A new simple method for estimating trunk and visceral fat by bioelectrical impedance: Comparison with magnetic resonance imaging and dual X-ray absorptiometry in Czech adolescents
Authors:
Hana Zamrazilová 1; Petr Hlavatý 1; Lenka Dušátková 1; Barbora Sedláčková 1; Irena Aldhoon Hainerová 2; Marie Kunešová 1; Antonín Škoch 3; Milan Hájek 3; Vojtěch Hainer 1
Authors place of work:
Endokrinologický ústav v Praze, Centrum pro diagnostiku a léčbu obezity
1; Univerzita Karlova v Praze, 3. lékařská fakulta, Klinika dětí a dorostu FNKV
2; IKEM, ZRIR, Oddělení MR – spektroskopie
3
Published in the journal:
Čas. Lék. čes. 2010; 149: 417-422
Category:
Original Article
Summary
Objective:
The enlargement of visceral fat (VF) in abdominal obesity is associated with increased cardiometabolic health risks in both adults and adolescents. A precise measurement of VF by sophisticated methods as computed tomography (CT) and magnetic resonance imaging (MRI) can not be applied in routine clinical practice. The aim of our study was to compare estimates on visceral and trunk fat in adolescents obtained by a new bioimpedance analysis instrument (BIA) - Tanita AB-140 ViScan - with those obtained by MRI, dual X-ray absorptiometry (DEXA) and anthropometry.
Methods and Results:
Investigated cohort: 39 adolescent secondary school students; median (lower quartile; upper quartile) - age: 16,4 (15,4; 17,4) years; body weight: 63.8 (54.1; 79.0) kg; BMI: 21.4 (19.5; 27.4) kg/m2. Investigated parameters: BMI, body circumferences and sagittal abdominal diameter (SAD), trunk, visceral and subcutaneous fat determined by BIA, MRI and DEXA. Statistics: Spearman’s correlations. The assesment of trunk fat by BIA correlated with DEXA estimates (r=0.979, p<0.0001) and with abdominal fat measured by MRI (r=0.930, p<0.0001). The visceral fat amount derived from abdominal BIA exhibited lower, however significant correlation with visceral fat determined by MRI (r=0.791, p<0.001). The visceral fat area presumed by abdominal BIA significantly correlated with anthropometric parameters as abdominal circumference (r=0.923, p<0.0001), waist circumference (r=0.913, p<0.0001) and SAD (r=0.891, p<0.0001).
Conclusions:
The new method estimating abdominal fat by BIA represents a reliable tool for clinical evaluation of the trunk fat in adolescents. However, its advantages over anthropometric measurements in evaluation of VF require further validation studies.
Key words:
visceral fat mass, waist circumference, sagittal abdominal diameter, bioelectrical impedance, magnetic resonance imaging, dual X-ray absorptiometry, adolescents.
Introduction
The prevalence of obesity has reached global epidemic proportions. This increasing trend of obesity can also be observed in children and adolescents and must be taken into account with regard to health risks and comorbidities associated with obesity. Many studies have demonstrated a relationship between obesity in children and adolescents and its manifestation into adulthood together with cardiometabolic risks related to the enlargement of visceral fat stores (1, 2, 3, 4, 5, 6).
At the present time the amount of visceral fat can be precisely quantified by sophisticated imaging methods as magnetic resonance imaging (MRI) and computerized tomography (CT). These methods can not be applied in a routine clinical practice due to financial demands, limited accessibility or radiation exposure. Simple anthropometric measurements i.e. waist circumference and sagittal abdominal diameter (SAD) were shown to correlate with visceral fat depots. Many studies have demonstrated a significant positive correlation between the amount of visceral fat and waist circumference values (7, 8, 9, 10, 11, 12).
The enlargement of visceral fat stores is mainly associated with cardiometabolic health risks. The visceral fat is a stronger independent predictor of metabolic syndrome than the subcutaneous abdominal fat (13, 14, 15, 16). Studies conducted in both adults (17, 18, 19, 20, 21) and children (22, 23) demonstrated that the degree of cardiometabolic health risk is significantly related to waist circumference.
