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Measuring nutritional status in children with chronic kidney disease^1,2,3

¹ From the Division of Nephrology, Department of Pediatrics, The Children’s Hospital of Philadelphia and the Department of Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia.

² Supported by a National Research Service Award (F32DK62637-01) and by a Duncan L Gordon Fellowship from the Hospital for Sick Children Foundation, Toronto, Canada (to BJF).

³ Reprints not available. Address correspondence to BJ Foster, Montreal Children’s Hospital, 2300 Tupper Avenue, Montreal, QC, Canada, H3H 1D3. E-mail: beth.foster{at}muhc.mc.mcgill.ca.

	ABSTRACT

TOP ABSTRACT INTRODUCTION FUNDAMENTALS OF BODY-COMPOSITION... CURRENT RECOMMENDATIONS FOR... OTHER NUTRITIONAL ASSESSMENT... SUMMARY Appendix A REFERENCES

 
Children with chronic kidney disease (CKD) are at risk of protein-energy malnutrition. Existing clinical practice guidelines recognize this and recommend specific methods to assess nutritional status in patients with CKD. This review summarizes the methods for nutritional assessment currently recommended in the United States for children with CKD and details the strengths and limitations of these techniques in the clinical setting. Dietary assessment, serum albumin, height, estimated dry weight, weight/height index, upper arm anthropometry, head circumference, and the protein equivalent of nitrogen appearance are reviewed. We also describe methods for body-composition assessment, such as dual-energy X-ray absorptiometry, bioelectrical impedance analysis (BIA), total body potassium, densitometry, and in vivo neutron activation analysis, pointing out some advantages and disadvantages of each. In CKD, fluid overload is the most important factor leading to misinterpretation of nutritional assessment measures. Abnormalities in the distribution of fat and lean tissue may also compromise the interpretation of some anthropometric measures. In addition, metabolic abnormalities may influence the results obtained by some techniques. Issues specific to evaluating nutritional status in the pediatric population are also discussed, including normalization of nutritional measures to body size and sexual maturity. We stress the importance of expressing body-composition measures relative to height in a population in whom short stature is highly prevalent.

Key Words: Nutritional status • chronic renal insufficiency • assessment techniques • growth • malnutrition • reference values • methods

	INTRODUCTION

TOP ABSTRACT INTRODUCTION FUNDAMENTALS OF BODY-COMPOSITION... CURRENT RECOMMENDATIONS FOR... OTHER NUTRITIONAL ASSESSMENT... SUMMARY Appendix A REFERENCES

 
Malnutrition is recognized to be a serious and common complication of chronic kidney disease (CKD) and is associated with increased morbidity and mortality in children (1–3) and adults (4–8). The importance of nutritional status has been emphasized in numerous clinical practice guidelines on the care of patients with CKD. American (9–11), Canadian (12), European (13, 14), and Australian (15) guidelines all address methods and frequency of nutritional assessment as well as nutritional management. Most of these guidelines, however, are based on expert opinion rather than on evidence. In addition, the limitations of these assessment methods in the setting of CKD are not addressed. Finally, few data are available on nutrition assessment in children with CKD.

Nutritional status is particularly important in children, because it influences growth, sexual development, and neurocognitive development (16, 17). The effect of nutrition is especially marked in infants; growth and developmental deficits acquired during infancy may never fully recover. Nutritional status should be monitored regularly in all children with CKD; however, the best measures of nutritional status in children with CKD have not been established.

Nutritional status is a complex concept that is difficult to define. Adequate nutritional status can perhaps be best defined as maintenance of a normal pattern of growth and a normal body composition by consumption of appropriate amounts and types of food. Malnutrition is even more difficult to define. Although severe malnutrition is easily recognized, the distinction between adequate nutrition and mild-to-moderate malnutrition is not clear. The World Health Organization recommends that a cutoff of 2 SDs below the National Center for Health Statistics sex-specific medians for weight-for-age, height-for-age, and weight-for-height be used to distinguish adequately from inadequately nourished children (18). Reference data are not available for all measures of body composition. Most studies in the existing literature included a healthy reference group and considered anything below the range seen in healthy persons inadequate.

Because it is a complex concept, no single measurement adequately reflects nutritional status. A multistaged evaluation of body composition is required to give a complete and accurate picture of nutritional status. The techniques available for assessing body composition range in sophistication from simple height and weight measures to complex multicomponent models that use specialized equipment. It is important to recognize that all techniques were developed and validated in healthy populations. As a result, applicability in disease states may be limited.

Kidney disease provides a striking example of the challenges of nutritional assessment in children with disease. The term CKD encompasses the entire spectrum of abnormal kidney function, from very mild disease to a complete absence of kidney function (19). For the purposes of this review, childhood CKD is divided into 2 categories: chronic renal insufficiency (CRI), defined on the basis of a glomerular filtration rate (GFR) <90 mL · min^–1 · 1.73 m^–2 (19), and end-stage renal disease (ESRD), defined on the basis of the need for dialysis or transplantation. In ESRD, fluid overload is the most important problem leading to misinterpretation of nutritional assessment measures. Children with severe CRI may also have subtle disturbances in fluid balance. Children with chronic nephrotic syndrome will have fluid overload unrelated to the level of renal function. Fluid overload will influence weight, estimates of lean body mass, and anthropometric measures such as arm circumference and skinfold-thickness measures. Abnormalities in the regional distribution of fat and lean tissue may also compromise the interpretation of skinfold-thickness and arm indexes. In addition, biochemical abnormalities such as hyperkalemia and elevated urea may influence the results obtained by some techniques.

This review summarizes the methods of nutritional assessment currently recommended for children with CKD, describes additional techniques available for assessment of body composition, and details the advantages and disadvantages of these methods in the setting of CKD. Although persons with CKD are not immune to micronutrient deficiencies, current guidelines focus on protein-energy malnutrition. Therefore, this review focuses on the assessment of protein-energy nutritional status.

Before discussing assessment methods, we define fundamental concepts in body composition. We also discuss the unique challenges of evaluating body composition in children, including the importance of normalizing measures for body size and maturity.

