The effects of summer temperature, age and socioeconomic circumstance on Acute Myocardial Infarction admissions in Melbourne, Australia

<p>Abstract</p> <p>Background</p> <p>Published literature detailing the effects of heatwaves on human health is readily available. However literature describing the effects of heat on morbidity is less plentiful, as is research describing events in the southern hemisphere and Australia in particular. To identify susceptible populations and direct public health responses research must move beyond description of the temperature morbidity relationship to include social and spatial risk factors. This paper presents a spatial and socio-demographic picture of the effects of hot weather on persons admitted to hospital with acute myocardial infarction (AMI) in Melbourne.</p> <p>Results</p> <p>In this study, the use of a spatial and socio-economic perspective has identified two groups within the population that have an increased 'risk' of AMI admissions to hospital during hot weather. AMI increases during hot weather were only identified in the most disadvantaged and the least disadvantaged areas. Districts with higher AMI admissions rates during hot weather also had larger proportions of older residents. Age provided some explanation for the spatial distribution of AMI admissions on single hot days whereas socio-economic circumstance did not. During short periods (3-days) of hot weather, age explained the spatial distribution of AMI admissions slightly better than socioeconomic circumstance.</p> <p>Conclusions</p> <p>This study has demonstrated that both age and socioeconomic inequality contribute to AMI admissions to hospital in Melbourne during hot weather. By using socioeconomic circumstance to define quintiles, differences in AMI admissions were quantified and demographic differences in AMI admissions were described. Including disease specificity into climate-health research methods is necessary to identify climate-sensitive diseases and highlight the burden of climate-sensitive disease in the community. Cardiac disease is a major cause of death and disability and identifying cardiac-specific climate thresholds and the spatio-demographic characteristics of vulnerable groups within populations is an important step towards preventative health care by informing public health officials and providing a guide for an early heat-health warning system. This information is especially important under current climatic conditions and for assessing the future impact of climate change.</p

Demographic, seasonal, and spatial differences in acute myocardial infarction admissions to hospital in Melbourne Australia

<p>Abstract</p> <p>Background</p> <p>Seasonal patterns in cardiac disease in the northern hemisphere are well described in the literature. More recently age and gender differences in cardiac mortality and to a lesser extent morbidity have been presented. To date spatial differences between the seasonal patterns of cardiac disease has not been presented. Literature relating to seasonal patterns in cardiac disease in the southern hemisphere and in Australia in particular is scarce. The aim of this paper is to describe the seasonal, age, gender, and spatial patterns of cardiac disease in Melbourne Australia by using acute myocardial infarction admissions to hospital as a marker of cardiac disease.</p> <p>Results</p> <p>There were 33,165 Acute Myocardial Infarction (AMI) admissions over 2186 consecutive days. There is a seasonal pattern in AMI admissions with increased rates during the colder months. The peak month is July. The admissions rate is greater for males than for females, although this difference decreases with advancing age. The maximal AMI season for males extends from April to November. The difference between months of peak and minimum admissions was 33.7%. Increased female AMI admissions occur from May to November, with a variation between peak and minimum of 23.1%. Maps of seasonal AMI admissions demonstrate spatial differences. Analysis using Global and Local Moran's I showed increased spatial clustering during the warmer months. The Bivariate Moran's I statistic indicated a weaker relationship between AMI and age during the warmer months.</p> <p>Conclusion</p> <p>There are two distinct seasons with increased admissions during the colder part of the year. Males present a stronger seasonal pattern than females. There are spatial differences in AMI admissions throughout the year that cannot be explained by the age structure of the population. The seasonal difference in AMI admissions warrants further investigation. This includes detailing the prevalence of cardiac disease in the community and examining issues of social and environmental justice.</p

Book reviews

Teaching/Communication/Extension/Profession,

Emissions Reduction Targets and the Great Barrier Reef

“Warming of the climate system is unequivocal, as is now evident from observations of increases in global average air and ocean temperatures, widespread melting of snow and ice, and rising global average sea level.” Scientific research from multiple independent sources indicates that the emission of greenhouse gases by human activities is the primary cause of the observed global average warming of 0.7oC over the past century1. Australia’s land and sea temperatures are currently warming at the global average rate. Furthermore, emissions over the past century have already committed us to a future increase in global average temperature of at least 1oC 1. The most recent evidence shows that the climate is changing more rapidly than earlier thought likely2. This underscores the need for immediate action to both reduce greenhouse gas emissions caused by human activities that are responsible for climate change, and to adapt to the changes we cannot prevent

