Effects of Variability in Blood Pressure, Glucose, and Cholesterol Concentrations, and Body Mass Index on End-Stage Renal Disease in the General Population of Korea

Abstract

Aim: Metabolic parameters, such as blood pressure, glucose, lipid levels, and body weight, can interact with each other, and this clustering of metabolic risk factors is related to the progression to end-stage renal disease (ESRD). The effect of variability in metabolic parameters on the risk of ESRD has not been studied previously. Methods: Using nationally representative data from the Korean National Health Insurance System, 8,199,135 participants who had undergone three or more health examinations between 2005 and 2012 were included in this analysis. Intraindividual variability in systolic blood pressure (SBP), fasting blood glucose (FBG), total cholesterol (TC), and body mass index (BMI) was assessed by examining the coefficient of variation, variability independent of the mean, and average real variability. High variability was defined as the highest quartile of variability and low variability was defined as the lower three quartiles of variability. Results: Over a median (5–95%) of 7.1 (6.5–7.5) years of follow-up after the variability assessment period, 13,600 (1.7/1000 person-years) participants developed ESRD. For each metabolic parameter, an incrementally higher risk of ESRD was observed for higher variability quartiles compared with the lowest quartile. The risk of ESRD was 46% higher in the highest quartile of SBP variability, 47% higher in the highest quartile of FBG variability, 56% higher in the highest quartile of BMI variability, and 108% higher in the highest quartile of TC variability. Compared with the group with low variability for all four parameters, the group with high variability for all four parameters had a significantly higher risk for incident ESRD (hazard ratio (HR) 4.12; 95% CI 3.72–4.57). Conclusions: Variability in each metabolic parameter was an independent predictor of the development of ESRD among the general population. There was a composite effect of the variability in additional metabolic parameters on the risk of ESRD.

Association between oral health and incidence of pneumonia: a population-based cohort study from Korea

“…BMI was calculated by dividing body weight (kg) by the square of the height in meters (m 2 ). Hypertension, diabetes mellitus, and dyslipidemia were defined using criteria from previous studies [18][19][20] . The presence of hypertension was defined according to the following criteria: (1) ICD-10 codes for hypertension (I10, I11) with at least one claim per year for prescription of an antihypertensive drug, or (2) systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥90 mmHg.…”

Association between hemoglobin variability and incidence of hypertension over 40 years: a Korean national cohort study

“…There are many methods to define hemoglobin variability. However, with no gold standard to measure variability, we used 3 representative indices of variability based on various studies that refer to variability [15][16][17][18] . SD is the most widely used indicator and used in this study.…”

Update on association between exposure to renin-angiotensin-aldosterone system inhibitors and coronavirus disease 2019 in South Korea

“…The study was performed on 234,427 subjects, all of whom were tested for COVID-19 with diagnosis codes of B342, B972, Z208, Z290, U18, U181, Z038, Z115, U071, and U072. The main study [14,15] or heart failure (I11.0, I13.0, I13.2, I50.0, I50.1, I50.9) [16] with at least one annual claim for prescription of an antihypertensive drug. A total of 62,909 subjects aged ≥ 19 years were analyzed.…”

“…Covariates were designated based on diagnosis codes of ICD-10. The covariates considered in this study were diabetes, dyslipidemia, [14] myocardial infarction (MI), stroke, [18] heart failure, [16] liver disease, cancer, chronic obstructive pulmonary disease (COPD), [19] asthma, [20] end-stage renal disease (ESRD) with dialysis, [15] and immunocompromised status including autoimmune diseases and HIV infections. [21] Definitions of each comorbidity are presented in Table S1 in the Supplement.…”

“…[14][15][16][18][19][20][21] Also, considering the rigorous control of national health insurance system of South Korea in the diagnosis of COVID-19,…”