Brief interventions for smoking and alcohol associated with the COVID-19 pandemic: a population survey in England.

BACKGROUND: Following the onset of the COVID-19 pandemic, in March 2020 health care delivery underwent considerable changes. It is unclear how this may have affected the delivery of Brief Interventions (BIs) for smoking and alcohol. We examined the impact of the COVID-19 pandemic on the receipt of BIs for smoking and alcohol in primary care in England and whether certain priority groups (e.g., less advantaged socioeconomic positions, or a history of a mental health condition) were differentially affected. METHODS: We used nationally representative data from a monthly cross-sectional survey in England between 03/2014 and 06/2022. Monthly trends in the receipt of BIs for smoking and alcohol were examined using generalised additive models among adults who smoked in the past-year (weighted N = 31,390) and those using alcohol at increasing and higher risk levels (AUDIT score 38, weighted N = 22,386), respectively. Interactions were tested between social grade and the change in slope after the onset of the COVID-19 pandemic, and results reported stratified by social grade. Further logistic regression models assessed whether changes in the of receipt of BIs for smoking and alcohol, respectively, from 12/2016 to 01/2017 and 10/2020 to 06/2022 (or 03/2022 in the case of BIs for alcohol), depended on history of a mental health condition. RESULTS: The receipt of smoking BIs declined from an average prevalence of 31.8% (95%CI 29.4-35.0) pre-March 2020 to 24.4% (95%CI 23.5-25.4) post-March 2020. The best-fitting model found that after March 2020 there was a 12-month decline before stabilising by June 2022 in social grade ABC1 at a lower level (~ 20%) and rebounding among social grade C2DE (~ 27%). Receipt of BIs for alcohol was low (overall: 4.1%, 95%CI 3.9-4.4) and the prevalence was similar pre- and post-March 2020. CONCLUSIONS: The receipt of BIs for smoking declined following March 2020 but rebounded among priority socioeconomic groups of people who smoked. BIs for alcohol among those who use alcohol at increasing and higher risk levels were low and there was no appreciable change over time. Maintaining higher BI delivery among socioeconomic and mental health priority groups of smokers and increasing and higher risk alcohol users is important to support reductions in smoking and alcohol related inequalities.

Who would be affected by a ban on disposable vapes? A population study in Great Britain.

OBJECTIVES: The UK government is consulting on banning disposable e-cigarettes. This study aimed to describe trends in disposable e-cigarette use among adults in Great Britain since 2021 and establish who would currently be affected by a ban on disposables. STUDY DESIGN: Nationally-representative monthly cross-sectional survey. METHODS: We analysed data from 69,973 adults surveyed between January 2021 and August 2023. We estimated monthly time trends in the weighted prevalence of current disposable e-cigarette use among adults and by sociodemographic characteristics and smoking status. RESULTS: From January 2021 to August 2023, the prevalence of disposable e-cigarette use grew from 0.1 % to 4.9 %. This rise was observed across all population subgroups but was most pronounced among younger adults (e.g. reaching 15.9 % of 18-year-olds compared with 1.3 % of 65-year-olds), those who currently smoke (16.3 %), and those who stopped smoking in the past year (18.2 %). Use among never smokers remained relatively rare (1.5 %), except among 18- to 24-year-olds (7.1 %). Use was significantly higher in England than Wales or Scotland (5.3 % vs. 2.0 % and 2.8 %) and among less (vs. more) advantaged social grades (6.1 % vs. 4.0 %), those with (vs. without) children (6.4 % vs. 4.4 %), and those with (vs. without) a history of mental health conditions (9.3 % vs. 3.1 %). CONCLUSIONS: A ban on disposable e-cigarettes would currently affect one in 20 adults in Great Britain (approximately 2.6 million people). The proportion who would be affected would be greatest among young people, including the 316,000 18-24 year-olds who currently use disposables but who have never regularly smoked tobacco, which may discourage uptake of vaping in this group. However, a ban would also affect 1.2 million people who currently smoke and a further 744,000 who previously smoked. It would also have a disproportionate impact on disadvantaged groups that have higher rates of smoking and typically find it harder to quit.

Prevalence and characteristics of co-occurrence of smoking and increasing-and-higher-risk drinking: A population survey in England.

