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Abstract Background Today’s primary school children have grown up in a climate of strong smoking restrictions, decreasing tobacco use, and the emergence of e-cigarettes. Children’s exposure to tobacco declined substantially in years following the introduction of smoke-free legislation, with smoking uptake and perceived smoking norms declining. There is debate regarding whether emergence of e-cigarettes may interrupt trends in children’s smoking perceptions, or offer a means for adults to limit children’s exposure to tobacco. This study examines change in children’s tobacco and e-cigarettes experimentation (ever use), exposure to secondhand smoking and vaping, and perceived smoking norms. Methods Data from four, repeat cross-sectional surveys of Year 6 primary school pupils (age 10–11 years) in Wales in 2007, 2008, 2014 and 2019 (n = 6741) were combined. E-cigarette use and perceptions were included in 2014 and 2019 surveys. Analyses used binary logistic regression analyses, adjusted for school-level clustering. Results Child tobacco experimentation and most indicators of exposure to tobacco smoke indicated a graded decreasing trend over time from 2007 to 2019. Exposure to e-cigarettes increased from 2014 to 2019, as did pupil awareness of e-cigarettes (OR = 2.56, 95%CI = 2.12–3.10), and parental use (OR = 1.26, 95%CI = 1.00–1.57). A decrease in child e-cigarette experimentation was not significant (OR = 0.80, 95%CI = 0.57–1.13). Children’s normative perceptions for smoking by adults and children indicated a graded decrease over time (OR = 0.66, 95%CI = 0.54–0.80; OR = 0.69, 95%CI = 0.55–0.86; respectively from 2014 to 2019). However, fewer reported disapproval of people smoking around them in 2019 relative to 2014 (OR = 0.68, 95%CI = 0.53–0.88). Higher exposure to tobacco cigarettes and e-cigarettes in public places, cars and households were associated with favourable normative perceptions for tobacco smoking; however in models adjusted for exposure to both associations of e-cigarette exposure were attenuated. Conclusion Children’s experimentation with and exposure to tobacco, and their perceptions of smoking as a normative behaviour, have continued to decline alongside growth in exposure to e-cigarettes. Although a large majority of pupils reported they minded people smoking around them, there was some evidence of diminishing disapproval of secondhand smoke since 2007. Further research is needed to understand whether use of e-cigarettes in cars and homes is displacing prior smoking or being introduced into environments where smoking had been eliminated.

Abstract Background Health surveys provide a rich array of information but on relatively small numbers of individuals and evidence suggests that they are becoming less representative as response levels fall. Routinely collected administrative data offer more extensive population coverage but typically comprise fewer health topics. We explore whether data combination and multiple imputation of health variables from survey data is a simple and robust way of generating these variables in the general population. Methods We use the UK Integrated Household Survey and the English 2011 population census both of which included self-rated general health. Setting aside the census self-rated health data we multiply imputed self-rated health responses for the census using the survey data and compared these with the actual census results in 576 unique groups defined by age, sex, housing tenure and geographic region. Results Compared with original census data across the groups, multiply imputed proportions of bad or very bad self-rated health were not a markedly better fit than those simply derived from the survey proportions. Conclusion While multiple imputation may have the potential to augment population data with information from surveys, further testing and refinement is required.

Abstract Background Concerns remain about potential negative impacts of e-cigarettes including possibilities that: youth e-cigarette use (vaping) increases risk of youth smoking; and vaping by parents may have impacts on their children’s vaping and smoking behaviour. Methods With panel data from 3291 youth aged 10–15 years from the 7th wave of the UK Understanding Society Survey (2015–2017), we estimated effects of youth vaping on youth smoking (ever, current and past year initiation), and of parental vaping on youth smoking and vaping, and examined whether the latter differed by parental smoking status. Propensity weighting was used to adjust for measured confounders and estimate average effects of vaping for all youth, and among youth who vaped. E-values were calculated to assess the strength of unmeasured confounding influences needed to negate our estimates. Results Associations between youth vaping and youth smoking were attenuated considerably by adjustment for measured confounders. Estimated average effects of youth vaping on youth smoking were stronger for all youth (e.g. OR for smoking initiation: 32.5; 95% CI: 9.8–107.1) than among youth who vaped (OR: 4.4; 0.6–30.9). Relatively strong unmeasured confounding would be needed to explain these effects. Associations between parental vaping and youth vaping were explained by measured confounders. Estimates indicated effects of parental vaping on youth smoking, especially for youth with ex-smoking parents (e.g. OR for smoking initiation: 11.3; 2.7–46.4) rather than youth with currently smoking parents (OR: 1.0; 0.2–6.4), but these could be explained by relatively weak unmeasured confounding. Conclusions While measured confounding accounted for much of the associations between youth vaping and youth smoking, indicating support for underlying propensities, our estimates suggested residual effects that could only be explained away by considerable unmeasured confounding or by smoking leading to vaping. Estimated effects of youth vaping on youth smoking were stronger among the general youth population than among the small group of youth who actually vaped. Associations of parental vaping with youth smoking and vaping were either explained by measured confounding or could be relatively easily explained by unmeasured confounding.

Abstract Background Smoking contributes significantly to socioeconomic health inequalities. Vaping has captured much interest as a less harmful alternative to smoking, but may be harmful relative to non-smoking. Examining inequalities in vaping by smoking status, may offer insights into potential impacts of vaping on socioeconomic inequalities in health. Methods Data were from 3291 youth (aged 10–15) and 35,367 adults (aged 16+) from wave 7 (2015–17) of the UK Household Longitudinal Study. In order to adjust for biases that could be introduced by stratifying on smoking status, marginal structural models were used to estimate controlled direct effects of an index of socioeconomic disadvantage (incorporating household education, occupation and income) on vaping by smoking status (among adults and youth), adjusting for relevant confounders and for selection into smoking states. We also estimated controlled direct effects of socioeconomic disadvantage on being an ex-smoker by vaping status (among adult ever-smokers; n = 18,128). Results Socioeconomic disadvantage was associated with vaping among never smoking youth (OR for a unit increase in the socioeconomic index: 1.17; 95%: 1.03–1.34), and among ex-smoking adults (OR: 1.17; 95% CI: 1.09–1.26), with little to no association among never smoking (OR: 0.98; 95% CI: 0.91–1.07) and current smoking (OR: 1.00; 95% CI: 0.93–1.07) adults. Socioeconomic disadvantage was also associated with reduced odds of being an ex-smoker among adult ever-smokers, but this association was moderately weaker among those who vaped (OR: 0.88; 95% CI: 0.82–0.95) than those who did not (OR: 0.82; 95% CI: 0.80–0.84; p-value for difference = 0.081). Conclusions Inequalities in vaping among never smoking youth and adult ex-smokers, suggest potential to widen health inequalities, while weaker inequalities in smoking cessation among adult vapers indicate e-cigarettes could help narrow inequalities. Further research is needed to understand the balance of these opposing potential impacts, and how any benefits can be maximised whilst protecting the vulnerable.