en ENGLISH
eISSN: 2083-8441
ISSN: 2081-237X
Pediatric Endocrinology Diabetes and Metabolism
Bieżący numer Archiwum Artykuły zaakceptowane O czasopiśmie Suplementy Rada naukowa Recenzenci Bazy indeksacyjne Prenumerata Kontakt Zasady publikacji prac
Panel Redakcyjny
Zgłaszanie i recenzowanie prac online
SCImago Journal & Country Rank
4/2018
vol. 24
 
Poleć ten artykuł:
Udostępnij:
Artykuł przeglądowy

Metody pomiaru składu ciała w pediatrii – przegląd. Część 1

Jakub Dobroch
1
,
Klaudia Cieśluk
1
,
Małgorzata Sawicka-Żukowska
2
,
Maryna Krawczuk-Rybak
2

1.
Students’ Scientific Group, Department of Paediatric Oncology and Haematology, Medical University of Bialystok, Poland
2.
Department of Paediatrics, Paediatric Oncology, and Haematology, Medical University of Bialystok, Poland
Pediatr Endocrinol Diabetes Metab 2018; 24 (4): 185-190
Data publikacji online: 2019/03/15
Plik artykułu:
Pobierz cytowanie
 
Metryki PlumX:
 

Introduction

Reports prepared by the World Health Organisation (WHO) and epidemiological studies have reported a consistently increasing in-cidence of overweight and obesity in children for the last 30 years. These data refer mainly to developed countries; in North America and Europe the incidence rates of overweight and obesity in the paediatric population reach 40% [1]. Data from Poland do not determine unequivocally the trend among Polish children. According to research conducted under the supervision of the Institute of Mother and Child, 30.7% [2] of second- and third-grade schoolchildren and 18% of teenagers [3] are overweight or obese. Population research on a representative group of children and adolescents (7-18 years) determined the incidence of overweight and obesity in relation to interna-tional standards of body mass index (BMI) as 18.7% in boys and 14.1% in girls [4]. Body mass index is widely used to diagnose overweight, because it allows us to determine quickly its presence in relation to growth charts. However, considering dynamics of growth in adolescence and individual variability [5], the index is not a useful tool in assessing the presence of excess adipose tissue [6]. The scale of the obesity problem and the awareness of its relationship with numerous complications, such as metabolic syndrome (in which pathogenesis not only the excessive body mass matters, but even more the increased adipose tissue content and its improper dis-tribution [7]), create the need for wider diagnostics and careful monitoring of the treatment. Proper assessment of the participation of particular tissues in the body structure requires the use of specific measurement methods. In practice indirect body composition meas-urements are used, in which, on the basis of the knowledge of physical properties of tissues, their contents are measured in the body, and then, using mathematical formulas, the contribution of individual compartments is estimated [8]. Measurements are divided into two- and multi-component ones. A single test usually provides information on the content of one type of tissue, most often fat (fat mass – FM), with the remaining mass qualifying as fat-free (fat-free mass – FFM); in this way a two-component model (2C) is created. Other methods, including e.g. water content in the body (total body water – TBW), allow the next component to be isolated, creating a three-component model (3C) [5]. The four-component model (4C) is considered to be the gold standard, requiring several independent meas-urements in the examination of one patient. Owing to this, it is additionally possible to extract the content of protein and minerals from the lean body mass, ensuring the highest accuracy analysis among the available methods [9]. It is possible thanks to the densitometry examination with the double X-ray technique (X-ray dual-energy absorption – DXA) completed with the body volume measurements (body volume – BV) and TBW [10]. Body composition measurements are applicable not only in the fight against the obesity epidemic, but also in paediatric oncology [11] and monitoring of treatment and complications in chronic diseases [12]. The methods used are char-acterised by variable accuracy of measurements and require the use of a variety of equipment, and multi-component models can be creat-ed with different combinations of these tests [13]. The following paper presents an overview of the methods available in paediatrics for body composition measurements, taking into account their accuracy and the possibilities of clinical use. The current part discusses multi-component models (considered to be the most accurate), screening of two-component anthropometric methods, and bioelectrical imped-ance analysis (BIA).

