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Background and aims Cigarette smoking takes place within a cultural and social context. Political views and practices are an important part of that context. To gain a better understanding of smoking, it may be helpful to understand its association with voting patterns as an expression of the political views and practices of the population who smoke. This study aimed to assess the association between cigarette smoking and voting intentions and to examine how far any association can be explained by sociodemographic factors and alcohol use. Methods Pooled monthly representative repeat cross-sectional household surveys of adults (16+) in England (N = 55,482) between 2015 and 2020 were used to assess the association between cigarette smoking status and voting intentions, and whether this was accounted for by age, occupational grade, gender, region and alcohol use. Voting intention was measured by asking ‘How would you vote if there were a General Election tomorrow?’ Respondents chose from a list of the major English political parties or indicated their intention not to vote. Results In adjusted multinomial regression, compared with intending to vote Conservative (majority party of government during the period), being undecided (aOR1.22 [1.13-1.33] Conclusions Controlling for a range of other factors, current as compared with never-smokers appear more likely to intend not to vote, to be undecided, to vote for Labour or a non-mainstream party, and less likely to vote for the Liberal Democrats, compared with the Conservative party.

Aims To estimate the associations between regular exposure to smoking by other people and motivation and attempts to quit among current smokers. To examine whether socio-demographic and other factors moderate these associations. Design A repeat nationally representative cross-sectional survey. Data were collected monthly between November 2014 and February 2019. Setting England. Participants Current smokers ≥16 years of age from the Smoking Toolkit Study (n = 15 136). Measurements Participants were asked whether other people regularly smoke in their presence, how motivated they were to quit and whether they had made a quit attempt in the past year. Moderators assessed were occupation-based social grade, housing tenure, urges to smoke, high-risk alcohol consumption, and disability. Adjusted analyses included moderators, socio-demographic (age/sex/ethnicity/sexual orientation/marital status/children in household) and seasonal (quarter/year) confounders. Findings Current smokers who were regularly exposed to other people smoking in their presence were less likely to be highly motivated to quit (OR = 0.88 [95% CI 0.80-0.97]), but were no less likely to have made a quit attempt in the past year (OR 1.04 [0.97-1.13], Bayes Factor (BF) = 0.05). The inverse relationship between regular smoking exposure and motivation to quit was moderated by urges to smoke, such that exposure was only associated with a reduction in motivation among those without strong urges to smoke (OR 0.83 [0.75-0.93] versus OR 1.04 [0.86-1.26]; P = 0.048). None of the other factors significantly moderated the association with motivation to quit, and none moderated the relationship between regular smoking exposure and quit attempts. All non-significant interactions, except social grade (BF = 1.44) with quit attempts, had Bayes Factors that supported the hypothesis of no moderation (BF range: 0.12-0.21). Conclusions Among current smokers in England, regular exposure to other smokers appears to be associated with lower motivation to quit in people without strong urges to smoke, yet there appears to be no association with quit attempts in the previous year. Social grade, housing tenure, high-risk alcohol consumption and disability do not moderate these associations.

Background and aims The National Institute for Health and Care Excellence (NICE) has called for research into tobacco harm reduction across ethnicities, genders and socio-economic status. Although there is increasing research focused on the latter two, relatively few studies have considered ethnic variations. Therefore this study aimed to assess (i) the association between ethnicity and use of e-cigarettes and nicotine replacement therapy (NRT) for temporary abstinence and cutting down, and (ii) trends in prevalence of these over time. Design Repeated cross-sectional household survey. Setting England. Participants Between April 2013 and September 2019, data were collected on 24 114 smokers, 16+ of age, taking part in the Smoking Toolkit Study (STS). Measurements Ethnicity coding included: White, mixed/multiple ethnic group, Asian, Black and Arab/other ethnic group. Smokers reported whether they were currently using e-cigarettes and/or NRT for cutting down or during periods of temporary abstinence. Findings Odds of e-cigarette use for cutting down and temporary abstinence were significantly lower among those of Asian ethnicity (OR = 0.79, 95% CI = 0.66-0.93) and Arab/other ethnicity (OR = 0.58, 95% CI = 0.40-0.83) compared with White ethnicity. Those of mixed/multiple ethnicity had higher odds for NRT us (OR = 1.42, 95% CI = 1.04-1.94) compared with those of White ethnicity. Trend analysis indicated that for White ethnicity, e-cigarette use by smokers for cutting down and temporary abstinence followed an 'inverse S' shaped cubic curve indicating an overall rise, whereas NRT use followed an 'S' shaped cubic curve, indicating an overall decline. For mixed/multiple ethnicity a similar trend was found for NRT use only, with other ethnicities showing no statistically significant trends (suggesting relative stability over time). Conclusions In England, e-cigarette use by smokers for cutting down and temporary abstinence is less common among Asian and Arab/other ethnicity smokers compared with White smokers. Smokers of mixed/multiple ethnicity are the most likely to be using NRT compared with other ethnic groups for cutting down and temporary abstinence. E-cigarette use by smokers for cutting down and temporary abstinence has increased over time among White smokers, whereas prevalence in other ethnic groups has remained stable.

AIMS: To establish the number of smokers in England who would be targeted by increasing the age of sale of cigarettes from 18 to 21 years and to assess the smoking and socio-demographic profile of those smokers. DESIGN AND SETTING: Nationally representative cross-sectional survey of adults in England conducted between January 2009 and July 2019. PARTICIPANTS: A total of 219 720 adults. MEASUREMENTS: All participants reported their current smoking status and socio-demographic characteristics (i.e. age, gender, home ownership, social grade and ethnicity). Smokers reported motivation to quit, urges to smoke and the Heaviness of Smoking Index (HIS). Weighted prevalence statistics were calculated. Multinomial regression and logistic regression were used to assess differences in smoking characteristics among smokers and socio-demographic characteristics relative to non-smokers. FINDINGS: The prevalence of smoking between January 2009 and July 2019 was highest among those aged 21-30. In 2019, 15.6% [95% confidence interval (CI) = 12.8-18.8%] of 18-20-year-olds reported smoking, which is estimated to represent 364 000 individuals in England. Relative to smokers aged 18-20, older smokers (aged 21+) had a higher motivation to quit smoking [odds ratios (ORs) = 1.40-1.45 range] and higher nicotine dependency as measured by urges to smoke (ORs = 1.06-1.24 range) and HSI (ORs = 1.05-2.85 range). Compared with non-smokers aged 18-20, smokers in this age group had lower odds of being female (OR = 0.89) and higher odds of being of white ethnicity (OR = 2.78) and from social grades C1-E (lower social grades) compared with AB (higher social grades) (OR = 1.19-1.83 range). CONCLUSION: Increasing the age of sale of cigarettes to 21 years in England would currently target approximately 364 000 lower dependent smokers from more disadvantaged backgrounds aged 18-20, who have less motivation to quit.

Objective To assess the long-term impact of the increase in age-of-sale of cigarettes from 16 to 18 in England in October 2007. Methods Data were collected between November 2006 and September 2018 on 252,601 participants taking part in a nationally representative survey of adults aged 16+ in England, the Smoking Toolkit Study (STS). We assessed the impact of the introduction of the increase in age-of-sale on prevalence of ever smoking, current smoking, and quit attempts, among 16–17 year olds compared with 18–24 year olds. Results Following the increase in age-of-sale, there was a declining trend in ever smoking that was greater among 16–17 year olds than 18–24 year olds (OR 0.990 versus OR 0.993; p = 0.019). Data on current smoking were insensitive to detect a difference between the age groups in a step-level change or change in trend following the increase in age-of-sale (Bayes factors (BFs) 0.75 and 2.10). Data on quit attempts were also insensitive to detect a change in trend (BF 0.71), and despite a greater step-level decline among those aged 16–17 (OR 0.311 versus OR 0.547, p = 0.025), quit attempts remained higher among those aged 16–17. Secondary analysis indicated that post-policy change, trends in current and ever smoking were linear for 16–17 year olds but quadratic for 18–24 year olds (slowing decline). Conclusion There is some evidence from an assessment of long-term trends in the Smoking Toolkit Study that the increase in legal age-of-sale of cigarettes in England was associated with a greater long-term decline in ever smoking among those aged 16–17 compared with those aged 18–24.

