cigarettes smokers.

Oral microorganisms are closely related to oral health, the occurrence of some oral diseases is associated with changes in the oral microbiota, and many studies have demonstrated that traditional smoking can affect the oral microbial community. However, due to the short time since the emergence of e-cigarettes, fewer studies are comparing oral microorganisms for users of e-cigarettes versus cigarettes. We collected saliva from 40 non-smokers (NS), 46 traditional cigarette smokers (TS), and 27 e-cigarette consumers (EC), aged between 18 and 35 years. We performed 16S rRNA gene sequencing on the saliva samples collected to study the effects of e-cigarettes versus traditional cigarettes on the oral microbiome. The results showed that compared with the NS group, the alpha diversity of oral flora in saliva was altered in the TS group, with no significant change in the e-cigarette group. Compared with the NS and EC groups, the relative abundance of Actinomyces and Prevotella was increased in the TS group. However, compared with the NS and TS groups, the relative abundance of Veillonella was increased, and the relative abundance of Porphyromonas and Peptostreptococcus was decreased in the EC group. These results showed that both e-cigarettes and traditional cigarettes could alter the structure and composition of oral microbiota. The use of traditional cigarettes promotes the growth of some anaerobic bacteria, which may contribute to dental decay and bad breath over time. E-cigarettes have a different effect on the structure and composition of the oral microbial community compared to conventional cigarettes. In order to better understand the effects of e-cigarettes and traditional cigarettes on users' mouths, future studies will investigate the relationship between diseases such as dental caries and periodontitis and changes in oral microbial species levels.

Partial Nicotine Reduction and E-Cigarette Users’ Puffing Behaviors Among Adults Aged 21 to 35 Years

The advent of salt-based, high-nicotine electronic nicotine delivery systems [e-cigarettes] has contributed to their epidemic use among young people in the US, necessitating the need for policies to address the addictiveness of these products. To evaluate the effect of partial nicotine reduction on new-generation e-cigarette users' puffing behaviors. This randomized crossover clinical trial was conducted at the Clinical Research Lab for Tobacco Smoking at Florida International University in Miami between April 15, 2022, and October 17, 2023. Using a volunteering sampling method by distributing flyers and advertisements, current e-cigarette users (who preferred 5% nicotine concentration), aged 21 to 35 years, were included. In a crossover design, participants completed 2 sessions of the same product (JUUL or NJOY) that differed by nicotine concentration (3% [JUUL] or 2.4% [NJOY] and 5% [JUUL or NJOY]) in random order. In each session, participants vaped up to 60 minutes ad libitum, preceded by 12 hours of nicotine abstinence. The primary outcomes were puffing topography parameters (eg, total session time, puffing time, total puffing number, interpuff interval, total inhaled volume, average puff volume, duration, and flow rate) measured during each session and plasma nicotine measured before and after each session. Among 735 participants who were approached for eligibility, 675 were excluded, and 10 did not complete session 2. Of the 50 remaining current e-cigarette users (mean [SD] age, 23 [3] years; 56% men), 23 (46%) were low nicotine dependent. The median topography parameters were significantly higher during the e-cigarette use sessions with 3% or 2.4% nicotine concentration compared with 5% nicotine concentration for 3 outcomes: puffing time (1.3 minutes [IQR, 0.3-9.4 minutes] vs 1.2 minutes [IQR, 0.2-5.6 minutes]; P = .02), puff duration (2.6 seconds [IQR, 0.8-6.9 seconds] vs 2.4 seconds [IQR, 0.4-6.6 seconds]; P = .02), and total inhaled volume (1990.0 mL [IQR, 279.0-24 400.0 mL] vs 1490.0 mL [IQR, 148.0-14 300.0 mL]; P = .05). The median plasma nicotine boost observed in the 5% nicotine concentration condition (0.0060 mg/L [IQR, 0.0001-0.0249 mg/L]) was significantly higher than that in the 3% or 2.4% session (0.0043 mg/L [IQR, 0.0008-0.0225 mg/L]) (P = .001). Additionally, deeper puffing (increased average puff duration and average puff volume) was observed in participants with higher nicotine dependence (1.42 seconds [95% CI, 1.12-1.80 seconds]; P = .03) and male users (1.38 mL [95% CI, 1.09-1.75 mL]; P = .04) in response to nicotine reduction. This randomized crossover clinical trial provides direct evidence that partial nicotine reduction in salt-based e-cigarettes was associated with acute compensatory puffing and the potential for increased exposure to toxicants. However, given the reduced nicotine delivery associated with nicotine reduction, the acute compensatory response observed in this study may not preclude a population benefit due to the marketing of less addictive products. These results suggest that at least for current e-cigarette users, partial nicotine reduction can lead to enhanced exposure to some toxicants in the short term. ClinicalTrials.gov Identifier: NCT05205382.