	FUNDAMENTALS OF BODY-COMPOSITION ASSESSMENT

TOP ABSTRACT INTRODUCTION FUNDAMENTALS OF BODY-COMPOSITION... CURRENT RECOMMENDATIONS FOR... OTHER NUTRITIONAL ASSESSMENT... SUMMARY Appendix A REFERENCES

 
Body compartments
Body composition can be conceptualized in many different ways: from fairly simple models, with only 2 compartments, to multicomponent models that resolve the body into 4–6 different compartments (20). Traditionally, most investigators and clinicians have focused on 2 compartments: fat mass and fat-free mass. Strictly speaking, the term fat-free mass excludes the essential fats present in cell membranes and nervous tissue. Because we are usually more interested in nonessential fat stores, the term lean body mass is used to denote lean tissue, including essential fats. Fat mass refers to the remaining nonessential fat. For the purposes of this review, fat-free mass and lean body mass are used interchangeably.

Whereas fat mass contains only fat, lean body mass contains water, mineral, protein, and small amounts of other substances such as glycogen and nucleic acids. Lean body mass is frequently broken down anatomically, into lean soft tissue mass and bone mineral mass. Alternatively, lean body mass can be divided into its water and solid (mineral and protein) components. These represent 3-compartment models. A 4-compartment model of body composition can be created by further subdividing the lean soft tissue mass into its water and protein components. These models are outlined in Figure 1. More complex models based on molecular and atomic components can also be created (20).

View larger version (20K): [in this window] [in a new window]   FIGURE 1.. Two-compartment, 3-compartment, and 4-compartment models for body-composition assessment.

Normalization
Assessment of body-composition measures across a range of ages and body sizes requires normalization to allow meaningful interpretation. Measures may be normalized for age, sex, Tanner stage, body size, or any combination of these factors. Body compartment masses must be normalized to body size.

It is common practice to report fat mass as percentage body fat (ie, the percentage of total body weight composed of fat). Fat-free mass, on the other hand, is most frequently reported as mass (kg). Both of these designations are problematic. The absolute fat-free mass is almost meaningless without normalization to body size, particularly in children. A tall child may have a greater fat-free mass than a short child just by virtue of being taller, even in the presence of wasting in the taller child. Although the expression of fat mass as percentage body fat serves to normalize fat mass to body size, this approach discounts interindividual variation in lean mass. Persons of the same height with the same fat mass will only have the same percentage body fat if their lean masses are identical. The problems with percentage body fat are illustrated in a patient receiving dialysis whose lean mass, and therefore percentage body fat, is different before and after dialytic fluid removal, without any real change in fat mass. To circumvent these problems, the fat mass index and fat-free mass index have been proposed as alternative ways of expressing fat mass and fat-free mass. This method normalizes fat mass and fat-free mass to height by dividing each by height squared (22). The fat mass index and fat-free mass index are conceptually similar to body mass index (BMI; weight/height²).

Measures of growth and nutritional status are often expressed as SD scores or z scores. SD scores are an alternative method of expressing percentiles; these 2 measures are interchangeable, as shown in Figure 2. An SD score is the difference, in SD units, between an individual’s measure and the mean for children with the same characteristics. For example, one could calculate a height SD score for age and sex (see Appendix A, Equation A1) by subtracting the mean height of a child of the same age and sex from the observed height and then dividing by the SD for children of that age and sex. This is not as simple as it appears. Because both age and height are continuous variables, statistical manipulations are required to determine the mean and SD at every possible age. Just as age increases smoothly, so too do means and SDs for height. In addition, the distribution of heights (or other measures) at any given age may not be normally distributed. One technique that deals with these issues is the LMS method, which is described in detail elsewhere (23).

View larger version (16K): [in this window] [in a new window]   FIGURE 2.. Hypothetical normal distribution, with z scores (SD scores) and the corresponding percentiles. With the use of height-for-age as an example, a z score of 0 indicates the mean height at a given age, which corresponds to the 50th percentile, ie, the point at which 50% of the total area under the curve lies to the left. At the 16th percentile, 16% of the total area under the curve lies to the left.

Reference data and the challenge of childhood
Evaluating nutritional status in any population requires high-quality reference values for body-composition measures in healthy persons. Unfortunately, reference values are available for only a limited number of measures in both adults (24, 25) and children (25, 26) (Table 1). Note that reference data for skinfold thicknesses, arm indexes, and height velocity were derived from whites only and may not represent the true variability of the general population (25, 27).

Racial differences in body composition and body proportions also exist. Blacks have a greater bone mineral content and a greater lean body mass for height than do whites (32). Blacks carry a greater proportion of the total fat mass on the trunk; fat tends to be deposited on the back and sides of the body in blacks but on the front in whites (32). Whites tend to have shorter limbs and longer trunks than do blacks (32). To account for these racial differences in body composition, race-specific reference values would be ideal.

When reference data are broken down into increasingly specific strata, such as sex, pubertal status, and race, greater numbers of children are required in the reference group. Each category must be large enough to represent the variability of the general population in that stratum. The World Health Organization recommends that each category have 200 children (33). Age, maturation, race, and sex-specific reference values for all body-composition variables—normalized appropriately to body size—would be ideal. However, even the largest available reference data sets (Table 1) only consider age and sex. Therefore, analytic techniques such as multivariate regression are needed to adjust for the potentially confounding effects of race and maturation in the assessment of children with CKD compared with in healthy children.

	CURRENT RECOMMENDATIONS FOR EVALUATION OF NUTRITIONAL STATUS IN CHILDREN WITH CHRONIC KIDNEY DISEASE

TOP ABSTRACT INTRODUCTION FUNDAMENTALS OF BODY-COMPOSITION... CURRENT RECOMMENDATIONS FOR... OTHER NUTRITIONAL ASSESSMENT... SUMMARY Appendix A REFERENCES

 
End-stage renal disease
The Kidney Disease Outcome Quality Initiative (K/DOQI) Clinical Practice Guidelines for Nutrition in Chronic Renal Failure (10) address the evaluation of protein-energy nutritional status for children receiving maintenance dialysis only. No guidelines for pediatric patients with CRI before the onset of ESRD are available. The dialysis guidelines emphasize that no single measure provides a complete picture of nutritional status; consequently, many different measures are recommended, with the implication that the treating team will integrate the results into a cogent assessment of nutritional status. The recommended measures include assessment of dietary intake, serum albumin, height or length (and SD score), estimated dry weight, weight/height index, skinfold thickness (sites not specified), midarm circumference (MAC), and head circumference (for children aged 3 y). For children maintained on peritoneal dialysis, the K/DOQI guidelines also suggest measurement of the protein equivalent of nitrogen appearance (9). The protein equivalent of nitrogen appearance is used to estimate protein intake. These measures and suggested frequency are summarized in Table 2.

