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

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.