Analysis of body composition by bioelectrical impedance (BIA) has been largely applied both in the clinical practice and in epidemiological studies (24, 25, 26). BIA instruments were validated in the Czech Republic by comparing body composition estimates obtained by BIA with more sophisticated methods such as hydrodensitometry or dual energy X-ray absorptiometry (DEXA) (27, 28, 29). It should be emphasized that an assessment of body composition by BIA is significantly influenced by the hydration of examined subjects and the calculation of body compartments should employ population specific algorithms (30). In spite of several disadvantages of BIA methods compared to sophisticated imaging methods strong correlations between the obtained measurements have been identified. According to Sluyter et al. (31) BIA when compared to DEXA tends to overestimate the amount of fat in normal weight adolescents aged 12-19 years, but underestimates fat stores in obese individuals. Recently developed instrument Tanita AB-140 ViScan (Tanita Corporation, Tokyo, Japan) evaluates a degree of visceral fat stores enlargement by using a principle of bioelectrical impedance. A measurement is quite simple and results are obtained immediately. If this instrument is able to reflect the amount of visceral fat, it could be a reliable diagnostic tool in specialized obesity and diabetes units as well as in primary care clinics. The company manufacturing ViScan declares significant correlations between the visceral fat measured by BIA and that obtained by CT (32). Company studies were conducted in a large sample of Japanese population of a variety of physiques from infants to athletes, healthy adults and people with spinal injuries, etc. The aim of our study was to validate the ViScan instrument in Czech adolescents. Results provided by the Tanita AB-140 ViScan (degree of visceral fat enlargement, percentage of trunk fat) were compared with the data provided by MRI and DEXA as well as with those obtained by selected anthropometric measurements.
Subjects
Thirty nine randomly selected adolescents (20 boys; 19 girls) at mean age of 16.4 yrs (range: 15.4–17.4 yrs, lower quartile: 15.4 yrs, upper quartile: 17.4 yrs) were recruited from a secondary school in Prague. The selection of subjects reflected a broad spectrum of Body Mass Index (BMI) (16.9–34.3 kg/m2) in investigated adolescent population (Table 1). The studied subjects when investigated took no medications. Subjects and their parents were informed in detail about planned examinations and all of them signed an informed consent form before the study started.
Methods
Bioimpedance (BIA)
The percentage of trunk fat (TF) and the degree of visceral fat enlargement (VF) were determined by the Tanita AB-140 ViScan (Tanita Corporation, Tokyo, Japan). Measurements were performed according to recommendations provided by the manufacturer.
Dual-Energy X-Ray Absorptiometry (DEXA)
Trunk fat mass (%, kg) was measured by DEXA (Hologic QDR 2000 (Hologic Inc, Waltham, MA, USA). The DEXA scanner utilizes an X-ray tube as the radiation source alternating between two excitation voltages of 70 and 140 kVp that generate effective dual-energy photons. Whole-body images were performed using array-beam (technique oblique stripes) measured from head to toe. This method minimizes parallax effect of array-beam sensing longitudinal lines tilted at an angle of 45 ° to the orientation of the fan. The scan was performed in the array-beam mode, which requires less than 6 min for scanning the whole body. Radiation dose is 0.005 mSv. Measured data were analyzed using software version 6.2. Body parts (hands, legs, trunk and head) are plotted using specific anatomical points. All images were made by one person in order to minimize variations in measurements.
Magnetic Resonance Imaging (MRI)
MRI to measure the volume of visceral fat (VF) and subcutaneous (SF) was performed on the device Siemens Avanto 1.5 T scanner. Another investigated parameter was the total fat in the examinated area of the abdomen (abdominal fat mass, AFM). AFM is the sum of VF and SF. A single-slice breath-hold turbo spin-echo (TSE) sequence (turbo factor 5, echo time TE 10 ms, TR 450 ms, slice thickness 10 mm) was modified to suppress the water signal so that the images contained practically only the fat signal. Abdominal volume of 270 mm was covered with 27 of the successive cuts. MRI images were measured in the standard whole-body coil with retention of breath of subject. On the one holding the breath accounted for 1 MRI image. To evaluate the volume of visceral and subcutaneous fat software written in MATLAB was used. For the identification of fat mass in the images and calculating their volume is necessary to find the optimal threshold for assigning the image pixel adipose tissue (to be known as segmentation). This was achieved through semi-automatic analysis of the histogram of all image layers. The result of segmentation was evaluated by the operator. The signal of visceral and subcutaneous fat in the pictures can not be separated by signal strength, but only on the basis of their anatomical deposit. It was necessary to make the border of visceral and subcutaneous fat areas. Borders have been performed manually by the operator (33) for each individual MRI image. To reduce the impact of the operator, visceral fat areas were evaluated by two independent persons.
