871 resultados para Area-level disadvantage
Resumo:
The implementation record of the Country Specific Recommendations (CSRs) has declined over time, as financial turbulence lessened and the economic outlook started to improve. Urgency for reforms seemingly receded to leave room to request member states to move towards more accommodative stances. It is mainly the small countries that implement, at least partially, the recommendations addressed to them. Unfortunately, there is little that the EU can do to change the status quo. Yet, the President of the Eurogroup could be held accountable for the implementation of the recommendations addressed to the euro area. The creation of National Competitiveness Boards risks making the European Semester even more complex and likely to have little impact in the countries that need them most, namely large countries and those with poor governance. To make it effective, a procedure would be needed to make national wage norms consistent at the euro-area level, which may be a very difficult objective to achieve.
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Understanding the particularly low intake of fruits and vegetables among socioeconomically disadvantaged groups is an important issue for public health. This study investigated whether access to retail outlets is similar across areas of varying socioeconomic disadvantage in an Australian urban setting, in terms of distance, the numbers of local shops, and their opening hours. This ecological cross-sectional study used 50 randomly sampled census collection districts and their nearby shopping environment (i.e. within 2.5 km), and generally found minimal or no socioeconomic differences in shopping infrastructure. Important methodological and social/economic issues may explain this contrast with overseas findings.
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This study has concentrated on the development of an impact simulation model for use at the sub-national level. The necessity for the development of this model was demonstrated by the growth of local economic initiatives during the 1970's, and the lack of monitoring and evaluation exercise to assess their success and cost-effectiveness. The first stage of research involved the confirmation that the potential for micro-economic and spatial initiatives existed. This was done by identifying the existence of involuntary structural unemployment. The second stage examined the range of employment policy options from the macroeconomic, micro-economic and spatial perspectives, and focused on the need for evaluation of those policies. The need for spatial impact evaluation exercise in respect of other exogenous shocks, and structural changes was also recognised. The final stage involved the investigation of current techniques of evaluation and their adaptation for the purpose in hand. This led to a recognition of a gap in the armoury of techniques. The employment-dependency model has been developed to fill that gap, providing a low-budget model, capable of implementation at the small area level and generating a vast array of industrially disaggregate data, in terms of employment, employment-income, profits, value-added and gross income, related to levels of United Kingdom final demand. Thus providing scope for a variety of impact simulation exercises.
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Background: Patterns of diagnosis and management for men diagnosed with prostate cancer in Queensland, Australia, have not yet been systematically documented and so assumptions of equity are untested. This longitudinal study investigates the association between prostate cancer diagnostic and treatment outcomes and key area-level characteristics and individual-level demographic, clinical and psychosocial factors.---------- Methods/Design: A total of 1064 men diagnosed with prostate cancer between February 2005 and July 2007 were recruited through hospital-based urology outpatient clinics and private practices in the centres of Brisbane, Townsville and Mackay (82% of those referred). Additional clinical and diagnostic information for all 6609 men diagnosed with prostate cancer in Queensland during the study period was obtained via the population-based Queensland Cancer Registry. Respondent data are collected using telephone and self-administered questionnaires at pre-treatment and at 2 months, 6 months, 12 months, 24 months, 36 months, 48 months and 60 months post-treatment. Assessments include demographics, medical history, patterns of care, disease and treatment characteristics together with outcomes associated with prostate cancer, as well as information about quality of life and psychological adjustment. Complementary detailed treatment information is abstracted from participants’ medical records held in hospitals and private treatment facilities and collated with health service utilisation data obtained from Medicare Australia. Information about the characteristics of geographical areas is being obtained from data custodians such as the Australian Bureau of Statistics. Geo-coding and spatial technology will be used to calculate road travel distances from patients’ residences to treatment centres. Analyses will be conducted using standard statistical methods along with multilevel regression models including individual and area-level components.---------- Conclusions: Information about the diagnostic and treatment patterns of men diagnosed with prostate cancer is crucial for rational planning and development of health delivery and supportive care services to ensure equitable access to health services, regardless of geographical location and individual characteristics. This study is a secondary outcome of the randomised controlled trial registered with the Australian New Zealand Clinical Trials Registry (ACTRN12607000233426)
