AJP-Endo Articles in PresS. Published on October 15, 2002 as DOI 10.1152/ajpendo.0199.2001
E-0199-2001.R3 1
Potassium per kg fat-free mass and total body K:
predictions from gender, age and anthropometry
Ingrid Larsson, Anna Karin Lindroos, Markku Peltonen, Lars Sjöström
The Sahlgrenska Academy at Göteborg University, Department of Body Composition and Metabolism,
SE-41345 Göteborg, Sweden.
Running head: Potassium content in humans
Correspondence to:
Name:
Lars Sjöström
Address:
The Sahlgrenska Academy at Göteborg University
Department of Body Composition and Metabolism
Vita Stråket 15
SE 41345 Göteborg, Sweden
Phone:
+46-31-3423053
Telefax:
+46-31-418527
E-mail:
[email protected]
Copyright 2002 by the American Physiological Society.
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ABSTRACT
Total body potassium (TBK) is mainly located intracellularly and constitutes an index of fat-free mass
(FFM). The aim was to examine if TBK and TBK/FFM -ratio can be estimated from gender, age,
weight and height. A primary study group (164 males, 205 females) and a validation group (161, 206),
aged 37-61 years, were randomly selected from the general population. TBK was determined by wholebody counting and FFM was obtained by DXA (dual-energy x-ray absorptiometry). The primary study
group was used to construct gender-specific equations predicting TBK and TBK/FFM from age, weight
and height. The equations were used to estimate TBK and TBK/FFM in the validation group. The
estimates were compared with measured values. TBK in different age ranges was predicted with errors
ranging from 5.0 to 6.8%, errors for TBK/FFM ranged from 2.7 to 4.8%, respectively. By adding
FFMDXA as a fourth predictor, the error of the TBK prediction decreased with approximately 2 percent
units. In conclusion, TBK and TBK/FFM can be meaningfully estimated from gender, age, weight and
height.
KEYWORDS: body composition, dual-energy X-ray absorptiomtery, 40K, TBK/FFM -ratio, randomly
selected study groups.
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INTRODUCTION
Since 98 percent of the total body potassium (TBK) is located intracellularly (27), TBK is an
excellent indicator of the respiratory cell mass of the body. TBK has therefore been the subject of
intensive research during the last 50 years.
In a classic paper from 1956 (8), Forbes and Lewis reported the potassium (K) content of two male
corpses, (7,8), one female corpse previously examined by Widdowson et al in 1951 (26), and one adult
carcass of unknown gender examined by Shol already in 1939 (20). The potassium content of these
cadavers was 66.5 (male), 66.6 (male), 72.6 (female) and 66.8 (adult) mmol per kg fat-free mass
(FFM), or on average of 68.1 mmol K per kg FFM.
In a follow-up paper from 1961, Forbes et al reported TBK in 42 males and 8 females measured by
means of a whole-body counter (9). FFM was estimated as TBK/68.1 and body fat (BF) was calculated
as body weight minus FFM. In males, percent BF was correlated with skinfold (r=0.80) and with the
weight:height ratio (r=0.56). Although Forbes did not specifically conclude that the potassium content
of FFM is constant, the subsequent literature often interpreted these data as evidence that it was.
More recently, several reports have indicated that the potassium content of the body is dependent not
only on FFM but also on gender (10,12), age (6,13) and body build (asthenic vs. athletic) (5,15,18).
Also, some studies based on underwater weighing (28) or computed tomography (CT) based body
composition (14,21) have indicated that the potassium content per kg FFM may be lower than 68.1
mmol/kg.
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Taken together, these studies suggest that the relationship between TBK and FFM is not as
straightforward as previously assumed and that more sophisticated conversion procedures are required.
FFM estimates based on TBK are dependent on a valid assumption of the potassium content per kg fatfree mass. Therefore, our primary aim was to examine if potassium-based FFM determinations could
be improved by using individual rather than fixed TBK/FFM estimates. The individual TBK/FFMratios were predicted from age, weight and height by using the measured ratio as the dependent
variable. TBK was determined using whole-body counting and FFM by means of dual energy x-ray
absorptiometry (DXA).
Our secondary aim was to examine if TBK could be predicted from age, weight, height alone or with
the addition of FFM determined by DXA (FFMDXA). Such estimates are potentially important since
relatively few whole-body counters are available worldwide.
