Effectiveness of a smartphone app (Drink Less) versus usual digital care for reducing alcohol consumption among increasing-and-higher-risk adult drinkers in the UK: a two-arm, parallel-group, double-blind, randomised controlled trial.

Background: Digital interventions, including apps and websites, can be effective for reducing alcohol consumption. However, many are not evidence- or theory-informed and have not been evaluated. We tested the effectiveness of the Drink Less app for reducing alcohol consumption compared with usual digital care in the UK. Methods: In this two-arm, parallel group, double-blind, randomised controlled trial, we enrolled increasing-and-higher-risk drinkers (AUDIT ≥ 8) in the UK, who were motivated to reduce their alcohol consumption and willing to use a digital intervention to do so, via online methods. Participants were randomly assigned (1:1), using an online algorithm, to receive a web link to download the Drink Less app (intervention) or to the NHS alcohol advice webpage (usual digital care). Researchers were masked to group allocation. Participants were followed up at one, three and six months. The primary outcome was self-reported weekly alcohol consumption at six months, adjusting for baseline consumption. The full analytic sample was used in most analyses, though missing data was treated in different ways. The primary, pre-registered intention-to-treat analysis assumed baseline-carried-forwards. Secondary pre-registered analyses also focused on the full analytic sample and used alternatives including multiple imputation and last observation carried forwards. This trial is registered with the ISRCTN registry, ISRCTN64052601. Findings: Between 07/13/2020 and 03/29/2022, 5602 people were randomly assigned to the Drink Less app (n = 2788) or comparator (n = 2814) groups. Six-month follow-up rates were 79% and 80%, respectively. The primary pre-registered conservative intention-to-treat approach assuming non-responders were drinking at baseline levels of consumption, found a non-significant greater reduction of 0.98 units in weekly alcohol consumption in the intervention group at 6-month follow-up (95% CI -2.67 to 0.70). The data were insensitive to detect the hypothesised effect (Bayes factor = 1.17). Data were not missing completely at random, with 6-month follow-up rates differing in terms of education, occupation, and income. We therefore conducted the pre-registered sensitivity analysis using multiple imputation, showing that the Drink Less app resulted in a 2.00-unit greater weekly reduction at 6-month follow-up compared with the NHS alcohol advice webpage (95% CI -3.76 to -0.24). Fewer than 0.1% of participants in both arms who responded to one, three or six-month follow-up reported adverse events linked to participation in the trial. Interpretation: The Drink Less app may be effective in reducing the alcohol consumption in increasing-and-higher-risk drinkers motivated to reduce their consumption. Funding: NIHR Public Health Research Programme.

Diffusible fraction of niche BMP ligand safeguards stem-cell differentiation.

Drosophila male germline stem cells (GSCs) reside at the tip of the testis and surround a cluster of niche cells. Decapentaplegic (Dpp) is one of the well-established ligands and has a major role in maintaining stem cells located in close proximity. However, the existence and the role of the diffusible fraction of Dpp outside of the niche have been unclear. Here, using genetically-encoded nanobodies called Morphotraps, we physically block Dpp diffusion without interfering with niche-stem cell signaling and find that a diffusible fraction of Dpp is required to ensure differentiation of GSC daughter cells, opposite of its role in maintenance of GSC in the niche. Our work provides an example in which a soluble niche ligand induces opposed cellular responses in stem cells versus in differentiating descendants to ensure spatial control of the niche. This may be a common mechanism to regulate tissue homeostasis.

Association between the implementation of standardised tobacco packaging legislation and illicit tobacco and cross-border purchasing in England: a time-series analysis between 2012 and 2020.