Anthropometric measurements
Body height was measured by a stadiometer (precision 0.1 cm), body weight was measured the Tanita BC 418 MA (precision 0.1 kg), body circumferences were determined by a tape measure (precision 0.1 cm). Waist, abdominal and hip circumferences were measured in a horizontal level; waist circumference midway between the upper iliac crest and the lower rib, abdominal circumference at the level of umbilicus and hip circumference over the maximum buttocks diameter. SAD was measured by pelvimeter at the level L4/5 in a horizontal level.
Statistical analysis
Due to non-Gaussian data distribution the median, lower and upper quartile were used to describe data. The relationships between compared methods were evaluated using non-parametric correlation analysis (The Spearman rank correlation coefficient). The statistical software Statgraphics Centurion v. XV from Statpoint, Inc. (Warrenton, Virginia, USA) a NCSS2002 (Kaysville, Utah, USA) were used for data analysis.
Results
The aim of the study was to validate the new instrument in the Czech adolescent population. Results of correlation analysis are presented for the total monitored group irrespective of sex. In order to better characterize the studied cohort, the basic descriptive statistics are demonstrated not only for the total group, but also for girls and boys separately. Essential characteristics including body composition assessments obtained by different methods are shown in Table 1. Spearman’s correlations between measurements are summarized in Table 2.
Significant positive correlations were demonstrated between results on visceral and trunk fat obtained by BIA and those assessed by DEXA (TF %, TF kg), MRI (MRI–SF) and anthropometry (waist circumference, abdominal circumference and SAD). The strongest correlations were shown when the percentage of trunk fat determined by BIA was compared with DEXA (TF %, TF kg), total abdominal fat (MRI–AFM) (graph 1, 2) and subcutaneous abdominal fat (MRI–SF). The visceral fat determined by BIA significantly correlated with anthropometric parameters as waist circumference, abdominal circumference and SAD. The SAD exhibited higher correlations with all measures of central fat obtained by MRI and DEXA in comparison to the waist circumference. Lower correlations were demonstrated between the level of visceral fat enlargement determined by BIA and the amount of visceral fat measured by MRI (MRI–VF).
Discussion
Primary aim of our study was to compare visceral and trunk fat in adolescents recorded by a new bioimpedance method (BIA - Tanita AB-140 ViScan) with measurements obtained by MRI, dual X-ray absorptiometry (DEXA) and anthropometry.
Tanita ViScan evaluates a degree of enlargement of the visceral fat depots („visceral fat level“) by calculating a degree scale, in which the value ten corresponds to 100 cm2 of visceral fat measured by CT (32). Tanita ViScan also evaluates a percentage of trunk fat. Manufacturer reports a comparison between the data obtained by the Tanita ViScan and those obtained by CT and DEXA. This finding is based on results of studies performed only in Japanese population. We assume that the BIA instrument derives the „visceral fat level“ from equations using not only BIA measurements but also anthropometric parameters as waist circumference and SAD. Unfortunately, no detailed information about both the calculation of the „visceral fat level“ and exact values for impedance measurements were provided by the manufacturer.
The study demonstrated significant positive correlations between indexes obtained by all methods used in our project (Table 2). It is obvious that the measurements by the Tanita ViScan yielded reliable results with regard to the amount of trunk fat. This was confirmed by high correlations with both the MRI (AFM: r = 0.930, p < 0.0001 – grapf 1) and DEXA (TF %: r = 0.979, p < 0.0001 – grapf 2; TF kg: r = 0.969, p < 0.0001) measurements. These results are in agreement with correlation analysis reported by the manufacturer as well as with results reported in other studies (34, 35, 36).
