837 resultados para Risk measures


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A major consequence of contamination at the local level’s population as it relates to environmental health and environmental engineering is childhood lead poisoning. Environmental contamination is one of the pressing environmental concerns facing the world today. Current approaches often focus on large contaminated industrial size sites that are designated by regulatory agencies for site remediation. Prior to this study, there were no known published studies conducted at the local and smaller scale, such as neighborhoods, where often much of the contamination is present to remediate. An environmental health study of local lead-poisoning data in Liberty City, Little Haiti and eastern Little Havana in Miami-Dade County, Florida accounted for a disproportionately high number of the county’s reported childhood lead poisoning cases. An engineering system was developed and designed for a comprehensive risk management methodology that is distinctively applicable to the geographical and environmental conditions of Miami-Dade County, Florida. Furthermore, a scientific approach for interpreting environmental health concerns, while involving detailed environmental engineering control measures and methods for site remediation in contained media was developed for implementation. Test samples were obtained from residents and sites in those specific communities in Miami-Dade County, Florida (Gasana and Chamorro 2002). Currently lead does not have an Oral Assessment, Inhalation Assessment, and Oral Slope Factor; variables that are required to run a quantitative risk assessment. However, various institutional controls from federal agencies’ standards and regulation for contaminated lead in media yield adequate maximum concentration limits (MCLs). For this study an MCL of .0015 (mg/L) was used. A risk management approach concerning contaminated media involving lead demonstrates that the linkage of environmental health and environmental engineering can yield a feasible solution.

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BACKGROUND: Recent studies have found low-normal potassium (K) to be associated with increased diabetes risk. We sought to verify these associations in a multi-ethnic US cohort; and to determine if these associations extend to US Hispanics and Asian-Americans. METHODS: We analyzed data from Multi-Ethnic Study of Atherosclerosis (MESA) participants who were free-of-diabetes at baseline. We examined cross-sectional associations between measures of K-serum, dietary, and urine-with fasting glucose and HOMA-IR. We examined longitudinal associations between K and diabetes risk over 8 years. FINDINGS: In multivariable models, compared to those with higher serum K (≥4.5mmol/L), those with lower serum K (<4.0mmol/L) had significantly higher fasting glucose [1.3 mg/dL (95%CI 0.2, 2.4), P-value = 0.03]. Incident diabetes developed in 1281 of 5415 at-risk participants. In minimally-adjusted models, we found inverse associations between serum and dietary K and diabetes risk. Compared to those with higher serum K, those with lower serum K had an HR (95% CI) of incident diabetes of 1.23 (1.04, 1.47), P-value = 0.02. However, these associations were attenuated in fully-adjusted models. We found no significant interaction between potassium and ethnicity. CONCLUSIONS: In this multi-ethnic cohort, we found a significant inverse association between serum K and fasting glucose but no significant association with longer-term diabetes risk. This inverse association between potassium and glucose must be studied further to understand the physiology and its potential impact on chronic health.

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Background: Injury is the leading cause of mortality for young people in Australia (AIHW, 2008). Adolescent injury mortality is consistently associated with risk taking behaviour, including transport and interpersonal violence (AIHW, 2003), which often occurs in the context of alcohol and other substance use. A rapid increase in risk taking and injury through early to late adolescence highlights the need for effective school based interventions. Aim: The aim of the current research was to examine the relationship between school connectedness and adolescent risk and injury, in order to inform effective prevention approaches. School connectedness, or students’ feelings of belongingness to school, has been shown to be a critical protective factor in adolescence which can be targeted effectively through teacher interventions. Despite evidence linking low school connectedness with increased health risk behaviour, including substance use and violence, research has not yet addressed possible links between connectedness and a broader range of risk taking behaviours (e.g. transport risks) or injury. Method: This study involved background data collection to inform the development of an intervention. A total of 595 Year 9 students (aged 13-14 years) from 5 Southeast Queensland high schools completed questionnaires that included measures of school connectedness, risk taking behaviour, alcohol and other substance use, and injuries. Results: Increased school connectedness was found to be associated with fewer transport risk behaviours and with decreased alcohol and other substance use for both males and females. Similarly, increased school connectedness was associated with fewer passenger and motorcycle injuries for male participants. Both males and females with increased school connectedness reported fewer alcohol related injuries. Implications: These results indicate that school connectedness appears to have protective effects for early adolescence. These findings may also hold for older adolescents and indicate that it may be an important factor to target in school based risk and injury prevention programs. A school connectedness intervention is currently being designed, focusing on teacher professional development. The intervention will be implemented in conjunction with a curriculum based injury prevention program for Year 9 students and will be evaluated through a large scale cluster randomised trial involving 26 schools.

