88 resultados para cigarette smoking


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Smoking is known to be linked to skin ageing and there is evidence for premature senescence of parenchymal lung fibroblasts in emphysema. To reveal whether the emphysema-related changes in cellular phenotype extend beyond the lung, we compared the proliferation characteristics of lung and skin fibroblasts between patients with and without emphysema. Parenchymal lung fibroblasts and skin fibroblasts from the upper torso (thus limiting sun exposure bias) were obtained from patients without, or with mild, or with moderate to severe emphysema undergoing lung surgery. We analysed proliferation rate, population doublings (PD), staining for senescence-associated beta-galactosidase (beta-gal) and gene expression of IGFBP-3 and IGFBP-rP1. Population doubling time of lung fibroblasts differed between control, mild, and moderate to severe emphysema (median (IQR) 29.7(10.0), 33.4(6.1), 44.4(21.2) h; p=0.012) and staining for beta-gal was elevated in moderate to severe emphysema. Compared to control subjects, skin fibroblasts from patients with emphysema did not differ with respect to proliferation rate, PD and beta-gal staining, and showed a lower abundance of mRNA for IGFBP-3 and -rP1 (p<0.05, each). These results suggest that the induction of a senescent fibroblast phenotype by cigarette smoke, as observed in emphysema, primarily occurs in the lung.

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BACKGROUND: Due to the predicted age shift of the population an increase in the number of patients with late AMD is expected. At present smoking represents the only modifiable risk factor. Supplementation of antioxidants in patients at risk is the sole effective pharmacological prevention. The aim of this study is to estimate the future epidemiological development of late AMD in Switzerland and to quantify the potential effects of smoking and antioxidants supplementation. METHODS: The modelling of the future development of late AMD cases in Switzerland was based on a meta-analysis of the published data on AMD-prevalence and on published Swiss population development scenarios until 2050. Three different scenarios were compared: low, mean and high. The late AMD cases caused by smoking were calculated using the "population attributable fraction" formula and data on the current smoking habits of the Swiss population. The number of potentially preventable cases was estimated using the data of the Age-Related Eye Disease Study (AREDS). RESULTS: According to the mean population development scenario, late AMD cases in Switzerland will rise from 37 200 cases in 2005 to 52 500 cases in 2020 and to 93 200 cases in 2050. Using the "low" and the "high" scenarios the late AMD cases may range from 49 500 to 56 000 in 2020 and from 73 700 to 118 400 in 2050, respectively. Smoking is responsible for approximately 7 % of all late AMD cases, i. e., 2600 cases in 2005, 3800 cases in 2020, 6600 cases in 2050 ("mean scenario"). With future antioxidant supplementation to all patients at risk another 3100 cases would be preventable until 2020 and possibly 23 500 cases until 2050. CONCLUSION: Due to age shift in the population a 2.5-fold increase in late AMD cases until 2050 is expected, representing a socioeconomic challenge. Cessation of smoking and supplementation of antioxidants to all patients at risk has the potential to reduce this number. Unfortunately, public awareness is low. These data may support health-care providers and public opinion leaders when developing public education and prevention strategies.

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OBJECTIVES Smoking is related to income and education and contributes to social inequality in morbidity and mortality. Socialisation theories focus on one's family of origin as regards acquisition of norms, attitudes and behaviours. Aim of this study is to assess associations of daily smoking with health orientation and academic track in young Swiss men. Further, to assess associations of health orientation and academic track with family healthy lifestyle, parents' cultural capital, and parents' economic capital. METHODS Cross-sectional data were collected during recruitment for compulsory military service in Switzerland during 2010 and 2011. A structural equation model was fitted to a sample of 18- to 25-year-old Swiss men (N = 10,546). RESULTS Smoking in young adults was negatively associated with academic track and health orientation. Smoking was negatively associated with parents' cultural capital through academic track. Smoking was negatively associated with health orientation which in turn was positively associated with a healthy lifestyle in the family of origin. CONCLUSIONS Results suggest two different mechanisms of intergenerational transmissions: first, the family transmission path of health-related dispositions, and secondly, the structural transmission path of educational inequality.

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A common form of social regulation of an individual’s health behavior is social control. The contextual model of social control assumes that higher relationship quality goes along with more beneficial effects of social control on health behavior. This study examined potential differential moderating effects of different dimensions of relationship quality on the associations between positive and negative social control and smoking behavior and hiding smoking. The sample consisted of 144 smokers (n = 72 women; mean age = 31.78, SD = 10.04) with a nonsmoking partner. Positive and negative social control, dimensions of relationship quality consensus, cohesion and satisfaction, numbers of cigarettes smoked (NCS), hiding smoking (HS), and control variables were assessed at baseline. Four weeks later NCS and HS were assessed again. Only for smokers with high consensus, but not cohesion and satisfaction, a negative association between positive control and NCS emerged. Moreover, smokers with high consensus tended to report more HS when being positively and negatively socially controlled. This also emerged for cohesion and positive control. Satisfaction with the relationship did not display any interaction effects. This study’s results emphasize the importance of differentiating not only between positive and negative social control but also between different dimensions of relationship quality in order to gain a comprehensive understanding of the dynamics in romantic dyads with regard to social regulation of behavioral change.

