Kyung Eun Yun

Metabolically-healthy obesity and coronary artery calcification.

OBJECTIVES The purpose of this study was to compare the coronary artery calcium (CAC) scores of metabolically-healthy obese (MHO) and metabolically healthy normal-weight individuals in a large sample of apparently healthy men and women. BACKGROUND The risk of cardiovascular disease among obese individuals without obesity-related metabolic abnormalities, referred to as MHO, is controversial. METHODS We conducted a cross-sectional study of 14,828 metabolically-healthy adults with no known cardiovascular disease who underwent a health checkup examination that included estimation of CAC scores by cardiac tomography. Being metabolically healthy was defined as not having any metabolic syndrome component and having a homeostasis model assessment of insulin resistance <2.5. RESULTS MHO individuals had a higher prevalence of coronary calcification than normal weight subjects. In multivariable-adjusted models, the CAC score ratio comparing MHO with normal-weight participants was 2.26 (95% confidence interval: 1.48 to 3.43). In mediation analyses, further adjustment for metabolic risk factors markedly attenuated this association, which was no longer statistically significant (CAC score ratio 1.24; 95% confidence interval: 0.79 to 1.96). These associations did not differ by clinically-relevant subgroups. CONCLUSIONS MHO participants had a higher prevalence of subclinical coronary atherosclerosis than metabolically-healthy normal-weight participants, which supports the idea that MHO is not a harmless condition. This association, however, was mediated by metabolic risk factors at levels below those considered abnormal, which suggests that the label of metabolically healthy for obese subjects may be an artifact of the cutoff levels used in the definition of metabolic health.

Elevated alanine aminotransferase levels predict mortality from cardiovascular disease and diabetes in Koreans

OBJECTIVE Metabolic syndrome is associated with increased cardiovascular morbidity and mortality. Nonalcoholic fatty liver disease (NAFLD) is closely associated with metabolic syndrome. This study investigated the relationship between elevated alanine aminotransferase (ALT) levels, as a proxy marker of NAFLD, and death from cardiovascular disease (CVD) or diabetes in a Korean population. METHODS The study population consisted of 37,085 patients who underwent health examinations at the Health Promotion Center of the Asan Medical Center, Seoul, Korea, in 2000 and 2001. Individuals with viral hepatitis or alcoholic liver disease were excluded from the study. The relationship between baseline ALT levels and CVD- or diabetes-related mortality was determined for a median period of 5.0 years. RESULTS A total of 407 deaths occurred during the follow-up period, with 91 deaths resulting from CVD or diabetes. The multivariate relative risk (RR) and 95% confidence interval (CI) for CVD- or diabetes-related mortality in patients with ALT levels >40IU/L were 2.26 (1.22-4.19). The multivariate RR and 95% CI for CVD- or diabetes-related mortality in patients with the highest quartile of ALT levels (> or =31IU/L) were 2.28 (95% CI: 1.02-5.08) when the lowest quartile (< or =15IU/L) was used as a reference. CONCLUSION Our findings demonstrate that elevated ALT levels are independently associated with increased CVD- or diabetes-related mortality in Koreans. Thus, elevated ALT levels, as a marker for NAFLD, may serve as a surrogate predictor of CVD- or diabetes-related mortality among the Korean population.

Metabolically Healthy Obesity and Development of Chronic Kidney Disease: A Cohort Study.