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Aims: Changing behaviour to reduce stroke risk is a difficult prospect made particularly complex because of psychological factors. This study examined predictors of intentions and behaviours to reduce stroke risk in a sample of at-risk individuals, seeking to find how knowledge and health beliefs influenced both intention and actual behaviour to reduce stroke risk. Methods: A repeated measures design was used to assess behavioural intentions at time 1 (T1) and subsequent behaviour (T2). One hundred and twenty six respondents completed an online survey at T1, and behavioural follow-up data were collected from approximately 70 participants 1 month later. Predictors were stroke knowledge, demographic variables, and beliefs about stroke that were derived from an expanded health belief model. Dependent measures were: exercise and weight loss, and intention to engage in these behaviours to reduce stroke risk. Findings: Multiple hierarchical regression analyses showed that, for exercise and weight loss respectively, different health beliefs predicted intention to control stroke risk. The most important exercise-related health beliefs were benefits, susceptibility, and self-efficacy; for weight loss, the most important beliefs were barriers, and to a lesser degree, susceptibility and subjective norm. Conclusions: Health beliefs may play an important role in stroke prevention, particularly beliefs about susceptibility because these emerged for both behaviours. Stroke education and prevention programmes that selectively target the health beliefs relevant to specific behaviours may prove most efficacious.

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Cutaneous malignant melanoma (CMM) is a major health issue in Queensland, Australia, which has the world’s highest incidence. Recent molecular and epidemiologic studies suggest that CMM arises through multiple etiological pathways involving gene-environment interactions. Understanding the potential mechanisms leading to CMM requires larger studies than those previously conducted. This article describes the design and baseline characteristics of Q-MEGA, the Queensland Study of Melanoma: Environmental and Genetic Associations, which followed up 4 population-based samples of CMM patients in Queensland, including children, adolescents, men aged over 50, and a large sample of adult cases and their families, including twins. Q-MEGA aims to investigate the roles of genetic and environmental factors, and their interaction, in the etiology of melanoma. Three thousand, four hundred and seventy-one participants took part in the follow-up study and were administered a computer-assisted telephone interview in 2002-2005. Updated data on environmental and phenotypic risk factors, and 2777 blood samples were collected from interviewed participants as well as a subset of relatives. This study provides a large and well-described population-based sample of CMM cases with follow-up data. Characteristics of the cases and repeatability of sun exposure and phenotype measures between the baseline and the follow-up surveys, from 6 to 17 years later, are also described.

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Illegal pedestrian behaviour is common and is reported as a factor in many pedestrian crashes. Since walking is being promoted for its health and environmental benefits, minimisation of its associated risks is of interest. The risk associated with illegal road crossing is unclear, and better information would assist in setting a rationale for enforcement and priorities for public education. An observation survey of pedestrian behaviour was conducted at signalised intersections in the Brisbane CBD (Queensland, Australia) on typical workdays, using behavioural categories that were identifiable in police crash reports. The survey confirmed high levels of crossing against the lights, or close enough to the lights that they should legally have been used. Measures of exposure for crossing legally, against the lights, and close to the lights were generated by weighting the observation data. Relative risk ratios were calculated for these categories using crash data from the observation sites and adjacent midblocks. Crossing against the lights and crossing close to the lights both exhibited a crash risk per crossing event approximately eight times that of legal crossing at signalised intersections. The implications of these results for enforcement and education are discussed, along with the limitations of the study.