Multi-component models

The four-component model (4C) [14] is considered to be the gold standard in body composition measurements. It is intended to provide more precise results than simple methods because it presupposes, apart from the fat content assessment, an accurate measure-ment of various components of lean body mass instead of assessment based on constant values of tissue density and water content in the body. In order to obtain the results, as well as weighing the patient, it is necessary to perform three independent measurements with various methods to measure individual parameters: body volume, bone mineral content (BMC), and water content in the body [13]. A typical set of methods that make up the 4C model includes BV measurement with ADP or HW (hydrostatic weighing), BMC with DXA, and TBW with D2O (deuterium oxide). Depending on the availability of devices to make a given measurement, TBW can also be obtained using the BIA method [15]. An alternative approach to creating multi-component models assumes the measurement of potassi-um content in the body, which allows accurate assessment of the muscle mass and protein, and thus the identification of all key compo-nents of lean body mass (TBW, BMC, protein) [16]. However, this is a highly specialised method with very limited access. Therefore, in most studies, protein content is included in the remaining FFM.
The advantage of using a multi-component model in children is elimination of the assumptions of a constant proportion of the relevant tissue content in the body. These values change significantly as children grow up, and this process does not occur in every child at the same pace [9]. In clinical practice, each body composition measurement with the 4C model would be too time-consuming and would require constant access to devices that measure the components of this model and the participation of personnel trained in carry-ing out measurements with each of the required methods. There are attempts to simplify the creation of the 4C model by combining the measurement of two components using one method, e.g. BV using DXA instead of ADP or HW. This solution has been proposed so far in adult studies [17]. The search for this type of improvement may be important in the studies carried out on the paediatric group because in the case of children the preferable methods are those that allow faster achievement of the desired effect and require shorter cooperation on the patient’s part [18].
In a few studies, the 3C model appears as the reference method, which extracts only TBW from the body lean mass, but does not require the use of the DXA method [19]. As a result, the body composition is divided into the following compartments: FM, TBW, and FFM. Determining the accuracy of simple, two-component methods in comparison with the 3C model does not raise any objections and allows a reliable comparison in the lack of availability of DXA or other technique provided in 4C.
The most advanced models include the use of special formulas or methods, such as neutron activation analysis [20] to measure the content of minerals in soft tissues and glycogen, making it possible to create five- or even six-component models [18]. These models are used in individual studies in groups of sportsmen [21], and their discussion goes beyond the scope of the current study.

Anthropometric body composition measurements

Anthropometry, due to the simplicity of measurements and low cost, is a commonly used group of methods for assessing body composition, in particular the content of adipose tissue [22]. Practical applications are primarily body mass measurements, BMI, waist circumference, and skinfold thickness.

Body mass

Body mass measurement plays a key role in assessing the nutritional status of both adults and children. Together with height, this parameter is used to estimate the fat content using the body mass index. Assuming that the most variable body component is adipose tissue, changes in body mass may serve as an independent determinant of fat content fluctuation [5]. In order to increase the accuracy of measurements, the test should be carried out in light clothes and without shoes, and in the youngest children – with a dry diaper [22]. However, it should be remembered that, apart from clothing, the level of hydration or the presence of oedema also affects the obtained values, which, together with the daily variability of obtained results, reaching up to 0.5 kg and more, limits the predictive value of this method [5].

