Use of Bayesian geostatistical prediction to estimate local variations in Schistosoma haematobium infection in western Africa

Objective We aimed to predict sub-national spatial variation in numbers of people infected with Schistosoma haematobium, and associated uncertainties, in Burkina Faso, Mali and Niger, prior to implementation of national control programmes. Methods We used national field survey datasets covering a contiguous area 2,750 × 850 km, from 26,790 school-aged children (5–14 years) in 418 schools. Bayesian geostatistical models were used to predict prevalence of high and low intensity infections and associated 95% credible intervals (CrI). Numbers infected were determined by multiplying predicted prevalence by numbers of school-aged children in 1 km2 pixels covering the study area. Findings Numbers of school-aged children with low-intensity infections were: 433,268 in Burkina Faso, 872,328 in Mali and 580,286 in Niger. Numbers with high-intensity infections were: 416,009 in Burkina Faso, 511,845 in Mali and 254,150 in Niger. 95% CrIs (indicative of uncertainty) were wide; e.g. the mean number of boys aged 10–14 years infected in Mali was 140,200 (95% CrI 6200, 512,100). Conclusion National aggregate estimates for numbers infected mask important local variation, e.g. most S. haematobium infections in Niger occur in the Niger River valley. Prevalence of high-intensity infections was strongly clustered in foci in western and central Mali, north-eastern and northwestern Burkina Faso and the Niger River valley in Niger. Populations in these foci are likely to carry the bulk of the urinary schistosomiasis burden and should receive priority for schistosomiasis control. Uncertainties in predicted prevalence and numbers infected should be acknowledged and taken into consideration by control programme planners.

A pilot randomised control trial of general practitioner and exercise physiologist interventions to reduce primary cardiovascular risk in overweight patients [Abstract]

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.

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

Disease prevention and control

Globally, the main contributors to morbidity and mortality are chronic diseases, including cardiovascular disease and diabetes. Chronic diseases are costly and partially avoidable, with around sixty percent of deaths and nearly fifty percent of the global disease burden attributable to these conditions. By 2020, chronic illnesses will likely be the leading cause of disability worldwide. Existing health care systems, both national and international, that focus on acute episodic health conditions, cannot address the worldwide transition to chronic illness; nor are they appropriate for the ongoing care and management of those already afflicted with chronic diseases. International and Australian strategic planning documents articulate similar elements to manage chronic disease; including the need for aligning sectoral policies for health, forming partnerships and engaging communities in decision-making. The Australian National Chronic Disease Strategy focuses on four core areas for managing chronic disease; prevention across the continuum, early detection and treatment, integrated and coordinated care, and self-management. Such a comprehensive approach incorporates the entire population continuum, from the ‘healthy’, to those with risk factors, through to people suffering from chronic conditions and their sequelae. This chapter examines comprehensive approach to the prevention, management and care of the population with non-communicable, chronic diseases and communicable diseases. It analyses models of care in the context of need, service delivery options and the potential to prevent or manage early intervention for chronic and communicable diseases. Approaches to chronic diseases require integrated approaches that incorporate interventions targeted at both individuals and populations, and emphasise the shared risk factors of different conditions. Communicable diseases are a common and significant contributor to ill health throughout the world. In many countries, this impact has been minimised by the combined efforts of preventative health measures and improved treatment of infectious diseases. However in underdeveloped nations, communicable diseases continue to contribute significantly to the burden of disease. The aim of this chapter is to outline the impact that chronic and communicable diseases have on the health of the community, the public health strategies that are used to reduce the burden of those diseases and the old and emerging risks to public health from infectious diseases.

The impact of globalisation on health

After reading this chapter, you should be able to: • understand the concept of globalisation and appreciate its complexity • identify the significant impacts of globalisation on population health, particularly the incidence of communicable and non-communicable diseases • understand the distribution of the global burden of disease in high-, middle- and low-income countries • critically evaluate the factors contributing to the major causes of death in low-income countries • understand some of the achievements of the global public health community and appreciate the challenges it faces.

