## 4 Discussion
These differences may also be due to the model of body composition measurement equipment used. Accuracy varies widely among BIA instruments [33]. Many variables can also distract the measurement, e.g., hydration status in the case of BIA or body position in the case of ADP [1,34]. Similar, though not identical, equipment (MF-BIA: InBody 720) was used by Sullivan et al. [35] to compare BIA and ADP body composition values in a homogeneous obese population (BMI > 30.0 kg/m\({}^{2}\)). They observed no differences in %BF between BIA and ADP. In addition, significant correlations were observed, accompanied by low SEE values. These findings are partially consistent with our results in the subgroup of overweight participants (BMI \(\geq\) 25 kg/m\({}^{2}\)) compared to the normal-weight subgroup (Table 4). These results may also be related to the BMI, the mean values of which are within the normal range for both sexes but do not necessarily reflect normal body composition. Our findings showed that less than 8% of the female group were classified as overweight based on BMI, while BIA results indicated central obesity in 37% of them, and only 6% had excess fat, according to FMI. Similarly inconsistent results were reported by [PERSON] et al. [36], where 22.1% of females had a BMI > 24.9, yet WHR and %BF were abnormally high in 50.4% and 44.3% of them, respectively. This leads to different interpretations of the health risks associated with high body fat. Furthermore, the FMI, calculated based on fat mass, has been proposed as a more reliable marker than BMI or %BF for identifying metabolic syndrome [25]. Classification of excess body fat based on FMI did not align with BMI estimates in our sample. Additionally, discrepancies in classification between ADP and BIA across the group make accurate assessments challenging. However, the findings of the large study by [PERSON] et al. [37] suggest that BMI performed similarly to body fat-based indicators in identifying cardiometabolic outcomes. These estimates require further research. Currently, many different indices have been proposed for the diagnosis of central obesity, such as WC, WHR, and WHtR. Existing evidence suggests that central obesity is more strongly associated with cardiometabolic risk factors and chronic disease risk than overall obesity. As a result, indices of central obesity may be more accurate than BMI in estimating adiposity and could, therefore, be more closely linked to the risk of mortality [15]. WC is considered the best and most simple measure of visceral fat and may be the best indicator for predicting cardiovascular risk factors. Advances in BIA devices have made it possible to estimate WC using special algorithms. However, available studies and our results showed clear differences between BIA estimates and manual measurement [14,38,39,40]. The Bland-Altman analysis prepared by [PERSON] et al. [14] on 597 elderly individuals (mean age 64.6 \(\pm\) 10.1 years) showed that bias was negative in both females and males, suggesting underestimation using BIA compared with manual measurements. This contrasts our results, where BIA overestimated WC in the total and female groups, but this may be due to age discrepancies. Comparable findings were observed in the study by [PERSON] et al. [41], where BIA-estimated WC values were significantly higher than manual measurements in a group of 1496 middle-aged individuals. Similarly, the estimation of central obesity based on WHR was statistically different between manual measurements and BIA results in our study, leading to an overestimation of the results based on BIA in the total and female groups. WHR was also'measured' by BIA in the study by [PERSON] et al. [38] on a cohort of 10,030 middle-aged adults. WHR calculated by BIA in this study was higher than measured manually, but these methods were not compared directly to each other. [PERSON] et al. [42] noted that WHR measured by BIA was significantly higher compared to anthropometry. [PERSON] et al.