ImJC/in iVi�tr 1992:56:835-9. Printed in USA. © 1992 American Society forClinical Nutrition 835

Is the impedance index (ht2/R) significant inpredicting total body water?13

Robert F Kushner, Dale A Schoeller, Carla R Fjeld, and Lynn Danford

ABSTRACT We investigated the general utility of bioelec-

tncal impedance analysis (BIA) and the implications of BIA

theory in populations ofvarious ages from infancy to adulthood

by developing a single impedance equation. Four subject data#{149}

sets representing 62 adults, 37 prepubertal children, 44 preschool

children, and 32 premature low-birth-weight neonates were

combined. Subjects were randomly divided into a development

group (n = 1 16) and a cross-validation group (n = 59). The

single best predictor of total body water (TBW) was height2,’

resistance (ht2lR), which explained 99% ofthe variation in TBW

(SEE = 1 .67 kg). The addition of weight reduced the SEE to

I .41 kg. A significant bias was only seen in the preschool children.

These results were confirmed in the cross-validation group and

the best prediction formula was TBW = 0.59 ht2/R + 0.065 wt

+ 0.04. We conclude that the impedance index (ht2lR) is a sig-

nificant predictor ofTBW and that there is some improvement

in prediction ofTBW by inclusion ofa weight term. Am J

C/in Nutr 1992:56:835-9.

KEY WORDS Bioelectrical impedance analysis, body corn-

position, anthropometry

Introduction

Bioelectrical impedance analysis (BIA) is based on the prim-

ciple that the impedance (Z) ofa cylindrical conductor is related

to its length (L), cross-sectional area, and applied signal fre-

quency. On the basis of this relationship, it was proposed that

the volume of a conductor is proportional to L2/Z. More than

30 y ago, Thomasset (1) and Hoffer et al (2) tested this hypothesis

in a biological system and demonstrated that the volume of total

body water (TBW) was indeed proportional to L2/Z. Thus, BIA

could be used to estimate TBW by applying a predictive equation

based on the measured bioelectncal impedance of the subject.

Using height as a measure of conductor length, Hoffer et al

showed that ht2lZ was a better predictor of 3H2O-denved TBW

than was the weight term alone in 20 normal volunteers (r = 0.92

vs r = 0.74). Subsequent regression analyses by several investi-

gators have also demonstrated that the impedance index (ht2l

R; where R is resistance) yielded larger correlation coefficients

than weight or height when used as predictors of TBW, densi-

tometrically determined fat-free mass (dFFM), or total body po-

tassium (3, 4).

Although the impedance index has been shown to be a strong

predictor of TBW, it has also been observed that the accuracy

of predicting TBW or dFFM by BIA is significantly improved

by the inclusion ofadditional variables such as weight, age, and

sex (4, 5). The selection of variables and their coefficients has

differed from one study to another because ofdissimilar subject

populations ranging in age from infants to elderly adults. Fur-

thermore, some investigators have observed that these anthro-

pometnc variables can be even stronger predictors ofTBW than

BIA. For example, Deurenberg et al (6) recently suggested that

the prediction of dFFM by the BIA method offered little or no

advantage over simpler anthropometric techniques that use

weight, height, sex, and age. Thus, it remains controversial

whether the high correlations reported for BIA prediction equa-

tions are primarily based on these additional independent subject

characteristics or whether they are due to BIA (7).

Despite this controversy, we have noted a striking similarity

ofthe various regression equations relating impedance to TBW

in a wide range of age groups studied by us and others (8- 1 1).

This suggested to us that there may be a single relationship re-

lating impedance to TBW. Therefore, the aims of this study

were to evaluate the underlying principle of BIA and develop a

single TBW-predictive equation, and to evaluate the importance

ofthe impedance term (ht2lR) as a predictor ofTBW compared

with other independent subject characteristics.