In the absence of specific guidelines for the nutritional assessment of children with CRI, it is our opinion that the same measures recommended for children with ESRD be undertaken in those with CRI, but less frequently. It is recommended that adults with a GFR < 60 mL · min^–1 · 1.73 m^–2 undergo evaluation of nutritional status at 6 to 12 mo intervals, and that this be increased to 1 to 3 mo intervals when the GFR falls below 30 mL · min^–1 · 1.73 m^–2, or in the face of evidence of malnutrition (11). These GFR cutoffs and frequency of assessment are probably appropriate for most children with CRI as well. However, growing, developing children may benefit from initiation of nutritional evaluation at a higher level of renal function and may require more frequent assessment. Monitoring of nutritional status at intervals similar to those recommended for children with ESRD may be warranted in some children with CRI. Infants in particular are at high risk of malnutrition and growth failure, which improve with nutritional supplementation (39, 42–44). Monthly nutritional evaluations may be beneficial in some infants with any degree of CRI.

Given that annual height, weight, and head circumference measurements are recommended even for healthy children, assessment of these 3 variables at 6-mo intervals should be a minimum standard for children with moderate renal insufficiency (GFR 30- 59 mL · min^–1 · 1.73 m^–2). We believe that dietary assessment, weight/height index, or BMI-for-age SD scores, triceps-skinfold thickness, and MAC would also be useful in this group of children. However, until more data on the risk of malnutrition in the pediatric CRI population are available, these additional measures can be considered optional for those with moderate CRI. We strongly recommend that all the measures be undertaken in children with severe CRI (GFR 15–29 mL · min^–1 · 1.73 m^–2) and in all infants with CRI. Our recommendations are summarized in Table 3.

Table 4

The guidelines suggest 2 methods of obtaining dietary information: prospectively, by means of a 3-d diary, or retrospectively, by interview with recall of intake over the previous 24 h. These methods are the most practical and clinically feasible ways to determine usual daily caloric intake. Intakes of protein, fat, vitamins, and minerals are also estimated from the recorded intake.

However, dietary assessment may be limited by inaccurate or incomplete data. In addition, the usefulness of the data collected depend on whether day-to-day dietary variability is captured, providing an accurate representation of average daily caloric intake. Different methods of assessment may be appropriate for different age groups. When selecting a method, it is important to consider differences in day-to-day variability of intake at different ages as well as the anticipated ability and interest of subjects in cooperating with the task of recording or recalling intake.

Studies of adults have indicated that to accurately capture average daily caloric intake, a minimum of 5–7 d of intake should be recorded. This will correctly classify 80% of persons into the extreme thirds of the distribution for energy and protein intakes (46). Although 3- or 4-d diaries may be adequate for determining the average intake of a group, longer periods are needed for individual subjects (46). Children are known to have a greater variability in day-to-day intake than are adults and therefore may require longer dietary records (47). Seven-day dietary diaries have been shown to give unbiased estimates of energy intake in normal-weight children younger than 10 y of age (48), but underreporting by 20% is seen when this method is applied to older children and adolescents (48, 49). The burden of completing such a long dietary record must be balanced against the benefits of better capturing variability in intake. In older children and adolescents, whose interest in cooperating with a prolonged diet diary may be limited, a diet history, in which subjects and their caregivers are questioned about usual weekly intakes, was shown to be an accurate method of determining energy intake (50). However, data obtained by this method lacked precision at the individual level, calling into question its validity as a measure of a person’s habitual intake.

The validity of 24-h dietary recalls has not been well studied in children. When this method is used in adults, those with low intakes tend to overreport, whereas those with high intakes underreport their true intakes (46). Another important limitation of this method is its inability to capture the day-to-day variability in intake. Multiple 24-h dietary recalls can be performed to circumvent this problem. In a study of 4-to-7 y olds, energy intake determined by using 3, nonconsecutive 24-h dietary recalls showed good agreement with the gold standard, doubly labeled water method (51). However, the limits of agreement were wide, suggesting that this method does not perform well on an individual level.

Although no studies have addressed the strengths and limitations of dietary assessment methods in CKD, there may be issues specific to renal disease. Children and families may deliberately omit or underestimate intakes of food restricted in CKD. Similarly, overreporting of intake may occur in persons who have been counseled to increase their intake.

The available data do not clearly identify one dietary assessment method as superior to the others in all age groups. Dietary diaries have the advantage of capturing some of the day-to-day variability in intake and are identified in the guidelines as the preferred method (10). Regardless of the method used, the quality of the information obtained is improved when children and their caregivers are trained in portion size estimation. Despite the limitations of the recommended methods, careful collection of information on dietary intake by a pediatric registered dietitian is a useful exercise, which allows the treating team to evaluate the adequacy of a patient’s intake before significant adverse changes in body composition occur.

Serum albumin
Hypoalbuminemia is frequently seen in patients with CKD. More than 50% of the 1937 children with ESRD identified through the United States Renal Data System for a study of hypoalbuminemia and mortality risk had serum albumin concentrations <3.5 g/dL (3). Hypoalbuminemia has been consistently shown to be associated with increased mortality in adults with CKD (4–6, 8). This association was also observed in children; each 1-g/dL decrease in serum albumin was associated with a 54% higher risk of death (3).