Differences in Attentional Bias Toward e-Cigarette Cues Between e-Cigarette Users and Nonusers.

The use of electronic nicotine delivery systems (ENDS) has increased rapidly in recent years, particularly among young adults. There is a dearth of research on the cognitive factors that contribute to ENDS use. One of the possible cognitive mechanisms involved with addictive behavior is attentional bias (AB). AB can manifest as either facilitated attention engagement toward or delayed attention disengagement from a relevant stimulus. The purpose of this study was to examine the difference in AB toward ENDS-related cues between ENDS users and non-ENDS users. ENDS users (n = 29) and nonusers (n = 24) between the ages of 18 and 29 years participated in the dot-probe and eye-tracking picture-viewing tasks. The results showed that there was a significant difference in the variance of AB between the two groups. In the eye-tracking task, ENDS users displayed significantly greater net dwell time and fixation time at time frames of 6-9, 9-12, and 12-15 seconds, compared to nonusers. It is noteworthy that ENDS users exhibited attentional fluctuation toward ENDS cues as well as difficulties disengaging attention from ENDS cues. The current findings offer insight into the nature of attentional processes associated with ENDS cues and provide useful data to guide the development of a nurse-led cognitive intervention focusing on biased attentional processing related to ENDS cues.

Tobacco and Nicotine Product Use Transitions by Race and Ethnicity: Results from a Latent Transition Analysis Using Data from the Truth Longitudinal Cohort (2020–2022)

Objective To examine use and frequency patterns across e-cigarettes, cigarettes, and little cigars, cigars, and cigarillos (LCCs) over time and determine whether patterns differ by race and ethnicity. Methods Data was obtained from the Truth Longitudinal Cohort of youth and young adults between September 2020 and June 2022. Latent class and transition analyses were used to classify participants (N = 4448) into subgroups, based on frequency of tobacco product use in the past 30 days, and to estimate the probability of use pattern transitions by race and ethnicity, adjusted for the effects of gender, financial situation, parental education, household tobacco use, and sensation seeking. Results Four latent classes were identified: former/noncurrent users, predominantly frequent to daily (FTD) e-cigarette users, predominantly FTD e-cigarette and LCC users, and predominantly FTD cigarette with polytobacco users. Use trajectories differed by race and ethnicity. A lower proportion of those who identified as non-Hispanic Black (60.0%) remained e-cigarette and LCC users, relative to those who identified as non-Hispanic White (86.0%), Hispanic or Latino (86.0%), and another race and ethnicity (79.0%). A lower proportion of those who identified as Hispanic or Latino (54.0%) and another race and ethnicity (59.9%) remained cigarette with polytobacco users, relative to those who identified as non-Hispanic White (76.0%) and non-Hispanic Black (72.0%). A greater proportion of non-Hispanic Black respondents transitioned from e-cigarette and LCC user to former/noncurrent user (40.0%) and polytobacco user to e-cigarette and LCC user (11.0%), relative to other racial/ethnic groups. Conclusion More research is needed to determine why tobacco use trajectories differ by race and ethnicity. Such research will be important in informing comprehensive approaches that promote evidence-based prevention policies and programs.

Determinants of Electric Cigarette (Vape) Use by Adolescents In Indonesia

Vaping is a form of changing conventional cigarettes into electronic cigarettes. Since 2014, the distribution of e-cigarettes throughout the world has become a trend and has reached various groups of consumers. In Indonesia, e-cigarette users continue to increase every year. GATS (Global Adult Tobacco Survey) findings in 2021 submitted by the Ministry of Health of the Republic of Indonesia found that there was an increase in the prevalence of e-cigarette users up to 10 times compared to the last survey in 2011, from 0.3% to 3% including in the world is increasing, especially in teenagers. This research aims to determine the determinants of electronic cigarette (vape) use among teenagers in Indonesia. This research uses a systematic literature study through searches using the Google Scholar site. The inclusion criteria are the article has been published in a journal, explains the factors of electronic cigarette/vape use among teenagers and the article can be downloaded while the exclusion criteria is the article only form an abstract. Based on these criteria, 13 articles were obtained. As a result, several factors influence the use of electronic cigarettes (vape) among teenagers in Indonesia. These factors include knowledge, perception of e-cigarettes, support from friends and family, cigarette information/advertisement, ease of access to e-cigarettes, price of e-cigarettes, and lifestyle influencing adolescent behavior in using e-cigarettes (vape). There needs to be a policy from the government to regulate the use of e-cigarettes in Indonesia.

Assessing the Dependence and Perceptions of the Harm and Addictiveness of Electronic Cigarettes among Saudi University Students: A Cross-Sectional Study.

