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Anorexia nervosa and nutritional assessment: contribution of body composition measurements

Published online by Cambridge University Press:  08 March 2011

Lama Mattar
Affiliation:
INSERM U669, Maison de Solenn, 97 Boulevard De Port Royal, 75014Paris, France Université Paris-Sud and Université Paris Descartes, UMR-S0669, 75679Paris, France
Nathalie Godart
Affiliation:
Service de psychiatrie, Institut Mutualiste Montsouris, 42 Boulevard Jourdan, 75014Paris, France
Jean Claude Melchior
Affiliation:
Unité de Nutrition clinique-Maladies infectieuses, Département de Médecine aiguë, Hôpital Raymond Poincaré, 92380Garches, France Université Versailles St Quentin en Yvelines, 94415Villejuif, France
Claude Pichard*
Affiliation:
Unité de Nutrition, Hôpitaux Universitaires de Genève, Rue Gabrielle-Perret-Gentil, 4, 1211Geneva 14, Switzerland
*
*Corresponding author: Dr Claude Pichard, fax +41 22 3729363, email claude.pichard@unige.ch
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Abstract

The psychiatric condition of patients suffering from anorexia nervosa (AN) is affected by their nutritional status. An optimal assessment of the nutritional status of patients is fundamental in understanding the relationship between malnutrition and the psychological symptoms. The present review evaluates some of the available methods for measuring body composition in patients with AN. We searched literature in Medline using several key terms relevant to the present review in order to identify papers. Only articles in English or French were reviewed. A brief description is provided for each body composition technique, with its applicability in AN as well as its limitation. All methods of measuring body composition are not yet validated and/or feasible in patients with AN. The present review article proposes a practical approach for selecting the most appropriate methods depending on the setting, (i.e. clinical v. research) and the goal of the assessment (initial v. follow-up) in order to have a more personalised treatment for patients suffering from AN.

Type
Review Article
Copyright
Copyright © The Authors 2011

Anorexia nervosa (AN) is one of the most common chronic diseases in adolescents(Reference Patton, Coffey and Sawyer1) and can also persist into adulthood. AN is associated with severe somatic symptoms due to restrictive eating and abnormal behaviour such as purging, potomania, over-exercising, laxative abuse, etc(Reference Steinhausen2). Malnutrition is a serious somatic aspect of AN; its amelioration is a fundamental part of the treatment: clinically, malnutrition affects the psychiatric condition of the patient(Reference Pollice, Kaye and Greeno3, Reference Meehan, Loeb and Roberto4). Similarly, in research, questions have been raised on the relationship between malnutrition and the psychological symptoms in AN (anxiety, depression and obsessionality). However, in previous studies, the methodology was questionable, as only body weight had been used for the nutritional assessment(Reference Pollice, Kaye and Greeno3Reference Wamboldt, Kaslow and Swift6). Complementary to body weight measurements, assessing the body's muscle and fat stores is fundamental for the diagnosis and treatment of malnutrition in AN as well as for assessing the patient's response to nutritional and other therapies. Generally, the two-compartment (2-C) model is used in studies that assess body composition in AN. The 2-C model separates the composition of the body into fat mass (FM) and fat-free mass (FFM) which requires the assumptions that body hydration level and bone mineral content are both stable. As those assumptions cannot constantly be done in AN patients, the 2-C model can thus lead to potentially large errors in estimates of components of body composition(Reference Peterson, Czerwinski and Siervogel7, Reference Heymsfield, Wang and Baumgartner8).

Recently, the four-compartment (4-C) model for assessing body composition has allowed researchers to measure variations in hydration levels and bone mineral contents(Reference Withers, LaForgia and Pillans9). By adding measurements only from direct and scientifically accepted methods of total body water (for example, via 2H dilution), bone mineral density (for example, via dual-energy X-ray absorptiometry (DXA)), and body density (for example, via underwater weighing (UWW)), it is possible to measure individual variations in minerals and water(Reference Wells, Fuller and Dewit10). In theory, this should lead to a more accurate measurement of percentage body fat in AN. However, to our knowledge, and because of practical constraints, no study has been done in AN using the 4-C model although it has been done in populations such as in elderly patients(Reference Goran, Toth and Poehlman11).

The present review will describe the impact of AN on body composition and will appraise the accuracy and applicability of the different methods for measuring body composition such as anthropometric measurements (for example, body weight, skinfolds measurements), bioelectrical impedance analysis (BIA), DXA and some other methods for research use only. In the final section, recommendations are made on which method to use depending on the setting, (i.e. clinical v. research) and the goal of the assessment (initial v. follow-up).

