Predictors Of E-cigarette Use Research Articles

Vaping Behavior and Intention to Quit among Undergraduate Students in a Hispanic-Serving University.

The surge in electronic nicotine delivery systems (ENDS) usage, particularly among young adults, poses significant public health concerns. This study aimed to identify predictors of e-cigarette use, quit attempts, and frequency among undergraduate students in a Hispanic-serving university in Texas. A cross-sectional study was conducted between August 1 and October 26, 2023, recruiting undergraduate students through the Sona system, an online experiment management platform. Participants completed an online survey that covered demographics, educational status, vaping status, initiation age, reasons for first and current e-cigarette use, frequency of past usage, intentions to quit, and quit attempt frequency. Statistical analysis included descriptive statistics, multinomial logistic regression, and multivariable linear regression. Among 316 participants, 33.9% reported current e-cigarette use. Junior and senior students, as well as prior tobacco users, were more likely to be current vapers. Prior vaping experience was more prevalent among Hispanic individuals and those with a history of tobacco use. Notably, 74.3% of current users attempted to quit in the past year, with a higher frequency of quit attempts among females, Hispanic students, and those with vaping acquaintances. However, the vaping behavior and quit attempt patterns were similar across other categories. This study highlights how various factors influence e-cigarette use among college students. It suggests that prevention and quitting programs should consider the specific needs of different groups. Future studies will continue to look at different student groups to find the most effective ways to help them quit vaping.

Knowledge and Attitude toward E-Cigarettes among First Year University Students in Riyadh, Saudi Arabia

Electronic cigarettes are immensely popular among youths across the globe. However, knowledge, attitudes, and perceptions regarding their use vary by country. The present study investigated the knowledge and attitudes toward e-cigarette use among first-year university students in Saudi Arabia. A cross-sectional design was adopted, and an online, self-administered questionnaire assessing the knowledge of and attitudes toward e-cigarette use was utilized to conduct this study. The study population included students from all streams enrolled in their first year of university. Descriptive statistics were used to report percentages and frequencies, while advanced statistics, such as multiple logistic regression analyses, were used to determine associations. The lifetime and current prevalence of e-cigarette use was 27.4% and 13.5%, respectively, among first-year university students. The mean age of smoking initiation was 16.4 ± 1.2 years. Of e-cigarette users, 31.3% smoked every day and 86.7% used flavored e-cigarettes. Knowledge of the harmful effects of e-cigarettes was high (addiction, 61.2%; asthma, 61%; nicotine content, 75.2%). However, when comparing e-cigarettes to regular cigarettes, only 22.5% and 48.4% of the students reported that they carry the same risk and contain the same chemicals as regular cigarettes do. There was a lack of knowledge (17.1%) regarding government regulations related to e-cigarettes. An attitude of support was observed regarding banning e-cigarettes (2.6 ± 1.5 on a scale of 0 to 4), while at the same time, some associated e-cigarette use with helping to reduce tobacco dependency (2.1 ± 1.2). Marketing adverts were agreed upon to positively influence youth (1.9 ± 1.4). However, the participants' perceptions relating e-cigarette use to style were not well articulated. Significant gender differences were found: most of the women who participated in the study had better knowledge of e-cigarettes (p < 0.001). Being male, having higher income status (OR = 1.67; p = 0.013), being a current smoker (OR = 11.6; p < 0.001), and having intention for future use (OR = 3.45; p < 0.001) were strong predictors of e-cigarette use. These findings suggested the increasing popularity of e-cigarette use among male first-year university students. More educational campaigns and stricter regulations are needed to curb this trend.

Determinants of E-Cigarette and Cigarette Use among Youth and Young Adults in Poland-PolNicoYouth Study.

