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Abstract: FR-PO463

Association of Anthropometric Measures of Obesity and CKD in Elderly Women Admitted in a Tertiary Care Government Teaching Hospital

Session Information

Category: Diabetic Kidney Disease

  • 602 Diabetic Kidney Disease: Clinical

Authors

  • Sayed, Muntazir Ali Parvez Akhtar, RCSM Government Medical College Kolhapur, India., Mumbai, India
  • Bharne, Renu Manohar, RCSM Government Medical College and CPR Hospital, Kolhapur, Maharashtra, India, Thane, India
  • Akbani, Adil A raheman, RCSM Government Medical College, Kolhapur, Maharashtra, India, Karanja lad, India
  • Salamwade, Rajashri, RCSM Government Medical College and CPR General Hospital Kolhapur, Mumbai, India

Group or Team Name

  • Team Kolhapurkars
Background

There is growing evidence which suggests that obesity is an important contributor to the development of CKD. However, the relationship between obesity and CKD is complex and not completely understood, and the best anthropometric index of obesity in predicting CKD is controversial. We carried out this study to determine the best anthropometric index of obesity in predicting CKD in a population of elderly women admitted in RCSM Government Medical College and CPR General Hospital, the only tertiary care government teaching hospital in the city of Kolhapur, India.

Methods

We carried out this study for the duration of 3 years from May 2015 to April 2018 at our institute. Anthropometric indices of obesity including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WheiR) and waist-to-hip-ratio (WHR), were obtained in 1706 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. Adequate statistical tests were carried out and for all tests, a p-value <0.05 was considered statistically significant.

Results

The prevalence of CKD stage ≥ 3 was 36.64%. Overweight and obesity was found in 54.16% and 34.88% of participants, respectively. Increased central fat distribution, as defined by WheiR, WC and WHR, was found in 84.34%, 89.86% and 86.52% individuals, respectively. Univariate linear regression analysis showed positive correlations between CKD and age (p<0.001), BMI (p<0.0001), WC (p<0.0001), WHR (p<0.005), WheiR (p<0.0001), diabetes (p<0.005), as well as triglicerydes (p<0.003); however there was a negative correlation between CKD and HDL level (p=0.025). 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 (0.638), followed by WC (0.619), BMI (0.603), and WHR (0.598).

Conclusion

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. However, the value for these obesity indices is limited in screening CKD and further research in this regard is highly encouraged.