Smoking and adolescence: Exploring tobacco consumption and related attitudes in three different age groups in Switzerland

The present study constitutes an investigation of tobacco consumption, related attitudes and individual differences in smoking or non-smoking behaviors in a sample of adolescents of different ages in the French-speaking part of Switzerland. We investigated three school-age groups (7th-grade, 9th-grade, and the second-year of high school) for differences in attitude and social and cognitive dimensions. We present both descriptive and inferential statistics. On an inferential level, we present a binary logistic regression-based model predicting risk of smoking. The resulting model most importantly suggests a strong relationship between smoking and alcohol consumption (both regular and sporadic). We interpret this result in terms of both the impact of the actual campaigns and the cognitive processes associated with adolescence.

Opinions on tobacco control policies in Lausanne, Switzerland, 2003-2006.

OBJECTIVE: To assess the determinants of opinions regarding tobacco control policies in the Swiss general population. METHODS: Cross-sectional study conducted between 2003 and 2006 on a random sample of adult residents of Lausanne, Switzerland, aged 35-75 years (2601 women and 2398 men). Nine questions on smoking policies were applied. RESULTS: Ninety-five percent of responders supported policies that would help smokers to quit, 92% no selling of tobacco to subjects aged less than 16 years, 87% a smoking ban in public places and 86% a national campaign against smoking. A further 77% supported a total ban on tobacco advertising, 74% the reimbursement of nicotine replacement therapies and 70% an increase in the price of cigarettes. A lower support was found for two non-evidence-based interventions total ban of tobacco sales (35%) and promotion of light cigarettes (22%). Never smokers, women, physically active subjects, teetotallers and subjects with lower educational level were more likely to favour stronger measures while no differences were found between age groups. Reimbursement of nicotine replacement therapies was favoured more by current smokers and inactive subjects. CONCLUSION: The vast majority of responders supported the recommended tobacco control policies. Opinions regarding specific interventions vary according to the policy and subjects' characteristics.

La prévention du tabagisme passif [Prevention of air pollution by indoor tobacco smoke in France]

A majority of smokers and non-smokers mind tobacco smoke. Passive smoking causes death by sudden infant death, lung cancer and coronary heart disease. 3000 to 6000 persons are killed every year in France. The lack of implementation of the Evin's law published in 1991 explains why non-smokers are not given the protection they can expect. The trend of scientific knowledge and of French and international public opinions support a growing demand for a complete protection of non-smokers with a total ban of smoking in all public or working places.

Interaction between tobacco and alcohol use and the risk of head and neck cancer: pooled analysis in the International Head and Neck Cancer Epidemiology Consortium.

BACKGROUND: The magnitude of risk conferred by the interaction between tobacco and alcohol use on the risk of head and neck cancers is not clear because studies have used various methods to quantify the excess head and neck cancer burden. METHODS: We analyzed individual-level pooled data from 17 European and American case-control studies (11,221 cases and 16,168 controls) participating in the International Head and Neck Cancer Epidemiology consortium. We estimated the multiplicative interaction parameter (psi) and population attributable risks (PAR). RESULTS: A greater than multiplicative joint effect between ever tobacco and alcohol use was observed for head and neck cancer risk (psi = 2.15; 95% confidence interval, 1.53-3.04). The PAR for tobacco or alcohol was 72% (95% confidence interval, 61-79%) for head and neck cancer, of which 4% was due to alcohol alone, 33% was due to tobacco alone, and 35% was due to tobacco and alcohol combined. The total PAR differed by subsite (64% for oral cavity cancer, 72% for pharyngeal cancer, 89% for laryngeal cancer), by sex (74% for men, 57% for women), by age (33% for cases <45 years, 73% for cases >60 years), and by region (84% in Europe, 51% in North America, 83% in Latin America). CONCLUSIONS: Our results confirm that the joint effect between tobacco and alcohol use is greater than multiplicative on head and neck cancer risk. However, a substantial proportion of head and neck cancers cannot be attributed to tobacco or alcohol use, particularly for oral cavity cancer and for head and neck cancer among women and among young-onset cases.

Perception of tobacco, cannabis, and alcohol use of others is associated with one's own use.

