Development of Anthropometry-Based Equations for the Estimation of the Total Body Water in Koreans

Abstract

For developing race-specific anthropometry-based total body water (TBW) equations, we measured TBW using bioelectrical impedance analysis (TBW_BIA) in 2,943 healthy Korean adults. Among them, 2,223 were used as a reference group. Two equations (TBW_K1 and TBW_K2) were developed based on age, sex, height, and body weight. The adjusted R² was 0.908 for TBW_K1 and 0.910 for TBW_K2. The remaining 720 subjects were used for the validation of our results. Watson (TBW_W) and Hume-Weyers (TBW_H) formulas were also used. In men, TBW_BIA showed the highest correlation with TBW_H, followed by TBW_K1, TBW_K2 and TBW_W. TBW_K1 and TBW_K2 showed the lower root mean square errors (RMSE) and mean prediction errors (ME) than TBW_W and TBW_H. On the Bland-Altman plot, the correlations between the differences and means were smaller for TBW_K2 than for TBW_K1. On the contrary, TBW_BIA showed the highest correlation with TBW_W, followed by TBW_K2, TBW_K1, and TBW_H in females. RMSE was smallest in TBW_W, followed by TBW_K2, TBW_K1 and TBW_H. ME was closest to zero for TBW_K2, followed by TBW_K1, TBW_W and TBW_H. The correlation coefficients between the means and differences were highest in TBW_W, and lowest in TBW_K2. In conclusion, TBW_K2 provides better accuracy with a smaller bias than the TBW_W or TBW_H in males. TBW_K2 shows a similar accuracy, but with a smaller bias than TBW_W in females.

INTRODUCTION

The measurement of total body water (TBW) is frequently performed to evaluate the body composition and nutritional status. The accurate measurement of TBW is difficult, and it requires isotopic dilution techniques. Therefore, several indirect equations for estimating the TBW using simple anthropometric variables are commonly employed. However, these equations are largely based on individuals of the western hemisphere.

The purpose of this study was to develop anthropometry-based TBW equations in Korean and to compare these equations with the other available TBW equations. Since it is difficult to perform isotopic dilution techniques on a large number of subjects, we used bioelectrical impedance analysis (BIA), which has been shown to accurately and reliably estimate TBW (1). Therefore, we first measured the TBW using BIA (TBW_BIA) in a large study population to develop an anthropometry-based TBW equation. Then to validate this equation, we analyzed the agreement between the TBW_BIA and the TBW derived from anthropometry-based equations in another control group.

MATERIALS AND METHODS

A total of 2,943 healthy adults were selected for this study from the 3,781 people visiting the Health Promotion Center (HPC) at Inha University Hospital (IUH) from May to December 2003. The exclusion criteria were as follows: age <18 yr, a serum creatinine >1.4 mg/dL, positive urine protein, subjects who complained of edema, those with an amputation or who had diabetes mellitus, congestive heart failure, chronic liver disease, or those subjects who did not allow BIA to be performed. Among them, 2,223 subjects were used for the development of equations. The remaining 720 subjects were used for the validation of equation. This study was approved by the ethical board of IUH.

After 8 hr of fasting, the subjects visited to the HPC at 9 a.m. Their height (Ht) and body weight (BW) were measured to the nearest 0.1 cm and 0.1 kg using a linear height scale and an electronic weight scale, respectively. The mean values of two measurements were used for data analysis.

BIA (Inbody 3.0, Biospace Co., Seoul, Korea) was performed by a well trained nursing staff. The equipment involves placing eight tactile electrodes on a patient in an upright posture. When the subject was standing on the sole electrodes and gripping the hand electrodes, the microprocessor was switched on and the impedance analyzer started to measure the segmental resistances of the right arm, left arm, trunk, right leg, and left leg at four frequencies (5, 50, 250 and 500 kHz), thus measuring a set of 20 segmental resistances for one individual. The mean values of two sets of BIA measurements were used for analysis. The repeat measured coefficient of variation for TBW was 0.29%, and the day-to-day coefficient of variation of TBW was 1.18%. The accuracy of the 8-point tactile-electrode impedance method on the measurement of TBW_BIA was validated on healthy subjects (2). The procedure was performed in 3 min or less and the TBW_BIA was automatically calculated from the BIA with equations installed in the instrument's program.

We chose the Watson (3) and Hume-Weyers (4) formulas to compare the accuracy of the newly developed equation:

Watson formula

Male: TBW_W=2.447-(0.09156×age)+(0.1074×Ht)+(0.3362×BW)

Female: TBW_W=-2.097+(0.1069×Ht)+(0.2466×BW)

Hume-Weyers formula

Male: TBW_H=(0.194786×Ht)+(0.296785×BW)-14.012934

Female: TBW_H=(0.34454×Ht)+(0.183809×BW)-35.270121

Where age in years, Ht in cm, and the BW in kg.

