BACKGROUND Chronic kidney disease (CKD) is a major microvascular complication of diabetes and a leading cause of morbidity and mortality. Obesity and visceral fat accumulation contribute to renal dysfunction, but traditional measures such as body mass index may incompletely reflect metabolism-related harm from adipose tissue. Although numerous adiposity indices have been developed, comparative evidence on their associations with CKD in adults with diabetes remains limited. AIM To compare 10 adiposity indices and evaluate their associations and discriminative abilities for CKD among adults with diabetes. METHODS This retrospective cross-sectional study included 3526 adults with diabetes who underwent health examinations at a tertiary hospital. A total of 10 adiposity indices were calculated. CKD was classified as estimated glomerular filtration rate below 60 mL/min/1.73 m2 and/or an albumin-to-creatinine ratio ≥ 30 mg/g. Multivariable logistic regression estimated odds ratios per standard-deviation increase, with additional adjustment. Restricted cubic splines assessed dose-response patterns, and discrimination was evaluated using the area under the receiver operating characteristic curve. RESULTS Among the 3526 participants, 456 (12.9%) had CKD. The CKD group had a higher proportion of men (86.0% vs 80.7%, P = 0.007) and a higher prevalence of hypertension (62.7% vs 46.4%, P < 0.001) compared with the non-CKD group. In both the primary and the comorbidity-adjusted sensitivity models, all examined indices were positively associated with CKD (all P < 0.001). Restricted cubic splines analyses showed no evidence of nonlinearity for body mass index, Chinese visceral adiposity index (CVAI), body roundness index, conicity index, and waist-to-height ratio, whereas the other indices showed evidence of nonlinearity (P < 0.05). CVAI had the highest area under the curve (0.637), whereas a body shape index had the lowest (0.526). CONCLUSION In adults with diabetes, multiple adiposity indices are associated with CKD. CVAI shows the best discrimination and may aid CKD risk assessment.
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Huang et al. (2026) studied this question.
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