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European Journal of Heart Failure 2006 8(2):208-214; doi:10.1016/j.ejheart.2005.07.007
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© 2006 European Society of Cardiology

Measuring body composition in chronic heart failure: A comparison of methods

Nicole H.M.K. Uszko-Lencera,*, Francien Bothmera, Petra E.J. van Polb and Annemie M.W.J. Scholsa

a Department of Respiratory Medicine Department of Cardiology, University Hospital Maastricht The Netherlands
b Reinier de Graaf gasthuis Delft, The Netherlands

* Corresponding author. E-mail address: n.lencer{at}cardio.azm.nl


   Abstract
Top
 Abstract
1. Introduction
 2. Study population and...
 3. Statistical analyses
 4. Results
 5. Discussion
 6. Limitations
 7. Conclusion
 References
 
Aims: Fat-free mass (FFM) is increasingly recognized as a systemic marker of disease severity in chronic organ failure and is an important target for physiologic and pharmacologic interventions to improve functional status. The aim of this study was therefore to evaluate two clinical methods to assess FFM in patients with chronic heart failure (CHF) using deuterium dilution (DEU) as reference and bromide dilution to assess the ratio between intracellular (ICW) and extracellular water (ECW) as potential confounder.

Methods: Body composition was measured with dual-energy X-ray absorptiometry (DXA), bioelectrical impedance analysis (BIA) and DEU in 22 stable patients from our heart failure outpatient clinic and 24 healthy age matched controls.

Results: FFM values measured by DXA and DEU in patients (r=0.92, SEE: 3.1 kg) and controls (r=0.99, SEE: 1.3 kg) were strongly related. In both patients and controls, the inter method difference increased with higher values of FFM (DXA overestimating DEU). The ICW/ECW ratio was within the normal range and comparable between the groups. In patients, a highly significant correlation coefficient was found (r=0.93, SEE 2.1 p=0.01) between total body water (DEU) and height squared/resistance (Ht2/R). On multiple regression next to Ht2/R, body weight was an independent predictor of FFMDEU (r=0.95, SEE 2.5 kg, p<0.001; TBWdeu=0.528 Ht2/R+(0.182 weight)+8.277).

Conclusion: DXA and DEU are appropriate and interchangeable laboratory methods for assessment of FFM in clinically stable heart failure patients, however, overestimation of FFMDXA should be considered. BIA is a suitable clinical alternative for diagnostic purposes.

Key Words: Body composition • Chronic heart failure • Bioelectrical impedance analysis

Received October 27, 2004; Revised April 4, 2005; Accepted July 12, 2005


   1. Introduction
Top
 Abstract
 1. Introduction
2. Study population and...
 3. Statistical analyses
 4. Results
 5. Discussion
 6. Limitations
 7. Conclusion
 References
 
There is increasing evidence that body composition should be considered as a systemic marker of disease severity in chronic organ diseases such as chronic obstructive pulmonary disease [1], chronic renal failure [2] and chronic heart failure (CHF) [3]. A large number of clinical studies have shown that involuntary weight loss, commonly referred to as the ‘cachexia syndrome' is related to increased morbidity and mortality independent of the severity of the disease [4]. Remarkably, mortality rates are increased in underweight and normal weight patients relative to overweight and even obese patients [5,6]. This relationship is different from the U-shaped survival curve that is commonly seen for BMI in large population studies, which show increasing mortality with higher BMI [7,8], due to an abundance of fat mass (FM). This difference may be due to the specific adverse effects of excess loss of the metabolically and functionally active fat-free mass (FFM) on functional impairment and related morbidity and mortality in chronic wasting disease, independent of FM. Muscle mass is the largest component of FFM and the major determinant of skeletal muscle strength. In patients with advanced COPD, or chronic heart failure, skeletal muscle dysfunction has been identified as a better predictor of exercise intolerance than airflow obstruction or left ventricular ejection fraction respectively [9]. In patients with COPD it has been consistently reported that loss of FFM not only occurs in underweight or weight losing patients, but also in normal weight subjects [10].

Elucidation of the molecular regulation of muscle atrophy and hypertrophy is a hot topic in experimental research and significant progress has been made in recent years, which should lead to the development of novel pharmacologic interventions in the near future [11,12]. In addition, rehabilitation programs are now part of modern heart failure therapy to improve impaired exercise capacity [13,14], and the effect of different rehabilitative regimens on body composition and functional capacity has been well studied [15,16].

