Patterns of bioelectrical impedance vector ... - Data-input.de

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TABLE 3 Impedance vector components in 9707 girls and 5898 boys by BMI and age classes 1 n Height R Xc H 2 /R H 2 /Xc r m cm 2 / cm 2 / Age 6–9 y Girls BMI 9–13 72 1.20 0.11 879.4 94.9 78.4 14.9 16.86 4.61 191.5 52.6 0.77 BMI 13–15 853 1.19 0.06 829.5 74.5 74.8 32.1 17.44 2.80 197.2 34.9 0.71 BMI 15–17 1168 1.21 0.08 777.9 71.2 72.0 12.0 19.19 3.60 209.5 40.3 0.65 BMI 17–25 Boys 879 1.30 0.14 714.1 79.8 67.8 9.6 24.72 8.02 259.4 75.6 0.91 BMI 9–13 39 1.19 0.06 858.2 97.2 72.0 12.7 16.85 2.51 204.1 39.7 0.74 BMI 13–15 860 1.20 0.06 787.8 63.0 69.6 9.4 18.59 2.68 214.4 71.3 0.33 BMI 15–17 1194 1.22 0.07 734.5 66.7 67.1 9.4 20.62 9.35 225.3 44.5 0.27 BMI 17–25 Age 10–13 y Girls 670 1.28 0.11 676.8 70.3 64.5 8.8 25.04 6.55 263.1 62.1 0.84 BMI 11–15 190 1.41 0.07 816.0 78.1 74.4 9.9 24.54 3.57 272.7 55.2 0.74 BMI 15–20 1113 1.44 0.09 733.4 79.1 69.9 9.8 28.86 5.50 304.5 61.5 0.77 BMI 20–25 748 1.53 0.11 653.0 71.5 63.8 8.5 36.64 7.92 376.1 80.7 0.84 BMI 25–30 654 1.59 0.09 586.3 62.8 58.7 7.4 43.92 7.82 439.7 80.4 0.80 BMI 30–35 Boys 293 1.63 0.08 538.9 55.1 55.2 7.8 49.75 7.55 490.2 86.6 0.73 BMI 11–15 186 1.42 0.06 786.2 72.0 72.1 8.9 25.93 3.84 285.1 51.0 0.78 BMI 15–20 1125 1.44 0.07 701.2 68.0 67.3 8.7 29.91 4.86 313.9 58.0 0.77 BMI 20–25 484 1.51 0.10 636.0 74.2 62.5 7.9 36.60 8.91 372.2 84.9 0.81 BMI 25–30 379 1.57 0.10 576.3 62.0 57.9 6.9 43.61 8.74 433.9 82.6 0.84 BMI 30–35 Age 14–17 y Girls 165 1.63 0.11 527.5 60.8 53.0 6.4 51.27 10.93 508.3 95.0 0.81 BMI 14–19 157 1.68 0.06 697.8 73.4 68.5 10.3 40.78 5.30 420.9 75.3 0.71 BMI 19–25 1138 1.67 0.06 624.4 65.9 64.7 8.5 45.40 5.79 441.3 69.8 0.72 BMI 25–30 1375 1.67 0.06 578.0 57.8 61.3 8.1 48.61 6.15 462.1 73.6 0.71 BMI 30–35 796 1.67 0.07 541.8 53.9 57.1 7.7 52.10 6.55 489.9 79.5 0.73 BMI 35–40 Boys 271 1.67 0.07 504.5 54.2 53.7 7.7 55.90 7.94 529.9 92.2 0.75 BMI 14–19 34 1.74 0.12 627.4 72.8 62.7 8.1 49.31 9.97 494.1 100.1 0.85 BMI 19–25 167 1.76 0.09 530.6 62.0 59.1 8.5 59.31 10.01 535.7 100.7 0.73 BMI 25–30 252 1.75 0.10 513.8 64.7 55.6 6.8 60.82 12.06 558.8 96.1 0.75 BMI 30–35 249 1.76 0.09 479.4 58.5 52.3 6.9 66.02 11.68 605.0 99.2 0.74 BMI 35–40 94 1.77 0.09 443.6 50.4 48.9 6.4 72.16 11.28 656.0 107.3 0.55 1 2 2 2 BMI is in kg/m . R, resistance; Xc, reactance; H, height; r, correlation coefficient between H /R and H /Xc. ANOVA showed significant interactions between age and BMI categories for both vector components (H 2 /R and H 2 /Xc). were stratified into 7 age groups (18–19, 20–29, 30–39, 40–49, 50–59, 60–69, and 70 y). Shown in Tables 1–3 are all the parameters necessary for calculation of the respective confidence or tolerance ellipses in subgroups of women (Table 1), men (Table 2), and children and adolescents (Table 3). The size of the confidence ellipses was influenced by the variability of the vector components and the sample size (smaller ellipses from a greater number of subjects with a similar SD). The shape of both the tolerance and the confidence ellipses was determined by the coefficient of correlation between H 2 /R and H 2 /Xc (more flat and elongated shape with a higher correlation). The sex and BMI dependency of the vector distribution patterns within age classes (95% confidence ellipses) for adults is shown in Figure 1. Within a BMI and age category, vectors for women were significantly shorter than those for men. With decreasing BMI, there was a progressive shortening of the impedance vectors with a combined decrease of both the H 2 /R and the H 2 /Xc components, without overlapping of confidence ellipses. EFFECT OF AGE ON IMPEDANCE VARIABLES 63 In Figure 2, 95% confidence ellipses were plotted for subgroups of children and adolescents. Mean impedance vectors in children were shorter than in adults, and a gradual vector shortening was observed with decreasing age. Sex differences in vector distribution were already apparent in children, although they were less pronounced than in adults. Longer vectors were found in boys than in girls of the same age and BMI group, without a difference in mean