12 resultados para Distribution factors

em University of Queensland eSpace - Australia


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Objective: Childhood injury remains the single most important cause of mortality in children aged between 1-14 years in many countries. It has been proposed that lower socio-economic status (SES) and poorer housing contribute to potential hazards in the home environment. This study sought to establish whether the prevalence of observed hazards in and around the home was differentially distributed by SES, in order to identify opportunities for injury prevention. Methods: This study was a cross-sectional, random sample survey of primary school children from 32 schools in Brisbane. Interviews and house audits were conducted between July 2000 and April 2003 to collect information on SES (income, employment and education) and previously identified household hazards. Results: There was evidence of a relationship between prevalence of household environmental hazards and household SES; however, the magnitude and direction of this relationship appeared to be hazard-specific. Household income was related to play equipment characteristics, with higher SES groups being more likely to be exposed to risk. All three SES indicators were associated with differences in the home safety characteristics, with the lower SES groups more likely to be exposed to risk. Conclusion:The differential distribution of environmental risk factors by SES of household may help explain the SES differential in the burden of injury and provides opportunities for focusing efforts to address the problem.

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End-stage liver disease associated with hepatitis C virus (HCV) infection is now the leading indication for liver transplantation in adults. However, reinfection of the graft is universal. We aimed to determine predictors of outcome of HCV-Iiver transplant recipients in the Australian and New Zealand communities. The following variables were analysed: demographic factors, coexistent pathology at the time of transplantation, HCV genotype, and donor age. Outcomes measures were: 1. mortality; 2. development of HCV-related complications, which were stage 3 or 4 fibrosis, or mortality from HCV-related graft failure, or both. Between January 1989 and December 30, 1999, 182 patients were transplanted for HCV-associated cirrhosis. The median follow-up period was 4 years (range, 0 to 13 years). Genotype data were available on 157 patients. The distribution of genotypes among the 157 patients was as follows: 36 (23%) genotype la, 30 (19%) genotype 1b, 4 (9%) genotype 1, 17 (11%) genotype 2, 41 (26%) genotype 3a, and 16 (10%) genotype 4. Eight (5%) patients were HCV-polymerase chain reaction (PCR)-negative (but HCV-antibody positive). Donor age and genotype 4 were associated with an increased risk of retransplantation or death (P < .001 and.05, respectively). Meanwhile, donor age, genotype 4, and pretransplant excess alcohol were risk factors for the development of HCV-related complications (P = .004, .008, and .02, respectively). In contrast, patients with genotype 3a were less likely to develop HCV-related complications (P = .05). In a population of HCV liver transplant recipients with a heterogeneous genotype distribution, donor age, and genotype 4, were predictors of a worse outcome, whereas genotype 3 was associated with a more favorable outcome.

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A study of the prevalence, intensity and risk factors for soil-transmitted helminth infection was undertaken among school children aged 5-9 years attending a primary school in the fishing village in Peda Jalaripet, Visakhapatnam, South India. One hundred and eighty nine (92.6%) of 204 children were infected with one or more soil transmitted helminth parasites. The predominant parasite was Ascaris lumbricoides (prevalence of 91%), followed by Trichuris trichiura (72%) and hookworm (54%). Study of age-specific prevalence and intensity of infection revealed that the prevalence and intensity of A. lumbricoides infection was higher among younger children than older children. While aggregation of parasite infection was observed, hookworm infection was more highly aggregated than either A. lumbricoides or T. trichiura. Multivariate analysis identified parental occupation, child's age and mother's education as the potential risk factors contributing to the high intensity of A. lumbricoides infection. Children from fishing families with low levels of education of the mother had the highest intensity of A. lumbricoides infection. As the outcome of chemotherapy programs to control soil transmitted helminth infection is dependant on the dynamics of their transmission, there is a need for further studies to better define the role of specific factors that determine their prevalence, intensity and aggregation in different epidemiological settings. (C) 2004 Elsevier B.V. All rights reserved.

