Different factor loadings for SF36: the Strong Heart Study and the National Survey of Functional Health Status

J Clin Epidemiol. 2006 Feb;59(2):208-15. doi: 10.1016/j.jclinepi.2005.07.010. Epub 2005 Sep 30.

Abstract

Background: To increase our understanding of the psychometric characteristics and factor structure of the SF36 in older American Indian populations.

Methods: Between 1993 and 1995, SF36 data were collected from 3,488 Phase II participants of the Strong Heart Study (SHS) between the ages of 48 and 81. Comparison data were provided by an age- and gender-matched sample (n = 695) from the National Survey of Functional Health Status (NSFHS) conducted in 1989 and 1990.

Results: Generally, the basic psychometric analyses showed that the SF36 performed adequately in these older American Indians. Exploratory factor analyses indicated that a one-factor model best fit the data for both older groups. On the other hand, confirmatory factor analyses showed that a two-factor model with correlated factors provided a superior fit to the data than a one-factor model. An assumption of equivalent factor loadings for the SHS and NSFHS groups was untenable.

Conclusion: These analyses demonstrate that use of summary scores assuming a differentiated physical/mental functioning structure is likely improper in at least some populations. The SF36 provides an important opportunity to understand cultural differences in the conceptualization and measurement of health-related quality of life.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Validation Study

MeSH terms

  • Aged
  • Aged, 80 and over
  • Cardiovascular Diseases / ethnology
  • Cardiovascular Diseases / etiology*
  • Cardiovascular Diseases / physiopathology
  • Case-Control Studies
  • Cross-Cultural Comparison
  • Factor Analysis, Statistical
  • Female
  • Health Status Indicators*
  • Health Surveys
  • Heart / physiopathology
  • Humans
  • Indians, North American
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Psychometrics
  • Risk Factors
  • United States
  • White People