METHODS
The SOS (Swedish Obese Subjects) reference study
The SOS reference study is an ongoing study including randomly selected middle-aged inhabitants of
the city of Mölndal, Sweden. The main purpose of the study is to obtain a reference sample for the
SOS-project (22). Other purposes of the study are to examine body composition, risk factors of
cardiovascular disease, habitual dietary intake and different aspects of quality of life in relation to age.
The subjects were randomly selected from a population registry using a computer-based procedure.
Each subject received a written invitation to a health examination, along with an explanation of the
purpose of the investigation. Between August 1994 and December 1998, a total of 360 men and 452
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women were examined (response rate: 52% in men and 57% in women). Of these individuals, 349 men
and 423 women were examined both with DXA and TBK techniques.
Individuals showing large differences between measured body weight and the sum of DXA
compartments (See “Results” and Figure 1) were excluded. Thus, 325 males and 411 females remained
available. After allocation into age groups these individuals were randomised to a primary study group
(164 men and 205 women) and a validation group (161 men and 206 women).
Anthropometry
All anthropomteric measurements in this study were performed with the subjects dressed in
underwear, after an over-night fast. Body height was measured to the nearest 0.01 meter with the
subject standing back to a wall-mounted stadiometer in bare feet. Weight was measured to the nearest
0.1 kilogram with calibrated scales. Body mass index (BMI) was calculated as weight in kilograms
divided by height in meters squared (kg/m2 ). The following anthropomteric measurements were also
performed: waist and hip circumferences, sagittal trunk diameter and thigh-, neck- and upper arm
circumferences (22,23).
Dual Energy X-ray absorptiometry (DXA)
Body composition by means of DXA results is a three-compartment model consisting of bone
mineral content (BMC), body fat (BF) and lean tissue mass (LTM) (25). BMC plus LTM correspond to
FFM with the total potassium technique and several other two-compartment methods. The DXAscanner used was a LUNAR DPX-L scanner, system number 7156, (Scanexport Medical, Helsingborg,
Sweden) with software version 1.31 and with the extended analysis program for total body analysis
(LUNAR Radiation Corp, Madison WI). This scanner uses a constant potential x-ray source and a K-
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edge filter to achieve a congruent beam of stable dual-energy radiation. A quality assurance test was
conducted on a daily basis, as recommended by the manufacturer (17). DXA determines BMC, BF and
LTM without using body weight. Therefore, one way to validate the method is to compare the sum of
the three body compartments with body weight. The manufacturer does not recommend examinations
of individuals being heavier than 120 kg since the sum of BMC, BF and LTM gradually lags behind
weight at higher body weights.
Precision errors of the scanner were determined by comparing results from two separate examinations
of ten healthy subjects. They were 1.7% for BF, 0.7% for LTM, 1.9% for BMC and 1.5% for bone
mineral density (BMD). One total body scan exposes the subject to a radiation doses equivalent to 0.5
µSv, which is in the lower range of radiation exposure measurements (16). For comparison, the
radiation from one chest radiography is 80 times higher than a total body DXA scan and the daily
background radiation in Göteborg is 3 µSv (Source: Department of Radiation Physics, Göteborg
University).
Whole-body potassium counting (TBK)
With the TBK method, body weight is compartmentalised into FFM and BF. The natural abundance
of the potassium-40 isotope (40K) is a constant fraction (=0.012%) of all natural potassium (6). The
40K-isotope emits a 1.46 MeV γ-ray that can be counted using a detection system with appropriate
shielding. The measurements took place in a high-sensitivity 3π whole body counter containing four
plastic scintillators with a total volume of 700 L (24). The standard deviation of a single TBK
determination (usually between 2000 and 4000 mmol) was approximately 80 mmol (3). The conversion
of TBK into FFM is traditionally based on the assumption that 1 kg FFM contains 68.1 mmol
potassium (FFM68.1) (9). We constructed TBK/FFMDXA -ratios in the primary study group and regressed
these by weight (W), height (H) and age (A) separately for men and women. In the validation group we
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used the resulting equations to predict individual [TBK/FFM]WHA-ratios. FFMK was calculated from
total body potassium either by using Forbes’ ratio (68.1 mmol K/kg FFM), or by using the individually
determined [TBK/FFM]WHA. In this paper, FFM K and BFK designate FFM and BF determined with the
TBK method without specifying which TBK/FFM -ratio was used, while FFM68.1 indicates FFM
determined from TBK and the assumption of 68.1mmol K/kg FFM. FFMWHA indicates FFM determined
from TBK and the individually estimated [TBK/FFM]WHA. Body fat (BF68.1 or BFWHA) was calculated as
the difference between body weight and FFM68.1 or FFM WHA.
