Abstract

Background: It is now evident that type 2 diabetes mellitus (DM) will have severe consequences if left untreated or poorly managed. Anthropometric measurements such as waist circumference (WC) and body mass index (BMI) are relatively easy to perform, non-invasive nature, and at the same time, they may have significant correlation with parameters like lipid profile. Even though the findings of invasive procedures like lipid profile measurement will have greater value in estimating cardio vascular diseases (CVD) risk in type 2 DM, there is a need for finding alternative approach for risk evaluation having attributes of applicability, adaptability, accessibility, and affordability.

Aims and Objectives: This study aims to study and compare parameters such as BMI, WC, and lipid profile in patients of Type 2 DM and also in age- and sex-matched healthy persons.

Materials and Methods: Anthropometric measures (BMI and WC) and lipid profile were compared and their correlation was studied in male patients with Type 2 DM (Group 2) and normal healthy male subjects (Group1) of age group 40–60 years. Results on continuous measurements are presented on Mean ± SD (Min-Max) and significance was assessed at 5% level of significance. Student’s t-test (two tailed, independent) has been used to find the significance of study parameters. Pearson’s correlation has been used to find the correlation of BMI and WC with lipid parameters.

Results: This study clearly shows that all the lipid fractions such as triglycerides (TGs), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and very LDL-C (VLDL-C) are abnormally elevated in Type 2 DM (Group 2) when compared to controls (Group 1) except high-density lipoprotein cholesterol (HDL-C). Both BMI and WC showed a strongly positive correlation with TG and VLDL and a weakly positive correlation with TC. Furthermore, BMI and WC showed a negative correlation with HDL-C.

Conclusion: Thus, simple anthropometric measures such as BMI and WC can independently contribute to the prediction of risk factors of CVD and can be routinely used to identify those at risk.

Key words: Body Mass Index; Waist Circumference; Low-density Lipoprotein; High-density Lipoprotein