Body composition alterations in anorexia nervosa

AN has a deep impact on body composition(Reference Kerruish, O'Connor and Humphries12). Adaptive changes to low body weight have an impact on bone metabolism and decrease bone mass density(Reference Misra, Aggarwal and Miller13). Mazess et al. (Reference Mazess, Barden and Hanson14) found that absolute bone mineral content was 25 % lower in AN patients when measured using dual-photon absorptiometry. The decreased bone mineral density in AN is related to the loss of muscle mass and reduced muscle strength rather than the bone mineral density itself(Reference Schneider, Biko and Schlamp15, Reference Miller, Wexler and Zha16). The FM, FFM and total body water are not all affected to the same extent due to the variable impact of factors such as physical activity, vomiting, laxative abuse and diet. For instance, patients with AN who achieve an extreme weight loss by semi-starvation can have a different body composition profile from patients who achieved the weight loss primarily through excessive exercise(Reference Helba and Binkovitz17). Based on The American Council on Exercise, normal fat percentages for adult women are between 21 and 31 % and for men between 14 and 25 % of total body weight, depending on age and exercise. In patients with AN, alterations are represented mainly by an extensive loss of FM, suggesting a preferential loss of body fat(Reference Mazess, Barden and Hanson14, Reference Misra, Katzman and Cord18). Nevertheless, there is also a loss in FFM but the extent of the loss depends on the level of exercise maintained by the patient(Reference Shephard19). Concerning weight gain, Iketani et al. (Reference Iketani, Kiriike and Nagata20) assessed by dual-photon absorptiometry twenty-one AN patients and showed that after weight gain and resumption of menses, most of the weight gain consisted of FM (80·6 % of total weight gained) compared with lean body mass (19·3 % of total weight gained). Also, Probst et al. (Reference Probst, Goris and Vandereycken21) who assessed AN patients by UWW and skinfolds thickness (SFT) found that after 23 weeks of treatment, patients gained more in FM (55·5 % of total weight gained) than in FFM (44·5 % of total weight gained). Besides, Russell et al. (Reference Russell, Prendergast and Darby22) found that the regained lean body mass assessed by SFT and anthropometric measurements had a complete restored function. On the contrary, an older study, in which body composition was assessed by SFT and by neutron activation analysis, found that FM accounts less than lean body mass to weight gain(Reference Russell, Mira and Allen23).

As a result, it is crucial to obtain the parameters of body composition in relative percentages of the total body mass in order to monitor accurately the response of the fat and lean components to therapy(Reference Pichard and Kyle24, Reference Melchior, Rigaud and Rozen25).

Body composition-measuring techniques in anorexia nervosa

Anthropometric techniques, BIA and DXA are clinically available methods for measuring body composition and will be discussed below. Many of those methods have limitations in AN. Practitioners can use some of these techniques whereas others are limited to research settings.

Basic anthropometric measurements: body height, weight and BMI

Brief description of body weight, height and BMI

When measuring body height, the patient should be standing with heels together, arms to the side, legs straight, shoulders relaxed and head in the horizontal plane while the patient is ‘looking straight ahead’. Measurement should be rounded to the nearest 0·1 cm(Reference Gordon, Chumlea, Roche, Lohman, Roche and Martorell26). Weight is measured in light clothing and the subject should be standing still in the middle of the scale's platform and not touching surrounding objects(Reference Lee and Neiman27). Measurement reading should be rounded to the nearest of 100 g. Because of diurnal variations (difference reaching up to 2 kg in adults), a good practice would be to record the time when weight was measured(Reference Gordon, Chumlea, Roche, Lohman, Roche and Martorell26). Alternatively, it is easy to determine the body weight in the morning after waking up and having voided the bladder. From the measured height and weight, BMI can be calculated. In children and adolescents, BMI should be used with caution as it is relative to the country's reference growth chart (i.e. Centers for Disease Control growth charts in the USA(28)) and to the age; a BMI of 17·5 kg/m2 would be on the 3rd percentile for a 19-year-old but on the 50th percentile for an 11-year-old(Reference Golden, Jacobson and Sterling29).

Applicability and limitation of body weight and BMI

In cases of severe malnutrition, body weight alone is not a sensitive tool to determine nutritional status(Reference Moreno, Djeddi and Jaffrin30, Reference Trocki, Theodoros and Shepherd31). The loss of body cell mass can be compensated by extracellular fluid accumulation and thus cannot be accurately sensed by body weight measurement(Reference Moreno, Djeddi and Jaffrin30, Reference Kyle, Bosaeus and De Lorenzo32). Trocki & Shepherd(Reference Trocki and Shepherd33) showed that in adolescents with AN, changes in BMI do not correlate well with changes in body composition. Although BMI alone does not differentiate between fat and lean masses in children and teenagers(Reference Cole, Flegal and Nicholls34), it is correlated with components of body composition. For example, BMI in children correlates more strongly with FM at the upper end of the adiposity range where FM makes up a larger proportion of weight, than at the lower end. Thus in thin children, BMI is a better predictor of lean mass than FM(Reference Freedman, Wang and Maynard35). Cole's index for thinness does not quantify malnutrition but rather gives cut-off points under which an individual is classified as thin or undernourished. Nevertheless, body weight for age and height and BMI percentiles have been shown to correlate with the resumption of menses in girls with AN and can therefore be used in setting a target weight. Golden et al. (Reference Golden, Jacobson and Schebendach36) have found that 86 % of patients who achieved a weight goal of 90 % of the average weight for age and height (using the National Center for Health Statistics (NCHS) tables) resumed menses within 6 months. More recently, Golden et al. (Reference Golden, Jacobson and Sterling29) have set the BMI percentile cut-off points at which adolescents with AN resumed their menses. Of the patients, 50 % resumed their menses when their BMI reached ≧ the 14th percentiles.