BACKGROUND: In May 2016, the UK announced standardising packaging legislation for tobacco products. There was a 12-month transition period with both branded and standardised packs on the market until May 2017. The aim of this study was to investigate whether the implementation of standardised packaging in England was associated with changes in illicit tobacco and cross-border purchasing. METHODS: We used Smoking Toolkit Study data covering the time period from 2012 to 2020. We ran time-series analysis using Autoregressive Integrated Moving Average with Exogenous Variable models to investigate the monthly changes in illicit tobacco and cross-border purchasing in England. The model was adjusted for other tobacco control policies implemented during the relevant time period and tobacco pricing. We used May 2017 as an implementation point and run sensitivity analysis using July 2016 and February 2017 as alternative implementation points given phased introduction of the policy. RESULTS: The average prevalence of illicit tobacco and cross-border purchasing in the past 6 months was 14.4%. The implementation of standardised tobacco packaging legislation was associated with a monthly decline in illicit tobacco and cross-border purchases after May 2017 by 0.16% per month (beta=-0.158, 95% CI -0.270 to -0.046). The results were robust to considering different implementation points for the policy (July 2016: beta=-0.109, 95% CI -0.213 to -0.005; February 2017: beta=-0.141, 95% CI -0.245 to -0.036). CONCLUSIONS: In contrast to the tobacco industry's argument that the legislation would lead to an increase in the illicit tobacco and cross-border market, this study demonstrates that the implementation of the policy is associated with a decline in illicit tobacco and cross-border purchases in England.

Associations of prevalence of e-cigarette use with quit attempts, quit success, use of smoking cessation medication, and the overall quit rate among smokers in England: a time-series analysis of population trends 2007-2022.

INTRODUCTION: This study aimed to: (i) provide up-to-date estimates of how changes in prevalence of e-cigarette use have been associated with changes in smoking cessation activities and use of licensed treatments among smokers in England; and (ii) explore any changes in these associations over time. METHODS: Data were aggregated quarterly on 67,548 past-year smokers between Q1-2007 and Q4-2022. Explanatory variables were prevalence of (i) current e-cigarette use among smokers and (ii) e-cigarette use during a quit attempt. Outcomes were rates of quit attempts and overall quits among past-year smokers, and the quit success rate and use of licensed treatments among those who made a quit attempt. RESULTS: The success rate of quit attempts increased by 0.040% (95%CI 0.019; 0.062) for every 1% increase in the prevalence of e-cigarette use during a quit attempt. No clear evidence was found for an association between current e-cigarette use and the quit attempt rate (Badj=0.008 [95%CI -0.045; 0.061]) or overall quit rate (Badj=0.063 [-0.031; 0.158]); or between use of e-cigarettes during a quit attempt and the overall quit rate (Badj=0.030 [-0.054; 0.114]), use of prescription medication (varenicline/bupropion/NRT: Badj=-0.036 [-0.175; 0.102]), or use of over-the-counter NRT (Badj=-0.052 [-0.120; 0.015]). There was no clear evidence this pattern of associations has changed substantially over time. CONCLUSIONS: Changes in prevalence of e-cigarette use in England through to 2022 have been positively associated with the success rate of quit attempts but not clearly associated with the quit attempt rate, overall quit rate, or use of licensed smoking cessation treatments. IMPLICATIONS: If the association between the increase in e-cigarette use and the quit success rate is causal, then the use of e-cigarettes in quit attempts has helped in the region of 30,000 to 50,000 additional smokers in England to successfully quit each year since they became popular in 2013, over and above the number who were quitting before the advent of e-cigarettes.

Have there been sustained impacts of the COVID-19 pandemic on trends in smoking prevalence, uptake, quitting, use of treatment, and relapse? A monthly population study in England, 2017-2022.

