195 resultados para Indoor smoking ban


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It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.

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BACKGROUND: A possible strategy for increasing smoking cessation rates could be to provide smokers who have contact with healthcare systems with feedback on the biomedical or potential future effects of smoking, e.g. measurement of exhaled carbon monoxide (CO), lung function, or genetic susceptibility to lung cancer. We reviewed systematically data on smoking cessation rates from controlled trials that used biomedical risk assessment and feedback. OBJECTIVES: To determine the efficacy of biomedical risk assessment provided in addition to various levels of counselling, as a contributing aid to smoking cessation. SEARCH STRATEGY: We systematically searched he Cochrane Collaboration Tobacco Addiction Group Specialized Register, Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (1966 to 2004), and EMBASE (1980 to 2004). We combined methodological terms with terms related to smoking cessation counselling and biomedical measurements. SELECTION CRITERIA: Inclusion criteria were: a randomized controlled trial design; subjects participating in smoking cessation interventions; interventions based on a biomedical test to increase motivation to quit; control groups receiving all other components of intervention; an outcome of smoking cessation rate at least six months after the start of the intervention. DATA COLLECTION AND ANALYSIS: Two assessors independently conducted data extraction on each paper, with disagreements resolved by consensus. MAIN RESULTS: From 4049 retrieved references, we selected 170 for full text assessment. We retained eight trials for data extraction and analysis. One of the eight used CO alone and CO + Genetic Susceptibility as two different intervention groups, giving rise to three possible comparisons. Three of the trials isolated the effect of exhaled CO on smoking cessation rates resulting in the following odds ratios (ORs) and 95% confidence intervals (95% CI): 0.73 (0.38 to 1.39), 0.93 (0.62 to 1.41), and 1.18 (0.84 to 1.64). Combining CO measurement with genetic susceptibility gave an OR of 0.58 (0.29 to 1.19). Exhaled CO measurement and spirometry were used together in three trials, resulting in the following ORs (95% CI): 0.6 (0.25 to 1.46), 2.45 (0.73 to 8.25), and 3.50 (0.88 to 13.92). Spirometry results alone were used in one other trial with an OR of 1.21 (0.60 to 2.42).Two trials used other motivational feedback measures, with an OR of 0.80 (0.39 to 1.65) for genetic susceptibility to lung cancer alone, and 3.15 (1.06 to 9.31) for ultrasonography of carotid and femoral arteries performed in light smokers (average 10 to 12 cigarettes a day). AUTHORS' CONCLUSIONS: Due to the scarcity of evidence of sufficient quality, we can make no definitive statements about the effectiveness of biomedical risk assessment as an aid for smoking cessation. Current evidence of lower quality does not however support the hypothesis that biomedical risk assessment increases smoking cessation in comparison with standard treatment. Only two studies were similar enough in term of recruitment, setting, and intervention to allow pooling of data and meta-analysis.

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PURPOSE: The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. METHODS: We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. RESULTS: Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. CONCLUSIONS: IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.

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Résumé Objectifs : Alors que de nombreuses études suggèrent que l'exposition au tabagisme passif représente un danger pour la santé des non-fumeurs, la plupart des études s'intéressant aux effets néfastes du tabagisme passif sur la santé respiratoire de sujets adultes étaient des études transversales. Les résultats d'études longitudinales restent rares et controversés. Le but de notre étude était de mesurer les effets d'une exposition antérieure au tabagisme passif sur l'évolution journalière de quatre catégories de symptômes respiratoires dans une étude journalière incluant des adultes n'ayant jamais fumé. Méthodes : Dans le cadre de l'étude SAPALDIA (Swiss study on air pollution and lung diseases in adults), nous avons mené une étude de cohorte prospective et multicentrique. 1421 adultes n'ayant jamais fumé étaient suivis durant deux ans sur la base de questionnaires journaliers remplis durant une à six périodes de quatre semaines répartis sur deux années (1992-1993). Nous avons ensuite déterminé le risque relatif (RR) de développer ou de s'amender de symptômes respiratoires en association avec une exposition antérieure au tabagisme passif. Résultats : Dans un échantillon d'adultes n'ayant jamais fumé, nous avons trouvé une association entre une exposition antérieure au tabagisme passif et une évolution péjorée de tous les symptômes respiratoires étudiés, montrant un risque relatif de 1.09 à 1.21 de développer les symptômes respiratoires, et un risque relatif de 0.91 à 0.83 de s'amender de ces symptômes. Une exposition au tabagisme passif sur la place de travail était associée à une diminution de la durée des intervalles libres sans symptômes bronchitiques (RR 1.33) et asthmatiques (RR 1.27), alors qu'une exposition uniquement en-dehors de la place de travail était associée avec un allongement de la durée des épisodes avec symptômes respiratoires des voies aériennes hautes ou basses (RR 0.78-0.77). Conclusion : Nos résultats suggèrent que l'exposition au tabagisme passif a des effets néfastes sur la dynamique journalière symptômes respiratoires, et que l'importance et le type d'effet sont influencés par le lieu d'exposition.

