Data were collected from patients with stage 2-5 CKD aged 18 and 80 years and were not on dialysis. These patients were followed up in the Nephrology Department of the Usak University Research and Training Hospital for at least 1 year between December 2017 and November 2018. This study was approved by the Ethics Committee of Usak University School of Medicine. Of 218 patients with stage 2-5 CKD, only 129 were eligible for the study. The exclusion criteria were as follows: missing data, patients older than 80 years, patients taking cholesterol and lipid lowering drugs and steroids. Demographic data (age, gender, and medical history such as diabetes mellitus and hypertension, medications) were collected from the electronic records of the patients, and physical examinations such as blood pressure measurement after 5 minutes of rest, height, weight, waist circumference (WC) measured at the level midway from the lower rib margin and the iliac crest in the midaxillary line while the patients were standing with their feet 25-30 cm apart were performed. Laboratory samples were collected from the patients, transported to the laboratory, and stored at -80°C until analysis. HbA1c levels were measured using the cation exchange high-performance liquid chromatography system (Variant II Turbo HbA1c analyzer, Bio-Rad Laboratories, Hercules, CA, USA). TG, HDL, uric acid, calcium, phosphorus, bicarbonate, urine protein, and creatinine levels were analyzed with the spectrophotometric method using Architect c8000 automated analyzer and original Abbott kits (Abbott Diagnostics Inc, Park City, IL, USA). Two milliliters of blood was added to ethylenediaminetetraacetic acid (EDTA) (1 mg/ml blood) and mixed thoroughly to perform complete blood count by Mindray BC 6800 (Mindray Bio-Medical Electronics Co., Ltd, Shenzhen, China). Parathyroid hormone (PTH) was analyzed with the electrochemiluminescence method using the ADVIA Centaur analyzer (Siemens Healthcare Diagnostics, Munich, Germany). Serum creatinine levels were measured over a 1-year interval. The eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. The stages of CKD were defined according to eGFR as stage 2 mild CKD (eGFR = 89-60 mL/min/1.73m2), stage 3a moderate CKD (eGFR = 45-59 mL/min/1.73m2), stage 3b moderate CKD (eGFR = 30-44 mL/min/1.73m2), stage 4 severe CKD (eGFR = 15-29 mL/min/1.73m2), and stage 5 end-stage CKD (eGFR = <15 mL/min/1.73m2). The eGFR change was calculated as the percentage of change in eGFR in 1 year to baseline eGFR. VAI was calculated using the formula (WC/36.8+(1.89xBMI))x(TG/0.81)x(1.52/HDL) for women and (WC/39.68+(1.88xBMI))x(TG/1.03)x(1.31/HDL) for men. BMI was calculated by dividing weight to square of height.~Data were analyzed with the IBM SPSS 22 statistical program. Descriptive statistics were used to define the main characteristics of the patients. Shapiro-Wilk and Kolmogorov-Smirnoff statistical tests were used to assess the normality of the data. All parameters except parathyroid hormone levels were normally distributed. The correlation between the eGFR difference, VAI values, and other parameters was tested with the Pearson correlation test. The difference between the patients with different CKD stages according to the eGFR change and VAI values were tested by the one-way ANOVA test. The independent samples t-test was used to investigate the difference between patients with and without DM and hypertension according to VAI values and eGFR change. Partial Correlation is used for to investigate the correlation between the two variables, where the effect of other variables is kept constant and controlled for both variables. A p value of less than 0.05 was defined as significant.
The visceral adiposity index (VAI) has been developed, an indicator for the metabolic function of VAT. Previous studies have confirmed the association between the VAI and CKD prevalence. In this study, we attempted to investigate the association between estimated glomerular filtration rate (eGFR) decline and visceral adiposity.