Human subjects
The ethical committee of the Medical Faculty of Göteborg University approved the protocol and
written informed consent was obtained from all subjects before the examinations.
Statistical procedures
Age, height, weight and body composition measurements are presented as mean±SD for men and
women separately. To describe age-related differences in body composition, the subjects were divided
into one of five age groups: 37-41, 42-46, 47-51, 52-56 and 57-61 years of age. Age-trend calculations
were also performed using age, TBK and TBK/FFM -ratios as continuous individual variables.
Subjects were allocated to either a primary study group or a validation group using the Microsoft Excel
(Microsoft Excel, Microsoft Corporation, 1998) random function within each gender and age group.
In the primary study group, multiple linear regression analysis was performed to develop gender
specific predictive equations to estimate individual TBK/FFM ratios from age, weight and height.
Measured TBK/FFM-ratios were used as dependent variable. Similarly, TBK was estimated from age,
weight and height with or without FFMDXA while using measured TBK as dependent variable.
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Measurements of sagittal diameter, circumferences of waist, hip, thigh, neck, upper arm, age2 , weight2 ,
and height2 were also considered and tested as predictors (independent variables) in the regression
analyses. P-values were considered significant when < 0.05 in two-sided tests.
Obtained equations from the primary study groups were then applied on the validation groups, and
errors between measured and estimated TBK or TBK/FFM-ratios were calculated as the within subjects
coefficient of variation (2):
∑d
2
÷ 2n × 100
X
where d is the difference between measured and estimated value, n the number of paired observations
and X the grand mean.
The statistical analyses were conducted with JMP statistical software package, version 3.2.1 (SAS
Institute Inc. Cary, NC, USA).
RESULTS
Since the main purpose of this study was to examine relationships between TBK and FFMDXA, it was
important to exclude individuals with erroneous values on these variables. We had no possibility to
independently check the potassium measurements. However, the sum of the DXA determined BMC,
LTM and BF (DXASUM) could be compared with the simultaneously measured body weight. The upper
panels of Figure 1 show
Figure 1
the difference between body weight and DXASUM as a function of body weight in those 349 men and
423 women in which both DXA and TBK were measured. The slopes were positive and significant in
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both genders and most observations above 100 kg body weight were located above the regression line,
indicating an increasing difficulty of the DXA equipment to detect the total body mass with increasing
body weight. Some outliers with less than 100 kg body weight were also observed.
To minimize the effects of systematic and random errors on the final TBK/FFMDXA -ratios, all
individuals with body weights above 100 kg or with [body weight – DXASUM] outside ±2SD shown in
the upper panels of Figure 1 were excluded in the lower panels. The excluded individuals were 24 men
(age: 51.9±5.6 (40.9-61.1) years; height: 181.6±5.5 (174.0-194.0) cm; weight: 97.2±13.0 (74.5-115.0)
kg) and 12 women (age: 48.6±7.4 (37.9-60.9) years; height: 169.3±4.7 (162.0-178.0) cm; weight:
77.6±13.8 (60.0-107.0) kg). The excluded subjects represented 6.8% and 2.8% of the men and women
who were examined both with DXA and TBK technique.
After the exclusions, the difference between body weight and DXASUM was –0.1±0.5 kg in men, and
0.2±0.4 kg in women, which was not significantly different from zero in any gender (Figure 1, lower
panels). In women, the slope for [body weight – DXA SUM] versus body weight was reduced from
0.0061 to 0.0017 and was no longer significant. In men, the corresponding slope dropped from 0.013 to
0.006 and the significance level from p=0.0002 to p=0.03.
The men and women of the lower panels of Figure 1, were first divided into age groups and within
each age group individuals were randomised to a primary study group or a validation group, as
described under “Statistical procedures”. Table 1 shows age, height, weight, BMI,
Table 1
TBK, FFM and BF of all men and women within the primary study group and the validation group.
There were no significant differences between the primary study group and the validation group, either
in men or women. All measurements of Table 1, except age and BF, were lower in women than in men.
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Although women had a lower BMI than men, they had higher BF as measured both with the DXA- and
the TBK68.1- methods.
Individually determined TBK and FFMDXA observations were used to calculate TBK/FFMDXA-ratios
for all men and women in the primary study group. These ratios were multivariately regressed by age,
weight and height. The resulting gender specific equations were (cf. Table 2):
Males:
TBK/FFM = 98.30 - 0.1594 x age + 0.1431 x weight – 0.1849 x height
Females:
TBK/FFM = 94.39 – 0.1735 x age + 0.1169 x weight – 0.1567 x height
Above, TBK/FFM-ratio is given in mmol/kg, age in years, weight, in kg, and height is given in cm.
