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Additional file 1.

Supplemental material, sj-docx-1-sjp-10.1177_14034948211031383 for Adjustment for survey non-participation using record linkage and multiple imputation: A validity assessment exercise using the Health 2000 survey by Megan A. Mcminn, Pekka Martikainen, Tommi Härkänen, Hanna Tolonen, Joonas Pitkänen, Alastair H. Leyland and Linsay Gray in Scandinavian Journal of Public Health

Supplemental material, sj-docx-1-sjp-10.1177_14034948211031383 for Adjustment for survey non-participation using record linkage and multiple imputation: A validity assessment exercise using the Health 2000 survey by Megan A. Mcminn, Pekka Martikainen, Tommi Härkänen, Hanna Tolonen, Joonas Pitkänen, Alastair H. Leyland and Linsay Gray in Scandinavian Journal of Public Health

Additional file 1: Appendix.

Safeguarding is rapidly rising up the international development agenda, yet literature on safeguarding in related research is limited. This paper shares processes and practice relating to safeguarding within an international research consortium (the ARISE hub, known as ARISE). ARISE aims to enhance accountability and improve the health and well-being of marginalised people living and working in informal urban spaces in low-income and middle-income countries (Bangladesh, India, Kenya and Sierra Leone). Our manuscript is divided into three key sections. We start by discussing the importance of safeguarding in global health research and consider how thinking about vulnerability as a relational concept (shaped by unequal power relations and structural violence) can help locate fluid and context specific safeguarding risks within broader social systems. We then discuss the different steps undertaken in ARISE to develop a shared approach to safeguarding: sharing institutional guidelines and practice; facilitating a participatory process to agree a working definition of safeguarding and joint understandings of vulnerabilities, risks and mitigation strategies and share experiences; developing action plans for safeguarding. This is followed by reflection on our key learnings including how safeguarding, ethics and health and safety concerns overlap; the challenges of referral and support for safeguarding concerns within frequently underserved informal urban spaces; and the importance of reflective practice and critical thinking about power, judgement and positionality and the ownership of the global narrative surrounding safeguarding. We finish by situating our learning within debates on decolonising science and argue for the importance of an iterative, ongoing learning journey that is critical, reflective and inclusive of vulnerable people.

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.

Objectives: To examine whether during a period of\ud limited e-cigarette regulation and rapid growth in their\ud use, smoking began to become renormalised among\ud young people.\ud \ud Design: Interrupted time-series analysis of repeated\ud cross-sectional time-series data.\ud \ud Setting: Great Britain\ud \ud Participants: 248 324 young people aged\ud approximately 13 and 15 years, from three national\ud surveys during the years 1998–2015.\ud Intervention Unregulated growth of e-cigarette use\ud (following the year 2010, until 2015).\ud \ud Outcome measures: Primary outcomes were\ud prevalence of self-reported ever smoking and regular\ud smoking. Secondary outcomes were attitudes towards\ud smoking. Tertiary outcomes were ever use of cannabis\ud and alcohol.\ud \ud Results: In final models, no significant change was\ud detected in the pre-existing trend for ever smoking (OR\ud 1.01, CI 0.99 to 1.03). There was a marginally significant\ud slowing in the rate of decline for regular smoking (OR\ud 1.04, CI 1.00 to 1.08), accompanied by a larger slowing\ud in the rate of decline of cannabis use (OR 1.21, CI 1.18\ud to 1.25) and alcohol use (OR 1.17, CI 1.14 to 1.19). In\ud all models and subgroup analyses for smoking attitudes,\ud an increased rate of decline was observed after 2010\ud (OR 0.88, CI 0.86 to 0.90). Models were robust to\ud sensitivity analyses.\ud \ud Conclusions: There was a marginal slowing in the\ud decline in regular smoking during the period following\ud 2010, when e-cigarettes were emerging but relatively\ud unregulated. However, these patterns were not unique\ud to tobacco use and the decline in the acceptability of\ud smoking behaviour among youth accelerated during\ud this time. These analyses provide little evidence that\ud renormalisation of youth smoking was occurring during\ud a period of rapid growth and limited regulation of\ud e-cigarettes from 2011 to 2015.

