Assessment of body composition by dual energy X-ray absorptiometry, skinfold thickness and creatinine kinetics in chronic kidney disease patients

Carla Maria Avesani, Sergio Antonio Draibe, Maria Ayako Kamimura, Miguel Cendoroglo, Alessandra Pedrosa, Marise Lazaretti Castro and Lilian Cuppari

Division of Nephrology and Nutrition, Graduate Program of the Federal University of São Paulo, São Paulo, Brazil

Correspondence and offprint requests to: Carla Maria Avesani, Federal University of Sao Paulo, Nephrology, Sao Paulo SP, Brazil. Email: carla{at}carrenho.com.br



   Abstract
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Background. Finding a method that can be routinely used to assess body composition with minimum error is still a challenge for those who work with chronic kidney disease (CKD) patients. This study aimed to compare the value of two surrogate techniques, skinfold thickness (SKF) and creatinine kinetics (CK) with dual energy X-ray absorptiometry (DEXA) as the reference method for measuring body fat and fat-free mass in non-dialysed CKD patients.

Methods. The body fat and fat-free mass of 50 non-dialysed CKD patients (38 male, 12 female) were measured by DEXA and compared with measurements obtained by SKF and CK.

Results. The mean values of body fat and fat-free mass obtained by SKF and CK differed significantly from measurements made by DEXA. The intra-class correlation coefficient (r) for body fat between SKF and DEXA (r = 0.74) and between CK and DEXA (r = 0.47) indicated a moderate degree of reproducibility. A Bland and Altman plot analysis showed a better agreement between SKF and DEXA [5.8 ± 3.9% (–2.0 to 13.6)] than between CK and DEXA [8.8 ± 8.8% (–8.8 to 26.4)]. Regarding fat-free mass, the intra-class correlation coefficient (r) between SKF and DEXA (r = 0.85) indicated a good degree of reproducibility, while that between SKF and CK (r = 0.57) indicated a moderate degree of reproducibility. The Bland and Altman plot analysis for fat-free mass showed that DEXA agreed better with SKF [–3.1 ± 3.4 kg (–9.9 to 3.7)] than with CK [–5.5 ± 6.4 kg (–18.2 to 7.3)].

Conclusion. Skinfold thickness seems to be the method of choice for evaluating body fat. The limitations inherent to DEXA in evaluating fat-free mass makes it difficult to designate an alternate method of choice for assessing this body compartment.

Keywords: body fat; chronic kidney disease; creatinine kinetics; DEXA; fat-free mass; skinfold thickness



   Introduction
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Malnutrition is widespread among patients with chronic kidney disease (CKD), and it is one of the main factors that increase morbidity and mortality in these patients [1]. Therefore, monitoring body composition is important for prescribing adequate nutritional therapy and preventing protein–energy malnutrition.

Hence, in this context it is important to identify a technique for assessing body composition that is simple, reliable, non-invasive and cost-effective and could be routinely used in the clinical setting. Among the commonly used methods, dual energy X-ray absorptiometry (DEXA) has the advantage of assessing the three main body components (fat mass, fat-free mass and bone mineral mass) with high precision and with minimal exposure of patients to radiation [2]. DEXA, however, has the disadvantages of being expensive, only moderately reliable and of including body water in the fat-free mass compartment [3, 4]. Although DEXA is not a gold standard, it has been proposed by the Kidney Disease Outcomes Quality Initiative (K-DOQI) as a reference method to assess body composition in CKD patients [5]. The sum of skinfold thicknesses (SKF) provides an estimation of the percent of body fat, and by subtraction from total body weight, yields fat-free mass [6]. SKF is very useful clinically, as it is a non-invasive and cost-effective method, but it has moderate reliability and high inter-observer variation [7]. The creatinine kinetics (CK) method can also be routinely used to estimate fat-free mass. It is based on creatinine excretion and has the advantage of being little influenced by the hydration status of the body [8]. The disadvantage of this method is that it requires great cooperation from the patient for the 24 h urine collection [8]. In addition, SKF and CK have the disadvantage of using predictive equations, derived from regression analyses that were based on data from a specific population.

