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Population-based health studies are critical resources for monitoring population health and related factors such as substance use, but reliable inference can be compromised in various ways. Non-response and attrition are major methodological problems which reduce power and can hamper the generalizability of findings if individuals who participate and who remain in a study differ systematically from those who do not. In this issue of SPPE, McCabe et al. studied participants of the 2001–2002 National Epidemiologic Survey on Alcohol and Related Conditions, comparing attrition in Wave 2 across participants with different patterns of substance use at Wave 1. The implications of differential follow-up and further possibilities for addressing selective participation are discussed.

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.

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.

ObjectiveTo examine trends in population exposure to secondhand smoke (SHS) and consider two exposure metrics as appropriate targets for tobacco control policy-makers.DesignComparison of adult non-smokers’ salivary cotinine data available from 11 Scottish Health Surveys between 1998 and 2016.MethodsThe proportions of non-smoking adults who had measurable levels of cotinine in their saliva were calculated for the 11 time points. The geometric mean (GM) concentrations of cotinine levels were calculated using Tobit regression. Changes in both parameters were assessed for the whole period and also for the years since implementation of smoke-free legislation in Scotland in 2006.ResultsSalivary cotinine expressed as a GM fell from 0.464 ng/mL (95% CI 0.444 to 0.486 ng/mL) in 1998 to 0.013 ng/mL (95% CI 0.009 to 0.020 ng/mL) in 2016: a reduction of 97.2%. The percentage of non-smoking adults who had no measurable cotinine in their saliva increased by nearly sixfold between 1998 (12.5%, 95% CI 11.5% to 13.6%) and 2016 (81.6%, 95% CI 78.6% to 84.6%). Reductions in population exposure to SHS have continued even after smoke-free legislation in 2006.ConclusionsScotland has witnessed a dramatic reduction in SHS exposure in the past two decades, but there are still nearly one in five non-smoking adults who have measurable exposure to SHS on any given day. Tobacco control strategies globally should consider the use of both the proportion of non-smoking adults with undetectable salivary cotinine and the GM as targets to encourage policies that achieve a smoke-free future.

Background Weight control is cited by some people, especially adolescent girls, as a reason for commencing smoking or not quitting. The aim of this study was to explore the relationship between smoking behaviour and being overweight or obese, overall and by age and sex sub-groups. Methods We used data from the six Scottish Health Surveys conducted to date (1995–2010) to undertake a population-based, cross-sectional study on 40,036 participants representative of the adult (≥16 years) Scottish population. Height and weight were measured by a trained interviewer, not self-reported. Results 24,459 (63.3%) participants were overweight (BMI ≥25 kg/m 2 ) and 9,818 (25.4%) were obese (BMI ≥30 kg/m 2 ). Overall, current smokers were less likely to be overweight than never smokers. However, those who had smoked for more than 20 years (adjusted OR 1.54, 95% CI 1.41-1.69, p < 0.001) and ex-smokers (adjusted OR 1.18, 95% CI 1.11-1.25, p < 0.001) were more likely to be overweight. There were significant interactions with age. Participants 16–24 years of age, were no more likely to be overweight if they were current (adjusted OR 1.01, 95% CI 0.84-1.20, p = 0.944) or ex (adjusted OR 0.88, 95% CI 0.67-1.14, p = 0.319) smokers. The same patterns pertained to obesity. Conclusions Whilst active smoking may be associated with reduced risk of being overweight among some older adults, there was no evidence to support the belief among young people that smoking protects them from weight gain. Making this point in educational campaigns targeted at young people may help to discourage them from starting to smoke.

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.

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.