Body weight alone is not a complete assessment tool; however, it is still essential to use it in the initial nutritional assessment and follow-up in clinical settings. Other methods have been developed to measure body composition. Commonly available methods to assess body composition (skinfolds, BIA, DXA) have not yet been validated against a reference 4-C model in AN patients. This would be important because in patients with AN, body composition extremely alters and they undergo drastic shifts in their electrolytes and hydration status.

Skinfolds thickness, mid-upper arm circumference and waist-to-hip ratio

Brief description of skinfolds thickness

SFT measurement is an inexpensive and basic tool for determining body composition(Reference Pollock and Jackson37). It consists of measuring the thickness of a double fold of skin and compressed subcutaneous adipose tissue with a caliper at specific points in the body. There are three points that are the most commonly used (triceps, subscapular, supra-iliac); however, there are other possible reference points (i.e. thigh)(Reference Lee and Neiman27). The measures obtained are then used in prediction equations(Reference Lee and Neiman27). Because 80 % of the body's adipose tissue is localised under the skin, SFT is a surrogate of body fat percentage(Reference Durnin and Womersley38). From clinical experience, SFT can still be assessed quite well in very lean subjects.

Applicability and limitation of skinfolds thickness in anorexia nervosa

SFT measurements have been frequently used in AN studies(Reference Russell, Allen and Mira39). Measurements are less affected by the hydration status of the patient compared with other methods, which makes this technique advantageous in AN patients. Disadvantages of SFT are its low sensitivity to short-term nutritional changes(Reference Caregaro, Favaro and Santonastaso40), to measuring visceral abdominal fat(Reference Helba and Binkovitz17) and to detecting changes in regional fat distribution(Reference Misra, Soyka and Miller41). Another general drawback of SFT is the large variability between different observers. As a result, SFT measurement is mainly relevant in healthy populations, especially in an epidemiological research setting(Reference Melchior, Rigaud and Rozen25).

Brief description of mid-upper arm circumference

Another reproducible and easy-to-do method is mid-upper arm circumference (MUAC). It consists of measuring on the non-dominant arm, midway between the tip of the acromium process and the olecranon using a non-stretch paper measuring tape, the circumference of the arm. It is an indicator of muscle mass(Reference Collins42).

Applicability and limitation of mid-upper arm circumference in anorexia nervosa

Martin et al. (Reference Martin, Pascoe and Forbes43) have used this method in AN, considering that weight and BMI can misinform on nutritional status, as AN patients can attempt to mislead the physician often by water-loading or discreetly placing weights on their body in order to increase their recorded weight, putting them at risk of complications of malnutrition. They found that MUAC was highly correlated with BMI (r 0·79; P < 0·001) and individuals with MUAC greater than 20 cm rarely required hospitalisation.

Brief description of waist-to-hip ratio

Waist-to-hip ratio (WHR) is used as an indicator of central fat distribution. It is the quotient of the waist circumference divided by the hip circumference. One of the accepted reference points to measure the waist circumference is at the level immediately below the lowest ribs and hip circumference is measured below the iliac crest; however, the importance is to always use the same reference point and to standardise the measurements(Reference Steinkamp, Cohen and Siri44).

Applicability and limitation of waist-to-hip ratio in anorexia nervosa

The WHR in AN allows follow-up on regional fat distribution, especially during weight gain(Reference Forbes, Kreipe and Lipinski45Reference Orphanidou, McCargar and Birmingham47). Forbes et al. (Reference Forbes, Kreipe and Lipinski45) were the first to examine body fat distribution in a cross-section of underweight women with AN. Using the WHR as a measure of body fat distribution, they reported no difference in the WHR between women with AN and healthy control subjects. However, Mayer et al. (Reference Mayer, Walsh and Pierson46) found by measuring the WHR that, immediately after weight restoration to a normal weight, women with AN have an adipose tissue distribution that differs significantly from healthy control subjects.

Bioelectrical impedance analysis

Brief description of body impedance analysis

The concept of BIA is based on applying to the human body a low-intensity electrical current through electrodes placed on the ankles and wrists. The current passes predominantly through water and electrolytes while it faces resistance through cell membranes and adipose tissue. Resistance and reactance are the main parameters measured. They are used to calculate, using mathematical equations, the FFM. However, it is important to note that those equations are based on the assumption that hydration status is constant: this is not the case in AN(Reference Kyle, Bosaeus and De Lorenzo32, Reference Maisonneuve, Genton and Karsegard48). The FM is indirectly measured by subtracting the FFM from the total weight. BIA is an easy-to-perform, reproducible, non-invasive and inexpensive method to measure body composition.