Subjects and methods

Four data sets from adults (group 1, n = 62), prepubertal

children (group 2, n = 37), preschool children (group 3, n = 44),

and premature low-birth.weight neonates (group 4, n = 32) were

used in this study. The subjects were previously enrolled in stud-

ies on body-composition measurement andlor energy metabo-

lism (8, 9, 12; L Danford, D Schoeller, R Kushner, unpublished

observations for group 2, 1990). All participating adult subjects

or guardians for the children gave informed written consent for

the study, which was approved by the Institutional Review Board

ofthe University ofChicago (groups 1 and 2) and ofthe Instituto

de Investigaci#{243}n Nutnci#{243}nal in Lima, Peru (group 3). Subjects

from group 4, taken from the study by Mayfield et al (12), were

studied during the first 24 h ofpostnatal life and at 4-7 d of age.

The protocol for group 4 was approved by the Institutional Re-

view Board of the University of Texas Southwestern Medical

I From the Clinical Nutrition Research Unit, University of Chicago,and the Washington University School of Medicine, St Louis.

2 Supported by NIH grant DK 30031.

3 Address reprint requests to RF Kushner, 584 1 South Maryland Av-

enue, MC4080, Chicago, IL 60637.

Received December 31, 1991.Accepted for publication May 7, 1992.

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125

100

75

50

25

00 10 20 30 40 50 60 70 80

TBW, kg

FIG 1. Relationship between impedance index (ht2/R) and total bodywater (TBW) measured by stable-isotope dilution in the development

group (r = 0.996, SEE = 1.47 kg).

836 KUSHNER ET AL

Center. Physical characteristics and TBW measurements for all

175 subjects are shown in Table 1 . The combined data set was

rerandomized into a development group (n = 1 16) and a cross-

validation group (n - 59) by using a random number table.

Although each of these data sets has been previously reported,

the combination of the four data sets produced a unique pop-

ulation representing a broad range of ages (6 h-66 y), heights

(35.2- 183 cm), weights (0.82-200 kg), and TBW (0.68-74. 1 kg).

All subjects had height, weight, BIA, and TBW determined

on the same day. Prepubertal children and adults were asked to

fast from the previous evening. Height was measured without

shoes to the nearest 1 .0 mm. Supine crown-heel length was used

instead of standing height in groups 3 and 4. Weight was mea-

sured to the nearest 0. 1 kg with a standard balance-beam scale

in two groups and an electronic balance in the preschool children

and infants. BIA was performed with a body-composition an-

alyzer (model BIA-lOl RJL Systems, Detroit) with a right-sided

tetrapolar placement of electrodes as previously described (8).

Whole-body R was recorded as the mean of three to five con-

secutive measurements made in immediate succession. The

mean CV for within-day repeated measurements was previously

demonstrated to be 1.3% (8).

TBW was obtained by deuterium dilution (D2O-TBW) in

groups 1 and 2 and by 80 dilution (‘8O-TBW) in groups 3 and

4 as previously described (8, 9). For the D2O-TBW technique,

baseline saliva samples were obtained followed by oral admin-

istration of0.06 (group 1) and 0.08 g (group 2) D2O (99.8 atom

% excess) per kg estimated TBW (TBW was assumed to ap-proximate 60% of body weight). The D2O dilution space was

measured by repeat saliva sampling at 3 h. The ‘8O-TBW in

group 3 was determined by obtaining a baseline morning urine

sample followed by an oral dose of 0.08 g 180 (1 1.34 atom %

excess) per kg body weight given as H218O by syringe. Urine

samples were collected for at least three postdose voids, the last

� 5 h postdose. Group 4 subjects were given 10% enriched H218O

(0.6 mLlkg body wt) by gavage. After a 3-h equilibrium period,

1 .5 mL venous blood was obtained for 180 dilution. D20-TBW

and “O-TBW were both analyzed by isotope-ratio mass spec-

trometry as previously described (8, 9). TBW was assumed to

be 96% ofD2O- and 99% ofH2t8O-dilution spaces, respectively.

We previously demonstrated that these techniques for TBW do

not differ by > 1-2% (13).