Background Lung function successfully predicts subsequent health. Although lung function is known to decline over age, little is known about changes in association with socioeconomic status (SES) throughout life, and whether explanatory factors for association vary with age or patterns for non smokers. Methods Analyses were based on data on 24 500 participants aged ≥18 years from the 1995, 1998 and 2003 Scottish Health Surveys who were invited to provide 1 s forced expiratory volume (FEV1) and forced vital capacity (FVC) lung measurements. Sex-stratified multiple linear regression assessed lung function–SES (occupational social class) associations and attenuation by covariates in three age groups (2003 data (n=7928)). Results The FEV1–SES patterns were clear (p<0.001) and constant over time. Relative to the least disadvantaged, FEV1 in the most disadvantaged was lower by 0.28 L in men and 0.20 L in women under 40 years compared with differences of 0.51 L in men and 0.25 L in women over 64 years (pinteraction<0.001 men, pinteraction=0.004 women). The greatest attenuation of these results was seen by height, parental social class and smoking, especially among the under 65s. Second-hand smoke exposure and urban/rural residence had some impact among older groups. Adjusting for physical activity and weight had little effect generally. Similar patterns were seen for FVC and among never smokers. Conclusions We found cross-sectional evidence that SES disparity in lung function increases with age, especially for men. Our findings indicate that early-life factors may predict inequity during younger adulthood, with environmental factors becoming more important at older ages.

IntroductionSeveral studies have shown that residents of urban informal settlements/slums are usually excluded and marginalised from formal social systems and structures of power leading to disproportionally worse health outcomes compared to other urban dwellers. To promote health equity for slum dwellers, requires an understanding of how their lived realities shape inequities especially for young children 0–4 years old (ie, under-fives) who tend to have a higher mortality compared with non-slum children. In these proposed studies, we aim to examine how key Social Determinants of Health (SDoH) factors at child and household levels combine to affect under-five health conditions, who live in slums in Bangladesh and Kenya through an intersectionality lens.Methods and analysisThe protocol describes how we will analyse data from the Nairobi Cross-sectional Slum Survey (NCSS 2012) for Kenya and the Urban Health Survey (UHS 2013) for Bangladesh to explore how SDoH influence under-five health outcomes in slums within an intersectionality framework. The NCSS 2012 and UHS 2013 samples will consist of 2199 and 3173 under-fives, respectively. We will apply Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy approach. Some of SDoH characteristics to be considered will include those of children, head of household, mothers and social structure characteristics of household. The primary outcomes will be whether a child had diarrhoea, cough, fever and acute respiratory infection (ARI) 2 weeks preceding surveys.Ethics and disseminationThe results will be disseminated in international peer-reviewed journals and presented in events organised by the Accountability and Responsiveness in Informal Settlements for Equity consortium and international conferences. Ethical approval was not required for these studies. Access to the NCSS 2012 has been given by Africa Population and Health Center and UHS 2013 is freely available.

COVID-19 brings uncertainties and new precarities for communities and researchers, altering and amplifying relational vulnerabilities (vulnerabilities which emerge from relationships of unequal power and place those less powerful at risk of abuse and violence). Research approaches have changed too, with increasing use of remote data collection methods. These multiple changes necessitate new or adapted safeguarding responses. This practice piece shares practical learnings and resources on safeguarding from the Accountability for Informal Urban Equity hub, which uses participatory action research, aiming to catalyse change in approaches to enhancing accountability and improving the health and well-being of marginalised people living and working in informal urban spaces in Bangladesh, India, Kenya and Sierra Leone. We outline three new challenges that emerged in the context of the pandemic (1): exacerbated relational vulnerabilities and dilemmas for researchers in responding to increased reports of different forms of violence coupled with support services that were limited prior to the pandemic becoming barely functional or non-existent in some research sites, (2) the increased use of virtual and remote research methods, with implications for safeguarding and (3) new stress, anxiety and vulnerabilities experienced by researchers. We then outline our learning and recommended action points for addressing emerging challenges, linking practice to the mnemonic ‘the four Rs: recognise, respond, report, refer’. COVID-19 has intensified safeguarding risks. We stress the importance of communities, researchers and co-researchers engaging in dialogue and ongoing discussions of power and positionality, which are important to foster co-learning and co-production of safeguarding processes.