Key result
Among eight anthropometric indices, CUN-BAE yielded the highest odds ratio (OR 28.306) for identifying metabolic syndrome in type 2 diabetes, with optimal indices varying by age and sex.
Why the study?
Although adiposity is associated with metabolic syndrome risk, which adiposity indices best identify metabolic syndrome in diabetic patients had not been studied.
Which anthropometric index is most effective for identifying metabolic syndrome in middle-aged and elderly Chinese patients with type 2 diabetes?
Cross-Sectional (n=906)
Which anthropometric index is most effective for identifying metabolic syndrome in middle-aged and elderly Chinese patients with type 2 diabetes?
Odds Ratio: 28.306
The most effective anthropometric indicator for identifying metabolic syndrome in type 2 diabetic patients varies across sex and age subgroups.
Index performance for MetS identification in diabetes varies by sex and age; leaves open optimal choice for clinical use.
PURPOSE: Several previous reports have highlighted the association between adiposity and risk of metabolic syndrome (MetS). Although it is necessary to identify which adiposity indices are best suited to identify MetS, no such study has been completed in diabetic patients. The aim of this study was to evaluate the ability of eight anthropometric indices to identify MetS in diabetic, middle-aged and elderly Chinese patients. PATIENTS AND METHODS: A cross-sectional study was conducted in 906 type 2 diabetic patients in Guangxi. RESULTS: The highest odds ratios for the identification of MetS were identified with CUN-BAE (OR = 28.306). The largest areas under the curve (AUCs) were observed for WHtR and BRI in men aged 40-59; CUN-BAE in men aged 60 and over; WHtR, BRI, and TyG in women aged 40-59; and BMI for women aged 60 and over. The weakest indicator for the screening of MetS in type 2 diabetes was the ABSI. CONCLUSION: The most effective anthropometric indicator for the identification of MetS varied across sex and age subgroups.
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Guo et al. (2021) conducted a cross-sectional in Type 2 diabetes (n=906). Anthropometric indices (CUN-BAE, WHtR, BRI, TyG, BMI, ABSI) was evaluated on Identification of metabolic syndrome (MetS) (OR 28.306). Among eight anthropometric indices, CUN-BAE yielded the highest odds ratio (OR 28.306) for identifying metabolic syndrome in type 2 diabetes, with optimal indices varying by age and sex.
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