838 resultados para Smoking habit


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Laboratory and field investigations were conducted to study the food habit of Chinese perch Siniperca chuatsi (Basilewsky) from first feeding through adult stage. Only fish larvae were consumed by Chinese perch larvae (2-21 days from hatching), and the presence of zooplankton did not have any significant effect on their survival rate. The ability of Chinese perch to feed on zooplankton is clearly limited by some innate factor. Instead of gill rakers, Chinese perch larvae have well-developed sharp teeth at the first feeding stage, and are well adapted to the piscivorous feeding habit unique to the larvae of Chinese perch, e.g. they bite and ingest the tails of other fish larvae. At the first feeding stage (2 days from hatching), daily rations were both very low, either in light or complete darkness. Although early-staged Chinese perch larvae (7-17 days from hatching) could feed in complete darkness, their daily rations were always significantly higher in light than in complete darkness. Late-staged Chinese perch larvae (21 days from hatching) were able to feed in complete darkness as well as in light, similar to the case of Chinese perch yearlings. Chinese perch yearlings (total length, 14-16 cm) consumed prey fish only and refused shrimp when visual cues were available (in light), but they consumed both prey when visual cues were not available (in complete darkness), suggesting that prey consumption by Chinese perch yearlings is affected by their sensory modality in predation. Both prey were found in the stomachs of similar-sized Chinese perch (total length, 14-32 cm) from their natural habitat, suggesting that shrimp are consumed by Chinese perch at night. Prey selection of Chinese perch with a length >38 cm, which consumed only fish in the field, appears to be based upon prey size instead of prey type. These results suggest that although environmental factors (e.g. light intensity) affect prey detection by Chinese perch, this fish is anatomically and behaviourally predisposed to prey on live fish from first feeding. This makes it a difficult fish to cultivate using conventional feeds.

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8-hydroxy-2'-deoxyguanosine (8OHdG) has been widely used as a biomarker of oxidative DNA damage in both animal models and human studies. To evaluate the effect of cigarette smoking on oxidative stress, we studied the levels of urinary 8OHdG from smokers and non-smokers and investigated the association with cigarette smoking. The urinary 8OHdG concentrations were determinated by capillary electrophoresis with end-column amprometric detection (CE-AD) after a single-step solid phase extraction (SPE), and then quantitatively expressed as a function of creatinine excretion. To increase the concentration sensitivity, a dynamic pH junction was used and the focusing effect was obvious when using 30 mM phosphate (pH 6.50) as sample matrix. The limit of detection is 4.3 nM (signal-to-noise ratio S/N = 3). The relative standard deviation (R.S.D.) was 1.1% for peak current, and 2.3% for migration time. Based on the selected CE-AD method, it was found that the mean value of urinary 8OHdG levels in the smokers significantly higher than that in non-smokers (31.4 +/- 18.9 nM versus 14.4 +/- 7.6 nM, P = 0.0004; 23.5 +/- 21.3 mug g(-1) creatinine versus 12.6 +/- 13.2 mug g(-1) creatinine, P = 0.028). (C) 2004 Elsevier B.V. All rights reserved.

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Byers, D., Peel, D., Thomas, D. (2007). Habit, aggregation and long memory: Evidence from television audience data. Applied Economics, 39 (3), 321-327. RAE2008

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The SIEGE (Smoking Induced Epithelial Gene Expression) database is a clinical resource for compiling and analyzing gene expression data from epithelial cells of the human intra-thoracic airway. This database supports a translational research study whose goal is to profile the changes in airway gene expression that are induced by cigarette smoke. RNA is isolated from airway epithelium obtained at bronchoscopy from current-, former- and never-smoker subjects, and hybridized to Affymetrix HG-U133A Genechips, which measure the level of expression of ~22 500 human transcripts. The microarray data generated along with relevant patient information is uploaded to SIEGE by study administrators using the database's web interface, found at http://pulm.bumc.bu.edu/siegeDB. PERL-coded scripts integrated with SIEGE perform various quality control functions including the processing, filtering and formatting of stored data. The R statistical package is used to import database expression values and execute a number of statistical analyses including t-tests, correlation coefficients and hierarchical clustering. Values from all statistical analyses can be queried through CGI-based tools and web forms found on the �Search� section of the database website. Query results are embedded with graphical capabilities as well as with links to other databases containing valuable gene resources, including Entrez Gene, GO, Biocarta, GeneCards, dbSNP and the NCBI Map Viewer.

