Association of weight-adjusted waist index and diabetic kidney disease in type 2 diabetes mellitus

• Verfasst von: Ding, Yunyi [VerfasserIn]
• Verfasst von: Lv, Siyao [VerfasserIn]
• Verfasst von: Xie, Ruijie [VerfasserIn]
• Verfasst von: Ye, Wei [VerfasserIn]
• Verfasst von: Luo, Yichen [VerfasserIn]
• Verfasst von: Li, Yayu [VerfasserIn]
• Titel: Association of weight-adjusted waist index and diabetic kidney disease in type 2 diabetes mellitus
• Verf.angabe: Yunyi Ding, Siyao Lv, Ruijie Xie, Wei Ye, Yichen Luo, Yayu Li
• Jahr: 2024
• Umfang: 10 S.
• Illustrationen: Diagramme
• Fussnoten: Online veröffentlicht: 4. März 2024 ; Gesehen am 09.09.2024
• Titel Quelle: Enthalten in: Endocrine Connections
• Ort Quelle: Bristol : BioScientifica, 2012
• Jahr Quelle: 2024
• Band/Heft Quelle: 13(2024), 4, Artikel-ID e230491, Seite ?
• ISSN Quelle: 2049-3614
• DOI: doi:10.1530/EC-23-0491
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: cross-sectional study
• Sach-SW: diabetic kidney disease
• Sach-SW: NHANES
• Sach-SW: obesity
• Sach-SW: weight-adjusted waist index
• K10plus-PPN: 1902190017

Abstract

Objective The aim of this study was to investigate the relationship between weight-adjusted-waist index (WWI) and diabetic kidney disease in individuals afflicted with type 2 diabetes. Methods Comprehensive data were ascertained from the National Health and Nutrition Examination Survey in 2013-March 2020. Weighted univariate, multivariate logistic regression models, subgroup analyses and tests for interaction were performed. Additionally, we employed smooth curve fitting to assess linear correlations and the threshold effects were calculated by applying a binary linear regression model. Breakpoints are identified by a model with maximum likelihood ratio and a two-step recursive approach. Receiver operating characteristic curve (ROC) along with the area under the curve (AUC) value predict the capability of WWI and body mass index for diabetic kidney disease. Results A total of 10,661 individuals diagnosed with type 2 diabetes were included, and the overall prevalence of diabetic kidney disease was 20.74%. WWI exhibited a positive correlation with the likelihood of diabetic kidney disease in type 2 diabetes patients (OR: 1.17, 95% CI: 1.03-1.33). The results of subgroup analysis showed significant interaction for gender (P < 0.05). Among female patients, U-shaped correlations were observed with a breakpoint at 11.48. Additionally, weight-adjusted waist index (AUC = 0.664) proved to be a more effective predictor of diabetic kidney disease compared to body mass index (AUC = 0.555). Conclusion In patients with type 2 diabetes, increased weight-adjusted-waist index is implicated with an increased risk of diabetic kidney disease. WWI can be used as a new anthropometric index to predict diabetic kidney disease, and its predictive ability is stronger than body mass index.