Intake of isoflavone and lignan phytoestrogens and associated demographic and lifestyle factors in older Australian women

The purpose was to determine intake of phytoestrogens in a sample of older Australian women, and to investigate associated lifestyle factors. Subjects were an age-stratified sample of 511 women aged 40-80 y, randomly selected from the electoral roll and participating in the Longitudinal Assessment of Ageing in Women at the Royal Brisbane and Women’s Hospital. A cross-sectional study was conducted to assess isoflavone and lignan intake over the past month from food and supplements using a 112-item phytoestrogen frequency questionnaire. Data were also collected on nutrient intakes, physical activity, smoking, alcohol, non-prescription supplements, hormone therapy, education and occupation. Logistic regression was used to evaluate associations between demographic and lifestyle variables and soy/linseed consumption while controlling for age. Isoflavone intakes were significantly higher in the younger compared to older age groups (p<0.001); there were no age-related differences in lignan intake. Forty-five percent of women consumed at least one serve of a soy and/or linseed item and were defined as a soy/linseed consumer. Median (range) intakes by consumers for isoflavones and lignans (3.9 (0-172) mg/d and 2.4 (0.1-33) mg/d) were higher than intakes by non-consumers (0.004 (0-2.6) mg/d and 1.57 (0.44-4.7) mg/d), respectively (p<0.001). Consumers had higher intakes of dietary fibre (p=0.003), energy (p=0.04) and polyunsaturated fat (p=0.004), and higher levels of physical activity (p=0.006), socio-economic position (p<0.001), education (p<0.001) and supplement use (p<0.001). Women who consumed soy or linseed foods differed in lifestyle and demographic characteristics suggesting these factors should be considered when investigating associations with chronic disease outcomes.

Diffusion of business improvement processes in manufacturing companies in India

Manufacturing organisations spend more on Business Process Improvement initiatives to make them more competitive in growing global market. This paper presents a Rapid Improvement Workshop (RIW) framework which companies can used to identify the critical factors regulating the diffusion of business process improvement in their company. The framework can then be used address how process improvement can be efficiently implemented. We use the results from case studies at Caterpillar India. The paper identifies the critical factors that contribute to the successful implementation of process improvement programs in manufacturing organisations. We further identify certain technological and cultural barriers to the implementation of process improvement programs and how Indian manufacturing companies can overcome these barriers to attain competitive advantage in the global markets.

Hierarchical Bayesian models for estimating the extent of plant pest invasions

Plant biosecurity requires statistical tools to interpret field surveillance data in order to manage pest incursions that threaten crop production and trade. Ultimately, management decisions need to be based on the probability that an area is infested or free of a pest. Current informal approaches to delimiting pest extent rely upon expert ecological interpretation of presence / absence data over space and time. Hierarchical Bayesian models provide a cohesive statistical framework that can formally integrate the available information on both pest ecology and data. The overarching method involves constructing an observation model for the surveillance data, conditional on the hidden extent of the pest and uncertain detection sensitivity. The extent of the pest is then modelled as a dynamic invasion process that includes uncertainty in ecological parameters. Modelling approaches to assimilate this information are explored through case studies on spiralling whitefly, Aleurodicus dispersus and red banded mango caterpillar, Deanolis sublimbalis. Markov chain Monte Carlo simulation is used to estimate the probable extent of pests, given the observation and process model conditioned by surveillance data. Statistical methods, based on time-to-event models, are developed to apply hierarchical Bayesian models to early detection programs and to demonstrate area freedom from pests. The value of early detection surveillance programs is demonstrated through an application to interpret surveillance data for exotic plant pests with uncertain spread rates. The model suggests that typical early detection programs provide a moderate reduction in the probability of an area being infested but a dramatic reduction in the expected area of incursions at a given time. Estimates of spiralling whitefly extent are examined at local, district and state-wide scales. The local model estimates the rate of natural spread and the influence of host architecture, host suitability and inspector efficiency. These parameter estimates can support the development of robust surveillance programs. Hierarchical Bayesian models for the human-mediated spread of spiralling whitefly are developed for the colonisation of discrete cells connected by a modified gravity model. By estimating dispersal parameters, the model can be used to predict the extent of the pest over time. An extended model predicts the climate restricted distribution of the pest in Queensland. These novel human-mediated movement models are well suited to demonstrating area freedom at coarse spatio-temporal scales. At finer scales, and in the presence of ecological complexity, exploratory models are developed to investigate the capacity for surveillance information to estimate the extent of red banded mango caterpillar. It is apparent that excessive uncertainty about observation and ecological parameters can impose limits on inference at the scales required for effective management of response programs. The thesis contributes novel statistical approaches to estimating the extent of pests and develops applications to assist decision-making across a range of plant biosecurity surveillance activities. Hierarchical Bayesian modelling is demonstrated as both a useful analytical tool for estimating pest extent and a natural investigative paradigm for developing and focussing biosecurity programs.