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OBJECTIVES To investigate and describe the relationship between indigenous Australian populations, residential aged care services, and community-onset Staphylococcus aureus bacteremia (SAB) among patients admitted to public hospitals in Queensland, Australia. DESIGN Ecological study. METHODS We used administrative healthcare data linked to microbiology results from patients with SAB admitted to Queensland public hospitals from 2005 through 2010 to identify community-onset infections. Data about indigenous Australian population and residential aged care services at the local government area level were obtained from the Queensland Office of Economic and Statistical Research. Associations between community-onset SAB and indigenous Australian population and residential aged care services were calculated using Poisson regression models in a Bayesian framework. Choropleth maps were used to describe the spatial patterns of SAB risk. RESULTS We observed a 21% increase in relative risk (RR) of bacteremia with methicillin-susceptible S. aureus (MSSA; RR, 1.21 [95% credible interval, 1.15-1.26]) and a 24% increase in RR with nonmultiresistant methicillin-resistant S. aureus (nmMRSA; RR, 1.24 [95% credible interval, 1.13-1.34]) with a 10% increase in the indigenous Australian population proportion. There was no significant association between RR of SAB and the number of residential aged care services. Areas with the highest RR for nmMRSA and MSSA bacteremia were identified in the northern and western regions of Queensland. CONCLUSIONS The RR of community-onset SAB varied spatially across Queensland. There was increased RR of community-onset SAB with nmMRSA and MSSA in areas of Queensland with increased indigenous population proportions. Additional research should be undertaken to understand other factors that increase the risk of infection due to this organism.
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Ross River virus (RRV) infection is a debilitating disease which has a significant impact on population health, economic productivity and tourism in Australia. This study examined epidemiological patterns of the RRV disease in Queensland, Australia between January 2001 and December 2011 at a statistical local area level. Spatial-temporal analyses were used to identify the patterns of the disease distribution over time stratified by age, sex and space. The results show that the mean annual incidence was 54 per 100,000 people, with a male: female ratio of 1:1.1. Two space-time clusters were identified: the areas adjacent to Townsville, on the eastern coast of Queensland; and the south east areas. Thus, although public health intervention should be considered across all areas in which RRV occurs, it should specifically focus on these high risk regions, particularly during the summer and autumn to reduce the social and economic impacts of RRV.
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BACKGROUND: To develop evidence-based approaches for reducing sedentary behavior, there is a need to identify the specific settings where prolonged sitting occurs, associated factors, and variations. PURPOSE: To examine the sociodemographic and health factors associated with mid-aged adults' sitting time in three contexts and variations between weekdays and weekend days. METHODS: A mail survey was sent to 17,000 adults (aged 40-65 years) in 2007; 11,037 responses were received (68.5%); and 7719 were analyzed in 2010. Respondents indicated time spent sitting on a usual weekday and weekend day for watching TV, general leisure, and home computer use. Multivariate linear mixed models with area-level random intercepts were used to examine (1) associations between sociodemographic and health variables and sitting time, and (2) interaction effects of weekday/weekend day with each of gender, age, education, and employment status, on sitting time. RESULTS: For each context, longer sitting times were reported by those single and living alone, and those whose health restricted activity. For watching TV, longer sitting times were reported by men; smokers; and those with high school or lower education, not in paid employment, in poor health, and with BMI ≥25. For general leisure, longer sitting times were reported by women, smokers, and those not employed full-time. For home computer use, longer sitting times were reported by men; and those aged 40-44 years, with university qualifications; in the mid-income range; and with BMI ≥30. Sitting times tended to be longer on weekend days than weekdays, although the extent of this differed among sociodemographic groups. CONCLUSIONS: Sociodemographic and health factors associated with sitting time differ by context and between weekdays and weekend days.
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This study aimed to explore the spatiotemporal patterns, geographic co-distribution, and socio-ecological drivers of childhood pneumonia and diarrhea in Queensland. A Bayesian conditional autoregressive model was used to quantify the impacts of socio-ecological factors on both childhood pneumonia and diarrhea at a postal area level. A distinct seasonality of childhood pneumonia and diarrhea was found. Childhood pneumonia and diarrhea mainly distributed in northwest of Queensland. Mount Isa was the high-risk cluster where childhood pneumonia and diarrhea co-distributed. Emergency department visits (EDVs) for pneumonia increased by 3% per 10-mm increase in monthly average rainfall, in wet seasons. In comparison, a 10-mm increase in monthly average rainfall may increase 4% of EDVs for diarrhea. Monthly average temperature was negatively associated with EDVs for childhood diarrhea, in wet seasons. Low socioeconomic index for areas (SEIFA) was associated with high EDVs for childhood pneumonia. Future pneumonia and diarrhea prevention and control measures in Queensland should focus more on Mount Isa.