BACKGROUND: Studies conducted during the early stages of the pandemic documented mixed changes in smoking behaviour: more smokers quitting successfully but little change in prevalence. This study aimed to examine whether there have been sustained impacts of the COVID-19 pandemic on smoking patterns in England. METHODS: Data were from 101,960 adults (≥ 18 years) participating in the Smoking Toolkit Study, a monthly representative household survey, between June 2017 and August 2022. Interviews were conducted face-to-face until March 2020 and via telephone thereafter. Generalised additive models estimated associations of the pandemic onset (March 2020) with current smoking, uptake, cessation, quit attempts, and use of support. Models adjusted for seasonality, sociodemographic characteristics, and (where relevant) dependence and tobacco control mass-media expenditure. RESULTS: Before the COVID-19 pandemic, smoking prevalence fell by 5.2% per year; this rate of decline slowed to 0.3% per year during the pandemic (RRΔtrend = 1.06, 95% CI = 1.02, 1.09). This slowing was evident in more but not less advantaged social grades (RRΔtrend = 1.15, 1.08, 1.21; RRΔtrend = 1.00, 0.96, 1.05). There were sustained step-level changes in different age groups: a 34.9% (95% CI = 17.7, 54.7%) increase in smoking prevalence among 18-24-year-olds, indicating a potential rise in uptake, in contrast to a 13.6% (95% CI = 4.4, 21.9%) decrease among 45-65-year-olds. In both age groups, these step-level changes were followed by the pre-pandemic declines stopping, and prevalence remaining flat. There were sustained increases in quitting among past-year smokers, with a 120.4% (95% CI = 79.4, 170.9%) step-level increase in cessation and a 41.7% (95% CI = 29.7, 54.7%) increase in quit attempts. The main limitation was the change in modality of data collection when the pandemic started; while this may have contributed to the step-level changes we observed, it is unlikely to explain changes in the slope of trends. CONCLUSIONS: In England, the rate of decline in adult smoking prevalence stagnated during the COVID-19 pandemic through to 2022. At the start of the pandemic, a potential reduction in smoking prevalence among middle-aged adults and increases in quitting among smokers may have been offset by an increase in smoking among young adults. The slowing in the rate of decline was pronounced in more advantaged social grades.

Effects of reduced-risk nicotine-delivery products on smoking prevalence and cigarette sales: an observational study.

Background: It is not currently clear what impact alternative nicotine-delivery products (electronic cigarettes, heated tobacco products and snus) have on smoking rates and cigarette sales. Objective: To assess whether access to these products promotes smoking in the population. Design and data sources: We examined associations of alternative nicotine product use and sales with smoking rates and cigarette sales overall, and in different age and socioeconomic groups, and compared smoking prevalence over time in countries with contrasting regulations of these products. For electronic cigarettes, we examined data from countries with historically similar smoking trajectories but differing current electronic cigarette regulations (United Kingdom and United States of America vs. Australia, where sales of nicotine-containing electronic cigarettes are banned); for heated tobacco, we used data from countries with state tobacco monopolies, where cigarette and heated tobacco sales data are available (Japan, South Korea), and for snus we used data from Sweden. Analysis methods: We pre-specified dynamic time series analyses to explore associations between use and sales of alternative nicotine-delivery products and smoking prevalence and cigarette sales, and time series analyses to compare trends of smoking prevalence in countries with different nicotine product policies. Results: Because of data and analysis limitations (see below), results are only tentative and need to be interpreted with caution. Only a few findings reached statistical significance and for most results the Bayes factor indicated inconclusive evidence. We did not find an association between rates of smoking and rates of the use of alternative nicotine products. The increase in heated tobacco product sales in Japan was accompanied by a decrease in cigarette sales. The decline in smoking prevalence seems to have been slower in Australia than in the United Kingdom overall, and slower than in both the United Kingdom and the United States of America among young people and also in lower socioeconomic groups. The decline in cigarette sales has also accelerated faster in the United Kingdom than in Australia. Limitations: Most of the available data had insufficient data points for robust time series analyses. The assumption of our statistical approach that causal interactions are more likely to be detected when longer-term changes are screened out may not apply for short time series and in product interaction scenarios, where short-term fluctuations can be caused by, for example, fluctuations in prosperity or product supplies. In addition, due to dual use, prevalence figures for smoking and alternative product use overlap. The ecological study design limits the causal inferences that can be made. Longer time periods are needed for any effects of exclusive use of the new products on smoking prevalence to emerge. Conclusions: We detected some indications that alternative nicotine products are competing with cigarettes rather than promoting smoking and that regulations that allow their sales are associated with a reduction rather than an increase of smoking, but the findings are inconclusive because of insufficient data points and issues with the assumptions of the pre-specified statistical analyses. Future work: As further prevalence and sales data emerge the analyses will become more informative. Accessing sales figures in particular is the current research priority. Study registration: The project is registered on Open Science Framework https://osf.io/bd3ah. Funding: This project was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (NIHR129968) and will be published in full in Public Health Research; Vol. 11, No. 7. See the NIHR Journals Library website for further project information.