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Plasma levels of clozapine and olanzapine are lower in smokers than in nonsmokers, which is mainly due to induction of cytochrome P4501A2 (CYP1A2) by some smoke constituents. Smoking cessation in patients treated with antipsychotic drugs that are CYP1A2 substrates may result in increased plasma levels of the drug and, consequently, in adverse drug effects. Two cases of patients who smoked tobacco and cannabis are reported. The first patient, who was receiving clozapine treatment, developed confusion after tobacco and cannabis smoking cessation, which was related to increased clozapine plasma levels. The second patient, who was receiving olanzapine treatment, showed important extrapyramidal motor symptoms after reducing his tobacco consumption. The clinical implication of these observations is that smoking patients treated with CYP1A2 substrate antipsychotics should regularly be monitored with regard to their smoking consumption in order to adjust doses in cases of a reduction or increase in smoking.

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Purpose: To assess the relation between cannabis and tobacco consumption among adolescents in Switzerland and whether cannabis and tobacco co-users can quit cigarette smoking. Methods: Based on individual interviews and focus groups, 22 youths aged 15-20 discussed cannabis consumption behaviours. Twenty (14 males) were cannabis consumers - of which 18 also smoked tobacco and 2 quit tobacco smoking - and 2 were former cannabis consumers (both females and daily smokers). Data were transcribed verbatim and analyzed using Atlas.ti qualitative analysis software. Results: Among the co-consumers, 9 started with tobacco, 7 with cannabis, and 2 with both. The main consumption mode among all cannabis consumers is joints, while other ways of consuming such as food preparations and water pipes are rare and experimental. Joints always mix cannabis with tobacco for 3 reasons: to burn correctly, pure cannabis is too strong, and smoking cannabis alone is too expensive. Two cannabis consumers - one former tobacco smoker and one occasional tobacco smoker - consider rolling tobacco less addictive than cigarette tobacco alone, and hence use it in their joints. Overall cannabis is considered 'natural' and less harmful to health than tobacco. Thus, many users describe their wish, in the longer term, to quit tobacco consumption without excluding occasional cannabis consumption. Nonetheless, all coconsumers declare that they smoke cigarettes as a substitute for cannabis: For example, "If I don't have a joint, I need fags; if I don't have fags, I need joints; and if I don't have anything, I go crazy!" or "About 20 minutes after smoking a joint we feel like smoking something again, because in the joint there is pure tobacco without a filter as in cigarettes, and that creates a crazy dependency!". Finally, all co-consumers state that the consumption of one of the substances increases when trying to diminish the other: "A few months ago I stopped smoking joints for a month. Well I was smoking more than a pack [of cigarettes] a day." Similarly, the 2 former cannabis consumers increased their cigarette use since quitting cannabis. Conclusions: The majority of cannabis users co-consume tobacco as a way of compensating for one substance or the other. Using tobacco within joints implies that there is a risk that even occasional joints can revive nicotine addiction. Consequently, health professionals wishing to help adolescents in substance use cessation and prevention efforts should consider both substances in a global perspective. Sources of Support: Dept. of Public Health of the canton of Vaud.

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Background: Visual analog scales (VAS) are used to assess readiness to changeconstructs, which are often considered critical for change.Objective: We studied whether 3 constructs -readiness to change, importance of changing and confidence inability to change- predict risk status 6 months later in 20 year-old men with either orboth of two behaviors: risky drinking and smoking. Methods: 577 participants in abrief intervention randomized trial were assessed at baseline and 6 months later onalcohol and tobacco consumption and with three 1-10 VAS (readiness, importance,confidence) for each behavior. For each behavior, we used one regression model foreach constructs. Models controlled for receipt of a brief intervention and used thelowest level (1-4) in each construct as the reference group (vs medium (5-7) and high(8-10) levels).Results: Among the 475 risky drinkers, mean (SD) readiness, importance and confidence to change drinking were 4.0 (3.1), 2.8 (2.2) and 7.2 (3.0).Readiness was not associated with being alcohol-risk free 6 months later (OR 1.3[0.7; 2.2] and 1.4 [0.8; 2.6] for medium and high readiness). High importance andhigh confidence were associated with being risk free (OR 0.9 [0.5; 1.8] and 2.9 [1.2;7.5] for medium and high importance; 2.1 [1.0;4.8] and 2.8 [1.5;5.6] for medium andhigh confidence). Among the 320 smokers, mean readiness, importance andconfidence to change smoking were 4.6 (2.6), 5.3 (2.6) and 5.9 (2.6). Neitherreadiness nor importance were associated with being smoking free (OR 2.1 [0.9; 4.7]and 2.1 [0.8; 5.8] for medium and high readiness; 1.4 [0.6; 3.4] and 2.1 [0.8; 5.4] formedium and high importance). High confidence was associated with being smokingfree (OR 2.2 [0.8;6.6] and 3.4 [1.2;9.8] for medium and high confidence).Conclusions: For drinking and smoking, high confidence in ability to change wasassociated -with similar magnitude- with a favorable outcome. This points to thevalue of confidence as an important predictor of successful change.

