Objective To investigate the time relations between long haul air travel and venous thromboembolism. Design Record linkage study using the case crossover approach. Setting Western Australia. Participants 5408 patients admitted to hospital with venous thromboembolism and matched with data for arrivals of international flights during 1981-99. Results The risk of venous thromboembolism is increased for only two weeks after a long haul flight; 46 Australian citizens and 200 non-Australian citizens had an episode of venous thromboembolism during this so called hazard period. The relative risk during this period for Australian citizens was 4.17 (95% confidence interval, 2.94 to 5.40), with 76% of cases (n = 35) attributable to the preceding flight. A "healthy traveller" effect was observed, particularly for Australian citizens. Conclusions The annual risk of venous thromboembolism is increased by 12% if one long haul flight is taken yearly. The average risk of death from flight related venous thromboembolism is small compared with that from motor vehicle crashes and injuries at work. The individual risk of death from flight related venous thromboembolism for people with certain pre-existing medical conditions is, however, likely to be greater than the average risk of 1 per 2 million for passengers arriving from a flight. Airlines and health authorities should continue to advise passengers on how to minimise risk.
To derive correction equations based on nationally representative data, for the error associated with self‐reported height and weight and to apply these to recent estimates of overweight and obesity in the Australian adult population.
Linear regression was used to derive correction equations to predict reporting error on height, weight and body mass index (BMI) for 8,435 adults, aged 20 and over, who had their height and weight accurately measured as participants of the 1995 National Nutrition Survey (NNS) and who had also supplied self‐reported information within the 1995 National Health Survey (NHS).
Evaluation of different correction algorithms suggests that simple correction equations for height and weight (each with one independent variable) are the most useful in the prediction of corrected prevalence of overweight and obesity. Applying these equations to nationally representative data suggests that the prevalence of overweight and obesity (BMI>=25) in Australia in 2004/05 was 66% compared with the value of 54% determined from self‐reported data.
We present a simple and reliable method for correcting true prevalence of overweight and obesity from self‐reported data.
In order to get realistic estimates of overweight and obesity in Australia, either measured height and weight data should be collected directly, or equations to correct for self report error should be used.
Controversy surrounds structural reform in local government, especially efforts aimed at involuntarily reducing the number of local authorities to secure scale economies. We examined whether scale economies exist in local government outlays by analyzing the expenditure of 152 New South Wales councils. Initially, council expenditure is characterized by scale economies. However, given the correlation between population and population density, it is important to determine whether the influence of population on expenditure is due to variations in population density. When areas are decomposed into subgroups on the basis of density, the evidence of scale economies largely disappears.
The aim of this study was to examine the association between musculoskeletal disorders and the level of obesity (as defined by the body mass index) for a sample of the Australian population aged 20-64. A logistic regression model was used to estimate the association between musculoskeletal disorders and obesity, controlling for a range of socio-demographic characteristics. Individual-level data on obesity, musculoskeletal disorders, and various socio-demographic characteristics were extracted from the Australian Bureau of Statistics (ABS) 1995 National Health Survey (NHS). Individuals with musculoskeletal disorders were identified using ICD-9 codes 710-739 from a sample of 28,376 individuals from the non-institutionalised population. Estimates from the logistic regression equation indicate that there is a statistically significant positive relationship between the probability of having a musculoskeletal disorder and the level of obesity. Socio-demographic variables such as age, sex, origin, income level, employment status and geographic location also had a statistically significant relationship. This information can be used by public health practitioners and educators to identify those at risk and to design health strategies that target at-risk patients.
Traditionally, the problem of determining the optimal size in local government has been empirically assessed by estimating the relationship between population size and the costs of services (usually measured in terms of per capita expenditure). These studies, however, have proved largely inconclusive. In comparison, an empirical analysis based on the relationship between the size of government and community satisfaction offers a potentially fruitful contribution to the debate regarding the optimal size of local government. However, to date, few studies have followed this approach. We therefore contribute to this literature by exploring the relationship between population size and community satisfaction for Victorian councils. Our findings provide evidence of an inverted 'U-shaped' relationship, which predicts low community satisfaction at very large and very small population sizes.
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