Introduction To gain a better understanding of the complex and independent associations between different measures of socioeconomic position (SEP) and smoking in England. Aims and Methods Between March 2013 and January 2019 data were collected from 120 496 adults aged 16+ in England taking part in the Smoking Toolkit Study. Of these, 18.04% (n = 21 720) were current smokers. Six indicators of SEP were measured: social grade, employment status, educational qualifications, home and car ownership and income. Models were constructed using ridge regression to assess the contribution of each measure of SEP, taking account of high collinearity. Results The strongest predictor of smoking status was housing tenure. Those who did not own their own home had twice the odds of smoking compared with homeowners (odds ratio [OR] = 2.01). Social grade, educational qualification, and income were also good predictors. Those in social grades C1 (OR = 1.04), C2 (OR = 1.29), D (OR = 1.39), and E (OR = 1.78) had higher odds of smoking than those in social grade AB. Similarly, those with A-level/equivalent (OR = 1.15), GCSE/vocational (OR = 1.48), other/still studying (OR = 1.12), and no post-16 qualifications (OR = 1.48) had higher odds of smoking than those with university qualifications, as did those who earned in the lowest (OR = 1.23), third (OR = 1.18), and second quartiles (OR = 1.06) compared with those earning in the highest. Associations between smoking and employment (OR = 1.03) and car ownership (OR = 1.05) were much smaller. Conclusions Of a variety of socioeconomic measures, housing tenure appears to be the strongest independent predictor of smoking in England, followed by social grade, educational qualifications, and income. Employment status and car ownership have the lowest predictive power. Implications This study used ridge regression, a technique which takes into account high collinearity between variables, to gain a better understanding of the independent associations between different measures of SEP and smoking in England. The findings provide guidance as to which SEP measures one could use when trying to identifying individuals most at risk from smoking, with housing tenure identified as the strongest independent predictor.

Introduction E-cigarettes (ECs) may benefit smokers with mental health conditions who are more likely to smoke, and smoke more heavily, than those without mental health conditions. This could be undermined if harm misperceptions in this group are high as is the case in the general population. This study aimed to assess EC harm perceptions relative to cigarettes as a function of mental health status and a variety of characteristics. Methods Data were collected from 6531 current smokers in 2016/2017 in household surveys of representative samples of adults. The associations of mental health status (self-reported mental health condition and past year treatment), smoking and EC use characteristics, and characteristics relating to use of potential information sources with harm perceptions of ECs relative to cigarettes (measured by correct response “less harmful” vs. wrong responses “more harmful,” “equally harmful,” “don’t know”) were analyzed with logistic regression. Results A similar proportion of smokers without mental health conditions (61.5%, 95% CI 60.1–62.9) and with mental health conditions (both with [61.3%, 95% confidence interval [CI] 58.7–63.8] and without past year treatment [61.5%, 95% CI 58.1–64.7]) held inaccurate EC harm perceptions (all P > 0.05). Being female, nonwhite, aged 25–34 compared with 16–24, from lower social grades (C2, D, and E), not having post-16 qualifications, no EC experience, a daily smoker, unmotivated to quit Conclusions The majority of smokers in England have inaccurate harm perceptions of ECs regardless of mental health status. Implications This study is the first to use a nationally representative sample in order to investigate whether smokers with and without mental health conditions differ with regard to harm perceptions of ECs. Findings show that the majority of smokers in England hold inaccurate harm perceptions of ECs, and this does not differ as a function of mental health status. A number of characteristics associated with disadvantaged groups were significantly associated with inaccurate harm perceptions. These findings highlight the need to improve awareness and understanding among disadvantaged groups regarding the relative harms of ECs compared with tobacco.

Background: It is unclear whether smoking increases the risk of COVID-19 hospitalisation. We first examined the association of smoking status with hospitalisation for COVID-19 compared with hospitalisation for other respiratory viral infections a year previous. Second, we examined the concordance between smoking status recorded on the electronic health record (EHR) and the contemporaneous medical notes. Methods: This case-control study enrolled adult patients (446 cases and 211 controls) at a single National Health Service trust in London, UK. The outcome variable was type of hospitalisation (COVID-19 vs. another respiratory virus a year previous). The exposure variable was smoking status (never/former/current smoker). Logistic regression analyses adjusted for age, sex, socioeconomic position and comorbidities were performed. The study protocol and analyses were pre-registered in April 2020 on the Open Science Framework. Results: Current smokers had lower odds of being hospitalised with COVID-19 compared with other respiratory viruses a year previous (ORadj=0.55, 95% CI=0.31-0.96, p=.04). There was no significant association among former smokers (ORadj=1.08, 95% CI=0.72-1.65, p=.70). Smoking status recorded on the EHR (compared with the contemporaneous medical notes) was incorrectly recorded for 168 (79.6%) controls (χ2(3)=256.5, p=2(3)=34.2, p= Conclusions: In a single UK hospital trust, current smokers had reduced odds of being hospitalised with COVID-19 compared with other respiratory viruses a year previous, although it is unclear whether this association is causal. Targeted post-discharge recording of smoking status may account for the greater EHR-medical notes concordance observed in cases compared with controls.