These methods have been frequently used to assess body composition in healthy individuals. However, abnormalities often present in CKD patients, such as fluid retention and bone disease, may affect the validity of these techniques in this population [9]. Previous studies have addressed the validity of simple methods to assess body composition in patients with chronic renal disease, but most of them have been conducted in patients on haemodialysis or peritoneal dialysis [3,4, 10–17]. Therefore, studies in non-dialysed CKD patients are lacking.

This study aimed to evaluate the agreement of, SKF, CK with DEXA for measuring body fat and fat-free mass in non-dialysed CKD patients.



   Subjects and methods
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
We entrolled in this study 50 non-dialysed CKD patients treated in the outpatient clinic of the Federal University of São Paulo (UNIFESP). The subjects were older than 18 years old and clinically stable, and had mild to advanced CKD with no oedema. Most of the patients (n = 40; 80%) had a diet consisting of 30–35 kcal/kg/day and 0.6–0.8 g of protein/kg/day, and were on diuretics and antihypertensive medications (n = 45; 90%). No patient took immunosuppressants or corticosteroids. Of the cohort, 21 diabetic patients were being treated with insulin and three were taking oral hypoglycemic agents.

The local Human Investigation Review Committee approved this study, and informed consent was obtained from each subject.

Methods
Study protocol
All subjects had their body composition assessed by DEXA, and by the sum of SKF and by CK. DEXA was used as the reference method, to compare the results obtained by SKF and CK.

Body mass index (BMI) was calculated for each patient as weight (kg)/height (m2).

In order to identify other influences, if any, on the measurements of body composition, the patients were divided according to gender and the presence of diabetes mellitus.

Dual energy X-ray absorptiometry
DEXA was performed using a Lunar DPX Bone Densitometer scanner (Lunar Radiation Corporation, Madison, WI) with the patient in the supine position. The DEXA system performs rectilinear scans over the length of the body. The scan begins at the top of the patient's head and moves downward toward the feet. The program allows scanning up to 205 lines. During the scan, the source shutter opens to emit an X-ray beam. Software calculates the grams of fat tissue, percent of fat mass, grams of lean tissue and grams of bone mineral mass. Fat-free mass is calculated as the sum of lean tissue plus bone mineral mass.

Skinfold thickness
SKF measurements were performed by a single observer at four sites (triceps, biceps, subscapular and suprailiac) according to standard techniques. The skinfold measurements were performed in the non-dominant arm using the Lange® skinfold caliper (Cambridge Instrument, Cambridge, MA, USA). Three sets of measurements were averaged for each site. Body density was calculated according to the formula of Durnin and Womersley [6] and percent of body fat was then derived using Siri's equation [18]. Fat-free mass in kilograms was calculated subtracting body fat from total body weight.

Creatinine kinetics
The CK method calculates fat-free mass as follows, according to the formula of Keshaviah et al. [10] based on Forbes’ and Bruining's work [8]:

Equation 1: FFM (kg) = 0.029 x daily creatinine production (mg/dl) + 7.38 [8]

Equation 2: Creatinine production (mg/dl) = CE (mg/day) + MD (mg/dl) [10]

Equation 3: MD (mg/dl) = 0.38 x serum creatinine (mg/dl) x BW (kg) [10]

where FFM is fat-free mass, CE is creatinine excretion, MD is metabolic degradation and BW is body weight. Percent of body fat was obtained subtracting percent of fat-free mass from 100.

Since body fat measured by SKF is primarily given as a percentage figure and fat-free mass measured by DEXA and CK is primarily given in kilograms, we judged that it would be more appropriate to report the data regarding body fat in percent and the data regarding fat-free mass in kilograms.

Biochemical data
Fasting blood samples were drawn to measure serum creatinine. Twenty-four hour urine was obtained for the determination of urinary creatinine concentration. Serum and urinary creatinine were measured by a Cobas Mira Plus autoanalyser (Roche Diagnostic System, Basel, Switzerland), which employs the modified Jaffé reaction. Glomerular filtration rate was estimated using standard creatinine clearance (24 h urine collection) corrected for body surface area (1.73 m2).