Context The risk for chronic kidney disease (CKD) among obese patients without metabolic abnormalities is unknown. Contribution In this cohort study of South Korean men and women, metabolically healthy overweight and obese participants had increased incidence of CKD compared with normal-weight participants. Caution Body mass index was a marker of obesity and was assessed only once at baseline. Implication Physicians should monitor metabolically healthy obese and overweight patients for CKD and counsel them about maintaining a healthy weight and lifestyle. Chronic kidney disease (CKD) is a major clinical and public health problem (1). It is a precursor for end-stage renal disease and a strong risk factor for cardiovascular morbidity and mortality (2). Its prevalence is increasing worldwide along with the growing prevalence of obesity and metabolic disease (3). Indeed, obesitymediated by hypertension, insulin resistance, hyperglycemia, dyslipidemia, and other metabolic abnormalitiesis a major risk factor for CKD (4). Although the role of obesity-induced metabolic abnormalities in CKD development is well-established, metabolically healthy obese (MHO) persons, seem to have a favorable profile with no metabolic abnormalities (5, 6). The association between MHO and CKD, however, is largely unknown. The only study available found no association (7), but the comparison between MHO and normal-weight participants could be biased because the reference group included overweight participants, and metabolically healthy participants were defined as those with fewer than 2 metabolic components. Therefore, we examined the association between categories of body mass index (BMI) and CKD in a large sample of metabolically healthy men and women who had health screening examinations. Methods Study Population The Kangbuk Samsung Health Study is a cohort study of South Korean men and women aged 18 years or older who had a comprehensive annual or biennial health examination at the clinics of the Kangbuk Samsung Hospital Health Screening Centers in Seoul and Suwon, South Korea (8). More than 80% of participants were employees of various companies and local governmental organizations and their spouses. In South Korea, the Industrial Safety and Health Act requires all employees to receive annual or biennial health screening examinations, offered free of charge. The remaining participants registered for the screening examinations on their own. Our analysis included all persons who had comprehensive health examinations from 1 January 2002 to 31 December 2009 and had at least 1 other screening examination before 31 December 2013 (that is, they all had a baseline visit and 1 follow-up visit [n=175859]) (Figure 1). We excluded persons who had metabolic abnormalities (5, 9, 10) or evidence of kidney disease at baseline (n=108263). We excluded those with fasting glucose levels of 100 mg/dL or greater or who used glucose-lowering agents; blood pressure (BP) of 130/85 mm Hg or greater or who used BP-lowering agents; triglyceride levels of 150 mg/dL or greater or who used lipid-lowering agents; high-density lipoprotein (HDL) cholesterol levels less than 40 mg/dL in men or less than 50 mg/dL in women; insulin resistance, defined as homeostasis model assessment of insulin resistance (HOMA-IR) scores of 2.5 or greater (11); estimated glomerular filtration rate (GFR) less than 60 mL/min/1.73 m2; proteinuria; history of CKD; or history of cancer. Among eligible participants (n=67596), we further excluded those with missing values in any of the study variables (n=5347 [7.9%]). The final sample size was 62249 participants (Figure 1), all of whom were metabolically healthy and did not have markers of kidney disease at baseline. This study was approved by the Institutional Review Board of the Kangbuk Samsung Hospital, which exempted the requirement for informed consent because we only accessed deidentified data routinely collected as part of health screening examinations. Figure 1. Study flow diagram. CKD = chronic kidney disease; HDL = high-density lipoprotein. * Participants in the screening program could have >1 criterion that made them ineligible for the study. Eligible participants could have missing data in >1 study variable. Measurements Data on medical history, medication use, family history, physical activity, alcohol intake, smoking habits, and education level were collected by a standardized, self-administered questionnaire. Anthropometry data, BP, and blood samples were obtained by trained staff during the examinations (8, 12). Smoking status was categorized as never, former, or current. Alcohol consumption was categorized as none, moderate (20 g per day), or high (>20 g per day). The weekly frequency of moderate- or vigorous-intensity physical activity was also assessed. Sitting BP, height, and weight were measured by trained nurses. Height was measured to the nearest 1 cm with a stadiometer while the participant stood barefoot. Weight was measured to the nearest 0.1 kg on a bioimpedance analyzer (InBody 3.0 and Inbody 720, Biospace), which was validated for reproducibility and accuracy of body composition measurements (13) and calibrated every morning before testing started. Body mass index was calculated as weight in kilograms divided by height in meters squared and was classified according to Asian-specific criteria (14) (underweight, BMI <18.5 kg/m2; normal weight, BMI of 18.5 to 22.9 kg/m2; overweight, BMI of 23 to 24.9 kg/m2; and obese, BMI 25 kg/m2). Blood specimens were sampled from the antecubital vein after at least a 10-hour fast. The methods for measuring serum levels of glucose, uric acid, total cholesterol, low-density lipoprotein (LDL) cholesterol, triglycerides, HDL cholesterol, aspartate aminotransferase, alanine aminotransferase, -glutamyltransferase, insulin, and high-sensitivity C-reactive protein (hsCRP) have been reported elsewhere (8, 12). The Department of Laboratory Medicine of the Kangbuk Samsung Hospital has been accredited by the Korean Society for Laboratory Medicine and the Korean Association of Quality Assurance for Clinical Laboratories and participates in the College of American Pathologists Proficiency Testing survey. Insulin resistance was assessed with the HOMA-IR equation (fasting insulin [uU/mL]fasting glucose [mmol/L] 22.5). An ultrasonographic diagnosis of fatty liver was defined as a diffuse increase of fine echoes in the liver parenchyma compared with the kidney or spleen parenchyma (15, 16). During the study period, serum creatinine levels were measured with the kinetic alkaline picrate method (Jaffe method) in an automated chemistry analyzer (from 2002 to 2009, we used the Advia 1650a Autoanalyzer [Bayer Diagnostics]; from 2010 to 2013, we used the Modular D2400 [Roche]). The within-batch and total coefficients of variation were 1.8% to 3.9% for low-level and 1.4% to 1.8% for high-level quality control specimens throughout the study. Because the laboratory method that was used to measure serum creatinine levels from 2002 to 2009 was not traceable to isotope-dilution mass spectrometry, we estimated GFR by using the 4-variable Modification of Diet in Renal Disease Study equation (17). The conclusions did not change if we used the Chronic Kidney Disease Epidemiology Collaboration equation (18) for GFR estimation (data not shown). Urine protein was measured semiquantitatively by urine dipstick (URiSCAN Urine test strips, YD Diagnostics) tested on fresh, midstream urine samples and was reported in the following 6 grades: absent, trace, 1+, 2+, 3+, and 4+ (corresponding to protein levels of undetectable, 10 mg/dL, 30 mg/dL, 100 mg/dL, 300 mg/dL, and 1000 mg/dL, respectively). Proteinuria was defined as a grade of 1+ or greater. Statistical Analysis Person-years of follow-up were calculated from the date of the baseline health examination until the date of CKD diagnosis or the last screening examination, whichever came first. The cumulative incidence of CKD for baseline BMI categories (<18.5, 18.5 to 22.9, 23.0 to 24.9, or 25.0 kg/m2) were standardized to the empirical distribution of baseline confounders in the overall study sample with inverse probability weighting (19, 20). We first fitted a multinomial logistic regression to estimate each participants probability of being in his or her own BMI category given the observed confounders. Stabilized weights were then calculated as the inverse of the estimated conditional probabilities of exposure, further rescaled by the overall proportion of participants in each BMI category to reduce variability of weights across groups and to avoid influential observations involving extremely obese persons (19). For risk analyses, we fitted a spline-based, parametric survival model (21) according to the stabilized weights and stratified by BMI category to obtain smooth estimates of the CKD cumulative incidence curves that would have been seen in the entire population if every participant had been in each category (20). This survival model parameterized stratum-specific log cumulative hazards as distinct natural cubic splines of log time with 3 internal knots at the 25th, 50th, and 75th percentiles; allowed for interval-censored events (incident CKD occurred at an unknown time point between the visit at which CKD was diagnosed and the previous visit); and used robust SEs for spline parameters that accounted for the correlation induced by weighting (21). For comparison, we also applied weighted KaplanMeier methods to estimate nonparametric cumulative incidence curves for each BMI category. We used the previously mentioned weighted, spline-based survival model to calculate adjusted differences in cumulative incidences of CKD at 2, 5, and 10 years of follow-up of normal-weight participants compared with those in the other BMI categories. We calculated 95% CIs by applying delta methods to the robust variance estimates of spline parameters. In addition to risk differences, we