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Background: The Health Action Process Approach (HAPA) assumes that volitional processes are important for effective behavioral change. This study examined the associations of volitional predictors and daily smoking in quitters at the inter- and intraindividual level. Method: Overall, 105 smokers completed daily electronic questionnaires 10 days before and 21 days after a self-set quit date, assessing intentions, self-efficacy, planning, action control and numbers of cigarettes smoked. Findings: Multilevel analyses showed that mean levels of volitional predictors across the 32 days were negatively associated with numbers of cigarettes smoked. Moreover, on days with higher intentions, self-efficacy, planning and action control than usual, less cigarettes were smoked. These effects were stronger after the quit date than before the quit date. Intentions and action control emerged as most powerful predictors at the intraindividual level. Discussion: Findings emphasize the importance of volitional processes at the intraindividual level in the context of quitting smoking.

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Background: The health action process approach (hapa) is a well-established model in predicting health behavior and assumes that volitional processes are important for effective behavioral change. however, only few studies have so far tested associations on the intraindividual level. thus, this study examined the inter- and intraindividual associations between volitional predictors and daily smoking around a quit attempt. method: overall, 105 smokers completed daily electronic questionnaires 10 days before and 21 days after a self-set quit date, including measures of intentions, self-efficacy, planning, action control and numbers of cigarettes smoked. multilevel analysis was applied. findings: at the interindividual level, higher mean levels of volitional predictors across the 32 days were associated with less numbers of cigarettes smoked. negative associations emerged also at the intraindividual level, indicating that on days with higher intentions, self-efficacy, planning and action control than usual, less cigarettes were smoked. moreover, these effects were stronger after the quit date than before the quit date. intentions and action control emerged as most powerful predictors at the intraindividual level. discussion: findings confirm assumptions of the hapa and emphasize the importance of volitional processes at the inter- and intraindividual level in the context of quitting smoking.

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This study analysed mechanisms through which stress-coping and temptation-coping strategies were associated with lapses. Furthermore, we explored whether distinct coping strategies differentially predicted reduced lapse risk, lower urge levels, or a weaker association between urge levels and lapses during the first week of an unassisted smoking cessation attempt. Participants were recruited via the internet and mass media in Switzerland. Ecological momentary assessment (EMA) with mobile devices was used to assess urge levels and lapses. Online questionnaires were used to measure smoking behaviours and coping variables at baseline, as well as smoking behaviour at the three-month follow-up. The sample consisted of 243 individuals, aged 20 to 40, who reported 4199 observations. Findings of multilevel regression analyses show that coping was mainly associated with a reduced lapse risk and not with lower urge levels or a weaker association between urge levels and lapses. 'Calming down' and 'commitment to change' predicted a lower lapse risk and also a weaker relation between urge levels and lapses. 'Stimulus control' predicted a lower lapse risk and lower urge levels. Conversely, 'task-orientation' and 'risk assessment' were related to higher lapse risk and 'risk assessment' also to higher urge levels. Disengagement coping i.e. 'eating or shopping', 'distraction', and 'mobilising social support' did not affect lapse risk. Promising coping strategies during the initial stage of smoking cessation attempt are targeted directly at reducing the lapse risk and are characterised by engagement with the stressor or one's reactions towards the stressor and a focus on positive consequences instead of health risks.

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OBJECTIVES: To examine smoking behaviour, former quit attempts and intention to quit among Swiss adolescents and young adults over five year's time. STUDY DESIGN: five-year longitudinal study (2003, 2005 and 2008) based on a random urban community sample (N = 1345 complete cases). METHODS: Data were collected by computer-assisted telephone interviews with adolescents (16-17) and young adults (18-24). Main outcome measures included self-reported smoking behaviour, former quit attempts, smoking cessation methods and current intentions to quit smoking. RESULTS: Adolescents were more often non-smokers and less often daily smokers when compared to young adults at baseline (χ(2)(4) = 28.68, P < .001). Their smoking behaviour increased significantly from baseline to follow-up (T = 1445.50, r = .20, P < .001) in contrast to the stable smoking behaviour in young adults (χ(2)(2) = .12, n.s.). In longitudinal analyses young adults were also more stable in their smoking status at the later measurement points. In comparison adolescents changed their smoking status more often being non-smokers at baseline and smokers later on. Independently of the age group, the majority of smokers already had previously attempted to quit (65%) or intended to give up smoking at some point (72%). However only 17% were motivated to make the quit attempt within the next 6 months. Self-quitting was the preferred method, and 25% of the self-quitters had been successful. CONCLUSION: This study illustrates that different developments in smoking behaviour exist in adolescents and young adults. Our study reveals that a majority of smokers are willing to quit but often fail. Furthermore, the data indicates that for adolescents the focus should lie on primary prevention.

