Identification and Prediction of Fatigue Trajectories in People With Rheumatoid Arthritis

Objective We aimed to identify groups demonstrating different long‐term trajectories of fatigue among people with rheumatoid arthritis and determine baseline predictors for these trajectories. Methods Our study included 2741 people aged 18 to 75 years who were independent in daily living. Data were collected from the Swedish Rheumatology Quality Register and questionnaires at baseline, 14 months, and 26 months. Fatigue was rated on a 100‐mm visual analog scale. K‐means cluster analysis was used to identify fatigue trajectories. Multinomial logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals for potential predictors of trajectory membership. Results The mean age was 60 years, 73% of participants were female, and the mean baseline fatigue level was 39. Three distinct fatigue trajectories were identified, representing mild (mean 15, n = 1024), moderate (mean 41, n = 986), and severe (mean 71, n = 731) fatigue. Consistent patterns indicated that poorer health perception (ORs 1.68‐18.40), more pain (ORs 1.38‐5.04), anxiety/depression (ORs 0.85‐6.19), and activity limitation (ORs 1.43‐7.39) were associated with more severe fatigue. Those in the severe fatigue group, compared with those in the mild fatigue group, were more likely to be college educated than university educated (OR 1.56) and less likely to maintain physical activity (OR 0.54). Those in the severe fatigue group, compared with those in both the moderate (OR 0.67) and mild (OR 0.59) fatigue groups, were less likely to have one additional adult in the household. Conclusion This study identified stable fatigue trajectories, predicted by health perception, pain, anxiety/depression, activity limitation, educational level, maintained physical activity, and household composition. Interventions aimed at reducing these disabilities and supporting physical activity behaviors may help reduce fatigue.