Moreover, strong correlations were also revealed between the degree of visceral fat enlargement determined by BIA and waist circumference. A significant relationship between the waist circumference and the visceral fat measured by CT was reported in previously published studies (7, 9, 10, 11). Waist circumference is recommended by the International Diabetes Federation as a simple parameter for evaluation of visceral fat while defining the metabolic syndrome (37). However, an interindividual variability in relation between the waist circumference and the amount of visceral fat should be carefully considered. The Japanese Association for the Study of Obesity (38) has shown that men with a narrow range of waist circumference (85–86 cm) exhibited significant differences in the amount of visceral fat (67–137 cm2). Nevertheless, the ease of use and the accessibility of anthropometric methods in routine clinical practice overcome theirs potential disadvantages due to the interindividual variability in the relationship between the waist circumference and the visceral fat.
Abdominal circumference and SAD were additional anthropometric parameters, which exhibited strong correlations with visceral fat determined by BIA. Moreover, SAD compared to waist and abdominal circumferences exhibited higher correlations with all measures of central fat obtained by MRI and DEXA. This finding supports previously published data, which demonstrated asignificant relation between SAD and visceral fat determined by CT (39, 40).
The amount of visceral fat determined by BIA significantly correlated with the amount of fat depots analyzed by MRI (SF, VF, AFM). However, these correlations were not as high as those with anthropometric parameters.
Similar positive associations between the visceral fat measured by BIA and MRI were described in the study using other BIA instruments as Tanita Inner Scan BC-532 a Omron BF-500 (41). Several other studies conducted also entirely in adults focused on the validity of BIA methods in determination of visceral fat (7, 10, 42). These studies confirmed significant correlations of BIA measurements with the assessment of visceral fat by CT.
Only a limited number of studies compared different methods of visceral adipose tissue assessment in children and adolescents. Regression analysis conducted in children and adolescents (aged 7–16 yrs) found the waist circumference as the strongest predictor of visceral fat (explains 64.8 % of variability) and BMI as the most reliable predictor of subcutaneous abdominal fat (explains 89.8 % of variability) (43).
BIA instruments used for the assessment of body composition should consider calculation algorithms, which are specific for ethnicity, gender and age. A precision of results provided by BIA instruments is dependent on a similarity of characteristics, as ethnicity, gender and age, between examined and reference populations of both adults (44, 45, 46, 47), and children (30, 31, 43).
Conclusion
A precise measurement of visceral fat stores by sophisticated methods as CT and MRI can not be applied in a routine clinical practice. Until now, particularly the waist circumference has been used as the most reliable and simple anthropometric measure of visceral fat. The bioimpedance instrument Tanita ViScan has recently been developed to measure trunk and visceral fat. Our study conducted in a group of Czech adolescents validated the data on the trunk and visceral fat obtained by ViScan against DEXA and MRI.
Our results indicate that the trunk fat determined by BIA closely reflects the trunk fat measured by DEXA as well as the total abdominal fat determined by MRI. Determination of trunk fat by ViScan could be a useful tool for assessment of abdominal obesity in clinical practice and in epidemiological studies. On the other hand, “visceral fat level“, calculated from BIA, was particularly related to anthropometric parameters as waist circumference, abdominal circumference and SAD. However, further studies in larger groups will be required to evaluate potential advantages of the bioimpedance instrument ViScan over anthropometry in clinical assessment of visceral fat. Our ongoing epidemiological survey in a representative sample of Czech adolescents (COPAT, Childhood Obesity Prevalence And Treatment) would enable us to evaluate a validity of abdominal fat quantification by bioimpedance with regard to the development of metabolic syndrome. In that study a degree of correlation of abdominal fat indexes determined by both anthropometry and ViScan with markers of cardiometabolic health risks will be compared in a cohort which included over 1200 adolescents.
Supported by a grant No. CZ 0123 from Norway through the Norwegian Financial Mechanisms.
