## 4 Discussion  
This study was designed to initially assess the predictive power of obesity indices in comparison to using FM(FMI) and/or FFM(FFMI). The results of our study confirmed that they can be implemented for obesity diagnosis and replace the questioned BMI. Considering the results of AUC, sensitivity, specificity, and Youden index (\(>\)0.9), fat mass index and percentage of fat mass could be considered the best marker for obesity screening in adults, regardless of sex. In women, the results also confirmed the need of a BIA analysis for sarcopenia obesity diagnosis. Undoubtedly, the current criteria for the diagnosis of obesity for commonly used indicators such as BMI, WC, WHtR, or WHR should be verified taking into account biological differences in body size and composition, including those determined by sex. ABSI had the lowest predictive value for obesity among the analyzed indices, regardless of sex. For the measurement of arm circumference and indicators based on its measurement, a positive moderate correlation with FFM was confirmed; but as an easy-to-use screening tool for the diagnosis of sarcopenia obesity or sarcopenia, this requires further investigation. We found that the optimal BMI cut-offs were slightly below the obesity threshold for both sexes (BMI \(>\) 29.99 kg/m\({}^{2}\)) and were sex-specific. This is in line with the results of [PERSON] et al. (2019), who identified the cut-off points for BMI at 27.5 kg/m\({}^{2}\) in women and 28.1 kg/m\({}^{2}\) in men for screening cardiometabolic risk in an older group of adults. It is necessary to underline that, according to standard BMI quantification, both estimated thresholds indicate overweight, not obesity. Due to the small difference between the common threshold for normal BMI values and the proposed limits for obesity, an increased risk of cardiometabolic disorders may be potentially misclassified, especially in women (2019). For indices of abdominal obesity estimation such as WC, WHtR, and WHR, the optimal cut-off values were close to the established ones (WC \(>\) 88  cm for women and \(>\)102  cm for men; WHtR \(\geq\) 0.5; WHR \(>\) 0.8 for women and 0.9 for men). WHtR lower than 0.5 was previously established as the universal cut-off point for assessing abdominal obesity and cardiometabolic risk (2019), but our results confirmed the need for further research, to establish sex-specific cut-off points for WHtR. Similarly, as indicated by other authors, this index is also ethnic-specific (2020). The optimal cut-off point of BRI was 4.71 in women and 5.59 (or 4.80 according to FM/FFM) in men. These values are lower than those given by [PERSON] (2019), according to whom values above 4.9 for women and 4.612 for men can be used as diagnostic criteria of metabolic disorders. [PERSON] (2019) indicated that the cut-off values of BRI reach values in the range 3.18 and 6.20, and even 1-16 (2019), which may be due to differences in the study group, race, and diagnostic criteria. BRI is a novel index used to assess metabolic disorders, which may also be used for detecting high cardiometabolic risk (2019), metabolic syndrome risk (2019), or diabetes risk (2019), and could be a better predictor than BMI. AVI is used to assess general volume, and it has been highly associated with the dysfunction of glucose metabolism [38]. For Iranian men, it was determined at 16.6, and for women 17.0 [39]. Lower values of AVI, 14.25 for men and 13.03 for women, were established by [PERSON] et al. [40] for predictive metabolic syndrome in the Chinese population. In our findings, the cut-off values for AVI were higher, but the AUC for AVI indicated excellent predictive power for obesity. Compared with other indices, the values of AUC of ABSI showed the lowest predictive power in obesity diagnosis in our study group. ABSI was proposed by [PERSON] and [PERSON], and based on WC, height, and BMI [11; 41]. In previous studies, ABSI appeared to be better than traditional measures, such as BMI, as a measure of metabolic changes [3].