Supplemental Digital Content is available in the text., Background: National surveys are used to capture US health trends and set clinical guidelines, yet the sampling frame often includes those in noninstitutional households, potentially missing those most vulnerable for poor health. Declining response rates in national surveys also represent a challenge, and existing inputs to survey weights have limitations. We compared mortality rates between those who respond to surveys and the general population over time. Methods: Survey respondents from 20 waves of the National Health Interview Survey from 1990 to 2009 who have been linked to death records through 31 December 2011 were included. For each cohort in the survey, we estimated their mortality rates along with that cohort’s mortality rate in the census population using vital statistics records, and differences were examined using Poisson models. Results: In all years, survey respondents had lower mortality rates compared with the general population when data were both weighted and unweighted. Among men, survey respondents in the weighted sample had 0.86 (95% confidence interval = 0.853, 0.868) times the mortality rate of the general population (among women, RR = 0.887; 95% confidence interval, 0.879, 0.895). Differences in mortality are evident along all points of the life course. Differences have remained relatively stable over time. Conclusion: Survey respondents have lower death rates than the general US population, suggesting that they are a systematically healthier source population. Incorporating nonhousehold samples and revised weighting strategies to account for sample frame exclusion and nonresponse may allow for more rigorous estimation of the US population’s health.

Background and aims:\ud \ud Analytical approaches to addressing survey non-participation bias typically only use demographic information to improve estimates. We applied a novel methodology which uses health information from data linkage to adjust for non-representativeness. We illustrate the method by presenting adjusted alcohol consumption estimates for Scotland.\ud Design:\ud \ud Data on consenting respondents to the Scottish Health Surveys (SHeSs) 1995-2010 were confidentially linked to routinely-collected hospital admission and mortality records. Synthetic observations representing non-respondents were created using general population data. Multiple imputation was performed to compute adjusted alcohol estimates given a range of assumptions about the missing data. Adjusted estimates of mean weekly consumption were additionally calibrated to per-capita alcohol sales data.\ud Setting:\ud \ud Scotland\ud Participants:\ud \ud 30,718 respondents to the SHeSs 1995-2010, aged 20-64 years.\ud Measurements:\ud \ud Weekly alcohol consumption, non-, binge- and problem-drinking.\ud Findings:\ud \ud Initial adjustment for non-response resulted in estimates of overall mean weekly consumption that were elevated by up to 15.1% [26.5 units (18.6 - 34.4)] compared with corrections based solely on socio-demographic data [22.5 (17.7 - 27.3)]; other drinking behaviour estimates were little changed. Under more extreme assumptions the overall difference was up to 53% and calibrating to sales estimates resulted in up to 87% difference. Increases were especially pronounced among males in deprived areas.\ud Conclusions:\ud \ud Use of routinely-collected health data to reduce bias arising from survey non-response resulted in higher alcohol consumption estimates among working age males in Scotland, with less impact for females. This new method of bias reduction can be generalised to other surveys to improve estimates of alternative harmful behaviours.

Background:\ud Alcohol-related mortality and morbidity are higher in socioeconomically disadvantaged populations. It is unclear if elevated harm reflects differences in consumption, reverse causation or greater risk of harm following similar consumption. We investigated whether the harmful effects differed by socioeconomic status accounting for alcohol consumption and other health-related factors.\ud Methods:\ud Alcohol consumption (weekly units and binge drinking) data (n=50,236; 429,986 person-years of follow-up) were linked to deaths, hospitalisations and prescriptions. The primary outcome was alcohol-attributable hospitalisation/death. The relationship between alcohol attributable harm and socioeconomic status was investigated for four measures (education level, social class, household income and area-based deprivation) using Cox proportional hazards models. The potential for alcohol consumption and other risk factors mediating the social patterning was explored. Downward social selection for high-risk drinkers (reverse causation) was tested by comparing change in area deprivation over time.\ud Findings:\ud Low socioeconomic status was consistently associated with markedly elevated alcohol-attributable harms, including after adjustment for weekly consumption, binge drinking, body mass index and smoking. There was evidence of effect modification: for example, relative to light drinkers living in advantaged areas, the hazard ratio for excessive drinkers was 6.75 (95% CI 5.09-8.93) in advantaged and 11.06 (95% CI 8.53-14.35) in deprived areas. We found little support for downward social selection.\ud Interpretation:\ud Disadvantaged social groups experience greater alcohol-attributable harms compared to the advantaged for given levels of alcohol consumption, even after accounting for different drinking patterns, obesity and smoking status at the individual level.

No abstract available.

