Metabolically Healthy and Unhealthy Obese Phenotypes among Arabs and South Asians:Prevalence and Relationship with Cardiometabolic Indicators

Obesity is a public health crisis in Kuwait. However, not all obese individuals are metabolically unhealthy (MuHO) given the link between obesity and future cardiovascular events. We assessed the prevalence of the metabolically healthy obese (MHO) phenotype and its relationship with high sensitivity C-reactive protein (hs-CRP), serum alanine aminotransferase (ALT), and insulin resistance (HOMA-IR) in Arab and South Asian ethnic groups in Kuwait. The national cross-sectional survey of diabetes and obesity in Kuwait adults aged 18–60 years were analysed. The harmonised definition of metabolic syndrome was used to classify metabolic health. Multinomial logistic regression analysis was used to model the relationship between the MHO and MuHO phenotypes and hs-CRP, ALT and HOMA-IR levels. Overall, the prevalence of MHO for body mass index (BMI)- and waist circumference (WC)-defined obesity was 30.8% and 56.0%, respectively; it was greater in women (60.4% and 61.8%, respectively) than men (39.6% and 38.2%, respectively). Prevalence rates were also lower for South Asians than for Arabs. The MHO phenotype had hs-CRP values above 3 µg/mL for each age group category. Men compared to women, and South Asians compared to Arabs had a lower relative risk for the MHO group relative to the MuHO group. This study shows there is high prevalence of MHO in Kuwait

BUSHFIRE BEHAVIOUR MODELLING USING FARSITE WITH GIS INTEGRATION FOR THE MITCHAM HILLS, SOUTH AUSTRALIA

Bushfire behaviour modelling using FARSITE with GIS integration for the Mitcham Hills, South Australia. Bushfires are now becoming of serious concern as they can have devastating effects on the natural and human ecosystems. An important element of bushfires is fire behaviour. Fire behaviour describes the mode in which a fire reacts to the influences of fuel, weather, topography and fire fighting. In order to understand and predict fire growth and the behaviour of fires, decision makers use fire models to simulate fire behaviour. Fire behaviour modelling can assist forest managers and environmental decision makers in the understanding of how a fire will behave with the influences of environmental factors such as fuels, weather and topography. This study models (spatially and temporally) the behaviour of a hypothetical fire for the Mitcham Hills in South Australia using FARSITE (Fire Area Simulator). FARSITE, a two-dimensional deterministic model, takes into account the factors that influence fire behaviour (fuels, weather and topography) and simulates the spread and behaviours of fires based on the parameters inputted. Geographic Information Systems (GIS) and Remote Sensing (RS) techniques were utilised for data preparation and the mapping of parameters that are needed and welcomed by FARSITE. The results are a simulation of spread of fire, fireline intensity, flame length and time of arrival for the area of interest. The simulation confirmed that it can be used for predicting how a fire will spread and how long it will take which can be very beneficial for fire suppression and control and risk assessment