Nutrition screening and assessment in Parkinson's disease : a comparison of methods

Background & Aims Nutrition screening and assessment enable early identification of malnourished people and those at risk of malnutrition. Appropriate assessment tools assist with informing and monitoring nutrition interventions. Tool choice needs to be appropriate to the population and setting. Methods Community-dwelling people with Parkinson’s disease (>18 years) were recruited. Body mass index (BMI) was calculated from weight and height. Participants were classified as underweight according to World Health Organisation (WHO) (≤18.5kg/m2) and age specific (<65 years,≤18.5kg/m2; ≥65 years,≤23.5kg/m2) cut-offs. The Mini-Nutritional Assessment (MNA) screening (MNA-SF) and total assessment scores were calculated. The Patient-Generated Subjective Global Assessment (PG-SGA), including the Subjective Global Assessment (SGA), was performed. Sensitivity, specificity, positive predictive value, negative predictive value and weighted kappa statistic of each of the above compared to SGA were determined. Results Median age of the 125 participants was 70.0(35-92) years. Age-specific BMI (Sn 68.4%, Sp 84.0%) performed better than WHO (Sn 15.8%, Sp 99.1%) categories. MNA-SF performed better (Sn 94.7%, Sp 78.3%) than both BMI categorisations for screening purposes. MNA had higher specificity but lower sensitivity than PG-SGA (MNA Sn 84.2%, Sp 87.7%; PG-SGA Sn 100.0%, Sp 69.8%). Conclusions BMI lacks sensitivity to identify malnourished people with Parkinson’s disease and should be used with caution. The MNA-SF may be a better screening tool in people with Parkinson’s disease. The PG-SGA performed well and may assist with informing and monitoring nutrition interventions. Further research should be conducted to validate screening and assessment tools in Parkinson’s disease.  

Global sequence variation in the histidine-rich proteins 2 and 3 of Plasmodium falciparum: implications for the performance of malaria rapid diagnostic tests

Background Accurate diagnosis is essential for prompt and appropriate treatment of malaria. While rapid diagnostic tests (RDTs) offer great potential to improve malaria diagnosis, the sensitivity of RDTs has been reported to be highly variable. One possible factor contributing to variable test performance is the diversity of parasite antigens. This is of particular concern for Plasmodium falciparum histidine-rich protein 2 (PfHRP2)-detecting RDTs since PfHRP2 has been reported to be highly variable in isolates of the Asia-Pacific region. Methods The pfhrp2 exon 2 fragment from 458 isolates of P. falciparum collected from 38 countries was amplified and sequenced. For a subset of 80 isolates, the exon 2 fragment of histidine-rich protein 3 (pfhrp3) was also amplified and sequenced. DNA sequence and statistical analysis of the variation observed in these genes was conducted. The potential impact of the pfhrp2 variation on RDT detection rates was examined by analysing the relationship between sequence characteristics of this gene and the results of the WHO product testing of malaria RDTs: Round 1 (2008), for 34 PfHRP2-detecting RDTs. Results Sequence analysis revealed extensive variations in the number and arrangement of various repeats encoded by the genes in parasite populations world-wide. However, no statistically robust correlation between gene structure and RDT detection rate for P. falciparum parasites at 200 parasites per microlitre was identified. Conclusions The results suggest that despite extreme sequence variation, diversity of PfHRP2 does not appear to be a major cause of RDT sensitivity variation.

Understanding causal relationships between the built and social environment, health and associated behaviours and risk factors

