The natural history of chronic pain in the community: a better prognosis than in the clinic?

J Rheumatol. 1996 Sep;23(9):1617-20.

Abstract

Objective: To evaluate the predictors of improvement at 2 years in subjects with chronic widespread pain ascertained from a community survey.

Methods: As part of a community based epidemiological survey on the occurrence of pain, 141 subjects (age range 24-74 years; 44 men, 97 women) were selected for more detailed assessment. Followup information on pain experience was collected at a median of 27 months (range 15-35). Subjects were categorized according to whether they had no pain, chronic widespread pain (according to the American College of Rheumatology criteria), or regional pain, both at initial assessment and followup. In addition, subjects were examined at both time periods for tender points.

Results: Of those with chronic widespread pain at initial assessment, 35% still had chronic widespread pain at followup, 50% regional pain, and 15% no pain. Of those originally with regional pain, 65% still had regional pain, 19% chronic widespread pain, and 16% no pain at followup. Logistic regression analysis was conducted to examine factors among those with chronic widespread pain associated with still having these symptoms at followup. Female sex, older age, leaving school at a young age, high tender point count, high levels of fatigue, or additional physical or psychological symptoms were all associated with symptoms being less likely to resolve.

Conclusion: Chronic widespread pain in the community has a generally good prognosis. However, those with additional symptoms associated with the fibromyalgia syndrome were more likely still to have chronic widespread pain 2 years later.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Chronic Disease
  • Female
  • Fibromyalgia / physiopathology
  • Follow-Up Studies
  • Humans
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Pain / physiopathology*
  • Regression Analysis
  • Risk Factors