Toyib Olaniyan
Toyib Olaniyan is an accomplished Environmental Epidemiologist and a dedicated Research Analyst in the Health Analysis Division at Statistics Canada. He also holds an Affiliate role at both McGill University and the University of Cape Town, in South Africa. He is involved in a wide range of Environmental Health Research and more recently Health Equity Research. Dr. Olaniyan obtained his PhD in Public Health with expertise in Environmental Epidemiology from the University of Cape Town, South Africa. He was a postdoctoral fellow at Carleton University, and Statistics Canada, respectively between 2018 and 2020. Before then, he did a fellowship at the Swiss Tropical and Public Health Institute in Basel, Switzerland, and had his other graduate trainings at the University of Northampton, Northampton UK (Public Health) and Memorial University of Newfoundland, St John’s Canada (Clinical Epidemiology).
Beyond his academic and research endeavors, Dr. Olaniyan plays a pivotal role as the Statistics Canada Liaison to the Canadian Black Scientists Network (CBSN). In this capacity, he leads and offers strategic guidance and support to senior management, and champions a pilot recruitment program initiative aimed at attracting Black STEM talents into opportunities within Statistics Canada. During the panel discussion, Dr. Olaniyan will share insights and experiences related to this cutting-edge initiative, born from the collaboration between Statistics Canada and CBSN.
I am involved in a wide range of environmental health research on ambient air pollution, natural environment (e.g. greenness), built environment (e.g. walkability), social environment (e.g. neighborhood deprivation), environmental & occupational contaminants (e.g. radon), and their respective intersections with Climate Change. I am also involved in Health Equity Research to inform policy related to inequalities and inequities in our society.
Ambient air pollution, natural environment (e.g. greenness), built environment (e.g. walkability), social environment (e.g. neighborhood deprivation), intersections with Climate Change, population/admin data, big data, causal inference.