Aims: This study investigates the link between personal income and smoking among adolescents, and aims to answer the following questions: (i) to what extent is personal income related to smoking, independent of family socio‐economic status (SES) and (ii) does the association between personal income and smoking apply to different subpopulations?Design: Cross‐sectional study.Setting: Six cities from European countries (Amersfoort, the Netherlands; Coimbra, Portugal; Hannover, Germany; Latina, Italy; Namur, Belgium; Tampere, Finland) in 2013.Participants: A school‐based sample of 10 794 adolescents aged 14–17 years.Measurements: We modelled smoking experimentation, weekly smoking, daily smoking and (among daily smokers) smoking intensity as function of personal income, adjusting for age, sex, family SES, parental smoking and country. We tested interactions between personal income and covariates. Stratification analyses were performed for the variables for which interactions were significant.Findings: Adolescents in the highest income quintile were more likely to be smoking experimenters [odds ratio (OR) = 1.87; P < 0.01], weekly smokers (OR = 3.51; P < 0.01) and daily smokers (OR = 4.55; P < 0.01) than those in the lowest quintile. They also consumed more cigarettes per month (β = 0.79; P < 0.01). Adjusting for family SES did not modify the significance of relationships, and increased the magnitude of the association for daily smoking. None of the interactions between covariates and personal income was significant for smoking measures. For the intensity of smoking, the interaction was significant for SES. The stratified analysis showed a non‐significant association between smoking intensity and personal income among the oldest adolescents and those with the lowest SES background, while significant among younger and higher SES backgrounds.Conclusion: In the Netherlands, Portugal, Germany, Italy, Belgium and Finland, adolescents' personal income is related positively to smoking behaviours independent of family socio‐economic status (SES). However, among low socio‐economic status adolescent daily smokers, the association between the intensity of smoking and personal income is weaker.

In Western countries, smoking accounts for a large share of socio-economic inequalities in health. As smoking initiation occurs around the age of 13, it is likely that school context and social networks at school play a role in the origin of such inequalities. So far, there has been little generic explanation of how social ties at school contribute to socio-economic inequalities in smoking. The SILNE (Smoking Inequalities – Learning from Natural Experiments) survey was designed to test the hypothesis that a combination of peer effect, homophilous social ties, and school context may explain how smoking inequalities are magnified at school – a theory known as network-induced inequality. In this paper, the survey theory and design are presented. The social network survey was carried out in 2013 in six medium-sized European cities with average incomes similar to the national average: Namur (Belgium), Tampere (Finland), Hannover (Germany), Latina (Italy), Amersfoort (The Netherlands), and Coimbra (Portugal). In each city, 6 to 8 schools were selected in a stratified sampling procedure. In each school, two grades in secondary education, corresponding to 14-16-year-olds, were selected. All adolescents in these two grades were invited to participate in the survey. Social ties were reported using the roster approach, in which each adolescent had to nominate up to 5 friends from a directory. The survey collected information from 11,015 adolescents in 50 schools, out of a total of 13,870 registered adolescents, yielding a participation rate of 79%. The SILNE survey yielded 57,094 social ties, 86.7% of which referred to friends who also participated in the survey. The SILNE survey was designed to measure the association between adolescents’ social ties at school, their socio-economic background, and their smoking behaviour. Two difficulties were encountered, however: legal privacy constraints made it impossible to apply the same parental consent procedure in all countries, leading to somewhat lower participation rates in two cities: Hannover and Latina. It was also difficult to match the 6 cities in terms of both age and type of education. The SILNE survey provided a comparable database for the study of smoking inequalities across European cities from a social network perspective.

