Canadian Socioeconomic and Sociodemographic Prevalence at DA Level

The dataset provides the prevalence of various socioeconomic and sociodemographic variables at a dissemination area (DA) level granularity across Canada, in 2021. Each variable is expressed as a percentage (%) of the total relevant population within that DA, with the exception of median and average income variables, which remain in nominal CAD value. Key socioeconomic indicators include low income status based on the low-income measure, after tax (LIM-AT), low income based on the Low-income cut-offs, after tax (LICO-AT), spending 30% or more of income on shelter costs only, etcetera. Key sociodemographic indicators include visible minority, immigrant status, Indigenous status, unemployment, etcetera. The DAUID_21 column provides a unique identification code (aligning with Statistics Canada) for each individual DA across the country. In total the dataset captures 57,936 DAs and 53 indicators.

The dataset can be paired with other DA-level exposure datasets (such as various air pollutants), in order to determine existing relationships between exposure risk and various socioeconomic and sociodemographic indicators. This is helpful in research pertaining to the disproportionate burden of environmental risk on minority and low-income populations, in addition to patterns of residential socioeconomic and sociodemographic characteristics across Canada. Due to the fine granularity, the dataset supports detailed urban analysis.

All data was retrieved from Statistics Canada, using the 2021 Census of Population. Each individual dataset can be found within the Comprehensive Downloads section of the 2021 Census profile: https://www12.statcan.gc.ca/census-recensement/2021/dp-pd/prof/details/download-telecharger.cfm?Lang=E. Six individual datasets were merged together: Canada, provinces, territories, census divisions (CDs), census subdivisions (CSDs) and dissemination areas (DAs) for Atlantic only, Quebec only, Ontario only, Prairies only, British Columbia only, and Territories only. Data cleaning - to remove CD and CSD data - and dataset merging was all completed using R.