Teen use of tobacco-related products is a significant public health concern. This study evaluated the predictors of e-cigarette use among secondary school students who were never cigarette smokers and ever cigarette smokers in Poland. Methods: This study examined a sample of Polish youths aged 13–19 (n = 19,241) attending 200 schools, 12 on average in each county. The study was a part of the National Health Program in Poland for 2016–2020. Logistic regression and multivariable logistic regression models were used to calculate crude and adjusted odds ratios. Results: Of all participants, 32.5% were ever cigarette users. Among the never cigarette users, 13.6% were deemed susceptible to e-cigarette use. Among the ever cigarette users, 60.6% were deemed susceptible to e-cigarette use. Of those susceptible to e-cigarette use, 68.2% were among the 32.5% ever cigarette users. The profile of e-cigarette use among never e-cigarette users also included: pocket money available per month (more than 150 PLN) (OR = 1.7; p = 0.001), 16–17 years old (OR = 1.9; p = 0.001), parental tobacco smoking and e-cigarette usage (OR = 2.0; p = 0.01 and OR = 1.7; p = 0.001 respectively), maternal secondary education (OR = 1.1; p = 0.04), and living in big cities >500,000 inhabitants (OR = 1.4; p = 0.04). E-cigarette users among ever cigarette users were similar to never cigarette users in their opinion that e-cigarette use is less harmful than traditional smoking (OR = 1.6; p = 0.0012) and living with both parents smoking cigarettes (OR = 1.3; p = 0.02). Additionally, the determinants were: female gender (OR = 1.5; p = 0.009) in the age group less than 15 years of age (OR = 1.3; p = 0.007). Conclusions: The major determinant of e-cigarette use in this population was prior smoking. Additionally, the results revealed that fairly obvious predictors such as parental smoking and a belief in the less harmfulness of e-cigarette use are important determinants for smoking among never or ever e-cigarette users.

Predictors of past-year e-cigarette use among young adults

Understanding the underpinnings of e-cigarette use among young adults is critical to addressing increasing uptake. We identified predictors of past-year e-cigarette use among young adults in Montreal, Canada. Data on potential predictors were available for 714 young adults participating in the ongoing Nicotine Dependence in Teens Study at age 20 in 2007–08. Past-year e-cigarette use was measured at age 30 in 2017–20. Each potential predictor was studied in a separate multivariable logistic regression model controlling for age, sex, and educational attainment. Male sex, friends who smoke, cigarette smoking, use of other tobacco products, alcohol use, use of marijuana, and impulsivity predicted past-year e-cigarette use. Higher educational attainment and very good/excellent self-rated health were protective. Program and policy makers will need to consider these predictors of e-cigarette use in the design of clinical and public health interventions targeting e-cigarette use in young adults.

Examining the Survey Setting Effect on Current E-Cigarette Use Estimates among High School Students in the 2021 National Youth Tobacco Survey.

The 2021 National Youth Tobacco Survey (NYTS) was completed by youth online during class time, either in school or at home due to the COVID-19 pandemic. Given the role of NYTS data in tobacco regulatory science, it is vital to understand the effect of survey settings (home, school) on tobacco-use estimates. We used a series of multivariable logistic regressions to examine whether survey settings (home vs. school) predicted current e-cigarette use among high school students, controlling for other known predictors of e-cigarette use as well as the pandemic learning model that was dominant in students’ counties (e.g., nearly all at-home, majority in school). We observed a significant survey setting effect. Those who completed the survey in school had higher odds of current e-cigarette use than those who completed the same survey at home (AOR = 1.74); this effect was attenuated when we controlled for the pandemic learning model (AOR = 1.38). Moreover, e-cigarette use was independently associated with students’ learning model; students whose schools were nearly entirely in-person had the highest odds of e-cigarette use compared to students whose learning model was nearly all at-home (AOR = 1.65). Survey setting is a methodological artifact in the 2021 NYTS. Perceived privacy and peer effects can potentially explain this artifact.

Exposure to e-cigarette health claims and association with e-cigarette use and risk perceptions: A cohort study of young adults