Introduction: Built environment interventions designed to reduce non-communicable diseases and health inequity, complement urban planning agendas focused on creating more ‘liveable’, compact, pedestrian-friendly, less automobile dependent and more socially inclusive cities.However, what constitutes a ‘liveable’ community is not well defined. Moreover, there appears to be a gap between the concept and delivery of ‘liveable’ communities. The recently funded NHMRC Centre of Research Excellence (CRE) in Healthy Liveable Communities established in early 2014, has defined ‘liveability’ from a social determinants of health perspective. Using purpose-designed multilevel longitudinal data sets, it addresses five themes that address key evidence-base gaps for building healthy and liveable communities. The CRE in Healthy Liveable Communities seeks to generate and exchange new knowledge about: 1) measurement of policy-relevant built environment features associated with leading non-communicable disease risk factors (physical activity, obesity) and health outcomes (cardiovascular disease, diabetes) and mental health; 2) causal relationships and thresholds for built environment interventions using data from longitudinal studies and natural experiments; 3) thresholds for built environment interventions; 4) economic benefits of built environment interventions designed to influence health and wellbeing outcomes; and 5) factors, tools, and interventions that facilitate the translation of research into policy and practice. This evidence is critical to inform future policy and practice in health, land use, and transport planning. Moreover, to ensure policy-relevance and facilitate research translation, the CRE in Healthy Liveable Communities builds upon ongoing, and has established new, multi-sector collaborations with national and state policy-makers and practitioners. The symposium will commence with a brief introduction to embed the research within an Australian health and urban planning context, as well as providing an overall outline of the CRE in Healthy Liveable Communities, its structure and team. Next, an overview of the five research themes will be presented. Following these presentations, the Discussant will consider the implications of the research and opportunities for translation and knowledge exchange. Theme 2 will establish whether and to what extent the neighbourhood environment (built and social) is causally related to physical and mental health and associated behaviours and risk factors. In particular, research conducted as part of this theme will use data from large-scale, longitudinal-multilevel studies (HABITAT, RESIDE, AusDiab) to examine relationships that meet causality criteria via statistical methods such as longitudinal mixed-effect and fixed-effect models, multilevel and structural equation models; analyse data on residential preferences to investigate confounding due to neighbourhood self-selection and to use measurement and analysis tools such as propensity score matching and ‘within-person’ change modelling to address confounding; analyse data about individual-level factors that might confound, mediate or modify relationships between the neighbourhood environment and health and well-being (e.g., psychosocial factors, knowledge, perceptions, attitudes, functional status), and; analyse data on both objective neighbourhood characteristics and residents’ perceptions of these objective features to more accurately assess the relative contribution of objective and perceptual factors to outcomes such as health and well-being, physical activity, active transport, obesity, and sedentary behaviour. At the completion of the Theme 2, we will have demonstrated and applied statistical methods appropriate for determining causality and generated evidence about causal relationships between the neighbourhood environment, health, and related outcomes. This will provide planners and policy makers with a more robust (valid and reliable) basis on which to design healthy communities.

Error and variance bounds on sigmoidal neurons with weight and input errors

Bounds on the expectation and variance of errors at the output of a multilayer feedforward neural network with perturbed weights and inputs are derived. It is assumed that errors in weights and inputs to the network are statistically independent and small. The bounds obtained are applicable to both digital and analogue network implementations and are shown to be of practical value.

Diabetes mellitus and the risk of depressive and anxiety disorders in Australian women: A longitudinal study

Background Longitudinal studies examining the risk of depressive and anxiety disorders associated with diabetes are limited. This study examined the association between diabetes and the risk of depressive and anxiety disorders in Australian women using longitudinal data. Methods Datawere froma sample of women who were part of anAustralian pregnancy and birth cohort study. Data comprised self-reported diabetes mellitus and the subsequent reporting of depressive and anxiety disorders. Mood disorders were assessed according to the Diagnostic and Statistical Manual of Mental Disorders, fourth edition, obtained from participants using Composite International Diagnostic Interview (CIDI)-Auto (WHO WMH-CIDI CAPI, version 21.1.3). Multiple regression models with adjustment for important covariates were used. Results Women with diabetes had a higher lifetime prevalence of any depressive and/or anxiety disorder than women without diabetes. About 3 in 10 women with diabetes experienced a lifetime event of any depressive disorder, while 1 in 2 women with diabetes experienced a lifetime event of any anxiety disorder. In prospective analyses, diabetes was only significantly associated with a 30-day episode of any anxiety disorder (odds ratio [OR] 1.53, 95% confidence interval [CI] 1.09–2.15). In the case of lifetime disorders, diabetes was significantly associated with any depressive disorder (OR 1.37, 95% CI 1.03–1.84), major depressive disorder (OR 1.36, 95% CI 1.01–1.85), and posttraumatic stress disorder (OR 1.42, 95% CI 1.01–2.02). Conclusions The findings suggest that the presence of diabetes is a significant risk factor for women experiencing current anxiety disorders. However, in the case of depression, the association with diabetes only held for women who had experienced past episodes, there was no association with current depression. This suggests that the evidence is not strong enough to support a direct effect of diabetes as a cause of mood disorders.

Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.

The paradox of creative uncertainty in learning and teaching

In an ever-changing and globalised world there is a need for higher education to adapt and evolve its models of learning and teaching. The old industrial model has lost traction, and new patterns of creative engagement are required. These new models potentially increase relevancy and better equip students for the future. Although creativity is recognised as an attribute that can contribute much to the development of these pedagogies, and creativity is valued by universities as a graduate capability, some educators understandably struggle to translate this vision into practice. This paper reports on selected survey findings from a mixed methods research project which aimed to shed light on how creativity can be designed for in higher education learning and teaching settings. A social constructivist epistemology underpinned the research and data was gathered using survey and case study methods. Descriptive statistical methods and informed grounded theory were employed for the analysis reported here. The findings confirm that creativity is valued for its contribution to the development of students’ academic work, employment opportunities and life in general; however, tensions arise between individual educator’s creative pedagogical goals and the provision of institutional support for implementation of those objectives. Designing for creativity becomes, paradoxically, a matter of navigating and limiting complexity and uncertainty, while simultaneously designing for those same states or qualities.

Pedestrian Crashes in Ethiopia: Identification of contributing factors through modelling of exposure and road environment variables

Pedestrian safety is a critical issue in Ethiopia. Reports show that 50 to 60% of traffic fatality victims in the country are pedestrians. The primary aim of this research was to examine the possible causes of and contributing factors to crashes with pedestrians in Ethiopia, and improve pedestrian safety by recommending possible countermeasures. The secondary aim was to develop appropriate pedestrian crash models for two-way two-lane rural roads and roundabouts in the capital city of Ethiopia. This research uses quantitative methods throughout the process of the investigation. The research has applied various statistical methods. The results of this research support the idea that geometric and operational features have significant influence on pedestrian safety and crashes. Accordingly, policies and strategies are needed to safeguard pedestrians in Ethiopia.

Quantifying the state of populations and effects of disturbances at large spatio-temporal scales: The case of coral populations in the great barrier reef

This project was a step forward in applying statistical methods and models to provide new insights for more informed decision-making at large spatial scales. The model has been designed to address complicated effects of ecological processes that govern the state of populations and uncertainties inherent in large spatio-temporal datasets. Specifically, the thesis contributes to better understanding and management of the Great Barrier Reef.

Using Bourdieu in education research: Theory and methods

This workshop will snapshot Bourdieu's sociology. In recognition of Bourdieu's work as a powerful theoretical instrument to speculate the reproduction of social orders and cultural values, the workshop will firstly discuss the core concepts of habitus, capital, and field – the foundational triad of Bourdieu's sociology. Although Bourdieu's original work was built on some quantitative studies, his sociology has been largely qualitatively used in education research. Different from the bulk of extant research, the workshop will secondly showcase some quantitative and mixed methods research that uses a Bourdieusian framework. Mindful of such a framework helping understand social practice at a macro level, the workshop will then make an attempt to think through the macro and the micro by weaving together Bourdieu's sociology with Garfinkel's ethnomethodology. The workshop will conclude with some reflections and communications in terms of how to better realise the full value of Bourdieu in education research.

