## 3 Results
### The Bland-Altman Analysis  
As shown in Figure 1A-G, the Bland-Altman graph plots represent the differences between the BF% measured using the BIA and estimated using the CUN-BAE against the average of the measurement in the comparison sample of elite athletes and the subsamples stratified by sex, age, and sport discipline.  
The differential bias (\(\alpha\)) of \(-2.7\) (95% CI: \(-6.5;7.1\)) units was represented by the gap between the \(x\)-axis in the sample of elite athletes. The data suggested that on average, the CUN-BAE method measured 2.7% more BF than the BIA, as the mean difference  
Figure 1: (**A–G**) Bland–Altman plots showing the limits of agreement between BF% measured using the BIA and estimated using the CUN-BAE in the comparison sample of elite athletes and the subsamples stratified by sex, age, and sport discipline: (**A**) Elite athletes (total): the differential bias \(\alpha\) (differential bias): \(-2.7\), 95% CI: \(-6.5;7.1\) and no \(\beta\) (proportional bias): \(-0.2\); 95% CI: \(-0.3\); \(-0.2\). (**B**) Elite male athletes: \(\alpha\): 0.8, 95% CI: \(-5.8;7.3\) and \(\beta\): \(-0.1\); 95% CI: \(-0.2\); \(-0.01\). (**C**) Elite female athletes: \(\alpha\): \(-2.9\); 95% CI: \(-6.9\); 2.0 and no \(\beta\): \(-0.03\); 95% CI: \(-0.1\); 0.1. (**D**) Elite athletes aged 14–18: \(\alpha\): \(-0.03\); 95% CI: \(-5.0\); 5.0 and no \(\beta\): \(-0.2\); 95% CI: \(-0.2\). (**F**) Elite athletes aged 18–33: \(\alpha\): \(-0.6\); 95% CI: \(-9.1\); 7.9 and \(\beta\): \(-0.4\); 95% CI: \(-0.5\); \(-0.2\). (**F**) Strength–power athletes: \(\alpha\): \(-0.1\); 95% CI: \(-7.7\); 7.4 and no \(\beta\): \(-0.2\); 95% CI: \(-0.3\); \(-0.1\). (**G**) Endurance athletes: \(\alpha\): \(-0.4\); 95% CI: \(-6.6\); 5.9 and \(\beta\): \(-0.3\); \(-0.2\). Dashed lines represent 95% limits of agreement; \(y=0\) is a line of the perfect average agreement. The middle red lines indicate the mean difference between the measured and estimated BF%. Dotted black lines represent the correlation lines. BIA—bioelectrical impedance analysis; BF—body fat; CUN-BAE—the body fat prediction equation; 95% CI—confidence interval.  
was nonzero. However, the Bland-Altman graph plots represented the differences in the differential biases depending on the elite athletes' age, sex, and sport discipline. More specifically, on average, the CUN-BAE method measured 2.9% more BF; however, the narrower limit of agreement range was \(\pm\)4.5 BF% (from \(-\)6.9 to 2.0 BF%) in the sample of female athletes. In the meantime, more favorable agreement was observed between the CUN-BAE method and the BIA in the subsamples of elite athletes aged 14-18 (\(\alpha\): \(-\)0.03; 95% CI: \(-\)5.0; 5.0) and those competing in strength and power sports (\(\alpha\): \(-\)0.1; 95% CI: \(-\)7.7; 7.4). Overall, more than 50% of the values were observed inside the limit, which indicated that there was agreement between the two assessment methods in all groups of athletes under analysis.  
As displayed in Figure 1A-G, the variability in the proportional differences (proportional biases (\(\beta\))) between the two measurements tended to become smaller (the \(\beta\) values ranged from \(-\)0.4 to \(-\)0.1, and the 95% CIs ranged from \(-\)0.5 to \(-\)0.2) as the averages increased in the subsamples of elite male athletes, those aged 18 or over, and those competing in endurance sports. Thus, in the athlete subsamples mentioned above, the existence of proportional biases indicated that the two methods, namely the CUN-BAE and BIA, did not agree equally through the range of measurements.