Statistical analysis

Linear- and stepwise multiple-regression analyses were applied

to the data to determine the most significant variable or variables

TABLE ISubject characteristics

Sex

Group Age

y

(Male, Female) Height

cm

Weight

kg

TBW*

kg

Equation developmentNeonates

(n = 21) 0.02 NAt 41 (37-44)� 1.6 (0.8-2.1) 1.3 (0.07-1.6)

Preschool children

(n = 29) 1.1 (0.3-2.5) 18, 1 1 71 (58-84) 7.6 (3.9-14.4) 4.9 (2.8-9.1)Prepubertal children

(n = 24) 7.6 (4.8-9.8) 14, 10 129 (104-145) 31 (16-69) 16 (10-26)

Adults

(n = 42) 41 (23-66) 15, 27 170 (155-193) 85 (48-200) 38 (25-74)

Equation validationNeonates

(n = 1 1) 0.02 (0.6-2.5) NAt 41 (35-46) 1.6 (0.8-2.2) 1.3 (0.7-1.8)Preschool children

(n = 15) 1.3 (0.6-2.5) 12, 3 73 (60-86) 8.7 (5.2-1 1.6) 5.4 (4.1-7.4)Prepubertal children

(n = 13) 7.9 (6.4-9.9) 9, 4 129 (108-143) 31 (17-57) 16 (10-23)

Adults(n = 20) 39 (22-67) 1 1, 9 169 (150-180) 77 (58-144) 38 (27-5 1)

* Total body water.

t Not available.1: 1 (range).

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e� #{149} #{149} �#{149} . #{149}.#{149} #{149}. * #{149}#{149}� .#{149} #{149}#{149}

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FIG 2. Residual plot for prediction of total body water (TBW) byequation using impedance index (ht2/R) and weight. TBW is plotted on

a semilog scale for visual purposes.

TABLE 2

IMPEDANCE INDEX AND BODY WATER 837

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.� 2

� I

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TBW, kg

to predict TBW and to yield the lowest SEE. Statistical calcu-

lations were performed by using Minitab (Minitab Inc. State

College, PA). The regression equations were then used to predict

TBW in the cross-validation group. The bias, or mean residual

(TBW predicted - TBW measured), was tested for significance

by using a Student’s t test with P < 0.01 to adjust for five com-

parisons. Precision, or SD ofthe residuals, ofthe various possible

predictive equations was tested for significance relative to the

impedance index plus weight equation by using the F test. A Pvalue < 0.0 1 was required for significance to adjust for five com-

parisons.

Results

Stepwise linear regression was performed by using height,

weight, age, ht2lR, height2, and llR for the 1 16 subjects in the

development group. Impedance index (ht2lR) was the strongest

predictor identified, explaining 99% of the variance in TBW (r

= 0.996, SEE - 1 .47 kg) (Fig 1). The only other predictor iden-

tified as significant was weight, which when combined with the

impedance index accounted for 99.5% ofthe variance (r = 0.997,

SEE= 1.24kg).

Cross validation of the predictive equations based on imped-

ance index plus weight (Fig 2), however, detected a significant

bias among the neonates (residual = 0.24 ± 0. 1 3 kg, P < 0.00 1)

and preschool children (residual = -0.37 ± 0.34 kg, P < 0.01).

Because of the bias detected in cross validation, the stepwise

regression was repeated without both the low-birth-weight-infant

and preschool-children groups. In this treatment impedance in-

dcx was identified as the most significant predictor and weight

as the only additional significant predictor. Again, residuals were

calculated for the cross-validation group. No significant bias was

detected for the neonatal group (residual = 0.05 ± 0. 1 3 kg, NS),

but bias was detected for the preschool group (residual = -0.54

± 0.34, P < 0.01), indicating that the preschool group was an

outlier. The preschool group was deleted from all further regres-

sion analysis of the development group.

Entering predictor variables from the neonates, prepubertal

children, and adults in the development group, stepwise regres-

I 00 sion identified impedance index as the strongest predictor (r= 0.995, SEE = 1 .67 kg) and weight as the only additional sig-

nificant predictor (r = 0.997, SEE = 1.41 kg). The developmental

equations based on impedance index alone and impedance index

and weight were tested in the cross-validation group (Table 2).

