'S'-shaped curve: modelling trends in smoking prevalence, uptake and cessation in Great Britain from 1973 to 2016

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.

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.

Trends in smoking prevalence in urban and rural China, 2007 to 2018: Findings from 5 consecutive nationally representative cross-sectional surveys

BACKGROUND

Tobacco smoking is a leading cause of premature death in China, especially among adult men. Since the implementation of the Framework Convention on Tobacco Control in 2005, nationwide tobacco control has been strengthened, but its long-term impact on smoking prevalence is unclear.

METHODS AND FINDINGS

Five nationally representative surveys of the China Chronic Disease and Risk Factor Surveillance (CCDRFS) were conducted in 2007, 2010, 2013, 2015, and 2018. A total of 624,568 adults (278,605 men and 345,963 women) aged 18 to 69 years were randomly selected from 31 provinces (or equivalent) in China. Temporal changes in smoking prevalence and patterns (e.g., percentages of those smoking manufactured cigarettes, amount smoked, and age at smoking initiation) were analyzed, overall and by sex, urban or rural residence, year of birth, education and occupation, using linear regression methods. Among men, the standardized prevalence of current smoking decreased from 58.4% (95% confidence interval [CI]: 56.1 to 60.7) to 50.8% (95% CI: 49.1 to 52.5, p < 0.001) between 2007 and 2018, with annual decrease more pronounced in urban (55.7% [95% CI: 51.2 to 60.3] to 46.3% [95% CI: 43.7 to 49.0], p < 0.001) than rural men (59.9% [95% CI: 57.5 to 62.4] to 54.6% [95% CI: 52.6 to 56.6], p = 0.05) and in those born before than after 1980. Among rural men born after 1990, however, the prevalence increased from 40.2% [95% CI: 34.0 to 46.4] to 52.1% ([95% CI: 45.7 to 58.5], p = 0.007), with the increase taking place mainly before 2015. Among women, smoking prevalence remained extremely low at around 2% during 2007 to 2018. No significant changes of current smoking prevalence (53.9% to 50.8%, p = 0.22) were observed in male patients with at least 1 of major chronic diseases (e.g., hypertension, diabetes, myocardial infarction, stroke, chronic obstructive pulmonary disease (COPD)). In 2018, 25.6% of adults aged ≥18 years smoked, translating into an estimated 282 million smokers (271 million men and 11 million women) in China. Across 31 provinces, smoking prevalence varied greatly. The 3 provinces (Yunnan, Guizhou, and Hunan) with highest per capita tobacco production had highest smoking prevalence in men (68.0%, 63.4%, and 61.5%, respectively), while lowest prevalence was observed in Shanghai (34.8%). Since the children and teenage groups were not included in the surveys, we could not assess the smoking trends among youths. Furthermore, since the smoking behavior was self-reported, the smoking prevalence could be underestimated due to reporting bias.

CONCLUSIONS

In this study, we observed that the smoking prevalence has decreased steadily in recent decades in China, but there were diverging trends between urban and rural areas, especially among men born after 1980. Future tobacco control strategies should target rural young men, regions with high tobacco production, and patients suffering from chronic diseases.

Understanding long-term trends in smoking in England, 1972-2019: an age-period-cohort approach

BACKGROUND AND AIMS

Smoking prevalence has been falling in England for more than 50 years, but remains a prevalent and major public health problem. This study used an age-period-cohort (APC) approach to measure lifecycle, historical and generational patterns of individual smoking behaviour.

DESIGN

APC analysis of repeated cross-sectional smoking prevalence data obtained from three nationally representative surveys.

SETTING

England (1972-2019).

PARTICIPANTS

Individuals aged 18-90 years.

MEASUREMENTS

We studied relative odds of current smoking in relation to age in single years from 18 to 90, 24 groups of 2-year survey periods (1972-73 to 2018-19) and 20 groups of 5-year birth cohorts (1907-11 to 1997-2001). Age and period rates were studied for two groups of birth cohorts: those aged 18-25 years and those aged over 25 years.

FINDINGS

Relative to age 18, the odds of current smoking increased with age until approximately age 25 [odds ratio (OR) = 1.48, 95% confidence interval (CI) = 1.41-1.56] and then decreased progressively to age 90 (OR = 0.06, 95% CI = 0.04-0.08). They also decreased almost linearly with period relative to 1972-73 (for 2018-19: OR = 0.30, 95% CI = 0.26-0.34) and with birth cohort relative to 1902-06, with the largest decreased observed for birth cohort 1992-96 (OR = 0.44, 95% CI = 0.35-0.46) and 1997-2001 (OR = 0.35, 95% CI = 0.74-0.88). Smoking declined in the 18-25 age group by an average of 7% over successive 2-year periods and by an average of 5% in those aged over 25.