IntroductionE-cigarettes have been marketed illicitly as smoking cessation aids and reduced risk tobacco products in the United States. Our study assessed consumers’ exposure to such claims and evaluated their impact on relative risk perceptions and e-cigarette use. MethodsData are from the Assessment of the post-College Experience study, which followed a cohort of young adults since 2010 when they were college freshmen. We used data from survey waves 10 (fall 2017) through 14 (fall 2019) to assess past 6 month exposure to e-cigarette marketing that made smoking cessation or modified risk tobacco product (MRTP) claims. Logistic regression models examined if exposure to claims at waves 11 through 14 were predictors of e-cigarette use and relative risk perceptions at wave 14. ResultsExposure to MRTP (28.4% to 40.1%) and cessation claims (29.1% to 46.6%) increased, with participants reporting more exposure to cessation than MRTP claims at each wave. Multiple exposures were associated with perceptions that e-cigarettes are less harmful compared to cigarettes (Cessation: AOR = 1.12, CI: 1.01–1.23; p = 0.025; MRTP: AOR = 1.16; CI: 1.05–1.29; p = 0.003). Neither claim type was associated with past 30-day e-cigarette use. Claim exposure did not increase e-cigarette initiation among never e-cigarette users. However, current cigarette smokers who had never used e-cigarettes at wave 10 had 2.5 higher odds of initiating e-cigarette use by wave 14 for each exposure to a cessation claim (AOR = 2.53; CI: 1.43–4.45; p = 0.001). ConclusionsYoung adults reported increasing exposure to unauthorized e-cigarette health claims. Exposure was associated with reduced relative risk perceptions, but was not associated with past 30-day e-cigarette use. Cessation claims may motivate current cigarette smokers to try e-cigarettes.

Impulsivity-Related Personality Traits as Predictors of E-Cigarette Use among Young Adults over Time

Introduction : There has been rising concern about e-cigarette usage among teenagers and young adults. As knowledge about the adverse health effects of e-cigarettes accumulates, it is critical to identify factors that may increase risk of vaping initiation and frequency of use. One potential risk factor known to increase risk for other substance use is impulsivity. This study tested the hypothesis that impulsivity prospectively predicts vaping over time. Methods : Active e-cigarette users (n = 137; 51.8% male; Mean age 20 years at baseline) completed 8 waves of assessment over 21 months (2017–2020). The S-UPPS-P impulse behavior scale was used at baseline to measure impulsivity, and frequency of e-cigarette, cigarette, marijuana and alcohol use was calculated at each wave thereafter. Results : Vaping frequency declined over time [Incidence Rate Ratio (IRR) = 0.92]. There were significant, stable, positive associations between e-cigarette use and lack of premeditation (IRR = 1.06) and sensation seeking (IRR = 1.09). Vaping frequency was inversely associated with negative urgency (IRR = 0.95). Positive urgency and lack of perseverance were not associated with frequency of vaping. Conclusion : These findings suggest that young adults who have higher impulsivity of certain types may use e-cigarettes more frequently. Thus, vaping interventions for young adults should address these factors to ensure the greatest impact on public health.

Employing the theory of planned behaviour to design an e-cigarette education resource for use in secondary schools

BackgroundAn extended version of the theory of planned behaviour (TPB) was used to inform the design of a framework for an educational resource around e-cigarette use in young people.MethodsA sequential exploratory design was employed. In Phase 1, elicited behavioural, normative and control beliefs, via 7 focus groups with 51 participants, aged 11–16 years, identified salient beliefs around e-cigarette use. These were used to construct a questionnaire administered to 1511 young people aged 11–16 years, which determined predictors of e-cigarette use and ever use. In Phase 2, sociodemographic variables, e-cigarette knowledge, access, use, marketing and purchasing of e-cigarettes and smoking behaviour were also gathered. The composite findings from Phase 1 and 2 informed the design of a post primary educational resource in Phase 3 around e-cigarette use.ResultsCurrent e-cigarette use was 4%, with almost 23% reporting ever use, suggesting current use is stable but experimentation may be increasing in this cohort. Sociodemographic variables, knowledge of e-cigarettes, smoking behaviour and TPB variables (direct and indirect measures of attitudes, subjective norm, and perceived behavioural control) accounted for 17% of the variance in current e-cigarette use, with higher intentions to use e-cigarettes within the next month, having the strongest impact on use (p < 0.001), followed by self-efficacy (p = 0.016). Sociodemographic and TPB variables accounted for 65% of the variance in intentions to use e-cigarettes in the next month; current e-cigarette use (p < 0.001), more positive attitudes (p < 0.001), stronger social influence (p < 0.001), higher self-efficacy (p < 0.001), higher control beliefs (p < 0.001) and greater motivation to use e-cigarettes (p < 0.001) were the main predictors of intentions. Phases 1 and 2 informed the mapping of key predictors of intentions and use of e-cigarettes onto the Theoretical Domains Framework, which identified appropriate intervention functions and behaviour change techniques.ConclusionsThis paper is the first to bridge the theoretical-practice gap in an area of significant public health importance through the development of a framework for a novel theory driven school-based educational resource aimed at reducing experimentation and uptake of e-cigarette use in young people.

