Quality of life in patients with multiple sclerosis: the impact of depression, fatigue, and disability

Int J Rehabil Res. 2011 Dec;34(4):290-8. doi: 10.1097/MRR.0b013e32834ad479.


Aim: The aim of this study was to assess the quality of life (QoL) in patients with multiple sclerosis (MS), and to evaluate its association with disability and psychosocial factors especially depression and fatigue.

Methods: Demographic characteristics, education level, disease severity, and disease duration were documented for each patient. QoL, fatigue level, cognitive status, and depression level of patients were assessed by Multiple Sclerosis Quality of Life-54, Fatigue Severity Scale, Mini Mental State Scale, and Beck Depression Inventory, respectively.

Results: Seventy-nine patients with MS were included in the study. There was a moderate degree of impairment in the QoL scores of MS patients. The most affected parts of QoL were included: role limitation-related physical and emotional problems and physical and social functions. Both physical and mental health components of QoL showed a positive correlation with the educational level and employment status; a negative correlation with the level of disability, fatigue, and depression. Depression, disability level, and fatigue were the strongest variables associated with QoL, and the most important predictor of QoL was depression.

Conclusion: Our results have shown that both physical and mental health components of QoL were negatively affected by MS. The most important predictor of QoL was depression followed by disability and fatigue. To improve the QoL for MS patients, in addition to physical disability, the influences of depression and fatigue on QoL should be taken into consideration.

MeSH terms

  • Adult
  • Depression / psychology*
  • Disabled Persons / psychology*
  • Educational Status
  • Employment
  • Fatigue / psychology*
  • Female
  • Health Status
  • Humans
  • Male
  • Mental Health
  • Multiple Sclerosis / psychology*
  • Psychiatric Status Rating Scales
  • Quality of Life*
  • Regression Analysis
  • Surveys and Questionnaires