All three predictors contributed significantly to the explained variances (Table 2).
Table 2
In contrast, the sagittal trunk diameter and circumferences of waist, hip, thigh, neck and upper arm
did not contribute to the explained variances, nor did age2 , weight2 or height2 when added separately as
a fourth variable in the equations given above (p=0.10 to p=0.97).
In addition, Table 2 provides TBK estimates based on age, weight and height alone and also when
adding FFMDXA. In the former equations, age was negatively related to TBK, while weight and height
were positively related to TBK. The explained variance was 52% in women and 68% in men. When
FFMDXA was added as a predictor, the explained variances increased to 73% and 88%, respectively.
Height became negatively related to TBK in men, and tended to be in women.
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In the validation group, the correlation between the measured TBK/FFM-ratio and the same ratio
estimated from age weight and height was significant both in men (r=0.48;p<0.0001) and in women
(r=0.39; p<0.0001). When TBK was estimated from age, weight and height, the estimate was closely
related to measured TBK both in men (r=0.75; p<0.0001) and women (r=0.73; p<0.0001). These
associations were even stronger when FFMDXA was added as a predictor (men: r=0.93; p<0.0001,
women: r=0.90; p<0.0001) (data not shown in figures).
In the validation group, the difference between FFMDXA and FFM68.1 was not significantly different
from zero, either in men (-0.3±3.3 kg) or in women (0.3±2.5 kg) (cf. Table 1). However, this difference
was negatively related to body weight in women (p=0.0053) and tended to be in men (p=0.08) (Figure
2, upper panels), i.e. FFM68.1 resulted in larger
Figure 2
values than FFMDXA at large body weights but in smaller values at low body weights. This weight bias
disappears completely if FFMK is calculated as TBK/(TBK/FFMDXA), since [FFMDXA –
TBK/(TBK/FFMDXA)] is equal to zero (data not shown). However, the bias also disappeared when
FFMK was calculated from measured TBK and TBK/FFM -ratios individually estimated from age,
weight and height according to the gender specific equations of Table 2 (Figure 2, lower panels).
As indirectly suggested by Table 2, [FFMDXA-FFM68.1] might be biased not only by weight, but also
by age and height. Usually this turned out to be the case and these biases disappeared or decreased
when individually estimated TBK/FFM -ratios was used. (WOMEN: [FFMDXA-FFM68.1] vs age:
β=0.070, p<0.01; [FFMDXA-FFMWHA] vs age: β=-0.018, p=0.42; [FFMDXA-FFM68.1] vs height: β=0.066,
p<0.02; [FFMDXA-FFMWHA] vs height: β=0.026, p=0.31. MEN: [FFM DXA-FFM68.1] vs age: β=0.22,
p<0.0001; [FFMDXA-FFMWHA] vs age: β=0.11, p<0.001; [FFMDXA-FFM68.1] vs height: β=0.016, p=0.69;
[FFMDXA-FFMWHA] vs height: β=-0.038, p=0.27).
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The difference between BFDXA and BF68.1 was not significantly different from zero in men in the
validation group (0.4±3.4 kg), but was in women (-0.5±2.5 kg; p=0.0075) (cf. Table 1). While [FFMDXA
– FFM68.1] was negatively related to body weight (see above), [BFDXA – BF68.1] was positively related to
body weight in women (p=0.0053). In men, the slope was also positive but non-significant (p=0.14)
(Figure 3, upper panels). Compared to BFDXA,
Figure 3
BF68.1 thus resulted in smaller BF values at large body weights and in larger values at low body weights,
particularly in women. This body weight bias disappeared when BFK was calculated as the difference
between body weight and FFMWHA (Figure 3). Similarly, the biases of [BFDXA-BF68.1] by age and height
disappeared or decreased when using the prediction equations of Table 2 (data not shown).
In Tables 3 (men) and 4 (women), measured values for weight, height, BMI, TBK and TBK/FFMDXA
are given by age groups in the pooled study group (primary + validation groups). In this cross-sectional
study, the increase in BMI by age was more dependent on decreasing height than increasing weight in
both genders. The total body potassium (TBK) as well as the TBK/FFMDXA-ratio decreased with age in
both men and women.
Table 3, Table 4
In addition, Tables 3 and 4 are comparing the anthropometrically estimated TBK and [TBK/FFM]WHA
-ratio with the measured TBK and TBK/FFMDXA-ratio in the validation group.