Applicability and limitation of body impedance analysis in anorexia nervosa

BIA is reliable in healthy subjects and ill patients with a stable fluid/electrolytes balance (using the appropriate equations). It has not yet been validated for use in extreme cases, such as in severely malnourished (including AN cases) or obese individuals(Reference Maisonneuve, Genton and Karsegard48, Reference Kyle, Bosaeus and De Lorenzo49). Many reference equations have been proposed in different studies, but they were based on either healthy subjects(Reference Kyle, Bosaeus and De Lorenzo32) or on a sample poorly representative of the general population. In AN, the variability in extra-cellular and intracellular volume is likely to be responsible for reduced accuracy of BIA measurements and for the unexplained variance of body FFM and leg FFM(Reference Bedogni, Marra and Bianchi50). Sexual dimorphism is an important factor, which has led to sex specificity in the BIA equations; Sun et al. (Reference Sun, Chumlea and Heymsfield51) have studied BIA equations in men and women based on 1801 subjects with BMI between 14 and 39 kg/m2. They did not restrict their population to very lean subjects. Using Sun's equations, Piccoli et al. (Reference Piccoli, Codognotto and Di Pascoli52) have compared results of body composition measured by SFT and BIA in seventy-four women with a BMI between 10 and 17·5 kg/m2. They showed that BIA and anthropometric measurements were highly correlated (r 0·80–0·90; P < 0·05) when BMI values were above 15 kg/m2. With BMI values less than 15 kg/m2, there was a disagreement of FM and FFM estimates between the two different methods. They concluded that for patients with AN with a BMI below 15 kg/m2 down to 10 kg/m2 neither skinfold measurements nor BIA should be used. This statement is in line with the consensus recently published that BIA should be interpreted with caution in longitudinal follow-ups of body composition (BMI between 16 and 34 kg/m2)(Reference Kyle, Bosaeus and De Lorenzo49), in cases of malnourished individuals. Moreno et al. (Reference Moreno, Djeddi and Jaffrin30) compared various BIA methods during refeeding against DXA in AN. They found that FFM derived from two commercially available BIA instruments (i.e. Tefal® and Xitron®) was underestimated v. FFM derived from DXA measurements. Only one study has used multi-frequency BIA in order to differentiate between extracellular and intracellular water; Mika et al. (Reference Mika, Herpertz-Dahlmann and Heer53) found that multi-frequency BIA may be an appropriate tool for monitoring nutritional status during refeeding in AN patients; however, they did not use a 4-C model reference.

BIA in AN should be used with caution, but can still be clinically relevant in following up the relative changes in body compartments (rather than one punctual measurement)(Reference Kyle, Bosaeus and De Lorenzo32) in patients with AN even if it is not yet validated against a 4-C model.

Dual-energy X-ray absorptiometry

Brief description of dual-energy X-ray absorptiometry

The DXA scanner has a scanning X-ray source, an X-ray detector that records absorption data at two energy levels, and an interface with a computer system for processing and analysing the absorption data. Body tissues absorb X-ray energy differently. Assumptions regarding the level of hydration, bone edge detection and body thickness are used to convert absorption data into mass values for bone, fat and lean tissue components. These measurements can be made for the entire body or specific body parts(Reference Helba and Binkovitz17). DXA is a valuable tool for body composition determination in research settings and in clinical settings it is mainly used for bone density assessment.

Applicability and limitation of dual-energy X-ray absorptiometry in anorexia nervosa

The limitations of DXA are related to the differences in the calibration for fat proportion between the different brands of DXA scanners and between models from the same manufacturer. Even small differences in calibration may lead to anomalous results in subjects with AN(Reference Shephard19, Reference Tothill and James Hannan54, Reference Genton, Hans and Kyle55). Moreover, DXA is associated with radiation exposure even if it is considered low; therefore it is not ideal to perform multiple measurements in children(Reference Helba and Binkovitz17). However, Blake et al. (Reference Blake, Naeem and Boutros56) propose to use the infant whole body mode (only available on the A-model), and stress the fact that it is still important to keep radiation as small as possible, even though doses from child DXA examinations are low (for details about adjusting the DXA scan on infant modes, see Blake et al. (Reference Blake, Naeem and Boutros56)). Recently, a study compared the body composition of premenopausal women, ranging from AN to obesity, with DXA and computed tomography (CT) scanning. They found that in AN, DXA is a useful method for assessing body composition. Measurements underestimated, compared with CT scanning, trunk FM by 10·7 % and thigh fat by 3·8 %, with an overestimation of thigh muscle mass of 3·5 %. This might be due to the hydration status in AN, which can have a greater impact on DXA accuracy when assessing changes in body composition such as in treatment and follow-up(Reference Bredella, Ghomi and Thomas57, Reference Hannan, Cowen and Freeman58). Another study on AN female adolescents that compared DXA with skinfolds measurements found that, on an individual level, although body fat measurements from DXA and skinfolds were highly correlated, estimates of body fat were 9 % higher or 6 % lower when using SFT. This wide difference is not acceptable clinically in AN, as the limits of the Bland–Altman agreements were wide. (The Bland–Altman plot is a statistical method that describes the agreement between two quantitative measurements; explained previously in Bland & Altman(Reference Bland and Altman59).) Even small differences in adiposity have great impact on physiological interpretations in patients with AN(Reference Haas, Kohn and Clarke60). Some authors consider that DXA cannot be considered as a ‘gold standard technology to assess fat mass’ in AN(Reference Haas, Kohn and Clarke60). Nevertheless, Helba & Binkovitz(Reference Helba and Binkovitz17) concluded in their review article that DXA is the most accurate and reliable method of determining body composition in children with AN; it identifies accurately variations in FM and FFM in children and provides a better diagnostic and treatment follow-up tool of malnutrition in children with AN. In fact, DXA is accurate in measuring FM, but the value of FFM indicated by DXA does not indicate the level of hydration.

