Associations between tobacco control mass media campaign expenditure and smoking prevalence and quitting in England: a time series analysis

BACKGROUND: It has been established that mass media campaigns can increase smoking cessation rates, but there is little direct evidence estimating associations between government expenditure on tobacco control mass media campaigns and smoking cessation. This study assessed the association over 8 years between mass media expenditure in England and quit attempts, smoking cessation and smoking prevalence. METHODS: Autoregressive integrated moving average modelling with exogenous variables (ARIMAX) was applied to monthly estimates from the Smoking Toolkit Study between June 2008 and February 2016. We assessed the association between the trends in mass media expenditure and (1) quit attempts in the last two months, (2) quit success among those who attempted to quit and (3) smoking prevalence. Analyses were adjusted for trends in weekly spending on tobacco by smokers, tobacco control policies and the use of established aids to cessation. RESULTS: Monthly spending on mass media campaigns ranged from nothing to £2.4 million, with a mean of £465 054. An increase in mass media expenditure of 10% of the monthly average was associated with a 0.51% increase (of the average) in success rates of quit attempts (95% CI 0.10% to 0.91%, p=0.014). No clear association was detected between changes in mass media expenditure and changes in quit attempt prevalence (β=-0.03, 95% CI -2.05% to 2.00%, p=0.979) or smoking prevalence (β=-0.03, 95% CI -0.09% to 0.03%, p=0.299). CONCLUSION: Between 2008 and 2016, higher monthly expenditure on tobacco control mass media campaigns in England was associated with higher quit success rates

Impact of the 'Stoptober' smoking cessation campaign in England from 2012 to 2017: A quasi-experimental repeat cross-sectional study

INTRODUCTION: Since 2012, England has an annual 'Stoptober' campaign for collective smoking cessation. Our aim was to assess 1) overall impact of the Stoptober campaign on quit attempts over its first 6 years, 2) consistency of impact over the campaign years, and 3) the role of the campaign budget. // METHODS: We used data of 51,399 adult smokers and ex-smokers in 132 repeat cross-sectional monthly surveys in England, 2007-2017. In a quasi-experimental design, adjusted logistic regression analyses compared past-month quit attempt rate between 1) October and other months in the year, between 2007-2011 and 2012-2017, 2) October and other months, across years 2012-2017, and 3) October and other months, between high-budget (2012-2015) and low-budget Stoptober campaigns (2016-2017). Bayes factors (BF) differentiated insensitive data and absence of an effect. // RESULTS: 1) In 2012-2017, quit attempts were more prevalent in October vs. other months (OR:1.24, 95%CI:1.00-1.53), while similar in 2007-2011 (OR:0·95, 95%CI:0·76-1·18; BF=0·2); data were somewhat insensitive, but supported this difference (OR:1·30, 95%CI:0·97-1·75; BF=2·1). 2) In 2012-2017, quit attempt prevalence ranged from 3.1-8.5% in October and 5.0-7.3% in other months. The difference between October and other months was large in 2012 (absolute unadjusted difference of 3.3%; OR:1·92, 95%CI:1·23-2·98) and 2015 (3.1%; OR:1·84, 95%CI:1·14-2·95), but small in 2013-2014 and 2016-2017 (0·36<BF<1·02). 3) Data were somewhat insensitive but supported interaction with campaign budget (OR:1·50, 95%CI:0·92-2·44; BF=2·2). // DISCUSSION: In 2012-2017, there appears to have been an increase in past-month quit attempts during October in England. The increase was inconsistent across Stoptober campaigns and appears to have been greater when the campaign budget was higher. // IMPLICATIONS: Over the first 6 years of Stoptober campaigns, there appears to have been an overall increase in past month quit attempts during October in England, and the data imply that a sufficiently high budget contributes to greater impact of the Stoptober campaign. These findings encourage the further spread of the Stoptober campaign to other countries. Future research should clarify how increased quit attempts as a consequence of Stoptober translate into quit success and which of Stoptober's ingredients were most important in increasing quit attempts, especially among vulnerable groups

The role of parental smoking on adolescent smoking and its social patterning: a cross-sectional survey in six European cities

Background Several studies have observed socio-economic (SE) inequalities in smoking among adolescents, but its causes are not fully understood. This study investigates the association between parental and adolescent smoking, and whether this association is socially patterned. Methods We used data from a survey administered in 2013 to students aged 14-17 years old of six European cities (n = 10 526). Using multilevel mixed-effects logistic regression, we modelled the probability of being a daily smoker as a function of parental smoking and SE status. We tested whether the smoking association differed across social strata. Results The prevalence of parental smoking was higher in low SE status adolescents. Boys and girls were more likely to smoke if they have a father [boys: adjusted odds ratio (AOR) = 1.90, 95% CI = 1.47-2.46; girls: AOR = 1.42, 95% CI = 1.09-1.86] and mother (boys: AOR = 1.77, 95% CI = 1.35-2.31; girls: AOR = 3.36, 95% CI = 2.56-4.40) who smoked. Among boys, the odds of smoking when having a smoking parent were higher in lower SE classes. However, this was not statistically significant, nor was it observed among girls. Conclusions Adolescents are more likely to smoke when their father and mother smoke. Although the susceptibility to parental smoking was similar across social classes, SE differences in parental smoking contribute to the transmission of SE inequalities in smokin

Relationship between alcohol-attributable disease and socioeconomic status, and the role of alcohol consumption in this relationship: a systematic review and meta-analysis

Background: Studies show that alcohol consumption appears to have a disproportionate impact on people of low socioeconomic status. Further exploration of the relationship between alcohol consumption, socioeconomic status and the development of chronic alcohol-attributable diseases is therefore important to inform the development of effective public health programmes. Methods: We used systematic review methodology to identify published studies of the association between socioeconomic factors and mortality and morbidity for alcohol-attributable conditions. To attempt to quantify differences in the impact of alcohol consumption for each condition, stratified by SES, we (i) investigated the relationship between SES and risk of mortality or morbidity for each alcohol-attributable condition, and (ii) where, feasible explored alcohol consumption as a mediating or interacting variable in this relationship. Results: We identified differing relationships between a range of alcohol-attributable conditions and socioeconomic indicators. Pooled analyses showed that low, relative to high socioeconomic status, was associated with an increased risk of head and neck cancer and stroke, and in individual studies, with hypertension and liver disease. Conversely, risk of female breast cancer tended to be associated with higher socioeconomic status. These findings were attenuated but held when adjusted for a number of known risk factors and other potential confounding factors. A key finding was the lack of studies that have explored the interaction between alcohol-attributable disease, socioeconomic status and alcohol use. Conclusions: Despite some limitations to our review, we have described relationships between socioeconomic status and a range of alcohol-attributable conditions, and explored the mediating and interacting effects of alcohol consumption where feasible. However, further research is needed to better characterise the relationship between socioeconomic status alcohol consumption and alcohol-attributable disease risk so as to gain a greater understanding of the mechanisms and pathways that influence the differential risk in harm between people of low and high socioeconomic status