OBJECTIVES: To assess whether body mass index (BMI) and body fat (BF) differ between rheumatoid arthritis (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: 641 individuals were assessed for BMI (kg/m(2)) 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 (F(1,294) = 5.10, p<0.05); age (F(1,293) = 22.43, p<0.001), sex (F(1,293) = 380.90, p<0.001) and disease (F(2, 293) = 18.7, p<0.001) accounted for the differences in BF. For a given BF, patients with RA exhibited BMI levels reduced by 1.83 kg/m(2) (p<0.001) compared to HC; there were no significant differences between OA and HC. A predictive model for BF was developed (R(2) = 0.769, p<0.001) and validated using limits of agreement Analysis against measured BF in the validation group (95%LIM(AG) = 6.17; CV = 8.94). CONCLUSIONS: In individuals with RA, BMI cut-off points should be reduced by 2 kg/m(2) (that is, to 23 kg/m(2) for overweight and 28 kg/m(2) for obesity). The equation developed can be used to accurately predict BF from BMI in RA patients. These findings may be important in the context of the cardiovascular comorbidity of RA.
OBJECTIVES: To assess whether body mass index (BMI) and body fat (BF) differ between rheumatoid arthritis (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: 641 individuals were assessed for BMI (kg/m(2)) 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 (F(1,294) = 5.10, p<0.05); age (F(1,293) = 22.43, p<0.001), sex (F(1,293) = 380.90, p<0.001) and disease (F(2, 293) = 18.7, p<0.001) accounted for the differences in BF. For a given BF, patients with RA exhibited BMI levels reduced by 1.83 kg/m(2) (p<0.001) compared to HC; there were no significant differences between OA and HC. A predictive model for BF was developed (R(2) = 0.769, p<0.001) and validated using limits of agreement Analysis against measured BF in the validation group (95%LIM(AG) = 6.17; CV = 8.94). CONCLUSIONS: In individuals with RA, BMI cut-off points should be reduced by 2 kg/m(2) (that is, to 23 kg/m(2) for overweight and 28 kg/m(2) for obesity). The equation developed can be used to accurately predict BF from BMI in RApatients. These findings may be important in the context of the cardiovascular comorbidity of RA.
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