As expected, significant bias was detected in the preschool chil-

dren. Among the other three groups bias was detected for equa-

tions based on impedance index alone and then only in the

neonates. The prediction equation based on impedance index

and weight had better precision than that based on impedance

index alone; however, the improvement was only statistically

significant in the adult group. The recommended equation for

predicting TBW (in kg) is 0.59 ht2/R + 0.065 wt + 0.04: however,

we are uncertain of its applicability among preschool children

(ages 1-60 mo).

Importantly, the residuals calculated by using the equation

based on impedance index and weight developed in the above

three groups were a relatively constant percentage of mean TBW

in each of the subject groups. The relative bias and CV for the

cross validation were neonates 0.8 ± 10.3%, prepubertal children

0.3 ± 3.2%, and adults -1.6 ± 4.5%.

To determine the relative importance ofthe impedance index

in predicting TBW, single- and multiple-regression analyses were

performed for height, weight, height2, and llR among the de-

velopment group and the results were compared with those ob-

tamed by using the impedance index (Table 3). Again, the pre-

school children were deleted from this comparison. Correlation

coefficients for all other variables were smaller than those of

impedance index plus weight. Similarly, SEEs were always larger

than those for impedance index plus weight.

To further investigate the predictive value of the impedance

index relative to height2 and llR, we calculated the residuals

among the cross-validation subjects (Fig 3A-D). Residuals for

the prediction ofTBW from either height2 or l,’R as single pre-

dictors were quite large and not consistent across the range of

subjects. Residuals using height2 and 1lR as independent van-

ables resulted in relatively constant residuals across the range of

Cross validation of predictive equations developed by using data from adults, children, and neonates*

Equation Adults Prepubertal children Preschool children Neonates

kg

TBW = 0.700 ht2/R - 0.32 -0.25 ± 2.53 0.21 ± 0.72 -0.74 ± 0.37t -0.25 ± 0.1StTBW = 0.593 ht2/R + 0.O6Swt + 0.04 -0.61 ± l.71f 0.05 ± 0.51 -0.58 ± 0.34t 0.01 ± 0.13

* Residual .� ± SD.

t Residual significantly different from 0, P < 0.01.� SD less than that predicted when only the impedance index was used, P < 0.05.

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TABLE 3Relative importance of the impedance index in predicting total bodywater in adults, children, and neonates

Predictor r SEE

kg

Height 0.897 7.59Weight 0.959 4.87Height + weight 0.98 1 3.36Height2 0.934 6.13Height2 + weight 0.986 2.841/resistance 0.907 7.24Height2 + 1/resistance 0.982 3.25Height2/resistance 0.995 1.67Height2/resistance + weight 0.997 1.41

subjects, but were still relatively large. Only when the ht2-R ratio

was used did the residuals become small enough (3-10%) for

this technique to be practically useful within the neonatal and

prepubertal-children groups.

Discussion

BIA has many advantages over other body-composition

methods in that it is safe, inexpensive, portable, rapid, and easy

to perform and it requires minimal operator training. Despite

these potential benefits, tojustify the use ofBIA it must be shown

to significantly improve the accuracy and precision of predictive

equations compared with those based on anthropometric mea-

surements alone.

In a recent review of validation studies involving adults and

children, which compared BIA with TBW or dFFM (14), the

impedance index was reported to be the best single predictor of

these compartments by multiple-regression analysis in 16 of 21

studies, accounting for 69% to 96% of the total predictive van-

ability (3- 10, 1 5-25). In five of the studies (7, 22-25), height

(or height2) and weight were more significant predictors than

were ht2/R or R alone.

Three of the latter studies incorporated a select group of sub-

jects for their analysis and we postulated that this might reduce

the importance of ht2lR. For example, Diaz et al (7) studied a

small group of young adults consisting of postpartum women,

farm laborers, and institute staffwhose body weights and heights

were smaller than those in other validation studies involving

adults. Diaz et al found that after height and weight were entered

into the multivariate equation, ht2lR contributed � 5% to the

prediction ofdFFM. In a study by Helenius et al (22) ofa group

of overweight middle-aged men and women, it was observed

that ht2/R did not contribute to the estimation of densitometry-

determined percent body fat when added to other selected an-

TBW, kg TBW, kg

FIG 3. Residual plots for total body water (TBW) predicted from various combinations of resistance (R) and heightindicate that the impedance index (ht2/R) is a better predictor than are other combinations of R and height in the

cross-validation group. A, TBW = -3.4 + 0.00140 ht2; B, TBW = -35.8 ± 37400/R; C, TBW = -23.7 + 19300/R+ 0.000871 ht2; and D, TBW = -0.3 + 0.70 ht2/R. Regression coefficients and SEEs are given in Table 3. TBW isplotted on a semilog scale for visual purposes.

