Metabolic syndrome is defined as a cluster of glucose intolerance, hypertension, dyslipidemia and central obesity with insulin resistance as the source of pathogenesis. Although several different combinations of criteria have been used to define metabolic syndrome, a recently published consensus recommends the use of ethnic-specific criteria, including waist circumference as an indicator of central obesity, triglyceride and high-density lipoprotein (HDL) cholesterol as indicators of dyslipidemia, and blood pressure greater than 130/85 mmHg. The definition of dysglycemia, and whether central obesity and insulin resistance are essential components remain controversial. Regardless of the definition, the prevalence of metabolic syndrome is increasing in Western and Asian countries, particularly in developing areas undergoing rapid socioenvironmental changes. Numerous clinical trials have shown that metabolic syndrome is an important risk factor for cardiovascular disease (CVD), type 2 diabetes mellitus and all-cause mortality. Therefore, metabolic syndrome might be useful as a practical tool to predict these two major metabolic disorders. Comprehensive management of risk factors is very important to the improvement of personal and public health. However, recent studies have focused on the role metabolic syndrome plays as a risk factor for CVD; its importance in the prediction of incident diabetes is frequently overlooked. In the present review, we summarize the known evidence supporting metabolic syndrome as a predictor for type 2 diabetes mellitus and CVD. Additionally, we suggest how metabolic syndrome might be useful in clinical practice, especially for the prediction of diabetes. (J Diabetes Invest,

BackgroundTo determine whether the TyG index, a product of the levels of triglycerides and fasting plasma glucose (FPG) might be a valuable marker for predicting future diabetes.MethodsA total of 5,354 nondiabetic subjects who had completed their follow-up visit for evaluating diabetes status were selected from a large cohort of middle-aged Koreans in the Chungju Metabolic Disease Cohort study. The risk of diabetes was assessed according to the baseline TyG index, calculated as ln[fasting triglycerides (mg/dL) × FPG (mg/dL)/2]. The median follow-up period was 4.6 years.ResultsDuring the follow-up period, 420 subjects (7.8%) developed diabetes. The baseline values of the TyG index were significantly higher in these subjects compared with nondiabetic subjects (8.9±0.6 vs. 8.6±0.6; P<0.0001) and the incidence of diabetes increased in proportion to TyG index quartiles. After adjusting for age, gender, body mass index, waist circumference, systolic blood pressure, high-density lipoprotein (HDL)-cholesterol level, a family history of diabetes, smoking, alcohol drinking, education level and serum insulin level, the risk of diabetes onset was more than fourfold higher in the highest vs. the lowest quartile of the TyG index (relative risk, 4.095; 95% CI, 2.701–6.207). The predictive power of the TyG index was better than the triglyceride/HDL-cholesterol ratio or the homeostasis model assessment of insulin resistance.ConclusionsThe TyG index, a simple measure reflecting insulin resistance, might be useful in identifying individuals at high risk of developing diabetes.

BackgroundMalnutrition is associated with many adverse clinical outcomes. The present study aimed to identify the prevalence of malnutrition in hospitalized patients in Korea, evaluate the association between malnutrition and clinical outcomes, and ascertain the risk factors of malnutrition.MethodsA multicenter cross-sectional study was performed with 300 patients recruited from among the patients admitted in 25 hospitals on January 6, 2014. Nutritional status was assessed by using the Subjective Global Assessment (SGA). Demographic characteristics and underlying diseases were compared according to nutritional status. Logistic regression analysis was performed to identify the risk factors of malnutrition. Clinical outcomes such as rate of admission in intensive care units, length of hospital stay, and survival rate were evaluated.ResultsThe prevalence of malnutrition in the hospitalized patients was 22.0%. Old age (≥ 70 years), admission for medical treatment or diagnostic work-up, and underlying pulmonary or oncological disease were associated with malnutrition. Old age and admission for medical treatment or diagnostic work-up were identified to be risk factors of malnutrition in the multivariate analysis. Patients with malnutrition had longer hospital stay (SGA A = 7.63 ± 6.03 days, B = 9.02 ± 9.96 days, and C = 12.18 ± 7.24 days, P = 0.018) and lower 90-day survival rate (SGA A = 97.9%, B = 90.7%, and C = 58.3%, P < 0.001).ConclusionMalnutrition was common in hospitalized patients, and resulted in longer hospitalization and associated lower survival rate. The rate of malnutrition tended to be higher when the patient was older than 70 years old or hospitalized for medical treatment or diagnostic work-up compared to elective surgery.

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