vector direction between the sexes. In Figure 3, the age dependency of mean vector placement is apparent as a continuous down-sloping of the mean vector as the result of a decrease in the H 2 /Xc component with decreasing age. By contrast, the H 2 /R component within each sex and BMI group remained fairly constant with increasing age. In Figure 4, 35 795 women were divided into 6 groups of a certain BMI and 6 age ranges. This classification required a large sample size and could therefore not be done in men because of insufficient numbers in individual BMI categories. As shown in Figure 4A, the H 2 /R component increased with increasing BMI (P 0.05 for all age groups), whereas there was no consistent change or even a slight
64 BOSY-WESTPHAL ET AL FIGURE 1. Mean impedance vectors with 95% confidence ellipses from subjects stratified by age and BMI groups [BMI (in kg/m 2 ) groups were as follows: 18.5–25, 25–30, 30–35, 35–40, and 40–50]. Within each graph, the ellipse sequence on the left represents women and that on the right represents men. Within each sex, vector shortening is observed with decreasing BMI; ie, the lowest BMI group is represented by the shortest vector and the highest BMI group by the longest vector. H, subjects’ height; R, resistance; Xc, reactance. The figure is based on data from 29 674 men and 179 429 women. The numbers of subjects in each BMI and age category are given in Tables 1 and 2. Graphically nonoverlapping 95% confidence ellipses are significantly different from each other, P 0.05 (conterminous with a significant Hotelling’s T 2 test). decrease in the H 2 /R component with age. Concomitantly, a prediction equation for body composition that relied on H 2 /R, R, and weight (11) did not show an age-related increase but rather a slight decrease in percentage fat mass in these women (Figure 4B). By contrast, the H 2 /Xc component decreased with increasing BMI and age (Figure 4C), which resulted in a decrease in body cell mass (calculated by the manufacturer’s algorithm as total body water/0.732 phase angle constant) with age in each BMI group (Figure 4D). DISCUSSION We established a large database of impedance vector distributions that exceeds current databases with respect to numbers and BMI and the age ranges covered. We used the database to analyze age-related changes in the vector components H 2 /R and H 2 /Xc with respect to their effects on body-composition analysis. The main result of our study was the insensitivity of conventional BIA to age-related changes in fat mass. Applications for vector BIA The RXc graph is a probability chart that relates an individual vector according to the mean value of the reference population (9). Sex-, BMI-, and age-specific vector distribution patterns 1) contribute to a better understanding of the factors influencing impedance results, 2) may be used a healthy reference when individual patient data are analyzed, and 3) serve as a quality criterion for BIA results before the application of algorithms to calculate total body water or fat-free mass. The comparison with reference vector distributions allows one to discriminate between impedance values that 1) lie within the normal range (and may therefore reasonably be converted into total body water or fat mass) or 2) lie outside the respective reference range and thus must not be converted into total body water or fat mass. If an individual vector does not match with its sex-, BMI-, and agespecific reference distribution, this is explained by either a measurement error (eg, false placement of electrodes) or increased or decreased hydration fraction of the fat-free mass (eg, in case of edema or dehydration). Vector BIA thus can be used as a measure of quality control to prevent misinterpretation of impedance readings and thus erroneous predictions of body compartments. A comparison of an individual impedance measurement with a reference database is easily achieved by using tolerance ellipses of the RXc graph. Tolerance ellipses are bivariate percentiles indicating the probability that an individual measurement falls at
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