BACKGROUND: Smoking and drinking alcohol both significantly contribute to mortality and morbidity, and there is a need to characterise the sociodemographic and health-related characteristics (e.g. mental distress) of people who do both in order to target resources. This study reports the prevalence and characteristics of adults in the general population in England who both drink alcohol at increasing-and-higher-risk levels and smoke. METHODS: We used cross-sectional data from a monthly, nationally representative survey of adults in England (n = 37,258; April 2020-March 2022). Weighted data were used to report prevalence and unweighted data were used to report descriptive statistics for sociodemographic and health-related characteristics. RESULTS: The prevalence of both smoking and increasing-and-higher-risk drinking was 4.6% (95% CI = 4.4-4.9; n = 1,574). They smoked a mean of 10.4 (SD = 8.86) cigarettes per day and had a mean AUDIT score of 12.8 (SD = 5.18). Nearly half (48.2%, n = 751) were trying to cut down on their smoking and 28.0% (n = 441) on their drinking. A quarter (25.3%, n = 397) had received General Practitioner advice on smoking while 8.7% (n = 76) had received advice on their drinking. Nearly half (48.6%, n = 745) reported experiencing psychological distress in the past month and 44.6% (n = 529) had a diagnosed mental health condition, both of which were higher than among all adults (28.1% and 29.1%, respectively). CONCLUSION: In England, from April 2020 to March 2022, the prevalence of both smoking and increasing-and-higher-risk drinking was 4.6%. This group appears to experience high rates of mental health problems and targeted support is needed.

Exploring changes in temporary abstinence in increasing and higher risk drinkers in England and Dry January participation in users of the Try Dry app in the UK between 2020 and 2021.

BACKGROUND: We looked at changes in the prevalence of increasing and higher risk drinkers reporting a reduction attempt motivated by temporary abstinence and changes in prevalence of use of the official app accompanying Dry January between 2020 vs 2021, following the onset of the COVID-19 pandemic. We also explored potential shifts in the sociodemographic composition of both groups. METHODS: We analysed data from: i) 1863 increasing and higher risk drinkers (defined as ≥ 8 on the AUDIT) responding to a nationally representative survey of adults in England in January and February 2020 and 2021, and ii) 104,598 users of the 'Try Dry' app, the official aid to those participating in Dry January 2020 and 2021 in the UK. We used logistic regression to examine shifts in the prevalence of increasing and higher risk drinkers reporting a reduction attempt motivated by temporary abstinence and explored whether there were shifts in the characteristics of this group in terms of AUDIT score, number of last year reduction attempts, smoking status, living alone, living with children, reducing alcohol consumption due to future health motives, age, sex, and occupational social grade between 2020 and 2021. We used t-tests and chi-squared tests to compare the prevalence of users of the 'Try Dry' app in 2020 and 2021 and examine whether the two groups differed in terms of age and sex. RESULTS: The proportion of increasing and higher risk drinkers reporting a reduction attempt motivated by temporary abstinence increased from 4% in 2020 to 8% in 2021 (OR = 2.07, 95% CI = 1.38-3.11, p < .001) with no changes detected in sociodemographic composition. The number of Try Dry app users in 2021 increased by 34.8% relative to 2020. App users in 2021 were two years older on average [p < .001, d = .02], with a 2% increase in the proportion of female app users [p < .001, vs. < .01]. CONCLUSIONS: Higher participation in Dry January 2021 relative to 2020 indicates increased engagement with a period of temporary abstinence following the COVID-19 related lockdowns in England and the UK, which is positive in the wider context of increasing alcohol consumption throughout the pandemic.

Characterising smoking and smoking cessation attempts by risk of alcohol dependence: A representative, cross-sectional study of adults in England between 2014-2021.

Background: There is a strong shared association between smoking tobacco and drinking alcohol. This study aimed to compare smoking prevalence and smoking characteristics in drinkers who were versus were not at risk of alcohol dependence in England. Methods: We used cross-sectional data from a monthly, nationally representative survey of adults in England (weighted n=144,583) collected between 2014-2021. Smoking and smoking cessation attempt characteristics were regressed on to alcohol dependence (drinkers at risk versus not at risk), adjusting for survey year. Findings: Past-year smoking prevalence was 63·3% (95% CI=59·7-66·8) among drinkers at risk of alcohol dependence compared with 18·7% (95% CI=18·4-18·9) among those not at risk, and 19·2% (95% CI=18·8-19·7) among non-drinkers. Among past-year smokers, drinkers at risk of alcohol dependence (versus not at risk) smoked more cigarettes per day (B=3·0, 95% CI=2·3-3·8) and were more likely to smoke their first cigarette within 5 (versus >60) minutes of waking (OR=2·81, 95% CI=2·25-3·51). Interpretation: In a representative sample of adults in England, a graded effect was observed where smoking prevalence increased with level of alcohol consumption. Past-year smokers at risk of alcohol dependence had higher levels of cigarette dependence than drinkers not at risk. Therefore, smokers at risk of alcohol dependence are a high priority group to target to reduce smoking prevalence as part of the NHS long-term plan. Funding: Cancer Research UK and the National Institute for Health Research.

