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Objective To examine whether the increase in use of electronic cigarettes in the USA, which became noticeable around 2010 and increased dramatically by 2014, was associated with a change in overall smoking cessation rate at the population level.Design Population surveys with nationally representative samples.Setting Five of the US Current Population Survey-Tobacco Use Supplement (CPS-TUS) in 2001-02, 2003, 2006-07, 2010-11, and 2014-15.Participants Data on e-cigarette use were obtained from the total sample of the 2014-15 CPS-TUS (n=161 054). Smoking cessation rates were obtained from those who reported smoking cigarettes 12 months before the survey (n=23 270). Rates from 2014-15 CPS-TUS were then compared with those from 2010-11 CPS-TUS (n=27 280) and those from three other previous surveys.Main outcome measures Rate of attempt to quit cigarette smoking and the rate of successfully quitting smoking, defined as having quit smoking for at least three months.Results Of 161 054 respondents to the 2014-15 survey, 22 548 were current smokers and 2136 recent quitters. Among them, 38.2% of current smokers and 49.3% of recent quitters had tried e-cigarettes, and 11.5% and 19.0% used them currently (every day or some days). E-cigarette users were more likely than non-users to attempt to quit smoking, 65.1% v 40.1% (change=25.0%, 95% confidence interval 23.2% to 26.9%), and more likely to succeed in quitting, 8.2% v 4.8% (3.5%, 2.5% to 4.5%). The overall population cessation rate for 2014-15 was significantly higher than that for 2010-11, 5.6% v 4.5% (1.1%, 0.6% to 1.5%), and higher than those for all other survey years (range 4.3-4.5%).Conclusion The substantial increase in e-cigarette use among US adult smokers was associated with a statistically significant increase in the smoking cessation rate at the population level. These findings need to be weighed carefully in regulatory policy making regarding e-cigarettes and in planning tobacco control interventions.

Introduction E-cigarettes are largely unregulated and internet sales are substantial. This study examines how the online market for e-cigarettes has changed over time: in product design and in marketing messages appearing on websites. Methods Comprehensive internet searches of English-language websites from May–August 2012 and December 2013–January 2014 identified brands, models, flavours, nicotine strengths, ingredients and product claims. Brands were divided into older and newer groups (by the two searches) for comparison. Results By January 2014 there were 466 brands (each with its own website) and 7764 unique flavours. In the 17 months between the searches, there was a net increase of 10.5 brands and 242 new flavours per month. Older brands were more likely than newer brands to offer cigalikes (86.9% vs 52.1%, p<0.01), and newer brands more likely to offer the more versatile eGos and mods (75.3% vs 57.8%, p<0.01). Older brands were significantly more likely to claim that they were healthier and cheaper than cigarettes, were good substitutes where smoking was banned and were effective smoking cessation aids. Newer brands offered more flavours per brand (49 vs 32, p<0.01) and were less likely to compare themselves with conventional cigarettes. Conclusions The number of e-cigarette brands is large and has been increasing. Older brands tend to highlight their advantages over conventional cigarettes while newer brands emphasise consumer choice in multiple flavours and product versatility. These results can serve as a benchmark for future research on the impact of upcoming regulations on product design and advertising messages of e-cigarettes.