Bayesian designs with frequentist and Bayesian error rate considerations

So far, most Phase II trials have been designed and analysed under a frequentist framework. Under this framework, a trial is designed so that the overall Type I and Type II errors of the trial are controlled at some desired levels. Recently, a number of articles have advocated the use of Bavesian designs in practice. Under a Bayesian framework, a trial is designed so that the trial stops when the posterior probability of treatment is within certain prespecified thresholds. In this article, we argue that trials under a Bayesian framework can also be designed to control frequentist error rates. We introduce a Bayesian version of Simon's well-known two-stage design to achieve this goal. We also consider two other errors, which are called Bayesian errors in this article because of their similarities to posterior probabilities. We show that our method can also control these Bayesian-type errors. We compare our method with other recent Bayesian designs in a numerical study and discuss implications of different designs on error rates. An example of a clinical trial for patients with nasopharyngeal carcinoma is used to illustrate differences of the different designs.

Analysing commercial catch and effort data from a penaeid trawl fishery: A comparison of linear models, mixed models, and generalised estimating equations approaches

Statistical methods are often used to analyse commercial catch and effort data to provide standardised fishing effort and/or a relative index of fish abundance for input into stock assessment models. Achieving reliable results has proved difficult in Australia's Northern Prawn Fishery (NPF), due to a combination of such factors as the biological characteristics of the animals, some aspects of the fleet dynamics, and the changes in fishing technology. For this set of data, we compared four modelling approaches (linear models, mixed models, generalised estimating equations, and generalised linear models) with respect to the outcomes of the standardised fishing effort or the relative index of abundance. We also varied the number and form of vessel covariates in the models. Within a subset of data from this fishery, modelling correlation structures did not alter the conclusions from simpler statistical models. The random-effects models also yielded similar results. This is because the estimators are all consistent even if the correlation structure is mis-specified, and the data set is very large. However, the standard errors from different models differed, suggesting that different methods have different statistical efficiency. We suggest that there is value in modelling the variance function and the correlation structure, to make valid and efficient statistical inferences and gain insight into the data. We found that fishing power was separable from the indices of prawn abundance only when we offset the impact of vessel characteristics at assumed values from external sources. This may be due to the large degree of confounding within the data, and the extreme temporal changes in certain aspects of individual vessels, the fleet and the fleet dynamics.

A new data source for fisheries resource assessment: genetic estimates of the effective number of spawners. Final Report to the Fisheries Research and Development Corporation.

The development of innovative methods of stock assessment is a priority for State and Commonwealth fisheries agencies. It is driven by the need to facilitate sustainable exploitation of naturally occurring fisheries resources for the current and future economic, social and environmental well being of Australia. This project was initiated in this context and took advantage of considerable recent achievements in genomics that are shaping our comprehension of the DNA of humans and animals. The basic idea behind this project was that genetic estimates of effective population size, which can be made from empirical measurements of genetic drift, were equivalent to estimates of the successful number of spawners that is an important parameter in process of fisheries stock assessment. The broad objectives of this study were to 1. Critically evaluate a variety of mathematical methods of calculating effective spawner numbers (Ne) by a. conducting comprehensive computer simulations, and by b. analysis of empirical data collected from the Moreton Bay population of tiger prawns (P. esculentus). 2. Lay the groundwork for the application of the technology in the northern prawn fishery (NPF). 3. Produce software for the calculation of Ne, and to make it widely available. The project pulled together a range of mathematical models for estimating current effective population size from diverse sources. Some of them had been recently implemented with the latest statistical methods (eg. Bayesian framework Berthier, Beaumont et al. 2002), while others had lower profiles (eg. Pudovkin, Zaykin et al. 1996; Rousset and Raymond 1995). Computer code and later software with a user-friendly interface (NeEstimator) was produced to implement the methods. This was used as a basis for simulation experiments to evaluate the performance of the methods with an individual-based model of a prawn population. Following the guidelines suggested by computer simulations, the tiger prawn population in Moreton Bay (south-east Queensland) was sampled for genetic analysis with eight microsatellite loci in three successive spring spawning seasons in 2001, 2002 and 2003. As predicted by the simulations, the estimates had non-infinite upper confidence limits, which is a major achievement for the application of the method to a naturally-occurring, short generation, highly fecund invertebrate species. The genetic estimate of the number of successful spawners was around 1000 individuals in two consecutive years. This contrasts with about 500,000 prawns participating in spawning. It is not possible to distinguish successful from non-successful spawners so we suggest a high level of protection for the entire spawning population. We interpret the difference in numbers between successful and non-successful spawners as a large variation in the number of offspring per family that survive – a large number of families have no surviving offspring, while a few have a large number. We explored various ways in which Ne can be useful in fisheries management. It can be a surrogate for spawning population size, assuming the ratio between Ne and spawning population size has been previously calculated for that species. Alternatively, it can be a surrogate for recruitment, again assuming that the ratio between Ne and recruitment has been previously determined. The number of species that can be analysed in this way, however, is likely to be small because of species-specific life history requirements that need to be satisfied for accuracy. The most universal approach would be to integrate Ne with spawning stock-recruitment models, so that these models are more accurate when applied to fisheries populations. A pathway to achieve this was established in this project, which we predict will significantly improve fisheries sustainability in the future. Regardless of the success of integrating Ne into spawning stock-recruitment models, Ne could be used as a fisheries monitoring tool. Declines in spawning stock size or increases in natural or harvest mortality would be reflected by a decline in Ne. This would be good for data-poor fisheries and provides fishery independent information, however, we suggest a species-by-species approach. Some species may be too numerous or experiencing too much migration for the method to work. During the project two important theoretical studies of the simultaneous estimation of effective population size and migration were published (Vitalis and Couvet 2001b; Wang and Whitlock 2003). These methods, combined with collection of preliminary genetic data from the tiger prawn population in southern Gulf of Carpentaria population and a computer simulation study that evaluated the effect of differing reproductive strategies on genetic estimates, suggest that this technology could make an important contribution to the stock assessment process in the northern prawn fishery (NPF). Advances in the genomics world are rapid and already a cheaper, more reliable substitute for microsatellite loci in this technology is available. Digital data from single nucleotide polymorphisms (SNPs) are likely to super cede ‘analogue’ microsatellite data, making it cheaper and easier to apply the method to species with large population sizes.