BACKGROUND: Interventions have been developed to reduce overestimations of substance use among others, especially for alcohol and among students. Nevertheless, there is a lack of knowledge on misperceptions of use for substances other than alcohol. We studied the prevalence of misperceptions of use for tobacco, cannabis, and alcohol and whether the perception of tobacco, cannabis, and alcohol use by others is associated with one's own use. METHODS: Participants (n=5216) in a cohort study from a census of 20-year-old men (N=11,819) estimated the prevalence of tobacco and cannabis use among peers of the same age and sex and the percentage of their peers drinking more alcohol than they did. Using the census data, we determined whether participants overestimated, accurately estimated, or underestimated substance use by others. Regression models were used to compare substance use by those who overestimated or underestimated peer substance with those who accurately estimated peer use. Other variables included in the analyses were the presence of close friends with alcohol or other drug problems and family history of substance use. RESULTS: Tobacco use by others was overestimated by 46.1% and accurately estimated by 37.3% of participants. Cannabis use by others was overestimated by 21.8% and accurately estimated by 31.6% of participants. Alcohol use by others was overestimated by more than half (53.4%) of participants and accurately estimated by 31.0%. In multivariable models, compared with participants who accurately estimated tobacco use by others, those who overestimated it reported smoking more cigarettes per week (incidence rate ratio [IRR] [95% CI], 1.17 [range, 1.05, 1.32]). There was no difference in the number of cigarettes smoked per week between those underestimating and those accurately estimating tobacco use by others (IRR [95% CI], 0.99 [range, 0.84, 1.17]). Compared with participants accurately estimating cannabis use by others, those who overestimated it reported more days of cannabis use per month (IRR [95% CI], 1.43 [range, 1.21, 1.70]), whereas those who underestimated it reported fewer days of cannabis use per month (IRR [95% CI], 0.62 [range, 0.23, 0.75]). Compared with participants accurately estimating alcohol use by others, those who overestimated it reported consuming more drinks per week (IRR [95% CI], 1.57 [range, 1.43, 1.72]), whereas those who underestimated it reported consuming fewer drinks per week (IRR [95% CI], 0.41 [range, 0.34, 0.50]). CONCLUSIONS: Perceptions of substance use by others are associated with one's own use. In particular, overestimating use by others is frequent among young men and is associated with one's own greater consumption. This association is independent of the substance use environment, indicating that, even in the case of proximity to a heavy-usage group, perception of use by others may influence one's own use. If preventive interventions are to be based on normative feedback, and their aim is to reduce overestimations of use by others, then the prevalence of overestimation indicates that they may be of benefit to roughly half the population; or, in the case of cannabis, to as few as 20%. Such interventions should take into account differing strengths of association across substances.

Modification de la composition des cigarettes durant te XXe siècle: rôle de l'industrie du tabac et effet sur la dépendance tabagique [Chemicals added to cigarettes and their effects on tobacco dependence]

This paper summarizes data on the factors involved in addiction and dependence to cigarettes. Nicotine has been intensively studied by the tobacco industry, for instance for its addictive effect at the lowest possible rates. The addition of diammonium phosphate and urea produces an alcalinization of the pH of cigarette smoke, and promotes the absorption and the trans-membrane passage of nicotine. The taste, the smell of smoke, and the visual aspect of the pack of cigarettes are also sensory components that promote addiction. Finally, menthol, sugar, cocoa and liquorice added to cigarettes also play a role in dependence and addiction to cigarettes by, for instance, making an anesthetic effect on the airways.

Assessing tobacco dependence among cannabis users smoking cigarettes.

INTRODUCTION: This study examines the relationship between nicotine exposure and tobacco addiction among young smokers consuming either only tobacco or only tobacco and cannabis. METHODS: Data on tobacco and cannabis use were collected by a questionnaire among 313 adolescents and young adults in Western Switzerland between 2009 and 2010. In addition, a urine sample was used to determine urinary cotinine level. Nicotine addiction was measured using the Fagerström Test for Nicotine Dependence (FTND). In this study, we focused on a sample of 142 participants (mean age 19.54) that reported either smoking only tobacco cigarettes (CIG group, n = 70) or smoking both tobacco cigarettes and cannabis (CCS group, n = 72). RESULTS: The FTND did not differ significantly between CIG (1.96 ± 0.26) and CCS (2.66 ± 0.26) groups (p = 0.07). However, participants in the CCS group smoked more cigarettes (8.30 ± 0.79 vs. 5.78 ± 0.8, p = 0.03) and had a higher mean cotinine value (671.18 ± 67.6 vs. 404.32 ± 68.63, p = 0.008) than the CIG group. Further, the association between cotinine and FTND was much stronger among the CIG than among the CCS group (regression coefficient of 0.0031 vs. 0.00099, p < 0.0001). CONCLUSION: Adolescents smoking tobacco and cannabis cigarettes featured higher levels of cotinine than youth smoking only tobacco; however, there was no significant difference in the addiction score. The FTND score is intended to measure nicotine dependence from smoked tobacco cigarettes. Hence, to accurately determine nicotine exposure and the associated dependence among young smokers, it seems necessary to inquire about cannabis consumption.