Body mass index

Body mass index, obtained from the formula: weight (kg)/height (m)², is the most frequently used tool for assessing relative body mass and nutritional status [9, 23]. It is a faster and more intuitive tool for assessing the degree of nutrition than the Cole index (CI). Cole index, shown as a percentage and calculated on the basis of the formula (body mass × standard body length)²/(standard body weight × body length²), requires a comparison of the patient’s height and weight with gender and age values in a growth chart, which is not is necessary when calculating BMI. The assessment of BMI is important in assessing the risk of diseases associated with increased body weight, such as type 2 diabetes or coronary heart disease in adults, but its use in children and adolescents is questionable. Body mass index does not differentiate between adipose tissue and lean body mass, which may lead to misinterpretation of the results ob-tained, both among malnourished people, who tend to increase relative fat tissue and decrease FFM, as well as in sportsmen with in-creased muscle mass in relation to fat content [9]. In addition, difficulties in developing a range of normal values due to the natural changes in the body composition of growing children significantly reduce the usefulness of the indicator in the paediatric population [23]. Therefore, BMI should not be used as the only method for assessing the body fat level of the subject [22].

Waist circumference

Waist circumference (WC) is the basic method of assessing abdominal obesity and predicting its adverse effects, such as insulin re-sistance or lipid metabolism disorders [9], and it is an equally effective technique for assessing total obesity as BMI [22]. The measure-ment is carried out in a standing position at the level of the navel or halfway between the rib arch and the iliac crest. WC lacks universal recommendations due to the proven dependence of the results obtained on age, gender, height, and ethnicity. Some conditions, such as constipation or ascites, may also limit the accuracy of this method [22].
The modification of this technique, also used for the estimation of central obesity, is the ratio of the waist to the hip (waist-hip ratio – WHR) measured in the upright position at the widest point of the hips and buttocks. However, it should be remembered that WHR values decrease with the age of the child due to the natural increase in the size of the pelvis, especially marked in girls. What is more, people with higher BMI and with even body fat distribution may have WHR values comparable to patients with lower BMI, which is the greatest disadvantage of this technique [22].

Skinfold thickness

Skinfold thickness is the measurement of the thickness of two layers of subcutaneous adipose tissue by pinching them with a body fat calliper [22] in selected areas of the body (most often at biceps and triceps, subscapular, supraumbrilical, and thigh areas). It is as-sumed that the thickness of subcutaneous fat measured this way reflects its total content in the body [24]. The method gives comparable results to the 3C and DXA models in estimating the average fat content in group measurements and is also the best screening technique for individual assessment of body fat, which can be used also in infants [5, 9, 25]. The disadvantage of the presented technique is first of all the necessity to use the formulas developed to determine the body composition, which limit its use to the population for which they were created [5, 9]. The assessment of the skinfold thickness is considered to be an imprecise method, with a tendency to increase the occurrence of errors together with the increase in the adipose tissue content and the age of the subject [5, 9, 22, 24]. Limited precision also results from the variety of available body fat callipers, differences in the selection of measurement sites, or techniques of skinfold by examining subjects [24]. Although the investigator’s experience and constant quality control allow more replicable results to be ob-tained [5], this method should be used only for screening body composition [9]. Taking into account the advantages and disadvantages of the presented methods, it can be concluded that anthropometric measurements are sufficient for general diagnostics of overweight and obesity in children, while more advanced and accurate techniques should be used for further detailed examination of body composition [22, 26].