Alternative nicotine-delivery products are now available which are much less hazardous than cigarettes. These include electronic cigarettes (which contain no tobacco), Swedish snus (oral tobacco with low levels of cancer-causing chemicals) and heated tobacco products. There is concern that these products attract young people to smoking and discourage smokers from quitting (i.e. increase smoking), but it is also possible that they help smokers quit and steer young people who find nicotine attractive away from smoking, or that they have no effect on smoking. To clarify which of these end results is likely, we looked at data on smoking and on the use of these alternative products over time, and also compared data on smoking from countries that have similar tobacco control history, but that either allow (i.e. United Kingdom and United States of America) or ban the sale of electronic cigarettes (i.e. Australia). As the sale of heated tobacco products increased in Japan, sales of cigarettes seem to have gone down, suggesting that this product is competing with cigarettes rather than encouraging their use. We also found that the drop in smoking may have been slower in Australia than in the United Kingdom. For young people and those on low income specifically, the reduction in smoking was slower in Australia than in both the United Kingdom and United States of America. Allowing alternative nicotine products to be sold seems to have been linked with lowered rather than increased rates of smoking. Our findings, however, are uncertain because only limited data were available. Clearer conclusions will become possible as more data on the use and especially on the sales of alternative nicotine products are collected.

E-cigarettes to Augment Stop Smoking In-person Support and Treatment With Varenicline (E-ASSIST): A Pragmatic Randomized Controlled Trial.

AIM: To examine whether, in adults receiving behavioral support, offering e-cigarettes together with varenicline helps more people stop smoking cigarettes than varenicline alone. METHODS: A two-group, parallel arm, pragmatic randomized controlled trial was conducted in six English stop smoking services from 2019-2020. Adults enrolled onto a 12-week programme of in-person one-to-one behavioral smoking cessation support (N  =  92) were randomized to receive either (1) a nicotine e-cigarette starter kit alongside varenicline or (2) varenicline alone. The primary outcome was biochemically verified abstinence from cigarette smoking between weeks 9-to-12 post quit date, with those lost to follow-up considered not abstinent. The trial was stopped early due to COVID-19 restrictions and a varenicline recall (92/1266 participants used). RESULTS: Nine-to-12-week smoking abstinence rates were 47.9% (23/48) in the e-cigarette-varenicline group compared with 31.8% (14/44) in the varenicline-only group, a 51% increase in abstinence among those offered e-cigarettes; however, the confidence interval (CI) was wide, including the possibility of no difference (risk ratio [RR] = 1.51, 95% CI = 0.91-2.64). The e-cigarette-varenicline group had 43% lower hazards of relapse from continuous abstinence than the varenicline-only group (hazards ratio [HR] = 0.57, 95% CI =  0.34-0.96). Attendance for 12 weeks was higher in the e-cigarette-varenicline than varenicline-only group (54.2% vs. 36.4%; RR = 1.49, 95% CI = 0.95-2.47), but similar proportions of participants in both groups used varenicline daily for ≥8 weeks after quitting (22.9% versus 22.7%; RR = 1.01, 95% CI = 0.47-2.20). Estimates were too imprecise to determine how adverse events differed by group. CONCLUSION: Tentative evidence suggests that offering e-cigarettes alongside varenicline to people receiving behavioral support may be more effective for smoking cessation than varenicline alone. IMPLICATIONS: Offering e-cigarettes to people quitting smoking with varenicline may help them remain abstinent from cigarettes, but the evidence is tentative because our sample size was smaller than planned-caused by Coronavirus Disease 2019 (COVID-19) restrictions and a manufacturing recall. This meant our effect estimates were imprecise, and additional evidence is needed to confirm that providing e-cigarettes and varenicline together helps more people remain abstinent than varenicline alone.

