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.