231 resultados para Furfuryl alcohol resin
Resumo:
BACKGROUND: The goals of our study are to determine the most appropriate model for alcohol consumption as an exposure for burden of disease, to analyze the effect of the chosen alcohol consumption distribution on the estimation of the alcohol Population- Attributable Fractions (PAFs), and to characterize the chosen alcohol consumption distribution by exploring if there is a global relationship within the distribution. METHODS: To identify the best model, the Log-Normal, Gamma, and Weibull prevalence distributions were examined using data from 41 surveys from Gender, Alcohol and Culture: An International Study (GENACIS) and from the European Comparative Alcohol Study. To assess the effect of these distributions on the estimated alcohol PAFs, we calculated the alcohol PAF for diabetes, breast cancer, and pancreatitis using the three above-named distributions and using the more traditional approach based on categories. The relationship between the mean and the standard deviation from the Gamma distribution was estimated using data from 851 datasets for 66 countries from GENACIS and from the STEPwise approach to Surveillance from the World Health Organization. RESULTS: The Log-Normal distribution provided a poor fit for the survey data, with Gamma and Weibull distributions providing better fits. Additionally, our analyses showed that there were no marked differences for the alcohol PAF estimates based on the Gamma or Weibull distributions compared to PAFs based on categorical alcohol consumption estimates. The standard deviation of the alcohol distribution was highly dependent on the mean, with a unit increase in alcohol consumption associated with a unit increase in the mean of 1.258 (95% CI: 1.223 to 1.293) (R2 = 0.9207) for women and 1.171 (95% CI: 1.144 to 1.197) (R2 = 0. 9474) for men. CONCLUSIONS: Although the Gamma distribution and the Weibull distribution provided similar results, the Gamma distribution is recommended to model alcohol consumption from population surveys due to its fit, flexibility, and the ease with which it can be modified. The results showed that a large degree of variance of the standard deviation of the alcohol consumption Gamma distribution was explained by the mean alcohol consumption, allowing for alcohol consumption to be modeled through a Gamma distribution using only average consumption.
Resumo:
BACKGROUND: Cigarette smoking is often initiated at a young age as well as other risky behaviors such as alcohol drinking, cannabis and other illicit drugs use. Some studies suggest that cigarette smoking may have an influence on other risky behaviors but little is known about the chronology of occurrence of those different habits. The aim of this study was to assess, by young men, what were the other risky behaviors associated with cigarette smoking and the joint prevalence and chronology of occurrence of those risky behaviors. METHODS: Cross-sectional analyses of a population-based census of 3526 young men attending the recruitment for the Swiss army, aged between 17 and 25 years old (mean age: 19 years old), who filled a self reported questionnaire about their alcohol, cigarettes, cannabis and other illicit drugs habits. Actual smoking was defined as either regular smoking (¡Ý1 cigarette/day, on every day) or occasional smoking, binge drinking as six or more drinks at least twice a month, at risk drinking as 21 drinks or more per week, recent cannabis use as cannabis consumption at least once during the last month, and use of illicit drugs as consumption once or more of illicit drugs other than cannabis. Age at begin was defined as age at first use of cannabis or cigarette smoking. RESULTS: In this population of young men, the prevalence of actual smoking was 51.2% (36.5% regular smoking, 14.6% occasionnal smoking). Two third of participamnts (60.1%) declared that they ever used cannabis, 25.2% reported a recent use of cannabis. 53.8% of participants had a risky alcohol consumption considered as either binge or at risk drinking. Cigarette smoking was significantly associated with recent cannabis use (Odds Ratio (OR): 3.85, 95% Confidence Interval (CI): 3.10- 4.77), binge drinking (OR: 3.48, 95% CI: 3.03-4.00), at risk alcohol drinking (OR: 4.04, 95% CI: 3.12-5.24), and ever use of illicit drugs (OR: 4.34, 95% CI: 3.54-5.31). In a multivariate logistic regression, odds ratios for smoking were increased for cannabis users (OR 3.10,, 95% CI: 2.48-3.88), binge drinkers (OR: 1.77, 95% CI: 1.44-2.17), at risk alcohol drinkers (OR 2.26, 95% CI: 1.52-3.36) and ever users of illicit drugs (OR: 1.56, 95% CI: 1.20-2.03). The majority of young men (57.3%) initiated smoking before cannabis and mean age at onset was 13.4 years old, whereas only 11.1% began to use cannabis before smoking cigarettes and mean age at onset was slightly older (14.4 years old). 31.6% started both cannabis and tobacco at the same age (15 years old). About a third of participants (30.5%) did have a cluster of risky behaviours (smoking, at risk drinking, cannabis use) and 11.0% did cumulate smoking, drinking, cannabis and ever use of illegal drugs. More than half of the smokers (59.6%) did cumulate cannabis use and at risk alcohol drinking whereas only 18.5% of non-smokers did. CONCLUSIONS: The majority of young smokers initiated their risky behaviors by first smoking and then by other psychoactive drugs. Smokers have an increased risk to present other risky behaviors such as cannabis use, at risk alcohol consumtion and illicit drug use compared to nonsmokers. Prevention by young male adults should focus on smoking and also integrate interventions on other risky behaviors.