Because protein-energy malnutrition is known to lead to hypoalbuminemia, serum albumin is generally considered a useful index of nutritional status. However, as pointed out in the K/DOQI guidelines, serum albumin is limited as a marker of malnutrition in the setting of CKD. Serum albumin may be insensitive to acute changes in nutritional status because of its long half-life. In addition, serum albumin is depressed both in the setting of systemic inflammation and in volume-overload states (52, 53). Current evidence supports the existence of a "malnutrition-inflammation complex," in which chronic inflammation leads to protein-energy malnutrition (52, 54–56). Although hypoalbuminemia may indicate malnutrition without coexistent inflammation in some persons with CKD, hypoalbuminemia in the absence of inflammatory markers is not predictive of increased mortality (57). Serum albumin remains an important part of the general evaluation of patients with CKD, but its limitations as a marker of nutritional status must be recognized.

Like albumin, depressed serum prealbumin concentrations have been linked to increased mortality risk (58, 59). Prealbumin is not recommended for the nutritional assessment of pediatric patients with CKD, but it is recommended in adults (10). Although prealbumin has many of the same limitations as albumin, its half-life is much shorter: 2 d, in contrast with 20 d for albumin. Therefore, it is more reflective of the prevailing state. However, prealbumin concentrations tend to increase in the setting of renal dysfunction due to decreased clearance. The validity of prealbumin concentrations as a marker of nutritional status in the setting of CKD has not been established.

Height or length SD score
Significant growth retardation and short stature are well-recognized complications of childhood CKD (30, 31, 34–37). Furthermore, short stature is associated with increased morbidity and mortality. Wong et al (2) reported a 14% increase in death risk for each one SD score decrease in height among children with ESRD. Children with height SD scores < –2.5 at dialysis initiation were found to have 2.07 (95% CI: 1.53, 2.77) times the risk of death and to spend 0.22 more days per month in the hospital compared with those with height SD scores > –2.5 (1).

Height should be measured by using a wall-mounted stadiometer, preferably by the same well-trained person at each assessment. Plotting the child’s height on the normal growth curve to determine the percentile, or calculating the SD score, allows comparison with healthy children. Recording serial height measurements allows assessment of the growth rate, or height velocity. This is the change in height per unit time (ie, cm/y). Height velocity SD scores can also be calculated. It is important to recognize that the interval over which growth velocity can be accurately assessed depends on the age of the child and is relatively long. Reference data for incremental growth are derived from the Fels Longitudinal Study (27). Participants in the Fels Study were measured only every 6 mo. No reference data are available for shorter intervals. Measuring stature more frequently than every 6 mo allows a running look at growth and gives a general impression of its adequacy.

Adequate growth is a good indication of adequate nutrition over the long term. Note however that growth usually continues at a normal rate in malnourished children until significant wasting occurs (60). Wasting is defined as weight-for-height 90% of the median weight for that height (61). Hence, a child may have severe weight loss and alterations in body composition before malnutrition is manifested as abnormal linear growth.

In addition, growth retardation may occur in patients with CKD for reasons unrelated to nutritional status. Short stature and low height velocity for age may result from metabolic acidosis, disturbances in the growth hormone insulin-like growth factor axis, or delayed sexual maturation due to renal insufficiency. Although linear growth is an important indicator of overall well being, it is not sufficient to assess growth alone when evaluating nutritional status.

Estimated dry weight
Children with CKD have been shown in several studies to have low weight-for-height, although the deficits have generally been mild (30, 36). No such deficits were observed in a study of children receiving peritoneal dialysis (31). Clearly, it is important to ensure that any weight measures are obtained in a euvolemic state. Dry weight, or euvolemic weight, is estimated by examining the patient for edema and jugular venous distention and by considering other factors such as blood pressure and response to fluid removal (in the case of patients receiving dialysis). However, a clinician’s ability to determine volume status from the clinical examination is notoriously poor (62). As discussed below, methods such as bioimpedance analysis may improve estimates of dry weight. However, at present the estimated dry weight, in combination with stature, remains the usual central component of the nutritional evaluation.

Weight/height index
This measure of wasting is expressed as an SD score, percentile, or the percentage expected (subject’s weight divided by the 50th percentile of weight for that height). It is easily understood, and reference values are available from birth to young adulthood. As mentioned above, weight for height may be decreased in CKD. As with any measure incorporating weight, this index may by falsely elevated in the face of fluid overload. The weight/height index is particularly well suited for use in CKD, in which short stature and pubertal delay are common.

With the revised growth charts, published in 2000, this index has been replaced in children over 2 y of age by the BMI, now that robust age- and sex-specific reference values are available (26). (Table 1) BMI as well may appear normal, or even high, in the face of fluid overload. A low BMI however, has been shown to be associated with increased morbidity and mortality in both adults (4) (7) and children (2) with ESRD. The study in children found a U-shaped association between BMI and mortality risk. As BMI moved either above or below a BMI SD score of 0.50, each change by 1.0 SD score was associated with a 6% increase in mortality risk. The excess mortality associated with increased BMI was presumably due, at least in part, to volume overload. Because of its apparent prognostic value, BMI is an important part of the nutritional assessment. However, it is not clear how BMI should be interpreted for clinical care in the pediatric CKD population. Normal BMI changes substantially during childhood, reaching a nadir of 15.5 (median) at 4–6 y of age and rising to 20 to 22 y (median) by maturity. Because children with CKD often experience growth retardation and delayed sexual maturation compared with healthy children, age may not be the best point of reference. BMI-for-height-age has been suggested as a more appropriate method of standardization in renal disease (63). This is a reasonable approach.

Skinfold thicknesses
Measuring skinfold thicknesses is the most common method of determining body fatness in clinical practice. Specialized calipers are used to determine the thickness of skinfolds containing subcutaneous fat at a variety of sites on the body. This method is extremely operator-dependent and lacks precision, except in very experienced hands. Interobserver variability of 8–20% and intraobserver variability of up to 7% have been reported (63).