Abbreviations
- AFM Abdominal Fat Mass (sum of VF a SF)
- BIA Bioelectrical Impedance Analysis
- BMI Body Mass Index
- COPAT Childhood Obesity Prevalence And Treatment
- CT Computed Tomography
- DEXA Dual Energy X-ray Absorptiometry
- IDF International Diabetes Federation
- L 4/5 lumbar vertebrae 4/5
- MRI Magnetic Resonance Imaging
- SAD Sagittal Abdominal Diameter
- SF Subcutaneous Fat
- TF Trunk Fat
- VF Visceral Fat
Correspondence to:
RNDr. Hana Zamrazilová, Ph.D.
Institute of Endocrinology
Obesity Management Centre
Národní 8
116 94 Prague 1
Czech Republic
e-mail: hzamrazilova@endo.cz
Zdroje
1. Demerath EW, Reed D, Choh AC, et al. Rapid Postnatal Weight Gain and Visceral Adiposity in Adulthood: The Fels Longitudinal Study. Obesity (Silver Spring) 2009; 17: 2060–2066.
2. Virdis A, Ghiadoni L, Masi S, et al. Obesity in the childhood: a link to adult hypertension. Curr Pharm Des 2009; 15: 1063–1071.
3. Ho TF. Cardiovascular risks associated with obesity in children and adolescents. Ann Acad Med Singapore 2009; 38: 48–49.
4. Mamun AA, Hayatbakhsh MR, O’Callaghan M, et al. Early overweight and pubertal maturation-pathways of association with young adults’ overweight: a longitudinal study. Int J Obes (Lond) 2009; 33: 14–20.
5. Bajzová M, Kováčiková M., Vítková M, et al. Vztah inzulínové rezistence a množství viscerálního tuku. Čas Lék čes 2008; 147(7): 376–380.
6. Ball GD, McCargar LJ. Childhood obesity in Canada: a review of prevalence estimates and risk factors for cardiovascular diseases and type 2 diabetes. Can J Appl Physiol 2003; 28: 117–140.
7. Watson S, Blundell HL, Evans WD, et al. Can abdominal bioelectrical impedance refine the determination of visceral fat from waist circumference? Physiol Meas 2009; 30: N53–N58.
8. Oka R, Miura K, Sakurai M, et al. Comparison of waist circumference with body mass index for predicting abdominal adipose tissue. Diabetes Res Clin Pract 2009; 83: 100–105.
9. Ryo M, Nakamura T, Kihara S, et al. Adiponectin as a biomarker of the metabolic syndrome. Circ J 2004; 68: 975–981.
10. Ryo M, Maeda K, Onda T, et al. A new simple method for the measurement of visceral fat accumulation by bioelectrical impedance. Diabetes Care 2005; 28: 451–453.
11. Rankinen T, Kim SY, Pérusse L, et al. The prediction of abdominal visceral fat level from body composition and anthropometry: ROC analysis. Int J Obes Relat Metab Disord 1999; 23: 801–809.
12. Kunešová M, Hainer V, Hergetová H, et al. Simple anthropometric measurements – relation to body fat mass, visceral adipose tissue and risk factors of atherogenesis. Sb Lek 1995; 96(3): 257–267.
13. Demerath EW, Reed D, Rogers N, et al. Visceral adiposity and its anatomical distribution as predictors of the metabolic syndrome and cardiometabolic risk factor levels. Am J Clin Nutr 2008; 88: 1263–1271.
14. Goodpaster BH, Krishnaswami S, Harris TB, et al. Obesity, regional body fat distribution, and the metabolic syndrome in older men and women. Arch Intern Med 2005; 165: 777–783.
15. Kuk JL, Church TS, Blair SN, et al. Does measurement site for visceral and abdominal subcutaneous adipose tissue alter associations with the metabolic syndrome? Diabetes Care 2006; 29: 679–684.
16. Carr D, Utzschneider KM, Hull RL, et al. Intra-abdominal fat is a major determinant of the National Cholesterol Education Program Adult Treatment Panel III criteria for the metabolic syndrome. Diabetes 2004; 53: 2087–2094.
17. Ghandehari H, Le V, Kamal-Bahl S, et al. Abdominal obesity and the spectrum of global cardiometabolic risks in US adults. Int J Obes (Lond) 2009; 33: 239–248.
