Fatigue and its association with sociodemographic variables among multiple sclerosis patients

Mult Scler. 2003 Oct;9(5):509-14. doi: 10.1191/1352458503ms943oa.

Abstract

Objective: To explore the relationship between fatigue, sociodemographic and clinical variables in a population of patients with multiple sclerosis (MS).

Rationale: There is a need to identify empirical relationships with possible antecedents of fatigue among patients with MS.

Methods: A mailed questionnaire designed to survey sociodemographic variables and the Fatigue Severity Scale (FSS) was mailed to 502 individuals from the population of patients with definite MS in the city of Oslo. A total of 368 (73%) responded. Clinical data were collected from the Oslo City MS-Registry.

Results: The prevalence of fatigue in this population was 60.1%. The FSS score showed a negative correlation with education (r = -0.15, P < 0.01) and a positive correlation with age (r = 0.20, P < 0.001) and time since disease onset (r = 0.11, P < 0.05). When controlled for gender, level of education and time since disease onset, the data showed a positive relationship between fatigue and age (P < 0.001) among patients with primary progressive (PP) disease. This relationship between age and fatigue was not found among patients with relapsing-remitting/secondary progressive (RR/SP) disease.

Conclusion: The negative relationship between level of formal education (FE) and fatigue among individuals with RR/SP disease suggests that behavioral factors may be among the antecedents of fatigue in this patient group. In contrast to normative data from the general population, our findings revealed no differences in fatigue related to gender Thus, this study supports the hypothesis that there are disease-specific antecedents of fatigue among patients with MS.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Educational Status
  • Fatigue / epidemiology
  • Fatigue / etiology*
  • Fatigue / psychology*
  • Female
  • Humans
  • Male
  • Multiple Sclerosis / complications*
  • Multiple Sclerosis / epidemiology
  • Multiple Sclerosis / psychology*
  • Predictive Value of Tests
  • Prevalence
  • Regression Analysis
  • Severity of Illness Index*
  • Surveys and Questionnaires