Depression and its assessment among stroke patients and their caregivers

Approximately one-third of stroke patients experience depression. Stroke also has a profound effect on the lives of caregivers of stroke survivors. However, depression in this latter population has received little attention. In this study the objectives were to determine which factors are associated with and can be used to predict depression at different points in time after stroke; to compare different depression assessment methods among stroke patients; and to determine the prevalence, course and associated factors of depression among the caregivers of stroke patients. A total of 100 consecutive hospital-admitted patients no older than 70 years of age were followed for 18 months after having their first ischaemic stroke. Depression was assessed according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-III-R), Beck Depression Inventory (BDI), Hamilton Rating Scale (HRSD), Visual Analogue Mood Scale (VAMS), Clinical Global Impression (CGI) and caregiver ratings. Neurological assessments and a comprehensive neuropsychological test battery were performed. Depression in caregivers was assessed by BDI. Depressive symptoms had early onsets in most cases. Mild depressive symptoms were often persistent with little change during the 18-month follow-up, although there was an increase in major depression over the same time interval. Stroke severity was associated with depression especially from 6 to 12 months post-stroke. At the acute phase, older patients were at higher risk of depression, and a higher proportion of men were depressed at 18 months post-stroke. Of the various depression assessment methods, none stood clearly apart from the others. The feasibility of each did not differ greatly, but prevalence rates differed widely according to the different criteria. When compared against DSM-III-R criteria, sensitivity and specificity were acceptable for the CGI, BDI, and HRSD. The CGI and BDI had better sensitivity than the more specific HRSD. The VAMS seemed not to be a reliable method for assessing depression among stroke patients. The caregivers often rated patients depression as more severe than did the patients themselves. Moreover, their ratings seemed to be influenced by their own depression. Of the caregivers, 30-33% were depressed. At the acute phase, caregiver depression was associated with the severity of the stroke and the older age of the patient. The best predictor of caregiver depression at later follow-up was caregiver depression at the acute phase. The results suggest that depression should be assessed during the early post-stroke period and that the follow-up of those at risk of poor emotional outcome should be extended beyond the first year post-stroke. Further, the assessment of well-being of the caregivers of stroke patients should be included as a part of a rehabilitation plan for stroke patients.