Climate Variability, Social and Environmental Factors, and Ross River Virus Transmission: Research Development and Future Research Needs

Background: Arbovirus diseases have emerged as a global public health concern. However, the impact of climatic, social and environmental variability on the transmission of arbovirus diseases remains to be determined. Objective: We provided an overview of research development and future research directions about the inter-relationship between climate variability, social and environmental factors and the transmission of Ross River virus (RRV) – the most common and widespread arbovirus disease in Australia. Methods: We conducted a systematic literature search on climatic, social and environmental factors and RRV disease. Potentially relevant studies were identified from a series of electronic searches. Databases searched were the MEDLINE (via EBSCOhost), Current Contents Connect (via ISI Web of Knowledge) and ScienceDirect. We critically reviewed key predictors of RRV transmission through an integration of our own research with literature. Results: The body of evidence reveals that the transmission cycles of RRV disease appeared to be sensitive to climate variability. Rainfall, temperature and high tides were among major determinants of the transmission of RRV disease at macro level. However, the nature and magnitude of the inter-relationship between climate variability, mosquito density and the transmission of RRV disease varied with geographic area and socio-environmental condition. Projected anthropogenic global climatic change may result in an increase in RRV infections. Conclusions: The analysis indicates that there is a complex relationship between climate variability, social and environmental factors and Ross River virus transmission. Different strategies should be adopted for the control and prevention of Ross River virus disease at different levels. These research findings could be used as an additional tool to support decision-making in disease control/surveillance and risk management

Weather Variability, Tides, and Barmah Forest Virus Disease in the Gladstone Region, Australia

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention

Development of a new mechano-chemical model in boundary lubrication

A newly developed tribochemical model based on thermodynamics of interfaces and kinetics of tribochemical reactions is implemented in a contact mechanics simulation and the results are validated against experimental results. The model considers both mechanical and thermal activation of tribochemical reactions instead of former thermal activation theories. The model considers tribofilm removal and is able to capture the tribofilm behaviour during the experiment. The aim of this work is to implement tribochemistry into deterministic modelling of boundary lubrication and study the effect of tribofilms in reducing friction or wear. A new contact mechanics model considering normal and tangential forces in boundary lubrication is developed for two real rough steel surfaces. The model is developed for real tribological systems and is flexible to different laboratory experiments. Tribochemistry (e.g. tribofilm formation and removal) and also mechanical properties are considered in this model. The amount of wear is calculated using a modified Archard’s wear equation accounting for local tribofilm thickness and its mechanical properties. This model can be used for monitoring the tribofilm growth on rough surfaces and also the real time surface roughness as well as changes in the λ ratio. This model enables the observation of in-situ tribofilm thickness and surface coverage and helps in better understanding the real mechanisms of wear

A Semi-deterministic Wear Model Considering the Effect of Zinc Dialkyl Dithiophosphate Tribofilm

Tribochemistry plays a very important role in the behaviour of systems in tribologically loaded contacts under boundary lubrication conditions. Previous works have mainly reported contact mechanics simulations for capturing the boundary lubrication regime, but the real mechanism in which tribofilms reduce wear is still unclear. In this paper, the wear prediction capabilities of a recently published mechanochemical simulation approach (Ghanbarzadeh et al. in Tribol Int, 2014) are tested. The wear model, which involves a time- and spatially dependent coefficient of wear, was tested for two additive concentrations and three temperatures at different times, and the predictions are validated against experimental results. The experiments were conducted using a mini-traction machine in a sliding/rolling condition, and the spacer layer interferometry method was used to measure the tribofilm thickness. Wear measurements have been taken using a white-light interferometry. Good agreement is seen between simulation and experiment in terms of tribofilm thickness and wear depth predictions

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability