Seon Yeong Lee

Assessment methods in human body composition

Purpose of reviewThe present study reviews the most recently developed and commonly used methods for the determination of human body composition in vivo with relevance for nutritional assessment. Recent findingsBody composition measurement methods are continuously being perfected with the most commonly used methods being bioelectrical impedance analysis, dilution techniques, air displacement plethysmography, dual energy X-ray absorptiometry, and MRI or magnetic resonance spectroscopy. Recent developments include three-dimensional photonic scanning and quantitative magnetic resonance. Collectively, these techniques allow for the measurement of fat, fat-free mass, bone mineral content, total body water, extracellular water, total adipose tissue and its subdepots (visceral, subcutaneous, and intermuscular), skeletal muscle, select organs, and ectopic fat depots. SummaryThere is an ongoing need to perfect methods that provide information beyond mass and structure (static measures) to kinetic measures that yield information on metabolic and biological functions. On the basis of the wide range of measurable properties, analytical methods and known body composition models, clinicians and scientists can quantify a number of body components and with longitudinal assessment, can track changes in health and disease with implications for understanding efficacy of nutritional and clinical interventions, diagnosis, prevention, and treatment in clinical settings. With the greater need to understand precursors of health risk beginning in childhood, a gap exists in appropriate in-vivo measurement methods beginning at birth.

2014 clinical practice guidelines for overweight and obesity in Korea.

The dramatic increase in the prevalence of obesity and its accompanying comorbidities are major health concerns in Korea. Obesity is defined as a body mass index ≥25 kg/m2 in Korea. Current estimates are that 32.8% of adults are obese: 36.1% of men and 29.7% of women. The prevalence of being overweight and obese in national surveys is increasing steadily. Early detection and the proper management of obesity are urgently needed. Weight loss of 5% to 10% is the standard goal. In obese patients, control of cardiovascular risk factors deserves the same emphasis as weight-loss therapy. Since obesity is multifactorial, proper care of obesity requires a coordinated multidisciplinary treatment team, as a single intervention is unlikely to modify the incidence or natural history of obesity.

Relationship between insulin resistance and serum alanine aminotransferase as a surrogate of NAFLD (nonalcoholic fatty liver disease) in obese Korean children.

There has been increasing number of obese children who accompany obesity-related comorbidities. It has been known that nonalcoholic fatty liver disease (NAFLD) as one of obesity-related comorbidities is related with insulin resistance. So, we investigated the relation between insulin resistance and NAFLD, using serum alanine aminotransferase (ALT) as a surrogate of NAFLD among obese children in Korea. The study subjects were 909 obese children aged 9-12 years (boys 613, girls 296). Body mass index (BMI), waist circumference (WC), blood pressure, fasting blood glucose, fasting insulin, lipid profile were measured. ALT, liver enzyme was used as a surrogate of NAFLD and homeostasis model assessment of insulin resistance (HOMA-IR) was used as the index of insulin resistance. The prevalence of elevated serum ALT (>or=40 mg/dl) was 33.4% in boys, and 19.6% in girls respectively. In boys, ALT was correlated with BMI, waist circumference, total cholesterol, triglyceride, HDL-cholesterol, systolic and diastolic blood pressure, HOMA-IR, fasting serum insulin. Odds ratio for HOMA-IR against the elevated ALT (>or=40 mg/dl) was 1.061 (95% confidence interval, 1.020-1.103, P=0.003). In girls, ALT was correlated with BMI, waist circumference, total cholesterol, triglyceride, glucose, systolic and diastolic blood pressure, HOMA-IR, fasting serum insulin. Odds ratio for HOMA-IR against the elevated ALT (>or=40 mg/dl) was 1.042 (95% confidence interval, 0.998-1.088, P=0.063). Among obese Korean children, insulin resistance and ALT, lipid profile, BMI, WC, blood pressure showed significant correlation. Especially, in boys, higher ALT is founded to be independently associated with insulin resistance.

Obesity in Korean pre-adolescent school children: comparison of various anthropometric measurements based on bioelectrical impedance analysis

Objectives:To examine the relationships between body mass index (BMI), percentage-weight-for-height (PWH) and percentage body fat (PBF), and to compare their validity based on PBF with the BMI criteria of International Obesity Task Force (IOTF) for childhood obesity in Korean pre-adolescent school children.Design:Statistical comparative analysis for anthropometric measures.Subjects:Korean pre-adolescent children (438 boys and 454 girls, aged 8–12 years, mean BMI 19.5±3.4 kg/m2).Measurements:Body mass index and PWH were calculated as body size indices from height and weight. Hand-to-foot bioelectrical impedance analysis (BIA) was performed to obtain PBF values, with obese children defined as PBF above 35%. Sensitivity and specificity were displayed with the gold standard of PBF, and receiver operating characteristic (ROC) curves were used to assess the performance of BMI and PWH in detecting obesity.Results:The prevalence of obesity varied by the criteria: 18.8% by Korean BMI standards for 95 percentile, 11% by the IOTF-BMI 30 kg/m2 and 29.4% by Korean PWH cutoffs. Body mass index and PWH were significantly correlated with PBF after adjusting for age, 0.910 (P<0.01) and 0.915 (P<0.01), respectively. The sensitivity and specificity of the PWH cutoffs were 0.909 and 0.882, respectively. The local BMI 95 percentiles had lower sensitivity (0.714) and specificity (0.790). The IOTF-BMI definition showed much lower sensitivity (0.457) and higher specificity (0.990). The BMI cutoffs corresponding with the highest accuracy were smaller than IOTF-BMI 30 kg/m2 for all age groups in both boys and girls.Conclusion:The prevalence of obesity among Korean pre-adolescent children widely varied according to the diagnostic criteria applied. Universally recommended cutoffs for children by IOTF showed the lowest sensitivity among the criteria used, and may therefore underestimate obesity in this population.

Elevated serum gamma-glutamyltransferase is a strong marker of insulin resistance in obese children

Elevated levels of serum gamma-glutamyltransferase (GGT) levels have been found to predict the development of type 2 diabetes in adults. The role of GGT in insulin resistance (IR) among children is largely unknown. We investigated whether GGT among hepatic enzymes is independently associated with IR in obese Korean children. A total of 1308 overweight (above the 85th BMI percentile of Korean reference) boys (n = 822) and girls (n = 486), aged 9–15 years, were studied. Measures acquired included weight, height, percent body fat (BF%), waist circumference, blood pressure, blood glucose and insulin, C-reactive protein, total cholesterol, triglycerides, HDL-Cholesterol, GGT, aspartate aminotransferase (AST), and alanine aminotransferase (ALT). IR was calculated using the homeostasis model assessment (HOMA-IR). Serum GGT and ALT, but not AST, were positively correlated with HOMA-IR in boys (r = 0.222 for GGT; P < 0.05, r = 0.188 for ALT; P < 0.05) and girls (r = 0.292 for GGT; P < 0.05, r = 0.258 for ALT; P < 0.05). In multiple regression analysis for HOMA-IR as dependent variable, GGT (β = 0.068; P = 0.053 in boys, β = 0.145; P = 0.002 in girls) and ALT (β = 0.074; P = 0.034 in boys, β = 0.130; P = 0.005 in girls) emerged as determinants of HOMA-IR after adjusting age, BMI, tanner stage, and triglycerides. Serum GGT level is a strong marker of IR in obese Korean children.

Martin’s Equation as the Most Suitable Method for Estimation of Low-Density Lipoprotein Cholesterol Levels in Korean Adults

Background Friedewald equation is the most widely used method for estimating low-density lipoprotein cholesterol (LDL-C) level. However, due to potential over- or underestimation, many studies have used a modified equation. This study aimed to compare estimates by 4 different equations to directly measured LDL-C concentrations in order to propose the most appropriate method for LDL-C estimation in the Korean population. Methods We studied data of 4,350 subjects that included total cholesterol, high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), and LDL-C concentrations that had been measured at one university hospital in Seoul. We investigated 4 equations: LDL-C by Friedewalds original equation (LDL-CF) and its 3 modifications. Pearson correlation analysis was performed to compare these estimates to the direct measurement. Results Pearson correlation analysis revealed a good correlation among all 4 estimated LDL-C values and the directly measured LDL-C value. The Pearson coefficients were 0.951 for LDL-CF, 0.917 for LDL-C by Hatta equation (LDL-CH), 0.968 for LDL-C by Puavilai equation (LDL-CP), and 0.983 for LDL-C by Martin equation (LDL-CM). Martin equation (LDL-CM) resulted in the best approximation (mean difference from the direct measurement, 5.5 mg/dL; mean percentage difference from the direct measurement, 5.1%) and the best agreement with the direct measurement (86.1%). LDL-CP resulted in the second-best approximation (mean difference, 7.0 mg/dL; mean percentage difference, 6.2%; concordance, 82.5%). LDL-CM was found to be less influenced by TG and HDL-C levels than by LDL-CF. Conclusion Estimates by Martin equation had the best agreement with direct LDL-C concentrations and both Martin and Puavilai equations were superior to Friedewald equation for estimating LDL-C concentrations in Korean adults.

Can Gut Microbiota Modulation Be Used as a Practical Treatment for Obesity

J Obes Metab Syndr 2018;27:75-77 It is well known that interactions between behavioral factors, specifically, energy intake and physical activity, environmental, and genetic factors can impact the development of obesity. Recently, the composition of gut microbiota has emerged as a possible important endogenous factor that influences nutrient acquisition and energy regulation. Knowledge and understanding about the association between the human gut microbiota and obesity has increased exponentially during last decade, and the concept of gut microbiota modulation has provided a new paradigm for obesity treatment. Mutual and complex mechanisms are involved in the relationship between the gut microbiota, environment and obesity, but these mechanisms still remain largely unexplored. Understanding the mechanisms for how gut microbiota modulate host appetite and metabolism can provide clues for new strategies for obesity treatment. In this context, much effort has been made to manipulate gut microbiota to target host metabolism and appetite control. Administration of live beneficial bacterial strains (probiotics) is a relatively safe and noninvasive approach for altering the gut microbiota in humans. Several studies have reported that particular bacterial strains could reduce body weight or metabolic disorders, such as metabolic endotoxemia and insulin resistance. Zhang et al.1 indicated that probiotic consumption could reduce weight and body mass index (BMI) when multiple species of probiotics were administrated. However, there is currently no evidence of compositional alterations of the fecal microbiota in response to probiotic administration.2 Recently, Borgeraas et al.3 reported a meta-analysis of randomized controlled trials, which were conducted to examine the effects of probiotic administration in only overweight (BMI, 25–29.9 kg/m2) or obese (BMI, ≥ 30 kg/m2) adults. The study showed that short-term (≤ 12 weeks) probiotic supplementation reduced body weight: weighted mean difference (95% confidence interval) of body weight is –0.60 kg (–1.19 to –0.01 kg, I2 = 49%); BMI, –0.27 kg/m2 (–0.45 to –0.08 kg/m2, I2 = 57%); and fat percentage, –0.60% (–1.20% to –0.01%, I2 =19%). Prebiotics are non-indigestible fibers, which undergo bacterial fermentation and subsequently stimulate the growth of particular types of bacteria, thus conferring a beneficial effect on the host. Parnell and Reimer4 suggested that oligofructose supplementation over 12 weeks reduced body weight, mainly body fat, in overweight and obese subjects. The mechanism for this effect is hypothesized to be associated with in-