VIEWPOINT
By Stacey Butler
C
anada may have a universal healthcare system, however the treatment Canadians receive is far from equal. Canadian rapper, John River, was experiencing shortness of breath and severe headaches, yet these symptoms were dismissed by hospitals in Toronto, simply because of his appearance and skin colour. Instead of his complaints being taken seriously, he was stereotyped, viewed as uneducated, and assumed to be faking symptoms to obtain drugs. This case of systemic racism resulted in significant delays in treatment and left John River in severe pain for months on end.1
construct that categorizes people based on visual traits such as the colour of their skin.4 Ethnicity refers to groups with a shared culture, ancestry, language, or belief system.4 Race has been used both historically and currently to discriminate against, exclude, or marginalize a group of people, and results in unequal opportunities. It is crucial to understand how both race and ethnicity contribute to health inequalities in Canada. Data on race can be used to identify health inequalities that exist due to bias and racism. While data on ethnicity can be used to understand and identify cultural barriers to healthcare.4
Stories like this bring to light the health inequalities experienced by racialized individuals in Canada. Despite culture and race (or more accurately, racism) being recognized by Health Canada as important social determinants of health,2 our healthcare system does not routinely collect data on race or ethnicity, with the exception of indigenous identity. Failing to collect race or ethnicity-based data in Canada is a major limitation that negatively impacts the quality of our research and our healthcare system. It prevents us from understanding the diversity of our patients and from being able to detect inequalities that we know exist as a result of systemic racism.3
Since individual-level data on race or ethnicity is not routinely collected in Ontario’s healthcare system, population health studies have resorted to using alternative methods to measure health inequalities. Typically these methods rely on neighbourhood, or area-level data available from the Canadian Census. For example, the Ontario Marginalization Index (ON-Marg) addresses race and ethnicity by identifying areas of Ontario with a high ‘ethnic concentration’, defined as areas with a high proportion of the population who identify as a visible minority or are a recent immigrant (arrived to Canada in the past five years).5 The ON-Marg tool is limited by its use of aggregated, area-level data, as opposed to data on each individual’s ethnicity. An additional limitation is the so-called ‘healthy immigrant effect’, where
The terms race and ethnicity are often used interchangeably, despite having different meanings and contexts. Race is a social 18 | IMS MAGAZINE SPRING/SUMMER 2021 PUBLIC HEALTH
recent immigrants are generally healthy but their health deteriorates over time. Furthermore, in the case of diabetes, this deterioration is greater for immigrants who belong to a visible minority group.6 Nonetheless, the ON-Marg tool is still useful to study several social determinants of health in Ontario at the neighbourhood level. Given the limitations of area-level data, epidemiologists at ICES, a population health research institute in Ontario, have gotten creative with their approach to addressing ethnicity. They have developed a tool that uses surnames to identify people of South Asian and Chinese ethnicity.7 Using this method, researchers have uncovered differences in the risk of several diseases and in the severity of mental illness.8 However, the surname algorithm is only able to categorize people into two distinct ethnic groups (South Asian and Chinese) and lumps the remainder into a ‘general population’ category. Thus, it cannot measure health inequalities in other ethnic groups that exist within the Ontario population, reiterating the need for individual-level data on ethnicity. The COVID-19 pandemic has put race and ethnicity in Canada in the spotlight, as aggregate, neighbourhood level data draws our attention to the disproportionate rates of infection and mortality among racialized communities.9 Visible minority groups are seven times more likely to have Graphic design by Ava Schroedl
