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Health-related quality of life in Canadian adolescents and young adults: normative data using the SF-36
Wilma M Hopman1, Claudie Berger, Lawrence Joseph
1Clinical Research Centre, Kingston General Hospital, Angada 4, Room 5-426, 76 Stuart Street, Kingston ON K7L 2V7. hopmanw@kgh.kari.net
Objectives:
Normative data for the SF-36 measure of health-related quality of life (HRQOL) exist for those over 25 years of age, based on data from the population-based Canadian Multicentre Osteoporosis Study (CaMos). CaMos recently recruited a sample of young Canadians aged between 16 and 24 years. The purpose of this study was to develop normative SF-36 data for this age group.
Methods:
After direct standardization to the Canadian population, means, standard deviations (SD), 95% confidence intervals and percentage at floor and ceiling were produced for the eight domain and two summary scores of the SF-36. Domains are scored from 0 (poor) to 100 (excellent). Summary scores are standardized to a mean of 50, with scores over 50 representing better than average and below 50 poorer than average function. Separate analyses were completed for men and women, and for those 16-19 years and 20-24 years.
Results:
The 1,001 community-based participants consisted of 474 men and 527 women from nine CaMos centres across Canada. Mean Physical Component Summary scores were 53.9 (SD = 6.9) and 53.3 (SD = 5.7) for young men and women, respectively. The equivalent Mental Component Summary scores were 49.3 (SD = 9.7) and 48.8 (SD = 8.9). In general, men scored somewhat higher than women, and younger (16-19 years) women scored higher than older (20-24 years) women, although the differences were small.
Conclusion:
HRQOL is good in this cohort of young Canadians. Both men and women scored somewhat better on physically than mentally oriented domains. In general, Canadian scores were similar to those of the US, while a comparable Swedish sample scored higher than both countries on most domains. Results underscore the importance of taking country, age and gender into consideration when using normative data.
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