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Objectives: This study aimed at identifying distinct quitting trajectories over 29 days after an unassisted smoking ces- sation attempt by ecological momentary assessment (EMA). In order to validate these trajectories we tested if they predict smoking frequency up to six months later. Methods: EMA via mobile phones was used to collect real time data on smoking (yes/no) after an unassisted quit attempt over 29 days. Smoking frequency one, three and six months after the quit attempt was assessed with online questionnaires. Latent class growth modeling was used to analyze the data of 230 self-quitters. Results: Four different quitting trajectories emerged: quitter (43.9%), late quitter (11.3%), returner (17%) and persistent smoker (27.8%). The quitting trajectories predicted smoking frequency one, three and six months after the quit attempt (all p < 0.001). Conclusions: Outcome after a smoking cessation attempt is better described by four distinct trajectories instead of a binary variable for abstinence or relapse. In line with the relapse model by Marlatt and Gordon, late quitter may have learned how to cope with lapses during one month after the quitting attempt. This group would have been allocated to the relapse group in traditional outcome studies.

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AIMS The genetic polymorphism of apolipoprotein E (APOE) has been suggested to modify the effect of smoking on the development of coronary artery disease (CAD) in apparently healthy persons. The interaction of these factors in persons undergoing coronary angiography is not known. METHODS AND RESULTS We analysed the association between the APOE-genotype, smoking, angiographic CAD, and mortality in 3263 participants of the LUdwigshafen RIsk and Cardiovascular Health study. APOE-genotypes were associated with CAD [ε22 or ε23: odds ratio (OR) 0.56, 95% confidence interval (CI) 0.43-0.71; ε24 or ε34 or ε44: OR 1.10, 95% CI 0.89-1.37 compared with ε33] and moderately with cardiovascular mortality [ε22 or ε23: hazard ratio (HR) 0.71, 95% CI 0.51-0.99; ε33: HR 0.92, 95% CI 0.75-1.14 compared with ε24 or ε34 or ε44]. HRs for total mortality were 1.39 (95% CI 0.39-0.1.67), 2.29 (95% CI 1.85-2.83), 2.07 (95% CI 1.64-2.62), and 2.95 (95% CI 2.10-4.17) in ex-smokers, current smokers, current smokers without, or current smokers with one ε4 allele, respectively, compared with never-smokers. Carrying ε4 increased mortality in current, but not in ex-smokers (HR 1.66, 95% CI 1.04-2.64 for interaction). These findings applied to cardiovascular mortality, were robust against adjustment for cardiovascular risk factors, and consistent across subgroups. No interaction of smoking and ε4 was seen regarding non-cardiovascular mortality. Smokers with ε4 had reduced average low-density lipoprotein (LDL) diameters, elevated oxidized LDL, and lipoprotein-associated phospholipase A2. CONCLUSION In persons undergoing coronary angiography, there is a significant interaction between APOE-genotype and smoking. The presence of the ε4 allele in current smokers increases cardiovascular and all-cause mortality.

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OBJECTIVES: The aim of the study was to assess whether prospective follow-up data within the Swiss HIV Cohort Study can be used to predict patients who stop smoking; or among smokers who stop, those who start smoking again. METHODS: We built prediction models first using clinical reasoning ('clinical models') and then by selecting from numerous candidate predictors using advanced statistical methods ('statistical models'). Our clinical models were based on literature that suggests that motivation drives smoking cessation, while dependence drives relapse in those attempting to stop. Our statistical models were based on automatic variable selection using additive logistic regression with component-wise gradient boosting. RESULTS: Of 4833 smokers, 26% stopped smoking, at least temporarily; because among those who stopped, 48% started smoking again. The predictive performance of our clinical and statistical models was modest. A basic clinical model for cessation, with patients classified into three motivational groups, was nearly as discriminatory as a constrained statistical model with just the most important predictors (the ratio of nonsmoking visits to total visits, alcohol or drug dependence, psychiatric comorbidities, recent hospitalization and age). A basic clinical model for relapse, based on the maximum number of cigarettes per day prior to stopping, was not as discriminatory as a constrained statistical model with just the ratio of nonsmoking visits to total visits. CONCLUSIONS: Predicting smoking cessation and relapse is difficult, so that simple models are nearly as discriminatory as complex ones. Patients with a history of attempting to stop and those known to have stopped recently are the best candidates for an intervention.