18. Christian AH, Mochari H, Mosca LJ. Waist circumference, body mass index, and their association with cardiometabolic and global risk. J Cardiometab Syndr 2009; 4; 12–19.
19. Janssen I. Influence of age on the relation between waist circumference and cardiometabolic risk markers. Nutr Metab Cardiovasc Dis 2009; 19: 163–169.
20. Després JP, Lemieux I, Bergeron J, et al. Abdominal obesity and the metabolic syndrome: contribution to global cardiometabolic risk. Arterioscler Thromb Vasc Biol 2008; 28: 1039–1049.
21. Phillips LK, Prins JB. The link between abdominal obesity and the metabolic syndrome. Curr Hypertens Rep 2008; 10: 156–164.
22. Sung RY, Yu CC, Choi KC, et al. Waist circumference and body mass index in Chinese children: cutoff values for predicting cardiovascular risk factors. Int J Obes (Lond) 2007; 3: 550–558.
23. Kim JA, Park HS. Association of abdominal fat distribution and cardiometabolic risk factors among obese Korean adolescents. Diabetes Metab 2008; 34(2): 126–130.
24. Shafer KJ, Siders WA, Johnson LK, et al. Validity of segmental multiple-frequency bioelectrical impedance analysis to estimate body composition of adults across a range of body mass index. Nutrition 2009; 25(1): 25–32.
25. Bunc V. Možnosti stanovení tělesného složení u dětí bioimpedanční metodou. Čas Lék čes 2007; 146(5): 492–496.
26. Fogelholm M, van Marken Lichtenbelt W. Comparison of body composition methods: a literature analysis. Eur J Clin Nutr 1997; 51(8): 495–503.
27. Hainer V, Kunešová M, Pařízková J, et al. Body fat assessment by a new bipedal bioimpedance instrument in normal weight and obese women. Sb Lek 1995; 96(3): 249–256.
28. Všetulová E, Bunc V. Využití bioimpedanční metody pro stanovení procenta tělesného tuku obézních žen. Čas Lék čes 2004; 143(8): 528–532.
29. Větrovská R, Lačňák Z, Haluzíková D, et al. Srovnání různých metod pro stanovení množství tuku v těle u žen s nadváhou a obezitou. Vnitř Lék 2009; 55(5): 455–461.
30. Haroun D, Taylor SJ, Viner RM, et al. Validation of Bioelectrical Impedance Analysis in Adolescents Across Different Ethnic Groups. Obesity (Silver Spring) 2009.
31. Sluyter JD, Schaaf D, Scragg RK, et al. Prediction of fatness by standing 8-electrode bioimpedance: a multiethnic adolescent population. Obesity (Silver Spring) 2010; 18(1): 183–189.
32. http://www.tanitashop.de/media/files_public/cnmmrieeno/AB140 M_D.pdf
33. Chabiniok R, Tintera J. Cardiac MRI data segmentation using the partial differential equation of Allen-Cahn type. Proceedings of the Czech-Japanese Seminar in Applied Mathematics 2006, Faculty of Mathematics, Kyushu University, Fukuoka, Japan.
34. Sato S, Demura S, Kitabayashi T, et al. Segmental body composition assessment for obese Japanese adults by single-frequency bioelectrical impedance analysis with 8-point contact electrodes. J Physiol Anthropol 2007; 26: 533–540.
35. Demura S, Sato S. Prediction of visceral fat area at the umbilicus level using fat mass of the trunk: The validity of bioelectrical impedance analysis. J Sports Sci 2007; 25: 823–833.
36. Pietrobelli A, Rubiano F, St-Onge MP, et al. New bioimpedance analysis system: improved phenotyping with whole-body analysis. Eur J Clin Nutr 2004; 58: 1479–1484.
37. International Diabetes Federation: The IDF consensus worldwide definition of the metabolic syndrome. Available from http://www.idf.org/webdata/docs/Metabolic_syndrome_defini tion.pdf. Accessed 2 September 2005
38. The Examination Committee of Criteria for “Obesity Disease” in Japan, Japan Society for the Study of Obesity: New criteria for “obesity disease” in Japan. Circ J 2002; 66: 987–992.
