Study participants
This study is based on the health risk assessment study that aims to characterize CVD risk factors and to explore surrogate markers for CVD in Korean adults. The study cohort consisted of 9,451 individuals aged ≥20 years who voluntarily visited the Health Promotion Center, Gangnam Severance Hospital, Yonsei University College of Medicine for regular health check-ups between March 2010 and May 2011. The current analysis was limited to 2,584 participants aged ≥45 years who received MRI scans. We excluded participants who met at least one of the following criteria: missing data, did not fast for 12 h prior to testing, or a history of cancer, ischemic heart disease, or stroke (n=422). Following these exclusions, 2,162 participants were included in the final analysis. This study was conducted in accordance with the ethical principles of the Declaration of Helsinki and was approved by the Institutional Review Board of Yonsei University College of Medicine, Seoul, Korea.
Data collection
Each participant completed a questionnaire about lifestyle and medical history. Self-reported cigarette smoking, alcohol consumption, and physical activity characteristics were gleaned from the questionnaires. The smoking status was categorized as non-smoker, ex-smoker, and current smoker. Questions regarding alcohol intake included the frequency of consumption on a weekly basis. Regular alcohol consumption was defined as alcohol drinking ≥ two times per week. Participants were asked about their physical exercise on a weekly basis, and regular exercise was defined as exercise ≥three times per week. Body weight and height were measured to the nearest 0.1 kg and 0.1 cm, respectively, in lightweight indoor clothing without shoes. Body mass index (BMI) was calculated as the weight in kilograms divided by the square of the height in meters (kg/m2). Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured using the patient’s right arm with a standard mercury sphygmomanometer in the sitting position after 10 min of rest (Baumanometer, W.A. Baum Co Inc., Copiague, NY, USA). All blood samples were obtained from the antecubital vein after overnight fasting for 12 h. Fasting plasma glucose, total cholesterol, triglyceride, and high density lipoprotein (HDL) cholesterol levels were measured by enzymatic methods using a Hitachi 7600 automated chemistry analyzer (Hitachi Co., Tokyo, Japan), and leukocyte counts were quantified using an automated blood cell counter (ADVIA 120, Bayer, NY, USA).
Hypertension was defined by SBP ≥ 140 mmHg, DBP ≥ 90 mmHg, or the current use of hypertension medication. Type 2 diabetes was defined by a fasting plasma glucose level ≥ 126 mg/dL or the current use of diabetes medications. The modified National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) was used to define metabolic syndrome. Because waist circumference was not measured, we defined obesity as BMI ≥ 25 kg/m2, as suggested by the position statement of the American College of Endocrinology[20]. Therefore, metabolic syndrome was defined by the presence of three or more of the following risk factors: obesity with BMI ≥25 kg/m2, elevated systolic blood pressure ≥130 mmHg, elevated diastolic blood pressure ≥85 mmHg, or the current use of hypertension medication, high fasting plasma glucose ≥126 mg/dL or the current use of diabetes medication, high triglycerides ≥ 150 mg/dL, and low HDL cholesterol (<40 mg/dL for men and <50mg/dL for women). An automatic waveform analyzer (model BP-203RPE; Colin Co., Komaki, Japan) was used to measure brachial-ankle pulse wave velocity (baPWV). This instrument simultaneously recorded blood pressure, phonocardiogram, electrocardiogram, and arterial blood pressure at both the left and right brachial arteries and tibial arteries after 10 min of bed rest. Electrocardiogram electrodes were placed on both wrists, and a microphone for the phonogram was placed on the left edge of the sternum. Pneumonic cuffs were wrapped around both the upper arms and ankles and connected to a plethysmographic sensor to determine the volume pulse waveform. Waveforms for the upper arm (brachial artery) and ankle (tibial artery) were stored for 10 sec sample times with automatic gain analysis and quality adjustment. An oscillometric pressure sensor was attached to the cuffs to measure blood pressure at the four extremities. The baPWVs were recorded using a semiconductor pressure sensor (1200 Hz sample acquisition frequency) and calculated using the equation: (La-Lb)/ΔTba. La and Lb were defined as the distance from the aortic valve to the elbow and to the ankle, respectively. The distance from the suprasternal notch to the elbow (La) was expressed by La = 0.2195 x height of subject (cm) - 2.0734, and the distance from the suprasternal notch to the ankle (Lb) was expressed by Lb = 0.8129 x height of subject (cm) + 12.328. The time interval between the arm and ankle distance (ΔTba) was defined as the pulse transit time between the brachial and tibial artery pressure waveforms.
Brain MRI acquisition and leukoaraiosis
All brain MRI scans were obtained with a 3.0 TMR scanner using a standard head coil (GE Signa VH/I; GE Medical Systems, Milwaukee, WI, USA). All participants were examined after administration of a Gd-DTPA contrast agent. The MRI protocol included the collection of T1- and T2-weighted images and FLAIR images. The current study was based on a retrospective review of the results of brain MRI scans. MRI features were independently evaluated by two experienced radiologists who were unaware of the aims of the study and blind to the laboratory findings. We analyzed the kappa statistics to analyze agreement between the two radiologists because the outcome encompassed ordinal scoring, and the kappa index (95% CI) was 0.859 (0.796-0.905). Leukoaraiosis was diagnosed when there was hyperintensity on the T2-weighted images or FLAIR images without hypointensity on the T1-weighted images in the white matter near the lateral ventricles and subcortical areas.
Statistical analysis
TyG index was defined as Ln (fasting triglycerides (mg/dl) × fasting blood glucose (mg/dl)/2). The TyG index quartiles were categorized as follows: Q1: ≤8.12, Q2: 8.13-8.50, Q2: 8.51-8.89, and Q4: ≥8.90. The clinical characteristics of the study population according to serum TyG index quartiles were compared using a one-way analysis of variance (ANOVA) or the Kruskal-Wallis test for continuous variables according to the normality of distributions, and the chi-square test was used for categorical variables. Normal distribution was evaluated with the determination of skewness using the Kolmogorov-Smirnov test. Continuous data are presented as mean (standard deviation, SD) or median (interquartile range, IQR), and categorical data are presented as frequencies. The differences of mean, median and proportion between groups were determined using post hoc analysis of ANOVA, Kruskal-Wallis test and chi-squared test using Bonferroni corrections. The odds ratios for leukoaraiosis were calculated using a multiple logistic regression analysis after adjusting for confounding variables across TyG index quartiles. All analyses were conducted using SAS statistical software (version 9.4; SAS Institute Inc., Cary, NC, USA). All statistical tests were two-sided, and statistical significance was determined at p value < 0.05. Additionally, the probabilities of leukoaraiosis for TyG index are presented with smooth spline curves using R packages version 3.4.3(Institute for Statistics and Mathematics)