Health related quality of life in a population sample with arthritis

J Rheumatol. 1999 Sep;26(9):2029-35.

Abstract

Objective: To determine the prevalence and health related quality of life of a community sample of people with arthritis and compare it with persons with other chronic diseases and the healthy population in South Australia.

Methods: A representative population survey by trained interviewers in autumn 1995 using a multi-stage, systematic, clustered area sample of 4200 urban and country households. There were 3001 (73.6%) respondents aged 15 or over. Subjects were asked, "Have you ever been told by a doctor that you have arthritis?" and "What type?", in addition to the Medical Outcome Survey Short Form-36 (SF-36) health status survey.

Results: Medically confirmed arthritis was self-reported in 666 (22.1%) as osteoarthritis (OA) (8.6%), rheumatoid arthritis (RA) (4.0%), and other, or unspecified arthritis (9.6%). People with arthritis were more likely to be female, aged, and of lower socioeonomic status. SF-36 scores were compared to nonarthritic subjects and adjusted for differences in age, sex, and occupational status. Scores were significantly lower for respondents with arthritis, compared with the rest of the population across all subscales of the SF-36 (p<0.05). This was most marked in the subscales measuring physical function and pain.

Conclusion: Self-reported arthritis is common in the South Australian population, particularly in those aged over 65 years. Arthritis has a major impact on the health related quality of life in the community setting.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Age Distribution
  • Aged
  • Aged, 80 and over
  • Arthritis / classification*
  • Arthritis / epidemiology*
  • Arthritis / psychology
  • Australia / epidemiology
  • Case-Control Studies
  • Chronic Disease
  • Female
  • Health Surveys
  • Humans
  • Male
  • Middle Aged
  • Prevalence
  • Quality of Life*
  • Reference Values
  • Risk Factors
  • Sampling Studies
  • Sex Distribution
  • Sickness Impact Profile*
  • Socioeconomic Factors