Anthropomorphic Measurements That Include Central Fat Distribution Are More Closely Related with Key Risk Factors than BMI in CKD Stage 3

Background: Body Mass Index (BMI) as a marker of obesity is an established risk factor for chronic kidney disease (CKD) and cardiovascular disease (CVD). However, BMI can overestimate obesity. Anthropomorphic measurements that include central fat deposition are emerging as a more important risk factor. We studied BMI, waist circumference (WC), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR) and conicity index (CI) in a cohort of patients with CKD stage 3 and compared the associations with other known risk factors for CKD progression and CVD. Methods: 1740 patients with CKD stage 3 were recruited from primary care for the Renal Risk in Derby study. Each participant underwent clinical assessment, including anthropomorphic measurements and pulse wave velocity (PWV), as well as urine and serum biochemistry tests. Results: The mean age of the cohort was 72.9 +/- 9 years with 60% females. The mean eGFR was 52.5 +/- 10.4 ml/min/1.73 m(2) and 16.9% of the cohort had diabetes. With the cohort divided into normal and increased risk of morbidity and mortality using each anthropomorphic measurement, those measurements that included increased central fat distribution were significantly associated with more risk factors for CKD progression and CVD than increased BMI. Univariable analysis demonstrated central fat distribution was correlated with more risk factors than BMI. Subgroup analyses using recognised BMI cut-offs to define obesity and quartiles of WHR and CI demonstrated that increasing central fat distribution was significantly associated with more CKD and CVD risk factors than increasing BMI. Conclusion: Anthropomorphic measurements that include a measure of central fat deposition are related to more key risk factors in CKD stage 3 patients than BMI. Central fat deposition may be of greater importance as a risk factor in CKD than BMI and reliance on BMI alone may therefore underestimate the associated risk.