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Background Most analyses of risks to health focus on the total burden of their aggregate effects. The distribution of risk-factor-attributable disease burden, for example by age or exposure level, can inform the selection and targeting of specific interventions and programs, and increase cost-effectiveness. Methods and Findings For 26 selected risk factors, expert working groups conducted comprehensive reviews of data on risk-factor exposure and hazard for 14 epidemiological subregions of the world, by age and sex. Age-sex-subregion-population attributable fractions were estimated and applied to the mortality and burden of disease estimates from the World Health Organization Global Burden of Disease database. Where possible, exposure levels were assessed as continuous measures, or as multiple categories. The proportion of risk-factor-attributable burden in different population subgroups, defined by age, sex, and exposure level, was estimated. For major cardiovascular risk factors (blood pressure, cholesterol, tobacco use, fruit and vegetable intake, body mass index, and physical inactivity) 43%-61% of attributable disease burden occurred between the ages of 15 and 59 y, and 87% of alcohol-attributable burden occurred in this age group. Most of the disease burden for continuous risks occurred in those with only moderately raised levels, not among those with levels above commonly used cut-points, such as those with hypertension or obesity. Of all disease burden attributable to being underweight during childhood, 55% occurred among children 1-3 standard deviations below the reference population median, and the remainder occurred among severely malnourished children, who were three or more standard deviations below median. Conclusions Many major global risks are widely spread in a population, rather than restricted to a minority. Population-based strategies that seek to shift the whole distribution of risk factors often have the potential to produce substantial reductions in disease burden.

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A new approach based on the nonlocal density functional theory to determine pore size distribution (PSD) of activated carbons and energetic heterogeneity of the pore wall is proposed. The energetic heterogeneity is modeled with an energy distribution function (EDF), describing the distribution of solid-fluid potential well depth (this distribution is a Dirac delta function for an energetic homogeneous surface). The approach allows simultaneous determining of the PSD (assuming slit shape) and EDF from nitrogen or argon isotherms at their respective boiling points by using a set of local isotherms calculated for a range of pore widths and solid-fluid potential well depths. It is found that the structure of the pore wall surface significantly differs from that of graphitized carbon black. This could be attributed to defects in the crystalline structure of the surface, active oxide centers, finite size of the pore walls (in either wall thickness or pore length), and so forth. Those factors depend on the precursor and the process of carbonization and activation and hence provide a fingerprint for each adsorbent. The approach allows very accurate correlation of the experimental adsorption isotherm and leads to PSDs that are simpler and more realistic than those obtained with the original nonlocal density functional theory.

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Ross River virus (RE) is a mosquito-borne arbovirus responsible for outbreaks of polyarthritic disease throughout Australia. To better understand human and environmental factors driving such events, 57 historical reports oil RR Outbreaks between 1896 and 1998 were examined collectively. The magnitude, regularity, seasonality, and locality of outbreaks were found to be wide ranging; however, analysis of climatic and tidal data highlighted that environmental conditions let differently ill tropical, arid, and temperate regions. Overall, rainfall seems to be the single most important risk factor, with over 90% of major outbreak locations receiving higher than average rainfall in preceding mouths. Many temperatures were close to average, particularly in tropical populations; however, in arid regions, below average maximum temperatures predominated, and ill southeast temperate regions, above average minimum temperatures predominated. High spring tides preceded coastal Outbreaks, both in the presence and absence of rainfall, and the relationship between rainfall and the Southern Oscillation Index and Lit Nina episodes suggest they may be useful predictive tools, but only ill southeast temperate regions. Such heterogeneity predisposing outbreaks supports the notion that there are different RE epidemiologies throughout Australia but also Suggests that generic parameters for the prediction and control of outbreaks are of limited use at a local level.

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Ross River virus is a common mosquito-borne arbovirus responsible for outbreaks of polyarthritic disease throughout Australia. To better understand climatic factors preceding outbreaks, we compared seasonal and monthly rainfall and temperature trends in outbreak and nonoutbreak years at four epidemic-prone locations. Our analyses showed that rainfall in outbreak years tended to be above average and higher than rainfall in nonoutbreak years. Overall temperatures were warmer during outbreak years. However, there were a number of distinct deviations in temperature, which seem to play a role in either promoting or inhibiting outbreaks. These preliminary findings show that climatic differences occur between outbreak and nonoutbreak years; however, seasonal and monthly trends differed across geo-climatic regions of the country. More detailed research is imperative if we are to optimize the surveillance and control of epidemic polyarthritic disease in Australia.