Statistical analysis
The results are expressed as mean±standard deviation. ANOVA for repeated measures was used for comparisons of the mean values of body fat and fat-free mass assessed by the three techniques.

The intra-class correlation coefficient (r) was used to test the reproducibility of body fat and fat-free mass measured by SKF and CK and compared with DEXA. Values of the coefficient below 0.4 were considered to indicate poor reproducibility, values between 0.4 and 0.75, medium reproducibility and values above 0.75, good reproducibility [19]. In addition, Bland and Altman plot analysis was applied to visually assess agreement between the two methods in each patient [20]. This analysis consists of a graph, in which the difference between the measurement of each method (y-axis, i.e. method A – method B), is plotted against their mean difference (x-axis, i.e. (method A + method B)/2). The 95% limits of individual agreement between the two methods were calculated as the mean difference between two methods±2.0 standard deviations. The ANOVA and mean±standard deviation of all variables were tested by True Epistat software (Texas, USA, 1995), while the intra-class correlation coefficient was calculated by Stata Corp software, version 7.0 (Texas, USA, 2001).



   Results
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Table 1 shows the main characteristics of the patients. There was a predominance of males (76 vs 24% female). Mean BMI indicated the subjects to be overweight. A more detailed analysis of patients’ BMI showed that 21 patients (42%) had BMI in the normal range, 20 (40%) were overweight and 9 (18%) were obese. The mean creatinine clearance indicated, according to the National Kidney Foundation Classification, stage 3 CKD [21]. The causes of CKD were: diabetes mellitus in 20 patients (40%), hypertensive nephrosclerosis in 20 patients (40%), other causes in two patients (4%), and in eight patients (16%) the causes of CKD were not determined. In the entire cohort, 25 patients (50%) had diabetes mellitus.


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Table 1. Patients’ characteristics (n = 50)

 
Body fat
The mean values of percent of body fat measured by the three techniques are shown in Table 2. As can be observed, the percent body fat of the entire group obtained by either SKF or CK was significantly higher than that derived by DEXA. When the cohort was divided according to gender (Table 2), results similar to those found for the entire group were observed for male and female patients and for diabetic and non-diabetic patients (data not shown). The results concerning the intra-class coefficients of correlation are presented in Table 3. Although the intra-class coefficients of correlation (r) obtained between both SKF and DEXA and between CK and DEXA were indicative of a moderate degree of reproducibility, the coefficient obtained between SKF and DEXA was higher than that obtained between CK and DEXA. In addition, the confidence interval calculated for SKF and DEXA was shorter than that for CK and DEXA.


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Table 2. Body fat and fat-free mass assessed by DEXA, SKF and CK

 

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Table 3. Intraclass coefficients of correlation

 
The Bland and Altman plot analysis for percent of body fat is illustrated in Figure 1a and b. The mean difference and 95% limits of agreement between SKF and DEXA were smaller than between CK and DEXA. These results indicate that, although both mean differences are statistically different from zero, SKF agreed more closely with DEXA than did with CK.



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Fig. 1. Comparison of the agreements between skinfold thickness (SKF) and DEXA (a), and between creatinine kinetics (CK) and DEXA (b) in the measurement of body fat (filled diamonds, male; open diamonds, female).

 
Extreme values of body fat and gender did not determine larger inter-method differences; there were homogeneous distributions of the points in the graphs (Figure 1a and b). Indeed, the inter-method differences between SKF and DEXA and between CK and DEXA did not correlate significantly with BMI ({Delta}SKF – DEXA vs BMI: r = –0.03, P = 0.6; {Delta}CK – DEXA vs BMI: r = –0.26, P = 0.06). Furthermore, these graphs also demonstrate that, using DEXA as the reference method, both SKF and CK overestimate body fat in the majority of the patients (90 and 86%, respectively).

