Predictive models for water sources with high susceptibility for bromine-containing disinfection by-product formation: Implications for water treatment

This study examines a matrix of synthetic water samples designed to include conditions that favour brominated disinfection by-product (Br-DBP) formation, in order to provide predictive models suitable for high Br-DBP forming waters such as salinity-impacted waters. Br-DBPs are known to be more toxic than their chlorinated analogues, in general, and their formation may be favoured by routine water treatment practices such as coagulation/flocculation under specific conditions; therefore, circumstances surrounding their formation must be understood. The chosen factors were bromide concentration, mineral alkalinity, bromide to dissolved organic carbon (Br/DOC) ratio and Suwannee River natural organic matter concentration. The relationships between these parameters and DBP formation were evaluated by response surface modelling of data generated using a face-centred central composite experimental design. Predictive models for ten brominated and/or chlorinated DBPs are presented, as well as models for total trihalomethanes (tTHMs) and total dihaloacetonitriles (tDHANs), and bromide substitution factors for the THMs and DHANs classes. The relationships described revealed that increasing alkalinity and increasing Br/DOC ratio were associated with increasing bromination of THMs and DHANs, suggesting that DOC lowering treatment methods that do not also remove bromide such as enhanced coagulation may create optimal conditions for Br-DBP formation in waters in which bromide is present.

Missing in space: An evaluation of imputation methods for missing data in spatial analysis of risk factors for type II diabetes

Background Spatial analysis is increasingly important for identifying modifiable geographic risk factors for disease. However, spatial health data from surveys are often incomplete, ranging from missing data for only a few variables, to missing data for many variables. For spatial analyses of health outcomes, selection of an appropriate imputation method is critical in order to produce the most accurate inferences. Methods We present a cross-validation approach to select between three imputation methods for health survey data with correlated lifestyle covariates, using as a case study, type II diabetes mellitus (DM II) risk across 71 Queensland Local Government Areas (LGAs). We compare the accuracy of mean imputation to imputation using multivariate normal and conditional autoregressive prior distributions. Results Choice of imputation method depends upon the application and is not necessarily the most complex method. Mean imputation was selected as the most accurate method in this application. Conclusions Selecting an appropriate imputation method for health survey data, after accounting for spatial correlation and correlation between covariates, allows more complete analysis of geographic risk factors for disease with more confidence in the results to inform public policy decision-making.

Factors influencing first-time mothers’ introduction of complementary foods: A qualitative exploration

Background Optimal infant nutrition comprises exclusive breastfeeding, with complementary foods introduced from six months of age. How parents make decisions regarding this is poorly studied. This study begins to address the dearth of research into the decision-making processes used by first-time mothers relating to the introduction of complementary foods. Methods This qualitative explorative study was conducted using interviews (13) and focus groups (3). A semi-structured interview guide based on the Theory of Planned Behaviour (TPB). The TPB, a well-validated decision-making model, identifies the key determinants of a behaviour through behavioural beliefs, subjective norms, and perceived behavioural control over the behaviour. It is purported that these beliefs predict behavioural intention to perform the behaviour, and performing the behaviour. A purposive, convenience, sample of 21 metropolitan parents recruited through advertising at local playgroups and childcare centres, and electronically through the University community email list self-selected to participate. Data were analysed thematically within the theoretical constructs: behavioural beliefs, subjective norms and perceived behavioural control. Data relating to sources of information about the introduction of complementary foods were also collected. Results Overall, first-time mothers found that waiting until six months was challenging despite knowledge of the WHO recommendations and an initial desire to comply with this guideline. Beliefs that complementary foods would assist the infants' weight gain, sleeping patterns and enjoyment at meal times were identified. Barriers preventing parents complying with the recommendations included subjective and group norms, peer influences, infant cues indicating early readiness and food labelling inconsistencies. The most valued information source was from peers who had recently introduced complementary foods. Conclusions First-time mothers in this study did not demonstrate a good understanding of the rationale behind the WHO recommendations, nor did they understand fully the signs of readiness of infants to commence solid foods. Factors that assisted waiting until six months were a trusting relationship with a health professional whose practice and advice was consistent with the recommendations and/or when their infant was developmentally ready for complementary foods at six months and accepted them with ease and enthusiasm. Barriers preventing parents complying with the recommendations included subjective and group norms, peer influences, infant cues indicating early readiness and food labelling inconsistencies.

The correlation between reading and mathematics ability at age twelve has a substantial genetic component

Dissecting how genetic and environmental influences impact on learning is helpful for maximizing numeracy and literacy. Here we show, using twin and genome-wide analysis, that there is a substantial genetic component to children’s ability in reading and mathematics, and estimate that around one half of the observed correlation in these traits is due to shared genetic effects (so-called Generalist Genes). Thus, our results highlight the potential role of the learning environment in contributing to differences in a child’s cognitive abilities at age twelve.