Mild-to-moderate deficits in triceps-skinfold thickness have been reported in children with CKD (30, 31, 37). Several predictive equations that incorporate the measurements at 2–4 sites have been developed to estimate percentage body fat or fat mass (64–66). Because the relation between subcutaneous fat and deep fat, and hence between skinfold-thickness measures and fat mass or percentage body fat, varies depending on age, sex, and maturity, population-specific regression equations have been developed (64–66). Again, it is important to recall that the available regression equations and reference data were developed in healthy persons and assume normal tissue hydration and normal fat distribution. In children with kidney disease, the influence of fluid overload on these measurements must be considered. Although the presence of edema influences skinfold-thickness measures less than it will circumferences (66), the effect may be important. No data indicate the reproducibility of skinfold-thickness measures in the setting of edema. In our experience, the measures are labile because the calipers displace the subcutaneous edema. There are also no data on the magnitude of the overestimation error in percentage body fat that may occur in a fluid-overloaded child.

Another potential limitation of skinfold-thickness measures in CKD relates to the distribution of fat. Regional distribution of fat as well as the ratio of subcutaneous to visceral fat may be distorted in some patients with CKD. A study of abdominal fat distribution in 92 adult patients receiving hemodialysis with the use of computed tomography (CT) showed significantly greater visceral fat area and significantly lower subcutaneous fat area in hemodialysis patients than in healthy adults (67). Although there are conflicting data on the effect of CKD on axial and appendicular growth (68, 69), Zivicnjak et al described abnormal body proportions in 17 children with CKD. They reported greater deficits in limb lengths than trunk length, suggesting that a greater proportion of total fat may be found on the trunk in these children (69).

The validity of the available skinfold-thickness regression equations has not been assessed in the CKD population, and there are no data associating either skinfold-thickness–derived fat mass, percentage body fat, or specific skinfold-thickness measures with outcome in the CKD population.

Midarm circumference, midarm muscle circumference, and midarm muscle circumference area
MAC is measured in the upper arm midway between the acromion and the olecranon process with a flexible measuring tape (70). Midarm muscle circumference (MAMC) and midarm muscle circumference area (MAMA) are estimated by using equations that incorporate MAC and the triceps-skinfold thickness measure (Appendix A, Equations A2, A3, and A4). MAMA can also be determined by using CT or magnetic resonance imaging. In comparison with MAMA determined by imaging techniques such as a CT scan, MAMA calculated by conventional anthropometric methods may overestimate muscle area by 7–8%; this error increases to >50% in obese persons (71).

These arm measures are meant to function as indexes of total muscle mass. Muscle mass is a nutritionally important compartment because it is the most variable component of lean soft tissue mass. Arm measures have the advantage of being inexpensive and easy to perform. However, it is difficult to quantify the correlation between upper arm measures and total muscle mass because total muscle mass is very difficult to measure. Methods of estimating total muscle mass include urinary creatinine excretion, nuclear techniques such as total body potassium and total body nitrogen, and imaging studies such as CT, magnetic resonance imaging, and dual energy X-ray absorptiometry (DXA). All of these methods have serious limitations (71, 72). Cadaver studies of 6 male adults found a good correlation (R² = 0.80) between MAMA and dissected whole-body muscle mass (73). However, few other studies have been conducted to validate arm indexes as predictors of total muscle mass. DXA provides excellent estimates of appendicular muscle mass, but a study of healthy adults showed only a fair correlation between appendicular muscle mass from DXA and upper arm anthropometry (R² = 0.67) (74).

As mentioned, the regional distribution of lean tissue may be abnormal in CKD, leading to a breakdown in the relation between MAMC or MAMA and total muscle mass. In addition, fluid overload may artificially increase MAMC and MAMA, leading to an overestimation of total muscle mass (71). At least one study showed a failure of arm measures to reliably detect decreased lean mass as measured by in vivo neutron activation analysis in hemodialysis patients (75). No significant deficit in MAMC (adjusted for height) has been found in studies of children with CKD (31).

Finally, although these arm measures have been associated with other indexes of malnutrition, there are limited data linking arm measures with outcome in the kidney disease population. Qureshi et al (6) followed 128 adult hemodialysis patients over a 3 y period in an effort to identify independent predictors of mortality. A variety of nutritional variables, including MAMC, were assessed at baseline. MAMC, expressed as a percentage of the normal mean value for each sex, was found to be significantly lower in the nonsurvivors than in the survivors in the unadjusted analysis. The Cox proportional hazard analysis, however, did not identify MAMC as an independent predictor of mortality in this group. In addition to the limitations noted above, it is not known whether arm measures have sufficient accuracy or sensitivity to capture clinically significant small changes in muscle mass in a person (71).

Head circumference
This is an important measure of brain growth in healthy and chronically ill children alike and should be measured regularly in all children <3 y old. Poor head growth is well documented in children with CKD (76, 77), with infants at highest risk. However, no studies have related head circumference to nutritional status. Head circumference may be overestimated in patients with severe edema.

Protein equivalent of nitrogen appearance
The protein equivalent of nitrogen appearance (PNA), formerly known as the protein catabolic rate (PCR), is used to estimate protein intake in patients with CKD in steady state. The term nitrogen appearance refers to the fact that the total amount of nitrogen "appearing" in the urine and dialysis fluid in a 24-h period is estimated. The principles behind the PNA are as follows: 1) nitrogen balance is neutral in steady state, 2) excreted nitrogen is derived from dietary protein, and 3) 1 g N is derived from 6.25 g dietary protein. Although growing children are never in a perfect steady state, daily positive nitrogen balance associated with a normal growth rate is small enough to be considered negligible (78).

Ideally, PNA would be calculated as the total nitrogen appearance multiplied by 6.25. However this is impractical in a clinical setting because it would require careful documentation of all nitrogen output (stool, sweat, etc). Urea nitrogen appearance is highly correlated with total nitrogen appearance, and regression equations estimate PNA from urea nitrogen appearance in urine and dialysate (9). The modified Borah equation, which controls for body size, is recommended in the K/DOQI guidelines (see Appendix A, Equation A5). A similar equation was developed from studies (79) in a group of 18 children receiving peritoneal dialysis (see Appendix A, Equation A6). Neither equation has been validated with formal nitrogen balance studies in children, so it is not clear which equation is preferable. The PNA provides an estimate of the dietary protein intake in g/d. Recommended protein intakes for children with CKD are published elsewhere (10).

