Gender- and age-group-specific associations between physical performance and bone mineral density, falls, and osteoporotic fractures in Koreans: the Chungju Metabolic Disease Cohort study.

Several factors increase the risk of fragility fracture, including low bone mineral density, falls, and poor physical performance. The associations among these factors have been investigated; however, most of the subjects of previous studies were either elderly men or elderly women, and the associations were controversial. The aim of this study was to evaluate the associations between physical performance and bone mineral density, and the history of falls and fractures, stratified by gender and age group. We analyzed 5368 subjects who were aged 50 years or older, including 1288 younger men (younger than 70 years), 1615 younger women (younger than 70 years), 1087 older men (70 years or older), and 1378 older women (70 years or older). We used the one-leg standing time (OLST) for assessing static balance and the timed up-and-go test (TUGT) for assessing dynamic balance. The subjects in the worst performance quartile for the OLST were more likely to have osteoporosis than those in the best performance quartile. Additionally, women who had experienced a fracture during the past 2 years were 1.68 times more likely to be in the worst performance quartile for the OLST than women without a previous fracture. Although the TUGT time was not associated with either the incidence of osteoporosis or the fracture history, the odds ratios for falling were 1.51 and 1.28 as the TUGT time increased by one standard deviation in younger men and younger women, respectively. The findings of the present study show that the OLST was associated with the incidence of osteoporosis and previous fracture and that the TUGT time was associated with the incidence of falling.

Identifying metabolically obese but normal-weight (MONW) individuals in a nondiabetic Korean population: the Chungju Metabolic disease Cohort (CMC) study.

OBJECTIVE: To investigate the prevalence and identify the phenotype of individuals suspected to be metabolically obese but normal weight (MONW). DESIGN AND SUBJECTS: Eight thousand nine hundred and eighty-seven nondiabetic subjects aged over 40 years were selected from the Chungju Metabolic disease Cohort study performed in 2003-2006 in Korea. Those within the highest quartile in the homeostasis model assessment of insulin resistance (HOMA-IR) with a normal body mass index (BMI) between 18·5 and 23 kg/m(2) were classified as MONW. MEASUREMENTS: Data on anthropometry, lipid profiles and HOMA-IR values were analysed. RESULTS: The prevalence of MONW was 14·2% for men and 12·9% for women amongst normal-weight subjects. Multiple logistic regression analysis showed that total cholesterol (TC) levels over 5·17 mm (odds ratio, OR = 1·481; 95% confidence intervals, CI 1·086-2·021), triglyceride (TG) levels over 1·69 mm (OR = 1·507; 95% CI 1·093-2·077) and high-density lipoprotein-cholesterol levels lower than 1·03 mm (OR = 1·580; 95% CI 1·053-2·371) independently had higher odds of diagnosing MONW amongst men. For women, a BMI over 21·5 kg/m(2) (OR = 1·405; 95% CI 1·034-1·909), TC levels over 5·17 mm (OR = 1·524; 95% CI 1·112-2·090) and TG levels over 1·69 mm (OR = 1·799; 95% CI 1·302-2·487) were independently associated with a diagnosis of MONW. CONCLUSIONS: More than 10% of normal-weight subjects were classed as MONW in this cohort. Identification of these subjects based on lipid profiles could aid in the early detection of a high risk group of developing cardiometabolic diseases.

Predictive Value of Glucose Parameters Obtained From Oral Glucose Tolerance Tests in Identifying Individuals at High Risk for the Development of Diabetes in Korean Population.

Previous studies suggest that the future risk for type 2 diabetes is not similar among subjects in the same glucose tolerance category. In this study, we aimed to evaluate simple intuitive indices to identify subjects at high risk for future diabetes development by using 0, 30, 120 minute glucose levels obtained during 75 g OGTTs from participants of a prospective community-based cohort in Korea.Among subjects enrolled at the Chungju Metabolic disease Cohort, those who performed an OGTT between 2007 and 2010 and repeated the test between 2011 and 2014 were recruited after excluding subjects with diabetes at baseline. Subjects were categorized according to their 30 minute glucose (G30) and the difference between 120 and 0 minute glucose (G(120-0)) levels with cutoffs of 9.75 and 2.50 mmol/L, respectively.Among 1126 subjects, 117 (10.39%) developed type 2 diabetes after 4 years. In diabetes nonconverters, increased insulin resistance was accompanied by compensatory insulin secretion, but this was not observed in converters during 4 years of follow-up. Subjects with G(120-0) ≥ 2.50 mmol/L or G30 ≥ 9.75 mmol/L demonstrated lower degrees of insulin secretion, higher degrees of insulin resistance, and ∼6-fold higher risk of developing future diabetes compared to their lower counterparts after adjustment for possible confounding factors. Moreover, subjects with high G(120-0) and high G30 demonstrated 22-fold higher risk for diabetes development compared to subjects with low G(120-0) and low G30.By using the G(120-0) and G30 values obtained during the OGTT, which are less complicated measurements than previously reported methods, we were able to select individuals at risk for future diabetes development. Further studies in different ethnicities are required to validate our results.

Changes in Metabolic Health Status Over Time and Risk of Developing Type 2 Diabetes: A Prospective Cohort Study.