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The Republic of Ireland became the first European country to implement nationwide smoke-free workplace legislation. Aims: To determine prevalence of smoking among bar workers and estimate the impact of the smoke-free workplace legislation on their smoking behaviour to that of a comparable general population sample. To approximate the influence of tobacco control measures on risk perception of second-hand smoke (SHS) among the general population. To explore the de-normalisation of smoking behaviour and the potential increased stigmatisation of smokers and their smoking. Methods: Prevalence estimates and behavioural changes were examined among a random sample of bar workers before and 1 year after the smoke-free legislation; comparisons made with a general population sub-sample. Changes in risk knowledge related to SHS exposure were based on general population data. Qualitative interviews were conducted among a purposive sample of smokers and non-smokers four years after the implementation of the legislation. Results: Smoking prevalence was extremely high among bar workers. Smoking prevalence dropped in bar workers and significantly among the general population 1 year post ban while cigarette consumption dropped significantly among bar workers. Disparity in knowledge between smokers and non-smoker of risk associated with SHS exposure reduced. Lack of understanding of the risk of ear infections in children posed by SHS exposure was notable. Evidence for advanced de-normalisation of smoking behaviour and intensification of stigma because of the introduction of the legislation was dependent on many factors, quality of smoking facilities played a key role. Conclusions: Ireland’s smoke-free legislation was associated with a drop in prevalence and cigarette consumption. Disparity in knowledge between smokers and non-smokers of the risk posed by SHS exposure reduced however the risk of ear infections in children needs to be effectively disseminated. The proliferation of ‘good’ smoking areas may diminish the potential to reduce smoking behaviour and de-normalise smoking.

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OBJECTIVE: This study examined the impact of smoking, quitting, and time since quit on absences from work. METHODS: Data from the nationally representative Tobacco Use Supplements of the 1992/93, 1995/96, and 1998/99 Current Population Surveys were used. The study included full time workers aged between 18-64 years, yielding a sample size of 383 778 workers. A binary indicator of absence due to sickness in the last week was analysed as a function of smoking status including time since quit for former smokers. Extensive demographic variables were included as controls in all models. RESULTS: In initial comparisons between current and former smokers, smoking increased absences, but quitting did not reduce them. However, when length of time since quit was examined, it was discovered that those who quit within the last year, and especially the last three months, had a much greater probability of absences than did current smokers. As the time since quitting increased, absences returned to a rate somewhere between that of never and current smokers. Interactions between health and smoking status significantly improved the fit of the model. CONCLUSIONS: Smokers who quit reduced their absences over time but increase their absences immediately after quitting. Quitting ill may account for some but not all of this short run impact.

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Smoking is an expensive habit. Smoking households spend, on average, more than $US1000 annually on cigarettes. When a family member quits, in addition to the former smoker's improved long-term health, families benefit because savings from reduced cigarette expenditures can be allocated to other goods. For households in which some members continue to smoke, smoking expenditures crowd-out other purchases, which may affect other household members, as well as the smoker. We empirically analyse how expenditures on tobacco crowd-out consumption of other goods, estimating the patterns of substitution and complementarity between tobacco products and other categories of household expenditure. We use the Consumer Expenditure Survey data for the years 1995-2001, which we complement with regional price data and state cigarette prices. We estimate a consumer demand system that includes several main expenditure categories (cigarettes, food, alcohol, housing, apparel, transportation, medical care) and controls for socioeconomic variables and other sources of observable heterogeneity. Descriptive data indicate that, comparing smokers to nonsmokers, smokers spend less on housing. Results from the demand system indicate that as the price of cigarettes rises, households increase the quantity of food purchased, and, in some samples, reduce the quantity of apparel and housing purchased.