It is important to include body composition in the clinical characterization of patients with CHF for several reasons:

  1. 1) To select patients at risk or actually suffering from (hidden) loss of FFM.
  2. To target and evaluate current and novel rehabilitative strategies.
  3. To adjust peak oxygen consumption during incremental exercise, which is commonly used as a discriminator in the selection of patients for surgery or transplantation, to FFM, which is a better predictor of peak VO2 than body weight [17].

There is limited data on the pattern of tissue depletion in patients with CHF [18]. This lack of clinical data may be related to the fact that a two compartment model of body composition (i.e. distinguishing FFM and FM) is not applicable in congested patients, since water retention will selectively increase the extra cellular water compartment and therefore overestimate FFM, while two compartment models assume a stable ratio between the intracellular and extracellular water compartment [19,20].

The aim of this study was therefore to compare a laboratory based method and a clinical method to assess body composition in patients with CHF and in age- and sex-matched healthy control subjects, using deuterium dilution (DEU), a well established reference method and bromide dilution to assess the ratio between intracellular and extra cellular water as a potential confounder.


   2. Study population and methods
Top
 Abstract
 1. Introduction
 2. Study population and...
3. Statistical analyses
 4. Results
 5. Discussion
 6. Limitations
 7. Conclusion
 References
 
A group of 22 CHF patients from our outpatient clinic were included. All patients had heart failure due to left ventricular systolic dysfunction (left ventricular ejection fraction EF<45%: (mean±SD) 30±8%) for more than 6 months. All patients attended the heart failure outpatient clinic at least once in 3 months and were receiving standard heart failure medication. The stability of the patient's body fluid/weight, heart rhythm, kidney function and functional class were evaluated by the cardiologist and concomitant illnesses, medication and other complaints were assessed. Patient education, which covered fluid and salt intake, signs of deterioration and lifestyle, was provided by a specialised heart failure nurse. Inclusion criteria were: clinically stable CHF and no concomitant confounding diseases (malignancies, gastrointestinal tract, COPD or endocrine disorders).

Patients were matched for age and sex with 24 healthy volunteers recruited through an advertisement in a local newspaper. All volunteers underwent a physical examination to ensure that they had no significant pulmonary or cardiac disease or other diseases as mentioned above. Written informed consent was obtained from all subjects and the study was approved by the medical ethics committee of the University Hospital Maastricht (Maastricht, The Netherlands).

2.1. Body composition
Body composition was measured by three different methods: Dual-energy X-ray absorptiometry (DXA), Deuterium(-Broom) dilution (DEU) and Bioelectrical impedance analyses (BIA). In addition, Body weight was measured using an electronic beam scale with digital readout to the nearest 0.1 kg (model 707: Seca, Hamburg, Germany) with all subjects barefoot and wearing light indoor clothing. Body height was measured to the nearest 0.1 cm (model 220: Seca). Body mass index (BMI) was calculated by dividing bodyweight by height2.

2.1.1. Dual-energy X-ray absorptiometry (DXA)
Whole body FFM, consisting of lean mass and bone mineral content (BMC), and FM were determined using a DPX-L Bone densimeter (Lunar Radiation Corporation, Madison, WI) (voltage: 76.0 kVp; current: 150 µA; collimation: 1.68 mm). Each subject was required to lie in supine position on a table for approximately 15 min while the DXA scanner performed multiple fast speed transverse scans from head to toe with 1 cm intervals, with a scan area of 576 by 1968 mm and a sample interval of 1/32 s. A rectilinear scanner was used to detect density differences as the two levels of photon energy were projected through the subject. The DPX-L DXA scanner used a constant potential X-ray source at 78 kV and a K-edge filter to achieve a congruent beam of stable dual-energy radiation with effective energies of 38 and 70 keV. Data were collected in s maximum of 205 scan lines by 120 sample points (pixel size 4.8x9.6 mm). The entrance radiation dose was minimal (<0.02 mSv/scan). BMC, FM and lean mass were derived according to computer algorithms (Lunar software version 1.3) provided by the manufacturer. Body weight was obtained by adding lean mass, BMC and FM. Percentage body fat was calculated as FM relative to body weight. FFM was computed as the sum of lean mass and BMC. Bone mineral density (BMD) is BMC normalised for bone size and is expressed as grams per centimetre squared. Quality assurance tests were run daily. Three times a week, DXA software validation phantoms provided by the manufacturer, and closely reflecting the attenuation characteristics of the major constituents of the body (lean mass, fat mass and bone) were scanned.