Aim:\ud Response rates in health surveys have diminished over the last two decades, making it difficult to obtain reliable information on health and health-related risk factors in different population groups. This study compared cause-specific mortality and morbidity among survey respondents and different types of non-respondents to estimate alcohol-, drug- and smoking related mortality and morbidity among non-respondents.\ud \ud Design:\ud Prospective follow-up study of respondents and non-respondents in two cross-sectional health surveys.\ud \ud Setting:\ud Denmark.\ud Participants:\ud A total sample of 39,540 Danish citizens aged 16 or older.\ud \ud Measurements:\ud Register-based information on cause-specific mortality and morbidity at the individual level was obtained for respondents (n=28,072) and different types of non-respondents (refusals n=8,954; illness/disabled n=731, uncontactable n=1,593). Cox proportional hazards models were used to examine differences in alcohol-, drug- and smoking-related mortality and morbidity, respectively, in a 12 year follow-up period.\ud \ud Findings:\ud Overall, non-response was associated with a significantly increased hazard ratio of 1.56 (95% CI: 1.36–1.78) for alcohol-related morbidity, 1.88 (95% CI: 1.38-2.57) for alcohol-related mortality, 1.55 (95% CI: 1.27–1.88) for drug-related morbidity, 3.04 (95% CI: 1.57–5.89) for drug-related mortality and 1.15 (95% CI: 1.03–1.29) for smoking-related morbidity. The hazard ratio for smoking-related mortality also tended to be higher among non-respondents compared with respondents although no significant association was evident (HR: 1.14; 95% CI: 0.95-1.36). Uncontactable and ill/disabled non-respondents generally had a higher hazard ratio of alcohol-, drug- and smoking related mortality and morbidity compared with refusal non-respondents.\ud Conclusion:\ud Health survey non-respondents in Denmark have an increased hazard ratio of alcohol-, drug-, and smoking-related mortality and morbidity compared with respondents, which may indicate more unfavourable health behaviours among non-respondents.

Health surveys are an important resource for monitoring population health, but selective nonresponse may impede valid inference. This study aimed to assess nonresponse bias in a population-sampled health survey in Scotland, with a focus on alcohol-related outcomes. Nonresponse bias was assessed by examining whether rates of alcohol-related harm (i.e., hospitalization or death) and all-cause mortality among respondents to the Scottish Health Surveys (from 1995 to 2010) were equivalent to those in the general population, and whether the extent of any bias varied according to sociodemographic attributes or over time. Data from consenting respondents (aged 20–64 years) to 6 Scottish Health Surveys were confidentially linked to death and hospitalization records and compared with general population counterparts. Directly age-standardized incidence rates of alcohol-related harm and all-cause mortality were lower among Scottish Health Survey respondents compared with the general population. For all years combined, the survey-to-population rate ratios were 0.69 (95% confidence interval: 0.61, 0.76) for the incidence of alcohol-related harm and 0.89 (95% confidence interval: 0.83, 0.96) for all-cause mortality. Bias was more pronounced among persons residing in more deprived areas; limited evidence was found for regional or temporal variation. This suggests that corresponding underestimation of population rates of alcohol consumption is likely to be socially patterned.

Background Small yet significant impacts of e-cigarettes on population smoking cessations rates indicate promise for harm reduction. However, non-smoking young people are increasingly experimenting with e-cigarettes, and while regular use remains rare, arguments for regulation have been driven by fears that e-cigarettes re-normalize smoking. Others counter that e-cigarettes may displace youth smoking and further de-normalize it. This study tests whether the secular decline in youth smoking prevalence, as well as perceived smoking norms, slowed or accelerated during the period from 2011–2015 (when e-cigarettes were emerging but prior to recent moves to regulate their use).\ud \ud Methods Data were taken from the Smoking Drinking and Drug Use survey in England, Health Behaviour in School Aged Children/School Health Research Network surveys in Wales, and the Scottish Adolescents Lifestyle and Substance Use Surveys between 1998 and 2015, including 247,515 13 and 15 year-old respondents. Segmented regression analyses examined trends for smoking prevalence (ever smoking and weekly smoking) and perceived smoking norms, testing for change in trend from 2011–15. Falsifiability checks examined change in trends for alcohol use and cannabis use for the same period.\ud \ud Results In final models for the whole sample, there was no change in rate of decline for ever smoking (OR=1.01; CI 0.99 to 1.03), with a marginally significant slowing in the rate of decline for weekly smoking (OR=1.04; CI 1.00 to 1.08). This slowing decline in weekly smoking was however limited to groups for whom rates were declining prior to 2010 at a rate which could not be sustained (i.e. girls and 13 year olds), and occurred in a greater magnitude for other substances, including cannabis use (OR=1.21, CI 1.18 to 1.25) and alcohol use (OR=1.17; CI 1.14 to 1.19). There was consistent evidence across all subgroups of an increased rate of decline in the percentage of young people saying that smoking is ok (OR=0.83; CI 0.81 to 0.86).\ud \ud Conclusion We found no evidence that the growing prevalence of e-cigarette use has led to increased experimentation with smoking, and some evidence that young people’s perceptions against smoking as a normative behavior have hardened rather than softened. Although the decline in weekly smoking rates is slowing, this appears to reflect a floor effect and is of smaller magnitude than change in trend for other substances. While the idea that e-cigarettes renormalize smoking has been central to much policy debate surrounding regulation, these findings indicate no reason to believe that this renormalization is occurring.