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BackgroundTobacco consumption is the largest avoidable health risk. Understanding changes of smoking over time and across populations is crucial to implementing health policies. We evaluated trends in smoking initiation between 1970 and 2009 in random samples of European populations.MethodsWe pooled data from six multicentre studies involved in the Ageing Lungs in European Cohorts consortium, including overall 119,104 subjects from 17 countries (range of median ages across studies: 33-52 years). We estimated retrospectively trends in the rates of smoking initiation (uptake of regular smoking) by age group, and tested birth cohort effects using Age-Period-Cohort (APC) modelling. We stratified all analyses by sex and region (North, East, South, West Europe).ResultsSmoking initiation during late adolescence (16-20 years) declined for both sexes and in all regions (except for South Europe, where decline levelled off after 1990). By the late 2000s, rates of initiation during late adolescence were still high (40-80 per 1000/year) in East, South, and West Europe compared to North Europe (20 per 1000/year). Smoking initiation rates during early adolescence (11-15 years) showed a marked increase after 1990 in all regions (except for North European males) but especially in West Europe, where they reached 40 per 1000/year around 2005. APC models supported birth cohort effects in the youngest cohorts.ConclusionSmoking initiation is still unacceptably high among European adolescents, and increasing rates among those aged 15 or less deserve attention. Reducing initiation in adolescents is fundamental, since youngsters are particularly vulnerable to nicotine addiction and tobacco adverse effects.

In this study we aimed at identifying main demographic, laboratory and environmental factors influencing the level of urinary biomarkers (DNA-derived 8-oxodG and lipid membrane-derived 8-isoprostane), and deriving their adjusted 95% reference intervals (RI) in a sample of healthy people from the general population. Data from 281 healthy subjects from the Gene Environment Interactions in Respiratory Diseases survey were used in this study. Generalized additive models for location, scale and shape (GAMLSS) were used to find determinants of the biomarkers among gender, age, season and distance from collection (DFC), and to predict their RI. The RI of the biomarkers stratified by season and adjusted for DFC showed a slight statistically significant decrease in the biomarkers at the increasing DFC in two seasons, except the 8-oxodG during the warm season: median levels at the min and max values of DFC were (ng/mgcreat) 7.0-1.1 in the cold and 3.9-3.9 in the warm seasons for 8-oxodG, 0.7-0.2 in the cold and 1.3-0.6 in the warm seasons for 8-isoprostane. Both the biomarkers should be evaluated in association with the DFC and season in large epidemiological studies. The (semi)parametric GAMLSS method is a useful and flexible technique, which makes it possible to estimate adjusted RI.