Fatigue among children with a chronic disease: a cross-sectional study

Objective To determine: (1) which biological/lifestyle, psychological and/or social factors are associated with fatigue among children with a chronic disease and (2) how much each of these factors contributes to explaining variance in fatigue. Design and setting This was a cross-sectional study across two children's hospitals. Patients We included children aged 8-18 years who visited the outpatient clinic with cystic fibrosis, an autoimmune disease or postcancer treatment. Main outcome measures Fatigue was assessed using the PedsQL Multidimensional Fatigue Scale. Generic biological/lifestyle, psychological and social factors were assessed using clinical assessment tools and questionnaires. Multiple linear regression analyses were used to test the associations between these factors and fatigue. Finally, a multivariable regression model was used to determine which factor(s) have the strongest effect on fatigue. Results A total of 434 out of 902 children were included (48% participation rate), with a median age of 14.5 years; 42% were male. Among these 434 children, 21.8% were severely fatigued. Together, all biopsychosocial factors explained 74.6% of the variance in fatigue. More fatigue was uniquely associated with poorer physical functioning, more depressive symptoms, more pressure at school, poorer social functioning and older age. Conclusions Fatigue among children with a chronic disease is multidimensional. Multiple generic biological/lifestyle, psychological and social factors were strongly associated with fatigue, explaining 58.4%; 65.8% and 50.0% of the variance in fatigue, respectively. Altogether, almost three-quarters of the variance in fatigue was explained by this biopsychosocial model. Thus, when assessing and treating fatigue, a transdiagnostic approach is preferred, taking into account biological, psychological and social factors.

Automated summary

Fatigue among children with a chronic disease is multidimensional. Various generic biological/lifestyle, psychological, and social factors are strongly associated with fatigue, explaining 58.4%, 65.8%, and 50.0% of the variance in fatigue, respectively. Overall, almost three-quarters of the variance in fatigue can be explained by this biopsychosocial model.