Diabetes Incidence and Risk Factors

This team is looking at diabetes in Mississauga and Peel to see how individual and community risk factors vary in order to determine future risk and potential solutions.


  1. Determine how the individual and community-level risk factors for diabetes vary by social determinants of health in Region of Peel and Mississauga
  2. Determine whether rates of pre-diabetes and gestational diabetes vary by individual and community-level social determinants of health
  3. Determine the transition time between gestational diabetes, pre-diabetes and diabetes and how they vary by individual and community-level social determinants of health
  4. Characterize future risk of diabetes across the region to target potential interventions

Lead Investigators

Ghazal Fazli

Ghazal Fazli, PhD

Dr. Ghazal Fazli is an Assistant Professor, Teaching Stream at the University of Toronto Scarborough, and a Diabetes Action Canada postdoctoral fellow based at Unity Health Toronto. Her research explores the impact of sociodemographic, immigration, and environmental related factors on diabetes development among high-risk population. As an epidemiologist, Ghazal is interested in research and policy initiatives that promote action on the social determinants of health to improve wellbeing and quality of life across the lifespan. In her current research, she is examining the impact of the COVID-19 pandemic on prediabetes and diabetes development among Ontarians, and particularly among marginalized and racialized communities via population-based databases and patient and community engagement initiatives.

Laura Rosella

Laura Rosella, PhD, MHSc

Dr. Laura Rosella is an epidemiologist and Associate Professor in the Dalla Lana School of Public Health (DLSPH) at the University of Toronto, where she holds a Tier 2 Canada Research Chair in Population Health Analytics. She is also the Program Director for the DLSPH PhD Program in Epidemiology, Site Director at ICES U of T, and a Faculty Affiliate at the Vector Institute for Artificial Intelligence. Laura leads the Population Health Analytics laboratory where she focuses on using linked population health data in new ways to support diabetes prevention. She has developed methodology to develop and validate population risk prediction tools, including the Diabetes Population Risk Tool and a new methodology to identify optimal cut-offs for diabetes screening. Her current research is focused on understanding how persons living with type 2 diabetes accumulate chronic conditions over their life course and elucidating what factors contribute to mortality outcomes.