2.1.2. Deuterium dilution (DEU)
Total body water (TBW) was estimated from deuterium dilution space. In the late evening, each subject consumed a pre-weighed oral dose of 2H2O (99.84 at.% excess) of 1 g/l predicted TBW (based on height, age, and sex). This dose was mixed into 50 ml deionised water.

In a random subgroup of 33 patients and control subjects extra cellular water (ECW) was measured by bromide dilution.

For the estimation of ECW, 60 mg sodium bromide/l predicted TBW (based on height, weight, age and sex) was added to the deuterium dose and administered at 22.00 hours. In the afternoon prior to dosing and approximately 10 h after dosing, venous blood and urine samples were collected; the latter was obtained after complete voiding of the bladder in the morning. An isotope ratio mass spectrometer was used to analyse 2H2O concentration in the urine according to the standard Maastricht protocol [21]. After complete equilibration, deuterium dilution space was calculated from the quantity of 2H2O administered and the urinary 2H2O concentrations. In calculating TBW, it was assumed that deuterium dilution space was a factor of 1.04 times greater than TBW, owing to the estimated 4% no aqueous hydrogen exchange and isotope fractionation. TBW was used to estimate deuterium-based FFM, based on the assumption that water represents a fixed proportion of the FFM (hydration factor of 0.73) and that fat is anhydrous. A two-compartment model was used to derive FFM: FFMDEU=TBW/(1.04x0.73). Fat mass was calculated by subtracting FFM from body weight and expressed as a percentage of body weight. Bromide concentration in serum ultra filtrate was determined by HPLC according to the anion-exchange chromatographic method. ECW was estimated by corrected bromide space (CBS) and calculated according to the following formula: CBS=Br dose(mmol)/(Brf-Brb)(mmol/l)x0.90x0.95. Where Brf is the final bromide concentration in the serum ultra filtrate (after 10 h of equilibrium), Brb is the background bromide concentration from the initial blood sample, 0.90 is the correction factor for bromide in the non extra cellular sites, and 0.95 is the correction factor for the Donan equilibrium.

2.1.3. Bioelectrical impedance analyses (BIA)
The principle of bio impedance (BI) is based on the conductance through body fluid of an electric current (800 µA, 50 kHz). Conductivity is higher in FFM, which contains body fluids and electrolytes, than in fat. Resistance was measured with subjects lying supine, on the right side as described by Lukaski et al. (BIA-101, RJL Systems, Detroit). Theoretically, fat-free mass is linearly related to height2/body resistance (Ht2/R).

2.1.4. Exercise testing
Patients underwent symptom-limited, incremental, cycle ergo metric test on an electro-magnetically braked cycle-ergo meter (ergo metrics 900, Ergoline, Frankfurt Germany) with breath by breath gas exchange analyses of expired air (Oxycon beta®, Jaeger, Wuerzburg, Germany). The initial workload of 0 W was increased by 10 W every minute. Peak maximal oxygen consumption heart rate and peak workload were determined at the moment of cessation.

All measurements were done on two consecutive days. The deuterium or deuterium-bromide dilution started on the evening of the first day. Equilibrium was reached over night, and next morning fasting blood and urine samples were taken. BIA was performed immediately afterwards, followed by DXA in the afternoon.


   3. Statistical analyses
Top
 Abstract
 1. Introduction
 2. Study population and...
 3. Statistical analyses
4. Results
 5. Discussion
 6. Limitations
 7. Conclusion
 References
 
Groups were analyzed using the unpaired Student's t-test (corrected for unequal variances, if appropriate).

3.1. Comparison between measurements
Comparison between the different methods of body composition were done using the statistical analysis of Bland and Altman [22]. To compare the DXA and DEU methods, the mean difference of the mean underestimation or overestimation from 0 (=bias) was calculated. In addition, the SD of the mean difference of the tests was calculated, which indicates the error of an individual prediction. The level of significance was determined as a p value<0.05.

3.2. Prediction equation for FFM by BIA
Following simple correlations a linear model was fitted to the data to enable variables that contributed to the total body water to be determined using stepwise linear regression analysis. The BIA predicted total body water was used to estimate BIA-FFM assuming a hydration factor of 0.73 of the FFM [23].


