Chronic Kidney Disease Modifies The Relationship Between Body Fat Distribution and Blood Pressure: A Cross-Sectional Analysis
Received 31 January 2020
Accepted for publication 15 March 2020
Published 13 May 2020 Volume 2020:13 Pages 107—118
Checked for plagiarism Yes
Review by Single-blind
Peer reviewer comments 2
Editor who approved publication: Professor Pravin Singhal
Cindy George,1 Tandi E Matsha,2 Florence E Davidson,2,3 Julia H Goedecke,1,4 Rajiv T Erasmus,5 Andre P Kengne1
1Non-Communicable Diseases Research Unit, South African Medical Research Council, Cape Town, South Africa; 2SAMRC/CPUT/Cardiometabolic Health Research Unit, Department of Biomedical Sciences, Faculty of Health and Wellness Science, Cape Peninsula University of Technology, Cape Town, South Africa; 3Department of Medical Imaging and Therapeutic Sciences, Faculty of Health and Wellness Science, Cape Peninsula University of Technology, Cape Town, South Africa; 4Department of Human Biology, University of Cape Town, Cape Town, South Africa; 5Division of Chemical Pathology, Faculty of Medicine and Health Sciences, National Health Laboratory Service (NHLS) and University of Stellenbosch, Cape Town, South Africa
Correspondence: Cindy George PO Box 19070, Tygerberg 7505, South Africa
Tel +27 21 9380482
Fax +27 21 9335519
Introduction: Measures of adiposity are related to cardiovascular disease risk, but this relationship is inconsistent in disease states, such as chronic kidney disease (CKD). This study investigated the relationship between adiposity and blood pressure (BP) by CKD status.
Materials and Methods: South Africans of mixed-ancestry (n=1,621) were included. Estimated glomerular filtration rate (eGFR) was based on the modification of diet in renal disease (MDRD) equation, and CKD defined as eGFR < 60mL/min/1.73m2. Body fat distribution was assessed using anthropometry [body mass index (BMI) and waist circumference (WC)] and dual-energy x-ray absorptiometry (DXA) (n=152). Pulse pressure (PP) and mean arterial pressure (MAP) were calculated from systolic blood pressure (SBP) and diastolic blood pressure (DBP).
Results: In participants without CKD, anthropometric and DXA-derived measures positively correlated with SBP, DBP, MAP and PP (p< 0.02 for all), except for leg fat mass (LFM), which was not associated with BP indices (p> 0.100 for all). Contrary, in prevalent CKD (6%, n=96), only BMI was inversely associated with PP (p=0.0349). In multivariable analysis, only BMI and WC remained independently associated with SBP, DBP and MAP in the overall sample. Notably, the association between BMI, WC and LFM with SBP and PP, differed by CKD status (interaction: p< 0.100 for all), such that only BMI and WC were associated with SBP in those without CKD and inversely associated with PP in those with CKD. LFM was inversely associated with SBP and PP in those with CKD.
Conclusion: In people without CKD, BP generally increases with increasing measures of adiposity. However, excess body fat has a seemingly protective or neutral effect on BP in people with CKD.
Keywords: kidney dysfunction, anthropometry, dual-energy x-ray absorptiometry
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