Weight-Adjusted Waist index as an Independent Predictor of Sarcopenia in Patients with type 2 Diabetes Mellitus
DOI:
https://doi.org/10.34256/ijk25211Keywords:
Sarcopenic, Type 2 diabetes mellitus, Anthropometry, Weight-adjusted waist index, Indian populationAbstract
Introduction: Diabetes, and sarcopenia frequently co-occur and adversely affect muscular strength, body composition, and functional performance in adults. Identifying anthropometric markers that effectively distinguish individuals with and without these conditions is crucial for early screening and intervention. Methods: We compared diabetic and non-diabetic groups on physical attributes—handgrip strength, calf circumference (CC), and six-meter walk test (6MWT). We evaluated anthropometric indices, including waist-to-height ratio (WHtR), waist circumference (WC), waist-to-hip ratio (WHR), and weight-adjusted waist index (WWI), using Receiver Operating Characteristic (ROC) curves (AUC) and Youden’s J statistic. Results: We found WWI showed the highest discriminative ability with an AUC of 0.745 (95% CI: 0.630–0.859) and the highest Youden Index (0.445), indicating the best overall balance between sensitivity and specificity. WHtR demonstrated the highest sensitivity (0.806), while WHR achieved the highest specificity (0.977) and the best positive predictive value (PPV = 0.857). WWI also provided the highest negative predictive value (NPV = 0.767). Collectively, these findings highlight WWI as the strongest overall predictor, with WHtR and WHR showing complementary strengths in sensitivity and specificity, respectively. Conclusion: Establishing simple, cost-effective anthropometric cutoffs for sarcopenia in Indian diabetics may facilitate early diagnosis in routine clinical and community settings, enabling timely intervention and improved outcomes. WWI may be considered to be included in clinical and public health screening programs targeting individuals at risk for diabetes, sarcopenia related functional decline.
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Copyright (c) 2025 Anil Kumar Yadav, Manjusha Shinde, Alpa Nasrin Samuel Shaikh, Rubia Mondal, Arpita Chakraborty, Subhadeep Ghoshal, Aruna Raju, Boudhayan Das Munshi, Tandra Ghosh
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