Patterns and predictors of adherence to health-protective measures during COVID-19 pandemic in the UK: cross-sectional and longitudinal findings from the HEBECO study.

BACKGROUND: Adherence to health-protective behaviours (regularly washing hands, wearing masks indoors, maintaining physical distancing, carrying disinfectant) remains paramount for the successful control of COVID-19 at population level. It is therefore important to monitor adherence and to identify factors associated with it. This study assessed: 1) rates of adherence, to key COVID-19 health-protective behaviours and 2) the socio-demographic, health and COVID-19-related factors associated with adherence. METHODS: Data were collected on a sample of UK-based adults during August-September 2020 (n = 1,969; lockdown restrictions were eased in the UK; period 1) and November 2020- January 2021 (n = 1944; second UK lockdown; period 2). RESULTS: Adherence ranged between 50-95%, with higher adherence during the period of stricter measures. Highest adherence was observed for wearing masks indoors (period 1: 80.2%, 95%CI 78.4%-82.0%, period 2: 92.4%, 95%CI 91.1%-93.6%) and lowest for carrying own disinfectant (period 1: 48.4%, 95%CI 46.2%-50.7%, period 2: 50.7%, 95%CI 48.4%-53.0%). Generalized estimating equation models indicated that key factors of greater odds of adherence included being female, older age, having higher income, residing in England, living with vulnerable individuals and perceived high risk of COVID-19. CONCLUSIONS: Targeted messages to different demographic groups may enhance adherence to health-protective behaviours, which is paramount for the control of airborne respiratory diseases. PROTOCOL AND ANALYSIS PLAN REGISTRATION: The analysis plan was pre-registered, and it is available at https://osf.io/6tnc9/ .

Longitudinal changes and correlates of meeting WHO recommended levels of physical activity in the UK during the COVID-19 pandemic: Findings from the HEBECO study.

BACKGROUND: The COVID-19 pandemic has seen repeated government enforced restrictions on movement. This study aimed to evaluate longitudinal trends in physical activity (PA) in a self-selected UK-based sample and identify the key correlates of these trends. METHODS: From 23 April 2020 to 30 January 2021, measures of PA engagement were collected in a sample of 1,947 UK-based adults. Generalised estimating equations (GEE) explored trends in PA engagement over time, and how sociodemographic, health and contextual factors impacted participant's attainment of World Health Organization (WHO) recommended levels of PA (constituting muscle strengthening activity (MSA), and moderate or vigorous PA (MVPA)). RESULTS: While one in five achieved the recommended levels of PA in the first UK lockdown in April-June 2020 (19.5%, 95%CI: 17.8-21.3%) and a similar proportion in June-July 2020 (17.7%, 95%CI: 16.1-19.5%), this reduced during the period of eased restrictions in August-September 2020 (15.2%, 95%CI: 13.7-16.9%) and the second UK lockdown in November 2020-January 2021 (14.1%, 95%CI: 12.6-15.9%). Similar trends were observed for MSA and MVPA individually. Better quality of life, higher socioeconomic position and pre-COVID-19 PA levels were associated with meeting the WHO recommended levels of PA, while those living with overweight or obesity, a limiting health condition, or isolating showed the inverse associations. Time-specific associations with MSA or MVPA were observed for gender and age. CONCLUSION: Reductions in PA levels throughout the first strict lockdown continued without reversal during the ensuing period. The association of negative change with socioeconomic and health-related indices points towards deepening health inequities during the pandemic.

