Dietary patterns associated with the new onset of chronic kidney disease using clustering algorithm

  • Park, Dougho; 
  • Kim, Jinmi; 
  • Kim, Da Woon; 
  • Lee, Donghyun; 
  • Kim, Taeyeon; 
  • ... Kim, Hyo Jin; 
  • 외 3명
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초록

Understanding how dietary patterns influence chronic kidney disease (CKD) development is crucial for effective prevention strategies. This study identified distinct dietary patterns among Korean adults and investigated their association with CKD development. This retrospective cohort study used data from the Korean Genome and Epidemiology Study health examinee study database of community-dwelling adults aged >= 40 years in South Korea (2004-2016). Then, dietary patterns were identified using K-means clustering analysis based on the quantity (weights) of 106 foods and intakes of energy and 22 nutrients. The dependent variable for Cox regression analyses was the development of new-onset CKD. A total of 57,213 participants were classified into three dietary clusters. Cluster C, characterized by lower overall food, energy, and nutrient intakes and higher carbohydrate intake, was independently associated with increased CKD risk (adjusted hazard ratio, 1.59; 95% confidence interval, 1.04-2.41; P = 0.031) compared to Cluster A, characterized by higher intake of vegetables and fish/shellfish. Subgroup analyses revealed that Cluster C still had a significantly high risk for CKD development in age >= 65 years, male sex, previous cardiovascular disease, systolic blood pressure >= 130 mm Hg, and body mass index >= 25 kg/m2. Both the quantity and quality of food intake may influence CKD development in Korean adults. Maintaining a balanced, nutrient-rich diet could be key for CKD prevention, especially in high-risk subgroups.

키워드

Chronic kidney disease; Cluster analysis; Cohort studies; Diet; Nutrition survey; GLOMERULAR-FILTRATION-RATE; CARDIOVASCULAR-DISEASE; CARBOHYDRATE INTAKE; SERUM CREATININE; COUNTRIES; EQUATION; FAT
제목
Dietary patterns associated with the new onset of chronic kidney disease using clustering algorithm
저자
Park, Dougho; Kim, Jinmi; Kim, Da Woon; Lee, Donghyun; Kim, Taeyeon; Koo, Dahyeon; Lee, Youjin; Kim, Won Hwa; Kim, Hyo Jin
DOI
10.1038/s41598-025-18627-1
발행일
2025-09
유형
Article
저널명
Scientific Reports
권
15
호
1