Specific rolling circle amplification of low-copy human polyomaviruses BKV, HPyV6, HPyV7, TSPyV, and STLPyV

Eleven new human polyomaviruses have been recently discovered, yet for most of these viruses, little is known of their biology and clinical impact. Rolling circle amplification (RCA) is an ideal method for the amplification of the circular polyomavirus genome due to its high fidelity amplification of circular DNA. In this study, a modified RCA method was developed to selectively amplify a range of polyomavirus genomes. Initial evaluation showed a multiplexed temperature-graded reaction profile gave the best yield and sensitivity in amplifying BK polyomavirus in a background of human DNA, with up to 1 × 10(8)-fold increases in viral genomes from as little as 10 genome copies per reaction. Furthermore, the method proved to be more sensitive and provided a 200-fold greater yield than that of random hexamers based standard RCA. Application of the method to other novel human polyomaviruses showed successful amplification of TSPyV, HPyV6, HPyV7, and STLPyV from low-viral load positive clinical samples, with viral genome enrichment ranging from 1 × 10(8) up to 1 × 10(10). This directed RCA method can be applied to selectively amplify other low-copy polyomaviral genomes from a background of competing non-specific DNA, and is a useful tool in further research into the rapidly expanding Polyomaviridae family.

Chemotherapy-induced nausea and vomiting: A narrative review to inform dietetics practice

Chemotherapy-induced nausea and vomiting (CINV) are common nutrition-impact symptoms experienced by cancer patients. They exert a detrimental effect on dietary intake, risk of malnutrition and quality of life. While CINV are primarily managed with medication, dietitians play an important role in the management of CINV-related complications such as reduced dietary intake. This review discusses the burden of nausea and vomiting which cancer patients can experience, including its effect on quality of life, nutrition status, and treatment outcomes. Implications for dietetic practice include the need to explore the nature of reported symptoms, identify predisposing risk factors, and to consider the use of a variety of interventions that are individualised to the patient’s symptoms. There are little clinical data regarding effective dietetic interventions for nausea and vomiting. In summary, this review discusses dietetic-related issues surrounding CINV including the pathophysiology, risk factors, prevalence, and both pharmacological and dietetic treatment options.

Disease mapping using Bayesian hierarchical models

description and analysis of geographically indexed health data with respect to demographic, environmental, behavioural, socioeconomic, genetic, and infectious risk factors (Elliott andWartenberg 2004). Disease maps can be useful for estimating relative risk; ecological analyses, incorporating area and/or individual-level covariates; or cluster analyses (Lawson 2009). As aggregated data are often more readily available, one common method of mapping disease is to aggregate the counts of disease at some geographical areal level, and present them as choropleth maps (Devesa et al. 1999; Population Health Division 2006). Therefore, this chapter will focus exclusively on methods appropriate for areal data...

Predicting health programme participation: A gravity‐based, hierarchical modelling approach

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.

Overfitting Bayesian mixture models with an unknown number of components

This paper proposes solutions to three issues pertaining to the estimation of finite mixture models with an unknown number of components: the non-identifiability induced by overfitting the number of components, the mixing limitations of standard Markov Chain Monte Carlo (MCMC) sampling techniques, and the related label switching problem. An overfitting approach is used to estimate the number of components in a finite mixture model via a Zmix algorithm. Zmix provides a bridge between multidimensional samplers and test based estimation methods, whereby priors are chosen to encourage extra groups to have weights approaching zero. MCMC sampling is made possible by the implementation of prior parallel tempering, an extension of parallel tempering. Zmix can accurately estimate the number of components, posterior parameter estimates and allocation probabilities given a sufficiently large sample size. The results will reflect uncertainty in the final model and will report the range of possible candidate models and their respective estimated probabilities from a single run. Label switching is resolved with a computationally light-weight method, Zswitch, developed for overfitted mixtures by exploiting the intuitiveness of allocation-based relabelling algorithms and the precision of label-invariant loss functions. Four simulation studies are included to illustrate Zmix and Zswitch, as well as three case studies from the literature. All methods are available as part of the R package Zmix, which can currently be applied to univariate Gaussian mixture models.

Neighborhood diversity, economic health and the role of the arts

Policymakers pursue a range of strategies aimed at diversifying neighborhoods despite research indicating the complicated and potentially damaging results of these efforts. One increasingly common approach is to incorporate the arts into planning efforts in the hope of enhancing diversity and catalyzing positive neighborhood change. Using data from the Cultural Data Project, we determine where newly established New York City art organizations locate in terms of neighborhood racial, income and industry diversity. We then analyze how diverse contexts interact with an arts presence to impact neighborhood economic health over time. We find that neighborhoods with high levels of racial diversity and low levels of income and industry diversity benefit most from an arts presence. However, the arts are attracted predominately to neighborhoods with moderate levels of racial diversity and high levels of income and industry diversity. This complicates the use of the arts as a tool in urban revitalization policy.