UK Adults' Exercise Locations, Use of Digital Programs, and Associations with Physical Activity During the COVID-19 Pandemic: Longitudinal Analysis of Data From the Health Behaviours During the COVID-19 Pandemic Study.

BACKGROUND: Digital physical activity (PA) program use has been associated with higher PA guideline adherence during COVID-19 pandemic confinements. However, little is known longitudinally about exercise locations (inside vs outside the home environment), digital program use, and their associations with moderate-to-vigorous PA (MVPA) and muscle-strengthening activities (MSAs) during the pandemic. OBJECTIVE: The aims of this study were to assess the relationship between exercise location and use of digital programs with PA guideline adherence during the COVID-19 pandemic, describe how individuals exercised inside and outside of their home environments, and explore which sociodemographic and contextual factors were associated with exercise locations and digital PA program use. METHODS: Active UK adults (N=1938) who participated in the 1-month follow-up survey of the Health Behaviours During the COVID-19 Pandemic (HEBECO) study (FU1, June-July 2020) and at least one more follow-up survey (FU2, August-September; FU3, November-December 2020) reported exercise locations and types of exercises inside and outside their homes, including digital programs (online/app-based fitness classes/programs), MVPA, and MSA. Generalized linear mixed models were used to assess associations of exercise location and digital PA program use with PA guideline adherence (MVPA, MSA, full [combined] adherence), and predictors of exercise location and digital program use. RESULTS: As the pandemic progressed, active UK adults were less likely to exercise inside or to use digital PA programs compared with periods of initial confinement: 61% (95% CI 58%-63%; weighted n=1024), 50% (95% CI 48%-53%; weighted n=786), and 49% (95% CI 46%-51%; weighted n=723) performed any exercise inside their homes at FU1, FU2, and FU3, respectively. At FU1, FU2, and FU3, 22% (95% CI 21%-25%; weighted n=385), 17% (95% CI 15%-19%; weighted n=265), and 16% (95% CI 14%-18%; weighted n=241) used digital PA programs, respectively. Most participants who exercised inside already owned indoor equipment, used digital PA programs, or had their own workout routines, whereas MVPA and gentle walking were the most common exercise types performed outside the home. Being female, nonwhite, having a condition limiting PA, indoor exercising space, a lower BMI, and living in total isolation were associated with increased odds of exercising inside the home or garden compared with outside exercise only. Digital PA program users were more likely to be younger, female, highly educated, have indoor space to exercise, and a lower BMI. While exercising inside was positively associated with MSA and exercising outside was positively associated with MVPA guideline adherence, both inside (vs outside only) and outside (vs inside only) activities contributed to full PA guideline adherence (odds ratio [OR] 5.05, 95% CI 3.17-8.03 and OR 1.89, 95% CI 1.10-3.23, respectively). Digital PA program use was associated with a higher odds of MSA (OR 3.97-8.71) and full PA (OR 2.24-3.95), but not with MVPA guideline adherence. CONCLUSIONS: During the COVID-19 pandemic, full PA guideline adherence was associated with exercising inside and outside of one's home environment and using digital PA programs. More research is needed to understand the reach, long-term adherence, and differences between digital PA solutions.

Smoking prevalence following the announcement of tobacco tax increases in England between 2007 and 2019: an interrupted time-series analysis.

AIMS: This study aimed to evaluate the impact of announcement of tax increases on factory-made (FM) and roll-your own (RYO) cigarettes in England. DESIGN, SETTING AND PARTICIPANTS: 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). MEASUREMENTS: 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. FINDINGS: 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. CONCLUSION: 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.

