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Association Between Anthropometric Indices and Presence of Type 2 Diabetes Mellitus in Obesity
Shehla Shaikh1, Sambit Das2, Sunil Kota3
1Department of Endocrinology, Saifee Hospital, Mumbai, Maharashtra, India.
Introduction:
Obesity and type 2 diabetes mellitus (T2DM) are global challenges, with obesity increasing risk of T2DM. Body mass index (BMI), the conventional measure of obesity, may not accurately predict metabolic risk, especially in Asian individuals. Evaluation of alternative anthropometric indices may offer additional approaches for risk assessment.
Methods:
The multicenter, cross-sectional study examined whether anthropometric indices-such as waist, hip, neck, calf, and wrist circumferences, as well as waist-hip, neck-height, and waist-calf ratios-are associated with T2DM in adults with obesity. The study included 750 adults (BMI ≥ 25 kg/m2) recruited from four endocrinology centers across India. Anthropometric and clinical data were recorded using a standardized electronic form.
Results:
T2DM was present in 73% of the cohort (81.6% of men, 67% of women). Obesity classes did not reliably predict the diabetes risk. In men, univariate analysis showed that T2DM increased with age [odds ratio (OR) 1.09, 95% confidence interval (CI) 1.06-1.12, p < 0.001], higher pulse rate (OR 1.03, 95% CI 1.00-1.06, p = 0.04), lower BMI (OR 0.94, 95% CI 0.88-1.00, p = 0.048), higher waist-hip ratio (WHR) (OR 2.63, 9% CI 1.45-4.76, p = 0.001), and neck-height ratio (NHR) (OR 3.35, 95% CI 1.05-10.65, p = 0.041). On logistic regression analysis, age, pulse rate, WHR, and NHR independently predicted diabetes in men. In women, T2DM was more prevalent with increasing age (OR 1.09, 95% CI 10.7-1.11, p < 0.001), higher systolic blood pressure (OR 1.05, 95% CI 1.03-1.06, p < 0.001), lower weight (OR 0.98, 95% CI 0.97-1.00, p = 0.032), higher neck circumference (OR 1.10, 95% CI 1.05-1.16, p < 0.001), and NHR (OR 7.83, 95% CI 3.52-17.42, p < 0.001), on univariate analysis. On logistic regression analysis, age, systolic blood pressure, and NHR retained statistical significance. Receiver operating characteristic analysis generated an optimal NHR cutoff of 0.24 (AUC 0.63) for predicting T2DM with moderate discriminatory ability.
Conclusion:
NHR showed the strongest association with T2DM risk in both men and women, although with moderate discriminatory ability. Additionally, WHR may be associated with risk of T2DM only in men. Anthropometric measures, such as NHR and WHR, may complement BMI, but require validation in larger multiethnic cohorts.
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