Assessment of Anthropometric Variables in Type-2 Diabetes Mellitus among 4,473 Subjects in 10 Wards of Urban Belagavi District, North Karnataka, India: A Community-based Cross-sectional Study

• Published in: Journal of clinical and diagnostic research Vol. 18; no. 5; pp. 01 - 05
• Main Authors: Prabhu, Madhav, Kothiwale, VA, Smitha, KS, Kour, Harpreet
• Format: Journal Article
• Language: English
• Published: JCDR Research and Publications Private Limited 01-05-2024
• Subjects: anthropometry; hyperglycaemia; sedentary lifestyle
• ISSN: 2249-782X; 0973-709X
• DOI: 10.7860/JCDR/2024/67379.19339

Introduction: Type-2 Diabetes Mellitus (T2DM) is a global epidemic and a serious risk for the younger generation. A sedentary lifestyle, urbanisation, and poor dietary choices are cornerstones of diabetes. Early detection of risk factors and prevention of their progression can go a long way in delaying the onset of the disease and reducing the economic burden due to its secondary complications. Aim: To assess anthropometric variables of T2DM among the population in Belagavi, North Karnataka, India. Materials and Methods: A community-based cross-sectional study was conducted among a study population of 4,473 individuals in 10 wards of urban Belagavi district from September 2021 to September 2023 by house-to-house visits. The 10 wards were selected using a random allocation method by computer-generated random sequence. The study population was divided into three groups: the diabetic group, children of the diabetic group, and a healthy non diabetic group (Group-1, Group-2, and Group-3) with population sizes of 649, 855, and 2,969, respectively. Anthropometric parameters were recorded by trained nurses using measuring tapes, stadiometers, and weighing scales. Data were analysed using Statistical Package for Social Sciences (SPSS) 24.0 software. One-way Analysis of Variance (ANOVA) test was used to compare the data between the three groups. The Pearson’s correlation test was used to find the association between Body Mass Index (BMI) and Waist Hip Ratio (WHR). A p-value less than 0.05 was considered significant. Results: There were no significant differences found in anthropometric parameters among the three groups (p>0.05). However, when comparing anthropometric parameters between different generations, a statistically significant difference was observed in Neck Circumference (NC) and WHR. Further, association between BMI and WHR among the three groups revealed that WHR is a better indicator of obesity compared to BMI, with a statistically significant p-value of 0.03. WHR detected 424 (90.4%), 463 (91.32%), and 1,220 (87%) obese cases in Group-1, Group-2, and Group-3, respectively, compared to BMI, which detected 371 (58.51%), 440 (52.25%), and 1,202 (41.91%) obese cases in Group-1, Group-2, and Group-3, respectively. Conclusion: The NC and WHR are better indicators of anthropometric measurements. Anthropometry could be a non invasive, cost-effective predictive tool for the future risk of developing DM. The present study determined there is an impending need to conduct regular screening programs for early identification of anthropometrics other than BMI, WHR, and NC.