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논문분류	춘계학술대회 초록집
제목	Interaction Between Metabolic Syndrome and Phthalate Exposure in Chronic Kidney Disease Risk Based on Machine Learning and RERI Analysis
저자	Wooin Sim
출판정보	2026; 2026(1):
키워드	Chronic Kidney Disease, Metabolic Syndrome, Phthalates, Interaction, Machine Learning
초록	Objectives: This study aimed to investigate whether the associations between environmental phthalate exposure and chronic kidney disease (CKD) are modified by the presence of metabolic syndrome (MetS). In addition, we evaluated the quantitative interaction effects between phthalate exposure and MetS. Methods: We analyzed data from 4,746 participants in the National Health and Nutrition Examination Survey (NHANES). Variable importance was identified using machine learning algorithms with SHAP value interpretation. Subsequently, confounder-adjusted logistic regression analyses stratified by MetS status were performed. To account for multiple comparisons, the Benjamini–Hochberg procedure was applied (false discovery rate q < 0.05). Additive interaction was assessed by calculating the relative excess risk due to interaction (RERI) and the attributable proportion (AP). Results: Among individuals with MetS, elevated concentrations of four phthalate metabolites (MBzP, MEHHP, MEOHP, and MECPP) were significantly associated with increased CKD prevalence. RERI analysis indicated a statistically significant additive interaction between MetS and high phthalate exposure. Approximately 18% to 46% of the excess CKD risk (maximum AP = 0.462) was attributable to this interaction. In contrast, in individuals without MetS, an inverse association was observed between urinary phthalate concentrations and CKD risk, suggesting differences in susceptibility across metabolic states. Conclusion: Metabolic syndrome may increase susceptibility to the nephrotoxic effects of phthalates, thereby elevating CKD risk. These findings highlight the importance of considering underlying metabolic status in environmental exposure assessments and risk evaluation strategies.
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