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140819 - Comorbidities contribute substantially - Final author version.pdf (777.09 kB)

Comorbidities contribute substantially to the severity of common multiple sclerosis symptoms

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Background: More research is needed to understand the contribution of comorbidities to MS symptomatology.

Objectives: To examine the dose-response relationship between the number of comorbidities and severity of MS symptoms and to assess the relative contribution of comorbidity groups and individual comorbidities to the severity of each symptom.

Methods: We surveyed 1223 participants of the Australian MS Longitudinal Study for the presence of 30 comorbidities and the severity of 13 MS symptoms (0-10 scale). The associations between comorbidities and symptoms were assessed using negative binomial regression. The relative contributions of comorbidities to the severity of symptoms were assessed using general dominance analysis.

Results: Higher number of comorbidities was most strongly associated with a higher severity of pain and feelings of anxiety and depression (ratios of means ≥ 0.12 per comorbidity increase). Comorbidities explained between 3.7% (spasticity) and 22.0% (feelings of anxiety) of the total variance of symptom severity. Mental health and musculoskeletal disorders contributed most strongly to the severity of the most common symptoms in MS.

Conclusions: Our findings support that early recognition and optimal management of comorbidities, particularly of mental health and musculoskeletal disorders, could have a positive impact on the severity of symptoms of people with MS.

History

Publication title

Journal of Neurology

Issue

September

Pagination

1-10

ISSN

0340-5354

Department/School

Menzies Institute for Medical Research

Publisher

Dr Dietrich Steinkopff Verlag

Place of publication

Po Box 10 04 62, Darmstadt, Germany, D-64204

Rights statement

© Springer-Verlag GmbH Germany, part of Springer Nature 2020. Post-prints are subject to Springer Nature re-use terms

Repository Status

  • Restricted

Socio-economic Objectives

Clinical health not elsewhere classified

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