Association of quarterly prevalence of e-cigarette use with ever regular smoking among young adults in England: a time-series analysis between 2007 and 2018.

AIMS: 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. DESIGN: Time-series analysis of population trends with autoregressive integrated moving average with exogeneous input (ARIMAX models). SETTING: England. PARTICIPANTS: Data were aggregated quarterly on young adults aged 16-24 years (n = 37 105) taking part in the Smoking Toolkit Study. MEASURES: 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]. FINDINGS: 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. CONCLUSION: 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.

Changes in Cigarette Smoking and Vaping in Response to the COVID-19 Pandemic in the UK: Findings from Baseline and 12-Month Follow up of HEBECO Study.

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.

Moderators of changes in smoking, drinking and quitting behaviour associated with the first COVID-19 lockdown in England.

AIM: To estimate changes in smoking, drinking and quitting behaviour from before to during the first COVID-19 lockdown in England, and whether changes differed by age, sex or social grade. DESIGN: Representative cross-sectional surveys of adults, collected monthly between August 2018 and July 2020. SETTING: England. PARTICIPANTS: A total of 36 980 adults (≥ 18 years). MEASUREMENTS: Independent variables were survey month (pre-lockdown: August-February versus lockdown months: April-July) and year (pandemic: 2019/20 versus comparator: 2018/19). Smoking outcomes were smoking prevalence, cessation, quit attempts, quit success and use of evidence-based or remote cessation support. Drinking outcomes were high-risk drinking prevalence, alcohol reduction attempts and use of evidence-based or remote support. Moderators were age, sex and occupational social grade (ABC1 = more advantaged/C2DE = less advantaged). FINDINGS: Relative to changes during the same time period in 2018/19, lockdown was associated with significant increases in smoking prevalence [+24.7% in 2019/20 versus 0.0% in 2018/19, adjusted odds ratio (aOR) = 1.35, 95% confidence interval (CI) = 1.12-1.63] and quit attempts (+39.9 versus -22.2%, aOR = 2.48, 95% CI = 1.76-3.50) among 18-34-year-olds, but not older groups. Increases in cessation (+156.4 versus -12.5%, aOR = 3.08, 95% CI = 1.86-5.09) and the success rate of quit attempts (+99.2 versus +0.8%, aOR = 2.29, 95% CI = 1.31-3.98) were also observed, and did not differ significantly by age, sex or social grade. Lockdown was associated with a significant increase in high-risk drinking prevalence among all socio-demographic groups (+39.5 versus -7.8%, aOR = 1.80, 95% CI = 1.64-1.98), with particularly high increases among women (aOR = 2.17, 95% CI = 1.87-2.53) and social grades C2DE (aOR = 2.34, 95% CI = 2.00-2.74). Alcohol reduction attempts increased significantly among high-risk drinkers from social grades ABC1 (aOR = 2.31, 95% CI = 1.78-3.00) but not C2DE (aOR = 1.25, 95% CI = 0.83-1.88). There were few significant changes in use of support for smoking cessation or alcohol reduction, although samples were small. CONCLUSIONS: In England, the first COVID-19 lockdown was associated with increased smoking prevalence among younger adults and increased high-risk drinking prevalence among all adults. Smoking cessation activity also increased: more younger smokers made quit attempts during lockdown and more smokers quit successfully. Socio-economic disparities in drinking behaviour were evident: high-risk drinking increased by more among women and those from less advantaged social grades (C2DE), but the rate of reduction attempts increased only among the more advantaged social grades (ABC1).

Association between cigarette smoking status and voting intentions: Cross sectional surveys in England 2015-2020.

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] <0.001), intending to vote Labour (aOR1.27 [1.16-1.36] <0.001), to vote "Other" (aOR1.54 [1.37-1.72] <0.001), or not to vote (aOR1.93 [1.77-2.11] <0.001) was associated with higher odds of current relative to never smoking rates. Intending to vote for the Liberal Democrats was associated with a significant lower odds of current smoking prevalence (aOR0.80 [0.70-0.91] <0.001) compared with intending to vote Conservative. 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.