Cohort Study of Non-alcoholic Fatty Liver Disease, NAFLD fibrosis score, and the Risk of Incident Diabetes in a Korean population

OBJECTIVES:No study has evaluated an association between non-alcoholic fatty liver disease (NAFLD) severity and the incidence of diabetes. We examined whether NAFLD and its severity—using the NAFLD fibrosis score (NFS)—predict the development of diabetes.METHODS:A cross-sectional study was performed in 43,166 apparently healthy Koreans aged 30–59 years, who underwent a health checkup in 2005 and 2006. Of these, 38,291 subjects without diabetes were followed annually or biennially until December 2011 for the cohort study. NAFLD was defined as hepatic steatosis on ultrasonography in the absence of excessive alcohol use or other identifiable causes. The NFS was used to categorize the severity of fibrosis. Diabetes was defined as fasting serum glucose ≥126 mg/dl, glycated hemoglobin (HbA1c) ≥6.5%, or medication use for diabetes.RESULTS:During 175,996 person-years of follow-up, 2,025 participants developed diabetes. An increase across NAFLD categories was positively associated with an increased risk of diabetes in both the cross-sectional and cohort studies in a dose–response manner (P-trend <0.001). In multivariate-adjusted models, the hazard ratios (95% confidence intervals) for diabetes comparing NAFLD with low NFS and NAFLD with intermediate or high NFS vs. no NAFLD were 2.00 (1.79–2.24) and 4.74 (3.67–6.13), respectively. This association remained significant even in subjects with fasting glucose <100 mg/dl and subjects with HbA1c <5.8%.CONCLUSIONS:In this cohort study of a healthy Korean population, NAFLD and its severity using NFS were independently and strongly associated with increased incidence of diabetes in men and women—even with a euglycemic range of glucose and HbA1c.