Background Although there is evidence for socioeconomic inequalities in health and health behaviour in adolescents, different indicators of socioeconomic status (SES) have rarely been compared within one data sample. We examined associations of five SES indicators with self-rated health (SRH) and smoking (ie, a leading cause of health inequalities) in Europe. Methods Data of adolescents aged 14–17 years old were obtained from the 2013 SILNE survey (smoking inequalities: learning from natural experiments), carried out in 50 schools in 6 European cities (N=10 900). Capturing subjective perceptions of relative SES and objective measures of education and wealth, we measured adolescents’ own SES (academic performance, pocket money), parental SES (parental educational level) and family SES (Family Affluence Scale, subjective social status (SSS)). Logistic regression models with SRH and smoking as dependent variables included all SES indicators, age and gender. Results Correlations between SES indicators were weak to moderate. Low academic performance (OR=1.96, 95% CI 1.53 to 2.51) and low SSS (OR=2.75, 95% CI 2.12 to 3.55) were the strongest indicators of poor SRH after adjusting for other SES-indicators. Results for SSS were consistent across countries, while associations with academic performance varied. Low academic performance (OR=5.71, 95% CI 4.63 to 7.06) and more pocket money (OR=0.21, 95% CI 0.18 to 0.26) were most strongly associated with smoking in all countries. Conclusions Socioeconomic inequalities in adolescent health were largest according to SES indicators more closely related to the adolescent’s education as well as the adolescent’s perception of relative family SES, rather than objective indicators of parental education and material family affluence. For future studies on adolescent health inequalities, consideration of adolescent-related SES indicators was recommended.

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 smoking.

To compare the clinical outcomes and cost-effectiveness of routine HIV screening in Portugal to the current practice of targeted and on-demand screening. We used Portuguese national clinical and economic data to conduct a model-based assessment. We compared current HIV detection practices to strategies of increasingly frequent routine HIV screening in Portuguese adults aged 18-69. We considered several subpopulations and geographic regions with varying levels of undetected HIV prevalence and incidence. Baseline inputs for the national case included undiagnosed HIV prevalence 0.16%, annual incidence 0.03%, mean population age 43 years, mean CD4 count at care initiation 292 cells/μL, 63% HIV test acceptance, 78% linkage to care, and HIV rapid test cost €6 under the proposed routine screening program. Outcomes included quality-adjusted survival, secondary HIV transmission, cost, and incremental cost-effectiveness. One-time national HIV screening increased HIV-infected survival from 164.09 quality-adjusted life months (QALMs) to 166.83 QALMs compared to current practice and had an incremental cost-effectiveness ratio (ICER) of €28,000 per quality-adjusted life year (QALY). Screening more frequently in higher-risk groups was cost-effective: for example screening annually in men who have sex with men or screening every three years in regions with higher incidence and prevalence produced ICERs of €21,000/QALY and €34,000/QALY, respectively. One-time HIV screening in the Portuguese national population will increase survival and is cost-effective by international standards. More frequent screening in higher-risk regions and subpopulations is also justified. Given Portugal’s challenging economic priorities, we recommend prioritizing screening in higher-risk populations and geographic settings.

Objectives Smoking contributes to socio-economic health inequalities; but it is unclear how smoking inequalities emerge at a young age. So far, little attention has been paid to the role of friendship ties. We hypothesised that the combination of peer exposure and friendship social homophily may contribute to socio-economic inequalities in smoking at school. Methods In 2013, a social network survey was carried out in 50 schools in six medium-size European cities (Namur, Tampere, Hanover, Latina, Amersfoort, and Coimbra). Adolescents in grades corresponding to the 14-to-16 age group were recruited (n = 11.015, participation rate = 79.4 %). We modelled adolescents’ smoking behaviour as a function of socio-economic background, and analysed the mediating role of social homophily and peer exposure. Results Lower socio-economic groups were more likely to smoke and were more frequently exposed to smoking by their close and distant friends, compared with adolescents of higher SES. The smoking risk of the lowest socio-economic group decreased after controlling for friends smoking and social homophily. Conclusions Smoking socio-economic inequalities amongst adolescents are driven by friendship networks.