Background The aim of this study was measuring the association between the hypertriglyceridemic-waist (HTGW) phenotype and chronic kidney disease in a large type 2 diabetes population. Methods A total of… Click to show full abstract
Background The aim of this study was measuring the association between the hypertriglyceridemic-waist (HTGW) phenotype and chronic kidney disease in a large type 2 diabetes population. Methods A total of 4254 diabetic patients from the cross-sectional Environmental Pollutant Exposure and Metabolic Diseases in Shanghai (METAL) study were enrolled. The hypertriglyceridemic-waist (HTGW) phenotype was defined as the presence of an elevated waist circumference (WC) and elevated triglyceride (TG) concentration. Chronic kidney disease (CKD) was defined as an estimated glomerular filtration rate (eGFR) less than 60 mL/min/1.73 m2 or urinary albumin creatinine ratio (uACR) more than 30 mg/g. Linear and multiple logistic regression models were used for measuring the association between HTGW phenotype and chronic kidney disease. Results The prevalence of CKD was 29% and 35.8% in total participants and participants with HTGW phenotype, respectively. Subjects in the HTGW phenotype group were more likely to have CKD (OR 1.47, 95% CI: 1.11, 1.95) compared with subjects in the normal waist circumference and normal triglycerides (NTNW) group. HTGW phenotype was both associated with the increasing risk of decreased eGFR (OR 1.31, 95% CI: 1.02, 1.75) and elevated uACR (OR 1.57, 95% CI: 1.18, 2.11). Furthermore, the stratified analysis showed that the strongest positive association between HTGW phenotype and CKD presence was found in the subgroup of presence of hypertension. The associations were all fully adjusted for age, sex, BMI, current smoking, current drinking and other confounding factors. Conclusion Our study suggested a positive association between the HTGW phenotype and CKD in Chinese type 2 diabetes patients. Further prospective studies are needed to confirm our findings and to investigate the underlying biological mechanisms.
               
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