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Purpose: Several occupational carcinogens are metabolized by polymorphic enzymes. The distribution of the polymorphic enzymes N-acetyltransferase 2 (NAT2; substrates: aromatic amines), glutathione S-transferase M1 (GSTM1; substrates: e.g., reactive metabolites of polycyclic aromatic hydrocarbons), and glutathione S-transferase T1 (GSTT1; substrates: small molecules with 1 - 2 carbon atoms) were investigated. Material and Methods: At the urological department in Lutherstadt Wittenberg, 136 patients with a histologically proven transitional cell cancer of the urinary bladder were investigated for all occupations performed for more than 6 months. Several occupational and non-occupational risk factors were asked. The genotypes of NAT2, GSTM1, and GSTT1 were determined from leucocyte DNA by PCR. Results: Compared to the general population in Middle Europe, the percentage of GSTT1 negative persons (22.1%) was ordinary; the percentage of slow acetylators (59.6%) was in the upper normal range, while the percentage of GSTM1 negative persons (58.8%) was elevated in the entire group. Shifts in the distribution of the genotypes were observed in subgroups who had been exposed to asbestos (6/6 GSTM1 negative, 5/6 slow acetylators), rubber manufacturing (8/10 GSTM1 negative), and chlorinated solvents (9/15 GSTM1 negative). Conclusions: The overrepresentation of GSTM1 negative bladder cancer patients also in this industrialized area and more pronounced in several occupationally exposed subgroups points to an impact of the GSTM1 negative genotype in bladder carcinogenesis.

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Power systems are large scale nonlinear systems with high complexity. Various optimization techniques and expert systems have been used in power system planning. However, there are always some factors that cannot be quantified, modeled, or even expressed by expert systems. Moreover, such planning problems are often large scale optimization problems. Although computational algorithms that are capable of handling large dimensional problems can be used, the computational costs are still very high. To solve these problems, in this paper, investigation is made to explore the efficiency and effectiveness of combining mathematic algorithms with human intelligence. It had been discovered that humans can join the decision making progresses by cognitive feedback. Based on cognitive feedback and genetic algorithm, a new algorithm called cognitive genetic algorithm is presented. This algorithm can clarify and extract human's cognition. As an important application of this cognitive genetic algorithm, a practical decision method for power distribution system planning is proposed. By using this decision method, the optimal results that satisfy human expertise can be obtained and the limitations of human experts can be minimized in the mean time.

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Background Our aim was to calculate the global burden of disease and risk factors for 2001, to examine regional trends from 1990 to 2001, and to provide a starting point for the analysis of the Disease Control Priorities Project (DCPP). Methods We calculated mortality, incidence, prevalence, and disability adjusted life years (DALYs) for 136 diseases and injuries, for seven income/geographic country groups. To assess trends, we re-estimated all-cause mortality for 1990 with the same methods as for 2001. We estimated mortality and disease burden attributable to 19 risk factors. Findings About 56 million people died in 2001. Of these, 10.6 million were children, 99% of whom lived in low-and-middle-income countries. More than half of child deaths in 2001 were attributable to acute respiratory infections, measles, diarrhoea, malaria, and HIV/AIDS. The ten leading diseases for global disease burden were perinatal conditions, lower respiratory infections, ischaemic heart disease, cerebrovascular disease, HIV/AIDS, diarrhoeal diseases, unipolar major depression, malaria, chronic obstructive pulmonary disease, and tuberculosis. There was a 20% reduction in global disease burden per head due to communicable, maternal, perinatal, and nutritional conditions between 1990 and 2001. Almost half the disease burden in low-and-middle-income countries is now from non-communicable diseases (disease burden per head in Sub-Saharan Africa and the low-and-middle-income countries of Europe and Central Asia increased between 1990 and 2001). Undernutrition remains the leading risk factor for health loss. An estimated 45% of global mortality and 36% of global disease burden are attributable to the joint hazardous effects of the 19 risk factors studied. Uncertainty in all-cause mortality estimates ranged from around 1% in high-income countries to 15-20% in Sub-Saharan Africa. Uncertainty was larger for mortality from specific diseases, and for incidence and prevalence of non-fatal outcomes. Interpretation Despite uncertainties about mortality and burden of disease estimates, our findings suggest that substantial gains in health have been achieved in most populations, countered by the HIV/AIDS epidemic in Sub-Saharan Africa and setbacks in adult mortality in countries of the former Soviet Union. our results on major disease, injury, and risk factor causes of loss of health, together with information on the cost-effectiveness of interventions, can assist in accelerating progress towards better health and reducing the persistent differentials in health between poor and rich countries.

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Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.