Background Heated tobacco products (HTPs) are designed to heat tobacco to a high enough temperature to release aerosol, without burning it or producing smoke. They differ from e‐cigarettes because they heat tobacco leaf/sheet rather than a liquid. Companies who make HTPs claim they produce fewer harmful chemicals than conventional cigarettes. Some people report stopping smoking cigarettes entirely by switching to using HTPs, so clinicians need to know whether they are effective for this purpose and relatively safe. Also, to regulate HTPs appropriately, policymakers should understand their impact on health and on cigarette smoking prevalence. Objectives To evaluate the effectiveness and safety of HTPs for smoking cessation and the impact of HTPs on smoking prevalence. Search methods We searched the Cochrane Tobacco Addiction Group's Specialised Register, CENTRAL, MEDLINE, and six other databases for relevant records to January 2021, together with reference‐checking and contact with study authors and relevant groups. Selection criteria We included randomised controlled trials (RCTs) in which people who smoked cigarettes were randomised to switch to exclusive HTP use or a control condition. Eligible outcomes were smoking cessation, adverse events, and selected biomarkers. RCTs conducted in clinic or in an ambulatory setting were deemed eligible when assessing safety, including those randomising participants to exclusively use HTPs, smoke cigarettes, or attempt abstinence from all tobacco. Time‐series studies were also eligible for inclusion if they examined the population‐level impact of heated tobacco on smoking prevalence or cigarette sales as an indirect measure. Data collection and analysis We followed standard Cochrane methods for screening and data extraction. Our primary outcome measures were abstinence from smoking at the longest follow‐up point available, adverse events, serious adverse events, and changes in smoking prevalence or cigarette sales. Other outcomes included biomarkers of harm and exposure to toxicants/carcinogens (e.g. NNAL and carboxyhaemoglobin (COHb)). We used a random‐effects Mantel‐Haenszel model to calculate risk ratios (RR) with 95% confidence intervals (CIs) for dichotomous outcomes. For continuous outcomes, we calculated mean differences on the log‐transformed scale (LMD) with 95% CIs. We pooled data across studies using meta‐analysis where possible. Main results We included 13 completed studies, of which 11 were RCTs assessing safety (2666 participants) and two were time‐series studies. We judged eight RCTs to be at unclear risk of bias and three at high risk. All RCTs were funded by tobacco companies. Median length of follow‐up was 13 weeks. No studies reported smoking cessation outcomes. There was insufficient evidence for a difference in risk of adverse events between smokers randomised to switch to heated tobacco or continue smoking cigarettes, limited by imprecision and risk of bias (RR 1.03, 95% CI 0.92 to 1.15; I2 = 0%; 6 studies, 1713 participants). There was insufficient evidence to determine whether risk of serious adverse events differed between groups due to very serious imprecision and risk of bias (RR 0.79, 95% CI 0.33 to 1.94; I2 = 0%; 4 studies, 1472 participants). There was moderate‐certainty evidence for lower NNAL and COHb at follow‐up in heated tobacco than cigarette smoking groups, limited by risk of bias (NNAL: LMD −0.81, 95% CI −1.07 to −0.55; I2 = 92%; 10 studies, 1959 participants; COHb: LMD −0.74, 95% CI −0.92 to −0.52; I2 = 96%; 9 studies, 1807 participants). Evidence for additional biomarkers of exposure are reported in the main body of the review. There was insufficient evidence for a difference in risk of adverse events in smokers randomised to switch to heated tobacco or attempt abstinence from all tobacco, limited by risk of bias and imprecision (RR 1.12, 95% CI 0.86 to 1.46; I2 = 0%; 2 studies, 237 participants). Five studies reported that no serious adverse events occurred in either group (533 participants). There was moderate‐certainty evidence, limited by risk of bias, that urine concentrations of NNAL at follow‐up were higher in the heated tobacco use compared with abstinence group (LMD 0.50, 95% CI 0.34 to 0.66; I2 = 0%; 5 studies, 382 participants). In addition, there was very low‐certainty evidence, limited by risk of bias, inconsistency, and imprecision, for higher COHb in the heated tobacco use compared with abstinence group for intention‐to‐treat analyses (LMD 0.69, 95% CI 0.07 to 1.31; 3 studies, 212 participants), but lower COHb in per‐protocol analyses (LMD −0.32, 95% CI −1.04 to 0.39; 2 studies, 170 participants). Evidence concerning additional biomarkers is reported in the main body of the review. Data from two time‐series studies showed that the rate of decline in cigarette sales accelerated following the introduction of heated tobacco to market in Japan. This evidence was of very low‐certainty as there was risk of bias, including possible confounding, and cigarette sales are an indirect measure of smoking prevalence. Authors' conclusions No studies reported on cigarette smoking cessation, so the effectiveness of heated tobacco for this purpose remains uncertain. There was insufficient evidence for differences in risk of adverse or serious adverse events between people randomised to switch to heated tobacco, smoke cigarettes, or attempt tobacco abstinence in the short‐term. There was moderate‐certainty evidence that heated tobacco users have lower exposure to toxicants/carcinogens than cigarette smokers and very low‐ to moderate‐certainty evidence of higher exposure than those attempting abstinence from all tobacco. Independently funded research on the effectiveness and safety of HTPs is needed. The rate of decline in cigarette sales accelerated after the introduction of heated tobacco to market in Japan but, as data were observational, it is possible other factors caused these changes. Moreover, falls in cigarette sales may not translate to declining smoking prevalence, and changes in Japan may not generalise elsewhere. To clarify the impact of rising heated tobacco use on smoking prevalence, there is a need for time‐series studies that examine this association., Plain language summary Do heated tobacco products help people to quit smoking, are they safe for this purpose, and have they led to falls in smoking rates? Key messages Heated tobacco probably exposes people to fewer toxins than cigarettes, but possibly more than not using any tobacco. Falls in cigarette sales appeared to speed up following the launch of heated tobacco in Japan, but we are uncertain whether this is caused by people switching from cigarettes to heated tobacco. We need more independently funded research into whether heated tobacco helps people stop smoking, whether it results in unwanted effects, and the impact of rising heated tobacco use on smoking rates. What are heated tobacco products? Heated tobacco products are designed to heat tobacco to a high enough temperature to release vapour, without burning it or producing smoke. They differ from e‐cigarettes because they heat tobacco leaf/sheet rather than a liquid. Many of the harmful chemicals in cigarette smoke are created by burning tobacco. So heating not burning tobacco could reduce the amount of chemicals a user ingests. Some people report stopping smoking cigarettes entirely by switching to using heated tobacco. Why we did this Cochrane Review Because cigarette smoking is addictive, many people find it difficult to stop despite the harm it causes. We aimed to find out whether trying to switch to heated tobacco helps people stop smoking cigarettes, and whether it results in unwanted effects. We also wanted to find out whether rising heated tobacco use has affected smoking rates or cigarette sales. What did we do? We looked for studies that reported on the use of heated tobacco for stopping smoking, and on unwanted effects and toxin exposure in people asked to use heated tobacco. Here we only included randomised controlled trials, where treatments were given to people at random. This type of study is considered the most reliable way of determining if a treatment works. Finally, we searched for studies looking at changes in smoking rates and cigarette sales following the launch of heated tobacco to market. We included studies published up to January 2021. What we found Our search found 13 relevant studies. No studies reported whether heated tobacco helps people stop smoking cigarettes. Eleven trials, all funded by tobacco companies and with 2666 adult smokers, compared unwanted effects and toxin levels in people randomly assigned to use heated tobacco or to continue smoking cigarettes or abstain from tobacco use. Two studies looked at how trends in cigarette sales changed following the launch of heated tobacco in Japan. What are the results of our review? We do not know whether using heated tobacco helps people to stop smoking cigarettes (no studies measured this). We are uncertain whether the chances of getting unwanted symptoms from being asked to use heated tobacco are different compared with cigarettes (6 studies, 1713 participants) or no tobacco (2 studies, 237 participants). Serious unwanted symptoms in the short time period studied (average 13 weeks) were rare in all groups, which means we are uncertain about any differences. Toxin levels were probably lower in people using heated tobacco than those smoking cigarettes (10 studies, 1959 participants), but may be higher than in people not using any tobacco products (5 studies, 382 participants). The launch of heated tobacco products in Japan may have caused the decline in cigarette sales to speed up over time (two studies), but it is unclear whether the fall in the percentage of people who smoke also sped up because no studies looked at this. How reliable are these results? Results are based on data from a small number of studies, most of which were funded by tobacco companies. Results on unwanted effects are likely to change as more evidence becomes available. However, we are moderately confident that levels of measured toxins are lower in people using heated tobacco than smoking cigarettes, but less confident that levels were higher than in people not using any tobacco. We are also less confident that the launch of heated tobacco caused the fall in cigarette sales to speed up, as results came from a single country.

This study investigated UK adults’ changes in cigarette smoking and vaping during the COVID-19 pandemic and factors associated with any changes. Data were from an online longitudinal study. A self-selected sample (n = 332) of 228 smokers and 155 vapers (51 participants were both smokers and vapers) completed 5 surveys between April 2020 and June 2021. Participants self-reported data on sociodemographics, COVID-19-related, and smoking/vaping characteristics. During the 12 months of observations, among smokers, 45% self-reported a quit attempt (27.5% due to COVID-19-related reasons) since the onset of COVID-19 pandemic and the quit rate was 17.5%. At 12 months, 35.1% of continuing smokers (n = 174) reported smoking less and 37.9% the same, while 27.0% reported an increase in the number of cigarettes smoked/day. Among vapers, 25.0% self-reported a quit attempt (16.1% due to COVID-19-related reasons) and the quit rate was 18.1%. At 12 months, 47.7% of continuing vapers (n = 109) reported no change in the frequency of vaping/hour, while a similar proportion reported vaping less (27.5%) and more (24.8%). Motivation to quit smoking and being younger were associated with making a smoking quit attempt and smoking cessation. Being a cigarette smoker was associated with vaping cessation. Among a self-selected sample, COVID-19 stimulated more interest in reducing or quitting cigarette smoking than vaping.

This study aimed to evaluate the impact of announcement of tax increases on factory-made (FM) and roll-your own (RYO) cigarettes in England.Autoregressive integrated moving average with exogeneous input (ARIMAX) time-series modelling in England, UK. Data were aggregated monthly on 274 890 participants between 2007 and 2019 taking part in the Smoking Toolkit Study (STS).The association of sustained step level changes for tax rises for FM cigarettes and temporary pulse effects for tax rises for RYO cigarettes with smoking, quit attempt and quit success prevalence as well as per-capita self-reported cigarette consumption and cost per cigarette was assessed.A 10% rise in tax on RYO cigarettes was associated with a temporary 21.1% decline [95% confidence interval (CI) = -30.4 to -10.7] in smoking prevalence, and 20.7% decline (95% CI = -32.4 to -7.0) in per-capita self-reported cigarette consumption; while a 3% rise of tax on RYO cigarettes was associated with a temporary 20.7% decline (95% CI = -33.3 to -5.8) in the amount paid per RYO cigarette. For tax increases on FM cigarettes, a 5% above inflation tax rise was associated with a step-level increase of 33.1% (95% CI = 18.4-49.5) in quit success rates. However, some of the findings were sensitive to model specification and temporally specific.The announcements of tax increases for cigarettes in England between 2010 and 2019 were inconsistently associated with temporary reductions in smoking prevalence, per-capita self-reported cigarette consumption and improved quit success. Paradoxically, reductions in the cost for roll-your-own cigarettes were also found. The results were not robust in all sensitivity analyses.