E-cigarettes have generated controversy in the tobacco control field similar to that of Swedish snus, which came to the U.S. market six years earlier. Some argue that e-cigarettes have great potential to help smokers quit regular cigarettes while others contend they should be banned for lack of safety and efficacy data. This study examined population data from the U.S. A U.S. population survey with a national probability sample (N=10,041) was conducted (February 24 to March 8, 2012, before any major paid advertisement of e-cigarettes appeared on television). Survey respondents were asked if they had heard about e-cigarettes, where they had heard about them, whether they had used e-cigarettes or snus, how often they used them, and why they used them. Responses were weighted to represent the entire U.S. population. A high proportion, 75.4%, reported having heard about e-cigarettes. Television ranked as the number one source of information, followed by \"in-person conversation\" and \"Internet.\" About 8.1% had tried e-cigarettes, and 1.4% were current users. These rates were twice those of snus (4.3% and 0.8%, respectively). Among current smokers, 32.2% had tried e-cigarettes, and 6.3% were current users. Over 80% of current e-cigarette users were non-daily users. Women were significantly more likely to have tried e-cigarettes than men. Those who had tried e-cigarettes were more likely than those who tried snus to report their products being safer than regular cigarettes (49.9% vs. 10.8%). Almost half (49.5%) of current smokers were susceptible to using e-cigarettes in the future. That e-cigarettes have surpassed snus in adoption rate, even before any promotion by major tobacco companies, suggests that the former have tapped into smokers' intuitive preference for potentially harm-reducing products, probably due to the product design. E-cigarette use is likely to increase in the next few years.

BackgroundE-cigarettes have grown popular. The most common pattern is dual use with conventional cigarettes. Dual use has raised concerns that it might delay quitting of cigarette smoking. This study examined the relationship between long-term use of e-cigarettes and smoking cessation in a 2-year period.MethodsA nationally representative sample of 2028 US smokers were surveyed in 2012 and 2014. Long-term e-cigarette use was defined as using e-cigarettes at baseline and follow-up. Use of e-cigarettes only at baseline or at follow-up was defined as short-term use. Non-users did not use e-cigarettes at either survey. Quit attempt rates and cessation rates (abstinent for 3 months or longer) were compared across the three groups.ResultsAt 2-year follow-up, 43.7% of baseline dual users were still using e-cigarettes. Long-term e-cigarette users had a higher quit attempt rate than short-term or non-users (72.6% vs 53.8% and 45.5%, respectively), and a higher cessation rate (42.4% vs 14.2% and 15.6%, respectively). The difference in cessation rate between long-term users and non-users remained significant after adjusting for baseline variables, OR=4.1 (95% CI 1.5 to 11.4) as did the difference between long-term users and short-term users, OR=4.8 (95% CI 1.6 to 13.9). The difference in cessation rate between short-term users and non-users was not significant, OR=0.9 (95% CI 0.5 to 1.4). Among those making a quit attempt, use of e-cigarettes as a cessation aid surpassed that of FDA-approved pharmacotherapy.ConclusionsShort-term e-cigarette use was not associated with a lower rate of smoking cessation. Long-term use of e-cigarettes was associated with a higher rate of quitting smoking.

BackgroundAlthough most US states prohibit cigarette smoking in public places and worksites, fewer jurisdictions regulate indoor use of electronic cigarettes (e-cigarettes). Given the dramatic increase in e-cigarette use and concern about its impact on non-users, there is a need to examine the use of e-cigarettes in smoke-free environments and related attitudes and perceptions.MethodsRecruited from a nationally representative adult panel (GfK's KnowledgePanel), 952 current users of e-cigarettes completed a cross-sectional online survey in 2014. Multivariate logistic regressions were conducted to examine the factors associated with ever using e-cigarettes in smoke-free environments.ResultsOverall, 59.5% of e-cigarette users had vaped where cigarette smoking was not allowed. Young adults (18–29 years) were most likely to do so, 74.2%. The places of first-time use most often mentioned were service venues (bar, restaurant, lounge and club), 30.7%, followed by worksites, 23.5%. Daily e-cigarette users were more likely to have vaped in smoke-free environments than non-daily users (OR=2.08, p=0.012). Only 2.5% of those who used e-cigarettes in smoke-free environments reported negative reactions from other people. Most e-cigarette users did not think e-cigarettes are harmful to themselves or to by-standers, and thus should not be banned where smoking is; those who had used e-cigarettes where smoking is banned were even more likely to hold these views.ConclusionsE-cigarette use in smoke-free environments was common, suggesting that most e-cigarette users do not consider smoke-free laws to apply to e-cigarettes. Explicit laws should be considered if jurisdictions want to prohibit e-cigarette use in public places.

