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Co-head, Diabetes and Obesity Research
Research Assistant
Recent diabetes technology is helping 12-year-old Drina keep on top of her condition and be independent, while significantly easing the disease burden on her family.
Once upon a time it was infectious diseases like polio, measles or tuberculosis that most worried parents. With these threats now largely under control, parents face a new challenge – sky-rocketing rates of non-infectious diseases such as asthma, allergies and autism.
Every decision a child with type 1 diabetes makes can impact on their blood glucose levels.
Liz Tim Davis Jones MBBS FRACP PhD MBBS DCH FRACP MD Co-director of Children’s Diabetes Centre Co-head, Diabetes and Obesity Research Co-director of
Aveni Liz Haynes Davis BA (Hons), MBBChir, MA (Cantab), PhD MBBS FRACP PhD Principal Research Fellow Co-director of Children’s Diabetes Centre
Temporal eating patterns and ultra-processed food (UPF) consumption have independently been associated with obesity and non-communicable diseases. Little is known about the temporal patterns of UPF consumption, as data is challenging to collect. Temporal data can be extracted from mobile food records (mFRs). The aim of this study was to identify the temporal eating patterns of those consuming UPFs using an mFR.
A main challenge identified by youth during exercise and sport is the lack of knowledge and awareness around type 1 diabetes (T1D) particularly in community sport settings. Working with youth living with T1D, parents and community sport coaches, our team has developed resources for the T1D and sporting community. This study was to evaluate the acceptability and usability of the resources.
Type 1 diabetes and diabetic ketoacidosis (DKA) have a significant impact on individuals and society across a wide spectrum. Our objective was to utilize machine learning techniques to predict DKA and HbA1c>7 %.