Correlation analysis of anthropometric indices and type 2 diabetes mellitus in residents aged 60 years and older

BACKGROUND AND PURPOSE: In recent years, the incidence of obesity in people aged 60 and over has increased significantly, and abdominal obesity has been recognized as an independent risk factor for diabetes. Aging causes physiologic decline in multiple body systems, leading to changes in obesity indicators such as BMI. At present, the relationship between abdominal obesity markers and Diabetes mellitus (DM) in people aged 60 years and older remains unclear. Therefore, it is necessary to study the correlation between anthropometric indices and diabetes and explore potential predictors. METHODS: The basic demographic information of participants aged 60 and above in Zhongshan City in 2020 was collected. Physical parameters, blood glucose and other biochemical indices were measured comprehensively. Binary logistic regression analysis was used to explore the relationship between abdominal obesity indicators [Waist circumference, Neck Circumference, Waist-to-hip ratio, Chinese Visceral Obesity Index (CVAI), and visceral obesity index] and diabetes mellitus. ROC characteristic curve was used to analyze the predictive ability of abdominal obesity indicators to DM, and the non-restrictive cubic spline graph was used to visualize the screened obesity indicators and diabetes risk. RESULTS: Among 9,519 participants, the prevalence of diabetes was 15.5%. Compared with low CVAI, High CVAI level was significantly associated with increased prevalence of DM in males and females (all p < 0.05), in males (OR, 2.226; 95%CI: 1.128–4.395), females (OR, 1.645; 95%CI: 1.013–2.669). After adjusting for potential confounding factors, there were gender differences between neck circumference and the prevalence of DM, and above-normal neck circumference in males was significantly associated with increased prevalence of DM (OR, 1.381; 95% CI: 1.091–1.747) (p < 0.05). CONCLUSION: Among these anthropometric indices, CVAI is consistent with the features of fat distribution in older individuals and shows superior discriminative power as a potential predictor of DM, compared to traditional anthropometric parameters.