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IMPEDANCE INDEX AND BODY WATER 839

thropometric variables. Gray et al (23) found that weight and

height2 were selected into a stepwise regression to explain a

greater portion ofthe variability by the statistical computer pro-

gram before ht2lR was used in a group of 87 adults, 75% of

whom were obese. Only Jackson et al (24) and Van Loan and

Mayclin (25) observed that standard anthropometnc measure-

ments were more powerful predictors of dFFM than was bio-

electrical impedance in a broad sample of adult subjects.

The present study was therefore performed to determine

whether a single BIA equation could be generated from a large,

heterogenous population, and to reinvestigate the significance

of the impedance term (ht2lR) as a predictor of TBW. The useof a large, heterogenous data set with a wide range of heights,

weights, and TBWs gave us the opportunity to statistically assess

the relative importance of measuring whole-body R compared

with simple anthropometric variables in a mixed population.

Furthermore, using TBW as the reference method instead of

dFFM, we eliminated the inherent errors in assuming a constant

density and hydration factor for fat-free mass across age groups.

We also included a cross-validation group to assess the predictive

value of the derived equations.

First, our results show that ht2/R is the single best predictor

of TBW (it results in the lowest SEE) and explains 99% of the

variance in TBW. In comparison, the combination of the an-

thropometric variables weight and height alone yield an SEE

that is twofold higher than ht2/R. The SEE is reduced slightly

by the substitution of height2 for height, as it is used in the

impedance term. Second, the impedance index is a superior pre-

dictor of TBW compared with either 1lR, height2, or both hR

and height2, demonstrating the importance of the impedance

term as suggested by the model originally described by Hoffer

et al (2).

The finding that weight improves the precision ofthe equation,

ie, reduces the SEE, most likely stems from the fact that the

human body does not behave as the ideal conductor proposed

during the development ofthe theory of BIA. BIA assumes that

the body is a geometrical isotropic conductor with uniform length

and cross-sectional area. However, the body more closely re-

sembles a series offive cylinders (two arms, two legs, and trunk),

each with a different geometry and resistivity. The addition of

weight, sex, and age probably adjusts for differences between

individuals and the relative underrepresentation ofthe trunk by

whole-body impedance.

The -7% underestimate ofTBW by BIA in the Peruvian pre-

school children (group 3) cannot now be fully explained. How-

ever, we do not believe that it results from the inclusion of mal-

nourished subjects in this group because the bias was observed

in both the well-nourished and malnourished subgroupings.

In summary, we conclude that the measurement of bioelec-

trical impedance significantly improves the prediction of TBW

as validated in a large heterogenous group ofadult and pediatric

subjects. The method should be useful in estimating the body

composition ofpopulation groups such as those in epidemiologic

studies. B

References

1 . Thomasett A. Bio-electrical properties of tissue impedance mea-surements. Lyon Med l962;207:l07-18.

2. Hoffer ED, Meador CK, Simpson DC. Correlation of whole-bodyimpedance with total body water volume. I Appl Physiol 1969;27:

53 1-4.

3. Lukaski HC, Johnson PE, Bolonchuk WW, Lykken GI. Assessmentof fat-free mass using bioelectrical impedance measurements of the

human body. Am J Clin Nutr l985;41:8l0-7.4. Segal KR, Gutin B, Presta E, Wang I, Van Itallie TB. Estimation

of human body composition by electrical impedance methods: acomparative study. J AppI Physiol l985;58: 1�6�-71.