The [TBK/FFM]WHA-ratios estimated from weight, height and age in the validation group were
similar to actually measured TBK/FFMDXA-ratios in all age groups of men and women. The errors
based on the squared differences between measured and estimated ratios ranged between 2.7% and
3.8% in men and 3.2% and 4.8% in women. The prediction of TBK from weight, height and age
resulted in errors ranging between 5.3% and 6.6% in men and between 5.0% to 6.8% in women.
Adding FFMDXA to the prediction of TBK reduced errors to 2.7-3.9% in men and 3.3-4.8% in women.
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DISCUSSION
There has been a lack of appropriate information on potassium content per kg FFM in the literature.
This prediction study on body composition based on a randomly selected sample from the general
population, illustrates that the TBK/FFM-ratio can be predicted from gender, age, weight and height
with errors being smaller than 5% in the age interval 37-61 years. Thus, our equations can improve the
estimation of FFM from TBK when whole body counters are available.
Our independent measurements of TBK with a whole body counter and FFM with DXA made it
possible to predict TBK from gender, age, weight, height and FFM DXA with errors smaller than 5 %.
Predictions of TBK from gender, age, weight and height alone resulted in errors ranging between 5.0%
to 6.8%. Thus research sites with or without access to DXA are able to make meaningful estimates of
TBK. Such estimates are of importance since TBK is a valuable indicator of respiratory cell mass (27).
In this cross-sectional study, we found that although randomly selected women had a lower BMI,
they had more body fat than randomly selected men, irrespective of the method (DXA or TBK) used.
Also, BMI increased with age in both genders, primarily due to decreasing height. Similar results have
previously been obtained in cross-sectional (3,19) and longitudinal (6) studies.
The TBK content was approximately 30 percent lower in women than in men across the five age
groups. This gender difference, as well as the decline in TBK with age, is consistent with earlier
longitudinal (6,11) and cross-sectional (1,13,19) studies. The agreement with longitudinal studies
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implies that the decline in TBK with age in this study is more related to the biology of aging than to
generation differences.
The manufacturer of LUNAR’s DXA machines points out that at body weights higher than 120 kg,
the sum of BMC, LTM and BF (DXASUM) gradually lags behind body weight. Figure 1 indicates that
by excluding observations above 100 kg body weight the difference between body weight and DXASUM
is negligible, particularly in women.
Our results show that, Forbes’ now 40 years old assumption on potassium content per kg FFM (68.1
mmol/kg) is approximately true in 50-year-old men and 45-year-old women. However, between the
ages of 39 to 59 years the TBK/FFM –ratio decreases 3.3 mmol/kg in men and 1.9-2.7 mmol/kg in
women, suggesting that the potassium content per kg FFM is not constant.
Since age, weight and height were related to the TBK/FFM-ratio (Table 2) it was anticipated that the
difference between FFMDXA, here considered the “gold standard”, and FFM68.1 might be biased by these
variables. In fact, this was the case. For instance, FFM 68.1 overestimated FFM at large body weights, but
underestimated FFM at low body weights, both in men and women (Figure 2). When the potassium
determined FFM was calculated from TBK by using the anthropomterically estimated [TBK/FFM]WHAratios on an individual basis, the age, weight and height biases disappeared.
The standard deviations for predicted TBK and predicted TBK/FFM-ratio were smaller than for
actually measured values. Thus, our equations are not able to detect the total biological variation in
these respects. However, resulting errors were acceptable in all age and gender groups and the weight,
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age and height bias of [FFMDXA-FFM68.1] disappeared when our equations were used. Thus, in spite of
imperfections, our equations appear to be useful.
TBK was negatively related to age but positively to weight and height (Table 2). When FFMDXA was
also used to predict TBK, height became negatively related to TBK. Thus, by keeping FFM constant,
TBK decreases with increasing height. This is consistent with the fact that bone and skin contain less
potassium per kg than the rest of FFM (4,10).
There are a number of factors that limit the generalizability of our results. Our equations have been
shown to be valid for the age interval 37-61 years, the body weight range 45-100 kg and the height
range 160-195 cm in men and 150-179 cm in women. Outside these intervals, the errors are not known.
Furthermore, the equations may not be valid for individuals suffering from diseases that influence body
composition or for athletic persons. Finally, our calculations of TBK/FFM-ratios are dependent on the
validity of the DXA-technique.
