Effective and accessible indicators are critical for the early detection and prevention of diabetes. A recent retrospective cross-sectional study, published in Scientific Reports, explored the correlation between the waist-to-calf circumference (WCR) ratio and diabetes risk in a large cohort of participants from the Look-Up trial. Diabetes in the study was defined as either a self-reported diagnosis, fasting plasma glucose levels ≥126 mg/dL, or random plasma glucose levels ≥200 mg/dL.

      The study analyzed data from 8,900 participants (mean age 57.1 ± 14.8 years; 55% women) who underwent comprehensive evaluations. These included a brief questionnaire, objective cardiovascular health measurements, and anthropometric assessments. Waist circumference (WC) was measured at the narrowest point between the ribs and hips at the end of a normal expiration, while the WCR was calculated by dividing the waist circumference by calf circumference (CC). Additional data on daily fruit and vegetable consumption, smoking status, and physical activity levels were also collected. Statistical analyses, including Analysis of Covariance (ANCOVA) and logistic regression, were used to examine the relationship between WCR and diabetes risk.

      The results demonstrated that individuals with diabetes had significantly higher WC compared to those without diabetes, while calf circumference showed no significant differences between the groups. WCR values were notably higher among participants with diabetes than those without. Furthermore, mean WCR displayed a significant trend across normal, pre-diabetes, and diabetes groups. ANCOVA confirmed significant differences in WCR values between these groups. Logistic regression analysis revealed a positive association between higher WCR and diabetes risk, which remained significant even after adjusting for confounding factors.

      While the relationship between WCR and various health outcomes has been gaining attention, its specific association with diabetes has been underexplored. This study highlights WCR as a novel, simple, and cost-effective anthropometric measure for identifying individuals at risk of diabetes. The findings suggest that WCR is particularly suitable for clinical use in resource-limited settings, offering a practical approach to early diabetes detection.