Prevalence and Distribution of Electronic Cigarette Use Before and During Pregnancy Among Women in 38 States of the United States.

To examine the prevalence and the changing pattern of e-cigarette use from preconception to pregnancy. This is a cross-sectional study using data from the multi-site Pregnancy Risk Assessment Monitoring System in the United States, 2016-2017. All participating mothers with information on e-cigarette use before and during pregnancy were included. Self-reported information about e-cigarette use were assessed using questionnaires. Weighted prevalences of e-cigarette use before and during pregnancy were calculated. Multivariable logistic regressions were used to examine the association between various demographic characteristics and e-cigarette use before or during pregnancy. This study included 69 508 pregnant women from 38 states in the United States. The weighted prevalence of e-cigarette use before pregnancy and during the last 3 months of pregnancy was 3.6% (95% confidence interval [CI] 3.4%-3.9%) and 1.1% (0.9%-1.2%), respectively. The prevalence varied across states, ranging from 1.3% to 8.3% for e-cigarette use before pregnancy and from 0.1% to 3.4% for e-cigarette use during the last 3 months of pregnancy. Among women who used e-cigarettes before pregnancy, 24.4% (21.7%-27.1%) continued to use e-cigarettes during pregnancy. Among women who used e-cigarettes during pregnancy, 62.3% (56.5%-68.0%) were dual users. In multivariable analyses, cigarette smoking was most strongly associated with e-cigarette use. The adjusted odds ratio comparing smokers with nonsmokers before pregnancy was 11.10 (95% CI 9.34-13.20) for e-cigarette use before pregnancy and 6.72 (95% CI 4.38-10.31) for e-cigarette use during pregnancy. Using data from 38 states in the United States, we showed geographical variations in the prevalence of e-cigarette use before and during pregnancy. Among women who used e-cigarettes before pregnancy, a quarter of them continued to use e-cigarettes during pregnancy. Conventional cigarette use is a strong risk factor for e-cigarette use before and during pregnancy. The prevalence of e-cigarette use needs to be monitored continuously. This study provides important information to understand the status and changing patterns of e-cigarette use in pregnant women in the United States. Among pregnant women in 38 states in the United States, 3.6% of them used e-cigarettes during the 3 months before pregnancy and 1.1% used them during the last 3 months of pregnancy. The prevalence varied across states. A quarter of women who used e-cigarettes before pregnancy continued to use e-cigarettes during pregnancy. Cigarette smoking is the strongest predictor of e-cigarette use. Future research about health effects of e-cigarette use during pregnancy is in urgent need.

School-Level Prevalence and Predictors of e-Cigarette Use in 8th, 10th, and 12th Grade U.S. Youth: Results From a National Survey (2015–2016)

PurposeThe aim of this study was to examine the school-level prevalence and predictors of e-cigarette use among U.S. adolescents. MethodsThe Monitoring the Future study is an annual national cross-sectional study of secondary (middle and high) school students. This study uses 2015 and 2016 survey data from 8th, 10th, and 12th grade students (n = 38,926) attending 580 U.S. public and private secondary schools. E-cigarette use, binge drinking, cigarette smoking, marijuana use, and nonmedical prescription drug use were measured at the individual level. School-level characteristics were measured with both aggregated student-level measures (e.g., school-level e-cigarette use, school-level racial composition) and school characteristics (e.g., public vs. private, urban vs. rural). ResultsThe prevalence of past-month e-cigarette use varied considerably across 580 U.S. middle and high schools, ranging from 0% to 60% at individual schools (mean = 10.2%, standard deviation = 8.9%). Multivariable regression analyses indicated that past-month e-cigarette use was significantly higher at schools with a higher proportion of White students, schools that were located in the U.S. Southern and Western regions, and schools with higher prevalence of past-month cigarette smoking, after controlling for relevant individual- and school-level covariates. ConclusionsE-cigarette use varies considerably across schools, and this study suggests that school context plays an important role in e-cigarette use. Cigarette smoking and e-cigarette use at the school level are closely linked and are important risk factors for individual-level e-cigarette use. The wide variation in prevalence of e-cigarette use highlights the need for schools to work with professionals to obtain school-level assessment rather than relying solely on state or national results to guide prevention efforts.

