Max Rady College of Medicine

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

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Concept Description

Last Updated: 2000-02-21

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)

Principal Components Coefficients for Index

Related concepts 

Related terms 

References 

  • Frohlich N, Mustard C. A regional comparison of socioeconomic and health indices in a Canadian province. Soc Sci Med 1996;42(9):1273-1281. [Abstract] (View)
  • Frohlich N, Carriere KC. Issues in Developing Indicators for Needs-Based Funding. Winnipeg, MB: Manitoba Centre for Health Policy and Evaluation, 1997. [Report] [Summary] (View)
  • Martens P, Frohlich N, Carriere K, Derksen S, Brownell M. Embedding child health within a framework of regional health: Population health status and sociodemographic indicators. Canadian Journal of Public Health 2002;93((Suppl)(2)):S15-S20. [Abstract] (View)
  • 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, Derksen S, Berthelot J, Wolfson MC, Roos LL, Carriere KC. Socioeconomic Gradients in Mortality and the Use of Health Care Services at Different Stages in the Life Course. Winnipeg, MB: Manitoba Centre for Health Policy and Evaluation, 1995. [Report] [Summary] (View)


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Manitoba Centre for Health Policy
Community Health Sciences, Max Rady College of Medicine,
Rady Faculty of Health Sciences,
Room 408-727 McDermot Ave.
University of Manitoba
Winnipeg, MB R3E 3P5 Canada

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