A physico-chemical characterisation of particulate emissions from a compression ignition engine : the influence of biodiesel feedstock

This study undertook a physico-chemical characterisation of particle emissions from a single compression ignition engine operated at one test mode with 3 biodiesel fuels made from 3 different feedstocks (i.e. soy, tallow and canola) at 4 different blend percentages (20%, 40%, 60% and 80%) to gain insights into their particle-related health effects. Particle physical properties were inferred by measuring particle number size distributions both with and without heating within a thermodenuder (TD) and also by measuring particulate matter (PM) emission factors with an aerodynamic diameter less than 10 μm (PM10). The chemical properties of particulates were investigated by measuring particle and vapour phase Polycyclic Aromatic Hydrocarbons (PAHs) and also Reactive Oxygen Species (ROS) concentrations. The particle number size distributions showed strong dependency on feedstock and blend percentage with some fuel types showing increased particle number emissions, whilst others showed particle number reductions. In addition, the median particle diameter decreased as the blend percentage was increased. Particle and vapour phase PAHs were generally reduced with biodiesel, with the results being relatively independent of the blend percentage. The ROS concentrations increased monotonically with biodiesel blend percentage, but did not exhibit strong feedstock variability. Furthermore, the ROS concentrations correlated quite well with the organic volume percentage of particles – a quantity which increased with increasing blend percentage. At higher blend percentages, the particle surface area was significantly reduced, but the particles were internally mixed with a greater organic volume percentage (containing ROS) which has implications for using surface area as a regulatory metric for diesel particulate matter (DPM) emissions.

Application of multi-criteria decision making methods to compression ignition engine efficiency and gaseous, particulate and greenhouse gas emissions

Compression ignition (CI) engine design is subject to many constraints which presents a multi-criteria optimisation problem that the engine researcher must solve. In particular, the modern CI engine must not only be efficient, but must also deliver low gaseous, particulate and life cycle greenhouse gas emissions so that its impact on urban air quality, human health, and global warming are minimised. Consequently, this study undertakes a multi-criteria analysis which seeks to identify alternative fuels, injection technologies and combustion strategies that could potentially satisfy these CI engine design constraints. Three datasets are analysed with the Preference Ranking Organization Method for Enrichment Evaluations and Geometrical Analysis for Interactive Aid (PROMETHEE-GAIA) algorithm to explore the impact of 1): an ethanol fumigation system, 2): alternative fuels (20 % biodiesel and synthetic diesel) and alternative injection technologies (mechanical direct injection and common rail injection), and 3): various biodiesel fuels made from 3 feedstocks (i.e. soy, tallow, and canola) tested at several blend percentages (20-100 %) on the resulting emissions and efficiency profile of the various test engines. The results show that moderate ethanol substitutions (~20 % by energy) at moderate load, high percentage soy blends (60-100 %), and alternative fuels (biodiesel and synthetic diesel) provide an efficiency and emissions profile that yields the most “preferred” solutions to this multi-criteria engine design problem. Further research is, however, required to reduce Reactive Oxygen Species (ROS) emissions with alternative fuels, and to deliver technologies that do not significantly reduce the median diameter of particle emissions.