Examining the Psychometric Properties of the CEAC (Comparing e-Cigarette and Cigarette) Questionnaire and Its Usefulness as a Predictor of e-Cigarette Use

Background: Electronic cigarette (e-cigarette) use continues to rise, while there is conflicting evidence about the health effects of its use. As such, research is needed to better determine risks factors for e-cigarette use. Accumulating evidence suggests that attitudes toward e-cigarette use could be a potential risk factor for e-cigarette use. Objectives: This study sought to examine the psychometric properties of the Comparing E-cigarette And Cigarette questionnaire (CEAC), and to replicate a structural model of the relationship between impulsive-related personality traits and e-cigarette use mediated by positive attitudes toward e-cigarettes. Methods: Participants were 525 adults (mean age = 33.42, SD = 11.27) who completed the CEAC and UPPS-P (trait impulsivity) questionnaires online. Results: Confirmatory factor analysis of the CEAC replicated the a priori factor structure of the questionnaire reasonably well (χ2(df = 32) =172.85, CFI = 0.94, TLI = 0.91, RMSEA = 0.09 (0.08–0.11, 90% Confidence Interval, SRMR = 0.06). Structural path analysis showed that deficits in conscientiousness was significantly negatively related to e-cigarette attitudes (β = –0.20, p = .01), while urgency (β = 0.19, p = .018) showed a significant positive relationship to e-cigarette attitudes. E-cigarette users showed significantly more positive attitudes toward e-cigarettes than nonusers (β = 0.59, p < .001). No significant direct effects were found between impulsivity-related traits and e-cigarette use. Conclusions: The present study suggests that impulsivity-related traits and attitudes toward e-cigarettes are likely to be important risk factors for e-cigarette use. Future prospective and experimental studies should test if the causal model described in this study predicts risk for e-cigarette use, and whether this model could therefore be used to guide strategies for reducing risk for e-cigarette use.

Factors associated with intentions to use e-cigarettes among Australian young adult non-smokers.

A growing body of evidence suggests e-cigarette use increases the risk of conventional cigarette use. Assessing the factors associated with intentions to use e-cigarettes can inform programs designed to minimise uptake, potentially assisting in preventing a new population of smokers. This study developed and tested a model assessing the importance of various factors that may be associated with intentions to use e-cigarettes among young adults who have never used e-cigarettes or tobacco cigarettes. A web-panel provider recruited 429 Australian 18- to 25-year-olds who had never used e-cigarettes or smoked tobacco cigarettes (56% female, mean age = 21.17 years). Various individual and social factors were assessed as potential direct and indirect predictors of e-cigarette use intentions. The developed model provided an excellent fit to the data and accounted for 49% of the variance in use intentions. Males had greater intentions to use e-cigarettes compared to females (β = -0.13). Having a greater number of friends who smoke tobacco cigarettes (β = 0.11) and curiosity about e-cigarette use (β = 0.58) were also directly associated with greater use intentions. Positive expectancies about e-cigarettes (β = 0.14), having family members who use e-cigarettes (β = 0.11), and having friends who smoke tobacco cigarettes (β = 0.07) were indirectly associated with intentions via curiosity. Curiosity about e-cigarette use was strongly associated with use intentions. Aspects of the social environment were also important. Further research is needed to identify effective means of challenging positive e-cigarette expectancies given these were found to be strongly associated with intentions via curiosity.

Electronic cigarette use among adults with asthma: 2014-2017 National Health Interview Survey.

Electronic cigarette (e-cigarette) use has increased dramatically in the United States among adults and adolescents. Patients with asthma may be most vulnerable to the chemical components of e-cigarettes as they may be a potential asthma trigger. To assess the prevalence of e-cigarette use among adult asthmatics and to evaluate the factors associated with e-cigarette use. This was a retrospective, cross-sectional study that used data from the 2014-2017 National Health Interview Survey (NHIS) database. The study sample included current asthmatics who were 18-85 years old. The outcome variable was ever use of an e-cigarette (Yes/No). The Andersen Behavioral Model of Health Services Utilization was used to identify independent variables with the potential to influence the patient's decision to try e-cigarettes. Descriptive statistics were used to describe the sample. Factors associated with e-cigarette use were assessed using logistic regression. All analyses were stratified by age group. Appropriate survey weights were used to account for the complex survey design. The study sample included 10,578 adults with current asthma and about 18% of the sample had ever tried an e-cigarette. About 20% of males and 20% of non-Hispanic Whites reported ever trying an e-cigarette. From 2014 to 2017, the e-cigarette use among the 18-24 year old age group increased the most from 20.3% to 29.1%. Current smokers were more likely to have tried e-cigarettes than former/never smokers (18-24 years OR: 11.5 CI: 7.4-18.0). This trend was significant among all age groups. Non-Hispanic Blacks were less likely to have tried e-cigarettes than non-Hispanic Whites (50-64 years OR: 0.34 CI: 0.22-0.52). The prevalence of e-cigarette use among adult asthmatics has continued to increase over time. Smoking status was the most consistent predictor of e-cigarette use among all age groups in this asthmatic population.