Calculation of the PNA is currently recommended only for children receiving peritoneal dialysis. Urea kinetic modeling can be used to calculate the PNA in patients receiving hemodialysis (9, 80, 81). In addition, PNA can be calculated by measuring urea in a 24-h urine collection in children with CRI. Limited data are available to validate the use of PNA in children either receiving hemodialysis (81, 82) or pre-ESRD. Harmon et al (82) adapted an equation developed in adults to calculate PCR from the urea generation rate (determined by urea kinetic modeling) for use in pediatric hemodialysis patients. This equation was then used to calculate PCR in 14 children, and the results were compared with those obtained in formal nitrogen balance studies. There was no significant difference between the 2 methods. Although there are no data on the use of PNA in children with CRI, the theoretical basis for its use is sound. In addition, measurement of urine nitrogen has been successfully used to estimate protein intake outside the setting of CKD (83).

	OTHER NUTRITIONAL ASSESSMENT TECHNIQUES

TOP ABSTRACT INTRODUCTION FUNDAMENTALS OF BODY-COMPOSITION... CURRENT RECOMMENDATIONS FOR... OTHER NUTRITIONAL ASSESSMENT... SUMMARY Appendix A REFERENCES

 
Many other methods are available to assess nutritional status. These methods can be divided into 2 groups: those that are clinically feasible and those that are better suited for research applications. These methods and their strengths and limitations in CKD are summarized in Table 5. Published reports of each technique in children with CKD are discussed where available.

DXA has been used extensively for body-composition assessment in adults and to a lesser degree in children with CKD (86–90). Deficits in lean body mass for age and sex have been reported in children with CKD (90); however, data have not been evaluated after adjustment for height. Currently available data do not show an association between decreased lean body mass (as measured by DXA) and adverse outcomes such as morbidity or mortality in adults or children.

Bioelectrical impedance analysis
BIA is used to estimate the volumes of body fluid compartments. Electrical current is conducted by body water, and impeded by other body components. The opposition to flow of electrical current is called impedance. Impedance is proportional to the length of the conductor, and inversely proportional to the cross-sectional area. Since volume is simply length multiplied by area, impedance is directly related to the volume of the body fluid (91).

Fluid compartment volume measures are a useful part of body-composition assessment for several reasons. Total body water (TBW) measures can be used to estimate lean body mass by applying age-appropriate hydration factors (92). In kidney disease, however, these hydration factors may not be valid and should not be used unless fluid status is clearly normal. Estimates of extracellular fluid (ECF) volume together with TBW volume allow calculation of intracellular fluid (ICF) volume. ICF volume correlates strongly with body cell mass and therefore may provide an excellent index of nutritional status (93).

The bioimpedance technique most frequently described in the literature is the whole-body method. An electrical current is passed through an ‘injecting’ electrode at the ankle and detected by a ‘sensing’ electrode at the wrist. Current is either applied at a single frequency or at multiple frequencies (bioimpedance spectroscopy). When single-frequency BIA is used, the single resistance measure is entered into an empirically derived predictive equation to estimate either the TBW or ECF volume. Because most of the predictive equations in use were developed in healthy persons, in whom the relation between ECF and TBW is almost constant, their validity in disease states is questionable.

Bioimpedance spectroscopy provides more information and allows estimation of ECF and ICF separately. A detailed explanation of how this is accomplished can be found in an excellent review by De Lorenzo et al (93) ECF volume is more accurately estimated from impedance measures than is ICF volume (94).

Despite extensive work with both single-frequency and multifrequency bioimpedance techniques, investigators have been unsuccessful at developing broadly applicable predictive equations that function well on the individual level (95). Although some of the equations that have been developed both in healthy persons and in CKD perform quite well on a population level, their usefulness is limited on an individual level (96–99). A study of children receiving maintenance dialysis by Wuhl et al (96) illustrates this problem. This group developed an equation to predict TBW from resistance to flow of a 50-kHz current applied wrist to ankle and compared the results with those obtained by isotope dilution. Although the group mean TBW measured by bioimpedance was within 170 mL of that measured by isotope dilution (used as the reference method gold standard), limits of agreement were wide (± 17% of the true TBW value). This means that an individual subject, with a true TBW volume of 30 L could be estimated to have a TBW volume as high as 35.1 L or as low at 24.9 L by BIA.

Bioimpedance may be more successful at predicting ECF volume than TBW. Smye et al (100) sought to validate estimates of ECF volume by multifrequency bioimpedance spectroscopy against isotope dilution in a small study of children with mild-to-moderate CRI and showed agreement within 6%. Bioimpedance spectroscopy is a promising technique, particularly for estimating ECF, but it has not yet been adequately validated in children or adults with CKD.

In addition to its poor performance on the individual level, the whole-body method has limitations when abnormalities in fluid distribution exist. This technique is insensitive to large changes in fluid volume in the trunk and very sensitive to small changes in the limbs (101). A segmental bioimpedance technique has been developed in an effort to circumvent this problem (101).

The segmental method considers the body as 5 segments (2 arms, 2 legs, and trunk) and requires that body segments (arm, leg, and trunk) be measured separately. The impedance from each segment is then weighted accordingly in the volume calculations, to account, in part, for the different contributions of each segment to total resistance (101). This is an effort to avoid overrepresentation of the limbs and underrepresentation of the trunk in the final total volume calculation. This technique may be particularly useful in fluid-overloaded persons. No studies using this method in children have been published.

Phase angle is also measured by using BIA and has been reported to be a useful index of nutritional status; a low phase angle is said to indicate malnutrition (102–104). Although this may be a valid method in euvolemic subjects, phase angle is difficult to interpret when volume status is abnormal. Changes in phase angle may be due either to changes in nutritional variables such as body cell mass or cell membrane integrity, or to changes in fluid volume. Phase angle has been shown to increase during fluid removal in patients receiving hemodialysis (105). Because patients with renal failure frequently experience changes in both nutritional and volume status, phase angle alone cannot be reliably used as an index of nutritional status in this group. When considered in conjunction with weight, it may be more useful. Reduction in phase angle, without a change in weight, suggests a loss of lean tissue accompanied by fluid retention. In addition, phase angle appears to be an index of overall well-being because it has been shown to be a good predictor of mortality in adult hemodialysis patients (106). Phase angle has not been evaluated as an index of nutritional status in children with CKD.