To assess how changes in the prevalence of e-cigarette use among young adults have been associated with changes in the uptake of smoking in England between 2007 and 2018.Time-series analysis of population trends with autoregressive integrated moving average with exogeneous input (ARIMAX models).England.Data were aggregated quarterly on young adults aged 16-24 years (n = 37 105) taking part in the Smoking Toolkit Study.In the primary analysis, prevalence of e-cigarette use was used to predict prevalence of ever regular smoking among those aged 16-24. Sensitivity analyses stratified the sample into those aged 16-17 and 18-24. Bayes' factors and robustness regions were calculated for non-significant findings [effect size beta coefficient (B) = 3.1].There was evidence for no association between the prevalence of e-cigarette use and ever regular smoking among those aged 16-24 [B = -0.015, 95% confidence interval (CI) = -0.046 to 0.016; P = 0.341; Bayes factor (BF) = 0.002]. Evidence for no association was also found in the stratified analysis among those aged 16-17 (B = 0.070, 95% CI -0.014 to 0.155, P = 0.102; BF = 0.015) and 18-24 (B = -0.021, 95% CI -0.053 to 0.011; P = 0.205; BF = 0.003). These findings were able to rule out percentage point increases or decreases in ever regular smoking prevalence greater than 0.31% or less than -0.03% for 16-17-year-olds and 0.01 or -0.08% for 18-24-year-olds for every 1%-point increase in e-cigarette prevalence.Prevalence of e-cigarette use among the youth population in England does not appear to be associated with substantial increases or decreases in the prevalence of smoking uptake. Small associations cannot be ruled out.

To measure whether the prevalence of use and real-world effectiveness of different smoking cessation aids has changed in England since the coronavirus disease 2019 (COVID-19) pandemic.Representative monthly cross-sectional surveys, January 2015-June 2021.England.A total of 7300 adults (≥18 y) who had smoked within the previous 12 months and had made ≥1 quit attempt during that period.The independent variable was the timing of the COVID-19 pandemic (pre-pandemic [January 2015-February 2020] vs pandemic [April 2020-June 2021]). We analysed (i) the association between the pandemic period and self-reported use (vs non-use) during the most recent quit attempt of: prescription medication (nicotine replacement therapy [NRT]/varenicline/bupropion), NRT bought over-the-counter, e-cigarettes, traditional behavioural support and traditional remote support (telephone support/written self-help materials/websites) and (ii) the interaction between the pandemic period and use of these cessation aids on self-reported abstinence from quit date to survey. Covariates included age, sex, social grade, level of cigarette addiction and characteristics related to the quit attempt.After adjustment for secular trends, there was a significant increase from the pre-pandemic to pandemic period in the prevalence of use of traditional remote support by past-year smokers in a quit attempt (OR = 2.18; 95% CI, 1.42-3.33); specifically telephone support (OR = 7.16; 95% CI, 2.19-23.45) and websites (OR = 2.39; 95% CI, 1.41-4.08). There was also an increase in the prevalence of use of prescription medication (OR = 1.47; 95% CI, 1.08-2.00); specifically varenicline (OR = 1.66; 95% CI, 1.09-2.52). There were no significant changes in prevalence of use of other cessation aids after adjustment for secular trends. People who reported using prescription medication (OR = 1.41; 95% CI, 1.09-1.84) and e-cigarettes (OR = 1.87; 95% CI, 1.62-2.16) had greater odds of reporting abstinence than people who did not. There were no significant interactions between the pandemic period and use of any cessation aid on abstinence, after adjustment for covariates and use of the other aids, although data were insensitive to distinguish no change from meaningful modest (OR = 1.34) effects (Bayes factors 0.72-1.98).In England, the COVID-19 pandemic was associated with an increase in use of remote support for smoking cessation and varenicline by smokers in a quit attempt up to June 2021. The data were inconclusive regarding an association between the pandemic and changes in the real-world effectiveness of popular smoking cessation aids.

Background To help implement behavior change interventions (BCIs) it is important to be able to characterize their key components and determine their effectiveness. Purpose This study assessed and compared the components of BCIs in terms of intervention functions identified using the Behaviour Change Wheel Framework (BCW) and in terms of their specific behavior change techniques (BCTs) identified using the BCT TaxonomyV1, across six behavioral domains and the association of these with cost-effectiveness. Methods BCIs in 251 studies targeting smoking, diet, exercise, sexual health, alcohol and multiple health behaviors, were specified in terms of their intervention functions and their BCTs, grouped into 16 categories. Associations with cost-effectiveness measured in terms of incremental cost-effectiveness ratio (ICER) upper and lower estimates were determined using regression analysis. Results The most prevalent functions were increasing knowledge through education (72.1%) and imparting skills through training (74.9%). The most prevalent BCT groupings were shaping knowledge (86.5%), changing behavioral antecedents (53.0%), supporting self-regulation (47.7%), and providing social support (44.6%). Intervention functions associated with better cost-effectiveness were those based on training (βlow = −15044.3; p = .002), persuasion (βlow = −19384.9; p = .001; βupp = −25947.6; p < .001) and restriction (βupp = −32286.1; p = .019), and with lower cost-effectiveness were those based on environmental restructuring (β = 15023.9low; p = .033). BCT groupings associated with better cost-effectiveness were goals and planning (βlow = −8537.3; p = .019 and βupp = −12416.9; p = .037) and comparison of behavior (βlow = −13561.9, p = .047 and βupp = −30650.2; p = .006). Those associated with lower cost-effectiveness were natural consequences (βlow = 7729.4; p = .033) and reward and threat (βlow = 20106.7; p = .004). Conclusions BCIs that focused on training, persuasion and restriction may be more cost-effective, as may those that encourage goal setting and comparison of behaviors with others.

Smoking prevalence in several high-income countries is steadily declining but remains persistently high in ‘lower’ socioeconomic position (SEP) groups, contributing to inequities in morbidity and mortality. Smoking to relieve stress is a commonly endorsed motive for continued smoking; however, it remains unclear whether smoking to relieve stress has a negative impact on motivation to stop and future quit attempts and if so, whether associations are moderated by SEP. This was an observational study with cross-sectional and prospective survey data from the nationally representative Smoking Toolkit Study in England. A total of 1,135 adult smokers were surveyed at baseline, with 153 (13.5%) respondents followed up at 12 months. Respondents provided information on demographic, social and smoking characteristics. A series of multivariable logistic regression analyses was conducted. Bayes Factors (BFs) were calculated to explore non-significant associations. Smoking to relieve stress was commonly endorsed by respondents from both ‘lower’ (43.2% [95% CI = 39.4%, 47.0%]) and ‘higher’ (40.5% [95% CI = 35.9%, 45.1%]) SEP groups (p = 0.39). Smoking to relieve stress was associated with high motivation to stop at baseline (ORadj = 1.48, 95% CI = 1.03–2.12, p = 0.035) but not significantly with the odds of making a quit attempt at a 12-month follow-up, although the magnitude and direction of the effect was similar to that observed for high motivation to stop (ORadj = 1.49, 95% CI = 0.69–3.20, p = 0.3). Data were insensitive to detect moderation effects of SEP (BF = 0.90 and BF = 1.65, respectively). Smoking to relieve stress is a commonly endorsed motive and is associated with high motivation to stop but not significantly with the odds of making a quit attempt in the next 12 months, although the magnitude and direction of the effect was similar for both outcomes. There was no clear evidence of moderation by SEP, although data were insensitive to distinguish the alternative from the null hypothesis.