Since monitoring body composition in patients with AN is crucial for treatment and follow-up, BIA and DXA have been compared in several studies. In their study done on thirteen anorexic patients, Moreno et al. (Reference Moreno, Djeddi and Jaffrin30) found that BIA instruments underestimated FFM in subjects with AN in comparison with DXA, but an adjustment in the software corrected this discrepancy. Additionally, DXA and BIA machines available on the market have different prediction equations and different physical characteristics, making their comparison with other techniques unreliable.

In their review, Pichard et al. (Reference Pichard, Genton and Jolliet61) explain that changes in body composition determine the patient's overall health status. Therefore, in patients with AN, it is recommended to monitor systematically the variation levels between two measurements rather than the absolute values of FM and FFM(Reference Kyle, Bosaeus and De Lorenzo32) because methods of measuring body composition are not yet validated against a 4-C model.

Some other methods: computed tomography and underwater weighing

Some other methods usually reserved for research purposes include CT and UWW.

Brief description of computed tomography

CT is an imaging technique that is particularly useful in studying the relative deposition of subcutaneous and intra-abdominal fat(Reference Rogalla, Meiri and Hoksch62). However, its use is limited by the problems of availability (mostly used for diagnostic procedures other than nutritional assessment), radiation exposure and the high cost of the instrument.

Applicability and limitation of computed tomography in anorexia nervosa

In AN, many studies used this method in order to study regional fat distribution: Mayo-Smith et al. (Reference Mayo-Smith, Hayes and Biller63) used CT to measure subcutaneous and visceral adipose tissue in women with AN. They reported that the proportion of visceral adipose tissue to total adipose tissue in the CT image was significantly higher in patients with AN (0·4) compared with control subjects (0·14). Zamboni et al. (Reference Zamboni, Armellini and Turcato64) replicated and extended the findings of Mayo-Smith et al. (Reference Mayo-Smith, Hayes and Biller63) and they also concluded that patients with AN gain more in abdominal fat than other body regions.

Brief description of underwater weighing

UWW estimates FM starting from body density and applying mathematical equations. The body density is measured by submerging the body in water(Reference Probst, Goris and Vandereycken65). It is commonly used in order to validate other indirect methods of body composition measurements(Reference Siri66).

Applicability and limitation of underwater weighing in anorexia nervosa

Probst et al. (Reference Probst, Goris and Vandereycken21) compared the skinfold method and the UWW method and tested their validity for evaluating body composition before and after weight gain in patients with AN with a BMI between 11·9 and 17·5 kg/m2. They examined the effects of weight changes on body composition and subcutaneous fat after a refeeding protocol. They found that body fat estimation by the SFT equation appeared to be as accurate as UWW with an acceptable error of percentage body fat between 2·5 and 3·8 %.

Conclusion

The success of the psychiatric treatment of patients with AN necessitates an improvement in their nutritional status. Unfortunately, body weight alone does not reflect the evolution of the different body compartments during refeeding in AN. Thus, it is beneficial that the treating team assesses the nutritional status of the patient according to methods that are accurate, reproducible and applicable clinically while keeping in mind the respective limitations of each method. The ‘gold standard method’ is the 4-C model which requires several hours for completion. Therefore, the choice of method for nutritional assessment in AN is mostly led by the techniques available and the objective of the assessment (routine v. research).

In clinical settings (i.e. follow-up of patients, punctual nutritional assessment, etc) a pragmatic recommendation is to maximise standardisation of the condition of measurements in order to get a homogeneous follow-up trend. When performed by trained personnel, weight, height and body impedance analysis are well adapted to the clinical setting for AN patients as well as MUAC and WHR. The latter is a very important tool in detecting the redistribution of the FM in AN patients. SFT might not be a sensitive tool for short-term weight-restored AN patients. DXA is a more expensive tool, but it also provides relevant information about bone mass status and can be used as one punctual assessment. A practical approach that is a reflective method for nutritional assessment and follow-up in AN and in clinical settings remains the use of at least two methods of assessment, for example, the BMI and BIA. It is recommended that the change between two periods is monitored rather than the isolated absolute values for any used method.

In research settings, more sophisticated methods such as UWW and CT can be considered if available in addition to DXA, BIA or SFT (for large sample population). As hydration and bone density cannot be considered stable in AN, it is recommended that a combination of at least two methods is used that do not measure directly the same compartments such as DXA and body impedance analysis, SFT and BIA, etc. This will ensure that a high level of accuracy is obtained and it meets partially the concept of the 4-C model, which takes into account the different components of body composition and not only FM and FFM.

We still lack an accurate, unfailing and clinically applicable method of body composition measurement in AN patients. More studies are needed to further validate and standardise the different methods of body composition measurements in AN.

Acknowledgements

We thank W. Mattar for help in the final editing of the article. L. M. receives grants from the Eiffel scholarship programme and C. P. receives grants from the public Foundation Nutrition 2000 Plus. N G. receives a grant from the ‘Interface Contract’ at INSERM-U669 (2004–2009). The funding source had no involvement in the writing of the review article and in the decision to submit the paper for publication.

L. M. managed the literature searches and wrote the majority of the present review article. J. C. M. assisted in critical proofreading of the whole manuscript and in correction, mainly of the parts on anthropometric measurements and the impact of AN on body composition. N. G. contributed to the meticulous correction of the whole article. C. P. supervised the whole process of writing, assisted in the writing of the part on bioelectrical impedance and undertook further corrections. All authors contributed to and have approved the final manuscript.