Research tools
Densitometry
Body composition can also be estimated from body density. Density is determined from a simple weight measurement and a measure of body volume. Volume can be measured either by underwater weighing or by air-displacement plethysmography. Underwater weighing uses the Archimedes principle that a body immersed in fluid experiences a loss of weight equal to the weight of the fluid it displaces. The density of water can then be used to determine the volume of the immersed body. Underwater weighing has long been the gold standard in densitometry (107).

More recently, however, air-displacement plethysmography was shown to give comparable results (108, 109). The measuring device, called the Bod Pod (Life Measurement Systems, Concord CA), takes advantage of physical relations between pressure and volume under different temperature conditions to allow measurement of the volume occupied by the subject’s body. A detailed explanation of the mechanics of the measurement was published elsewhere (108). Children as young as 5 y of age are able to complete this measurement.

Once body volume is measured, body mass is then divided by the body volume to give whole-body density. The estimated body density is then used in a 2-, 3- or 4-compartment model to determine body composition (107) (Figure 1). All models require 2 basic assumptions: 1) the densities of the compartments are additive in parallel (see Appendix A, Equations A8, A9, and A10) and 2) the density of each compartment is constant between individual persons. The first assumption is mathematically sound. The second assumption may be problematic, particularly in 2- and 3-compartment models. Although there may be some interindividual variability in fat density, it is likely very small and would lead to very small errors. The variability in fat-free mass density on the other hand may be substantial, leading to more significant errors. This is particularly true in children, in whom the hydration of fat-free mass decreases with age, or in fluid-overload states. Expanding the model to 3 or 4 compartments can circumvent this problem. A 3-compartment model that separates fat-free mass into water and solids relieves the problem of variable hydration. The assumption that the densities of water and solids (mineral and protein) are constant is still required. A constant density is assigned to lean solids by assuming constant densities of mineral and protein and a constant ratio of mineral to protein. Although the densities of mineral and protein are likely quite consistent between individual persons, the ratio of mineral to protein may vary, particularly in those with renal osteodystrophy. A 4-compartment model, which further divides solids into protein and mineral components, assumes constant densities of fat, water, protein, and mineral. This model is the one most appropriate for research in patients with CKD.

To use a 3-compartment model, TBW must be measured by isotope dilution. In addition to TBW measurement, a 4-compartment model requires estimation of total-body mineral mass, available from DXA. Because DXA will only provide an estimate of bone mineral mass, an assumption about the ratio of bone mineral to extraosseous mineral mass is required. (see Appendix A, Equation A7) Errors resulting from this assumption would be trivial, given the small contribution of nonosseous mineral mass to total body mass. No studies in children with CKD, and only small studies in adults with CKD, have used the 4-compartment model to evaluate body composition (110).

Total-body potassium counting
This technique takes advantage of the fact that ⁴⁰K occurs naturally in the body, and the decay can be detected as rays. Total body potassium is calculated by multiplying the number of ⁴⁰K counts by a calibration factor (21). The calibration factor is determined by measuring counts of a body with a known potassium content. Total body potassium is directly proportional to body cell mass. Body cell mass is the active tissue found in muscle, viscera, blood, and brain and is the tissue most likely to be affected by malnutrition over short periods of time (21). By making assumptions about the potassium content of lean tissue, the body cell mass can be estimated from total body potassium. In renal insufficiency these assumptions may not hold. Because the kidney is responsible for potassium homeostasis, persons with CKD may have abnormal potassium balance and elevated tissue potassium content. This will lead to an overestimation of body cell mass in these subjects (111).

Total body potassium was evaluated in 2 studies of children with CKD (112, 113). One of these studies showed decreased total body potassium, suggesting a lower body cell mass in children with CKD than in healthy children (113). The other did not include a reference group.

In vivo neutron activation analysis
This research tool is available at only a small number of centers worldwide. It provides a noninvasive analysis of the total body content of major elements (calcium, nitrogen, sodium, oxygen, hydrogen, and carbon). An in-depth review of the technical aspects of this method is beyond the scope of this article. Basically, neutrons directed at the supine subject’s body are captured by atoms, transforming the atoms to another nuclear state. The excited atoms then decay with a known half-life and energy. Decay is measured, allowing calculation of the whole-body content of specific elements (21).

This technique is most frequently used to measure total body nitrogen. Because there is a fixed relation between nitrogen and protein [protein (g) = 6.25 x nitrogen (g)], total body protein can be calculated from estimated total body nitrogen. This is considered the gold standard for estimating total body protein. Total body nitrogen can also be expressed as a nitrogen index, where the nitrogen index equals measured total body nitrogen divided by predicted total body nitrogen. Predicted total body nitrogen is determined using a prediction equation developed in healthy persons on the basis of sex, height, and age (75).

The accuracy of total body nitrogen measures may be reduced in CKD, in which nonprotein nitrogen, in the form of urea, is present in increased amounts. However, even in severe ESRD, in which urea is markedly elevated, the total body protein determined by in vivo neutron activation analysis would be overestimated by only 2–3% (21).

Studies using in vivo neutron activation analysis for total body nitrogen measurement have shown deficits in total body nitrogen in adult patients with CKD (75, 114, 115). Furthermore, Arora et al (114) found that a nitrogen index <0.8 was associated with a hazard ratio of 2.62 (95% CI: 1.21, 7.95) for mortality over 76 mo of follow-up in a study of 91 adult hemodialysis patients. Baur et al (116) reported deficits in total body nitrogen for age in a group of 17 children with CKD. However, these deficits could be attributed to short stature; when total body nitrogen was evaluated relative to height rather than age, no deficits were observed.

Isotope dilution
The current gold standard for measuring body fluid compartment volumes is isotope dilution. The principle is simple. The baseline level of isotope in the body is measured; then, a known quantity of isotope is administered and allowed to equilibrate in the body water. A sample of body fluid is then taken, and the concentration of the isotope is determined (117). Isotopic enrichment of the body fluid sample is determined either by mass spectrometry or infrared spectroscopy in the case of stable isotopes or by ß or counting in the case of radioactive isotopes (117, 118). The volume of fluid into which the isotope was diluted, called the dilution space, is then calculated.