Fat-free mass
The mean values of fat-free mass measured by the different techniques are shown in Table 2. It can be noted that the fat-free mass of the entire group measured by SKF and CK was significantly lower than that obtained by DEXA. When the group was divided according to gender, only in females were the mean values of fat-free mass measured by SKF not statistically different from DEXA (Table 2). When the group was divided according to the presence of diabetes, the same pattern observed for the entire group was seen in diabetic and non-diabetic patients (data not shown). Table 3 shows that the intra-class coefficient of correlation (r) obtained between SKF and DEXA was indicative of good reproducibility, but the coefficient obtained between CK and DEXA represented moderate reproducibility. It can also be seen that the confidence interval for SKF and DEXA was shorter than the one observed for CK and DEXA.

The Bland and Altman comparisons of techniques for measuring fat-free mass are illustrated in Figure 2a and b. The mean difference and the 95% limits of agreement between SKF and DEXA indicate that fat-free mass measured by SKF has a better agreement with DEXA than with CK. Furthermore, the differences between the fat-free masses measured by SKF and DEXA and by CK and DEXA were influenced neither by extreme values for the fat-free mass nor by gender. In fact, BMI was not correlated with differences in fat-free mass between SKF and DEXA ({Delta}SKF – DEXA vs BMI: r = 0.08, P = 0.81) or between CK and DEXA ({Delta}CK – DEXA vs BMI: r = 0.31, P = 0.10). These graphs also demonstrate that, using DEXA as a reference method, SKF and CK underestimated fat-free mass in 84 and 80% of the patients, respectively.



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Fig. 2. Comparison of the agreements between skinfold thickness (SKF) and DEXA (a) and between creatinine kinetics (CK) and DEXA (b) in the measurement of fat-free mass (filled diamonds, male; open diamonds, female).

 


   Discussion
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
This study aimed to evaluate the agreement of SKF and CK with DEXA for measuring body fat and fat-free mass in non-dialysed CKD patients.

Body fat
Our findings show that the mean values of body fat assessed by SKF and CK were significantly higher than those obtained by DEXA; however, there was a better agreement between SKF and DEXA than between CK and DEXA. Considering DEXA as a reference method, our findings suggest that SKF presented an advantage over CK for assessing body fat.

The worse results obtained by CK for assessing body fat might be related to methodological features and to the hydration status of patients. SKF and DEXA primarily yield the amount of body fat [2,6], while CK primarily derives fat-free mass [8]. The estimation of body fat by CK is obtained by the subtraction of fat-free mass from total body weight. Because the measurement of fat-free mass by CK suffers little from the hydration status [3,10], an excess of body fluid could erroneously result in a higher figure for body fat. Therefore, if the patient is overhydrated, CK might yield falsely high values of body fat. Although our patients had no oedema, it is possible that some degree of fluid overload may have occurred. Unfortunately, previous studies cannot confirm our assumptions, as to the best of our knowledge, our study is the first to use CK in the estimation of body fat in non-dialyzed CKD patients.

SKF measurement is a simple, non-invasive, cost-effective and very useful method in clinical practice. The disadvantages of this technique are the large inter-observer variations and its poor precision in obese individuals [7]. However, these factors did not contribute to the significant inter-method difference found between SKF and DEXA, since SKF was measured by a single observer and no significant correlation was found between inter-method differences and BMI.

The comparison of body fat calculated with SKF and DEXA in patients with chronic renal failure has been previously studied. Woodrow et al. [12] and Kamimura et al. [15] found that body fat measures obtained by SKF were more similar to DEXA than those obtained using bioelectrical impedance. Similarly, in renal transplant patients the agreement between SKF and DEXA in the estimation of body fat was slightly better than between DEXA and bioelectrical impedance [14]. In view of our findings, SKF seems to be a method of choice, compared with CK, to estimate body fat. In order to confirm the reliability of SKF to estimate body fat in CKD patients, comparisons with gold standard techniques, such as hydrodensitometry, computerized tomography and magnetic ressonance, are still necessary.

