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Studies investigating the prevalence, cause, and consequence of multiple sclerosis (MS) fatigue typically use single measures that implicitly assume symptom-stability over time, neglecting information about if, when, and why severity fluctuates. We aimed to examine the extent of moment-to-moment and day-to-day variability in fatigue in relapsing-remitting MS and healthy individuals, and identify daily life determinants of fluctuations. Over 4 weekdays, 76 participants (38 relapsing-remitting MS; 38 controls) recruited from multiple sites provided real-time self-reports six times daily (n = 1661 observations analyzed) measuring fatigue severity, stressors, mood, and physical exertion, and daily self-reports of sleep quality. Fatigue fluctuations were evident in both groups. Fatigue was highest in relapsing-remitting MS, typically peaking in late-afternoon. In controls, fatigue started lower and increased steadily until bedtime. Real-time stressors and negative mood were associated with increased fatigue, and positive mood with decreased fatigue in both groups. Increased fatigue was related to physical exertion in relapsing-remitting MS, and poorer sleep quality in controls. In relapsing-remitting MS, fatigue fluctuates substantially over time. Many daily life determinants of fluctuations are similar in relapsing-remitting MS and healthy individuals (stressors, mood) but physical exertion seems more relevant in relapsing-remitting MS and sleep quality most relevant in healthy individuals.
Background: Understanding which factors influence dietary intake, particularly in daily life, is crucial given the impact diet has on physical as well as mental health. However, a factor might influence whether but not how much an individual eats and vice versa or a factor’s importance may differ across these two facets. Distinguishing between these two facets, hence, studying dietary intake as a dual process is conceptually promising and not only allows further insights, but also solves a statistical issue. When assessing the association between a predictor (e.g. momentary affect) and subsequent dietary intake in daily life through ecological momentary assessment (EMA), the outcome variable (e.g. energy intake within a predefined time-interval) is semicontinuous. That is, one part is equal to zero (i.e. no dietary intake occurred) and the other contains right-skewed positive values (i.e. dietary intake occurred, but often only small amounts are consumed). However, linear multilevel modelling which is commonly used for EMA data to account for repeated measures within individuals cannot be applied to semicontinuous outcomes. A highly informative statistical approach for semicontinuous outcomes is multilevel two-part modelling which treats the outcome as generated by a dual process, combining a multilevel logistic/probit regression for zeros and a multilevel (generalized) linear regression for nonzero values. Methods: A multilevel two-part model combining a multilevel logistic regression to predict whether an individual eats and a multilevel gamma regression to predict how much is eaten, if an individual eats, is proposed. Its general implementation in R, a widely used and freely available statistical software, using the R-package brms is described. To illustrate its practical application, the analytical approach is applied exemplary to data from the Eat2beNICE-APPetite-study. Results: Results highlight that the proposed multilevel two-part model reveals process-specific associations which cannot be detected through traditional multilevel modelling. Conclusions: This paper is the first to introduce multilevel two-part modelling as a novel analytical approach to study dietary intake in daily life. Studying dietary intake through multilevel two-part modelling is conceptually as well as methodologically promising. Findings can be translated to tailored nutritional interventions targeting either the occurrence or the amount of dietary intake.