Resumo:
AIMS: This study aimed to estimate the prevalence of life-time abstainers, former drinkers and current drinkers, adult per-capita consumption of alcohol and pattern of drinking scores, by country and Global Burden of Disease region for 2005, and to forecast these indicators for 2010. DESIGN: Statistical modelling based on survey data and routine statistics. SETTING AND PARTICIPANTS: A total of 241 countries and territories. MEASUREMENTS: Per-capita consumption data were obtained with the help of the World Health Organization's Global Information System on Alcohol and Health. Drinking status data were obtained from Gender, Alcohol and Culture: An International Study, the STEPwise approach to Surveillance study, the World Health Survey/Multi-Country Study and other surveys. Consumption and drinking status data were triangulated to estimate alcohol consumption across multiple categories. FINDINGS: In 2005 adult per-capita annual consumption of alcohol was 6.1 litres, with 1.7 litres stemming from unrecorded consumption; 17.1 litres of alcohol were consumed per drinker, 45.8% of all adults were life-time abstainers, 13.6% were former drinkers and 40.6% were current drinkers. Life-time abstention was most prevalent in North Africa/Middle East and South Asia. Eastern Europe and Southern sub-Saharan Africa had the most detrimental pattern of drinking scores, while drinkers in Europe (Eastern and Central) and sub-Saharan Africa (Southern and West) consumed the most alcohol. CONCLUSIONS: Just over 40% of the world's adult population consumes alcohol and the average consumption per drinker is 17.1 litres per year. However, the prevalence of abstention, level of alcohol consumption and patterns of drinking vary widely across regions of the world.
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Alcohol treatment professionals are often reluctant to address tobacco dependence in their patients or to implement smoke-free policies in inpatient treatment programs, fearing, among others, non-adherence to alcohol treatment. The aim of the present study was to evaluate the acceptance of an intended smoking ban in a specialized hospital for alcohol withdrawal. Fifteen of 54 patients reported that they would not begin or quit alcohol treatment if smoking were banned in the clinic, but only five would not begin or quit if nicotine replacement were available. The present study indicates that a non-smoking policy would be feasible in a Swiss alcohol clinic, without jeopardizing alcohol treatment adherence.
Resumo:
QUESTIONS UNDER STUDY / PRINCIPLES: The main aim of this study was to investigate profiles of drug users, with a particular focus on illicit drugs other than cannabis, and to explore the effect of early-onset intensive use (drunkenness, daily smoking, high on cannabis) on profiles of illicit drug use. METHODS: Baseline data from a representative sample of 5,831 young Swiss men in the ongoing Cohort Study on Substance Use Risk Factors were used. Substance use (alcohol, tobacco, cannabis and 15 types of other illicit drug) and age of onset of intensive use were assessed. The Item Response Theory (IRT) and prevalence rates at different ages of onset were used to reveal different profiles of illicit drug use. RESULTS: In addition to cannabis, there were two profiles of other illicit drug use: (a) "softer" drug users (uppers, hallucinogens and inhaled drugs), among which ecstasy had the highest discriminatory potential (IRT slope = 4.68, standard error (SE) = 0.48; p <0.001); and (b) "harder" drug users (heroin, ketamine, gamma-hydroxybutyrate/gamma-hydroxylactone, research chemicals, crystal meth and spice), among which ketamine had the highest discriminatory potential (slope = 4.05; SE = 0.63; p <0.001). Onset of intensive use at the age of 12 years or younger also discriminated between these two profiles. CONCLUSION: Both the IRT model and the effect of onset of intensive use enabled two groups of illicit drugs to be identified. In particular, very early onset (at 12 years or younger) intensive use of any substance was a marker for later use of the second group of drugs.