Regular exercise participation mediates the affective response to acute bouts of vigorous exercise

Physical inactivity is a leading factor associated with cardiovascular disease and a major contributor to the global burden of disease in developed countries. Subjective mood states associated with acute exercise are likely to influence future exercise adherence and warrant further investigation. The present study examined the effects of a single bout of vigorous exercise on mood and anxiety between individuals with substantially different exercise participation histories. Mood and anxiety were assessed one day before an exercise test (baseline), 5 minutes before (pre-test) and again 10 and 25 minutes post-exercise. Participants were 31 university students (16 males, 15 females; Age M = 20), with 16 participants reporting a history of regular exercise with the remaining 15 reporting to not exercise regularly. Each participant completed an incremental exercise test on a Monark cycle ergometer to volitional exhaustion. Regular exercisers reported significant post-exercise improvements in mood and reductions in state anxiety. By contrast, non-regular exercisers reported an initial decline in post-exercise mood and increased anxiety, followed by an improvement in mood and reduction in anxiety back to pre-exercise levels. Our findings suggest that previous exercise participation mediates affective responses to acute bouts of vigorous exercise. We suggest that to maximise positive mood changes following exercise, practitioners should carefully consider the individual’s exercise participation history before prescribing new regimes.

Access and Quality of Heart Failure Management Programs in Australia

Background/aim In response to the high burden of disease associated with chronic heart failure (CHF), in particular the high rates of hospital admissions, dedicated CHF management programs (CHF-MP) have been developed. Over the past five years there has been a rapid growth of CHF-MPs in Australia. Given the apparent mismatch between the demand for, and availability of CHF-MPs, this paper has been designed to discuss the accessibility to and quality of current CHF-MPs in Australia. Methods The data presented in this report has been combined from the research of the co-authors, in particular a review of the inequities in access to chronic heart failure which utilised geographical information systems (GIS) and the survey of heterogeneity in quality and service provision in Australian. Results Of the 62 CHF-MPs surveyed in this study 93% (58) centres had been located areas that are rated as Highly Accessible. This result indicated that most of the CHF-MPs have been located in capital cities or large regional cities. Six percent (4 CHF-MPs) had been located in Accessible areas which were country towns or cities. No CHF-MPs had been established outside of cities to service the estimated 72,000 individuals with CHF living in rural and remote areas. 16% of programs recruited NYHA Class I patients and of these 20% lacked confirmation (echocardiogram) of their diagnosis. Conclusion Overall, these data highlight the urgent need to provide equitable access to CHF-MP's. When establishing CHF-MPs consideration of current evidence based models to ensure quality in practice.

The effect of housing characteristics and occupant activities on the respiratory health of women and children in Lao PDR

The paper presents the results of a study conducted into the relationship between dwelling characteristics and occupant activities with the respiratory health of resident women and children in Lao People’s Democratic Republic (PDR). Lao is one of the least developed countries in south-east Asia with poor life expectancies and mortality rates. The study, commissioned by the World Health Organisation, included questionnaires delivered to residents of 356 dwellings in nine districts in Lao PDR over a five month period (December 2005-April 2006), with the aim of identifying the association between respiratory health and indoor air pollution, in particular exposures related to indoor biomass burning. Adjusted odds ratios were calculated for each health outcome separately using binary logistic regression. After adjusting for age, a wide range of symptoms of respiratory illness in women and children aged 1-4 years were positively associated with a range of indoor exposures related to indoor cooking, including exposure to a fire and location of the cooking place. Among women, “dust always inside the house” and smoking were also identified as strong risk factors for respiratory illness. Other strong risk factors for children, after adjusting for age and gender, included dust and drying clothes inside. This analysis confirms the role of indoor air pollution in the burden of disease among women and children in Lao PDR.