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AIMS: To assess the impact of involuntary job loss due to plant closure or layoff on relapse to smoking and smoking intensity among older workers. DESIGN, PARTICIPANTS, SAMPLE: Data come from the Health and Retirement Study, a nationally representative survey of older Americans aged 51-61 in 1991 followed every 2 years beginning in 1992. The 3052 participants who were working at the initial wave and had any history of smoking comprise the main sample. METHODS: Primary outcomes are smoking relapse at wave 2 (1994) among baseline former smokers, and smoking quantity at wave 2 among baseline current smokers. As reported at the wave 2 follow-up, 6.8% of the sample experienced an involuntary job loss between waves 1 and 2. FINDINGS: Older workers have over two times greater odds of relapse subsequent to involuntary job loss than those who did not. Further, those who were current smokers prior to displacement that did not obtain new employment were found to be smoking more cigarettes, on average, post-job loss. CONCLUSIONS: The stress of job loss, along with other significant changes associated with leaving one's job, which would tend to increase cigarette consumption, must outweigh the financial hardship which would tend to reduce consumption. This highlights job loss as an important health risk factor for older smokers.

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This study investigates the effect of serious health events including new diagnoses of heart attacks, strokes, cancers, chronic lung disease, chronic heart failure, diabetes, and heart disease on future smoking status up to 6 years postevent. Data come from the Health and Retirement Study, a nationally representative longitudinal survey of Americans aged 51-61 in 1991, followed every 2 years from 1992 to 1998. Smoking status is evaluated at each of three follow-ups, (1994, 1996, and 1998) as a function of health events between each of the four waves. Acute and chronic health events are associated with much lower likelihood of smoking both in the wave immediately following the event and up to 6 years later. However, future events do not retrospectively predict past cessation. In sum, serious health events have substantial impacts on cessation rates of older smokers. Notably, these effects persist for as much as 6 years after a health event.

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OBJECTIVE: The authors sought to increase understanding of the brain mechanisms involved in cigarette addiction by identifying neural substrates modulated by visual smoking cues in nicotine-deprived smokers. METHOD: Event-related functional magnetic resonance imaging (fMRI) was used to detect brain activation after exposure to smoking-related images in a group of nicotine-deprived smokers and a nonsmoking comparison group. Subjects viewed a pseudo-random sequence of smoking images, neutral nonsmoking images, and rare targets (photographs of animals). Subjects pressed a button whenever a rare target appeared. RESULTS: In smokers, the fMRI signal was greater after exposure to smoking-related images than after exposure to neutral images in mesolimbic dopamine reward circuits known to be activated by addictive drugs (right posterior amygdala, posterior hippocampus, ventral tegmental area, and medial thalamus) as well as in areas related to visuospatial attention (bilateral prefrontal and parietal cortex and right fusiform gyrus). In nonsmokers, no significant differences in fMRI signal following exposure to smoking-related and neutral images were detected. In most regions studied, both subject groups showed greater activation following presentation of rare target images than after exposure to neutral images. CONCLUSIONS: In nicotine-deprived smokers, both reward and attention circuits were activated by exposure to smoking-related images. Smoking cues are processed like rare targets in that they activate attentional regions. These cues are also processed like addictive drugs in that they activate mesolimbic reward regions.

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BACKGROUND: Antibodies (Abs) to the HPV16 proteome increase risk for HPV-associated OPC (HPVOPC). The goal of this study was to investigate the association of a panel of HPV16 Abs with risk for OPC as well as the association of these Abs with tumor HPV and smoking status among patients with OPC. METHODS: IgG Abs to the HPV16 antigens E1, E2, E4, E5, E6, E7, L1, L2 were quantified using a programmable ELISA assay. Sera were obtained from 258 OPC patients at diagnosis and 250 healthy controls. HPV16 tumor status was measured by PCR for 137 cases. Multivariable logistic regression was used to calculate odds ratios for the association of HPV16 Abs with risk for OPC. RESULTS: HPV16 E1, E2, E4, E5, E6, E7 and L1-specific IgG levels were elevated in OPC patients compared to healthy controls (p<0.05). After multivariable adjustment, Ab positivity for NE2, CE2, E6, and/or E7 was associated with OPC risk (OR [95% CI], 249.1 [99.3-624.9]). Among patients with OPC, Ab positivity for these antigens was associated with tumor HPV status, especially among never or light smokers (OR [95% CI], 6.5 [2.1-20.1] and OR [95% CI], 17.5 [4.0-77.2], respectively). CONCLUSIONS: Antibodies to HPV16 proteins are associated with increased risk for HPVOPC. Among patients with OPC, HPV16 Abs are associated with tumor HPV status, in particular among HPV positive patients with no or little smoking history.