TBW volume can be estimated by using deuterium or oxygen-18, both of which are stable isotopes of water that distribute equally to the intracellular and extracellular spaces. Tritium, a radioactive isotope of hydrogen, may also be used. ECF volume can be estimated by using bromide or ³⁵S, which distribute almost exclusively to the extracellular space. The fluid sampled for TBW measurement is a matter of choice; plasma, urine, saliva, and respiratory water have all been used and validated (119). Only blood plasma may be sampled for extracellular water measurement.

Isotope dilution methods have been used extensively in many populations, including children with kidney disease. The technique works equally well in any population; however, the time to equilibration of isotope may be longer in a fluid-overloaded person, particularly if the excess fluid is in poorly vascularized compartments (eg, ascitic fluid). Studies have indicated that the equilibration of deuterium in plasma occurs within 2 h after an oral dose of tracer in normal, euvolemic children (96, 117). Even in children receiving hemodialysis, who may be volume expanded, equilibrium in plasma is complete within 2 h of an oral dose (96). Tracer concentrations do not plateau in peritoneal fluid, however, until 4 h after an oral load (96). Bromide equilibration generally takes longer: 3–4 h in healthy children and 6 h when fluid overload is present (117). The time to equilibrium also depends on the fluid being sampled.

	SUMMARY

TOP ABSTRACT INTRODUCTION FUNDAMENTALS OF BODY-COMPOSITION... CURRENT RECOMMENDATIONS FOR... OTHER NUTRITIONAL ASSESSMENT... SUMMARY Appendix A REFERENCES

 
We have reviewed the major methods available for body-composition evaluation in children. Emphasis has been placed on the ways in which these techniques may be compromised in children with CKD. Although there are many potential sources of error in children with CKD, fluid overload is the factor most likely to influence interpretation of body-composition measures in this population. One can be quite confident that measures indicative of malnutrition in a fluid-overloaded person correctly classify that person as malnourished. The degree of malnutrition, however, may be underestimated. Classification problems arise when progressive fluid retention, as may occur in patients receiving maintenance dialysis, masks a gradual decrease in nutritional indexes. Alternatively, weight loss may be interpreted as worsening nutritional status, when in fact it represents only loss of water. These issues affect mainly maintenance dialysis patients, although children with severe CRI or nephrotic syndrome may also experience abnormal fluid balance.

Throughout this review we have stressed the importance of normalizing all measures appropriately. This point cannot be overemphasized. Because growth retardation and pubertal delay are pervasive in childhood CKD, short stature for age is common. In general, measures should be expressed relative to height or height age rather than to chronological age.

The K/DOQI guidelines make specific recommendations regarding the assessment of nutritional status in children receiving maintenance dialysis. These guidelines, however, inadequately account for the effect that abnormal body composition may have on the validity of the recommended measures in this population. One clinical strategy is to conduct measures only when the child is considered to be at dry weight. Unfortunately, clinical evaluation of volume status is frequently inaccurate; but, until there is a better method to determine dry weight, we must rely on skilled clinical judgment.

No consensus guidelines for the nutritional evaluation of children with CRI are currently available. We have suggested that the nutritional assessment of this group should be modeled on the recommendations for children with ESRD and that the required frequency of assessment depends on the level of renal function. The nutritional status of children with CRI cannot be ignored. Early identification of nutrition and growth abnormalities, followed by swift intervention with nutritional supplements and growth hormone, may allow correction of deficits. One of the main goals in caring for children with CRI is to prevent abnormalities in body composition before the onset of ESRD. Reversal of deficits may be more easily achieved in children with CRI than in those with ESRD.

No data can be adequately interpreted without an understanding of the methods by which they were obtained. For both clinical care and research, it is important that the limitations of nutrition and body-composition evaluation methods be recognized. For measures that have not been validated in the pediatric CKD population, the magnitude and direction of potential biases should be understood. Longitudinal studies to determine the value of the various nutritional indexes in predicting important clinical outcomes such as school attendance, morbidity, and mortality are equally important. Accurate growth and nutritional status assessment is central to the management of children with kidney disease. Only when we recognize the limitations of our assessment methods will we begin to improve our understanding and, hence, the treatment of the nutritional deficits faced by these children.

	Appendix A

TOP ABSTRACT INTRODUCTION FUNDAMENTALS OF BODY-COMPOSITION... CURRENT RECOMMENDATIONS FOR... OTHER NUTRITIONAL ASSESSMENT... SUMMARY Appendix A REFERENCES

 

1. Calculation of SD scores:
   

   (A1)

   
   

2. Anthropometric measures (1):
   

   (A2)

   
   

   (A3)

   
   

   (A4)

   where MAMC is midarm muscle circumference, MAC is midarm circumference, MAMA is midarm muscle area, and TSF is triceps-skinfold thickness. All of these variables are measured in cm.
   

3. Modified Borah equation (2):
   

   (A5)

   where PNA is the protein equivalent of nitrogen appearance, UNA is the urea nitrogen appearance, and V is the volume of distribution of urea. PNA and protein losses are measured in g/d:
   

4. Alternate PNA equation (3):
   

   (A6)

   
   

5. Total-body (4): mineral content and the 4-compartment model.
   Total-body mineral content is calculated from bone mineral content (BMC), as determined by dual-energy X-ray absorptiometry. Total-body mineral content = BMC x 1.2741. The resulting equation for the 4-compartment model is as follows:
   

   (A7)

   
   

6. Equations to calculate the fractional masses of body compartments if body density and mass are known (see Figure 1):
   

   (A8)

   
   

   (A9)

   
   

   (A10)

   where D is the density of fat (f), lean tissue (l), protein (p), mineral (m), and water (w).
   

	ACKNOWLEDGMENTS

 
BJF conducted the background research and wrote the manuscript. MBL provided advice and consultation and was instrumental in the organization of the manuscript, tables, and figures. The authors had no conflicts of interest to report.

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