Barriers of Indigenous Environmental Health Cancer Research in Canada

ID: 1916

Presenting Author: Maja Wetzl

Session: 714 - Assessing Information: Conflicting Data Interpretation and Eroding Public Trust

Status: pending


Summary Statement

Supporting Indigenous Data Sovereignty in IA by accessing Statistics Canada Microdata to develop statistical analysis techniques for Indigenous environmental health cancer research.


Abstract

Indigenous peoples experience poorer health outcomes than non-Indigenous populations due to the ongoing effects of colonialism and land dispossession, including from the direct impacts of extractive industry. Our research affirms that Indigenous-led and community-owned culturally relevant health data is needed to make informed decisions around health. This research leverages an Indigenous-led community-based participatory research methodology and statistical analysis techniques to compile cancer rates for three Indigenous communities in Fort Chipewyan (Athabasca Chipewyan First Nation, Mikisew Cree First Nation, and Fort Chipewyan Métis Nation), affected by extractive industry, using the Canadian Cancer Registry (CCR) accessed through Statistics Canada. This data is compared to other Indigenous and non-Indigenous populations at different geographic scales for contextualization. Revising and updating the methods from Fort Chipewyan’s 2009 cancer incidence report, this presentation will describe the process of obtaining the CCR and Statistics Canada data, and not the data itself, and the barriers that may affect Indigenous communities’ abilities to access and utilize their own cancer data to make informed decisions, including in impact assessment processes. We encourage a dialogue about addressing structural barriers in information and data access to support Indigenous communities' self-determination of health and well-being through relational research and data sovereignty.


Author Bio

Maja Wetzl has a HBSc in Mathematical Science, from the University of Guelph. She started her Master of Science in Applied Statistics last year, continuing at the University of Guelph.


Coauthor 1: Diana Lewis

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