[Undernutrition and sarcopenic obesity according to the GLIM criteria phenotype in elderly patients with diabetes].

OBJECTIVE: To evaluate the frequency of malnutrition and sarcopenic obesity in elderly patients with diabetes according to the Global Leadership Initiative on Malnutrition (GLIM) phenotypes. METHODS: The subjects were outpatients with diabetes who were ≥65 years of age and were managed at Ise Red Cross Hospital. Undernutrition was assessed and categorized into the following GLIM criteria phenotypes: (1) no undernutrition, (2) undernutrition (weight loss or low body mass index [BMI]/no low appendicular skeletal muscle mass index [ASMI]), (3) undernutrition (no weight loss or no low BMI/low ASMI), and (4) undernutrition (weight loss or low BMI/low ASMI). Sarcopenia was diagnosed according to the definition of the Asian Working Group for Sarcopenia 2019, and obesity was diagnosed based on the body fat percentage. RESULTS: In total, 490 patients were included in the analysis. The frequency of undernutrition was 29.0%, and the frequency of undernutrition according to the GLIM criteria phenotypes was as follows: weight loss or low BMI/no low ASMI group, 10.6%; no weight loss and no low BMI/low ASMI group, 9.8%; and weight loss or low BMI/low ASMI group, 8.6%. The frequency of sarcopenic obesity was 7.3%, with the majority of cases found in the no weight loss or no low BMI/low ASMI groups. CONCLUSION: The frequency of undernutrition and sarcopenic obesity in elderly patients with diabetes, according to the GLIM phenotypes, was revealed. It is important to pay attention not only to weight loss and low BMI, but also to undernutrition and sarcopenic obesity with reduced skeletal muscle mass when diagnosing undernutrition in elderly diabetic patients.

Association of mean corpuscular volume with sarcopenia and visceral obesity in individuals without anemia.

AIMS/INTRODUCTION: Sarcopenia and visceral obesity are major global public health issues, and higher mean corpuscular volume (MCV) levels are related to adverse outcomes. Nevertheless, no study has determined the association between MCV and body composition. Therefore, we evaluated the association between MCV levels and trunk muscle quality, muscle quantity and visceral fat area. MATERIALS AND METHODS: In our cross-sectional study, we investigated 702 middle-aged Japanese individuals without anemia and with normal MCV levels who underwent physical checkups. The cross-sectional area of skeletal muscle or visceral fat was analyzed by computed tomography. RESULTS: In the adjusted model, the MCV was independently associated with the visceral fat area index (ß = -0.107, P = 0.0007), total skeletal muscle index (ß = 0.053, P = 0.0341) and total skeletal muscle density (ß = 0.099, P = 0.0012). MCV as a continuous variable was related to the prevalence of sarcopenia (odds ratios [OR] 0.93, 95% confidence intervals (CI) 0.88-0.98, per 1.0 fL increment; P = 0.0097) and visceral obesity (OR 0.91, 95% CI 0.86-0.97, per 1.0 fL increment; P = 0.0046). The highest MCV quartile was independently associated with the prevalence of sarcopenia (OR 0.48, 95% CI 0.27-0.83; P = 0.0089) and visceral obesity (OR 0.49, 95% CI 0.27-0.88; P = 0.0170), compared with the lowest quartile. CONCLUSIONS: In individuals without anemia and with normal MCV levels, a lower MCV was associated with unfavorable body composition, including lower muscle quality, lower muscle quantity, sarcopenia and visceral obesity.