   4. Results
Top
 Abstract
 1. Introduction
 2. Study population and...
 3. Statistical analyses
 4. Results
5. Discussion
 6. Limitations
 7. Conclusion
 References
 
4.1. Characteristics of the study group
The study group characteristics are shown in Table 1. Patients had normal body weight with a mean BMI of 25.2 kg/m2 (SD 3.6), which was not significantly different from controls. Patients were all in New York Heart Association (NYHA) class II-III +, indicative of moderate to severe disability. Peak oxygen consumption was 15 (3.1) ml/kg/min.


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  		Table 1 Characteristics of study population

 
4.2. Comparison between DXA and deuterium (bromide) dilution
Fig. 1A shows that there was a strong relationship between the FFM measured with DXA and DEU in patients (R=0.92, SEE: 3.1 kg) and controls (R=0.99, SEE: 1.3 kg). Mean FFMDEU was lower than mean FFMDXA in patients and controls (mean difference 1.7 (3.1) kg). Fig. 1B shows that the inter method difference in FFM increases with higher values for FFM. The possible difference between patients and controls could not be attributed to differences in body water compartments, since the ratio between ECW and ICW was within the normal range for both groups (patients 0.73, controls 0.75) and unrelated to TBW (Fig. 2). Bone mineral content measured with DXA was also comparable and within the normal range for patients and controls (100.9 (8.9)% and 102.5 (9.0)%, respectively).


Figure 1
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  		Fig. 1 (A) Relationship between FFM measured by DXA and DEU in patients with CHF and healthy age matched control subjects. Squares=CHF patients and triangles=controls. (B) Bland Altman plot of inter method difference in FFM between DEU and DXA (kg) related to mean FFM (DEU and DXA) (kg) in patients with CHF and healthy age matched control subjects. Solid line: mean difference; dotted lines: mean difference±SD. Squares=CHF patients and triangles=controls.

 


Figure 2
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  		Fig. 2 Relationship between total body water (TBW (L)) and ECW (L)/ICW (L). Squares=CHF patients and triangles=controls.

 
4.3. Comparison between BIA and deuterium dilution
In Fig. 3 the relation between total body water (TBW) and Ht2/R is shown for patients. A highly significant correlation coefficient was found (r=0.93, SEE 2.1 p=0.01). On multiple regression next to Ht2/R, body weight was an independent predictor of FFMDEU (r=0.95, SEE 2.5 kg, p<0.001) The regression equation for FFM (kg) based on BIA was 0.528 Ht2/R+(0.182*weight)+8.277.


Figure 3
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  		Fig. 3 Linear regression between TBW and height2 (cm)/resistance ({Omega}). Closed squares=patients and open squares=controls.

 

   5. Discussion
Top
 Abstract
 1. Introduction
 2. Study population and...
 3. Statistical analyses
 4. Results
 5. Discussion
6. Limitations
 7. Conclusion
 References
 
In this study we evaluated the reliability and applicability of two clinical methods for measuring body composition in patients with chronic heart failure from our heart failure outpatient clinic. Mean left ventricular ejection fraction and peak oxygen consumption indicate that the study group had moderate to severe heart failure. The ratio between ICW and ECW in the CHF patients was not different from the healthy age and sex matched control group. The study group could therefore be considered as representative of patients with CHF eligible for rehabilitative therapeutic strategies.

Deuterium dilution was used as a well established reference method and bromide dilution was used to adjust for the potential confounding effect of fluid shifts [21]. Overall a good and comparable relation was found between FFM assessed by DXA and DEU in patients and control subjects. For the whole group, DXA overestimated FFM compared to DEU, which is in line with recent studies in healthy subjects [24,25]. This means that stable patients with CHF do not differ significantly from healthy elderly subjects, which was also illustrated by a similar ICW/ECW ratio, which was within the normal range. Therefore, we conclude that DXA is applicable as a marker of FFM but is not interchangeable with DEU in clinically stable heart failure patients. While DEU is generally assumed to be a more direct and accurate measure of body composition, DXA has the advantage that it is a well-established method to measure bone mineral density. Osteoporosis is a prevalent condition in chronic wasting diseases [18] and in the elderly [26]. Furthermore, DXA not only provides information about body composition at the whole body level, but also distinguishes between the trunk and the extremities [27]. Measurement of FFM may be useful to evaluate the efficacy of different anabolic interventions such as exercise, and anabolic pharmacological agents, while abnormal fat distribution has been linked to insulin resistance and may be useful to evaluate the efficacy of metabolic interventions targeted at improving insulin sensitivity in CHF [28].

