Journal of Family Medicine and Primary Care (Jun 2024)

Unravelling the obesity maze in diabetic patients: A comparative analysis of classification methods

  • M Yogesh,
  • Mansi Mody,
  • Naresh Makwana,
  • Samyak Shah,
  • Jenish Patel,
  • Samarth Rabadiya

DOI
https://doi.org/10.4103/jfmpc.jfmpc_1255_23
Journal volume & issue
Vol. 13, no. 6
pp. 2283 – 2288

Abstract

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Background: Obesity is a significant health concern among individuals with type 2 diabetes mellitus (T2DM). Emerging evidence suggests that alternative measures, such as abdominal girth (AG) and body fat percentage (BF%), can provide a more accurate reflection of obesity-related metabolic risks in diabetic populations. This study aimed to compare the accuracy of different obesity classification methods, including BMI, AG, and BF%, among individuals with T2DM. Methodology: This was an observational cross-sectional study conducted among T2DM patients who came to the non-communicable diseases clinic of GG Govt Hospital, Jamnagar, Gujarat during the period of March–April 2023. Demographic and anthropometric information was collected. Body fat analysis was done using a validated Omron fat analyzer. Results: The study found the sensitivity of BMI in males and females as 41.6% and 45% against BF%, respectively. It also showed that the sensitivity of BMI in males and females was 38% and 40.7%, respectively, against AG. The present study also found a moderate positive correlation (r = 0.575) between AG and BF% in individuals with T2DM. Conclusion: The findings indicate that BF% and AG provide valuable insights into adiposity, surpassing the limitations of BMI as a measure of body composition. BF% is an indicator of body fat content, whereas AG serves as a proxy for central adiposity. The correlations between BF% and AG suggest that excess abdominal fat accumulation signifies increased body fat. By incorporating measures such as BF% and AG alongside BMI, clinicians can obtain a more comprehensive understanding of body composition and its relationship with metabolic abnormalities.

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