Bioelectrical impedance analysis

Bioelectrical impedance analysis is a popular, non-invasive method of body composition measurement, based on the presence of dif-ferences in the electrical impedance of individual tissues, which is generated by electric current at a specific frequency [27]. As a screening indirect measurement method, BIA requires the use of equations with certain assumptions. They concern the geometry of the examined body (the cylinder volume depends on the measured body mass and on data of the subject height entered into the device), the uniform distribution of tissues in the body and the constancy of the environment in which the measurement is made [28]. The non-conductive FM mass is isolated, and dry cell mass (which consists of protein, bone mass, and electrolytes) and TBW divided between intracellular fluid (ICF) and extracellular fluid (ECF) can be estimated from the remaining FFM. These estimates are elaborated on the basis of appropriate formulas, which, especially in paediatric groups, should take into account variables such as age, gender, and ethnici-ty. The level of nutrition and physical activity and the proportions of the limb length to the patient’s torso also influence the analysis course. The inhomogeneity of the group and the lack of appropriate modifications of the equations limit the reliability of the study [27, 29, 30].
There is a high commercial availability of devices that allow the body composition measurement by the BIA method. They dif-fer technologically. Therefore, it is possible to distinguish devices generating a signal with one or more frequencies (in the range of 5-200 kHz) and using a different number and arrangement of electrodes in foot-foot configurations (leg-to-leg/foot-to-foot), hand-to-foot, and hand-to-hand [31]. Newer devices present the analysis results for five separate body segments – four limbs and torso, allowing the estimation of the distribution of adipose tissue within the body [5]. The multitude of available solutions is conducive to the widespread use of BIA, but it limits the possibilities of comparing the results obtained by means of various devices, and even more by different methods. This is shown by studies in which the body composition of the test group was measured in the same conditions with a different number of devices, location of electrodes, and frequency of current used. The compared analysers showed variable compli-ance of the fat percentage (% BF) and FFM with the reference method (DXA) in paediatric groups; however, it is impossible to deter-mine which BIA model would be the most accurate [32].
The advantages of BIA in the context of usefulness in clinical practice undoubtedly include the simplicity and quickness of analysis and the relatively low cost of the apparatus. The measurement can be carried out by one person after basic training. Modern analysers resemble a scale with a built-in display and electrodes, which should be in contact with bare skin during the measurement. Depending on the type of device, it is required that the patient stays still, usually in a standing position (in the case of traditional hand-foot electrodes, the position should be lying), from a few dozen seconds to several minutes. In order to ensure credibility and repeatabil-ity, each study should be conducted to meet certain conditions. The patient should be properly hydrated, optimally on an empty stomach, and avoid intense exercise for 12 hours before the test, and for a few hours should not take diuretics or caffeine. The patient should be dressed lightly and loosely, should not wear jewellery, and should not use creams for hands or feet immediately before the test [28].
Bioelectrical impedance analysis is the subject of numerous comparisons with methods considered as reference, such as DXA [32], ADP [33], D2O [34], or HW [35], or multi-component methods [19]. The research provides ambiguous data on the accuracy of BIA; depending on the publication, it is indicated that there is a tendency to overestimate [35] or underestimate [32] FM or the BF per-centage. Regardless of differences in the compliance of measurements with BIA and reference methods, a high correlation between the obtained results is observed [36]. While maintaining repetitive analysis conditions, BIA is an invaluable help in monitoring changes in body composition in individual patients [37]. An interesting direction is also the development of norms specific for a given population of parameters measured by BIA [38].