Using underwater weighing, Womersley et al reported individual FFM density and TBK values for 36
men and 43 women (28). From this information, we calculated the TBK/FFMdensity-ratio and found it to
range from 56.5-77.8 (mean±s.d: 66.0±3.9) mmol/kg in men and from 52.9 to 72.1 (61.6±4.9) mmol/kg
in women.
Similarly, comparisons between TBK and CT examinations in 17 males (14) and 12 women (21)
suggest a TBK/FFM-ratio of 64.7 mmol/kg in men and 62.0 mmol/kg in women. Thus, both
underwater weighing and CT results in lower TBK/FFM-ratios than the DXA-technique. Although the
sum of FFM (=BMC+LTM) and BF was close to body weight, this fact does not exclude the possibility
that the DXA-technique allocates a too small fraction of body weight to FFM and a too large fraction to
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BF, thus resulting in apparently large TBK/FFM-ratios. These circumstances must be further evaluated
in studies using several techniques to measure FFM.
In conclusion, we have demonstrated that TBK and the TBK/FFM-ratio can be predicted from age,
weight and height with errors small enough to make the equations useful within a wide range of
biological applications.
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ACKNOWLEDGEMENTS
This study was supported by grants from the Swedish Medical Research Council, grant no. 05239.
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E-0199-2001.R3 22
LEGEND TO FIGURE 1
Figure 1. Body weight - DXASUM by body weight in the total study group. On the y-axes, the
differences between body weight and the sum of bone mineral content, lean tissue mass and body fat by
DXA (DXASUM) are shown as a function of body weight. Panels A (men, n=349) and B (women,
n=423) show all available subjects. Panels C (men, n=325) and D (women, n=411) show the same
relationship after exclusion of subjects with body weights above 100 kg and outside ±2 SD.
β is the regression coefficient.
LEGEND TO FIGURE 2
Figure 2. FFMDXA - FFMK by body weight in the validation group. Upper panels show the
differences between fat-free mass measured with DXA (FFMDXA) and TBK (FFM68.1) as a function of
body weight in men, n=325 (A) and women, n=411 (B). Lower panels give the differences between
measured FFMDXA and FFMK when using a TBK/FFM-ratio and estimated from weight, height and age
(FFMWHA) in men, n=325 (C) and women, n=411 (D). β is the regression coefficient.
LEGEND TO FIGURE 3
Figure 3. BFDXA - BFK by body weight in the validation group. Upper panels show the differences
between body fat measured with DXA (BF DXA) and TBK (BF68.1) as a function of body weight in men,
n=325 (A) and women, n=411 (B). Lower panels give the differences between measured BFDXA and
BFWHA in men, n=325 (C) and women, n=411 (D). BFWHA is calculated as the difference between body
weight and FFMWHA (c.f. legend to Figure 2 and “Methods”). β is the regression coefficient.
E-0199-2001.R3 23
Table 1. Age, height, weight, body mass index, total body potassium, fat-free mass and body fat
in the primary study group and the validation group. Mean±SD.
Primary study group
Variables
Men
Women
Numbers
164
205
Age, yrs.
49.3±6.9
49.0±.6.8
Height, cm.
179.2±6.0
Weight, kg.
a
Validation group
Men
Women
161
206
=0.60
49.4±7.0
49.1±7.0
=0.65
166.5±5.6
<0.0001
178.7±6.6
165.6±6.1
<0.0001
80.7±9.4
66.6±10.0
<0.0001
80.5±9.8
66.5±9.7
<0.0001
25.1±2.7
24.0±3.4
<0.001
25.2±2.8
24.2±3.5
<0.01
TBK, mmol
4216±473
2927±359
<0.0001
4172±540
2910±359
<0.0001
FFMDXA
61.2±5.8
43.3±4.3
<0.0001
61.0±6.5
43.0±4.3
<0.0001
FFM68.1
61.9±6.9
43.0±5.3
<0.0001
61.3±7.9
42.7±5.3
<0.0001
e
BFDXA
19.6±5.9
23.0±8.0
<0.0001
19.6±6.3
23.3±7.4
<0.0001
f
BF68.1
18.7±5.9
23.6±8.1
<0.0001
19.2±7.3
23.8±7.4
<0.0001
BMI, kg/m2
b
c
d
P-value
P-value
Footnote Table 1.
a
BMI= body mass index, b TBK=total body potassium, cFFMDXA= fat free mass determined by the dual-
energy x-ray absorptiometry (DXA) method, d FFM68.1= fat free mass determined by the total body
potassium (TBK) method based on the assumption of 68.1 mmol potassium per kg FFM according to
Forbes et al. (9), eBFDXA= body fat determined by the DXA-method, fBF68.1= body fat calculated as the
difference between body weight and FFM 68.1.