Host location behaviour in the desert caterpillar, Heliothis punctifera

The host location behaviour of foraging caterpillars has received little attention, despite the wealth of theoretical and empirical studies that have been directed at this behavioural trait in adult Lepidoptera. Here, we study caterpillars of the moth Heliothis punctifera Walker (Lepidoptera: Noctuidae), which inhabits the arid inland desert areas of Australia. Caterpillars of this species consume many flowerheads before completing development and can be observed moving across the sand in search of new hosts. Consequently, if host location behaviour favours attraction to certain plant species, it might be expected to influence the distribution and abundance of caterpillars in the field. We present field data showing that H. punctifera caterpillars are unevenly distributed throughout mixed patches of two of its host species, with a higher abundance on Senecio gregorii F. Muell., the annual yellow top, compared to Myriocephalus stuartii (F. Muell. & Sond.) Benth., the poached egg daisy (both Asteraceae). Using laboratory studies, we test whether this distribution may, in part, be due to host location behaviour of caterpillars. Our results show that caterpillars exhibit a preference for locating S. gregorii in their pre- and post-contact foraging behaviour. In addition, our results provide evidence that feeding history plays a role in host location behaviour in this insect. We propose that key features of the desert environment and the ecology of H. punctifera would favour adaptations to host location behaviour by immatures.

Dietary and exercise interventions to improve quality of life, metabolic risk factors and androgen deficiency symptoms in men with prostate cancer undergoing androgen deprivation therapy

Introduction Lifestyle interventions might be useful in the management of adverse effects of androgen deprivation therapy (ADT) in men with prostate cancer. Objectives To examine the effects of dietary and exercise interventions on quality of life (QoL), metabolic risk factors and androgen deficiency symptoms in men with prostate cancer undergoing ADT. Methods CINAHL, Cochrane library, Medline and PsychINFO were searched to identify randomised controlled trials published from January, 2004 to October, 2014. Data extraction and methodological quality assessment was independently conducted by two reviewers. Meta-analysis was conducted using RevMan® 5.3.5. Results Of 2183 articles retrieved, 11 studies met the inclusion criteria and had low risk of bias.Nine studies evaluated exercise (resistance and/or aerobic and/or counselling) and three evaluated dietary supplementation. Median sample size =79 (33–121) and median intervention duration was 12 weeks (12–24). Exercise improved QoL measures (SMD 0.26, 95%CI −0.01 to 0.53) but not body composition, metabolic risk or vasomotor symptoms. Qualitative analysis indicated soy (or isoflavone) supplementation did not improve vasomotor symptoms; however, may improve QoL. Conclusions Few studies have evaluated the efficacy of lifestyle interventions in the management of adverse effects of ADT. We found inconclusive results for exercise in improving QoL and negative results for other outcomes. For soy-based products, we found negative results for modifying vasomotor symptoms and inconclusive results for improving QoL. Future work should investigate the best mode of exercise for improving QoL and other interventions such as dietary counselling should be investigated for their potential to modify these outcomes.

Exercise improves quality of life in ADT-treated prostate cancer: Systematic review of RCTs

Men receiving androgen deprivation therapy (ADT) for prostate cancer (PCa) are likely to develop metabolic conditions such as diabetes, cardiovascular disease, abdominal obesity and osteoporosis. Other treatment-related side effects adversely influence quality of life (QoL) including vasomotor distress, depression, anxiety, mood swings, poor sleep quality and compromised sexual function. The objective of this study was to systematically review the nature and effects of dietary and exercise interventions on QoL, androgen deprivation symptoms and metabolic risk factors in men with PCa undergoing ADT. An electronic search of CINAHL, CENTRAL, Medline, PsychINFO and reference lists was performed to identify peer-reviewed articles published between January 2004 and December, 2014 in English. Eligible study designs included randomised controlled trials with pre- and post-intervention data. Data extraction and assessment of methodological quality with the Cochrane approach was conducted by two independent reviewers. Seven exercise studies were identified. Exercise significantly improved QoL, but showed no effect on metabolic risk factors (weight, waist circumference, lean or fat mass, blood pressure, lipid profile). Two dietary studies were identified, both of which tested soy supplements. Soy supplementation did not improve any outcomes. No dietary counselling studies were identified. No studies evaluated androgen-deficiency symptoms (libido, erectile function, sleep quality, mood swings, depression, anxiety, bone mineral density). Evidence from RCTs indicates that exercise enhances health- and disease-specific QoL in men with PCa undergoing ADT. Further studies are required to evaluate the effect of exercise and dietary interventions on QoL, androgen deprivation symptoms and metabolic risk factors in this cohort.