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Marijuana is the most widely used illicit drug, however its effects on cognitive functions underling safe driving remain mostly unexplored. Our goal was to evaluate the impact of cannabis on the driving ability of occasional smokers, by investigating changes in the brain network involved in a tracking task. The subject characteristics, the percentage of Δ(9)-Tetrahydrocannabinol in the joint, and the inhaled dose were in accordance with real-life conditions. Thirty-one male volunteers were enrolled in this study that includes clinical and toxicological aspects together with functional magnetic resonance imaging of the brain and measurements of psychomotor skills. The fMRI paradigm was based on a visuo-motor tracking task, alternating active tracking blocks with passive tracking viewing and rest condition. We show that cannabis smoking, even at low Δ(9)-Tetrahydrocannabinol blood concentrations, decreases psychomotor skills and alters the activity of the brain networks involved in cognition. The relative decrease of Blood Oxygen Level Dependent response (BOLD) after cannabis smoking in the anterior insula, dorsomedial thalamus, and striatum compared to placebo smoking suggests an alteration of the network involved in saliency detection. In addition, the decrease of BOLD response in the right superior parietal cortex and in the dorsolateral prefrontal cortex indicates the involvement of the Control Executive network known to operate once the saliencies are identified. Furthermore, cannabis increases activity in the rostral anterior cingulate cortex and ventromedial prefrontal cortices, suggesting an increase in self-oriented mental activity. Subjects are more attracted by intrapersonal stimuli ("self") and fail to attend to task performance, leading to an insufficient allocation of task-oriented resources and to sub-optimal performance. These effects correlate with the subjective feeling of confusion rather than with the blood level of Δ(9)-Tetrahydrocannabinol. These findings bolster the zero-tolerance policy adopted in several countries that prohibits the presence of any amount of drugs in blood while driving.

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A cross-over controlled administration study of smoked cannabis was carried out on occasional and heavy smokers. The participants smoked a joint (11 % Δ9-tetrahydrocannabinol (THC)) or a matching placebo on two different occasions. Whole blood (WB) and oral fluid (OF) samples were collected before and up to 3.5 h after smoking the joints. Pharmacokinetic analyses were obtained from these data. Questionnaires assessing the subjective effects were administered to the subjects during each session before and after the smoking time period. THC, 11-hydroxy-THC (11-OH-THC) and 11-nor-9-carboxy-THC (THCCOOH) were analyzed in the blood by gas chromatography or liquid chromatography (LC)-tandem mass spectrometry (MS/MS). The determination of THC, THCCOOH, cannabinol (CBN), and Δ9-tetrahydrocannabinolic acid A (THC-A) was carried out on OF only using LC-MS/MS. In line with the widely accepted assumption that cannabis smoking results in a strong contamination of the oral cavity, we found that THC, and also THC-A, shows a sharp, high concentration peak just after smoking, with a rapid decrease in these levels within 3 h. No obvious differences were found between both groups concerning THC median maximum concentrations measured either in blood or in OF; these levels were equal to 1,338 and 1,041 μg/L in OF and to 82 and 94 μg/L in WB for occasional and heavy smokers, respectively. The initial WB THCCOOH concentration was much higher in regular smokers than in occasional users. Compared with the occasional smokers, the sensation of confusion felt by the regular smokers was much less while the feeling of intoxication remained almost unchanged.

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Background: Medical and pharmacological direct costs of cigarette smoking cessation programmes are not covered by health insurance in several countries despite documented cost-effectiveness. Design: prospective cost identification study of a 9-week programme in Switzerland. Methods: A total of 481 smokers were followed-up for 9 weeks. Socio-demographic characteristics, number of outpatient visits, dosage and frequency of use of nicotine replacement therapy (NRT) as well as date of relapse were prospectively collected. Individual cost of care until relapse or programme end as well as cost per week of follow-up were computed. Comparisons were carried out between the groups with or without relapse at the end of the programme. Results: Of the 209 men and 272 women included, 347 patients (72%) finished the programme. Among them, 240 patients (70%) succeeded in quitting and 107 patients (30%) relapsed. As compared with the group relapsing by the end of the programme, the group succeeding in quitting was more often living in a couple (68% vs. 55%, p = 0.029). Their mean weekly costs of visits were higher (CHF 81.2 ± 6.1 vs. 78.4 ± 7.6, p = 0.001), while their mean weekly costs for NRT were similar (CHF 24.2 ± 12.6 vs. 25.4 ± 15.9, p = 0.711). Mean total costs per week were similar (CHF 105.4 ± 15.4 vs. 103.8 ± 19.4, p = 0.252). More intensive NRT at week 4 increased the probability not to relapse at the end of the programme. Conclusions: Over 9 weeks, medical and pharmacological costs of stopping smoking are low. Good medical and social support as well as adequate NRT seem to play a role in successful quitting.