Association Between BMI and Metabolic Syndrome and Adenomatous Colonic Polyps in Korean Men

Obesity and insulin resistance are associated with the risk of colon cancer. Adenomatous colonic polyps are precancerous lesions of colon cancer. We investigated whether BMI and the metabolic syndrome are associated with the presence of adenomatous colonic polyps in Korean men. Anthropometric measurements, metabolic risk factors, and colonoscopic pathologic findings were assessed in 1,898 men who underwent routine colonoscopy at the Health Promotion Center of Asan Medical Center in 2005. The modified National Cholesterol Education Program Adult Treatment Panel III (NCEP‐ATP III) and International Diabetes Federation (IDF) criteria were used for the definition of the metabolic syndrome. Multiple logistic regression analysis was used to evaluate the association between BMI and the metabolic syndrome and adenomatous polyps. Compared with men in the 1st quintile of the BMI, the adjusted odds ratio (OR) and 95% confidence interval (CI) for adenomatous polyps in men in the 2nd, 3rd, 4th, and 5th quintiles of the BMI were 1.55 (1.10–2.19), 1.57 (1.10–2.24), 1.94 (1.34–2.81), and 1.99 (1.31–3.01), respectively (P for trend <0.0001). Men with triglycerides (TGs) ≥150 mg/dl were significantly more likely to have adenomatous polyps than were men with TG <150 mg/dl (OR 1.29; 95% CI 1.03–1.62). As a function of the number of metabolic risk factors, the ORs for adenomatous polyps were 1.41 (1.03–1.93), 1.52 (1.08–2.12), 1.46 (1.01–2.12), and 1.77 (1.08–2.90) for 1, 2, 3, and ≥4 risk factors, respectively (P for trend <0.05). Adenomatous colonic polyps were significantly associated with increased BMI levels. Subjects with even one component of the metabolic syndrome had a significantly higher risk for developing adenomatous polyps compared to those subjects without any component in Korean men.

Sleep duration and quality in relation to non-alcoholic fatty liver disease in middle-aged workers and their spouses

BACKGROUND & AIMS Although accumulated evidence implies that short sleep duration and poor sleep quality may lead to an altered metabolic milieu, potentially triggering the development of non-alcoholic fatty liver disease (NAFLD), no studies have explored this association. This study sought to examine whether short sleep duration or poor sleep quality is associated with NAFLD in the general population. METHODS We assessed sleep duration and quality using the Pittsburgh Sleep Quality Index in 69,463 middle-aged workers and their spouses and carried out biochemical and anthropometric measurements. The presence of fatty liver was determined using ultrasonographic findings. Logistic regression models were used to evaluate the association of sleep duration and quality with NAFLD, after adjusting for potential confounders. RESULTS After controlling for the relevant confounding factors (age, alcohol intake, smoking, physical activity, systolic blood pressure, education level, marital status, presence of job, sleep apnea, and loud snoring), the adjusted odds ratio (95% confidence interval) for NAFLD comparing sleep duration ≤5 h to the reference (>7h) was 1.28 (1.13-1.44) in men and 1.71 (1.38-2.13) in women. After further adjustments for BMI, this association was not significant in men (OR: 1.03, 95% CI: 0.90-1.19) but remained significant in women (OR: 1.59, 95% CI: 1.23-2.05). The multivariate-adjusted odds ratio comparing participants with poor sleep quality vs. participants with good sleep quality was 1.10 (95% CI 1.02-1.19) and 1.36 (95% CI 1.17-1.59) in men and women, respectively. CONCLUSIONS In the middle-aged, general population, short sleep duration, and poor sleep quality were significantly associated with an increased risk of NAFLD. Prospective studies are required to confirm this association.

Impact of BMI on the incidence of metabolic abnormalities in metabolically healthy men

