Estimating uncertainty of alcohol-attributable fractions for infectious and chronic diseases

Background: Alcohol is a major risk factor for burden of disease and injuries globally. This paper presents a systematic method to compute the 95% confidence intervals of alcohol-attributable fractions (AAFs) with exposure and risk relations stemming from different sources.Methods: The computation was based on previous work done on modelling drinking prevalence using the gamma distribution and the inherent properties of this distribution. The Monte Carlo approach was applied to derive the variance for each AAF by generating random sets of all the parameters. A large number of random samples were thus created for each AAF to estimate variances. The derivation of the distributions of the different parameters is presented as well as sensitivity analyses which give an estimation of the number of samples required to determine the variance with predetermined precision, and to determine which parameter had the most impact on the variance of the AAFs.Results: The analysis of the five Asian regions showed that 150 000 samples gave a sufficiently accurate estimation of the 95% confidence intervals for each disease. The relative risk functions accounted for most of the variance in the majority of cases.Conclusions: Within reasonable computation time, the method yielded very accurate values for variances of AAFs

Volume of alcohol consumption, patterns of drinking and burden of disease in sub-Saharan Africa, 2002

The aim of this study was to provide an overview of the volume of alcohol consumption, type of beverage, patterns of drinking and alcohol-attributable burden of disease among adults in sub- Saharan Africa (SSA) for the year 2002. Exposure data were taken from surveys, the World Health Organization (WHO) Global Status Report on Alcohol and the WHO Global Alcohol Database. Mortality and disability data were obtained directly from WHO. The results showed that adult per capita alcohol consumption (population15 years and above) in SSA was higher than the global consumption rate (7.4 L vs. 6.2 L) and that alcohol consumption per adult drinker was 42% higher than the global rate. Alcohol was responsible for a considerable disease burden: 2.2% of all deaths and 2.5% of all DALYs could be attributed to this exposure. Intentional and unintentional injuries accounted for 53% of all alcohol-attributable deaths and almost 57% of alcohol-attributable disease burden. Among men 70% of all alcohol-attributable injury deaths occurred among 15-44 year olds (52% among women). This first attempt to quantify the health burden attributable to alcohol in SSA provides evidence of the direct health costs associated with drinking in the continent. In light of known effective and cost-effective measures, there is urgent need to implement interventions aimed at reducing levels of risky drinking and the high burden of alcohol-related harm in African countries. KEY WORDS: alcohol consumption, patterns of drinking, sub-Saharan Africa, burden of diseas

Low Mach Number Modeling of Type Ia Supernovae

We introduce a low Mach number equation set for the large-scale numerical simulation of carbon-oxygen white dwarfs experiencing a thermonuclear deflagration. Since most of the interesting physics in a Type Ia supernova transpires at Mach numbers from 0.01 to 0.1, such an approach enables both a considerable increase in accuracy and savings in computer time compared with frequently used compressible codes. Our equation set is derived from the fully compressible equations using low Mach number asymptotics, but without any restriction on the size of perturbations in density or temperature. Comparisons with simulations that use the fully compressible equations validate the low Mach number model in regimes where both are applicable. Comparisons to simulations based on the more traditional anelastic approximation also demonstrate the agreement of these models in the regime for which the anelastic approximation is valid. For low Mach number flows with potentially finite amplitude variations in density and temperature, the low Mach number model overcomes the limitations of each of the more traditional models and can serve as the basis for an accurate and efficient simulation tool.Comment: Accepted for publication in the Astrophysical Journal 31 pages, 5 figures (some figures degraded in quality to conserve space

Mortality risk and mental disorders: longitudinal results from the Upper Bavarian Study

The object of the study was the assessment of the mortality risk for persons with a mental disorder in an unselected representative community sample assessed longitudinally. Subjects from a rural area in Upper Bavaria (Germany) participated in semi-structured interviews conducted by research physicians in the 1970s (first assessment) and death-certificate diagnoses were obtained after an interval up to 13 years later. The sample consisted of 1668 community residents aged 15 years and over. Cox regression estimates resulted in an odds ratio of 1·35 (confidence interval 1·01 to 1·81) for persons with a mental disorder classified as marked to very severe. The odds ratio increased with increasing severity of mental illness from 1·04 for mild disorders, 1·30 for marked disorders, to 1·64 for severe or very severe disorders. The relative risk (odds ratio) for persons with a mental disorder only and no somatic disorder was 1·22, for persons with only a somatic disorder 2·00, and for those with both a mental and a somatic disorder 2·13. The presence of somatic illness was responsible for most of the excess mortality. Somatic disorders associated with excess mortality in mental disorders were diseases of the nervous system or sensory organs, diseases of the circulatory system, diseases of the gastrointestinal tract, and diseases of the skeleton, muscles and connective tissue (ICD-8). Thus, while mental illness alone had a limited effect on excess mortality, comorbidity with certain somatic disorders had a significant effec