Does addition of craving management tools in a stop smoking app improve quit rates among adult smokers? Results from BupaQuit pragmatic pilot randomised controlled trial.

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.

Impact of COVID-19 Pandemic on Weight and BMI among UK Adults: A Longitudinal Analysis of Data from the HEBECO Study.

COVID-19-related restrictions impacted weight and weight-related factors during the initial months of the pandemic. However, longitudinal analyses are scarce. An online, longitudinal study was conducted among self-selected UK adults (n = 1818), involving three surveys (May-June, August-September, November-December 2020), covering anthropometric, sociodemographic, COVID-19-related and behavioural measures. Data were analysed using generalised estimating equations. Self-reported average weight/body mass index (BMI) significantly increased between the May-June period and the August-September period (74.95 to 75.33 kg/26.22 kg/m2 to 26.36kg/m2, p < 0.001, respectively), and then significantly decreased to November-December (to 75.06 kg/26.27 kg/m2, p < 0.01), comparable to May-June levels (p = 0.274/0.204). However, there was great interindividual variation, 37.0%/26.7% increased (average 3.64 kg (95% confidence interval: 3.32, 3.97)/1.64 kg/m2 (1.49, 1.79)), and 34.5%/26.3% decreased (average 3.59 kg (3.34, 3.85)/1.53 kg/m2 (1.42, 1.63)) weight/BMI between May-June and November-December. Weight/BMI increase was significantly negatively associated with initial BMI, and positively associated with monthly high fat, salt and sugar (HFSS) snacks intake and alcohol consumption, and for BMI only, older age. Associations were time-varying; lower initial BMI, higher HFSS snacks intake and high-risk alcohol consumption were associated with maintaining weight/BMI increases between August-September and November-December. The average weight/BMI of UK adults fluctuated between May-June and November-December 2020. However, the substantial interindividual variation in weight/BMI trajectories indicates long-term health impacts from the pandemic, associated with food and alcohol consumption.

Protocol for expansion of an existing national monthly survey of smoking behaviour and alcohol use in England to Scotland and Wales: The Smoking and Alcohol Toolkit Study.

Background The Smoking and Alcohol Toolkit Study (STS/ATS) in England has delivered timely insights to inform and evaluate strategies aimed at reducing tobacco smoking- and alcohol-related harm. From the end of 2020 until at least 2024 the STS/ATS is expanding to Scotland and Wales to include all constituent nations in Great Britain. Expanding data collection to Scotland and Wales will permit the evaluation of how smoking and alcohol related behaviours respond to divergent policy scenarios across the devolved nations. Methods The STS/ATS consists of monthly cross-sectional household interviews (computer or telephone assisted) of representative samples of adults in Great Britain aged 16+ years. Commencing in October 2020 each month a new sample of approximately 1700 adults in England, 450 adults in Scotland and 300 adults in Wales complete the survey (~n = 29,400 per year). The expansion of the survey to Scotland and Wales has been funded for the collection of at least 48 waves of data across four years. The data collected cover a broad range of smoking and alcohol-related parameters (including but not limited to smoking status, cigarette/nicotine dependence, route to quit smoking, prevalence and frequency of hazardous drinking, attempts and motivation to reduce alcohol consumption, help sought and motives for attempts to reduce alcohol intake) and socio-demographic characteristics (including but not limited to age, gender, region, socio-economic position) and will be reviewed monthly and refined in response to evolving policy needs and public interests. All data analyses will be pre-specified and available on a free online platform. A dedicated website will publish descriptive data on important trends each month. Discussion The Smoking and Alcohol Toolkit Study will provide timely monitoring of smoking and alcohol related behaviours to inform and evaluate national policies across Great Britain.