E-0199-2001.R3 24
Table 2. Multiple regression equations of the TBK/ FFMDXA-ratio and TBK, as dependent
variables, and age, weight, height and FFMDXA as independent variables in males and females of
the primary study group.
Dependent variables
Independent variables
Males, n=164
age, yrs
weight, kg
height, cm
β1
β2
β3
β4
-0.1594***
0.1431***
-0.1849***
-
98.30
25.5***
TBK, mmol
-12.04**
34.67***
13.75**
-
-449.6
67.7***
TBK, mmol
-9.179***
7.827**
-11.95***
71.82***
1784
88.0***
TBK/FFMDXA, mmol/kg
Dependent variables
Independent variables
Females, n=205
age, yrs
FFMDXA , kg intercept
adjusted
R2 , %
weight, kg
height, cm
β1
β2
β3
β4
TBK/FFMDXA, mmol/kg
-0.1735**
0.1169**
-0.1567*
-
94.39
9.2***
TBK, mmol
-13.37***
18.55***
18.97***
-
-810.4
52.3***
TBK, mmol
-8.0107***
6.0907**
-5.743n.s.
63.91***
1103
72.7***
*=P<0.01; **=P<0.001; ***=P<0.0001; n.s.=not significant
FFMDXA , kg intercept
adjusted
R2 , %
E-0199-2001.R3 25
Table 3. Body weight, height, BMI, TBK and measured as well as predicted TBK and TBK/FFM
-ratios by age in indicated study groups in men. Mean±SD.
Group
Age groups, years
Men
37-41
42-46
47-51
52-56
57-61
Age trend, p
Age, years
a
P+V 39.4±1.4
44.4±1.4
48.9±1.4
539.±1.4
58.8±1.4
Numbers
P+V
61
60
61
79
64
Body weight, kg
P+V
80.0±9.8
82.0±8.9
80.9±10.0 80.4±9.3
Height, cm
P+V
180.6±6.5 179.1±6.9 180.3±5.9 179.0±5.5 176.0±6.1 <0.001
b
BMI, kg/m2
P+V
24.5±2.8
TBK,mmol
P+V
4365±555 4342±492 4243±475 4073±427 3998±503 <0.0001
P+V
70.4±3.4
70.1±2.6
68.5±3.1
67.4±3.2
67.1±3.1
c
d
TBK/FFMDXA , mmol/kg
25.5±2.6
24.9±2.6
25.1±2.7
79.6±10.0 =0.71
25.7±2.9
=0.06
<0.0001
Numbers
V
30
30
30
39
32
TBK/FFMDXA , mmol/kg
V
70.6±4.0
69.9±3.0
68.4±3.3
67.1±3.3
66.2±2.8
<0.0001
e
[TBK/FFM]WHA, mmol/kg
V
69.9±1.4
70.1±1.5
68.6±1.2
68.3±1.3
67.7±1.4
<0.0001
f
Error, %
V
3.4
2.7
3.2
3.8
3.3
TBK, mmol
V
4382±619 4250±519 4215±496 4163±456 3875±520 <0.001
g
TBKWHA , mmol
V
4317±346 4256±351 4233±394 4245±374 3964±441 <0.01
Error, %
V
6.2
h
TBKWHAD, mmol
V
4328±506 4256±494 4228±426 4242±446 3963±528 <0.05
Error, %
V
3.7
f
f
6.2
2.7
6.6
3.1
6.1
3.9
5.3
3.2
E-0199-2001.R3 26
Footnote Table 3
a
P+V= primary study group+validation group, b BMI= body mass index, cTBK= total body potassium,
d
TBK/FFMDXA= ratio of measured TBK by whole-body counter and measured FFM by DXA,
e
[TBK/FFM]WHA-ratio= the predicted TBK/FFM-ratio based on weight, height and age according to
equation in Table 2, fError= within subjects coefficient of variation (2) between measured and
predicted TBK/FFM -ratio, or measured and predicted TBK, g TBKWHA= predicted TBK from weight,
height and age according to equation in Table 2, h TBKWHAD= predicted TBK from weight, height, age
and FFMDXA according to equation in Table 2.
E-0199-2001.R3 27
Table 4. Body weight, height, BMI, TBK and measured as well as predicted TBK and
TBK/FFM -ratios by age in indicated study groups in women. Mean±SD.