Fat-free mass
In our study, fat-free mass measured by SKF had a better agreement with DEXA and a better degree of reproducibility than it did with CK. The reason for these findings may be attributed to some features of CK. The CK method estimates fat-free mass based upon the assumption that, in the steady state, creatinine production is proportional to the amount of fat-free mass [8]. Creatinine production is equal to the sum of metabolic degradation and creatinine excretion [10]. Thus, the accuracy of this method depends on the correct estimation of metabolic degradation and creatinine excretion. In our study, metabolic degradation was calculated using the equation proposed by Keshaviah et al. [10] (equation 3 shown in the methodology), which was based on data from haemodialysis and peritoneal dialysis patients, and was not validated for non-dialysed CKD patients. Moreover, creatinine excretion was measured in 24 h urine collection, which require great cooperation from patients. It has been shown that a 15 min error in voiding time for a 24 h collection period leads to a 1% error in the value of urinary creatinine excretion [8]. Therefore, although our patients were instructed to collect urine very carefully, imprecise urine collections may have occurred, which to a lesser extent, could have led to errors in the calculation of fat-free mass by CK. Diet may be another factor to influence the measures of fat-free mass obtained by CK [8]. Although the idea is controversial, meat intake may raise the amount of creatinine excreted, leading to the overestimation of fat-free mass [8]. This possibility did not seem to come into play in our study, as fat-free mass estimated by CK was significantly lower than the one estimated by the other techniques. Similarly, previous studies on peritoneal dialysis patients also have reported that fat-free mass assessed by CK was significantly lower than fat-free mass assessed by other methods [3, 10, 11, 13].

In this study, DEXA was used as a reference method to estimate fat-free mass. However, it is well known that fat-free mass measured by DEXA is influenced by the hydration status of the patient. This has been shown in studies conducted in haemodialysis patients, in whom the amount of fat-free mass decreased after the dialysis session and the difference was equivalent to the amount of the ultrafiltrate [4]. Similar results were noted in peritoneal dialysis patients in whom fat-free mass estimated by DEXA also decreased after the drainage of the dialysis fluid from the abdomen [3]. Another limitation of DEXA for assessing the fat-free mass of CKD patients is that it assumes that 73% of the lean mass is water. This may not be true for haemodialysis patients, since Arkouche et al. [22] measured body water by the oxygen 18 labelled-water method in 18 patients on haemodialysis and found that 69.4±3% of the lean mass of those patients was water. In non-dialysed CKD patients, it is not known if the hydration status of the lean mass is equivalent to 73%, as it is assumed to be for healthy individuals. Estimation of fat-free mass by SKF might be also influenced by hydration status, since this method estimates fat-free mass as the difference of body fat from total body weight. On the other hand, the influence of body water on the fat-free mass estimated by the CK method is minimal [10]. Although our patients had no oedema, we cannot exclude the possibility of some degree of fluid overload. Thus, the higher mean values of fat-free mass measured by SKF and DEXA may be explained by the fact that these two techniques included the excess of body water in the fat-free mass compartment. Indeed, previous studies in haemodialysis and in peritoneal dialysis patients also have reported that fat-free mass measured by those techniques, such as DEXA, SKF and bioelectrical impedance, that are readily influenced by body water were higher than the fat-free mass estimated by CK [3,10,11,13,17]. Of particular importance is the study of Lo et al. [11] on peritoneal dialysis patients. They reported that the fat-free mass assessed by counting total body potassium, a method that is not influenced by hydration status, was better correlated with CK than with SKF, bioelectrical impedance or near-infrared interactance. The present study does not provide evidence to conclude which of these two techniques, SKF or CK, is more reliable for estimating fat-free mass.

In conclusion, SKF presented a better agreement with DEXA than it did with CK for both body compartments. As DEXA is a reliable method to assess body fat, SKF seems to be the method of choice to evaluate body fat. However, since DEXA might have some drawbacks for measuring fat-free mass, further cross-sectional and longitudinal studies concerning the applicability of SKF or CK for measuring fat-free mass in CKD patients are necessary.



   Acknowledgments
 
The authors thank Professor Clovis and Alexandre Shinzato for their helpful statistical assistance, and Professor Dirce Maria Sigulem for support during the research. This study was supported by the Oswaldo Ramos Foundation and by Fundação de Amparo à Pesquisa do Estado de São Paulo (Fapesp).

Conflict of interest statement. The author and co-authors declare that there is no conflict of interest in this study.



   References
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 

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Received for publication: 15. 7.03
Accepted in revised form: 18. 3.04