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Redefining overweight and obesity in rheumatoid arthritis patients
  1. Antonios Stavropoulos-Kalinoglou (as{at}wlv.ac.uk)
  1. University of Wolverhampton, United Kingdom
    1. Giorgos S Metsios (gm{at}wlv.ac.uk)
    1. University of Wolverhampton, United Kingdom
      1. Yiannis Koutedakis (y.koutedakis{at}pe.uth.gr)
      1. University of Thessaly, Greece
        1. Alan M Nevill (a.m.nevill{at}wlv.ac.uk)
        1. University of Wolverhampton, United Kingdom
          1. Karen M J Douglas (karen.douglas{at}dgoh.nhs.uk)
          1. Dudley Group of Hospitals, United Kingdom
            1. Athanasios Jamurtas (ajamurt{at}pe.uth.gr)
            1. University of Thessaly, Greece
              1. Jet JCS Veldhuijzen van Zanten (veldhujj{at}bham.ac.uk)
              1. University of Birmingham, United Kingdom
                1. Mourad Labib (mourad.labib{at}dgoh.nhs.uk)
                1. Dudley Group of Hospitals, United Kingdom
                  1. George Demetrios Kitas (g.d.kitas{at}bham.ac.uk)
                  1. Dudley Group of Hospitals, United Kingdom

                    Abstract

                    Objectives: To assess whether body mass index (BMI) and body fat (BF) differ between RA patients, patients with non-inflammatory arthritis (Osteoarthritis – OA) and healthy individuals, and whether disease-specific measures of adiposity are required to accurately reflect BF in these groups.

                    Methods: A total of 641 individuals were assessed for BMI (kg/m2) and BF (bioelectrical impedance). Of them, 299 [174 RA, 43 OA and 82 healthy controls (HC)] formed the observation group and 342 (all RA) the validation group. RA disease characteristics were collected.

                    Results: ANOVA revealed significant differences between disease groups for BMI (p<0.05) and BF (p<0.001). ANCOVA showed that age accounted for the differences in BMI (F1,294 = 5.10, p<0.05); age (F1,293 = 22.43, p<0.001), gender (F1,293 = 380.90, p<0.001) and disease (F2, 293 = 18.7, p<0.001) accounted for the differences in BF. For a given BF, patients with RA exhibited BMI levels reduced by 1.83kg/m2 (p<0.001) compared to HC; there were no significant differences between OA and HC. A predictive model for BF was developed (R2=0.769, p<0.001) and validated using Limits of Agreement Analysis against measured BF in the validation group (95%LIMAG = 6.17; CV = 8.94).

                    Conclusions: In individuals with RA, BMI cut-off points should be reduced by 2 kg/m2 (i.e. to 23 kg/m2 for overweight and 28 kg/m2 for obesity). The equation developed can be used to accurately predict body fat from BMI in RA patients. These findings may be important in the context of the cardiovascular comorbidity of RA.

                    • bioelectrical impedance
                    • body composition
                    • body mass index
                    • cardiovascular risk
                    • rheumatoid arthritis

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