Predictors of E-cigarette Use Among Young Australian Women

E-cigarette use is controversial worldwide. The majority of previous studies on e-cigarette use were not gender specific. This study aimed to identify the predictors of e-cigarette use among young Australian women. This study used cross-sectional data from the 1989-1995 cohort of the Australian Longitudinal Study on Women's Health. In 2015, study participants (N=8,915) aged 19-26 years completed an online survey. Multivariable logistic regression was used to identify predictors of e-cigarette use. Data were analyzed in 2018. The prevalence of ever and past-year e-cigarette use among young Australian women was 11.1% and 6.4%, respectively. More than a quarter of past-year and ever e-cigarette users were never cigarette smokers. Use of e-cigarettes in the past year was associated with younger age (AOR per year increase=0.87, 95% CI=0.82, 0.93); financial difficulty (AOR=0.68, 95% CI=0.54, 0.87); being an ex-smoker (AOR=5.05, 95% CI=3.64, 7.01) or current cigarette smoker (AOR=10.01, 95% CI=7.77, 12.89); drinking at a level of lifetime risk of harm from alcohol-related disease or injury (AOR=1.23, 95% CI=1.01, 1.53). Ever e-cigarette use showed similar associations and was also associated with rural residence (AOR=0.74, 95% CI=0.60, 0.91) and intimate partner violence (AOR=1.44, 95% CI=1.17, 1.76). The high prevalence of e-cigarette use among never cigarette smokers has significant public health implications. Interventions to curb the use of e-cigarettes among young Australian women should focus on risk factors, such as early age, cigarette smoking, alcohol use, and intimate partner violence.

Smokers' use of electronic cigarettes before, during, and in the month after hospitalization. Findings from the Helping HAND 2 Study

IntroductionHospitalization can motivate smokers to attempt cessation, and some smokers might use e-cigarettes to aid quitting after discharge. Little is known about the patterns and predictors of smokers' e-cigarette use immediately before, during, and after hospitalization. MethodsSecondary data analysis of a multi-site randomized controlled trial that enrolled 1357 hospitalized smokers planning to quit offered two intensities of post-discharge cessation treatment and reached 1100 participants at 1-month follow-up. We assessed reasons for and patterns of e-cigarette use before, during and immediately after hospitalization. Multivariable logistic regression models identified independent predictors of e-cigarette use. ResultsE-cigarettes were used, primarily to aid quitting, by 21.4% of smokers in the month before admission, 3.1% during hospitalization, and 18.3% in the month after discharge. At 1 month, 10.6% were past 7-day (current) e-cigarette users, but few used e-cigarettes regularly and 57.3% also smoked tobacco. New e-cigarette use in the month after discharge was rare. The adjusted odds ratio (AOR;95%CI) for current e-cigarette use was higher among smokers who used e-cigarettes before hospitalization (5.08;3.31–7.81), consumed more alcohol (1.80;1.16–2.80) and had less confidence to quit (1.66;1.05–2.61). The AOR was lower among non-Hispanic blacks (0.25;0.09–0.71), Medicaid-insured (0.56;0.33–0.93), and those randomly assigned to receive free cessation medication and counseling at discharge (0.58;0.38–0.90). ConclusionsFollowing hospitalization, some smokers who plan to quit use e-cigarettes, particularly if they used them before admission, are less confident to quit, or have less easy access to conventional treatment. Clinicians should document and be prepared to address e-cigarette use among hospitalized smokers.

