• Maria Cristina Gonzalez, Carla A Pastore, Silvana P Orlandi, and Steven B Heymsfield.
• Postgraduation Program on Health and Behavior, Catholic University of Pelotas, Pelotas, Brazil (MCG); the Nutrition College of Nutrition, Federal University of Pelotas, Pelotas, Brazil (CAP and SPO); the Pennington Biomedical Research Center, Baton Rouge, LA (SBH and MCG); and the Study Group on Body Composition and Nutrition, COCONUT (MCG, CAP, and SPO).
• Am. J. Clin. Nutr. 2014 May 1;99(5):999-1005.

BackgroundObesity, defined by body mass index (BMI), appears to have a paradoxical protective effect in several chronic diseases.ObjectiveWe investigated the obesity paradox in cancer patients by using body composition.DesignThe study was an observational study of 175 cancer patients assessed before chemotherapy. Obesity was defined as BMI (in kg/m(2)) ≥30 or fat mass index (FMI; fat mass divided by the square of height) ≥5.2 (men) and ≥8.2 (women) measured by using a bioelectrical impedance analysis. Low muscle mass (sarcopenia) was defined as fat-free mass index (fat-free mass divided by the square of height) <17.5 (men) and <15.1 (women).ResultsMost patients were women (65.7%) and had a mean (±SD) age of 56.9 ± 12.8 y. According to BMI criteria, 60% of patients were overweight or obese. The median survival time for overweight (2.64 y; range: 0.23-3.16 y) and obese (2.61 y; range: 0.26-3.20 y) patients was significantly higher than for patients with a normal (2.04 y; range: 0.06-3.05 y) or low (0.52 y; range: 0.19-0.98 y) BMI (P < 0.001). Sarcopenic patients had shorter survival, regardless of their FMI. Obesity predicted higher survival rates only when sarcopenia was absent. In a multivariate Cox regression model, sarcopenia was an independent predictor of higher mortality (HR: 5.19; 95% CI: 2.58, 10.43) after we controlled for BMI, age, and tumor stage.ConclusionsThe obesity paradox is present in cancer patients only when obesity is defined by BMI. Patients with sarcopenic obesity had the poorest prognosis. Cancer patients with high mortality risk can be identified by a body-composition assessment.

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