Statistics Canada defines census geography for efficient collection and reporting of census data. The geography is structured to ensure that each level fits neatly within the larger levels, with some exceptions that will be discussed later.
You'll come across the following acronyms in this training:
- DA (Dissemination Area)
- CT (Census Tract)
- ADA (Aggregate Dissemination Area)
- CSD (Census Subdivision)
- CD (Census Division)
- CMA (Census Metropolitan Area)
- MIZ (Metropolitan Influenced Zone)
The diagram below presents how census geographies nest within each other. Each box contains a level of census geography that will be covered in this guide, from the smallest spatial area, a DA, to the largest, Canada. The arrows represent different geographical relationships, where the geography below nests within the geography above, e.g., DAs within CSDs.
Don't worry! You're in good hands – we don't expect you to fully understand this diagram yet. You'll notice how some arrows are crossed out, non-existent or dashed. We'll be covering these exceptions, too.
Dissemination Areas
Dissemination Areas (DA) represent small, effective units for mapping and data analysis. DAs aim to maintain consistent population sizes, typically ranging from 200-400 households or 400-700 population.
DAs are designed to be as homogeneous as possible; for example, they do not cross rivers, major highways, or political boundaries. Some of our data are released at this level.
I'm looking at a map of DAs and this one is tiny (spatially) - what's up with that?
It's all about consistency of population and/or household count. That means that one DA could be an apartment building or a wide area that is less populated. Here's an example of two very different sized DAs:
In the real world, postal codes can cross DA boundaries (in rural areas), and comparing the two can get a little messy. At EA, however, we use Canada Post's Postal Code Conversion File and our own proprietary techniques to combine the two.
Depending on your license, you can use the ePCCFopens in new window or your PRIZMopens in new window License file to identify the link between DAs and postal codes.
Census Divisions & Subdivisions
Dissemination Areas (DAs) roll up to Census Subdivisions (CSDs), which all neatly fit together. They consist of multiple DAs.
These maps show how DAs respect CSD boundaries. CSDs can be spatially large or small, with many or few corresponding DAs.
CSDs tend to be municipalities, cities, or regions, such as Mississauga, Richmond Hill, Montreal West, or Pointe-Claire. Their populations range from large cities with millions of residents, to small rural municipalities with just a few hundred inhabitants.
Good to Know!
CSDs are categorized into 57 types, such as Fire Districts (FD), Towns (T), and Rural Municipalities (RM).
CSDs fit neatly within CDs, of which there are around 290 across Canada. However, this can change depending on the census.
CD population sizes can vary widely. For example, the CD of Stikine, BC, has the lowest population of 691 in an area of 119,681 km², while the CD of Toronto, ON, has the highest population at 3,035,455 in just 633 km².
DAs, CSDs, and CDs roll up to Provinces/Territories, and then to Canada as a whole, as you can see in the diagram at the beginning of this page.
Census Tracts & Census Metropolitan Areas/Census Agglomerations
Unlike our previous geography levels that fit together nicely to provide full Canadian coverage, CMAs and CAs exist like islands of higher population densities across Canada. They can also cross provincial boundaries, for example Ottawa/Gatineau (ON/QC).
CTs are created by subdividing CMA/CAs that cover larger areas. CTs provide finer geographic detail, aiding analysis. You'll find 2,500 to 8,000 people living here. These are only found in population centres where CMAs and CAs exist.
If CMAs and CAs are different sizes, why are they mentioned together?
Both CMAs and CAs are defined by municipalities (referred to as the "fringe") that are connected to a population centre (commonly called the "core"). CMAs and CAs will have a relatively high population density in the core and a higher relative urbanity. A high proportion of fringe residents travel to the core to access this urban area for things like employment.
This focus on only areas of high density is why both appear like little islands across Canada, rather than the complete coverage you've seen with other geographies so far.
Additionally, while we've learned DAs are the basic building blocks for both CDs/Provinces, and CMA/CAs and CTs, these urban and fringe geographies (CMA/CAs and CTs) can occasionally cross CD and provincial boundaries.
CMAs and CAs have minimum population thresholds in the core (and in the fringe for CMAs). Once a CMA is created, it will remain in the census even if its population falls below the minimum, while CAs will be retired from the next census should their core population drop below the minimum.
Why use CTs, CMAs, and CAs? Why not just use the previous census geography levels?
CMAs and CAs were created to observe highly urban cities and the behaviours of neighbouring rural areas that visit them. Because of how they develop, urban areas don't always fit nicely into other census geographies and don't cover all of Canada.
While all CMAs are subdivided into CTs, only CAs with a core population above 50,000 contain CTs to help capture differences between core and fringe populations as they develop in very human, and often unpredictable, ways.
Aggregate Dissemination Areas
ADAs tend to be slightly larger than CTs, with a population of 5,000 to 15,000. As the name suggests, ADAs group DAs based on population. Small CSDs may be grouped wholesale to form an ADA in places where CSD populations are below the ADA requirement.
DAs are the basic building block, but ADAs are also defined by combining lower-population CSDs or CTs. From a practical point of view, it makes sense to keep CSDs and CTs "whole" when forming ADAs.
By including CTs and CSDs, depending on the context, ADAs have the unique ability to respect the boundaries of CSDs, CDs, and Provinces while also respecting the boundaries of CMA/CAs, even though the urban geographies don't always align with the standard hierarchy.
I've come across this level of geography in your data... What does PRCDADA stand for in the variables?
This code defines the geographical level as an ADA, merging the acronyms with higher levels of geography.
PR = Province
CD = Census Division
ADA = Aggregate Dissemination Area
Together, you get PRCDADA!
Learn more about Standard Geography Codes and Names. opens in new window
What do the numbers mean?
Each province is assigned a unique two-digit code by Statistics Canada. All lower levels of nesting census geography begin with those two digits. For example, Ontario is 35, Quebec is 24, and British Columbia is 59.
You'll get more familiar with the numbering scheme as you work with our data in flat file format. The geography codes follow a hierarchy.
Each dissemination area (DA) is assigned a four-digit code that consists of the two-digit province (PR) code and the two-digit census division (CD) code. For example, these DAs in Mississauga all start with 3521 (Ontario (PR) = 35 and Peel Region (CD) = 21).
Metropolitan Influenced Zones
The Census Metropolitan Influenced Zone (MIZ) categorizes areas in Canada outside major cities into four groups based on their degree of influence from nearby urban centers.
The category of MIZ represents the influence of CMA/CAs on the surrounding CSDs that are not captured by either. The four categories are:
- Strong Influence: at least 30% of the municipality's residents in the labour force commute to work in any CMA or CA.
- Moderate Influence: More than 5%, but less than 30% of the municipality's residents in the labour force commute to work in any CMA or CA.
- Weak Influence: more than 0%, but less than 5% of the municipality's residents in the labour force commute to work in any CMA or CA.
- No Influence: fewer than 40 of the municipality's residents in the labour force commute to work in any CMA or CA.
Now let's examine how EA puts postal and census geographies together.