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We have shown previously that voluntary ethanol consumption and resistance to ethanol-induced sedation are inversely related to neuropeptide Y (NPY) levels in NPY-knock-out (NPY(-/-)) and NPY-overexpressing mice. In the present report, we studied knock-out mice completely lacking the NPY Y1 receptor (Y1(-/-)) to further characterize the role of the NPY system in ethanol consumption and neurobiological responses to this drug. Here we report that male Y1(-/-) mice showed increased consumption of solutions containing 3, 6, and 10% (v/v) ethanol when compared with wild-type (Y1(+/+)) control mice. Female Y1(-/-) mice showed increased consumption of a 10% ethanol solution. In contrast, Y1(-/-) mice showed normal consumption of solutions containing either sucrose or quinine. Relative to Y1(+/+) mice, male Y1(-/-) mice were found to be less sensitive to the sedative effects of 3.5 and 4.0 gm/kg ethanol as measured by more rapid recovery from ethanol-induced sleep, although plasma ethanol levels did not differ significantly between the genotypes. Finally, male Y1(-/-) mice showed normal ethanol-induced ataxia on the rotarod test after administration of a 2.5 gm/kg dose. These data suggest that the NPY Y1 receptor regulates voluntary ethanol consumption and some of the intoxicating effects caused by administration of ethanol.
Resumo:
BACKGROUND AND AIMS: Moderate alcohol consumption has been shown to decrease the risk of type 2 diabetes (T2DM), but whether this association is also valid for impaired fasting glucose (IFG) is less well known. We aimed at assessing the impact of alcohol consumption and of type of alcoholic beverage on the incidence of T2DM and T2DM + IFG. METHODS AND RESULTS: As many as 4765 participants (2613 women, mean age 51.7 ± 10.5 years) without T2DM at baseline and followed for an average of 5.5 years. The association between alcohol consumption, type of alcoholic beverage and outcomes was assessed after adjustment for a validated T2DM risk score. During follow-up 284 participants developed T2DM and 643 developed IFG. On bivariate analysis, alcohol consumption was positively associated with the risk of developing T2DM or T2DM + IFG. Moderate (14-27 units/week) alcohol consumption tended to be associated with a lower risk of T2DM, but no protective effect was found for T2DM + IFG. Multivariable-adjusted odds ratio (OR) and (95% confidence interval) for T2DM: 0.89 (0.65-1.22), 0.66 (0.42-1.03) and 1.63 (0.93-2.84) for 1-13, 14-27 and 28 + units/week, respectively (p for quadratic trend < 0.005). For T2DM + IFG, the corresponding ORs were 1.09 (0.90-1.32), 1.33 (1.02-1.74) and 1.54 (0.99-2.39), respectively, p for trend = 0.03. No specific effect of alcoholic beverage (wine, beer or spirits) was found for T2DM or for T2DM + IFG. CONCLUSION: Moderate alcohol consumption is associated with a reduced risk of developing T2DM, but not of developing T2DM + IFG. No specific effect of type of alcoholic beverage was found.
Resumo:
Although cigarette smoking and alcohol consumption increase risk for head and neck cancers, there have been few attempts to model risks quantitatively and to formally evaluate cancer site-specific risks. The authors pooled data from 15 case-control studies and modeled the excess odds ratio (EOR) to assess risk by total exposure (pack-years and drink-years) and its modification by exposure rate (cigarettes/day and drinks/day). The smoking analysis included 1,761 laryngeal, 2,453 pharyngeal, and 1,990 oral cavity cancers, and the alcohol analysis included 2,551 laryngeal, 3,693 pharyngeal, and 3,116 oval cavity cancers, with over 8,000 controls. Above 15 cigarettes/day, the EOR/pack-year decreased with increasing cigarettes/day, suggesting that greater cigarettes/day for a shorter duration was less deleterious than fewer cigarettes/day for a longer duration. Estimates of EOR/pack-year were homogeneous across sites, while the effects of cigarettes/day varied, indicating that the greater laryngeal cancer risk derived from differential cigarettes/day effects and not pack-years. EOR/drink-year estimates increased through 10 drinks/day, suggesting that greater drinks/day for a shorter duration was more deleterious than fewer drinks/day for a longer duration. Above 10 drinks/day, data were limited. EOR/drink-year estimates varied by site, while drinks/day effects were homogeneous, indicating that the greater pharyngeal/oral cavity cancer risk with alcohol consumption derived from the differential effects of drink-years and not drinks/day.