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First-degree relatives of men with prostate cancer have a higher risk of being diagnosed with prostate cancer than men without a family history. The present review examines the prevalence and predictors of testing in first-degree relatives, perceptions of risk, prostate cancer knowledge and psychological consequences of screening. Medline, PsycInfo and Cinahl databases were searched for articles examining risk perceptions or screening practices of first-degree relatives of men with prostate cancer for the period of 1990 to August 2007. Eighteen studies were eligible for inclusion. First-degree relatives participated in prostate-specific antigen (PSA) testing more and perceived their risk of prostate cancer to be higher than men without a family history. Family history factors (e.g. being an unaffected son rather than an unaffected brother) were consistent predictors of PSA testing. Studies were characterized by sampling biases and a lack of longitudinal assessments. Prospective, longitudinal assessments with well-validated and comprehensive measures are needed to identify factors that cue the uptake of screening and from this develop an evidence base for decision support. Men with a family history may benefit from targeted communication about the risks and benefits of prostate cancer testing that responds to the implications of their heightened risk.

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Purpose: Television viewing time, independent of leisure-time physical activity, has cross-sectional relationships with the metabolic syndrome and its individual components. We examined whether baseline and five-year changes in self-reported television viewing time are associated with changes in continuous biomarkers of cardio-metabolic risk (waist circumference, triglycerides, high density lipoprotein cholesterol, systolic and diastolic blood pressure, fasting plasma glucose; and a clustered cardio-metabolic risk score) in Australian adults. Methods: AusDiab is a prospective, population-based cohort study with biological, behavioral, and demographic measures collected in 1999–2000 and 2004–2005. Non-institutionalized adults aged ≥ 25 years were measured at baseline (11,247; 55% of those completing an initial household interview); 6,400 took part in the five-year follow-up biomedical examination, and 3,846 met the inclusion criteria for this analysis. Multiple linear regression analysis was used and unstandardized B coefficients (95% CI) are provided. Results: Baseline television viewing time (10 hours/week unit) was not significantly associated with change in any of the biomarkers of cardio-metabolic risk. Increases in television viewing time over five years (10 hours/week unit) were associated with increases in: waist circumference (cm) (men: 0.43 (0.08, 0.78), P = 0.02; women: 0.68 (0.30, 1.05), P <0.001), diastolic blood pressure (mmHg) (women: 0.47 (0.02, 0.92), P = 0.04), and the clustered cardio-metabolic risk score (women: 0.03 (0.01, 0.05), P = 0.007). These associations were independent of baseline television viewing time and baseline and change in physical activity and other potential confounders. Conclusion: These findings indicate that an increase in television viewing time is associated with adverse cardio-metabolic biomarker changes. Further prospective studies using objective measures of several sedentary behaviors are required to confirm causality of the associations found.

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Aims & Rationale/Objectives: With the knowledge that overweight is a major public health concern in Australia, that a multidisciplinary team approach to the management of lifestyle-related conditions is supported, and that the Australian Government recently recognised the role of the exercise physiologist (EP) in reducing the health burden of disease by their inclusion for reimbursement under the Medicare Plus scheme, this study sought to undertake a pilot RCT to compare GP and EP interventions to reduce primary cardiovascular risk in the overweight general practice population. Methods and Measures: Overweight patients recruited by a convenience sample of GPs were randomised into one of three arms: the control group, or the GP or EP intervention group (in which patients received either five GP or five EP consultations over 24 weeks). Patients had baseline, 12- and 24-week measures of body composition and cardio-respiratory fitness, and completed baseline and end-of-study surveys, fasting lipids and glucose. GPs and EPs completed an end-of-study survey. Results:Sixty-seven patients attended the baseline assessment. Overall retention rate was 67%. Patients were generally satisfied with the effectiveness of the interventions and their weight reduction. Favourable trends in BMI, weight, glucose and exercise levels for GP and EP intervention groups and in physical activity levels for all groups Conclusions: This study supports the feasibility of a RCT of GP and EP interventions for decreasing primary cardiovascular risk in the overweight general practice population.