Prevalence and correlates of adolescents’ e-cigarette use frequency and dependence

BackgroundUnderstanding predictors of e-cigarette use among adolescents in the context of wide availability and extreme popularity of these products is important for prevention and treatment. This study identifies correlates of e-cigarette use frequency and dependence among adolescent users. MethodsAdolescent e-cigarette users (N = 173) were recruited from the San Francisco Bay Area. Participants reported demographic and psychosocial characteristics, e-cigarette use behaviors, and cigarette use. Bivariate relationships between potential correlates were examined, and correlates significant at p < .10 were included in full models predicting frequency and dependence. ResultsIn the full models, frequent use was associated with receiving one’s first e-cigarette from a family member rather than a friend (r = −0.23, p < .001) or a store ( = −0.13, p = .037), using nicotine in all e-cigarettes versus some e-cigarettes (r = −0.17, p = .007) or unknown nicotine use (r = −0.15, p = .014), using a customizable device versus a Juul (r = −0.22, p < .001), vape pen (r = −0.20, p = .002), or other/unknown device (r = −0.16, p = .009), and friends’ e-cigarette use (r = 0.20, p = .002). Dependence was associated with younger age of first use (r = −0.18, p = .012), friends’ use (r = 0.18, p = .01), and recent cigarette use (r = 0.17, p = .019). ConclusionsWhen assessing problematic e-cigarette use among adolescents, it is important to consider social factors (e.g., friends’ and family members’ e-cigarette use), device type, and dual use with cigarettes.

Electronic Cigarette Use Among Emerging and Young West Indian Adults

Currently, evidence concerning electronic cigarette (e-cigarette) use in the West Indies is unavailable. This study examines the prevalence and associated factors of e-cigarette use in young Trinidadian adults, 6 years after e-cigarettes were introduced in Trinidad. Young adults between the ages of 18 and 40 years were surveyed from May–June 2016. Based on the survey results, descriptive statistics and logistic regression models were used to identify correlations in e-cigarette use. The prevalence of those who had used e-cigarettes was 24.6%, and 41.9% of these people had used both e-cigarettes and tobacco cigarettes. A high proportion (16.95%) of those who had never used tobacco cigarettes had used e-cigarettes. Males were twice as likely as females to have used e-cigarettes (odds ratio [OR]: 2.60; 95% confidence interval [CI]: 1.85–3.68), and participants aged 18–25 years were more likely than those aged 36–40 years to use e-cigarettes (OR: 0.37; 95% CI: 0.14–0.81). The predictors of e-cigarette use as assessed by univariate analysis were current tobacco cigarette smoking (OR: 9.34; 95% CI: 6.14–14.39; p&lt;0.001) and the belief that e-cigarettes are dangerous to health (OR: 0.61; 95% CI: 0.44–0.85; p=0.004). The predictors as assessed by multivariate logistic regression (adjusted OR) were ethnicity (p=0.043), education (p=0.012), and age group (p=0.007). Those who quit using tobacco cigarettes were 7.98 times more likely to use e-cigarettes (95% CI: 4.21–15.45), and those who knew that e-cigarettes contain nicotine were 2.70 times more likely to use them (95% CI: 1.53–4.86; p&lt;0.001). Two summative scales were constructed that measured knowledge and perception. The perception scale, but not the knowledge scale (Cronbach’s alpha=0.736), was a significant predictor of e-cigarette use. The number of e-cigarette users is high (24.6%) in young adults in Trinidad and in those who have never smoked tobacco (16.95%). Current smokers, as well as those who have quit smoking, are at an increased risk of e-cigarette use. This study established that young adults have a low level of knowledge regarding e-cigarettes and shows that they should be educated on e-cigarette use. Further research to examine the reasons for, and susceptibility to, e-cigarette use is necessary.