In addition to being used as an outcome marker, assessment of body composition is used to screen for early signs of muscle wasting, to identify non-cardiac reasons for exercise intolerance and to adjust peak oxygen consumption during incremental exercise as commonly used discriminator for the selection of patients for surgery or transplantation. [29-31].

DXA and DEU are both expensive laboratory methods that are not applicable for clinical studies or large screening purposes. BIA however, is a non-invasive, cheap method to assess body composition. It can easily be performed during an outpatient clinic visit or at home by a trained nurse. However, in addition to a standardised procedure, it is generally assumed that pathology-specific BIA equations are needed, which have to be tested for validity in the populations for which they are intended. Recently the European Society of Enteral and Parenteral Nutrition published guidelines for the use of BIA in clinical practice [32,33]. With the exception of a small study by Steele et al., there are no validation studies in patients with CHF [34]. The second aim of our study was therefore to validate BIA and to establish a disease specific prediction equation for heart failure patients. Since body fluid and electrolytes are responsible for electrical conductance, which is used in BIA, the comparison with deuterium dilution as an index of total body water seems to be appropriate. We found a highly significant correlation between TBW and Ht2/R, comparable to those seen in previous studies in COPD patients and in healthy subjects [35]. On stepwise regression analyses only Ht2/R and weight, but not sex were predictors for TBW. Interestingly, when we compared the regression equation in our patient group with a previously reported regression equation for patients with COPD (y=0.58 ht2/res+(0.23 weight)+2.38 (SEE 22.5 kg, r2=0.88) [35], the slope and intercept of the two regression lines were similar and not significantly different. Age was comparable in these two groups of patients. Although we present another regression equation, specifically developed for patients with CHF, our results indicate that generic factors such as age and nutritional status are perhaps more important in the selection of an appropriate regression equation for screening purposes in chronic wasting conditions including CHF than regression equations that are validated in a specific disease. This is clinically very important, since it allows comparative studies between different patient groups to elucidate the mechanisms of cachexia and the efficacy of therapeutic interventions as well as the applicability of recently developed normal values for body composition [34,36].


   6. Limitations
Top
 Abstract
 1. Introduction
 2. Study population and...
 3. Statistical analyses
 4. Results
 5. Discussion
 6. Limitations
7. Conclusion
 References
 
The sample size of our study is rather small. However the power was determined based on previous studies in other well-defined patient groups [35]. The study groups were matched for sex. Assessment of possible differences between males and females in the inter-method comparison was beyond the scope of this study. The patients recruited from our specialised heart failure clinic had stable fluid status and medication. As this is not the case in all heart failure patients, applicability of the clinical methods in the general population needs to be confirmed.


   7. Conclusion
Top
 Abstract
 1. Introduction
 2. Study population and...
 3. Statistical analyses
 4. Results
 5. Discussion
 6. Limitations
 7. Conclusion
References
 
Our data suggest that dual energy X-ray absorptiometry and deuterium dilution are applicable and interchangeable methods for the assessment of body composition in CHF patients. We found a comparable ratio of extra cellular and intracellular water in patients and controls, which was unrelated to total body water. Furthermore we established a prediction equation for bioelectrical impedance measurement in CHF.


   References
Top
 Abstract
 1. Introduction
 2. Study population and...
 3. Statistical analyses
 4. Results
 5. Discussion
 6. Limitations
 7. Conclusion
 References
 

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M A Spruit, R-M A Eterman, V A C V Hellwig, P P Janssen, E F M Wouters, and N H M K Uszko-Lencer
Effects of moderate-to-high intensity resistance training in patients with chronic heart failure
Heart, September 1, 2009; 95(17): 1399 - 1408.
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 ChestHome page
M. J. H. Sillen, C. M. Speksnijder, R.-M. A. Eterman, P. P. Janssen, S. S. Wagers, E. F. M. Wouters, N. H. M. K. Uszko-Lencer, and M. A. Spruit
Effects of Neuromuscular Electrical Stimulation of Muscles of Ambulation in Patients With Chronic Heart Failure or COPD: A Systematic Review of the English-Language Literature
Chest, July 1, 2009; 136(1): 44 - 61.
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 Eur J Heart FailHome page
A. Sandek and M. Rauchhaus
Use of bioimpedance analysis in patients with chronic heart failure?
Eur J Heart Fail, January 1, 2007; 9(1): 105 - 105.
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