Association between fibromyalgia syndrome clinical severity and body composition. A principal component analysis

Introduction: The type of body composition modulates the severity of some musculoskeletal conditions, in fibromyalgia syndrome (FMS), this type of association remains relatively unexplored. Objective: To analyze the association between the type of body composition and FMS using Principal Component Analysis (PCA). The FMS clinical outcome measures were: Symptom Severity Scale (SSS), Widespread Pain Index (WPI; and Fibromyalgia Impact Questionnaire (FIQ). Methods: Forty-three women with FMS (ACR 2010 criteria) were clinically and anthropometrically evaluated. The anthropometric data were integrated into two indicators using a PCA methodology (PCA-Fat and PCA-muscle). Additionally, the patients were classified into high and low categories for each clinical indicator, which were used as dependent variables in binomial logistic regression (BLR) models. Results: We found a positive correlation between PCA-Fat with WPI (r = 0.326, P = .043) and FIQ (r = 0.325, P = .044), and negative correlation (r = −0.384, P = .013) between PCA-muscle and SSS. In the BLR analysis, PCA-Fat was a significant predictor for high WPI (OR = 2.477, P = .038); while for high SSS, PCA-muscle (OR = 0.303, P = .009) was an inversely significant predictor. Conclusions: The results suggest that the volume of fat mass can negatively modulate the severity of FMS. We propose that the evaluation of body composition should be a basic element for the clinical approach of patients with FMS.