Diet quality and incident chronic kidney disease in the general population: The Lifelines Cohort Study

Autor: Gerjan Navis, Stephan J. L. Bakker, Qingqing Cai, Martin H. de Borst, Petra C Vinke, Eva Corpeleijn, Louise H. Dekker
Přispěvatelé: Reproductive Origins of Adult Health and Disease (ROAHD), Groningen Institute for Organ Transplantation (GIOT), Groningen Kidney Center (GKC), Value, Affordability and Sustainability (VALUE)
Rok vydání: 2021
Předmět:
Zdroj: Clinical Nutrition, 40(9), 5099-5105. Churchill Livingstone
ISSN: 0261-5614
DOI: 10.1016/j.clnu.2021.07.033
Popis: RATIONALE & AIMS: Healthy dietary patterns have been associated with a lower risk of chronic kidney disease (CKD). We aimed to investigate the association of a fully food-based diet quality score assessed by the Lifelines Diet Score (LLDS) with either incident CKD or eGFR decline in the general population.METHODS: For this study, data from a prospective general population-based Lifelines cohort in the Northern Netherlands was used. Diet was assessed with a 110-item food frequency questionnaire at baseline. The LLDS, based on international evidence for diet-disease relations at the food group level, was calculated to assess diet quality. For the analysis, the score was divided into tertiles. Logistic regression was performed to evaluate the association of the LLDS at baseline with either incident CKD (eGFR RESULTS: A total of 78 346 participants free of CKD at baseline were included. During a mean (SD) follow-up of 3.6 ± 0.9 years, 2071 (2.6%) participants developed CKD and 7611 (9.7%) had a ≥20% eGFR decline. Participants in the highest tertile of LLDS had a lower risk of incident CKD (fully adjusted OR 0.83, [95% CI: 0.72-0.96]) and ≥20% eGFR decline (fully adjusted OR 0.80, [95% CI: 0.75-0.86]), compared with those in the lowest tertile. Similar dose-response associations were observed in continuous LLDS.CONCLUSIONS: Higher adherence to a high-quality diet was associated with a lower risk of incident CKD or ≥20% eGFR decline in the general population.
Databáze: OpenAIRE