Background/Aims: The expense associated with using non-combustible nicotine products as an alternative to smoking may deter smoking reduction or cessation. This study aimed to estimate (i) how much adults in England spend each week on smoking and alternative nicotine products and (ii) the potential cost saving that could be achieved by switching from smoking to using an alternative nicotine delivery product. // Design/Setting: Data came from September to November 2018 waves of the Smoking Toolkit Study, a series of national household surveys of the adult population in England. // Participants: A total of 859 adults (≥16 years) who reported current smoking or current use of an alternative nicotine product. // Measurements: Participants reported their average weekly expenditure on smoking and alternative nicotine products (nicotine replacement therapy (NRT) or e-cigarettes). // Findings: Current smokers who did not use any alternative nicotine delivery products (n=602) reported spending on average £23.09 (95%CI £21.64-24.54) on smoking each week. Ex-smokers who used alternative nicotine products (n=91) reported spending on average £8.59 (95% CI £6.80-10.39) on these products each week; £8.03 (95%CI £6.03-10.03) on e-cigarettes and £10.05 (95%CI £5.62-14.47) on NRT. People who both smoked and used alternative nicotine products (dual users, n=166) spent on average £24.54 (95%CI £21.78- 27.29) on smoking and £7.49 (95%CI £6.00-8.99) on alternative nicotine products each week. Expenditure on smoking was higher among heavier, more addicted smokers and lower among those with routine/manual occupations, non-daily smokers, and roll-your-own tobacco users. Expenditure on ecigarettes was higher among men, users from central and southern vs. northern England, and smokers who had tried to quit in the past year, and lower among current smokers. Expenditure on NRT was lower among roll-your-own tobacco users. // Conclusions: In England, expenditure among e-cigarette and nicotine replacement therapy (NRT) users is approximately one third of the expenditure of smokers. The average smoker may save an estimated £15 per week by switching completely to e-cigarettes or £13 per week by switching to NRT, although this is likely to differ according to individual usage patterns.

Introduction Up-to-date monitoring of non-combustible nicotine products (e.g. e-cigarettes, nicotine replacement therapies (NRT), heated tobacco products (HTP); NNP) is important to assess their impact. To date, there is little evidence on the association between ever regular use (defined here as 1 year or more) of NNP and current smoking status. Aims/methods The purpose of this study was to examine the prevalence, and sociodemographic, alcohol and smoking status correlates, of ever regular use of NNP in England in 2020. A cross-sectional survey of adults in England was conducted between February and June 2020. Results A total of 8486 adults were surveyed; 94.9% (8055) were complete cases. The weighted prevalence of ever regular NNP use was 5.4% (n = 436; 95% CI 5.0–6.0), of which 82% (n = 360; 95% CI 78.7–85.8) was single and 18% (n = 79; 95% CI 14.8–22) multiple product use. Amongst ever regular NNP users, the prevalence of ever regular NRT, e-cigarette and HTP use was 64.7% (95% CI 60.1–69), 43.4% (95% CI 38.8–48) and 2.5% (95% CI 1.4–4.5), respectively. In adjusted analysis, ever regular NNP use was associated with smoking status, being significantly higher among current (22.3%; adjusted OR (aOR) 34.9, 95% CI 24.0–50.8) and ex-smokers (12.7%, aOR 19.8, 95% CI 11.1–14.4) than among never-smokers (0.6%). More advantaged occupational grade (aOR, 1.27 95% CI 1.02–1.57) and at least hazardous alcohol use (aOR, 1.38 95% CI 1.06–1.78) were associated with greater prevalence of ever regular NNP use. Conclusions Ever regularly using NNP was highest among smokers and ex-smokers and rare among never-smokers. Among people who have ever regularly used NNP, NRT is the most popular.

Objectives Delivery of craving management tools via smartphone applications (apps) may improve smoking cessation rates, but research on such programmes remains limited, especially in real-world settings. This study evaluated the effectiveness of adding craving management tools in a cessation app (BupaQuit). Methods The study was a two-arm pragmatic pilot parallel randomised controlled trial, comparing a fully-automated BupaQuit app with craving management tool with a control app version without craving management tool. A total of 425 adult UK-based daily smokers were enrolled through open online recruitment (February 2015–March 2016), with no researcher involvement, and individually randomised within the app to the intervention ( n = 208) or control ( n = 217). The primary outcome was self-reported 14-day continuous abstinence assessed at 4-week follow-up. Secondary outcomes included 6-month point-prevalence and sustained abstinence, and app usage. The primary outcome was assessed with Fisher's exact test using intent to treat with those lost to follow-up counted as smoking. Participants were not reimbursed. Results Re-contact rates were 50.4% at 4 weeks and 40.2% at 6 months. There was no significant difference between intervention and control arms on the primary outcome (13.5% vs 15.7%; p = 0.58; relative risk = 0.86, 95% confidence interval = 0.54–1.36) or secondary cessation outcomes (6-month point prevalence: 14.4% vs 17.1%, p = 0.51; relative risk = 0.85, 95% confidence interval = 0.54–1.32; 6-month sustained: 11.1% vs 13.4%, p = 0.55; relative risk = 0.83, 95% confidence interval = 0.50–1.38). Bayes factors supported the null hypothesis ( B[0, 0, 1.0986] = 0.20). Usage was similar across the conditions (mean/median logins: 9.6/4 vs 10.5/5; time spent: 401.8/202 s vs 325.8/209 s). Conclusions The addition of craving management tools did not affect cessation, and the limited engagement with the app may have contributed to this.

AIM: To examine changes in smoking, drinking and quitting/reduction behaviour following the COVID-19 lockdown in England. DESIGN/SETTING: Monthly cross-sectional surveys representative of the adult population in England, aggregated before (April 2019-February 2020) versus after (April 2020) lockdown. PARTICIPANTS: A total of 20 558 adults (≥ 16 years). MEASUREMENTS: The independent variable was the timing of the COVID-19 lockdown (before versus after March 2020). Dependent variables were: prevalence of smoking and high-risk drinking, past-year cessation and quit attempts (among past-year smokers), past-year attempts to reduce alcohol consumption (among high-risk drinkers) and use of evidence-based (e.g. prescription medication/face-to-face behavioural support) and remote support [telephone support/websites/applications (apps)] for smoking cessation and alcohol reduction (among smokers/high-risk drinkers who made a quit/reduction attempt). Covariates included age, sex, social grade, region and level of nicotine and alcohol dependence (as relevant). FINDINGS: The COVID-19 lockdown was not associated with a significant change in smoking prevalence [17.0% (after) versus 15.9% (before), odds ratio (OR) = 1.09, 95% CI = 0.95-1.24], but was associated with increases in quit attempts [39.6 versus 29.1%, adjusted odds ratio (ORadj ) = 1.56, 95% CI = 1.23-1.98], quit success (21.3 versus 13.9%, ORadj = 2.01, 95% CI = 1.22-3.33) and cessation (8.8 versus 4.1%, ORadj = 2.63, 95% CI = 1.69-4.09) among past-year smokers. Among smokers who tried to quit, there was no significant change in use of evidence-based support (50.0 versus 51.5%, ORadj = 1.10, 95% CI = 0.72-1.68) but use of remote support increased (10.9 versus 2.7%, ORadj = 3.59, 95% CI = 1.56-8.23). Lockdown was associated with increases in high-risk drinking (38.3 versus 25.1%, OR = 1.85, CI = 1.67-2.06), but also alcohol reduction attempts by high-risk drinkers (28.5 versus 15.3%, ORadj = 2.16, 95% CI = 1.77-2.64). Among high-risk drinkers who made a reduction attempt, use of evidence-based support decreased (1.2 versus 4.0%, ORadj = 0.23, 95% CI = 0.05-0.97) and there was no significant change in use of remote support (6.9 versus 6.1%, ORadj = 1.32, 95% CI = 0.64-2.75). CONCLUSIONS: Following the March 2020 COVID-19 lockdown, smokers and high-risk drinkers in England were more likely than before lockdown to report trying to quit smoking or reduce alcohol consumption and rates of smoking cessation and use of remote cessation support were higher. However, high-risk drinking prevalence increased post-lockdown and use of evidence-based support for alcohol reduction by high-risk drinkers decreased with no compensatory increase in use of remote support.

Highlights • Mental health of the general population has deteriorated since the onset of the COVID-19 pandemic. • Smoking is strongly associated with poor mental health. • Deterioration in mental health among smokers may exacerbate health inequalities. • There were increases in psychological distress in smokers between 2016/17 and 2020., Changes in the prevalence of psychological distress among smokers during the COVID-19 pandemic in England may exacerbate existing health inequalities. This study examined the prevalence of psychological distress among smokers following the onset of the pandemic compared with previous years. Cross-sectional data came from a representative survey of smokers (18+) in England (n = 2,927) between April–July in 2016, 2017 and 2020. Logistic regressions estimated the associations between past-month distress across 2016/2017 and 2020, and age. Weighted proportions, chi-squared statistics and stratified logistic regression models were used to compare the distributions of moderate and severe distress, respectively, within socio-demographic and smoking characteristics in 2016/2017 and 2020. Between the combined April–July 2016 and 2017 sample and April–July 2020 the prevalence of moderate and severe distress among past-year smokers increased (2016/2017: moderate 20.66%, 19.02–22.43; severe 8.23%, 7.16–9.47; 2020: moderate 28.79%, 95%CI 26.11–31.60; OR = 2.08, 95%CI 1.34–3.25; severe 11.04%, 9.30–13.12; OR = 2.16, 1.13–4.07). While there was no overall evidence of an interaction between time period and age, young (16–24 years) and middle-age groups (45–54 years) may have experienced greater increases in moderate distress and older age groups (65+ years) increases in severe distress. There were increases of moderate distress among more disadvantaged social grades and both moderate and severe distress among women and those with low cigarette addiction. Between April–July 2016/2017 and April–July 2020 in England there were increases in both moderate and severe distress among smokers. The distribution of distress among smokers differed between 2016/2017 and 2020 and represents a widening of inequalities.

