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Dietary intake of non-dialysis chronic kidney disease patients: the PROGREDIR study. A cross-sectional study

BACKGROUND: Despite evidence that diet is very important in relation to chronic kidney disease (CKD) progression, studies in this field are scarce and have focused only on some specific nutrients. We evaluated the energy, macronutrient and micronutrient intakes and dietary patterns of non-dialysis C...

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Detalles Bibliográficos
Autores principales: Machado, Alisson Diego, dos Anjos, Fernanda Silva Nogueira, Domingos, Maria Alice Muniz, Molina, Maria del Carmen Bisi, Marchioni, Dirce Maria Lobo, Benseñor, Isabela Judith Martins, Titan, Silvia Maria de Oliveira
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Associação Paulista de Medicina - APM 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9907748/
https://www.ncbi.nlm.nih.gov/pubmed/29924288
http://dx.doi.org/10.1590/1516-3180.2017.0177141217
Descripción
Sumario:BACKGROUND: Despite evidence that diet is very important in relation to chronic kidney disease (CKD) progression, studies in this field are scarce and have focused only on some specific nutrients. We evaluated the energy, macronutrient and micronutrient intakes and dietary patterns of non-dialysis CKD participants in the PROGREDIR study. DESIGN AND SETTING: Cross-sectional study; CKD cohort, São Paulo, Brazil. METHODS: Baseline data on 454 participants in the PROGREDIR study were analyzed. Dietary intake was evaluated through a food frequency questionnaire. Dietary patterns were derived through principal component analysis. Energy and protein intakes were compared with National Kidney Foundation recommendations. Linear regression analysis was performed between energy and nutrient intakes and estimated glomerular filtration rate (eGFR), and between sociodemographic and clinical variables and dietary patterns. RESULTS: Median energy and protein intakes were 25.0 kcal/kg and 1.1 g/kg, respectively. In linear regression, protein intake (β = -3.67; P = 0.07) was related to eGFR. Three dietary patterns (snack, mixed and traditional) were retained. The snack pattern was directly associated with male gender (β = 0.27; P = 0.006) and inversely with diabetes (β = -0.23; P = 0.02). The traditional pattern was directly associated with male gender (β = 0.27; P = 0.007) and schooling (β = 0.40; P < 0.001) and inversely with age (β = -0.01; P = 0.001) and hypertension (β = -0.34; P = 0.05). CONCLUSIONS: We identified low energy and high protein intake in this population. Protein intake was inversely related to eGFR. Dietary patterns were associated with age, gender, schooling level, hypertension and diabetes.