39. Sampaio LR, Simões EJ, Assis AM, et al. Validity and reliability of the sagittal abdominal diameter as a predictor of visceral abdominal fat. Arq Bras Endocrinol Metabol 2007; 51: 980–986.
40. Zamboni M, Turcato E, Armellini F,et al. Sagittal abdominal diameter as a practical predictor of visceral fat. Int J Obes Relat Metab Disord 1998; 22: 655–660.
41. Bosy-Westphal A, Later W, Hitze B, et al. Accuracy of bioelectrical impedance consumer devices for measurement of body composition in comparison to whole body magnetic resonance imaging and dual X-ray absorptiometry. Obes Facts 2008; 1: 319–324.
42. Nagai M, Komiya H, Mori Y, et al. Development of a new method for estimating visceral fat area with multi-frequency bioelectrical impedance. Tohoku J Exp Med 2008; 214(2): 105–112.
43. Brambilla P, Bedogni G, Moreno LA, et al. Crossvalidation of anthropometry against magnetic resonance imaging for the assessment of visceral and subcutaneous adipose tissue in children. Int J Obes (Lond) 2006; 30: 23–30.
44. Deurenberg-Yap M, Deurenberg P. Is a re-evaluation of WHO body mass index cut-off values needed? The case of Asians in Singapore. Nutr Rev 2003; 61: S80–S87.
45. Sun SS, Chumlea WC, Heymsfield SB, et al. 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 2003; 77: 331–340.
46. Rush EC, Chandu V, Plank LD. Prediction of fat free mass by bioimpedance analysis in migrant Asian Indian men and women: a cross validation study. Int J Obes (Lond) 2006; 30: 1125–1131.
47. Kotani K, Tokunaga K, Fujioka S, et al. Sexual dimorphism of age-related changes in whole body fat distribution in the obese. Int J Obes Relat Metab Disord 1994; 18: 207–212.
Štítky
Addictology Allergology and clinical immunology Anaesthesiology, Resuscitation and Inten Angiology Audiology Clinical biochemistry Dermatology & STDs Paediatric dermatology & STDs Paediatric gastroenterology Paediatric gynaecology Paediatric surgery Paediatric cardiology Paediatric nephrology Paediatric neurology Paediatric clinical oncology Paediatric ENT Paediatric pneumology Paediatric psychiatry Paediatric radiology Paediatric rheumatology Paediatric urologist Diabetology Endocrinology Pharmacy Clinical pharmacology Physiotherapist, university degree Gastroenterology and hepatology Medical genetics Geriatrics Gynaecology and obstetrics Haematology Hygiene and epidemiology Hyperbaric medicine Vascular surgery Chest surgery Plastic surgery Surgery Medical virology Intensive Care Medicine Cardiac surgery Cardiology Clinical speech therapy Clinical microbiology Nephrology Neonatology Neurosurgery Neurology Nuclear medicine Nutritive therapist Obesitology Ophthalmology Clinical oncology Orthodontics Orthopaedics ENT (Otorhinolaryngology) Anatomical pathology Paediatrics Pneumology and ftiseology Burns medicine Medical assessment General practitioner for children and adolescents Orthopaedic prosthetics Clinical psychology Radiodiagnostics Radiotherapy Rehabilitation Reproduction medicine Rheumatology Nurse Sexuology Forensic medical examiner Dental medicine Sports medicine Toxicology Traumatology Trauma surgery Urology Laboratory Home nurse Phoniatrics Pain management Health Care Dental Hygienist Medical studentČlánok vyšiel v časopise
Journal of Czech Physicians
- Advances in the Treatment of Myasthenia Gravis on the Horizon
- Memantine Eases Daily Life for Patients and Caregivers
- What Effect Can Be Expected from Limosilactobacillus reuteri in Mucositis and Peri-Implantitis?
Najčítanejšie v tomto čísle
- A new simple method for estimating trunk and visceral fat by bioelectrical impedance: Comparison with magnetic resonance imaging and dual X-ray absorptiometry in Czech adolescents
- Clinical, biochemical and molecular characteristics in 11 Czech children with tyrosinemia type I
- Shopping as problem: shopping addiction
- Alternative methods of microvolt T wave alternans measurements in patients with left ventricular cardiac dysfunction