AimsTo explore 1) associations between suspected SARS-CoV-2 infection, hand washing, smoking status, e-cigarette use, and nicotine replacement therapy (NRT) use and 2) whether COVID-19 has prompted smoking and vaping quit attempts, and more smoking inside the home.DesignCross-sectional household surveys of a representative sample of the population in England from April–May 2020.ParticipantsThe sample included 3,285 adults aged ≥18 years.MeasurementsParticipants who reported they definitely or think they had coronavirus were classified as having a suspected SARS-CoV-2 infection. Participants were asked how often they wash their hands after returning home, before eating, before preparing foods or before touching their face. They were also asked whether, due to COVID-19, they had i) attempted to quit smoking, ii) attempted to quit vaping, and iii) changed the amount they smoke inside the home.FindingsOdds of suspected SARS-CoV-2 infection were significantly greater among current smokers (20.9%, adjusted odds ratio [ORadj]=1.34, 95% confidence interval [CI]=1.04–1.73) and long-term (>1-year) ex-smokers (16.1%, ORadj=1.33, 95%CI=1.05–1.68) than never smokers (14.5%). Recent (adj=1.50, 95%CI=0.85–2.53, Bayes factor= 0.55–1.17). Bayes factors indicated there was sufficient evidence to rule out large differences in suspected SARS-CoV-2 infection by NRT use and medium differences by e-cigarette use. With the exception of hand washing before face touching, engagement in hand washing behaviours was high (>85%) regardless of nicotine use. A minority (12.2%) of past-year smokers who made a quit attempt in the past three months were triggered by COVID-19, and approximately one-in-ten current e-cigarette users reported attempting to quit vaping because of COVID-19. Most people reported smoking the same amount inside the home.ConclusionsIn a representative sample of the adult population in England, current smokers and long-term ex-smokers had higher odds of suspected SARS-CoV-2 infection than never smokers, but there were no large differences by NRT or e-cigarette use. In general, engagement in hand washing was high regardless of nicotine or tobacco use. A minority of past-year smokers and current e-cigarette users, respectively, attempted to quit smoking/vaping due to COVID-19.

Background The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak may motivate smokers to attempt to stop in greater numbers. However, given the temporary closure of UK stop smoking services and vape shops, smokers attempting to quit may instead seek out mobile health support, such as smartphone apps. Objective We examined, using an interrupted time series approach, whether the SARS-CoV-2 outbreak has been associated with a step change or increasing trend in UK downloads of an otherwise popular smoking cessation app, Smoke Free. Methods Data were from daily and nondaily adult smokers in the United Kingdom who had downloaded the Smoke Free app between January 1, 2020, and March 31, 2020 (primary analysis), and January 1, 2019, and March 31, 2020 (secondary analysis). The outcome variable was the number of downloads aggregated at the 12-hourly (primary analysis) or daily level (secondary analysis). The explanatory variable was the start of the SARS-CoV-2 outbreak, operationalized as March 1, 2020 (primary analysis), and January 15, 2020 (secondary analysis). Generalized additive mixed models adjusted for relevant covariates were fitted. Results Data were collected on 45,105 (primary analysis) and 119,881 (secondary analysis) users. In both analyses, there was no evidence for a step change or increasing trend in downloads attributable to the start of the SARS-CoV-2 outbreak. Calculation of Bayes factors (BFs) indicated that the data for the primary analysis favored the null hypothesis compared with large associations (for level, BF=0.25; for slope, BF=0.26) but were insensitive to the detection of small associations (for level, BF=0.78; for slope, BF=1.35). Conclusions In the United Kingdom, between January 1, 2020, and March 31, 2020, and between January 1, 2019, and March 31, 2020, there was no evidence that the SARS-CoV-2 outbreak has been associated with a large step change or increasing trend in downloads of a popular smoking cessation app. Findings on the association of the SARS-CoV-2 outbreak with a small step change or increasing trend were inconclusive.

Purpose Nicotine replacement therapy (NRT) is often used suboptimally by smokers. Previous research has focused on cognitions and attitudes as potential reasons. This study drew on theoretical frameworks of behaviour to comprehensively explore smokers’ NRT use to identify new intervention targets. Methods Semi-structured face-to-face interviews were conducted with 16 adult UK-based smokers and ex-smokers who used NRT in recent quit attempts (mean (SD) age = 34.9(10.3); 82.3% women). The COM-B (capability, opportunity, motivation, behaviour) model and the theoretical domains framework informed the interviews and analyses. Data were analysed in NVivo 11. Results Two related behaviours were identified relevant to NRT use: use of NRT per se and engaging with information and support with NRT use. A meta-theme of “missed opportunity” identified instances when smokers did not or could not engage in these behaviours. For use of NRT per se, these included limited knowledge, poor technique of use, low motivation to optimise use, and lack of role models. For engaging with information and support, they included low awareness of optimal use techniques, selective information-seeking, low expectations, limited exposure to guidelines, deficient advice from healthcare professionals, and suboptimal product display. Prior suboptimal experience tended to negatively affect subsequent use and views. Participants were interested in accessible and comprehensive guidelines on NRT and its use. Conclusions There appear to be important missed opportunities for optimal use of NRT both in terms of use itself and engagement with information on optimal use. These missed opportunities arise from a range of capability, motivational, and opportunity-related factors. Electronic supplementary material The online version of this article (10.1007/s12529-018-9735-y) contains supplementary material, which is available to authorized users.

ObjectivesTo examine the prevalence of, and sociodemographic and smoking-related characteristics associated with, long-term e-cigarette use compared with long-term nicotine replacement therapy (NRT) use.DesignCross-sectional and prospective survey, the Smoking Toolkit Study, with baseline data collected between September 2014 and September 2016 and follow-ups at 6 and 12 months.SettingEngland.ParticipantsPopulation representative sample of 40 933 adults aged 16+ years.Main outcome measuresPrevalence of long-term (≥12 months) use of e-cigarettes and NRT by retrospective self-report among baseline respondents (all adults, n=40 933; smokers, n=8406) and current use at baseline, 6 months and 12 months in a subsample of smokers who responded to follow-up (n=733).ResultsOf baseline respondents, 1.5% (95% CI 1.4% to 1.6%, n=604) of adults and 3.9% (95% CI 3.5% to 4.3%, n=327) of smokers were long-term e-cigarette users and 0.5% (95% CI 0.4% to 0.6%, n=205) of adults and 1.3% (95% CI 1.1% to 1.5%, n=112) of smokers were long-term NRT users. Assessed prospectively, 13.4% (95% CI 10.9% to 15.9%, n=100) of smokers were long-term e-cigarette users and 1.9% (95% CI 0.9% to 2.9%, n=14) were long-term NRT users. Among all adults, long-term use by never smokers of either e-cigarettes (0.1%, n=27) or NRT (0.0%, n=7) was rare. Among past-year smokers, long-term e-cigarette and NRT use was higher among older smokers compared with those who were 16–34 years old (OR range=1.55–5.21). Long-term e-cigarette use only was lower in smokers who were less educated (OR=0.63, 95% CI 0.49 to 0.81), from social grades C2DE (OR=0.66, 95% CI 0.52 to 0.84) and with children in the household (OR=0.66, 95% CI 0.51 to 0.85). Long-term e-cigarette use and long-term NRT use were higher among smokers more motivated to quit (OR=2.05, 95% CI 1.63 to 2.60 and OR=2.33, 95% CI 1.57 to 3.46).ConclusionsIn the adult population in England, long-term use of e-cigarettes and long-term use of NRT are almost exclusively by current or ex-smokers. Only a minority of past-year smokers retrospectively report long-term e-cigarette or NRT use, but this figure may be an underestimate, especially for e-cigarette use, which is more than threefold higher when assessed prospectively.