Patterns of care: Primary research in mental health nursing

The foundation of mental health nursing has historically been grounded in an interpersonal, person-centred process of health care, yet recent evidence suggests that the interactional work of mental health nursing is being eroded. Literature emphasises the importance of person-centred care on consumer outcomes, a model reliant upon the intimate engagement of nurses and consumers. Yet, the arrival of medical interventions in psychiatry has diverted nursing work from the therapeutic nursing role to task-based roles delegated by medicine, distancing nurses from consumers. This study used work sampling methodology to observe the proportion of time nurses working in an inpatient mental health setting engage in specific activities. The observations of this study determined that nurses' time is accounted for 31.65% in direct care, 51.63% in indirect care and 16.71% in service related activities.

A journey access tool to facilitate better health outcomes for people with disabilities

- Background One of the three objectives of the WHO Global Disability Action Plan 2014–2021 is removal of barriers and improved access to health services and programmes. Access to transport contributes to positive health outcomes; however, people with disabilities leaving their dwellings are confronted with barriers to their mobility. Mobility restrictions, sensory or other disabilities increase their vulnerability as road users, exposing them to higher risks of injury. PHSW and CARRS-Q have been collaborating with Handicap International Cambodia (HIC) on a Journey Access Tool (JAT). - Aims Use of the JAT is to (1) Identify transport and journey safety and barriers for people with disability and (2) Evaluation and modification of the tool after trailing to for use by NGOs and government agencies in prioritising actions around barriers. - Methodology The tool has undergone initial proof-of-concept testing in India and Viet Nam, and was trialled in Cambodia in February and May, 2015. Five teams were formed comprising a person with disability (physical, sensory or intellectual), researchers from QUT, staff from HIC, and local university students. The JAT was completed by each team and then discussed and evaluated. Two further Cambodian trials are scheduled for 2015. - Results The JAT is responsive to rural and urban contexts, and has utility for people with different disabilities. Two tools have been developed: a short version for people with a disability to complete independently, or with assistance; and a version for NGOs, DPOs and government. The tool has efficacy for advocacy.   - Conclusion The JAT has potential to assist the Mekong region with: (1) evaluating access for people with disability and other vulnerable members of the community including older people; (2) developing plans for changes to the routes in consultation with local authorities; (3) evaluating the effectiveness of implemented changes in terms of access and health; (4) inputting into policy; (5) The tool can be used for advocacy for change.

Sampling Methods for Exploring Between Subject Variability in Cardiac Electrophysiology Experiments

Between-subject and within-subject variability is ubiquitous in biology and physiology and understanding and dealing with this is one of the biggest challenges in medicine. At the same time it is difficult to investigate this variability by experiments alone. A recent modelling and simulation approach, known as population of models (POM), allows this exploration to take place by building a mathematical model consisting of multiple parameter sets calibrated against experimental data. However, finding such sets within a high-dimensional parameter space of complex electrophysiological models is computationally challenging. By placing the POM approach within a statistical framework, we develop a novel and efficient algorithm based on sequential Monte Carlo (SMC). We compare the SMC approach with Latin hypercube sampling (LHS), a method commonly adopted in the literature for obtaining the POM, in terms of efficiency and output variability in the presence of a drug block through an in-depth investigation via the Beeler-Reuter cardiac electrophysiological model. We show improved efficiency via SMC and that it produces similar responses to LHS when making out-of-sample predictions in the presence of a simulated drug block.

Vulnerability criminalised: Transgender people in prisons

Purpose of this paper: International research identifies transgender people as a vulnerable group in prison systems, with basic needs often being denied. This paper outlines Australian contexts of incarceration, and links between institutional responses and the vulnerabilisation of transgender prisoners. Design/methodology/approach: The paper critically analyses Australian prison policies regarding the treatment of transgender prisoners. Findings: The policy analysis illustrates the links between institutional practices and the increased vulnerability of transgender prisoners. The paper argues that policies further criminalise, and potentially doubly punish, transgender prisoners. Research limitations/implications: This paper analyses the publicly available policies on regulating transgender people’s imprisonment. Given the limited Australian research into transgender prisoner’s lived experiences, there is a gap in relation to policies, their perception, and how corrective services personnel enact the limited procedures available to them in managing transgender prisoners. Practical Implications: Current policies and practices significantly enhance the vulnerability of transgender prisoners. This policy analysis highlights the critical importance of policy and practice reform in relation to housing, safety, health and welfare services, and misgendering. What is the original/value of paper: The policy analysis provides practitioners with an outline of critical issues that arise when transgender people are imprisoned and suggests key areas for future research.