Statistical analysis

The data were expressed as means±SD. Linear regression analysis was performed to develop the anthropometry-based TBW equation. Stepwise selection was employed using entry and exit criteria of p<0.01. TBW_BIA was used as a dependent variable. Sex, age, Ht and BW were used as independent variables. Polynomial terms for continuous variables and multiplicative interaction terms were considered in the model building process. Pearson's correlation coefficient (r) was used to find the relationship between two variables. To analyze the differences in TBW_BIA and TBWs derived from anthropometry-based equations, one-way analysis of variance (ANOVA) was performed with using the Bonferroni method for the post-hoc test. To assess the agreement, Bland-Altman plots using the means and differences between TBW_BIA and calculated TBW were used (5). To quantitate the degrees of bias, we compared the correlation coefficients of the respective differences and means. The closer the correlation coefficient of Bland-Altman plot was to zero, the less the bias. Root mean square error (RMSE) and mean prediction error (ME) were also used. ME was also an indication of bias, but not of accuracy. The RMSE value was used as a measure of the goodness-of-fit of an equation. If there were more than one equation to fit the data, the one with the smallest RMSE value had the highest precision. The equations used for ME and RMSE are as follows:

A p value less than 0.05 was considered as statistically significant.

RESULTS

Development of anthropometry-based TBW equations

For the 2,223 subjects, the male to female ratio was 1.72:1, the mean age was 45.1±10.9 yr, the mean BW was 64.3±11.0 kg, the mean Ht was 164.9±8.5 cm, and the mean TBW_BIA was 34.9±6.6 L. The simple (TBW_K1) and complicated (TBW_K2) TBW equations based on the anthropometric variables were developed by linear regression analysis (Table 1). The adjusted R² was 0.908 for TBW_K1 and 0.910 for TBW_K2.

Table 1.

Linear regression equation for TBW_BIA in 2,223 subjects

TBW_K2=1.485+0.001518×BW×Ht-0.0007872×Age²+0.349×BW-0.00199×BW²+0.06611×Sex×BW+0.0002861×Age×Ht.

Sex: male=1, female=0, Age: years, Ht: cm, BW: kg.

Validation of newly developed TBW equations

In another 720 control subjects, the male to female ratio was 1.28:1, the mean age was 47.0±11.1 yr, the mean BW was 63.6±10.5 kg, the mean Ht was 163.8±9.3 cm, and the mean TBW_BIA was 33.6±6.2 L. In males, TBW_BIA showed the highest correlation with TBW_H (r=0.951), followed by TBW_K1 (r=0.945), TBW_K2 (r=0.945) and TBW_W (r=0.937) (Table 2). There were no differences between the TBW_BIA and TBW_K1 or TBW_K2. However, TBW_W and TBW_H were significantly larger than the TBW_BIA. There were significant differences between TBW_W and TBW_K1 or TBW_K2 and between the TBW_H and TBW_K1. In females, TBW_BIA showed the highest correlation with TBW_W (r=0.902), followed by TBW_K2 (r=0.895), TBW_K1 (r=0.890), and TBW_H (r=0.887). There were no differences between TBW_BIA and TBW_W, TBW_K1 or TBW_K2. The TBW_H was significantly larger than the others.

Table 2.

Comparison and correlation coefficients of TBW_BIA with TBWs from anthropometry-based equation

Unit of number: Liter.

Statistical analysis by One-way ANOVA with post-hoc test with Bonferroni method and Pearson correlation.

^*p=0.000 vs. TBW_BIA, ^†p=0.019 vs. TBW_K1 and p=0.025, vs. TBW_K2, ^‡p=0.04, vs. TBW_K1.

In males, the TBW_K1 and TBW_K2 showed the lower RMSE (1.58, 1.58, 2.14, and 2.08 for TBW_K1 TBW_K2 and TBW_W TBW_H, respectively) and ME (0.526, 0.547, 1.426, and 1.362 for TBW_K1 TBW_K2 TBW_W and TBW_H, respectively) than the TBW_W and TBW_H (Table 3). On the Bland-Altman plot, the correlations between the difference and means were smallest for the TBW_K2 (r= -0.192), followed by the TBW_K1, TBW_W, and TBW_H (Fig. 1A, C, E, G). In females, the RMSEs were smallest for the TBW_W, followed by the TBW_K2, TBW_K1, and TBW_H (1.49, 1.50, 1.62, and 1.70 for the TBW_W, TBW_K2, TBW_K1 and TBW_H, respectively). The ME was closest to zero for the TBW_K2, followed by the TBW_K1, TBW_W and TBW_H (0.554, 0.556, 0.593, and 0.988 for the TBW_K2, TBW_K1, TBW_W and TBW_H, respectively). The correlation coefficients between the means and differences were highest for the TBW_W (r=-0.553), and lowest for the TBW_K2 (r=0.057) (Fig. 1B, D, F, and H).

Table 3.

Anthropometry-based TBW estimates relative to TBW_BIA

RMSE, root mean square error; ME, mean prediction error.

Fig. 1.

Bland-Altman plot between anthropometry-based TBW and TBW_BIA according to gender and each equation. The three horizontal lines indicate the upper limit of agreement, the mean prediction error, and the lower limit of agreement.

