Abstract: TH-PO731
The Magnitude of Obesity and Metabolic Syndrome among the Diabetic CKD Population: A Nationwide Study
Session Information
- Diabetic and Obesity Induced Kidney Disease - Clinical - I
November 02, 2017 | Location: Hall H, Morial Convention Center
Abstract Time: 10:00 AM - 10:00 AM
Category: Diabetes
- 502 Diabetes Mellitus and Obesity: Clinical
Authors
- Kittiskulnam, Piyawan, Chulalongkorn university, Bangkok, Thailand
- Thokanit, Nintita Sripaiboonkij, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
- Katavetin, Pisut, King Chulalongkorn Memorial Hospital, Thai Red Cross Society and Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Susantitaphong, Paweena, Chulalongkorn University, Bangkok, Thailand
- Praditpornsilpa, Kearkiat, Chulalongkorn University, Bangkok, Thailand
- Eiam-Ong, Somchai, Chulalongkorn University, Bangkok, Thailand
Background
Although the prevalence of obesity among dialysis patients has been exceeding than that of in general population, little is known regarding obesity in non-dialysis CKD. We aimed to find the magnitude of obesity and metabolic syndrome (MetS) and their associations with the development of CKD among diabetic patients.
Methods
A national survey of type 2 diabetes mellitus (T2DM) patients was collected in the Thai National Health Security Office database during 2014-5. The sampling frame was designated as distinct geographic regions throughout the country. A stratified two-stage cluster sampling was used to select study population. Anthropometry and 12-hour fasting blood samples were obtained by trained personnel. BMI of ≥25 kg/m2 was classified as obesity. MetS was defined as having elevated waist circumference (>90 cm in men and >80 cm in women) plus any 2 of the followings: triglyceride>150 mg/dL, HDL<40 in men or <50 mg/dL in women, BP≥130/85 mmHg, and blood sugar ≥100 mg/dL. CKD was defined as eGFR <60 ml/min according to the CKD-EPI equation. Logistic regression analysis was performed to examine the relationship between obesity and MetS with the development of CKD.
Results
A total of 32,616 patients were finally recruited from 997 hospitals. The mean age was 61.5±10.9 years and eGFR 70.9±26.6 ml/min with 32% men. Of the participants, 35% were CKD patients (n=10,672). The prevalence of obesity was 46.5% in CKD and 54.1% in non-CKD patients with T2DM. In contrast, the prevalence of MetS in CKD was higher than non-CKD patients (58.5 vs 57.2, p=0.03). There was a trend association between the prevalence of MetS with CKD stage from 3 to 5 (58.1, 61.6, and 63.2%, respectively, p=0.01). When stratified by sex in diabetic CKD group, the presence of MetS was significantly higher among female compared to male (68.6% vs 38.0%, p<0.001). MetS, but not obesity, had a significant higher risk prediction for developing of CKD among T2DM patients after adjusting for age, sex, and comorbidities [OR 1.11; 95%CI 1.03-1.21, p=0.01].
Conclusion
The relatively high prevalence of both obesity and MetS were observed in diabetic CKD community. Identification of obesity-related metabolic phenotypes is necessary to determine risk for the development of CKD among T2DM patients.
Funding
- Government Support - Non-U.S.