• Jiyoung Hwang, Hyesook Kim, and Oran Kwon.
• Department of Nutritional Science and Food Management, Ewha Womans University, Seoul, Republic of Korea; Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul, Republic of Korea.
• Nutrition. 2024 Sep 1; 125: 112491112491.

ObjectiveThe aim of this study was to identify dietary patterns associated with diabetes in Korean adults and to investigate their association with diabetes risk in both a cross-sectional and prospective study.MethodsPredefined food groups collected by the Korea National Health and Nutrition Examination Survey (KNHANES 2015-2018, n = 19 721) were entered in a reduced rank regression (RRR) model, followed by stepwise linear regression analyses to identify the most predictive dietary patterns. We evaluated the construct validity of dietary patterns in two independent samples from KNHANES 2019 to 2021 (n = 14 223) and the Health Examinees (HEXA) cohort study (n = 30 013). Associations between dietary patterns and diabetes risk were examined using multivariable regression and multivariable-adjusted Cox proportional hazard models, respectively.ResultsA dietary pattern was identified with high positive loadings for refined white rice, kimchi and salted vegetables, wheat flour and bread, and seasonings, and high negative loadings for whole grains, legumes with tofu and soymilk, poultry, eggs, and plant oils. The higher pattern scores were significantly associated with diabetes risk in KNHANES 2015 to 2018 (male: odds ratio [OR]: 1.59; 95% confidence interval [CI]: 1.35, 1.88; female: OR: 1.37; 95% CI: 1.18, 1.52), KNHANES 2019 to 2021 (male: OR: 1.47; 95% CI: 1.01, 1.69; female: OR: 1.37; 95% CI: 1.18, 1.54), and HEXA study (male: hazard ratio [HR]: 1.10; 95% CI: 1.01, 1.34; female: HR: 1.24; 95% CI: 1.02, 1.52).ConclusionsDietary patterns derived by RRR followed by stepwise linear regression analyses were associated with increased risks of diabetes among Korean adults.Copyright © 2024 Elsevier Inc. All rights reserved.

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