BIA, TBW by BIA; Watson, TBW by Watson formula; Hume, TBW by Hume-Weyers formula; K1, TBW by K1 formula; K2, TBW by K2 formula.

DISCUSSION

In this study, we developed two anthropometry-based TBW equations (TBW_K1 and TBW_K2) for Koreans using TBW_BIA as a reference. Among them, TBW_K2 showed the highest precision and the smallest bias for males and a similar precision and the smallest bias for females compared to the TBWs derived from Watson or Hume-Weyers formulas.

Accurate estimation of the TBW is important in many pathophysiologic states, as the clinical symptoms and signs of volume dysregulation complicate a variety of medical and surgical conditions. Furthermore, the disposition of electrolytes, enteral and parenteral nutrition, and selected drugs largely depends on the size and distribution of the TBW space. As the majority of TBW resides in the skeletal muscle, TBW may also be used as estimates of somatic protein stores (6).

The need for an accurate measurement of the TBW is particularly important for dialysis patients, as it equates to the distribution volume of urea (V). In hemodialysis (HD) patients, urea is the substance that is most often monitored as a surrogate for measurement of dialysis adequacy (7). A dose of HD (prescribed or delivered) is best described as the fractional clearance of urea as a function of its distribution volume (Kt/V) (8). However, in the dialysis centers, it is not easy to measure TBW each time using an accurate method such as BIA. For convenience, the Kt/V is automatically calculated using a computerized program in which the TBW equations are installed by simply entering height, sex, the pre- and post-HD blood urea nitrogen concentration, the ultrafiltration amount and duration of HD. For the calculation of V, the Watson and Hume-Weyers formulas are generally recommended (9). However, these TBW equations were mainly derived from the age, gender, height and weight of a western population. These equations have not been validated in a Korean population, nor have their accuracies been compared with a race-specific formula. In this study, we found that the TBW equations derived from a western population showed greater bias than our formulas. They tended to overestimate the small TBWs and underestimate large TBWs. Compared to Caucasians, Koreans are smaller with lower body weights and lower values of TBW (10). Therefore, it is natural that systematic errors occur when applying the prediction formula from a reference population to another population under study. Several studies have pointed out that race-specific TBW equations should be used when applying them to another race with a different body build (11-13). Considering this background, TBW_K2 may be helpful for assessing the nutritional status and dialysis adequacy more exactly for the Korean healthy control population and the Korean patients with end-stage renal disease.

In this study, TBW_W showed a lower RMSE value than the TBW_K2 in females. Therefore, TBW_W might have a better accuracy than TBW_K2, at least in females. However, TBW_W showed a greater bias than TBW_K2, as shown in Fig. 1B, H. TBW_K2 had a similar RMSE value and its ME was closer to zero than TBW_W. Furthermore, it had the least bias in females. Therefore, TBW_K2 seemed to be more suitable for the estimation of the TBW in Korean females.

In this study, TBWs estimated from the Watson and Hume-Weyers formula showed overestimation in small TBWs and underestimation in large TBWs. The reason for this might be due to the characteristics of subjects when the Watson and Hume-Weyers formulas were derived. For the Watson formula, the mean TBW was between 36.7 and 44.1 L in males and between 31.4 and 33.2 L in females (3). For the Hume-Weyers formula, the mean TBW was between 35.3 and 46.2 L in males and between 30.2 and 39.8 L in females (4). Therefore, when the TBWs were out of those ranges, the TBWs estimated from the Watson and Hume-Weyer formula seemed to over- or under-estimate the real TBWs.

There are several limitations to this study. First, TBW was estimated using BIA rather than using deuterium oxide or another standard dilution method. However, any methods, even the gold standard methods, for the assessment of TBW are based upon assumptions that allow for some inherent errors. Furthermore, the gold standard methods are expensive, laborious and hard to apply to a large number of subjects, as in this study. BIA does have several advantages; it is easy to use, rapid, non-invasive, inexpensive and applicable at the bedside. Several studies have shown that TBW can accurately and reliably estimated by BIA in normal healthy subjects (1, 14, 15). We used segmental BIA by the eight-polar tactile electrode impedance method. Segmental BIA reduced the errors from whole body BIA estimation (16). The accuracy of the TBW assessment by this method has been validated in control subjects (2). Second, the subjects of this study were not randomly selected from nationwide regions. Therefore, the study subjects may not be representative of the entire Korean population. In spite of this problem, the number of study subjects was large enough to overcome this drawback. We also validated the accuracy of newly developed equations in another set of subjects. Third, for the males, the newly developed TBW equations (and even the TBW_K2) still showed weak correlation between the means and differences in the Bland-Altman plot. Thus, the TBW derived from TBW_K2 might underestimate the real TBW in men with large BW. Fourth, this study was limited to the healthy subjects. Therefore, it should be validated for patients with the volume disorders such as acute renal failure, liver cirrhosis with ascites, ESRD, congestive heart failure, and nephrotic syndrome.

In summary, our race specific anthropometry-based equation provides superior or at least similar precision of TBW, compared to Watson or Hume-Weyers formula, in Korean subjects, with least bias. This equation may be useful for the estimation of TBW in a large number of subjects.