Objective To assess associations between sexual orientation and smoking and quitting behavior among adults in England. Methods Data were collected from 112 537 adults (≥16 years) participating in a nationally representative monthly cross-sectional survey between July 2013 and February 2019. Sexual orientation was self-reported as heterosexual, bisexual, lesbian/gay, or prefer-not-to-say. Main outcomes were smoking status, e-cigarette use, cigarettes per day, time to first cigarette, motivation to stop smoking, motives for quitting, use of cessation support, and past-year quit attempts. Associations were analyzed separately for men and women using multivariable regression models adjusted for relevant covariates. Results Smoking prevalence is now similar between gay (21.6%), prefer-not-to-say (20.5%) and heterosexual men (20.0%), and lesbian (18.3%) and heterosexual women (16.9%), but remains higher among bisexual men (28.2%, adjusted odds ratio [ORadj] = 1.41, 95% confidence interval [CI] = 1.11 to 1.79) and bisexual women (29.8%, ORadj = 1.64, 95% CI = 1.33 to 2.03) and lower among prefer-not-to-say women (14.5%, ORadj = 0.85, 95% CI = 0.72 to 0.99). Among smokers, bisexuals were less addicted than heterosexuals, with bisexual men smoking fewer cigarettes per day (Badj = −2.41, 95% CI = −4.06 to −0.75) and bisexual women less likely to start smoking within 30 min of waking (ORadj = 0.66, 95% CI = 0.45 to 0.95) than heterosexuals. However, motivation to stop smoking and quit attempts did not differ significantly. Conclusions In England, differences in smoking prevalence among people with different sexual orientations have narrowed, primarily driven by a larger decline in smoking rates among sexual minority groups than heterosexuals. Bisexual men and women remain more likely to smoke but have lower levels of addiction while being no less likely to try to quit. Implications This population-based study provides an up-to-date picture of smoking and quitting behavior in relation to sexual orientation among adults in England. Findings suggest that widely documented disparities in smoking prevalence have narrowed over recent years, with gay men and lesbian women no longer significantly more likely to smoke than heterosexuals, although smoking remains more common among bisexual men and women. Insights into differences in level of addiction, use of cessation support, and motives for quitting may help inform the development of targeted interventions to further reduce smoking among sexual minority groups.

ObjectivesTo help implement behaviour change interventions (BCIs) in practice it is important to be able to characterize their key components. This study compared broad features of cost-effective BCIs that addressed smoking, diet, physical activity, alcohol and sexual health. It also assessed the association of these with the magnitude of the cost-effectiveness estimates.MethodsA content analysis of 79 interventions based on 338 intervention descriptions was conducted, using the Behaviour Change Wheel (BCW) to classify intervention content in terms of intervention functions, and the BCT taxonomy to identify and categorise component Behaviour Change Techniques (BCT). Regression analysis identified the association of these with upper (pessimistic) and lower (optimistic) cost-effectiveness estimates.ResultsThe most and least common functions and BCT clusters were education (82.3%) and shaping knowledge (79.7%), and coercion (3.8%) and covert learning (2.5%). Smoking interventions contained the largest ([Formula: see text] = 12) number of BCTs and were most cost-effective. Several other factors were associated with worse (coercionfunction βupper = 36551.24; shaping knowledgeBCT βlower = 2427.78; comparison of outcomesBCT βupper = 9067.32; repetition and substitutionBCT βupper = 7172.47) and better (modellingfunction βlower = -2905.3; environmental restructuringfunction βupper = -8646.28; reward and threatBCT βupper = -5577.59) cost-effectiveness (pDiscussionCost-effective BCIs rely heavily on education with smoking interventions exhibiting the most comprehensive range of BCTs. Providing an example to aspire to, restructuring the environment and rewarding positive behaviour may be associated with greater cost-effectiveness.

Background Tobacco use kills half a million people every month, most in low–middle income countries (LMICs). There is an urgent need to identify potentially low-cost, scalable tobacco cessation interventions for these countries. Objective To evaluate a brief community outreach intervention delivered by health workers to promote tobacco cessation in India. Design Cluster-randomised controlled trial. Setting 32 low-income administrative blocks in Delhi, half government authorised (‘resettlement colony’) and half unauthorised (‘J.J. cluster’) communities. Participants 1213 adult tobacco users. Interventions Administrative blocks were computer randomised in a 1:1 ratio, to the intervention (16 clusters; n=611) or control treatment (16 clusters; n=602), delivered and assessed at individual level between 07/2012 and 11/2013. The intervention was single session quit advice (15 min) plus a single training session in yogic breathing exercises; the control condition comprised very brief quit advice (1 min) alone. Both were delivered via outreach, with contact made though household visits. Measurements The primary outcome was 6-month sustained abstinence from all tobacco, assessed 7 months post intervention delivery, biochemically verified with salivary cotinine. Results The smoking cessation rate was higher in the intervention group (2.6% (16/611)) than in the control group (0.5% (3/602)) (relative risk=5.32, 95% CI 1.43 to 19.74, p=0.013). There was no interaction with type of tobacco use (smoked vs smokeless). Results did not change materially in adjusted analyses, controlling for participant characteristics. Conclusions A single session community outreach intervention can increase tobacco cessation in LMIC. The effect size, while small, could impact public health if scaled up with high coverage. Trial registration number ISRCTCN23362894.

Background and aims In smoking treatment trials comparing varenicline with transdermal nicotine replacement therapy (NRT), stratified by nicotine metabolite (3‐hydroxycotinine/cotinine) ratio (NMR), the relative benefit of varenicline is greater among normal rather than slow metabolizers. This study tested if the relative effectiveness of varenicline and NRT is associated with NMR status in a natural treatment setting. A secondary aim was to test if this relationship is moderated by behavioural support. Design Prospective observational multi‐centre study with 4‐week and 52‐week follow‐up. Setting Nine English Stop Smoking Services (SSS). Participants Data came from 1556 smokers (aged ≥ 16 years) attending SSS between March 2012 and March 2013. Interventions Participants received pharmacotherapy together with behavioural support. Measurements The primary outcome was carbon monoxide‐verified continuous abstinence at both follow‐up times. Main explanatory variables were (1) NMR status [slow (NMR

Introduction: Harm reduction involving partial or complete substitution of cigarettes with nicotine replacement therapy (NRT) is likely to benefit smokers by reducing exposure to carcinogens and by increasing the likelihood of permanent cessation. This article aimed to assess the determinants of short- and long-term NRT use for harm reduction in order to inform interventions aimed at helping smokers struggling to quit to switch to complete NRT substitution. / Methods: Data were used from the Smoking Toolkit Study, a population-based survey of adults in England aged 16 years and older (n = 9,224). Participants were asked about their sociodemographic characteristics and tobacco use. Attitudes toward smoking were also assessed using questions covering 4 factors: motives, identity, evaluations, and plans. / Results: Concurrent short-term (

ObjectivesTo (1) estimate the combined risks of cigarette smoking and physical inactivity for chronic disease, disability and depressive symptoms and (2) determine whether risks associated with these behaviours are additive or synergistic.Design and settingLongitudinal observational population study using data from Waves 2 (2004/2005) through 8 (2016/2017) of the English Longitudinal Study of Ageing, a prospective study of community-dwelling older adults in England.Participants6425 men and women aged ≥52 years (mean (SD) 65.88 (9.34) years) at baseline.Main outcome measuresSmoking status (never, former, current) and level of physical activity (high, defined as moderate/vigorous physical activity (MVPA) more than once a week; low, defined as MVPA once a week or less) were self-reported at Wave 2 baseline. Self-rated health, limiting long-standing illness, chronic conditions (coronary heart disease (CHD), stroke, cancer, chronic lung disease) and depressive symptoms were reported in each biennial wave.ResultsBoth smoking and low levels of physical activity were associated with increased risk of incident health problems over the 12-year follow-up period. Current smokers with low levels of physical activity had especially high risks of developing fair/poor self-rated health, CHD, stroke, cancer and chronic lung disease compared with highly active never smokers (adjusted relative risk range 1.89–14.00). While additive effects were evident, tests of multiplicative interactions revealed no evidence of large synergistic effects of smoking and low physical activity (Bayes factor range 0.04–0.61), although data were insensitive to detect smaller effects.ConclusionsAmong older adults in England, there was no evidence of large synergistic effects of smoking and low levels of physical activity on risk of developing chronic disease or depressive symptoms over 12 years. However, additive effects of smoking and low levels of physical activity were evident, underscoring the importance of each of these lifestyle risk behaviours for disease onset.