Youth drinking in decline: What are the implications for public health, public policy and public debate?

Youth drinking has declined across most high-income countries in the last 20 years. Although researchers and commentators have explored the nature and drivers of decline, they have paid less attention to its implications. This matters because of the potential impact on contemporary and future public health, as well as on alcohol policy-making. This commentary therefore considers how youth drinking trends may develop in future, what this would mean for public health, and what it might mean for alcohol policy and debate. We argue that the decline in youth drinking is well-established and unlikely to reverse, despite smaller declines and stabilising trends in recent years. Young people also appear to be carrying their lighter drinking into adulthood in at least some countries. This suggests we should expect large short- and long-term public health benefits. The latter may however be obscured in population-level data by increased harm arising from earlier, heavier drinking generations moving through the highest risk points in the life course. The likely impact of the decline in youth drinking on public and policy debate is less clear. We explore the possibilities using two model scenarios, the reinforcement and withdrawal models. In the reinforcement model, a 'virtuous' circle of falling alcohol consumption, increasing public support for alcohol control policies and apparent policy successes facilitates progressive strengthening of policy, akin to that seen in the tobacco experience. In the withdrawal model, policy-makers turn their attention to other problems, public health advocates struggle to justify proposed interventions and existing policies erode over time as industry actors reassert and strengthen their partnerships with government around alcohol policy. We argue that disconnects between the tobacco experience and the reinforcement model make the withdrawal model a more plausible scenario. We conclude by suggesting some tentative ways forward for public health actors working in this space.

Clustering of health-related behaviours within children aged 11-16: a systematic review.

OBJECTIVE: We aimed to systematically review and synthesise evidence on the clustering of a broad range of health-related behaviours amongst 11-16 year olds. METHOD: A literature search was conducted in September 2019. Studies were included if they used cluster analysis, latent class analysis, prevalence odds ratios, principal component analysis or factor analysis, and considered at least three health-related behaviours of interest among 11-16 year olds in high-income countries. Health-related behaviours of interest were substance use (alcohol, cigarettes and other drug use) and other behavioural risk indicators (diet, physical activity, gambling and sexual activity). RESULTS: The review identified 41 studies, which reported 198 clusters of health-related behaviours of interest. The behaviours of interest reported within clusters were used to define eight behavioural archetypes. Some included studies only explored substance use, while others considered substance use and/or other health-related behaviours. Consequently, three archetypes were comprised by clusters reporting substance use behaviours alone. The archetypes were: (1) Poly-Substance Users, (2) Single Substance Users, (3) Substance Abstainers, (4) Substance Users with No/Low Behavioural Risk Indicators, (5) Substance Abstainers with Behavioural Risk Indicators, (6) Complex Configurations, (7) Overall Unhealthy and (8) Overall Healthy. CONCLUSION: Studies of youth health behavioural clustering typically find both a 'healthy' cluster and an 'unhealthy' cluster. Unhealthy clusters are often characterised by poly-substance use. Our approach to synthesising cluster analyses may offer a means of navigating the heterogeneity of method, measures and behaviours of interest in this literature.

Association of the COVID-19 lockdown with smoking, drinking and attempts to quit in England: an analysis of 2019-20 data.

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.

Trends in the psychosocial characteristics of 11-15-year-olds who still drink, smoke, take drugs and engage in poly-substance use in England.

INTRODUCTION AND AIMS: Youth substance use is declining in many high-income countries. As adolescent substance use becomes less common, it may concentrate in higher-risk groups. This paper aims to examine how the psychosocial characteristics of young substance users in England have changed over time. DESIGN AND METHODS: Annual cross-sectional data from the 2001-2014 Smoking, Drinking and Drug Use Among Young People in England survey are analysed (n = 112 792, age: 11-15). Logistic and Poisson regression analyses are used to test whether the sex, socioeconomic status (SES) and prevalence of truancy and exclusion from school of those who drink alcohol, smoke cigarettes, take cannabis, take other drugs and engage in poly-substance use changed across the study period. RESULTS: Use of all substances decreased and there were shifts in the psychosocial characteristics of young smokers, illicit drug users and poly-substance users. The proportion of current smokers and ever-users of cannabis of low SES and who had been excluded increased significantly between 2001/2003-2014. The proportion of last month drug users who had been excluded from school also increased significantly and there were increases in the proportion of polysubstance-users who had truanted and been excluded. The proportion of low SES alcohol users who had been excluded also increased significantly, but this change was very small. There was no evidence of substance use becoming more or less concentrated in one gender. DISCUSSION AND CONCLUSIONS: There is some evidence that smoking, illicit drug use and poly-substance use are becoming more concentrated in potentially at risk populations. There is limited evidence of concentration amongst young drinkers.

