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

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/m<sup>2</sup>. 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.

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Publication Details

Journal
Scientific Reports
Published
2025-09-29
DOI
https://doi.org/10.1038/s41598-025-18627-1
Citations
1
Primary Topic
Liver Disease Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
1.35

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article

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

Dae Lim Koo, Dougho Park, Won Hwa Kim, Jinmi Kim et al.
1 citations
Scientific Reports
Liver Disease Diagnosis and Treatment
1.35
article

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

Dae Lim Koo, Dougho Park, Won Hwa Kim, Jinmi Kim, Hyo Jin Kim, Dong-Hyun Lee, Tae‐Yeon Kim, Youjin Lee, Da Woon Kim
article en
1 citations

Abstract

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/m<sup>2</sup>. 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.

Scientific ReportsVol. 15(1)
Pohang University of Science and Technology (KR), Korea University Medical Center (KR), Sunlin University (KR), Pusan National University Hospital (KR), Pohang TechnoPark (South Korea) (KR)
Korea Disease Control and Prevention Agency, National Research Foundation, Ministry of Science and ICT, South Korea
Openalex Percentile: Top 15%
Liver Disease Diagnosis and Treatment
1.35
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