INTRODUCTION AND OBJECTIVE: Growing evidence suggests that obesity is an important contributor to the development of chronic kidney disease (CKD). The relationship between obesity and CKD is complex and not completely understood, and the best anthropometric index of obesity in predicting CKD is controversial. This study aimed to determine the best anthropometric index of obesity in predicting CKD in a population of elderly women. MATERIALS AND METHODS: Anthropometric indexes of obesity including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WheiR) and waist-to-hip-ratio (WHR), were obtained in 730 selected females. Biochemical measurements including blood glucose, lipid profile, and 2-h postprandial blood glucose were performed. GFR was estimated by using CKD-EPI equation. RESULTS: The prevalence of CKD stage ≥ 3 was 12.2%. Overweight and obesity was found in 50% and 36% of participants, respectively. Increased central fat distribution, as defined by WheiR, WC and WHR, was found in 89.6%, 91.7% and 89.4% individuals, respectively. Univariate linear regression analysis showed positive correlations between CKD and age (p<0.001), BMI (p<0.001), WC (p<0.001), WHR (p=0.007), WheiR (p<0.001), diabetes (p=0.002), as well as triglicerydes (p=0.031), and negative correlation between CKD and HDL level (p=0.017). Multivariable analysis demonstrated that hypertension, diabetes, WC and WheiR were independent predictors of CKD. The area under the receiver operating characteristics curve was best for WheiR (0.647), followed by WC (0.620), BMI (0.616), and WHR (0.532). CONCLUSIONS: Abdominal obesity is an important predictor of CKD. Of commonly used anthropometric parameters of obesity WheiR ≥ 0.6 is particularly associated with CKD in elderly females.
INTRODUCTION AND OBJECTIVE: Growing evidence suggests that obesity is an important contributor to the development of chronic kidney disease (CKD). The relationship between obesity and CKD is complex and not completely understood, and the best anthropometric index of obesity in predicting CKD is controversial. This study aimed to determine the best anthropometric index of obesity in predicting CKD in a population of elderly women. MATERIALS AND METHODS: Anthropometric indexes of obesity including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WheiR) and waist-to-hip-ratio (WHR), were obtained in 730 selected females. Biochemical measurements including blood glucose, lipid profile, and 2-h postprandial blood glucose were performed. GFR was estimated by using CKD-EPI equation. RESULTS: The prevalence of CKD stage ≥ 3 was 12.2%. Overweight and obesity was found in 50% and 36% of participants, respectively. Increased central fat distribution, as defined by WheiR, WC and WHR, was found in 89.6%, 91.7% and 89.4% individuals, respectively. Univariate linear regression analysis showed positive correlations between CKD and age (p<0.001), BMI (p<0.001), WC (p<0.001), WHR (p=0.007), WheiR (p<0.001), diabetes (p=0.002), as well as triglicerydes (p=0.031), and negative correlation between CKD and HDL level (p=0.017). Multivariable analysis demonstrated that hypertension, diabetes, WC and WheiR were independent predictors of CKD. The area under the receiver operating characteristics curve was best for WheiR (0.647), followed by WC (0.620), BMI (0.616), and WHR (0.532). CONCLUSIONS:Abdominal obesity is an important predictor of CKD. Of commonly used anthropometric parameters of obesity WheiR ≥ 0.6 is particularly associated with CKD in elderly females.