All authors of the present review article declare that they have no conflicts of interest or any other material benefit or profit.

References

1Patton, GC, Coffey, C & Sawyer, SM (2003) The outcome of adolescent eating disorders: findings from the Victorian Adolescent Health Cohort Study. Eur Child Adolesc Psychiatry 12, Suppl. 1, I25I29.CrossRefGoogle ScholarPubMed
2Steinhausen, HC (2009) Outcome of eating disorders. Child Adolesc Psychiatr Clin N Am 18, 225242.CrossRefGoogle ScholarPubMed
3Pollice, C, Kaye, WH, Greeno, CG, et al. . (1997) Relationship of depression, anxiety, and obsessionality to state of illness in anorexia nervosa. Int J Eat Disord 21, 367376.3.0.CO;2-W>CrossRefGoogle ScholarPubMed
4Meehan, KG, Loeb, KL, Roberto, CA, et al. . (2006) Mood change during weight restoration in patients with anorexia nervosa. Int J Eat Disord 39, 587589.CrossRefGoogle ScholarPubMed
5Channon, S & DeSilva, WP (1985) Psychological correlates of weight gain in patients with anorexia nervosa. J Psychiatr Res 19, 267271.CrossRefGoogle ScholarPubMed
6Wamboldt, FS, Kaslow, NJ, Swift, WJ, et al. . (1987) Short-term course of depressive symptoms in patients with eating disorders. Am J Psychiatry 144, 362364.Google ScholarPubMed
7Peterson, MJ, Czerwinski, SA & Siervogel, RM (2003) Development and validation of skinfold-thickness prediction equations with a 4-compartment model. Am J Clin Nutr 77, 11861191.CrossRefGoogle ScholarPubMed
8Heymsfield, SB, Wang, Z, Baumgartner, RN, et al. . (1997) Human body composition: advances in models and methods. Annu Rev Nutr 17, 527558.CrossRefGoogle ScholarPubMed
9Withers, RT, LaForgia, J, Pillans, RK, et al. . (1998) Comparisons of two-, three-, and four-compartment models of body composition analysis in men and women. J Appl Physiol 85, 238245.CrossRefGoogle ScholarPubMed
10Wells, JC, Fuller, NJ, Dewit, O, et al. . (1999) Four-component model of body composition in children: density and hydration of fat-free mass and comparison with simpler models. Am J Clin Nutr 69, 904912.CrossRefGoogle ScholarPubMed
11Goran, MI, Toth, MJ & Poehlman, ET (1998) Assessment of research-based body composition techniques in healthy elderly men and women using the 4-compartment model as a criterion method. Int J Obes Relat Metab Disord 22, 135142.CrossRefGoogle ScholarPubMed
12Kerruish, KP, O'Connor, J, Humphries, IR, et al. . (2002) Body composition in adolescents with anorexia nervosa. Am J Clin Nutr 75, 3137.CrossRefGoogle ScholarPubMed
13Misra, M, Aggarwal, A, Miller, KK, et al. . (2004) Effects of anorexia nervosa on clinical, hematologic, biochemical, and bone density parameters in community-dwelling adolescent girls. Pediatrics 114, 15741583.CrossRefGoogle ScholarPubMed
14Mazess, RB, Barden, HS & Hanson, JA (1990) Body composition by dual-photon absorptiometry and dual-energy X-ray absorptiometry. Basic Life Sci 55, 427432.Google ScholarPubMed
15Schneider, P, Biko, J, Schlamp, D, et al. . (1998) Comparison of total and regional body composition in adolescent patients with anorexia nervosa and pair-matched controls. Eat Weight Disord 3, 179187.CrossRefGoogle ScholarPubMed
16Miller, KK, Wexler, TL, Zha, AM, et al. . (2007) Androgen deficiency: association with increased anxiety and depression symptom severity in anorexia nervosa. J Clin Psychiatry 68, 959965.CrossRefGoogle ScholarPubMed
17Helba, M & Binkovitz, LA (2009) Pediatric body composition analysis with dual-energy X-ray absorptiometry. Pediatr Radiol 39, 647656.CrossRefGoogle ScholarPubMed
18Misra, M, Katzman, DK, Cord, J, et al. . (2008) Bone metabolism in adolescent boys with anorexia nervosa. J Clin Endocrinol Metab 93, 30293036.CrossRefGoogle ScholarPubMed
19Shephard, RJ (1991) Pathological disturbances of body composition. In Body Composition in Biological Anthropology, pp. 226241. Cambridge: Cambridge University Press.Google Scholar
20Iketani, T, Kiriike, N, Nagata, T, et al. . (1999) Altered body fat distribution after recovery of weight in patients with anorexia nervosa. Int J Eat Disord 26, 275282.3.0.CO;2-I>CrossRefGoogle ScholarPubMed
21Probst, M, Goris, M, Vandereycken, W, et al. . (2001) Body composition of anorexia nervosa patients assessed by underwater weighing and skinfold-thickness measurements before and after weight gain. Am J Clin Nutr 73, 190197.CrossRefGoogle ScholarPubMed