Objectives:Although the existence of metabolically healthy obese (MHO) individuals has been recognized, little is known regarding metabolic health status in these subjects over time. Thus, we evaluated longitudinal changes in metabolic parameters among MHO subjects compared with metabolically healthy, normal-weight (MHNW) subjects.Methods:A cohort study was performed on 2599 Korean men, 30–59 years of age, with no evidence of fatty liver disease on ultrasound and no traits of metabolic syndrome at baseline. BMI was categorized based on criteria for Asian population. Study participants were followed annually or biennially between 2002 and 2009. At each visit, the fatty liver on ultrasound was assessed and metabolic abnormalities were measured. Parametric Cox models and a pooled logistic regression models were used to evaluate the relationships of BMI with incident metabolic abnormalities.Results:During 9647.1 person-years of follow-up, 1673 participants developed metabolic abnormalities. After adjusting for age, smoking, alcohol intake and exercise, higher baseline BMI categories predicted increased incidences of metabolic abnormalities in a dose-response manner. The hazard ratios (95% confidence intervals) for hypertriglyceridemia, prediabetes, pre-hypertension, low high-density lipoprotein-cholesterol, fatty liver, elevated high sensitivity-C reactive protein, elevated homeostasis model assessment of insulin resistance, any metabolic abnormality and metabolic syndrome among the MHO subjects compared with the MHNW subjects were 1.51 (1.23–1.85), 1.43 (1.19–1.72), 1.79 (1.45–2.22), 1.80 (1.30–2.49), 2.69 (2.19–3.31), 1.39 (1.16–1.67), 2.90 (2.31–3.62), 1.68 (1.45–1.93) and 1.84(1.02–3.30), respectively.Conclusion:In this study, MHO individuals showed higher incidences of metabolic abnormalities compared with MHNW individuals. This suggests that initially MHO individuals undergo adverse metabolic changes associated with obesity over time.

Relationship of sitting time and physical activity with non-alcoholic fatty liver disease

BACKGROUND & AIMS The goal of this study was to examine the association of sitting time and physical activity level with non-alcoholic fatty liver disease (NAFLD) in Korean men and women and to explore whether any observed associations were mediated by adiposity. METHODS A cross-sectional study was performed on 139,056 Koreans, who underwent a health examination between March 2011 and December 2013. Physical activity level and sitting time were assessed using the validated Korean version of the international Physical Activity Questionnaire Short Form. The presence of fatty liver was determined using ultrasonographic findings. Poisson regression models with robust variance were used to evaluate the association of sitting time and physical activity level with NAFLD. RESULTS Of the 139,056 subjects, 39,257 had NAFLD. In a multivariable-adjusted model, both prolonged sitting time and decreased physical activity level were independently associated with increasing prevalence of NAFLD. The prevalence ratios (95% CIs) for NAFLD comparing 5-9 and ⩾10 h/day sitting time to <5h/day were 1.04 (1.02-1.07) and 1.09 (1.06-1.11), respectively (p for trend <0.001). These associations were still observed in subjects with BMI <23 kg/m(2). The prevalence ratios (95% CIs) for NAFLD comparing minimally active and health-enhancing physically active groups to the inactive group were 0.94 (0.92-0.95) and 0.80 (0.78-0.82), respectively (p for trend <0.001). CONCLUSIONS Prolonged sitting time and decreased physical activity level were positively associated with the prevalence of NAFLD in a large sample of middle-aged Koreans, supporting the importance of reducing time spent sitting in addition to promoting physical activity.

Metabolic syndrome and quality of life (QOL) using generalised and obesity-specific QOL scales

Objectives:  We investigated the association between metabolic syndrome (MS) and health‐related quality of life (HRQOL) assessed using generalised and obesity‐specific QOL instruments.

Metabolically Healthy Obesity and the Development of Nonalcoholic Fatty Liver Disease.

OBJECTIVES:The risk of nonalcoholic fatty liver disease (NAFLD) among obese individuals without obesity-related metabolic abnormalities, a condition referred to as metabolically healthy obese (MHO), is largely unexplored. Therefore, we examined the association between body mass index (BMI) categories and the development of NAFLD in a large cohort of metabolically healthy men and women.METHODS:A cohort study was conducted in 77,425 men and women free of NAFLD and metabolic abnormalities at baseline, who were followed-up annually or biennially for an average of 4.5 years. Being metabolically healthy was defined as not having any metabolic syndrome component and having a homeostasis model assessment of insulin resistance <2.5. The presence of fatty liver was determined using ultrasound.RESULTS:During 348,193.5 person-years of follow-up, 10,340 participants developed NAFLD (incidence rate, 29.7 per 1,000 person-years). The multivariable adjusted hazard ratios (95% confidence intervals) for incident NAFLD comparing overweight and obese with normal-weight participants were 2.15 (2.06–2.26) and 3.55 (3.37–3.74), respectively. In detailed dose–response analyses, increasing baseline BMI showed a strong and approximately linear relationship with the incidence of NAFLD, with no threshold at no risk. This association was present in both men and women, although it was stronger in women (P for interaction <0.001), and it was evident in all clinically relevant subgroups evaluated, including participants with low inflammation status.CONCLUSIONS:In a large cohort of strictly defined metabolically healthy men and women, overweight and obesity were strongly and progressively associated with an increased incidence of NAFLD, suggesting that the obese phenotype per se, regardless of metabolic abnormalities, can increase the risk of NAFLD.