ANALYSIS OF CORRELATIONS BETWEEN BASIC AND DERIVED ANTHROPOMETRIC INDICES AND BODY FAT IN INDIVIDUALS WITH TYPE 2 DIABETES

58. KONGRES ANTROPOLOŠKOG DRUŠTVA SRBIJE (ADS 2025), [pp. 10-19]

AUTHOR(S) / AUTOR(I):  Maja Šibarević , Jelena Malinović Pančić , Tamara Dojčinović , Bojana Carić , Rajko Roljić , Elvira Hadžiahmetović Jurida

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DOI: 10.46793/ADS25.10S

ABSTRACT / SAŽETAK:

Anthropometric indices play a key role in medicine, particularly in assessing body composition, obesity, and the risk of metabolic disorders. The aim of this study is to examine the relationship between basic and derived anthropometric indices and body fat percentage in patients with type 2 diabetes. The sample comprised 160 people with an average age of 65.3 years. Body weight, height, waist circumference (WC), and hip circumference (HC) were measured. Body fat percentage was determined using a bioelectrical impedance analysis (BIA) device, Omron BF-511. Derived anthropometric indices were calculated: BMI (body mass index), WHtR (waist-to-height ratio), WHR (waist-to-hip ratio), BRI (body roundness index), BAI (body adiposity index), CI (conicity index), and AVI (abdominal volume index). Pearson’s correlation coefficient was used for statistical analysis. The strongest positive correlation with body fat percentage was shown by BAI (r=0.553; p<0.001), BMI (r=0.551; p<0.001), BRI (r=0.529; p<0.001), and WHtR (r=0.510; p<0.001), compared to WC (r=0.362; p<0.001) and HC (r=0.461; p<0.001), which had weaker correlations than the derived indices, indicating their greater reliability in assessing body composition. On the other hand, WHR (r=0.052; p=0.516) and CI (r=0.159; p=0.045) showed the weakest associations, suggesting they are not reliable indicators of body fat. Since certain anthropometric indices exhibited a moderate correlation with the BIA-derived body fat assessment, the findings indicate that additional methods should be utilized to improve the accuracy of body fat estimation.

KEYWORDS / KLJUČNE REČI:

anthropometric indices, bioelectrical impedance analysis, type 2 diabetes

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