22Russell, DM, Prendergast, PJ, Darby, PL, et al. . (1983) A comparison between muscle function and body composition in anorexia nervosa: the effect of refeeding. Am J Clin Nutr 38, 229237.CrossRefGoogle ScholarPubMed
23Russell, JD, Mira, M, Allen, BJ, et al. . (1994) Protein repletion and treatment in anorexia nervosa. Am J Clin Nutr 59, 98102.CrossRefGoogle ScholarPubMed
24Pichard, C & Kyle, UG (1998) Body composition measurements during wasting diseases. Curr Opin Clin Nutr Metab Care 1, 357361.CrossRefGoogle ScholarPubMed
25Melchior, JC, Rigaud, D, Rozen, R, et al. . (1989) Energy expenditure economy induced by decrease in lean body mass in anorexia nervosa. Eur J Clin Nutr 43, 793799.Google ScholarPubMed
26Gordon, C, Chumlea, W & Roche, A (1988) Stature, recumbent length, and weight. In Anthropometric Standardization Reference Manual, chapter 1, pp. 38 [Lohman, TG, Roche, AR and Martorell, R, editors]. Champaign, IL: Human Kinetics Books.Google Scholar
27Lee, RD & Neiman, D (2003) Anthropometry. In Nutritional Assessment, 3rd ed., pp. 165170. London: McGraw Hill.Google Scholar
28Centers for Disease Control and Prevention (2010) Prevention CfDCa. http://www.cdc.gov/growthcharts/clinical_charts.htm (accessed July 2010).Google Scholar
29Golden, NH, Jacobson, MS, Sterling, WM, et al. . (2008) Treatment goal weight in adolescents with anorexia nervosa: use of BMI percentiles. Int J Eat Disord 41, 301306.CrossRefGoogle ScholarPubMed
30Moreno, MV, Djeddi, DD & Jaffrin, MY (2008) Assessment of body composition in adolescent subjects with anorexia nervosa by bioimpedance. Med Eng Phys 30, 783791.CrossRefGoogle ScholarPubMed
31Trocki, O, Theodoros, MT & Shepherd, RW (1998) Lack of sensitivity of weight targets compared with body cell mass for determining recovery from malnutrition in adolescents with anorexia nervosa. Int J Eat Disord 23, 169176.3.0.CO;2-I>CrossRefGoogle ScholarPubMed
32Kyle, UG, Bosaeus, I, De Lorenzo, AD, et al. . (2004) Bioelectrical impedance analysis - part I: review of principles and methods. Clin Nutr 23, 12261243.CrossRefGoogle ScholarPubMed
33Trocki, O & Shepherd, RW (2000) Change in body mass index does not predict change in body composition in adolescent girls with anorexia nervosa. J Am Diet Assoc 100, 457460.CrossRefGoogle Scholar
34Cole, TJ, Flegal, KM, Nicholls, D, et al. . (2007) Body mass index cut offs to define thinness in children and adolescents: international survey. BMJ 335, 194.CrossRefGoogle ScholarPubMed
35Freedman, DS, Wang, J, Maynard, LM, et al. . (2005) Relation of BMI to fat and fat-free mass among children and adolescents. Int J Obes (Lond) 29, 18.CrossRefGoogle ScholarPubMed
36Golden, NH, Jacobson, MS, Schebendach, J, et al. . (1997) Resumption of menses in anorexia nervosa. Arch Pediatr Adolesc Med 151, 1621.CrossRefGoogle ScholarPubMed
37Pollock, M & Jackson, A (1984) Research progress in validation of clinical methods of assessing body composition. Med Sci Sports Exerc 16, 606613.CrossRefGoogle ScholarPubMed
38Durnin, JVGA & Womersley, J (1974) Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 years. Br J Nutr 32, 7797.CrossRefGoogle ScholarPubMed
39Russell, J, Allen, B, Mira, M, et al. . (1994) Total body nitrogen as a predictor of clinical status in anorexia nervosa. Int J Eat Disord 15, 275278.3.0.CO;2-9>CrossRefGoogle ScholarPubMed
40Caregaro, L, Favaro, A, Santonastaso, P, et al. . (2001) Insulin-like growth factor 1 (IGF-1), a nutritional marker in patients with eating disorders. Clin Nutr 20, 251257.CrossRefGoogle ScholarPubMed
41Misra, M, Soyka, LA, Miller, KK, et al. . (2003) Regional body composition in adolescents with anorexia nervosa and changes with weight recovery. Am J Clin Nutr 77, 13611367.CrossRefGoogle ScholarPubMed
42Collins, S (1996) Using middle upper arm circumference to assess severe adult malnutrition during famine. JAMA 276, 391395.CrossRefGoogle ScholarPubMed
43Martin, AC, Pascoe, EM & Forbes, DA (2009) Monitoring nutritional status accurately and reliably in adolescents with anorexia nervosa. J Paediatr Child Health 45, 5357.CrossRefGoogle ScholarPubMed
44Steinkamp, RC, Cohen, NL, Siri, WE, et al. . (1965) Measures of body fat and related factors in normal adults. I. Introduction and methodology. J Chronic Dis 18, 12791291.CrossRefGoogle ScholarPubMed
45Forbes, GB, Kreipe, RE, Lipinski, BA, et al. . (1984) Body composition changes during recovery from anorexia nervosa: comparison of two dietary regimes. Am J Clin Nutr 40, 11371145.CrossRefGoogle ScholarPubMed