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Cane fibre content has increased over the past ten years. Some of that increase can be attributed to new varieties selected for release. This paper reviews the existing methods for quantifying the fibre characteristics of a variety, including fibre content and fibre quality measurements – shear strength, impact resistance and short fibre content. The variety selection process is presented and it is reported that fibre content has zero weighting in the current selection index. An updated variety selection approach is proposed, potentially replacing the existing selection process relating to fibre. This alternative approach involves the use of a more complex mill area level model that accounts for harvesting, transport and processing equipment, taking into account capacity, efficiency and operational impacts, along with the end use for the bagasse. The approach will ultimately determine a net economic value for the variety. The methodology lends itself to a determination of the fibre properties that have a significant impact on the economic value so that variety tests can better target the critical properties. A low-pressure compression test is proposed as a good test to provide an assessment of the impact of a variety on milling capacity. NIR methodology is proposed as a technology to lead to a more rapid assessment of fibre properties, and hence the opportunity to more comprehensively test for fibre impacts at an earlier stage of variety development.
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Background Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in cancer survival. Multilevel models assume independent geographical areas, whereas spatial models explicitly incorporate geographical correlation, often via a conditional autoregressive prior. However the relative merits of these methods for large population-based studies have not been explored. Using a case-study approach, we report on the implications of using multilevel and spatial survival models to study geographical inequalities in all-cause survival. Methods Multilevel discrete-time and Bayesian spatial survival models were used to study geographical inequalities in all-cause survival for a population-based colorectal cancer cohort of 22,727 cases aged 20–84 years diagnosed during 1997–2007 from Queensland, Australia. Results Both approaches were viable on this large dataset, and produced similar estimates of the fixed effects. After adding area-level covariates, the between-area variability in survival using multilevel discrete-time models was no longer significant. Spatial inequalities in survival were also markedly reduced after adjusting for aggregated area-level covariates. Only the multilevel approach however, provided an estimation of the contribution of geographical variation to the total variation in survival between individual patients. Conclusions With little difference observed between the two approaches in the estimation of fixed effects, multilevel models should be favored if there is a clear hierarchical data structure and measuring the independent impact of individual- and area-level effects on survival differences is of primary interest. Bayesian spatial analyses may be preferred if spatial correlation between areas is important and if the priority is to assess small-area variations in survival and map spatial patterns. Both approaches can be readily fitted to geographically enabled survival data from international settings
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Statistical analyses of health program participation seek to address a number of objectives compatible with the evaluation of demand for current resources. In this spirit, a spatial hierarchical model is developed for disentangling patterns in participation at the small area level, as a function of population-based demand and additional variation. For the former, a constrained gravity model is proposed to quantify factors associated with spatial choice and account for competition effects, for programs delivered by multiple clinics. The implications of gravity model misspecification within a mixed effects framework are also explored. The proposed model is applied to participation data from a no-fee mammography program in Brisbane, Australia. Attention is paid to the interpretation of various model outputs and their relevance for public health policy.
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Background A pandemic strain of influenza A spread rapidly around the world in 2009, now referred to as pandemic (H1N1) 2009. This study aimed to examine the spatiotemporal variation in the transmission rate of pandemic (H1N1) 2009 associated with changes in local socio-environmental conditions from May 7–December 31, 2009, at a postal area level in Queensland, Australia. Method We used the data on laboratory-confirmed H1N1 cases to examine the spatiotemporal dynamics of transmission using a flexible Bayesian, space–time, Susceptible-Infected-Recovered (SIR) modelling approach. The model incorporated parameters describing spatiotemporal variation in H1N1 infection and local socio-environmental factors. Results The weekly transmission rate of pandemic (H1N1) 2009 was negatively associated with the weekly area-mean maximum temperature at a lag of 1 week (LMXT) (posterior mean: −0.341; 95% credible interval (CI): −0.370–−0.311) and the socio-economic index for area (SEIFA) (posterior mean: −0.003; 95% CI: −0.004–−0.001), and was positively associated with the product of LMXT and the weekly area-mean vapour pressure at a lag of 1 week (LVAP) (posterior mean: 0.008; 95% CI: 0.007–0.009). There was substantial spatiotemporal variation in transmission rate of pandemic (H1N1) 2009 across Queensland over the epidemic period. High random effects of estimated transmission rates were apparent in remote areas and some postal areas with higher proportion of indigenous populations and smaller overall populations. Conclusions Local SEIFA and local atmospheric conditions were associated with the transmission rate of pandemic (H1N1) 2009. The more populated regions displayed consistent and synchronized epidemics with low average transmission rates. The less populated regions had high average transmission rates with more variations during the H1N1 epidemic period.