CONCLUSIONS

Smoking in England appears to have declined over recent decades mainly as a result of reduced smoking uptake before age 25, and to a lesser extent to smoking cessation after age 25.

Inequalities in Smoking and Quitting-Related Outcomes Among Adults With and Without Children in the Household 2013-2019: A Population Survey in England

INTRODUCTION

Smoking among those who live with children is an important influence on smoking initiation among children. This study assessed socioeconomic inequalities in smoking and quitting-related outcomes among all adults with and without children in the household.

AIMS AND METHODS

Monthly repeat cross-sectional household survey of adults (16+) from 2013-2019 in England (N = 138 583). We assessed the association between cigarette smoking and quitting-related outcomes and having children in the household, and whether these relationships were moderated by occupational social grade (categories AB-E from most to least advantaged). Trends in smoking prevalence among adults with and without children in the household were explored.

RESULTS

In adjusted analysis, the association of having children in the household with smoking prevalence depended on social grade: smoking prevalence was between 0.71 (95% confidence interval 0.66-0.77) and 0.93 (0.88-0.98) times lower among social grades AB-D with children in the household relative to those without. Conversely, it was 1.11 (1.05-1.16) times higher among social grade E. Yearly prevalence declined similarly among those with and without children (both prevalence ratio: 0.98, 95% confidence interval 0.97-0.99). Motivation to stop smoking was higher among those with children than those without, but lower among disadvantaged than more advantaged groups. Social grades D-E had greater heavy smoking, but higher prevalence of past-month quit attempts.

CONCLUSIONS

Among the most disadvantaged social grade in England, smoking prevalence was higher in those with children in the household than without. To attenuate future smoking-related inequalities, there is an urgent need to target support and address barriers to quitting and promote longer-term quit success.

IMPLICATIONS

In the most disadvantaged occupational social grade, having children in the household was associated with higher smoking prevalence compared with not having children. This contrasts with all other social grades in which there was lower comparative smoking prevalence among those with than without children in the household. Without attention this disparity could exacerbate existing and future health inequalities related to smoking.

COVID-19, smoking and inequalities: a study of 53 002 adults in the UK

BACKGROUND

This study aimed to examine associations between smoking and COVID-19 relevant outcomes, taking into account the influence of inequalities and adjusting for potential confounding variables.

METHODS

Cross-sectional data were used from an online study of adults in the UK (n=53 002). Main outcome measures were confirmed and suspected COVID-19, worry about catching or becoming seriously ill from COVID-19 and adherence to protective behaviours. Covariates included age, sex, ethnicity, education (post-16 qualifications: yes/no), key worker status and comorbid health conditions.

RESULTS

Compared with never smokers (0.26% (95% CI 0.21% to 0.33%)), prevalence of confirmed COVID-19 was higher among current (0.56% (0.41% to 0.75%)) but not ex-smokers (0.19% (0.13% to 0.28%)). Associations were similar before (current: OR=2.14 (1.49-3.08); ex-smokers: OR=0.73 (0.47-1.14)) and after (current: OR=1.79 (1.22-2.62); ex-smokers: OR=0.85 (0.54-1.33)) adjustment. For current smokers, this was moderated by socio-economic position, with higher rates only seen in those without post-16 qualifications (OR=3.53 (2.04-6.10)). After including suspected cases, prevalence was higher among current smokers (11.2% (10.6% to 11.9%), OR=1.11 (1.03-1.20)) and ex-smokers (10.9% (10.4% to 11.5%), OR=1.07 (1.01-1.15)) than never smokers (10.2% (9.9% to 10.6%)), but remained higher only among ex-smokers after adjustment (OR=1.21 (1.13-1.29)). Current and ex-smokers had higher odds than never smokers of reporting significant stress about becoming seriously ill from COVID-19 (current: OR=1.34 (1.27-1.43); ex-smokers: OR=1.22 (1.16-1.28)). Adherence to recommendations to prevent spread of COVID-19 was high (96.3% (96.1% to 96.4%)), but lower among current than never smokers (OR=0.70 (0.62-0.78)).

CONCLUSIONS

In a population sample, current smoking was independently associated with self-reported confirmed COVID-19 infection. There were socio-economic disparities, with the association only apparent among those without post-16 qualifications. Smokers reported lower adherence to guidelines despite being more worried than non-smokers about catching or becoming seriously ill from COVID-19.

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.