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Objective:  This study was carried out to investigate the role and necessity of human body composition analysis in assessing the nutritional status of initially diagnosed Crohn's disease (CD) patients.   Methods:  A total of 47 initially diagnosed CD patients were recruited. The skeletal muscle mass index (SMI), fat-free mass index (FFMI), body fat mass, body fat percent, visceral fat area (VFA), and body cell mass were determined with the Biospace Inbody S10 composition analyzer.   Results:  In 47 patients with initially diagnosed CD, SMI could determine the muscular mass reduction that could not be determined by the body mass index (BMI) (35.3%), albumin (ALB) (65.6%), nutrition risk screening (NRS)2002 (25.0%), and Patient-Generated Subjective Global Assessment (PG-SGA) (55.6%). FFMI could determine the malnutrition that could not be determined by the BMI (58.8%), albumin (90.6%), NRS2002 (50.0%), and PG-SGA (55.6%). VFA in the fistulizing CD patients was significantly higher than in the stricturing and non-fistulizing, non-stricturing patients ( P  < 0.05). SMI and BMI had the same performance ( P  = 1.000) and general consistence (Kappa = 0.487,  P  = 0.001) in the assessment of malnutrition; SMI and ALB had different performance ( P  < 0.001) and inconsistence was noted (Kappa = 0.069,  P  = 0.489) in the assessment of malnutrition; the results of the nutrition assessment were different between SMI and NRS2002 ( P  = 0.002), and inconsistence was observed (Kappa = 0.190,  P  = 0.071). SMI and PG-SGA had the same performance in the assessment of nutrition ( P  = 0.143), but there was inconsistence (Kappa = 0.099,  P  = 0.464). FFMI and BMI had general consistence in the assessment of malnutrition (Kappa = 0.472,  P  < 0.001), but the positive rate determined by FFMI (85.1%) was markedly higher than that by BMI (63.8%) ( P  = 0.002). FFMI and ALB had different performance in the assessment of malnutrition ( P  < 0.001) and there was inconsistence (Kappa = −0.008,  P  = 0.877). FFMI and NRS2002 had the same performance in the assessment of malnutrition ( P  = 0.453), but the consistence was poor (Kappa = 0.286,  P  = 0.039). The results determined by SMI and PG-SGA were consistent ( P  = 0.727), but the consistence was poor (Kappa = 0.399,  P  = 0.006).   Conclusion:  Human body composition analysis can identify the patients with muscular mass reduction that cannot be identified by commonly used nutrition assessment scales/parameters. Thus, it is helpful for the assessment of disease severity and also important for the nutrition assessment in CD patients.

frontiers in medicine

Role of Human Body Composition Analysis and Malnutrition Risk Questionnaire in the Assessment of Nutritional Status of Patients With Initially Diagnosed Crohn's Disease