Cannabis and tobacco use: where are the boundaries? A qualitative study on cannabis consumption modes among adolescents.

The purpose of this article is to identify tobacco and cannabis co-consumptions and consumers' perceptions of each substance. A qualitative research including 22 youths (14 males) aged 15-21 years in seven individual interviews and five focus groups. Discussions were recorded, transcribed verbatim and transferred to Atlas.ti software for narrative analysis. The main consumption mode is cannabis cigarettes which always mix cannabis and tobacco. Participants perceive cannabis much more positively than tobacco, which is considered unnatural, harmful and addictive. Future consumption forecasts thus more often exclude tobacco smoking than cannabis consumption. A substitution phenomenon often takes place between both substances. Given the co-consumption of tobacco and cannabis, in helping youths quit or decrease their consumptions, both substances should be taken into account in a global approach. Cannabis consumers should be made aware of their tobacco use while consuming cannabis and the risk of inducing nicotine addiction through cannabis use, despite the perceived disconnect between the two substances. Prevention programs should correct made-up ideas about cannabis consumption and convey a clear message about its harmful consequences. Our findings support the growing evidence which suggests that nicotine dependence and cigarette smoking may be induced by cannabis consumption.

Second hand tobacco smoke exposure in Switzerland

A passive sampling device called Monitor of NICotine or "MoNIC", was constructed and evaluated by IST laboratory for determining nicotine in Second Hand Tobacco Smoke (SHTS) or Environmental Tobacco Smoke (ETS). Vapour nicotine was passively collected on a potassium bisulfate treated glass fibre filter as collection medium. Analysis of collected nicotine on the treated filter by gas chromatography equipped with Thermoionic-Specific Detector (GC-TSD) after liquid-liquid extraction of 1mL of 5N NaOH : 1 mL of n-heptane saturated with NH3 using quinoline as internal standard. Based on nicotine amount of 0.2 mg/cigarette as the reference, the inhaled Cigarette Equivalents (CE) by non-smokers can be calculated. Using the detected CE on the badge for non-smokers, and comparing with amount of nicotine and cotinine level in saliva of both smokers and exposed non-smokers, we can confirm the use of the CE concept for estimating exposure to ETS. The regional CIPRET (Center of information and prevention of the addiction to smoking) of different cantons (Valais (VS), Vaud (VD), Neuchâtel (NE) and Fribourg (FR)) are going to organize a big campaign on the subject of the passive addiction to smoking. This campaign took place in 2007-2008 and has for objective to inform clearly the Swiss population of the dangerousness of the passive smoke. More than 3'900 MoNIC badges were gracefully distributed to Swiss population to perform a self-monitoring of population exposure level to ETS, expressed in term of CE. Non-stimulated saliva was also collected to determine ETS biomarkers nicotine/cotinine levels of participating volunteers. Results of different levels of CE in occupational and non-occupational situations in relation with ETS were presented in this study. This study, unique in Switzerland, has established a base map on the population's exposure to SHTS. It underscored the fact that all the Swiss people involved in this campaign (N=1241) is exposed to passive smoke, from <0.2 cig/d (10.8%), 1-2 to more than 10 cig/d (89.2%). In the area of high exposure (15-38 cig/d), are the most workers in public restaurant, cafe, bar, disco. By monitoring ETS tracer nicotine and its biomarkers, salivary nicotine and cotinine, it is demonstrated that the MoNIC badge can serve as indicator of CE passive smoking. The MoNIC badge, accompanied with content of salivary nicotine/cotinine can serve as a tool of evaluation of the ETS passive smoking and contributes to supply useful data for future epidemiological studies. It is also demonstrated that the salivary nicotine (without stimulation) is a better biomarker of ETS exposure than cotinine.