We evaluate the accuracy of whole body muscle mass (WBMM) and appendicular skeletal muscle mass (ASMM) assessed by bioelectrical impedance analysis (BIA) using an InBody770 machine (InBody, Seoul, Korea) referenced to dual-energy X-ray absorptiometry (DXA) in 507 people (mean age 63.7 ± 10.8 years, body mass index (BMI) 25.2 ± 3.5 kg/m²). Mean WBMMs measured by BIA and DXA were 49.3 ± 6.6 kg and 46.8 ± 6.5 kg in men and 36.1 ± 4.7 kg and 34.0 ± 4.8 kg in women, respectively. The respective effect sizes and 95% confidence intervals (CIs) for the difference were 2.49 (2.22–2.76) for men, and 2.12 (1.91–2.33) for women. Mean ASMMs measured by BIA and DXA were 22.1 ± 3.3 kg and 19.9 ± 3.2 kg in men, and 15.3 ± 2.5 kg and 13.5 ± 2.2 kg in women, respectively. The respective effect sizes and 95% CIs for the difference were 2.26 (2.10–2.41) for men and 1.75 (1.65–1.87) for women. The BIA clearly overestimated WBMM by 2.28 kg and ASMM by 1.97 kg compared with DXA. Using BMI, gender, and fat percentage, we derive equations that improved the residuals to <2 kg between methods from 38.29% to 85.91% for WBMM and 52.78% to 97.02% for ASMM.

We evaluated the concordance between visceral fat area (VFA) estimated by bioelectrical impedance analysis (BIA) or computed tomography (CT) in Korean subjects with a wide range in age and body mass index (BMI). In 1006 individuals (mean age 55.2 ± 11.8 (19–87) years, mean BMI 26.0 ± 3.5 (17–46) kg/m², 48.9% men), VFA quantified by CT was compared with VFA using multifrequency BIA machines within 15 days. Concordance rates were compared by age or BMI using correlation analysis, Bland-Altman plots, and intraclass correlation coefficient (ICC). Using BIA data, we established a regression formula to reflect CT-VFA. The mean VFAs by CT and BIA were 131.9 ± 57.3 cm² and 110.5 ± 33.9 cm², respectively (r = 0.605, p < 0.001). The mean difference was 21.4 ± 45.6 cm², tending to increase with BMI. In women with BMI <25 kg/m² or age <50 years, the VFAs by BIA were similar to those by CT (ICC = 0.496 in BMI <25 kg/m² and ICC = 0.638 in age <50 years). However, the difference was greater in men with BMI ≥25 kg/m² or age ≥50 years. Applying our formula, the difference between estimations decreased to 0.2 ± 38.2cm². VFA estimated by BIA correlated well with that by CT, but a more accurate formula is needed to match CT data, particularly in older men or subjects with a high BMI.

Background: Liver function tests (LFTs) can be affected by many factors and the proposed effects of coffee on LFT require a comprehensive evaluation. The aim of this study was to elucidate whether drinking coffee, smoking, or drinking alcohol have independent effects on LFTs in Korean health-check examinees. Methods: We used the responses of 500 health-check examinees, who had participated in a self-administered questionnaire survey about coffee, alcohol drinking, and smoking habits. Results: Coffee consumption was closely related to male gender, high body mass index (BMI), alcohol drinking, and smoking. On univariable and multivariable analyses, drinking coffee lowered serum levels of total protein, albumin, and aspartate aminotransferases (AST). On multivariable analyses, smoking raised serum γ-glutamyl transferase (GGT) level and decreased serum protein and albumin levels, while alcohol drinking raised GGT level after adjustment for age, gender, regular medication, BMI, coffee and alcohol drinking amounts, and smoking. Conclusions: Coffee consumption, smoking, and alcohol drinking affect the individual components of LFT in different ways, and the above 3 habits each have an impact on LFTs. Therefore, their effects on LFTs should be carefully interpreted, and further study on the mechanism of the effects is warranted.

Lee JO, et al. J Korean Med Sci. 2014 Feb;29(2):224-229. http://dx.doi.org/10.3346/jkms.2014.29.2.224

Background: Hepatitis E virus (HEV) has emerged as an important cause of epidemic and sporadic acute viral hepatitis worldwide. This study investigated the seroprevalence of anti-HEV in a Korean population and compared the performance of two commercially available anti-HEV assays. Methods: A total 147 health-check examinees were randomly sampled as matched to the age- and sex- adjusted standard population based on the Korean National Census of 2007. Serum immunoglobulin G anti-HEV was determined by using the Genelabs assay (Genelabs, Singapore) and the Wantai assay (Wantai, Beijing, China). Results: The overall anti-HEV seroprevalence was 23.1% (95% CI, 16.1-30.1%) using the Wantai assay and 14.3% (95% CI, 8.3-20.3%) using the Genelabs assay. Only 12 samples (8.1%) were positive for anti-HEV as measured by both assays; agreement between the two assays was poor (kappa value of 0.315). The anti-HEV seroprevalence increased with age from 2% and 3% in the people younger than 20-years-of-age to 34.6% and 42.3% in those over 59-years-of-age by the Genelabs and Wantai assay, respectively. Conclusions: The HEV seroprevalence in Korean population is about 20% overall, with seroprevalence increasing in this population with increasing age. There was poor concordance in the results of the Genelabs and Wantai assays, which warrants further study concerning a reliable diagnostic test for the diagnosis of hepatitis E.