Are political views related to smoking and support for tobacco control policies? A survey across 28 European countries.

Background: General political views are rarely considered when discussing public support for tobacco control policies and tobacco use. The aim of this study was to explore potential associations between political views, smoking and support for tobacco control policies. Methods: We analysed responses from 22,313 individuals aged ≥15 years from 28 European Union (EU) member states, who self-reported their political views (far-left [1-2 on a scale 1-10]; centre-left (3-4); centre (5-6); centre-right (7-8); and far-right (9-10) in wave 82.4 of the Eurobarometer survey in 2014. We ran multi-level logistic regression models to explore associations between political views and smoking, as well as support for tobacco control policies, adjusting for socio-demographic factors. Results: Compared to those placing themselves at the political centre, people with far-left political views were more likely to be current smokers (Odds Ratio [OR] = 1.13; 95% Confidence Interval [CI]: 1.01-1.26), while those in the centre-right were the least likely to smoke (OR = 0.84; 95% CI: 0.76-0.93). Similar associations were found for having ever been a smoker. Respondents on the left side of the political spectrum were more likely to support tobacco control policies and those on the centre-right were less likely to support them, as compared to those at the political centre, after controlling for smoking status. Conclusions: General political views may be associated not only with support for tobacco control policies, but even with smoking behaviours, which should be taken into account when discussing these issues at a population level. Further research is needed to explore the implications of these findings

Two year trends and predictors of e-cigarette use in 27 European Union member states

Objective: This study assessed changes in levels of ever use, perceptions of harm from e-cigarettes and socio-demographic correlates of use among EU adults during 2012-2014, as well as determinants of current use in 2014. Methods: We analysed data from the 2012 (n=26,751) and 2014 (n=26,792) waves of the adult Special Eurobarometer for Tobacco survey. Point prevalence of current and ever use were calculated and logistic regression assessed correlates of current use and changes in ever use and perception of harm. Correlates examined included age, gender, tobacco smoking, education, area of residence, difficulties in paying bills and reasons for trying an e-cigarette. Results: The prevalence of ever use of e-cigarettes increased from 7.2% in 2012 to 11.6% in 2014 (Adjusted Odds Ratio [aOR]=1.91). EU-wide coefficient of variation in ever e-cigarette use was 42.1% in 2012 and 33.4% in 2014. The perception that e-cigarettes are harmful increased from 27.1% in 2012 to 51.6% in 2014 (aOR=2.99), but there were major differences in prevalence and trends between member states. Among those who reported that they had ever tried an e-cigarette in the 2014 survey, 15.3% defined themselves as current users. Those who tried an e-cigarette to quit smoking were more likely to be current users (aOR=2.82). Conclusion: Ever use of e-cigarettes increased during 2012-2014. People who started using e-cigarettes to quit smoking tobacco were more likely to be current users, but the trends vary by country. These findings underscore the need for more research into factors influencing e-cigarette use and its potential benefits and harms

Geographic variation and socio-demographic determinants of the co-occurrence of risky health behaviours in 27 European Union member states.

BACKGROUND: Risky health behaviours such as tobacco and alcohol abuse, physical inactivity and poor diet may play an important role in disease development. The aim of the present study was to assess the geographical distribution and socio-demographic determinants of risky health-related behaviours in 27 member states (MSs) of the European Union (EU). METHODS: Data from the 2009 Eurobarometer survey (wave 72.3; n = 26 788) were analysed. Tobacco use, alcohol consumption, physical activity and fruit consumption were assessed through a self-reported questionnaire provided to participants from 27 EU MSs. Within the analyses, participants with three or more lifestyle risk factors were classified as individuals with co-occurrence of risk factors. RESULTS: Among respondents aged 15 or older, 28.2% had none of the aforementioned behavioural risk factors, whereas 9.9% had three or more lifestyle risk factors. Males [adjusted odds ratio (aOR) = 2.50; 95% confidence interval (95% CI): 2.17-2.88] and respondents of middle (aOR = 1.60; 95% CI: 1.36-1.89) or lower income (aOR = 2.63; 95% CI: 2.12-3.26) were more likely to report co-occurrence of behavioural risk factors, as well as respondents in Northern (aOR = 1.43; 95% CI: 1.14-1.78), Western (aOR = 1.28; 95% CI: 1.06-1.56) and Eastern Europe (aOR = 1.28; 95% CI: 1.06-1.55), when compared with Southern European respondents. CONCLUSIONS: The above analyses indicate significant geographical and social variation in the distribution of the co-occurrence of behavioural risk factors for disease development