Objectives. We examined smoking cessation rate by education and determined how much of the difference can be attributed to the rate of quit attempts and how much to the success of these attempts. Methods. We analyzed data from the National Health Interview Survey (NHIS, 1991–2010) and the Tobacco Use Supplement to the Current Population Survey (TUS-CPS, 1992–2011). Smokers (≥ 25 years) were divided into lower- and higher-education groups (≤ 12 years and > 12 years). Results. A significant difference in cessation rate between the lower- and the higher-education groups persisted over the last 2 decades. On average, the annual cessation rate for the former was about two thirds that of the latter (3.5% vs 5.2%; P < .001, for both NHIS and TUS-CPS). About half the difference in cessation rate can be attributed to the difference in quit attempt rate and half to the difference in success rate. Conclusions. Smokers in the lower-education group have consistently lagged behind their higher-education counterparts in quitting. In addition to the usual concern about improving their success in quitting, tobacco control programs need to find ways to increase quit attempts in this group.

People with mental health conditions (MHC) smoke at high rates and many die prematurely from smoking-related illnesses. Smoking cessation programs, however, generally do not screen for MHC. This study examined the utility of MHC screening in a large tobacco quitline to determine whether self-reported MHC predicts service utilization and quitting behaviors. A brief set of question on MHC was embedded in the routine intake of a state quitline, and 125,261 smokers calling from June 2012 to September 2015 were asked the questions. Quit attempt rate and 6-month success rate were analyzed for a random subset of participants. Overall, 52.2% of smokers reported at least one MHC. Demographic patterns like gender or ethnic difference in self-reported MHC were similar to that in the general population. Depression disorder was reported most often (38.6%), followed by anxiety disorder (33.8%), bipolar disorder (17.0%), drug/alcohol abuse (11.9%), and schizophrenia (7.9%). Among those reporting any MHC, about two-thirds reported more than 1 MHC. Smokers with MHC received more counseling than smokers with no MHC. Quit attempt rates were high for all three groups (>70%). The probability of relapse was greater for those with more than one MHC than for those with one MHC (p<0.005), which in turn was greater than those with no MHC (p < .01). The six-month prolonged abstinence rates for the three conditions were, 21.8%, 28.6%, and 33.7%, respectively. The main limitation of this study is the use of a non-validated self-report question to assess MHC, even though it appears to be useful for predicting quitting behavior. Smokers with MHC actively seek treatment to quit. Smoking cessation services can use a brief set of questions to screen for MHC to help identify smokers in need of more intensive treatment to quit smoking.

Background Individuals with mental health conditions (MHC) have disproportionately high tobacco-related morbidity and mortality due to high smoking prevalence rates. As high consumers of cigarettes, smokers with MHC may consider using e-cigarettes as an alternative form of nicotine delivery. Objective Examination of the susceptibility to use e-cigarettes by individuals with MHC. Methods A US population survey with a national probability sample (n=10 041) was used to assess ever use and current use of regular cigarettes, e-cigarettes, and US Food and Drug Administration-approved pharmacotherapy for smoking cessation. Survey respondents provided information about whether they had been diagnosed with an anxiety disorder, depression, or other MHC. Results Individuals with MHC were more likely to have tried e-cigarettes (14.8%) and to be current users of e-cigarettes (3.1%) than those without MHC (6.6% and 1.1%, respectively; p<0.01). Ever smokers with MHC were also more likely to have tried approved pharmacotherapy (52.2% vs 31.1%, p<0.01) and to be currently using these products (9.9% vs 3.5%, p<0.01) than those without MHC. Additionally, current smokers with MHC were more susceptible to future use of e-cigarettes than smokers without MHC (60.5% vs 45.3%, respectively, p<0.01). Conclusions Smokers with MHC are differentially affected by the rise in popularity of e-cigarettes. Clinical interventions and policies for tobacco control on e-cigarettes should take into account the possible outcomes and their implications for this priority population.