46Mayer, L, Walsh, BT, Pierson, RN Jr, et al. . (2005) Body fat redistribution after weight gain in women with anorexia nervosa. Am J Clin Nutr 81, 12861291.CrossRefGoogle ScholarPubMed
47Orphanidou, CI, McCargar, LJ, Birmingham, CL, et al. . (1997) Changes in body composition and fat distribution after short-term weight gain in patients with anorexia nervosa. Am J Clin Nutr 65, 10341041.CrossRefGoogle ScholarPubMed
48Maisonneuve, N, Genton, L, Karsegard, VL, et al. . (2004) Role of impedance measurement in nutritional screening (article in French). Rev Med Suisse Romande 124, 611615.Google Scholar
49Kyle, UG, Bosaeus, I, De Lorenzo, AD, et al. . (2004) Bioelectrical impedance analysis - part II: utilization in clinical practice. Clin Nutr 23, 14301453.CrossRefGoogle ScholarPubMed
50Bedogni, G, Marra, M, Bianchi, L, et al. . (2003) Comparison of bioelectrical impedance analysis and dual-energy X-ray absorptiometry for the assessment of appendicular body composition in anorexic women. Eur J Clin Nutr 57, 10681072.CrossRefGoogle ScholarPubMed
51Sun, SS, Chumlea, WC, Heymsfield, SB, et al. . (2003) Development of bioelectrical impedance analysis prediction equations for body composition with the use of a multicomponent model for use in epidemiologic surveys. Am J Clin Nutr 77, 331340.CrossRefGoogle ScholarPubMed
52Piccoli, A, Codognotto, M, Di Pascoli, L, et al. . (2005) Body mass index and agreement between bioimpedance and anthropometry estimates of body compartments in anorexia nervosa. JPEN J Parenter Enteral Nutr 29, 148156.CrossRefGoogle ScholarPubMed
53Mika, C, Herpertz-Dahlmann, B, Heer, M, et al. . (2004) Improvement of nutritional status as assessed by multifrequency BIA during 15 weeks of refeeding in adolescent girls with anorexia nervosa. J Nutr 134, 30263030.CrossRefGoogle ScholarPubMed
54Tothill, P & James Hannan, W (2004) Dual-energy X-ray absorptiometry measurements of fat and lean masses in subjects with eating disorders. Int J Obes Relat Metab Disord 28, 912919.CrossRefGoogle ScholarPubMed
55Genton, L, Hans, D, Kyle, UG, et al. . (2002) Dual-energy X-ray absorptiometry and body composition: differences between devices and comparison with reference methods. Nutrition 18, 6670.CrossRefGoogle ScholarPubMed
56Blake, GM, Naeem, M & Boutros, M (2006) Comparison of effective dose to children and adults from dual X-ray absorptiometry examinations. Bone 38, 935942.CrossRefGoogle ScholarPubMed
57Bredella, MA, Ghomi, RH, Thomas, BJ, et al. (2010) Comparison of DXA and CT in the assessment of body composition in premenopausal women with obesity and anorexia nervosa Obesity (Silver Spring) (epublication ahead of print version 28 January 2010).CrossRefGoogle Scholar
58Hannan, WJ, Cowen, SJ, Freeman, CP, et al. . (1993) Evaluation of dual-energy X-ray absorptiometry for the assessment of body composition in anorexic females. Basic Life Sci 60, 169172.Google ScholarPubMed
59Bland, JM & Altman, DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet i, 307310.CrossRefGoogle Scholar
60Haas, VK, Kohn, MR, Clarke, SD, et al. . (2009) Body composition changes in female adolescents with anorexia nervosa. Am J Clin Nutr 89, 10051010.CrossRefGoogle ScholarPubMed
61Pichard, C, Genton, L & Jolliet, P (2000) Measuring body composition: a landmark of quality control for nutritional support services. Curr Opin Clin Nutr Metab Care 3, 281284.CrossRefGoogle ScholarPubMed
62Rogalla, P, Meiri, N, Hoksch, B, et al. . (1998) Low dose spiral computed tomography for measuring abdominal fat volume and distribution in a clinical setting. Eur J Clin Nutr 52, 597602.CrossRefGoogle ScholarPubMed
63Mayo-Smith, W, Hayes, CW, Biller, BM, et al. . (1989) Body fat distribution measured with CT: correlations in healthy subjects, patients with anorexia nervosa, and patients with Cushing syndrome. Radiology 170, 515518.CrossRefGoogle ScholarPubMed
64Zamboni, M, Armellini, F, Turcato, E, et al. . (1997) Body fat distribution before and after weight gain in anorexia nervosa. Int J Obes Relat Metab Disord 21, 3336.CrossRefGoogle ScholarPubMed
65Probst, M, Goris, M, Vandereycken, W, et al. . (2008) Body composition in girls and young women with anorexia nervosa: comparison of different equations. Int J Eat Disord 41, 180183.CrossRefGoogle Scholar
66Siri, WE (1993) Body composition from fluid spaces and density: analysis of methods. 1961. Nutrition 9, 480492.Google ScholarPubMed