Making difference count: a demographic study of overseas born teachers

This article reports on the findings of a demographic study which is part of an Australian Research Council funded case study. It seeks to better understand the experiences and challenges facing teachers who are overseas born and educated non-native speakers of English. The investigation has been carried out in Victorian government metropolitan, regional city and rural secondary schools. A statewide survey has provided data about this previously `invisible' population of teachers, their demographic location, their qualifications, backgrounds and the nature of their teaching experiences. The findings raise a number of concerns in relation to overseas born teachers of ethnic difference in rural schools where cultural and professional isolation may be of particular concern. We explore some of the implications for teacher education in the light of increasing numbers of overseas born students entering teacher education courses.

Understanding environmental influences on nutrition and physical activity behaviors: where should we look and what should we count?

Research interest in the influence of environmental factors on nutrition and physical activity behaviors has surged internationally in recent years. This is evident from a rapidly expanding literature and facilitated by advances in methodological and analytical approaches to assessing multiple levels of influence on health behaviors. However, a number of conceptual challenges complicate research endeavours in this field. The purpose of this paper is to provide a 'state of the science' overview of evidence regarding environmental influences on nutrition and physical activity behaviors. We focus particularly on a number of key conceptual and methodological issues, including: a consideration of how the environment is defined; the selection and operationalization of environmental exposures; and the importance of integrating existing understanding of individual influences on behavior with the emerging data on the role of the environment. We draw on examples from the published literature including our own research studies to illustrate these issues. We conclude by proposing a research agenda to progress understanding of the influences of the environment on population nutrition and physical activity behaviors.

A nonparametric Bayesian Poisson Gamma model for count data

We propose a nonparametric Bayesian, linear Poisson gamma model for count data and use it for dictionary learning. A key property of this model is that it captures the parts-based representation similar to nonnegative matrix factorization. We present an auxiliary variable Gibbs sampler, which turns the intractable inference into a tractable one. Combining this inference procedure with the slice sampler of Indian buffet process, we show that our model can learn the number of factors automatically. Using synthetic and real-world datasets, we show that the proposed model outperforms other state-of-the-art nonparametric factor models.

Disease mapping and regression with count data in the presence of overdispersion and spatial autocorrelation: a Bayesian model averaging approach

This paper applies the generalised linear model for modelling geographical variation to esophageal cancer incidence data in the Caspian region of Iran. The data have a complex and hierarchical structure that makes them suitable for hierarchical analysis using Bayesian techniques, but with care required to deal with problems arising from counts of events observed in small geographical areas when overdispersion and residual spatial autocorrelation are present. These considerations lead to nine regression models derived from using three probability distributions for count data: Poisson, generalised Poisson and negative binomial, and three different autocorrelation structures. We employ the framework of Bayesian variable selection and a Gibbs sampling based technique to identify significant cancer risk factors. The framework deals with situations where the number of possible models based on different combinations of candidate explanatory variables is large enough such that calculation of posterior probabilities for all models is difficult or infeasible. The evidence from applying the modelling methodology suggests that modelling strategies based on the use of generalised Poisson and negative binomial with spatial autocorrelation work well and provide a robust basis for inference.

Daily step-count and change in waist circumference during a workplace pedometer program

Background: The health benefit associated with a daily step-count target within pedometer pro- grams is unclear. The aim of this study was to determine if the daily step-count attained during a four month pedometer-based workplace health program was associated with change in waist circumference (WC).

Methods: 762 Australian adults enrolled in a workplace pedometer pro- gram were recruited from ten workplaces in 2008. At the end of the program (four months), 436 participants were eligible for the current analysis. Data included demographics, perceived physical activity change during the program, measured WC at baseline and follow-up, and reported daily pedometer step-counts throughout the program. The association between daily step count and change in WC was examined using linear re- gression.

Results: WC improved by an average of –1.61cm (95% CI: –2.13, –1.09) by the end of the program. There was no relationship between daily step-count and the degree of change in WC. However, among participants reporting an in- crease in physical activity during the program a relationship between daily step count and change in WC was observed, such that those who un-dertook on average 10,000 steps or more per day improved their WC by –1.38cm (95%CI: –2.14, –0.63) more than those who did not achieve an average of 10,000 steps per day. Similarly, among individuals not meeting WC guidelines at baseline a greater daily step count was associ-ated with a greater decrease in WC.

Conclusions: Within a workplace pedometer program, reported daily step count was not associated with greater reductions in WC. However, it was a useful in-dicator of potential health benefits in those who increased their level of physical activity during the program. Pedometer programs need to com- municate clearly the importance of both a step goal and improvement in step count to manage participant expectations about improvements in health markers.