Investigators: Dimpal Patel, Rachel Foong, Graham Hall
Partners: Curtin University, the Raine Study
Asthma is the most common lung disease of childhood. In Western Australia, nearly 9% of children report having a doctor diagnosis of asthma. Asthma diagnosis is difficult in young children. Therefore, there has been a worldwide effort to develop ways to identify asthma risk as early as possible in order to prevent disease.
This study aims to show that asthma and allergies in individuals can be predicted before it occurs based on individual family history and information on the early environment. We aim to create individual scores to predict the chance of developing asthma and allergy using new data science techniques, which will help in preventing and managing asthma. We will use data from the Raine Study to develop the prediction scores. The Raine Study recruited over 2800 pregnant women in Perth, WA and asthma and allergies have been well-studied in this cohort at 6-years and 14-years in children.
Once prediction scores have been developed, we will test if these scores are also valid in international birth cohort studies. A predictive model of asthma and allergies based on questionnaire data and family history may help doctors make decisions quickly in a cost-efficient way. It can improve diagnosis of asthma and allergy and can be helpful in understanding how asthma and allergies develop.