Correlates of self-reported exposure to advertising of tobacco products and electronic cigarettes across 28 European Union member states.

BACKGROUND: Despite advertising bans in most European Union (EU) member states, outlets for promotion of tobacco products and especially e-cigarettes still exist. This study aimed to assess the correlates of self-reported exposure to tobacco products and e-cigarettee advertising in the EU. METHODS: We analysed data from wave 82.4 of the Eurobarometer survey (November-December 2014), collected through interviews in 28 EU member states (n=27 801 aged ≥15 years) and data on bans of tobacco advertising extracted from the Tobacco Control Scale (TCS, 2013). We used multilevel logistic regression to assess sociodemographic correlates of self-reported exposure to any tobacco and e-cigarette advertisements. RESULTS: 40% and 41.5% of the respondents reported having seen any e-cigarette and tobacco product advertisement respectively within the past year. Current smokers, males, younger respondents, those with financial difficulties, people who had tried e-cigarettes and daily internet users were more likely to report having seen an e-cigarette and a tobacco product advertisement. Respondents in countries with more comprehensive advertising bans were less likely to self-report exposure to any tobacco advertisements (OR 0.87; 95% CI 0.79 to 0.96 for one-unit increase in TCS advertising score), but not e-cigarette advertisements (OR 1.08; 95% CI 0.95 to 1.22). CONCLUSION: Ten years after ratification of the Framework Convention for Tobacco Control, self-reported exposure to tobacco and e-cigarette advertising in the EU is higher in e-cigarette and tobacco users, as well as those with internet access. The implementation of the Tobacco Products Directive may result in significant changes in e-cigarette advertising, therefore improved monitoring of advertising exposure is required in the coming years

Impact of tobacco control policies on smoking prevalence and quit ratios in 27 European Union countries from 2006-2014

Background: Smoking is still highly prevalent in Europe. According to the WHO, tobacco control policies vary substantially across countries. The Tobacco Control Scale (TCS) was developed to quantify the implementation of tobacco control policies at country level in Europe. The objective was to assess the impact of tobacco control policies (quantified by TCS scores) on smoking prevalence and quit ratios and their relative changes from 2006-2014 in 27 European Union (EU27) countries. Methods: We conducted an ecological study at the country level. We used TCS scores in EU27 in 2007, and the prevalence of tobacco and quit ratios (No. ex-smokers/ No. ever smokers) data from the Eurobarometer surveys (2006 and 2014 waves). We analysed the relationship between the TCS scores and smoking prevalence and quit ratios and their relative changes by means of scatter plots, Spearman rank-correlation coefficients (rsp), and a multiple linear regression model adjusted for all TCS components. Results: In EU27, the smoking prevalence decreased by 14% (95%CI:7.3%-20.6%) (2006-2014) and varied from a relative decrease of 48.9% in Sweden to 0.4% in Bulgaria. The increase in the quit ratio in EU27 was 19.2% (95%CI:5.4%-33.1%) (2006-2014) and ranged from 125.8% in Sweden to 4.3% in Bulgaria. The correlation between TCS scores and smoking prevalence was negative (rsp=-0.444;p=0.02). A positive correlation was observed between TCS scores and quit ratios in 2014 (rsp=0.373;p=0.06) and in the relative changes in smoking prevalence (rsp=0.415;p=0.03). The percentage of smoking prevalence in 2014 explained by all TCS components in the regression model was 28.9% Conclusions: European countries with higher TCS scores, which indicates higher tobacco control efforts, have lower prevalence of smokers, higher quit ratios, and higher relative decreases in their smoking prevalence over the last decade. Funding: EC Horizon2020 HCO-6-2015 (EUREST-PLUS No. 681109); Government of Spain & European Regional Development Fund (RTICC RD12/0036/0053); Government of Catalonia (2014SGR999)