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The case study of Lusoponte illustrates the concession awarded by the Portuguese Government to finance, design, build and operate two bridges over the Tagus in Lisbon, Portugal. It includes an overview of the project's background and an analysis of the main risk categories stating both the actual risks encountered and the mitigation measures adopted. Throughout the project a great attention was given to whole life cycle costs, and gains in efficiency and cost control. Among the lessons that can be learned from both the public and private sector is that a complete risk management analysis must include not only the technical factors but also a realistic assessment of environmental and social risks. These were the risks that were somewhat overseen and that caused the main problems to the project's development.

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BACKGROUND:Previous epidemiological investigations of associations between dietary glycemic intake and insulin resistance have used average daily measures of glycemic index (GI) and glycemic load (GL). We explored multiple and novel measures of dietary glycemic intake to determine which was most predictive of an association with insulin resistance.METHODS:Usual dietary intakes were assessed by diet history interview in women aged 42-81 years participating in the Longitudinal Assessment of Ageing in Women. Daily measures of dietary glycemic intake (n = 329) were carbohydrate, GI, GL, and GL per megacalorie (GL/Mcal), while meal based measures (n = 200) were breakfast, lunch and dinner GL; and a new measure, GL peak score, to represent meal peaks. Insulin resistant status was defined as a homeostasis model assessment (HOMA) value of >3.99; HOMA as a continuous variable was also investigated.RESULTS:GL, GL/Mcal, carbohydrate (all P < 0.01), GL peak score (P = 0.04) and lunch GL (P = 0.04) were positively and independently associated with insulin resistant status. Daily measures were more predictive than meal-based measures, with minimal difference between GL/Mcal, GL and carbohydrate. No significant associations were observed with HOMA as a continuous variable.CONCLUSION:A dietary pattern with high peaks of GL above the individual's average intake was a significant independent predictor of insulin resistance in this population, however the contribution was less than daily GL and carbohydrate variables. Accounting for energy intake slightly increased the predictive ability of GL, which is potentially important when examining disease risk in more diverse populations with wider variations in energy requirements.

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Background: The effect of patient education on reducing stroke has had mixed effects, raising questions about how to achieve optimal benefit. Because past evaluations have typically lacked an appropriate theoretical base, the design of past research may have missed important effects. --------- Method: This study used a social cognitive framework to identify variables that might change in response to education. A mixed design was used to evaluate two approaches to an intervention, both of which included education. Fifty seniors completed a measure of stroke knowledge and beliefs twice: before and after an intervention that was either standard (educational brochure plus activities that were not about stroke) or enhanced (educational brochure plus activities designed to enhance beliefs about stroke). Outcome measures were health beliefs, intention to exercise to reduce stroke, and stroke knowledge. --------- Results: Selected beliefs changed significantly over time but not differentially across conditions. Beliefs that changed were (a) perceived susceptibility to stroke and (b) perceived benefit of exercise to reduce risk. Benefit beliefs, in particular, were strongly and positively associated with intention to exercise. -------- Conclusion: Findings suggest that basic approaches to patient education may influence health beliefs. More effective stroke prevention programs may result from continued consideration of the role of health beliefs in such programs.

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Using the Education Queensland Reform Agenda to illustrate examples and approaches to education reform, this article discusses education reform for at-risk youth. It argues that the characteristics of modernity, the rise of Mode 2 Society, and the power asymmetries associated with the emergence of the politico-economic will contain the reform ambitions of the Education Queensland and other education reform agendas. It is proposed that the State adopt a transgressive and complimentary set of reform strategies including the adoption of distributed governance, making available meaningful school performance data, encouraging experimentation and facilitating broad stakeholder, community and neighbourhood engagement in school planning and operations. The article argues that measures such as these will assist to mobilize trust, minimise social fragmentation, generate and regenerate community resources, build cohesion, foster the socio-cultural-self-identities of 'at-risk' youth and will assist youth to achieve full participation in a robust and vibrant democracy.

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The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.