Concept: Socioeconomic Factor Index (SEFI) - Based on the 1986, 1991, and 1996 Census Data

Introduction

Socioeconomic variables are perhaps the most important predictors of health. Thus, members of MCHP have created indices to examine the relationship of a population's socioeconomic characteristics to its health status and use of health care services. The Socioeconomic Factor Index (SEFI) is based on the earlier Socioeconomic Risk Index (SERI). For more information on the SERI, please read the Socio-Economic Risk Index (SERI) concept.

Source Data

Basic Summary Tables from Statistics Canada

The source for socioeconomic characteristics is the basic summary tabulations released by Statistics Canada. These contain comprehensive data from 2A and 2B census forms by large and small levels of geography. These include Canada, the provinces and territories, census sub-divisions, census tracts, enumeration areas, federal electoral districts and forward sortation areas.

Measures of Area Socioeconomic Characteristics

In the development of the original 1986 census SERI, 23 socioeconomic characteristics for Manitoba at the enumeration area level were collected. These variables were also collected from the 1991, and 1996 censuses. From this large class of variables, a smaller group of 12 variables was selected to form the basis of the longitudinal index as shown in Table 1.

The number of socioeconomic characteristics were further reduced to 7 variables by combining the 4 age-specific unemployment rate variables and the 3 age-specific education rate variables into a single unemployment principal component factor and a single education principal component factor.

Methodology

SEFI was developed at the municipality code level. Thus the socioeconomic characteristics available at the enumeration area level needed to be recalculated at the municipality code level. Characteristics that were missing at the municipality code level were imputed a value according to the strategy below.

Imputation Strategy

To protect the confidentiality of individual responses, Statistics Canada has adopted a technique known as area suppression.

Area suppression - the deletion of all characteristic data for geographic areas below a specified size.


• Income distributions and related statistics are suppressed if the total non-institutional population in the area from either the 100% or 20% databases is less than 250.
  
• Other characteristics are suppressed if the total non-institutional population in the area from either the 100% or 20% databases is less than 40.

The municipality code level value of each of the socioeconomic characteristics was calculated by the weighted mean of the enumeration area values (where the weight is dependent upon the specific characteristic).


• If all of the enumeration area values for a specific characteristic were suppressed within the municipality, the municipality code level value was missing.
  
• To calculate the imputation value, each municipality code was defined as either a first nation community or not.
  
• Then weighted mean values were calculated for each characteristic by physician service area and first nation community status.
  
• Each missing municipality code within a physician service area was imputed the appropriate first nation community average value or non-first nation community value.

Index Construction

See "Constructing the SEFI" document for details.

After imputation was completed, several candidate socioeconomic indices were constructed. The components of each were either the 12 characteristics described above including the age-specific unemployment and education rates or the 7 characteristics where the age-specific rates were reduced to a single unemployment principal component factor and a single education principal component factor. Two kinds of indices were examined:


1. indicators based upon a stepwise regression model using the prototype poor health status indicator as the dependent variable.
   
   
2. indicators based upon a principal components analysis.

Six Candidate Socioeconomic Indicators

See Table 2.

After careful consideration, the first principal component factor of six socioeconomic characteristics (SPASFLUE) was chosen as the index which best met the theoretical requirements.

Geographic Levels

The selected socioeconomic factor has been calculated at the following geographic levels:


1. Regional Health Authority (RHA)
   
2. Physician Service Area (PSA) (rural non-Winnipeg areas only)
   
3. Municipality Codes

The factor has not been calculated for the nine Winnipeg regions as these regions have been made obsolete by the new WHA regions (which are not currently fully defined).

Calculation of Socioeconomic Factor Index at a Geographic Level:


Step 1: Obtain municipality code level SEFI values and population values. We used the first principal component factor from the SAS PRINCOMP procedure (standardized to have mean 0 and variance 1) and population values from the MCHP population databases.

Step 2: Calculate the weighted provincial mean SEFI value using the appropriate population as the weight.

Step 3: Calculate the weighted geographic level mean values of the municipality code level SEFI values weighted by population.

Step 4: Centre the geographic level values by subtracting the weighted provincial mean.

Step 5: Standardize the geographic level values by dividing by the (un-weighted) standard deviation of the geographic level values.

NOTE: This method assumes that the geographic level of interest is fully definable by municipality code.

Comparison with Direct Adjusted Premature Mortality Rate and Socioeconomic Risk Index (SERI)

• Table 3: 1986 Census SEFI by Regional Health Authority
  
  
• Table 4: 1991 Census SEFI by Regional Health Authority
  
  
• Table 5: 1996 Census SEFI by Regional Health Authority

Principal Components Coefficients for Index

• Appendix 1: Principal Component Coefficients for Unemployment Index
  
  
• Appendix 2: Principal Component Coefficients for Education Index
  
  
• Appendix 3: Principal Component Coefficients for Socioeconomic Factor Index