DIY in Your Research Design – Best Practices in the Use of Race, Ethnicity and Immigration Data

Dr. Susitha Wanigaratne, Senior Research Associate at the Edwin S.H. Leong Centre for Healthy Children and social epidemiologist, presented a lecture titled “Best Practices in the use of Routinely Collected Race, Ethnicity, and Immigration Data” at the DIY-Diversity and Inclusion in Your research design at the SickKids Research Institute event on April 18. She provides a summary of her presentation.

The disproportionate impact that the COVID-19 pandemic has had on racialized communities in Canada and around the world, has intensified the interest in collecting data on racial and ethnic identifiers. This presentation provided an overview of best practices when thinking about using race and ethnicity in research. Race and ethnicity are socially constructed and have no measurable biological or genetic basis. Race constructs differences between groups which have significant impacts on people’s health and well-being. Ethnicity is related to aspects of cultural group membership such as language or religion. This understanding impacts how we should be using race and ethnicity in scientific research. Specifically, geneticists acknowledge that racial groupings are not related to genetic or continental ancestral groups and that continuing to conflate the two is likely to contribute to health inequities rather than address them, and reinforce misunderstandings of race. Race should not be described as a risk factor for disease pathology in clinical practice guidelines or used as a co-efficient in clinical algorithms. Instead, we should consider race and ethnicity and accompanying experiences of racism, discrimination and xenophobia as structural and social determinants of health and follow recently developed guidance from numerous medical journals and organizations on how to conduct anti-racist research.

View her PowerPoint slide deck here.