Group
Age groups, years
Women
37-41
42-46
47-51
52-56
57-61
Age trend, p
Age, years
a
P+V 39.1±1.4
44.2±1.6
49.2±1.4
54.2±1.4
58.8±1.2
Numbers
P+V
75
87
90
88
71
Body weight, kg
P+V
64.8±7.8
66.7±10.5 67.0±11.1 66.8±9.9
Height, cm
P+V
167.9±6.5 166.8±5.2 166.4±5.7 165.2±5.7 163.9±5.8 <0.0001
b
BMI, kg/m2
P+V
23.0±2.5
TBK,mmol
P+V
3050±376 3014±389 2893±389 2822±284 2815±270 <0.0001
P+V
68.8±4.1
68.6±4.8
66.8±3.8
66.7±3.8
67.1±3.8
c
d
TBK/FFMDXA , mmol/kg
24.0±3.6
24.2±3.7
24.2±3.4
67.2±9.2
25.1±3.5
=0.12
<0.001
<0.0001
Numbers
V
37
44
45
44
36
TBK/FFMDXA , mmol/kg
V
69.3±4.6
68.0±3.4
66.8±3.4
66.6±3.2
67.4±4.5
<0.0001
e
[TBK/FFM]WHA, mmol/kg
V
69.0±1.1
68.5±1.3
67.8±1.4
66.7±1.1
66.4±1.3
<0.01
f
Error, %
V
4.2
3.3
3.3
3.2
4.8
TBK, mmol
V
3040±417 2998±365 2895±396 2787±285 2836±255 <0.001
g
TBKWHA , mmol
V
3028±251 3023±254 2931±271 2799±219 2755±212 <0.0001
Error, %
V
6.8
h
TBKWHAD, mmol
V
3024±318 3019±315 2931±345 2788±250 2800±252 <0.0001
g
Error, %
V
4.2
f
6.0
3.3
5.0
3.3
5.2
3.3
6.7
4.8
E-0199-2001.R3 28
Footnote Table 4
a
P+V= primary study group+validation group, b BMI= body mass index, cTBK= total body potassium,
d
TBK/FFMDXA= ratio of measured TBK by whole-body counter and measured FFM by DXA,
e
[TBK/FFM]WHA-ratio= the predicted TBK/FFM-ratio based on weight, height and age according to
equation in Table 2, fError within subjects coefficient of variation (2) between measured and predicted
TBK/FFM -ratio, or measured and predicted TBK,
g
TBKWHA= predicted TBK from weight, height and age according to equation in Table 2, h TBKWHAD=
predicted TBK from weight, height, age and FFM DXA according to equation in Table 2.
E-0199-2001.R3 29
Men
5
Women
A. ”before”, n=349
R2adj=3.6%; ß=0.013; p=0.0002
B. ”before”, n=423
R2adj=0.9%; ß=0.0061; p=0.03
weight, kg
C. ”after”,body
n=325
2
R adj=1.2%; ß=0.006; p=0.03
D. ”after”, n=411
R2adj=0 .1%; ß=0.0017; p=0.43
2,5
body weight-DXAsum, kg
0
-2,5
-5
-7,5
5
2,5
0
-2,5
-5
-7,5
40
50
60
70
80
90
100 110
40
50
body weight, kg
Figure 1.
60
70
80
90
100 110
E-0199-2001.R3 30
Men, n=161
Women, n=206
FFM DXA-FFM 68.1, kg
15
10
5
0
-5
-10
-15
FFM DXA-FFM WHA , kg
-20
15
A. R2 adj=1.3%; ß=-0.0478; p=0.08
B.R2adj=3.3%; ß=-0.0480; p=0.0053
C.R2 adj=0.0%; ß=0.0289; p=0.22
D.R2adj=0.0%; ß=0.0054; p=0.74
10
5
0
-5
-10
-15
-20
40
50
60
70
80
90
100 110
40
50
body weight, kg
Figure 2.
60
70
80
90
100 110
E-0199-2001.R3 31
Men, n=161
Women, n=206
15
BFDXA-BF68.1, kg
10
5
0
-5
-10
-15
A. R2adj=0.8%; ß=0.0416; p=0.14
B. R2adj=3.3%; ß=0.0500; p=0.0053
C. R2adj=0.7%; ß=-0.0350; p=0.15
D. R2adj=0.4%; ß=-0.00444; p=0.79
BF DXA-BFWHA, kg
-20
15
10
5
0
-5
-10
-15
-20
40
50
60
70
80
90
100 110
40
body weight , kg
Figure 3.
50
60
70
80
90
100 110