Max Rady College of Medicine
Concept: Construction of Census Income Quintiles
Concept Description
Last Updated: 2008-05-21
Introduction
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Income quintiles are generally used when constructing a description of socio-economic status. The income quintiles consists of 5 income rankings that are separate for urban areas and rural areas (described below). The income quintiles have changed over the years and are not easily calculated. Never-the-less, to give you an idea of how the quintiles break down, consider the following:
1984 Minimum and Maximum value of Average Income by Quintile Rank and Urban/Rural Indicator
GURBAN RANK (QUINTILE) Minimum Maximum Mean RURAL 1 6866.00 19803.00 16857.07 2 19852.80 24038.27 22131.48 3 24137.00 26915.12 25491.65 4 27287.00 33915.53 29779.15 5 33946.16 47038.52 37494.37 URBAN 1 8767.00 23740.00 18964.24 2 23740.00 28393.00 26037.00 3 28393.00 34150.00 31381.63 4 34150.00 43048.00 38373.23 5 43048.00 126512.00 54967.41
Income Quintile Rankings
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Income quintile rankings are based upon the income rankings of the Manitoba population from 1984 to 1993. The 1986 census was used to rank years 1984 to 1988 and the 1991 census was used to rank 1989 to 1993.
Income quintiles were attached by postal code in strictly urban areas and by municipality code in mixed urban/rural areas and strictly rural areas. A variable called _RANK_ was created, which has the following range of values:
N1=Out of Province Municipal CodeThe values N1 to N7 identify observations that are not rankable. U1 to U5 and R1 to R5 are the income quintile rankings within an urban (U) or rural (R) designation. The urban/rural designation is based on a census definition of urban/rural involving a population density rule.
N2=Out of Province Postal Code
N3=Postal Code of a Personal Care Home
N4=Postal Code of Other Institution
N5=Postal Code Missing Income
N6=Municipal code Missing Income
N7=Post Code Not Present on Postal Code Conversion File
U1 to U5 =Urban Quintile 1 (lowest) to 5 (highest)
R1 to R5 =Rural Quintile 1 (lowest) to 5 (highest)
Both the 1986 and 1991 censuses are organized as one record per enumeration area (EA). Enumeration areas are the smallest unit of geography for which census data are normally available. Enumeration areas can be grouped up into census tracts (CT), census subdivisions (CSD), and census divisions(CD).
In most cases, particularly in Winnipeg, two or more postal codes make up an enumeration area. In 1986, there were 1,867 populated enumeration areas in the province of Manitoba, with a mean population of approximately 600 people. The classification into urban and rural residents was based on a geographic measure of population density used by Statistics Canada to classify census geography units. Under this definition, enumeration areas with population densities greater than 400 persons per square kilometer area are classified as urban. This definition will include small towns of population in the range of 5,000 persons in the urban category.
Method of Assigning Income Values
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The method of attaching census average income values available at the enumeration area level to the Manitoba population databases involved several steps.
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Postal codes associated with a Personal Care Home (PCH): Postal codes where the majority of residents (>90%) were in a personal care home (PCH) were excluded from ranking because the census does not collect income for institutionalized populations.
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Postal codes associated with other institutions: Some examples of such postal codes are those belonging to the public trustee office, prisons, and mental health institutions. These postal codes were collected from various sources, most notably, Charles Burchill, who, in collaboration with Fred Toll, provided a most comprehensive list of institutions which have their own postal code.
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Postal codes not present on the postal code conversion file (PCCF): The postal code conversion file (PCCF) provides a link from the postal code to the census enumeration area. If the postal code is not present on the PCCF there is no way to attach census income values required for the ranking procedure. (This was not entirely true as a portion of the data may be linked to the census by municipality code. More on this later.)
- No income value was provided on the census: The census will suppress income information for the EA if the non-institutional population of the EA is less than 250. An effort was made to impute an income value to these EAs as much as possible. Some EAs were left with a missing income value as the census defined no non-institutional population in that EA; for example, other institutions not defined above, or industrial or business districts in the city with no homes present.
- The 1986 population file contains several pre-1989 municipalities which were re-assigned in 1989. Since the municipality/census subdivision correspondence was developed in 1990, no corresponding census subdivision was provided for these municipality codes. A link was determined between the pre- and post-1989 municipalities and a weighted average income value was provided for the "old" municipal codes. Two old municipal codes (309 and 314) could not be fixed using this technique so it was decided that the population in these municipal codes would be forced to "strictly urban" and ranked by postal code.
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Several First Nations bands boycotted the 1986 and 1991 censuses and hence no average income value was provided for their municipalities. An average income value was imputed to these municipalities by calculating the weighted average income value of all First Nations bands that did not boycott the census by north/south zone. The average income value was imputed to the boycotting bands on the basis of their zone.
- One municipality code (A53) is defined as Inuit and out of province.
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First Nations people who are registered Treaty Status Indians and who have strictly urban postal codes will be assigned an income quintile on the basis of their postal code. All others will be assigned an income quintile on the basis of their home reserve, regardless of whether they actually live on the reserve. This cannot be overcome, because Treaty Status Indians always maintain their home reserve municipal code whether they live there or not.