5. Lukaski HC, Bolonchuk WW, Hall CB, Siders WA. Validation oftetrapolar bioelectrical impedance method to assess human body

composition. J Appl Physiol l986;60: 1327-32.6. Deurenberg P, van der Kooy K, Leenen R, Weststrate JA, Seidell

JC. Sex and age specific prediction formulas for estimating body

composition from bioelectrical impedance: a cross-validation study.IntiObes 199h;l5:l7-25.

7. Diaz EO, Villar J, Immink M, Gonzales T. Bioimpedance or an-thropometry? Eur J Gin Nutr l989;43: 129-37.

8. Kushner RF, Schoeller DA. Estimation oftotal body water by bio-electrical impedance analysis. Am J Chin Nutr 1986;44:4h7-24.

9. Fjeld CR, Freundt-Thurne J, Schoeller DA. Total body water mea-

sured by 80 dilution and bioelectrical impedance in well and mal-nourished children. Pediatr Res 1990;27:98-l02.

10. Davies PSW, Preece MA, Hicks Ci, Halhiday D. The prediction oftotal body water using bioelectncal impedance in children and ad-olescents. Ann Hum Biol l988;l5:237-40.

1 1. Lukaski HC, Bolonchuk WW. Estimation of body fluid volumes

using tetrapolar bioelectrical impedance measurements Aviat SpaceEnviron Med 1988;59:l 163-9.

12. MayfIeld SR. Vauy R, Waidelich D. Body composition of low-birth-weight infants determined by using bioelectrical resistance and re-

actance. Am J Chin Nutr 199l;54:296-303.13. Schoeller DA, Kushner RF, Taylor P, Dietz WH, Bandini L. Mea-

surement oftotal body water� isotope dilution techniques. In: RocheAF, ed. body composition assessments in youth and adults. Colum-

bus, OH: Ross Laboratories, 1985:24-9.14. Kushner RE. Bioelectrical impedance analysis: a review of principles

and applications. J Am Coll Nutr 1992;l 1:199-209.

15. Segal KR, Van Loan M, Fitzgerald P1, Hodgdon JA, Van Italic TB.

Lean body mass estimation by bioclectrical impedance analysis: afour-site cross-validation study. Am J Gin Nutr 1988;47:7-l4.

16. Heitmann BL. Prediction ofbody water and fat in adult Danes from

measurement ofelectrical impedance. A validation study. Int J Obes

l990;l4:789-802.

17. Deurenberg P, van der Kooy K, Evers P, Hulshofl. Assessment ofbody composition by bioelectrical impedance in a population aged> 60 y. Am J Clin Nutr l990;5 1:3-6.

18. Cordain L, Whicker RE, Johnson JE. Body composition determi-nation in children using bioelectiical impedance. Gmwth Dev Aging

1988;52:37-40.

19. Deurenberg P, van der Kooy K, Paling A, Withagen P. Assessment

of body composition in 8-I 1 year old children by bioelectricalimpedance. Eur J Gin Nutr l989;43:623-9.

20. Houtkooper LB, Lohman TO, Going SC, Hall MC. Validity of bio-

electric impedance for body composition assessment in children. J

Appl Physiol l989;66:8h4-2l.21. Deurenberg P, Kusters CSL, Smit HE. Assessment of body corn-

position by bioelectrical impedance in children and young adults is

strongly age-dependent. Eur J Gin Nutr l990;44:26l-8.22. Helenius MYT, Albanes D, Micozzi MS, Taylor PR, Heinonen OP.

Studies ofbioelectnc resistance in overweight, middle-aged subjects.Hum Biol l987;59:27l-9.

23. Gray DA, Bray GA, Gemayal N, Kaplan K. Effect of obesity on

bioelectrical impedance. Am J Gin Nutr 1989;50:255-60.

24. Jackson AS, Pollock ML, Graves JE, Mahar MT. Reliability andvalidity ofbioelectncal impedance in determining body composition.

J Appl Physiol l988;64:529-34.25. Van Loan M, Mayclin P. Bioelectrical impedance analysis: is it a

reliable estimator of lean body mass and total body water? Hum

Biol l987;59:299-309.

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