It has been proposed that positive smoker identity may be an important factor undermining smoking cessation but very little research exists on this. This study tested the hypothesis that a simple measure of positive smoker identity would predict quit attempts over and above other known predictors in a population sample. More tentatively it explored whether this measure would also predict quit success.A representative sample of adult smokers in England (n=9456) was included at baseline and 2099 were followed-up at six months. Demographic and smoking characteristics, a single item measure of positive smoker identity (endorsing the statement: 'I like being a smoker'), measures of smoking-related attitudes, quit attempts and quit success were included.A total of 18.3% (95% CI=17.5-19.2) of smokers reported a positive smoker identity. Adjusting for all other predictors, those with a positive smoker identity were more likely to be older (p0.001), male (p=0.013), more nicotine dependent (p0.001), have lower motivation to stop (p0.001), have not made a quit attempt in the past year (p=0.025), enjoy smoking (p0.001), and consider themselves to be addicted (p0.001). Having a positive smoker identity independently predicted failure to make a quit attempt at six months (p=0.007). The independent association with quit success was similar in magnitude but did not reach statistical significance (p=0.053).Only a minority of smokers in England have a positive smoker identity. However, where it is present it may be an important barrier to quitting smoking and merits further study.

Nicotine replacement therapy (NRT) has been used in the treatment of tobacco dependence for over three decades. Whilst the choice of NRT was limited early on, in the last ten years there has been substantial increase in the number of nicotine delivery devices that have become available. This article briefly summarises existing forms of NRT, evidence of their efficacy and use, and reviews the rationale for the development of novel products delivering nicotine via buccal, transdermal or pulmonary routes (including nicotine mouth spray, nicotine films, advanced nicotine inhalers and electronic cigarettes). It presents available evidence on the efficacy, tolerability and abuse potential of these products, with a focus on their advantages as well as disadvantages compared with established forms of NRT for use as an aid to both smoking cessation as well as harm reduction.

Background: This article reports a pilot study of a new smoking cessation website ('StopAdvisor'), which has been developed on the basis of PRIME theory, evidence, web-design expertise and user-testing. The aims were to i) evaluate whether cessation, website usage and satisfaction were sufficiently high to warrant a randomised controlled trial (RCT) and ii) assess whether outcomes were affected by socio-economic status. Methods: This was an uncontrolled pilot study. Two hundred and four adult daily smokers willing to make a serious quit attempt were included. All participants received support from 'StopAdvisor', which recommends a structured quit plan and a variety of evidence-based behaviour change techniques for smoking cessation. A series of tunnelled sessions and a variety of interactive menus provide tailored support for up to a month before quitting through until one-month post-quit (http://www.lifeguideonline.org/player/play/stopadvisordemonstration). The primary outcome was self-report of at least 1. month of continuous abstinence collected at 2. months post-enrolment and verified by saliva cotinine or anabasine. Usage was indexed by log-ins and page views. Satisfaction was assessed by dichotomous ratings of helpfulness, personal relevance, likelihood of recommendation and future use, which were collected using an online questionnaire at 2. months post-enrolment. Outcomes according to socio-economic status were assessed. Results: At 8. weeks post-enrolment, 19.6% (40/204) of participants were abstinent according to the primary outcome criteria (95% C.I.=. 14.1% to 25.1%). Participants viewed a mean of 133.5 pages (median. =. 71.5) during 6.4 log-ins (median. =. 3). A majority of respondents rated the website positively on each of the four satisfaction ratings (range. =. 66.7% to 75.3%). There was no evidence of an effect of socio-economic status on abstinence (OR. =. 1.01, C.I.=. 0.50-2.07), usage (page-views, t(202). =. 0.11, p=. .91; log-ins, t(202). =. 0.21, p=. .83), or satisfaction (helpfulness, OR. =. 1.09, C.I.=. 0.41-2.88; personal relevance, OR. =. 0.55, C.I.=. 0.20-1.56; recommendation, OR. =. 0.98, C.I.=. 0.34-2.81; use in future, OR. =. 1.45, C.I.=. 0.49-4.27). Conclusions: The systematic application of theory, evidence, web-design expertise, and user-testing has resulted in a website that shows sufficiently promising efficacy and usability to warrant evaluation in a RCT. The website appears to be similarly effective and acceptable to users across the social spectrum. © 2012 Elsevier Ltd.

A wide range of support is available to help smokers to quit and to aid attempts at harm reduction, including three first-line smoking cessation medications: nicotine replacement therapy, varenicline and bupropion. Despite the efficacy of these, there is a continual need to diversify the range of medications so that the needs of tobacco users are met. This paper compares the first-line smoking cessation medications with (1) two variants of these existing products: new galenic formulations of varenicline and novel nicotine delivery devices; and (2) 24 alternative products: cytisine (novel outside Central and Eastern Europe), nortriptyline, other tricyclic antidepressants, electronic cigarettes, clonidine (an anxiolytic), other anxiolytics (e.g. buspirone), selective serotonin reuptake inhibitors, supplements (e.g. St John’s wort), silver acetate, Nicobrevin, modafinil, venlafaxine, monoamine oxidase inhibitors (MAOIs), opioid antagonists, nicotinic acetylcholine receptor (nAChR) antagonists, glucose tablets, selective cannabinoid type 1 receptor antagonists, nicotine vaccines, drugs that affect gamma-aminobutyric acid (GABA) transmission, drugs that affect N-methyl-d-aspartate (NMDA) receptors, dopamine agonists (e.g. levodopa), pioglitazone (Actos; OMS405), noradrenaline reuptake inhibitors and the weight management drug lorcaserin. Six ‘ESCUSE’ criteria—relative efficacy, relative safety, relative cost, relative use (overall impact of effective medication use), relative scope (ability to serve new groups of patients) and relative ease of use—are used. Many of these products are in the early stages of clinical trials; however, cytisine looks most promising in having established efficacy and safety with low cost. Electronic cigarettes have become very popular, appear to be efficacious and are safer than smoking, but issues of continued dependence and possible harms need to be considered.

Introduction The existence of a social gradient in tobacco use has been clearly established in a number of countries with people with lower socioeconomic status being more likely to use tobacco. It is not clear how far this gradient is evident within severely deprived communities. This study assessed the association between occupation as a marker of socioeconomic status and use of smoked and smokeless tobacco within “slum” areas of Delhi, India. Methods A census survey of 11 888 households, comprising 30 655 adults from 28 low-income communities (14 government-authorized and 14 unauthorized settlements called “Jhuggi-Jhopri/JJ” clusters) was conducted in 2012. The survey assessed age, sex, household size, occupational group, and current tobacco use. Independent associations with tobacco use were conducted using complex samples regression analysis, stratified by gender. Results A quarter of participants (24.3%, 95% confidence interval [CI] 21.5–27.5) used any tobacco. Slightly more people used smoked (14.6%, 95% CI 12.9–16.3) than smokeless (12.6%, 95% CI 10.7–14.8) tobacco, with a small minority being dual users (2.7%, 95% CI 2.1–3.5). Prevalence of any tobacco use was highest in unskilled (45.13%, 95% CI 42.4–47.9) and skilled (46.2%, 95% CI 41.1–51.4) manual occupations and lower in nonmanual (30.3%, 95% CI 26.2–34.7) occupations and those who were unemployed (29.0%, 95% CI 25.3–33.0). This was confirmed in adjusted analysis in men but associations were more complex in women. Conclusions Use of smoked and smokeless tobacco in low-income urban communities in India has a complex association with occupational status with both nonmanual occupation and unemployment being associated with lower prevalence of smoked and smokeless tobacco in men. Implications Tobacco use in high-income countries shows a strong inverse relationship with social grade, income, and deprivation such that use is much more common among those who can least afford it. This study is the first to look at this social gradient in the context of low-income communities in India, finding that both unemployment and nonmanual occupation were associated with lower rates of tobacco use in men. The data present a challenge to existing explanations of the social gradient, requiring further consideration of the conditions under which affordability may work to reduce health inequalities arising from tobacco use.