The factor structure of the SF-36 Health Survey in 10 countries: results from the IQOLA Project. International Quality of Life Assessment

J Clin Epidemiol. 1998 Nov;51(11):1159-65. doi: 10.1016/s0895-4356(98)00107-3.

Abstract

Studies of the factor structure of the SF-36 Health Survey are an important step in its construct validation. Its structure is also the psychometric basis for scoring physical and mental health summary scales, which are proving useful in simplifying and interpreting statistical analyses. To test the generalizability of the SF-36 factor structure, product-moment correlations among the eight SF-36 Health Survey scales were estimated for representative samples of general populations in each of 10 countries. Matrices were independently factor analyzed using identical methods to test for hypothesized physical and mental health components, and results were compared with those published for the United States. Following simple orthogonal rotation of two principal components, they were easily interpreted as dimensions of physical and mental health in all countries. These components accounted for 76% to 85% of the reliable variance in scale scores across nine European countries, in comparison with 82% in the United States. Similar patterns of correlations between the eight scales and the components were observed across all countries and across age and gender subgroups within each country. Correlations with the physical component were highest (0.64 to 0.86) for the Physical Functioning, Role Physical, and Bodily Pain scales, whereas the Mental Health, Role Emotional, and Social Functioning scales correlated highest (0.62 to 0.91) with the mental component. Secondary correlations for both clusters of scales were much lower. Scales measuring General Health and Vitality correlated moderately with both physical and mental health components. These results support the construct validity of the SF-36 translations and the scoring of physical and mental health components in all countries studied.

MeSH terms

  • Cross-Cultural Comparison
  • Europe / epidemiology
  • Factor Analysis, Statistical
  • Female
  • Health Status Indicators*
  • Humans
  • Male
  • Psychometrics
  • Quality of Life*
  • Surveys and Questionnaires