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- Objective The purpose of this research was to explore which demographic and health status variables moderated the relationship between psychological distress and three nutrition indicators: the consumption of fruits, vegetables and takeaway. - Method We analysed data from the 2009 Self-Reported Health Status Survey Report collected in the state of Queensland, Australia. Adults (N = 6881) reported several demographic and health status variables. Moderated logistic regression models were estimated separately for the three nutrition indicators, testing as moderators demographic (age, gender, educational attainment, household income, remoteness, and area-level socioeconomic status) and health status indicators (body mass index, high cholesterol, high blood pressure, and diabetes status). - Results Several significant interactions emerged between psychological distress, demographic (age, area-level socioeconomic status, and income level), and health status variables (body mass index, diabetes status) in predicting the nutrition indicators. Relationships between distress and the nutrition indicators were not significantly different by gender, remoteness, educational attainment, high cholesterol status, and high blood pressure status. - Conclusions The associations between psychological distress and several nutrition indicators differ amongst population subgroups. These findings suggest that in distressed adults, age, area-level socio-economic status, income level, body mass index, and diabetes status may serve as protective or risk factors through increasing or decreasing the likelihood of meeting nutritional guidelines. Public health interventions for improving dietary behaviours and nutrition may be more effective if they take into account the moderators identified in this study rather than using global interventions.
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Background
It is not clear whether the availability of tobacco affects the likelihood of smoking cessation. We examined whether the proximity to a tobacco store and
the number of stores were associated with smoking cessation, and compared results for proximity variables based on walking and straight-line (as the crow flies) distance.
Methods
The study population consisted of 8751 baseline smokers from the Finnish Public Sector study in 1997–2005. Smoking intensity (cigarettes/day) was
determined at baseline and smoking cessation was determined from a follow-up survey in 2008–2009. Proximity was measured using straight-line and walking
distance from home to the nearest tobacco store, and another exposure variable was the number of stores within 0.50 km from home. We calculated associations
with log-binomial regression models, adjusting for individual-level and area-level confounders.
Results
Of the participants, 3482 (39.8%) quit smoking during the follow-up (mean follow-up 5.5 years, SD 2.3 years). Among men who were moderate/heavy smokers at baseline and lived <0.50 km walking distance from the nearest tobacco store, the likelihood of smoking cessation was 27% (95% CI 12% to 40%) lower compared with those living ≥0.50 km from a store. Having even one store within 0.50 km walking distance from home decreased cessation in men who were moderate/heavy smokers by 37% (95% CI 19% to 51%). No decrease was found for men who were light smokers at baseline or for women.
Conclusions
Living within walking distance of a tobacco store reduced the likelihood of smoking cessation among men who were moderate/heavy smokers.
Resumo:
Background
Neighbourhood segregation has been described as a fundamental determinant of physical health, but literature on its effect on mental health is less clear. Whilst most previous research has relied on conceptualized measures of segregation, Northern Ireland is unique as it contains physical manifestations of segregation in the form of segregation barriers (or “peacelines”) which can be used to accurately identify residential segregation.
Methods
We used population-wide health record data on over 1.3 million individuals, to analyse the effect of residential segregation, measured by both the formal Dissimilarity Index and by proximity to a segregation barrier, on the likelihood of poor mental health.
Results
Using multi-level logistic regression models we found residential segregation measured by the Dissimilarity Index poses no additional risk to the likelihood of poor mental health after adjustment for area-level deprivation. However, residence in an area segregated by a “peaceline” increases the likelihood of antidepressant medication by 19% (OR=1.19, 95% CI: 1.14, 1.23) and anxiolytic medication by 39% (OR=1.39, 95% CI: 1.32, 1.48), even after adjustment for gender, age, conurbation, deprivation and crime.
Conclusions
Living in an area segregated by a ‘peaceline’ is detrimental to mental health suggesting segregated areas characterised by a heightened sense of ‘other’ pose a greater risk to mental health. The difference in results based on segregation measure highlights the importance of choice of measure when studying segregation.