Publication Details

AFRICAN RESEARCH NEXUS

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medicine

Greater Dietary Inflammatory Index score is associated with higher likelihood of chronic kidney disease

British Journal of Nutrition, Volume 120, No. 2, Year 2018

Chronic kidney disease (CKD) is described as a progressive alteration of kidney function, resulting from multiple factors, including behaviours. We investigated the association of the Dietary Inflammatory Index (DII®) with prevalent CKD in adult Americans. National Health and Nutrition Examination Survey participants with measured data on kidney function markers from 2005 to 2012 were included in this study. Prevalent CKD was based on an estimated glomerular filtration rate (eGFR) <60 ml/min per 1·73 m2 or urinary albumin/creatinine≥30 mg/g. Energy-adjusted DII (E-DIITM) scores were calculated from 24-h dietary recalls. Statistical analyses accounted for the survey design and sample weights. We included 21 649 participants, with 1634 (6·8 %) having prevalent CKD. Participants with high E-DII scores had greater BMI, fasting blood glucose and systolic blood pressure, and were more likely to be diabetic or hypertensive (all P<0·001) compared with those with lower E-DII scores. In regression models adjusted for age, sex, race, fasting blood glucose, blood pressure, BMI, hypertension and diabetes status, mean eGFR significantly decreased across increasing quartiles of E-DII, whereas serum uric acid level and log urinary albumin:creatinine ratio significantly increased (all P<0·001). Prevalent CKD increased from 5·3 % in the lowest to 9·3 % in the highest E-DII quartile (P=0·02). In multivariable-adjusted logistic regression models, the odds of prevalent CKD were 29 % higher in the highest compared with the lowest E-DII quartile. Pro-inflammatory diet is associated with declining kidney function and high prevalence of CKD. Dietary changes that reduce inflammation have a potential to prevent CKD.
Statistics
Citations: 36
Authors: 5
Affiliations: 4
Identifiers
Research Areas
Food Security
Noncommunicable Diseases
Study Design
Cross Sectional Study
Study Approach
Quantitative