Metabolic health and obesity are not stable conditions, and changes in the status of these conditions might lead to different clinical outcomes. We aimed to determine whether changes in metabolic health status or obesity over time have any effect on the risk of future diabetes. Nondiabetic individuals (n = 2692) from a population-based prospective cohort study with baseline and 2 follow-up examinations at 4-year intervals were included. Being "metabolically obese" (MO) was defined as being in the highest quartile of the TyG index (ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]), whereas falling into the lower 3 quartiles was regarded as being "metabolically healthy" (MH). Individuals were classified as "obese" (O) or "nonobese" (NO) using a body mass index of 25 kg/m2 as a cut-off. The risk of diabetes at year 8 was assessed according to changes of metabolic health status between year 0 and 4. Multivariate-adjusted relative risks (RRs) (95% confidence interval [CI]) of diabetes were significantly higher in individuals who retained the MONO phenotype (RR 3.72, 95% CI 2.10, 6.60) or who had progressed to MONO from the MHNO phenotype (RR 1.96, 95% CI 1.06, 3.61), whereas it was not significant in individuals who had improved to MHNO from the MONO phenotype (RR 0.67, 95% CI 0.26, 1.74) compared with individuals who retained the MHNO phenotype. In contrast, obese individuals had significantly higher RRs for diabetes, independent of changes in metabolic health status, whereas weight reduction resulted in a decreased risk of diabetes. Sensitivity analysis using the presence or absence of the metabolic syndrome as a definition of metabolic health revealed similar results. Changes in metabolic health status were an independent risk factor for future diabetes in nonobese individuals, whereas general obesity had a greater contribution to the risk of obese individuals developing diabetes. These observations might imply a different intervention strategy for diabetes prevention according to obesity status.

Predicting the development of diabetes using the product of triglycerides and glucose: the Chungju Metabolic Disease Cohort (CMC) study.

BACKGROUND: To 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. METHODS: A 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. RESULTS: During 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. CONCLUSIONS: The TyG index, a simple measure reflecting insulin resistance, might be useful in identifying individuals at high risk of developing diabetes.

Characteristics of metabolically obese, normal-weight women differ by menopause status: the Fourth Korea National Health and Nutrition Examination Survey.

OBJECTIVE: People with metabolically obese, normal-weight (MONW) phenotype, characterized by insulin resistance, are vulnerable to cardiovascular disease even though they are not physically obese. We assessed whether the characteristics of the MONW phenotype differed by menopause status in Korean women. METHODS: A nationally representative sample of 1,736 Korean women aged 19 years or older (1,197 premenopausal women and 539 postmenopausal women), without diabetes, and with a body mass index of 18.5 to less than 25 kg/m were randomly selected from the Fourth Korean National Health and Nutrition Examination Survey in 2008. MONW individuals were defined as those included in the highest quartile of a homeostatic model assessment of insulin resistance. RESULTS: The prevalence of the MONW phenotype was highest (23.8%) in young women (<30 y) and decreased with age in premenopausal women. In postmenopausal women, there was a sharp increase in the prevalence of the MONW phenotype after the age of 60 years. After adjustment for covariates, including age, we found that young age, rural residence, high body mass index, high systolic blood pressure, low high-density lipoprotein cholesterol, high white blood cell count, and lack of regular exercise were significantly associated with the MONW phenotype in premenopausal women. However, for postmenopausal women, alanine aminotransferase was the only predictor that was independently associated with the MONW phenotype. CONCLUSIONS: The characteristics of the MONW phenotype seem to vary between premenopausal and postmenopausal women. This suggests that optimal clinical approaches to preventing cardiovascular disease in women with the MONW phenotype may differ according to menopause status.

Metabolic syndrome as a predictor of type 2 diabetes, and its clinical interpretations and usefulness.

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.

Factors Associated with Insulin Resistance in a Middle-Aged Non-Obese Rural Population: The Chungju Metabolic Disease Cohort (CMC) Study.

OBJECTIVES: We aimed to determine the characteristics affecting insulin resistance in non-obese middle-aged adults in a rural community. METHODS: A total of 1,270 non-diabetic adults aged between 40 and 64 years old with body mass index (BMI) less than 25 kg/m(2) were analyzed. Subjects with insulin resistance were defined as those who had the highest quartile value of the homeostasis model assessment of insulin resistance (HOMA-IR) in a non-diabetic population. RESULTS: A total of 217 subjects (20.6%) had insulin resistance. Prevalence of metabolic syndrome was significantly higher in insulin-resistant subjects in both men (29.3% vs. 10.3%) and women (34.1% vs. 15.6%). Among metabolic syndrome components, elevated waist circumference and elevated triglyceride were higher in insulin-resistant subjects in both genders. After being controlled for socioeconomic status and lifestyle related covariates, the association between insulin resistance and BMI was statistically significant in the category of 23.0-24.9 kg/m(2) in men (adjusted OR, 4.63; 95% confidence interval [95% CI], 1.77-12.15) using the category of 18.5-20.9 kg/m(2) as a reference. In addition, the association between insulin resistance and abdominal obesity was statistically significant only for men (adjusted OR, 2.57; 95% CI, 1.29-5.11). CONCLUSION: Insulin resistance appears to be highly associated with high BMI and abdominal obesity, even in non-obese, non-diabetic middle-aged men.