Background: There is a high prevalence of orofacial trauma in rugby union players. Mouthguards reduce complications following dental injuries, should dental injuries occur. The aim of this study was to investigate the prevalence of oral trauma and the significance of mouthguard use in adult amateur rugby union players in New South Wales, Australia. Methods: Questionnaires were distributed to players in rugby union clubs. It questioned players about their mouthguard use and orofacial trauma experience; the type of injury, complications, if a mouthguard was worn, where treatment was sought and outcome. Results: The prevalence of orofacial trauma in rugby union players is 64.9%. The most common injury was laceration to intraoral and extraoral soft tissues at 44.5%. Of all orofacial injuries reported, 41.9% were to the dentition. Following dental injury, loss of the tooth was the most common complication (34.7%). 76.9% of players wore mouthguards. By wearing a mouthguard, the risk reduction for ongoing complications following dental injuries was 18.5% (p-value = 0.009). Of these, 10.4% (p-value = 0.45) represented loss of the tooth. Conclusions: Rates of orofacial trauma and complications in amateur rugby union players are high in Australia. Use of mouthguards results in significant risk reduction for complications following dental injuries, including loss of tooth.

Both hGH and its C-terminal fragment reduce body weight gain, increase fat oxidation, and stimulate lipolysis in obese mice, yet AOD9604 does not interact with the hGH receptor. Thus, the concept of hGH behaving as a pro-hormone is further confirmed. This data shows that fragments of hGH can act in a manner novel to traditional hGH-stimulated pathways.

Dynamic simulation modelling is increasingly being recognised as a valuable decision-support tool to help guide investments and actions to address complex public health issues such as suicide. In particular, participatory system dynamics (SD) modelling provides a useful tool for asking high-level 'what if' questions, and testing the likely impacts of different combinations of policies and interventions at an aggregate level before they are implemented in the real world.We developed an SD model for suicide prevention in Australia, and investigated the hypothesised impacts over the next 10 years (2015)(2016)(2017)(2018)(2019)(2020)(2021)(2022)(2023)(2024)(2025) of a combination of current intervention strategies proposed for population interventions in Australia: 1) general practitioner (GP) training, 2) coordinated aftercare in those who have attempted suicide, 3) school-based mental health literacy programs, 4) brief-contact interventions in hospital settings, and 5) psychosocial treatment approaches.Findings suggest that the largest reductions in suicide were associated with GP training (6%) and coordinated aftercare approaches (4%), with total reductions of 12% for all interventions combined. This paper highlights the value of dynamic modelling methods for managing complexity and uncertainty, and demonstrates their potential use as a decision-support tool for policy makers and program planners for community suicide prevention actions.

This study demonstrates the utility of dynamic simulation models, co-designed with multi-disciplinary stakeholder groups, to capture and analyse complex mental health and suicide prevention regional planning problems. The model can be used by WentWest - Western Sydney Primary Health Network as a decision support tool to guide the commissioning of future service activity, and more efficiently frame the monitoring and evaluation of interventions as they are implemented in Western Sydney.

Background: The need to understand and respond to the unique characteristics and drivers of suicidal behaviour in rural areas has been enabled through the Australian Government’s 2015 mental health reforms facilitating a move to an evidence-based, regional approach to suicide prevention. However, a key challenge has been the complex decision-making environment and lack of appropriate tools to facilitate the use of evidence, data and expert knowledge in a way that can inform contextually appropriate strategies that will deliver the greatest impact. This paper reports the co-development of an advanced decision support tool that enables regional decision makers to explore the likely impacts of their decisions before implementing them in the real world. Methods: A system dynamics model for the rural and remote population catchment of Western New South Wales was developed. The model was based on defined pathways to mental health care and suicidal behaviour and reproduced historic trends in the incidence of attempted suicide (self-harm hospitalisations) and suicide deaths in the region. A series of intervention scenarios were investigated to forecast their impact on suicidal behaviour over a 10-year period. Results: Post-suicide attempt assertive aftercare was forecast to deliver the greatest impact, reducing the numbers of self-harm hospitalisations and suicide deaths by 5.65% (95% interval, 4.87−6.42%) and 5.45% (4.68−6.22%), respectively. Reductions were also projected for community support programs (self-harm hospitalisations: 2.83%, 95% interval 2.23−3.46%; suicide deaths: 4.38%, 95% interval 3.78−5.00%). Some scenarios produced unintuitive impacts or effect sizes that were significantly lower than what has been anticipated under the traditional evidence-based approach to suicide prevention and provide an opportunity for learning. Conclusion: Systems modelling and simulation offers significant potential for regional decision makers to better understand and respond to the unique characteristics and drivers of suicidal behaviour in their catchments and more effectively allocate limited health resources.

The persistent prevalence of childhood overweight and obesity raises significant concerns about the impact on health, society and the economy. Responding to a target announced in September 2015 by the New South Wales (Australia) Premier to reduce childhood overweight and obesity by five percentage points by 2025, a system dynamics model was developed to support Government and stakeholders responsible for meeting the target. A participatory model building process, drawing cross-sectorial expertise, was undertaken to estimate the individual and combined impact of interventions on meeting the target.The model demonstrated that it is theoretically possible to meet the target by implementing a comprehensive combination of policies and programmes. When limited to existing and enhanced population health interventions, the modelled result did not reach the target. The project provides an example of how participatory simulation modelling can combine a broad range of interventions together into likely scenarios and usefully inform government decision-making.

1 The use of the cytoplasmic enzyme, alpha glutathione s-transferase (α-GST) as an early index of carbon tetrachloride (CCl4) toxicity in the rat was investigated and compared with a standard enzyme marker, aspartate aminotransferase (AST). The hepatotoxic effects of CCl 4 in the rat were determined in a time and dose-response study. 2 Following CCl 4 exposure, α-GST release was shown to be an earlier and more sensitive biomarker of hepatotoxicity than AST. 3 Significant increases in α-GST were detected 2 h after CCl4 exposure. Using the enzyme marker AST, this early hepatotoxic injury went undetected. At 6 and 16 h, α-GST was also a more sensitive indicator of hepatotoxicity than AST. 4 α-GST release was significantly increased at a dose of 5 μl/kg, the lowest concentration of CCl4 administered and clearly responded in a dose-dependent manner with increasing doses of CCl4. In contrast, release of AST did not reach statistical significance until a dose of 25 μl/kg. 5 Thus, these findings indicate that α-GST is a more sensitive and more accurate reflector of CCl4 induced hepatotoxicity than AST.

Traditional epidemiological measures used to estimate population health burden have several limitations that are often understated and can lead to unrealistic expectations of the potential impact of evidence-based interventions in real-world settings. This study highlights these limitations and proposes an alternative analytic approach to guide policy and practice decisions to achieve reductions in Australian suicide.