Who receives treatment for alcohol use disorders in the European Union? A cross-sectional representative study in primary and specialized health care

Background Alcohol use disorders (AUDs) are highly prevalent in Europe, but only a minority of those affected receive treatment. It is therefore important to identify factors that predict treatment in order to reframe strategies aimed at improving treatment rates. Methods Representative cross-sectional study with patients aged 18\u201364 from primary health care (PC, six European countries, n = 8476, data collection 01/13\u201301/14) and from specialized health care (SC, eight European countries, n = 1762, data collection 01/13\u201303/14). For descriptive purposes, six groups were distinguished, based on type of DSM-IV AUD and treatment setting. Treatment status (yes/no) for any treatment (model 1), and for SC treatment (model 2) were main outcome measures in logistic regression models. Results AUDs were prevalent in PC (12-month prevalence: 11.8%, 95% confidence interval (CI): 11.2\u201312.5%), with 17.6% receiving current treatment (95%CI: 15.3\u201319.9%). There were clear differences between the six groups regarding key variables from all five predictor domains. Prediction of any treatment (model 1) or SC treatment (model 2) was successful with high overall accuracy (both models: 95%), sufficient sensitivity (model 1: 79%/model 2: 76%) and high specificity (both models: 98%). The most predictive single variables were daily drinking level, anxiety, severity of mental distress, and number of inpatient nights during the last 6 months. Conclusions Variables from four domains were highly predictive in identifying treatment for AUD, with SC treatment groups showing very high levels of social disintegration, drinking, comorbidity and functional losses. Earlier intervention and formal treatment for AUD in PC should be implemented to reduce these high levels of adverse outcomes

There are many barriers to species’ migrations

Temperature-change trajectories are being used to identify the geographic barriers and thermal ‘cul-de-sacs’ that will limit the ability of many species to track climate change by migrating. We argue that there are many other potential barriers to species’ migrations. These include stable ecotones, discordant shifts in climatic variables, human land use, and species’ limited dispersal abilities. To illustrate our argument, for each 0.5° latitude/longitude grid cell of the Earth’s land surface, we mapped and tallied the number of cells for which future (2060–2080) climate represents an analog of the focal cell’s current climate. We compared results when only considering temperature with those for which both temperature and total annual precipitation were considered in concert. We also compared results when accounting for only geographic barriers (no cross-continental migration) with those involving both geographic and potential ecological barriers (no cross-biome migration). As expected, the number of future climate analogs available to each pixel decreased markedly with each added layer of complexity (e.g. the proportion of the Earth’s land surface without any available future climate analogs increased from 3% to more than 36% with the inclusion of precipitation and ecological boundaries). While including additional variables can increase model complexity and uncertainty, we must strive to incorporate the factors that we know will limit species’ ranges and migrations if we hope to predict the effects of climate change at a high-enough degree of accuracy to guide management decisions

Coupled-Channels Approach for Dissipative Quantum Dynamics in Near-Barrier Collisions

A novel quantum dynamical model based on the dissipative quantum dynamics of open quantum systems is presented. It allows the treatment of both deep-inelastic processes and quantum tunneling (fusion) within a fully quantum mechanical coupled-channels approach. Model calculations show the transition from pure state (coherent) to mixed state (decoherent and dissipative) dynamics during a near-barrier nuclear collision. Energy dissipation, due to irreversible decay of giant-dipole excitations of the interacting nuclei, results in hindrance of quantum tunneling.Comment: 8 pages, 4 figures, Invited talk by A. Diaz-Torres at the FUSION08 Conference, Chicago, September 22-26, 2008, To appear in AIP Conference Proceeding

Losing your edge: climate change and the conservation value of range-edge populations

Populations occurring at species\u27 range edges can be locally adapted to unique environmental conditions. From a species\u27 perspective, range-edge environments generally have higher severity and frequency of extreme climatic events relative to the range core. Under future climates, extreme climatic events are predicted to become increasingly important in defining species\u27 distributions. Therefore, range-edge genotypes that are better adapted to extreme climates relative to core populations may be essential to species\u27 persistence during periods of rapid climate change. We use relatively simple conceptual models to highlight the importance of locally adapted range-edge populations (leading and trailing edges) for determining the ability of species to persist under future climates. Using trees as an example, we show how locally adapted populations at species\u27 range edges may expand under future climate change and become more common relative to range-core populations. We also highlight how large-scale habitat destruction occurring in some geographic areas where many species range edge converge, such as biome boundaries and ecotones (e.g., the arc of deforestation along the rainforest-cerrado ecotone in the southern Amazonia), can have major implications for global biodiversity. As climate changes, range-edge populations will play key roles in helping species to maintain or expand their geographic distributions. The loss of these locally adapted range-edge populations through anthropogenic disturbance is therefore hypothesized to reduce the ability of species to persist in the face of rapid future climate change