Keywords : Body Roundness Index
A Cross Sectional Study to Assess and Compare the Efficiency of Older Anthropometric Measurements with Newer Parameters in Predicting the Risk of Diabetes Mellitus among the Urban Population of Mandya City in Karnataka, India.
European Journal of Molecular & Clinical Medicine,
2022, Volume 9, Issue 8, Pages 1808-1818
Obesity is a major risk factor for Diabetes Mellitus(DM). Older anthropometric measurements like Body Mass Index(BMI), Waist Circumference(WC), Waist Circumference Height ratio(WHt ratio) etc and newer ones like A Body Shape Index(ABSI) and Body Roundness Index(BRI) are used to detect obesity. This study was undertaken to determine the utility of newer and older anthropometric measurements in predicting the risk of DM among urban population of Mandya city.
Methods: Fasting Blood Sugar(FBS) and anthropometric measurements like BMI, WC, WHt ratio, BRI and ABSI were measured. Correlation analysis, Odds Ratio and ROC curves were analyzed to know the ability of each anthropometric measurement in predicting the risk of DM.
Results: Overall prevalence of DM in the study population was 23.4%. All anthropometric measurements except ABSI were significantly high in subjects with DM. According to OR value, WHt ratio(2.254) was the best predictor of DM, followed by BMI(Asia Pacific classification) with 2.16.Older anthropometric measurements such as BMI(r=0.252;p=0.000*), WC(r=0.230;p=0.000) showed a significantly positive correlation with FBS compared to BRI and ABSI. According to ROC curves, the highest AUC was found with older methods such as WC(0.617) and BMI(0.616) followed by WHt ratio(0.595) and newer methods such as BRI(0.595) and ABSI(0.542).
Conclusion: Older anthropometric measurements have better discriminatory powers and significant strength of association with DM compared to newer ones. Establishing newer reference ranges of FBS for Asian population and incorporation of Asia Pacific Guidelines of BMI classification at all levels of health care in India is needed for better risk stratification and the prevention of DM.