Trends in the sequence of first alcohol, cannabis and cigarette use in Australia, 2001-2016.

BACKGROUND: Recent analyses of data from the US found that young people were increasingly engaging in cannabis use before alcohol and cigarettes. These shifts are important for public health, but it is not clear whether such trends extend beyond the US. The aim of this study is to examine whether and how the age and sequencing of initiation into alcohol, cannabis and cigarette use has changed in Australia since the early 2000s. METHODS: Data came from six waves of the Australian National Drug Strategy Household Survey, spanning 2001-2016. We used data from 18 to 21 year-olds (n = 6849) and examined trends in the age at first use for each of the three substances plus any changes in the order of initiation. RESULTS: The mean age of initiation increased steadily for all three substances (e.g. from 14.9 in 2001 to 16.4 in 2016 for alcohol), while the prevalence of any use declined. There were some changes in ordering of use. For example, in 2001, 62 % of respondents who used both cigarettes and cannabis had first used cigarettes at an earlier age than cannabis, compared with 41 % in 2016. Young people who used both alcohol and cannabis remained more likely to try alcohol before cannabis across the study period. CONCLUSIONS: Our results partly replicated US findings, with differences potentially reflecting the substantially different environment around these substances in the US compared to Australia. The age of initiation for alcohol, cigarette and cannabis use in Australia has increased sharply over the past 15 years.

The decline in youth drinking in England-is everyone drinking less? A quantile regression analysis.

BACKGROUND AND AIMS: Youth alcohol consumption has declined significantly during the past 15 years in many high-income countries, which may have significant public health benefits. However, if the reductions in drinking occur mainly among lighter drinkers who are at lower risk, then rates of alcohol-related harm among young people today and adults in future may not fall in line with consumption. There is conflicting evidence from Swedish school studies, with some suggesting that all young people are drinking less, while others suggest that alcohol consumption among heavier drinkers may be stable or rising while average consumption declines. This paper extends the geographical focus of previous research and examines whether the decline in youth drinking is consistent across the consumption distribution in England. DESIGN: Quantile regression of 15 waves of repeat cross-sectional survey data. SETTING: England, 2001-16. PARTICIPANTS: A total of 31 882 schoolchildren (50.7% male) aged 11-15 who responded to the Smoking Drinking and Drug Use among Young People surveys. MEASUREMENTS: Past-week alcohol consumption in UK units at each fifth percentile of the consumption distribution. FINDINGS: Reductions in alcohol consumption occurred at all percentiles of the consumption distribution analysed between 2001 and 2016, but the magnitude of the decline differed across percentiles. The decline in consumption at the 90th percentile [ß = -0.21, confidence interval (CI) = -0.24, -0.18] was significantly larger than among either lighter drinkers at the 50th percentile (ß = -0.02, CI = -0.02, -0.01) or heavier drinkers at the 95th percentile (ß = -0.16, CI = -0.18, -0.13). CONCLUSIONS: Alcohol consumption among young people in England appears to be declining across the consumption distribution, and peaks among heavy drinkers. The magnitude of this decline differs significantly between percentiles of the consumption distribution, with consumption falling proportionally less among the lightest, moderate and very heaviest youth drinkers.

The psychosocial experience of feeling overweight promotes increased snack food consumption in women but not men.

Self-identification of being overweight has been associated with overeating and weight gain in observational studies, irrespective of whether the individual in question is objectively overweight. The aims of the present studies were to examine whether experimentally manipulating the psychosocial experience of feeling overweight impacted on snack food consumption and to identify mechanisms explaining this effect. In Study 1, to manipulate the psychosocial experience of feeling overweight, 120 women wore an obese body suit or control clothing in public or private settings, before consuming snack foods. Wearing the obese body suit resulted in an increase in snack food consumption and this effect was not moderated by whether participants wore the obese body suit in public or in private. In Study 2, we aimed to replicate the effect of the obese body suit on snack food consumption and also examined whether the effect of the body suit on eating behaviour was moderated by participant sex (n = 150; 80 women). Women who wore the obese body suit ate significantly more than women who wore the control clothing, but this effect was not observed in men. Across both studies we examined a number of potential mechanisms that could explain the effect that wearing the obese body suit had on snack food consumption, but did not find supporting evidence. The psychosocial experience of feeling overweight may lead to increased snack food consumption in women, but the psychological mechanism explaining this effect is unclear.