Academic journal article Canadian Journal of Public Health

Is There Regional Variation in the SF-36 Scores of Canadian Adults?

Academic journal article Canadian Journal of Public Health

Is There Regional Variation in the SF-36 Scores of Canadian Adults?

Article excerpt


Background: Canadian normative data for the Medical Outcomes Study 36-item short form (SF-36) have recently been published. However, there is evidence from other countries to suggest that regional variation in health-related quality of life (HRQOL) may exist. We therefore examined the SF-36 data from nine Canadian centres for evidence of systematic differences.

Methods: Bayesian hierarchical modelling was used to compare the differences in the eight SF-36 domains and the two summary component scores within each of the age and gender strata across the nine sites.

Results: Five domains and the two summary component scores showed little clinically important variation. Other than a small number of exceptions, there was little overall evidence of HRQOL differences across most domains and across most sites.

Interpretation: Our finding of only a few small differences suggests that there is no need to develop region-specific Canadian normative data for the SF-36 health survey.

The Medical Outcomes Study 36-item short form (SF-36)1,2 health survey has proven to be useful for comparing the relative burden of different diseases, as well as the efficacy of treatment interventions on quality of life.3 Moreover, it is increasingly being used in clinical trials research, reflecting a shift away from research that had a more narrow focus on clinical indicators such as morbidity and mortality, to a broader assessment of patient functioning and well-being.4

The recent publication of Canadian normative data for the SF-36 health surveys has allowed researchers and health care professionals to compare SF-36 data they have collected to age- and/or gender-- appropriate norms. While this marks a substantial improvement over comparisons with US normative data,1 there is also evidence to suggest that there may be regional variation in SF-36 scores in some countries.6 Within Canada, where both an English and a French version of the SF-36(7) have been used, there may also be differences according to language of form completion.8

The initiation of data collection for the Canadian Multicentre Osteoporosis Study (Cantos) in 1996 provided the opportunity to develop the age- and sex-adjusted norms for Canadians.5 Since these data were collected at nine centres across Canada, they can also be used to assess differences between the nine cities and surrounding regions. This will provide an opportunity to validate and confirm the usefulness of the normative data within all regions of Canada, as well as address the question of whether those living in various parts of Canada have similar health-related quality of life.


The Canadian Multicentre Osteoporosis Study (Cantos) is a prospective cohort study of 9,423 non-institutionalized randomly selected males and females aged 25 years and older. The sample is drawn from a 50-km radius of nine Canadian cities: Vancouver, Calgary, Saskatoon, Hamilton, Toronto, Kingston, Quebec City, Halifax and St. John's. Details of the study's purpose, methodology and sampling framework are presented elsewhere.5,9 Ethical approval for the study was obtained through the Review Boards of each participating centre, as well as at the coordinating centre in Montreal.

The SF-36 contains 36 items which, when scored, yield 8 domains, including physical functioning, role physical, role emotional, bodily pain, vitality, social functioning, mental health, and general health perceptions. A detailed description of these domains is available elsewhere.1,5 Summary scores for a Physical Component and a Mental Component can also be derived.2 All domains are scored on a scale from 0 to 100, with 100 representing the best possible health state.

The data were scored by means of the Medical Outcomes Trust scoring methodology.1,2 The data were age- and sex-- standardized to the Canadian population by weighting the total means based on the underlying population for each of the nine centres, using Statistics Canada data. …

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