Impact of tobacco control policies on smoking prevalence and quit ratios in 27 European Union countries from 2006 to 2014

BACKGROUND: Tobacco use is still highly prevalent in Europe, despite the tobacco control efforts made by the governments. The development of tobacco control policies varies substantially across countries. The Tobacco Control Scale (TCS) was introduced to quantify the implementation of tobacco control policies across European countries OBJECTIVE: To assess the midterm association of tobacco control policies on smoking prevalence and quit ratios among 27 European Union (EU) Member States (EU27). METHODS: Ecological study. We used the TCS in EU27 in 2007 and the prevalence of tobacco and quit ratios data from the Eurobarometer survey (2006 (n=27 585) and 2014 (n=26 793)). We analysed the relationship between the TCS scores and smoking prevalence and quit ratios and their relative changes (between 2006 and 2014) by means of scatter plots and multiple linear regression models. RESULTS: In EU27, countries with higher scores in the TCS, which indicates higher tobacco control efforts, have lower prevalence of smokers, higher quit ratios and higher relative decreases in their prevalence rates of smokers over the last decade. The correlation between TCS scores and smoking prevalence (rsp=-0.444; P=0.02) and between the relative changes in smoking prevalence (rsp=-0.415; P=0.03) was negative. A positive correlation was observed between TCS scores and quit ratios (rsp=0.373; P=0.06). The percentage of smoking prevalence explained by all TCS components was 28.9%. CONCLUSION: EU27 should continue implementing comprehensive tobacco control policies as they are key for reducing the prevalence of smoking and an increase tobacco cessation rates in their population

Electronic cigarette use in 12 European countries. Results from the TackSHS survey.

BACKGROUND: Limited data on electronic cigarette prevalence, patterns and settings of use are available from several European countries. METHODS: Within the TackSHS project, a face-to-face survey was conducted in 2017-2018 in 12 European countries (Bulgaria, England, France, Germany, Greece, Ireland, Italy, Latvia, Poland, Portugal, Romania and Spain). Overall, 11,876 participants, representative of the population aged ≥15 years in each country, provided information on electronic cigarette. RESULTS: 2.4% (95% confidence interval, CI: 2.2-2.7) of the subjects (2.5% among men and 2.4% among women; 0.4% among never, 4.4% among current- and 6.5% among ex-smokers) reported current use of electronic cigarette, ranging from 0.6% in Spain to 7.2% in England. Of the 272 electronic cigarette users, 52.6% were dual users (i.e., users of both electronic and conventional cigarettes) and 58.8% used liquids with nicotine. In all, 65.1% reported using electronic cigarette in at least one indoor setting where smoking is forbidden, in particular in workplaces (34.9%), and bars and restaurants (41.5%). Multivariable logistic regression analysis showed that electronic cigarette use was lower among older individuals (p for trend <0.001) and higher among individuals with high level of education (p for trend 0.040). Participants from countries with higher tobacco cigarette prices more frequently reported electronic cigarette use (odds ratio 3.62; 95% CI: 1.80-7.30). CONCLUSIONS: Considering the whole adult population of these 12 European countries, more than 8.3 million people use electronic cigarettes. The majority of users also smoked conventional cigarettes, used electronic cigarettes with nicotine and consumed electronic cigarettes in smoke-free indoor areas