The California Tobacco-Use Prevention Education (TUPE) program promotes the use of evidence-based tobacco-specific prevention and cessation programs for adolescents within the school setting. Through a competitive grant process, schools are funded to provide programs for grades 6-12. This research evaluates the association between TUPE funding and tobacco prevention activities and tobacco use prevalence. This study utilized two data sources: (1) 2016 California Educator Tobacco Survey (CETS), and (2) 2015-2016 California Student Tobacco Survey (CSTS). The CETS collected data from educators about school prevention efforts, priority of tobacco prevention, and confidence in addressing tobacco issues with students. A total of 3,564 educators from 590 schools participated in CETS. The CSTS collected data from 8th, 10th, and 12th graders in California on their exposure to, attitudes about, and utilization of tobacco products. A total of 47,981 students from 117 schools participated in CSTS. This study found that TUPE-funded schools were more likely to provide tobacco-specific health education programs, to place a priority on tobacco-prevention efforts, and to prepare educators to address tobacco use than non-TUPE schools. Educators at both types of schools felt better prepared to talk with students about traditional tobacco products than about emerging products such as e-cigarettes. Overall, students at TUPE-funded schools were more likely to report receiving anti-tobacco messages from school-based programs than those at non-TUPE schools. The former were also less likely to use tobacco products, even when the analysis controlled for demographics and school-level characteristics (OR = 0.82 [95% CI = 0.70-0.96]). TUPE funding was associated with an increase in schools' tobacco-specific prevention activities and these enhanced activities were associated with lower tobacco use among students. This study also found that education and prevention efforts regarding emerging tobacco products need to be strengthened across all schools.

Abstract Introduction The objective of this study was to examine access, engagement, and quitting behaviors of American Indian/Alaska Native (AIAN) callers to the California Smokers’ Helpline. Telephone counseling is the primary function of the quitline. The overarching theoretical framework for California’s quitline is social cognitive theory, although it also utilizes motivational interviewing and cognitive-behavioral strategies. Aims and Methods AIAN (n = 16 089) and White (n = 173 425) California quitline callers from 2009 to 2018 were compared on their characteristics, engagement, and quitting behaviors. Quitline callers responded to a telephone survey at intake. A random selection was called for evaluation 7 months later (White n = 8194, AIAN n = 764). Data from the 2009 to 2017 California Health Interview Survey (CHIS) were used as a reference point for AIANs (AIAN n = 1373). Results The quitline and CHIS had similar proportions of AIANs (4.6% vs. 4.3%, respectively). AIAN smokers were more likely than White smokers to report physical (53.6% vs. 44.9%) and mental (65.7% vs. 57.8%) health conditions at intake. AIANs were more likely to participate in counseling than White callers (67.1% vs. 65.7%). Among those who received counseling, AIANs had greater odds than White smokers of making a quit attempt (adjusted odds ratio = 1.39 [1.06, 1.81]) and similar odds of quitting for 180 days (adjusted odds ratio = 0.95 [0.69, 1.31]). Conclusions Rates of access, engagement, and quitting suggest that individualized quitline counseling was as effective with AIANs as it was with White smokers. Increasing efforts to refer AIANs to existing state quitlines can help more smokers quit. Implications This study showed that AIAN smokers were well represented among California quitline callers, even without a targeted campaign. It also found that AIAN smokers engaged in quitline services and were as able to quit as their White counterparts were, even after adjusting for other baseline characteristics. One implication is that public health programs can promote quitlines using broad-based campaigns knowing that they will still motivate AIAN smokers to seek help. Another implication is that a standard, individualized counseling protocol delivered by culturally competent quitline staff can effectively help AIAN smokers to quit.