References

1. Han JC, Lawlor DA, Kimm SY. Childhood obesity. Lancet 2010; 375: 1737-1748. doi: 10.1016/S0140-6736(10)60171-7
2. Dzielska A, Zawadzka D, Mazur J, et al. Nadwaga i otyłość u polskich 8-latków w świetle uwarunkowań biologicznych, beha-wioralnych i społecznych: Raport z międzynarodowych badań WHO Childhood Obesity Surveillance Initiative (COSI). Instytut Matki i Dziecka, Warszawa 2017.
3. Zdrowie i zachowania zdrowotne młodzieży szkolnej w Polsce na tle wybranych uwarunkowań socjodemograficznych. Mazur J (ed.). Wyniki badań HBSC 2014. Instytut Matki i Dziecka, Warszawa 2015.
4. Kułaga Z, Litwin M, Tkaczyk M, et al. Polish 2010 growth references for school-aged children and adolescents. Eur J Pediatr 2011; 170: 599-609. doi: 10.1007/s00431-010-1329-x
5. Norgan NG. Laboratory and field measurements of body composition. Public Health Nutr 2005; 8: 1108-1122.
6. Vanderwall C, Randall Clark R, et al. BMI is a poor predictor of adiposity in young overweight and obese children. BMC Pe-diatr 2017; 17: 135. doi: 10.1186/s12887-017-0891-z
7. Taksali SE, Caprio S, Dziura J, et al. High visceral and low abdominal subcutaneous fat stores in the obese adolescent: a determinant of an adverse metabolic phenotype. Diabetes 2008; 57: 367-371. doi: 10.2337/db07-0932
8. Lohman TG, Going SB. Body composition assessment for development of an international growth standard for preadolescent and adolescent children. Food Nutr Bull 2006; 27: 314-325. doi: 10.1177/15648265060274S512
9. Wells JC, Fewtrell MS. Measuring body composition. Arch Dis Child 2006;91:612-617. doi: 10.1136/adc.2005.085522
10. Wilson JP, Mulligan K, Fan B, et al. Dual-energy X-ray absorptiometry-based body volume measurement for 4-compartment body composition. Am J Clin Nutr 2012; 95: 25-31. doi: 10.3945/ajcn.111.019273
11. Murphy AJ, White M, Elliott SA, et al. Body composition of children with cancer during treatment and in survivorship. Am J Clin Nutr 2015; 102: 891-896. doi: 10.3945/ajcn.114.09969
12. Martinez EE, Smallwood CD, Quinn NL, et al. Body Composition in Children with Chronic Illness: Accuracy of Bedside As-sessment Techniques. J Pediatr 2017; 190: 56-62. doi: 10.1016/j.jpeds.2017.07.045
13. Fields DA, Goran MI. Body composition techniques and the four-compartment model in children. J Appl Physiol 2000; 89: 613-620. doi: 10.1152/jappl.2000.89.2.613
14. Vergara FV, Bustos ED, Marques LL, et al. The four-compartment model of body composition in obese Chilean schoolchil-dren, by pubertal stage: comparison with simpler models. Nutrition 2014; 30: 305-312. doi: 10.1016/j.nut.2013.09.002
15. Wilson JP, Strauss BJ, Fan B, et al. Improved 4-compartment body-composition model for a clinically accessible measure of total body protein. Am J Clin Nutr 2013; 97: 497-504. doi: 10.3945/ajcn.112.048074
16. Ellis KJ, Yao M, Shypailo RJ, et al. Body-composition assessment in infancy: air-displacement plethysmography compared with a reference 4-compartment model. Am J Clin Nutr 2007; 85: 90-95. doi: 10.1093/ajcn/85.1.90
17. Smith-Ryan AE, Mock MG, Ryan ED, et al. Validity and reliability of a 4-compartment body composition model using dual en-ergy x-ray absorptiometry-derived body volume. Clin Nutr 2017; 36: 825-830. doi: 10.1016/j.clnu.2016.05.006
18. Silva AM, Fields DA, Sardinha LB. A PRISMA-driven systematic review of predictive equations for assessing fat and fat-free mass in healthy children and adolescents using multicomponent molecular models as the reference method. J Obes 2013; 2013: 148696. doi: 10.1155/2013/148696
19. Delisle Nyström C, Henriksson P, Alexandrou C, et al. The Tanita SC-240 to Assess Body Composition in Pre-School Children: An Evaluation against the Three Component Model. Nutrients 2016; 8: pii: E371. doi: 10.3390/nu8060371.
20. Wang Z, Pi-Sunyer FX, Kotler DP, et al. Multicomponent methods: evaluation of new and traditional soft tissue mineral models by in vivo neutron activation analysis. Am J Clin Nutr 2002; 76: 968-974. doi: 10.1093/ajcn/76.5.968
