Prof. Dr. Matthias Schmid
Institute of medical Biometry, Computer Science and Epidemiology
sekretariat@imbie.uni-bonn.de View member: Prof. Dr. Matthias Schmid
European journal of clinical nutrition
BACKGROUND/OBJECTIVES: A diet following chronic kidney disease (CKD)-specific recommendations is considered essential for optimal management of patients with CKD. However, data on the adherence to these recommendations and its implications for health-relevant biomarkers are lacking. The objectives were to estimate adherence to CKD-specific dietary recommendations, to identify characteristics and lifestyle variables associated with poor adherence, and to investigate the relationship of adherence with biomarkers.
METHODS: In this cross-sectional analysis, average dietary intake was estimated in 3193 participants with moderately severe CKD enrolled into the observational multicenter German CKD study using a food frequency questionnaire. A CKD diet score was developed to assess adherence to CKD-specific dietary recommendations based on intake of sodium, potassium, fiber, protein, sugar, and cholesterol. The associations of dietary adherence with characteristics, lifestyle variables, and biomarker levels were determined.
RESULTS: Logistic regression analysis revealed younger age, higher body mass index, male gender, lower educational attainment, various lifestyle variables (cigarette smoking, infrequent alcohol consumption, low physical activity), and lower estimated glomerular filtrate rate associated with lower adherence to dietary recommendations. Low adherence to dietary recommendations was further associated with dyslipidemia, higher uric acid, and C-reactive protein levels. Associations between low dietary adherence and biomarkers were mostly driven by low intake of fiber and potassium, and high intake of sugar and cholesterol.
CONCLUSIONS: This study revealed differential characteristics and biomarkers associated with lower adherence to CKD-specific dietary recommendations. Promotion of CKD-specific dietary recommendations may help to mitigate the adverse prognosis in CKD patients.
© 2021. The Author(s).
PMID: 33531632
Institute of medical Biometry, Computer Science and Epidemiology
sekretariat@imbie.uni-bonn.de View member: Prof. Dr. Matthias Schmid