Prognostic significance of IGF and ECM induced signalling proteins in breast cancer patients

Breast cancer is a leading contributor to the burden of disease in Australia. Fortunately, the recent introduction of diverse therapeutic strategies have improved the survival outcome for many women. Despite this, the clinical management of breast cancer remains problematic as not all approaches are sufficiently sophisticated to take into account the heterogeneity of this disease and are unable to predict disease progression, in particular, metastasis. As such, women with good prognostic outcomes are exposed to the side effects of therapies without added benefit. Furthermore, women with aggressive disease for whom these advanced treatments would deliver benefit cannot be distinguished and opportunities for more intensive or novel treatment are lost. This study is designed to identify novel factors associated with disease progression, and the potential to inform disease prognosis. Frequently overlooked, yet common mediators of disease are the interactions that take place between the insulin-like growth factor (IGF) system and the extracellular matrix (ECM). Our laboratory has previously demonstrated that multiprotein insulin-like growth factor-I (IGF-I): insulin-like growth factor binding protein (IGFBP): vitronectin (VN) complexes stimulate migration of breast cancer cells in vitro, via the cooperative involvement of the insulin-like growth factor type I receptor (IGF-IR) and VN-binding integrins. However, the effects of IGF and ECM protein interactions on the dissemination and progression of breast cancer in vivo are unknown. It was hypothesised that interactions between proteins required for IGF induced signalling events and those within the ECM contribute to breast cancer metastasis and are prognostic and predictive indicators of patient outcome. To address this hypothesis, semiquantitative immunohistochemistry (IHC) analyses were performed to compare the extracellular and subcellular distribution of IGF and ECM induced signalling proteins between matched normal, primary cancer, and metastatic cancer among archival formalin-fixed paraffin-embedded (FFPE) breast tissue samples collected from women attending the Princess Alexandra Hospital, Brisbane. Multivariate Cox proportional hazards (PH) regression survival models in conjunction with a modified „purposeful selection of covariates. method were applied to determine the prognostic potential of these proteins. This study provides the first in-depth, compartmentalised analysis of the distribution of IGF and ECM induced signalling proteins. As protein function and protein localisation are closely correlated, these findings provide novel insights into IGF signalling and ECM protein function during breast cancer development and progression. Distinct IGF signalling and ECM protein immunoreactivity was observed in the stroma and/or in subcellular locations in normal breast, primary cancer and metastatic cancer tissues. Analysis of the presence and location of stratifin (SFN) suggested a causal relationship in ECM remodelling events during breast cancer development and progression. The results of this study have also suggested that fibronectin (FN) and ¥â1 integrin are important for the formation of invadopodia and epithelial-to-mesenchymal transition (EMT) events. Our data also highlighted the importance of the temporal and spatial distribution of IGF induced signalling proteins in breast cancer metastasis; in particular, SFN, enhancer-of-split and hairy-related protein 2 (SHARP-2), total-akt/protein kinase B 1 (Total-AKT1), phosphorylated-akt/protein kinase B (P-AKT), extracellular signal-related kinase-1 and extracellular signal-related kinase-2 (ERK1/2) and phosphorylated-extracellular signal-related kinase-1 and extracellular signal-related kinase-2 (P-ERK1/2). Multivariate survival models were created from the immunohistochemical data. These models were found to fit well with these data with very high statistical confidence. Numerous prognostic confounding effects and effect modifications were identified among elements of the ECM and IGF signalling cascade and corroborate the survival models. This finding provides further evidence for the prognostic potential of IGF and ECM induced signalling proteins. In addition, the adjusted measures of associations obtained in this study have strengthened the validity and utility of the resulting models. The findings from this study provide insights into the biological interactions that occur during the development of breast tissue and contribute to disease progression. Importantly, these multivariate survival models could provide important prognostic and predictive indicators that assist the clinical management of breast disease, namely in the early identification of cancers with a propensity to metastasise, and/or recur following adjuvant therapy. The outcomes of this study further inform the development of new therapeutics to aid patient recovery. The findings from this study have widespread clinical application in the diagnosis of disease and prognosis of disease progression, and inform the most appropriate clinical management of individuals with breast cancer.