Inter-relationship of stated diet adherence and relapse, disability, and fatigue in multiple sclerosis
- Research Opportunity
- PhD, Masters by Research, Honours
- Number of Honour Places Available
- Medicine and Radiology
- Royal Melbourne Hospital
|Dr Steve Simpson, Jr.||firstname.lastname@example.org||Personal web page|
|A/Professor Tracey Weilandemail@example.com||Personal web page|
Multiple sclerosis (MS) is a progressive, autoimmune, demyelinating condition of the central nervous system, manifesting in sensory, motor and/or cognitive dysfunction. Given its onset is typically in the prime years of life – often in the 20s – it has devastating impacts on the quality of life and independent living of the patients so affected.
Diet quality, and associated qualities like BMI and dyslipidaemia, have been implicated in MS onset and progression. Accordingly, a number of diets have been proposed which may improve clinical course in MS, including vegetarian, paleo, non-dairy, and other diets. People with MS, seeking to find some way to improve their disease, frequently attempt these diets but with varying degrees of adherence.
This project, making use of HOLISM longitudinal cohort study (n=1,401 at 2.5-yr follow-up, n=952 at 5-yr follow-up), will assess the relationship of stated diet adherence to several prominent MS-specific diets reported at the 5-yr timepoint with clinical outcomes in MS, including relapse rate, disability as measured by the Patient Determined Disease Steps and fatigue as measured by the Fatigue Severity Scale. By using longitudinally measured diet quality, this study will examine the prospective relationship of diet quality with these core elements of clinical course in MS, with a goal to determine whether diet associations with clinical course reflect causal pathways or reverse causality. Understanding the potential beneficial impacts of diet adherence with clinical course will be of great import in MS, both in terms of potential beneficial effects, as well as appreciating any potential negative effects.
Analysis methods to be employed include linear regression, multilevel mixed-effects linear regression, log-binomial regression, and/or Poisson regression, including univariable and multivariable models, as well as potential inter-group assessment of interaction by sex, age, MS course, or others as appropriate.
Faculty Research Themes
School Research Themes
PhD, Masters by Research, Honours
Students who are interested in joining this project will need to consider their elegibility as well as other requirements before contacting the supervisor of this research
For further information about this research, please contact a supervisor.
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