970 resultados para TOBACCO-SMOKE EXPOSURE
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This is a report for the Iowa Department of Revenue and Finance about the receipts on cigarettes and tobacco for each month of the year. This receipt is the tax of each sale of cigarettes and tobacco.
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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.
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This is a report for the Iowa Department of Revenue and Finance about the receipts on cigarettes and tobacco for each month of the year. This receipt is the tax of each sale of cigarettes and tobacco.
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This is a report for the Iowa Department of Revenue and Finance about the receipts on cigarettes and tobacco for each month of the year. This receipt is the tax of each sale of cigarettes and tobacco.
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This is a report for the Iowa Department of Revenue and Finance about the receipts on cigarettes and tobacco for each month of the year. This receipt is the tax of each sale of cigarettes and tobacco.
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The Work Package 4 of the ORAMED project, a collaborative project (2008-11) supported by the European Commission within its seventh Framework Programme, is concerned with the optimisation of the extremity dosimetry of medical staff in nuclear medicine. To evaluate the extremity doses and dose distributions across the hands of medical staff working in nuclear medicine departments, an extensive measurement programme has been started in 32 nuclear medicine departments in Europe. This was done using a standard protocol recording all relevant information for radiation exposure, i.e. radiation protection devices and tools. This study shows the preliminary results obtained for this measurement campaign. For diagnostic purposes, the two most-used radionuclides were considered: (99m)Tc and (18)F. For therapeutic treatments, Zevalin(®) and DOTATOC (both labelled with (90)Y) were chosen. Large variations of doses were observed across the hands depending on different parameters. Furthermore, this study highlights the importance of the positioning of the extremity dosemeter for a correct estimate of the maximum skin doses.
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This is a report for the Iowa Department of Revenue and Finance about the receipts on cigarettes and tobacco for each month of the year. This receipt is the tax of each sale of cigarettes and tobacco.
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In this study, we assessed the mixed exposure of highway maintenance workers to airborne particles, noise, and gaseous co-pollutants. The aim was to provide a better understanding of the workers' exposure to facilitate the evaluation of short-term effects on cardiovascular health endpoints. To quantify the workers' exposure, we monitored 18 subjects during 50 non-consecutive work shifts. Exposure assessment was based on personal and work site measurements and included fine particulate matter (PM2.5), particle number concentration (PNC), noise (Leq), and the gaseous co-pollutants: carbon monoxide, nitrogen dioxide, and ozone. Mean work shift PM2.5 concentrations (gravimetric measurements) ranged from 20.3 to 321 μg m(-3) (mean 62 μg m(-3)) and PNC were between 1.6×10(4) and 4.1×10(5) particles cm(-3) (8.9×10(4) particles cm(-3)). Noise levels were generally high with Leq over work shifts from 73.3 to 96.0 dB(A); the averaged Leq over all work shifts was 87.2 dB(A). The highest exposure to fine and ultrafine particles was measured during grass mowing and lumbering when motorized brush cutters and chain saws were used. Highest noise levels, caused by pneumatic hammers, were measured during paving and guardrail repair. We found moderate Spearman correlations between PNC and PM2.5 (r = 0.56); PNC, PM2.5, and CO (r = 0.60 and r = 0.50) as well as PNC and noise (r = 0.50). Variability and correlation of parameters were influenced by work activities that included equipment causing combined air pollutant and noise emissions (e.g. brush cutters and chain saws). We conclude that highway maintenance workers are frequently exposed to elevated airborne particle and noise levels compared with the average population. This elevated exposure is a consequence of the permanent proximity to highway traffic with additional peak exposures caused by emissions of the work-related equipment.
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This is a report for the Iowa Department of Revenue and Finance about the receipts on cigarettes and tobacco for each month of the year. This receipt is the tax of each sale of cigarettes and tobacco.
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Risperidone is metabolized by polymorphic enzymes, and a large variability in plasma concentration and therapeutic response is observed. Risperidone long-acting injection (RLAI) avoids the first-pass effect, and little is known about the influence of gene polymorphisms involved in its pharmacokinetics. The influence on plasma concentrations of risperidone (RIS), its metabolite 9-hydroxy-risperidone, and on adverse effects were investigated for polymorphisms of cytochrome P450 2D6 (CYP2D6) (*3, *4, *5, *6), CYP3A (CYP3A4*1B, CYP3A4 rs4646437, CYP3A5*3, CYP3A7*1C), ABCB1 (1236C>T, 2677G>T, 3435C>T), NR1/2 coding for pregnane X receptor (rs1523130, rs2472677, rs7643645), and for CYP3A activity measured by a phenotyping test. Forty-two patients with at least 4 consecutive unchanged doses of RLAI were included in a multicenter cross-sectional study. A 55% lower dose-adjusted plasma levels of RIS were observed for CYP2D6 ultrarapid metabolizers (n = 5) as compared with CYP2D6 intermediate metabolizers (P < 0.007). NR1/2 polymorphism (rs7643645A>G) influenced RIS exposure with a 2.8-fold lower active moiety (P = 0.031) in GG compared with the AA genotype. This was confirmed in a second independent cohort (n = 16). Furthermore, high-density lipoprotein cholesterol was positively correlated with CYP3A activity (P = 0.01), and the NR1/2 (rs2472677) polymorphism was associated with different adverse effects including prolactin plasma levels adjusted for age and sex. In conclusion, our results confirmed the influence of CYP2D6 genotype on plasma levels of RIS. This is the first report on the influence of NR1/2 polymorphisms on RLAI exposure and on drug-induced adverse effects. These results should be validated in larger cohorts.
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PURPOSE: Few studies compare the variabilities that characterize environmental (EM) and biological monitoring (BM) data. Indeed, comparing their respective variabilities can help to identify the best strategy for evaluating occupational exposure. The objective of this study is to quantify the biological variability associated with 18 bio-indicators currently used in work environments. METHOD: Intra-individual (BV(intra)), inter-individual (BV(inter)), and total biological variability (BV(total)) were quantified using validated physiologically based toxicokinetic (PBTK) models coupled with Monte Carlo simulations. Two environmental exposure profiles with different levels of variability were considered (GSD of 1.5 and 2.0). RESULTS: PBTK models coupled with Monte Carlo simulations were successfully used to predict the biological variability of biological exposure indicators. The predicted values follow a lognormal distribution, characterized by GSD ranging from 1.1 to 2.3. Our results show that there is a link between biological variability and the half-life of bio-indicators, since BV(intra) and BV(total) both decrease as the biological indicator half-lives increase. BV(intra) is always lower than the variability in the air concentrations. On an individual basis, this means that the variability associated with the measurement of biological indicators is always lower than the variability characterizing airborne levels of contaminants. For a group of workers, BM is less variable than EM for bio-indicators with half-lives longer than 10-15 h. CONCLUSION: The variability data obtained in the present study can be useful in the development of BM strategies for exposure assessment and can be used to calculate the number of samples required for guiding industrial hygienists or medical doctors in decision-making.