21. Moon JR, Eckerson JM, Tobkin SE i wsp. Estimating body fat in NCAA Division I female athletes: a five-compartment model validation of laboratory methods. Eur J Appl Physiol 2009; 105: 119-130. doi: 10.1007/s00421-008-0881-9
22. Horan M, Gibney E, Molloy E, et al. Methodologies to assess paediatric adiposity. Ir J Med Sci 2015; 184: 53-68. doi: 10.1007/s11845-014-1124-1
23. Weber DR, Leonard MB, Zemel BS. Body composition analysis in the pediatric population. Pediatr Endocrinol Rev 2012; 10: 130-139.
24. Fosbol MØ, Zerahn B. Contemporary methods of body composition measurement. Clin Physiol Funct Imaging 2015; 35: 81-97. doi: 10.1111/cpf.12152
25. Wohlfahrt-Veje C, Tinggaard J, Winther K, et al. Body fat throughout childhood in 2647 healthy Danish children: agreement of BMI, waist circumference, skinfolds with dual X-ray absorptiometry. Eur J Clin Nutr 2014; 68: 664-670. doi: 10.1038/ejcn.2013.282
26. Jensen SM, Mølgaard C, Ejlerskov KT, et al. Validity of anthropometric measurements to assess body composition, including muscle mass, in 3-year-old children from the SKOT cohort. Matern Child Nutr 2015; 11: 398-408. doi: 10.1111/mcn.12013
27. Dehghan M, Merchant AT. Is bioelectrical impedance accurate for use in large epidemiological studies? Nutr J 2008; 7: 26. doi: 10.1186/1475-2891-7-26.
28. Bera TK. Bioelectrical Impedance Methods for Noninvasive Health Monitoring: A Review. J Med Eng 2014; 2014: 381251. doi: 10.1155/2014/381251
29. Nightingale CM, Rudnicka AR, Owen CG, et al. Are ethnic and gender specific equations needed to derive fat free mass from bioelectrical impedance in children of South asian, black african-Caribbean and white European origin? Results of the assess-ment of body composition in children study. PLoS One 2013; 8: e76426. doi: 10.1371/journal.pone.0076426
30. Montagnese C, Williams JE, Haroun D, et al. Is a single bioelectrical impedance equation valid for children of wide ranges of age, pubertal status and nutritional status? Evidence from the 4-component model. Eur J Clin Nutr 2013; 67: 34-39. doi: 10.1038/ejcn.2011.213
31. Khalil SF, Mohktar MS, Ibrahim F. The Theory and Fundamentals of Bioimpedance Analysis in Clinical Status Monitoring and Diagnosis of Diseases. Sensors (Basel) 2014; 14: 10895-10928. doi: 10.3390/s140610895.
32. Lee LW, Liao YS, Lu HK, et al. Validation of two portable bioelectrical impedance analyses for the assessment of body compo-sition in school age children. PLoS One 2017; 12: e0171568. doi: 10.1371/journal.pone.0171568
33. Foucart L, De Decker A, Sioen I, et al. Hand-to-foot bioelectrical impedance analysis to measure fat mass in healthy children: A comparison with air-displacement plethysmography. Nutr Diet 2017; 74: 516-520. doi: 10.1111/1747-0080.12345
34. Liu A, Byrne NM, Ma G, et al. Validation of bioelectrical impedance analysis for total body water assessment against the deu-terium dilution technique in Asian children. Eur J Clin Nutr 2011; 65: 1321-1327. doi: 10.1038/ejcn.2011.122
35. Jensky-Squires NE, Dieli-Conwright CM, Rossuello A, et al. Validity and reliability of body composition analysers in children and adults. Br J Nutr 2008; 100: 859-865. doi: 10.1017/S000711450892546
36. Chula de Castro JA, Lima TR, Silva DAS. Body composition estimation in children and adolescents by bioelectrical impedance analysis: A systematic review. J Bodyw Mov Ther 2018; 22: 134-146. doi: 10.1016/j.jbmt.2017.04.010
37. Meredith-Jones KA, Williams SM, Taylor RW. Bioelectrical impedance as a measure of change in body composition in young children. Pediatr Obes 2015; 10: 252-259. doi: 10.1111/ijpo.263
38. Chiplonkar S, Kajale N, Ekbote V, et al. Reference Centile Curves for Body Fat Percentage, Fat-free Mass, Muscle Mass and Bone Mass Measured by Bioelectrical Impedance in Asian Indian Children and Adolescents. Indian Pediatr 2017; 54: 1005-1011.

© 2024 Termedia Sp. z o.o.
Developed by Bentus.