Electronic cigarette use and uptake of cigarette smoking: A longitudinal examination of U.S. college students

IntroductionElectronic cigarette (e-cigarette) use prevalence is increasing among U.S. adolescents and adults but recent longitudinal data for college/university students are scarce. Furthermore, the extent that e-cigarette use is associated with the onset of cigarette smoking and the factors that lead to the uptake of e-cigarettes in college students has not been explored. Methods3757 participants from a Mid-Atlantic university (women: 66%; White: 45%; Black: 21%; Asian: 19%; Hispanic/Latino: 6%) were surveyed in 2014 and again in 2015. ResultsAmong participants reporting never smoking at time 1, those who had ever tried e-cigarettes or were currently using e-cigarettes (at least one use in past 30days) were more likely to have ever tried cigarettes by time 2 relative to individuals who had not used e-cigarettes. Ever use of e-cigarettes (but not current use) also increased participants' likelihood of being current cigarette smokers at time 2. Among initial never users of e-cigarettes or cigarettes, males and ever marijuana users had an increased probability of trying e-cigarettes by time 2. Furthermore, less perseverance (an index of impulsivity) and ever use of other tobacco products increased initial never users' chances of trying both cigarettes and e-cigarettes by time 2. ConclusionsGiven that never-smoking participants who had tried e-cigarettes were more likely to initiate cigarette use later, limiting young adults' access to these products may be beneficial. As the long-term health implications of e-cigarette use become clearer, predictors of e-cigarette use could help identify future populations likely to use and abuse these products.

PREVALENCE AND PREDICTORS OF E-CIGARETTE TRIAL AMONG ADOLESCENTS IN ARGENTINA.

Over the last few years, the increasing use of electronic cigarettes has become a new public health problem. Since 2011, Argentina has had a complete ban on marketing and sale of e-cigarettes. However, e-cigarettes are marketed online and can be easily bought in stores. We conducted a longitudinal study to evaluate the determinants of e-cigarette trial among Argentinean early adolescents. A school-based longitudinal study was conducted in 2014-15, in 3 large cities in Argentina. Among students who reported never smoking an e-cigarette at baseline, we assessed demographics, media use, sensation seeking, smoking behavior, network member smoking, use of other substances, and perception of e-cigarette risk as potential risk factors for e-cigarette trial at follow up (mean between-wave interval 17.1 months) using multilevel logistic regression models with random intercepts for schools. E-cigarette trial prevalence increased from baseline (1.8%; n=57) to follow up (7.1%; n=139). Independent predictors of e-cigarette use at follow up included: higher sensation seeking (OR: 1.49 95% CI 1.21-1.84); being a current smoker (OR: 2.58 95% CI 1.38-4.83); having close friends that smoke cigarettes (OR: 1.93 95% CI 1.25-2.99) and being highly exposed to tobacco product ads online (OR: 1.87 95% CI 1.04-3.36). Attending a public school was the only protective factor (OR: 0.40 95% CI 0.22-0.73). In Argentina, illicit trial of e-cigarettes among early adolescents is low but appears to be rapidly increasing. Identifying students at risk could help identify policies and programs to prevent increasing use in this population.

E-Cigarette Use and Perceived Harm Among Women of Childbearing Age Who Reported Tobacco Use During the Past Year.

The prevalence of electronic cigarette use grows. Amid increased e-cigarette use nationwide, this paper attempts to identify underlying risk factors for the most vulnerable populations. The purpose of the study was to assess predictors of e-cigarette use among female current and former tobacco users of childbearing age-specifically to determine whether demographic factors, pregnancy status, conventional cigarette smoking, and perceived e-cigarette harm are associated with e-cigarette use. Reasons for using e-cigarettes were also measured. A cross-sectional, correlational design was used; 194 current and former female tobacco users, 18-45 years of age, from two university-affiliated prenatal clinics and one women's health clinic in Kentucky took part. Slightly more than half were pregnant. Age, race/ethnicity, education, pregnancy status, use history for cigarettes and e-cigarettes, and perception of health hazard from e-cigarettes were measured, and associations with e-cigarette use were made with Mann-Whitney U-tests or Spearman's rank correlations. Predictors of e-cigarette use were determined using proportional odds modeling. Most current e-cigarette users were also current cigarette smokers (88%). Nearly half of current and former e-cigarette users were pregnant. Most women perceived e-cigarettes as a minor (38%) or moderate (31%) health hazard. In the proportional odds model, younger women were at greater risk for e-cigarette use, whereas minority women and those who were pregnant were less likely to be e-cigarette users. Pregnant women were less likely to be more recent e-cigarette users, compared with nonpregnant women. However, nearly all current e-cigarette users were dual tobacco users, including pregnant women. It is both imperative and timely to determine the impact of e-cigarette use on maternal and infant health, thus improving healthcare provider confidence to discuss the health implications of e-cigarette use with their patients.