(1) Background: The rising prevalence of e-cigarette use among university students necessitates a comprehensive understanding of dependence levels and associated factors. This study investigates e-cigarette dependence among Jazan University students in Saudi Arabia. (2) Methods: With the use of a cross-sectional design, data were collected from 1187 students through an online survey from January to April 2024. Dependence levels were assessed using the Penn State Electronic Cigarette Dependence Index (PS-ECDI), and the Arabic version of the questionnaire was validated through pilot testing. Multivariable logistic regression analysis was employed to identify factors associated with e-cigarette dependence. (3) Results: The results indicated that among current e-cigarette users, 37.4% had low dependence, 34.4% had medium dependence, and 13.8% had high dependence. A significant proportion of current and ever users regarded e-cigarettes to be less harmful (50.6% and 44.4%, respectively) and less addictive (37.9% and 32.3%, respectively) than cigarettes. Significant factors influencing dependence included gender, with males showing higher odds of medium (AOR = 12.8, 95% CI: 3.4-47.6) and low dependence (AOR = 9.7, 95% CI: 2.5-37.3) compared to females. Longer duration of e-cigarette use (>2 years) was strongly associated with high dependence (AOR = 50, 95% CI: 7.7-324). Daily use and multiple quit attempts were also significant predictors of higher dependence levels. (4) Conclusions: These findings highlight the substantial e-cigarette dependence among university students and underscore the need for targeted interventions to address this growing public health concern.

Quitting intentions and behaviours among young Australian e-cigarette users.

With the prevalence of e-cigarette use among Australian youth increasing significantly in recent years, greater attention is being paid to encouraging and supporting cessation. However, research to inform such efforts is lacking. The present study sought to (i) measure desire to quit e-cigarette use and actual quitting attempts among young Australians and (ii) explore correlates of quitting-related cognitions and behaviours. This was a cross-sectional on-line survey conducted in Australia. The participants were 14-25-year-old e-cigarette users (n = 602; 53% women). Desire to quit vaping and attempts to quit vaping were the primary dependent variables. The independent variables included several individual (e.g. harm perceptions, perceived appeal of vapes), social (descriptive norms) and environmental (e.g. ease of e-cigarette access) factors. A majority of respondents (61%) expressed a desire to quit vaping, and just over half (55%) had made a quit attempt. Finding vapes easy to access was associated with both a lack of desire [odds ratio (OR) = 0.71] and attempts to quit (OR = 0.77), while self-reported addiction to vaping (OR = 1.42 and OR =3.11) and perceiving vaping to be associated with mental health risks (OR =1.30 and OR =1.40) were positively correlated with these variables. Perceiving that vaping is common among people of one's age (OR = 0.82) and finding vapes appealing (OR = 0.55) were associated with a lack of desire to quit, while perceiving vaping to have physical health risks was positively associated with quitting desire (OR = 1.58). School-based education on vaping was associated with reporting an attempt/s to quit (OR = 0.47). This survey of young Australian e-cigarette users suggests a high level of desire to quit using e-cigarettes and attempts to quit. Increasing knowledge regarding the physical and mental health risks associated with e-cigarette use may assist with promoting quitting-related intentions. Changing social norms, reducing the accessibility of e-cigarettes and reducing the appeal of the products also constitute potential means of increasing the desire to quit.

Cannabis and vaping nicotine: An exploration of risk factors using a nationally representative sample of youth and young adults

BackgroundGiven that cannabis and e-cigarettes are among the most commonly used substances among young people, there is a need to identify risk factors for concurrent cannabis consumption and nicotine vaping among youth and young adults. MethodsData were obtained from the Truth Longitudinal Cohort, collected from September 2020 to March 2021, among a cohort aged 15–24 years (N = 6379). Chi-square tests were conducted to detect differences in sample characteristics by dual use status (never e-cigarette and never cannabis users, never cannabis and former/noncurrent e-cigarette users, never e-cigarette and former/noncurrent cannabis users, former/noncurrent e-cigarette and cannabis users, current e-cigarette only users, current cannabis only users, and concurrent cannabis and e-cigarette dual users). Multinomial logistic regression was used to determine key demographic variables predicting dual use status. ResultsHousehold tobacco use (Relative Risk Ratio, RRR = 4.93), higher sensation seeking (RRR = 3.98), and mental health score (RRR = 2.58) were associated with higher risk of dual use. Being 15–17 years (RRR = 0.22), being female (RRR = 0.59) and having parents with an education level of some college or more (RRR = 0.64) were associated with lower risk of dual use. ConclusionFindings suggest the need to carefully monitor cannabis and vaping nicotine among young people. The identification of risk factors provides additional guidance for prevention and treatment efforts, suggesting the need to address use of both substances and target those most at risk.