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Portions of any event data set will not be ranked for various reasons. These reasons were described in the deletions above.
- Populations living on the periphery of Winnipeg may be defined as rural by the census. The census defines the urban/rural nature of a population by a density rule. Populations living in East St. Paul Rural Municipality, for example, are defined as rural by the census.
STEP 1: EXCLUSION OF RECORDS WHICH CANNOT BE RANKED TO AN INCOME QUINTILE.
An observation was defined as not rankable for several reasons:
STEP 2: PREPARING THE REMAINING POPULATION FOR RANKING.
After removing the observations that could not be ranked, the population was divided into a group rankable by postal code (strictly urban population) and a group that can be ranked by municipality code (mixed urban/rural and strictly rural populations).
The urban/rural status of a postal code was determined by the urban/rural designation of the EA linked to the postal code using the postal code conversion file. In addition several postal codes identified from the postal code book as rural routes link to strictly urban EA's according to the postal code conversion file. In reality, however, these postal codes are mixed urban/rural since they involve post office boxes which, while they are located in urban areas, have mail delivered to populations residing in rural areas.
a). Preparing the Strictly Urban Population for Ranking
The strictly urban population was ranked by postal code. The postal code was linked to the census enumeration area via the postal code conversion file.
When a postal code linked to two or more EAs, the average income value assigned was the weighted mean of the average income values of each EA, using the total number of private households in each EA as the weight.
It was possible to link to EAs where the average income value had been set to "0". These "0" values were reset to missing so that they do not contribute to the weighted mean average income value assigned to the postal code.
b). Preparing Mixed Urban/Rural and Strictly Rural Populations for Ranking
After preparing the strictly urban postal codes, the mixed urban/rural and strictly rural postal codes remained. This population was ranked by municipality code.
Previously it was found that ranking rural populations by postal code was unsatisfactory because rural postal codes often encompass too wide a geographical area. (For example, a rural town and the surrounding municipality often share a common postal code. Municipal code can be used to distinguish them, however, and the mean income value was calculated on the basis of municipality code.)
The municipality was linked to the federal enumeration areas belonging to the census subdivision that corresponds to the municipality. In most cases there was a one-to-one correspondence between municipality and census subdivision. The link between municipality and census subdivision was provided by some work done by Cam Mustard and Fred Toll.
Like the strictly urban postal codes, it was possible for a municipality to link to two or more EAs. When this happened, the weighted mean of the average income value of each linking EA was assigned to the municipality. Again, the weighted mean was calculated using the total number of private households as the weight.
SEVERAL MUNICIPALITIES DID NOT LINK TO A CENSUS SUBDIVISION FOR THREE REASONS:
Several municipalities linked to mixed urban and rural EAs. Because the municipality had to be defined as either urban or rural, the weighted mean of GURBAN (GURBAN=0 indicates rural EA, and GURBAN=1 indicates urban EA) was calculated for each municipality. The rounded value of this mean determined the urban/rural nature of the municipality.
STEP 3: RANKING BY URBAN AND RURAL DESIGNATION.
Strictly urban populations were summed by postal codes, defined as urban (GURBAN=1 in all cases) and having an average income value attached. Mixed urban/rural populations were summed by municipality codes, defined as urban or rural by a weighted majority rule and also had an average income value attached.
To rank postal codes and municipal codes to a quintile, these two files were concatenated, sorted by rural/urban and average income value. The total population by urban/rural was calculated. Within an urban/rural designation, postal code or municipal code populations were summed into classes so that approximately 20% of the population was in each class. These classes formed quintiles within the urban/rural designation.
After ranking each postal code or municipal code, the population was again broken apart into the set ranked by postal code and the set ranked by municipal code.
From these two data sets, a format that assigns an income quintile value to a postal code and a format that assigns an income quintile value to a municipal code was produced.
IMPORTANT CONSEQUENCES OF THIS METHOD OF ASSIGNING INCOME QUINTILE:
This work follows in the footsteps of many previous brave pioneers including Cam Mustard and Ngiap Koh who took the first steps in understanding the 1986 census. Cam Mustard, Teresa Mayer, Shelley Derksen and Leonard McWilliam continued the journey into the 1991 census. The original document was prepared by Shelley Derksen.
Related concepts
Related terms
- Canadian Census Data
- Income Adequacy Quintiles
- Income Quintiles / Income Quintile
- Manitoba Health Insurance Registry (MHIR) Data
- Manitoba Health Population File
- Postal Code Conversion Files (PCCF)
- Q1/Q5 Ratio
References
- Mustard CA, Derksen S, Berthelot JM, Wolfson M, Roos LL. Age-specific education and income gradients in morbidity and mortality in a Canadian province. Soc Sci Med 1997;45(3):383-397. [Abstract] (View)
- Mustard CA, Frohlich N. Socioeconomic status and the health of the population. Med Care 1995;33(12 Suppl):DS43-DS54. [Abstract] (View)
- Roos NP, Mustard CA. Variation in health and health care use by socioeconomic status in Winnipeg, Canada: does the system work well? Yes and no. Milbank Q 1997;75(1):89-111. [Abstract] (View)
Keywords
- census
- income quintiles
- postal codes
- socioeconomic status
- statistics
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