© Borgis - New Medicine 4/2008, s. 89-93
*Petr Kutáč1, Vojtěch Gajda1, Miroslava Přidalová2, Vít Šmajstrla3
Validity of Measuring Body Composition by Means of the BIA Method
1Centre of Human Motion Diagnostics – Department of Physical Education, Pedagogical Faculty of Ostrava University in Ostrava, Czech Republic
Head of Department: Doc. PhDr. Vojtěch Gajda, CSc.
2 Department of Functional Anthropology and Physiology, Faculty of Physical Culture, Palacký University, Olomouc, Czech Republic
Head of Department: Prof. RNDr. Jarmila Riegerová, CSc.
3 Bormed Health Centre (Osteocentre), Ostrava, Czech Republic
Head of Department: MUDr. Vít Šmajstrla
Introduction. Body composition represents a significant diagnostic data item regarding the process of training. It also plays a role when we focus on health-based skills.
Aim. The aim of this study is to verify the validity of measuring body composition by means of the BIA method and to compare the results obtained with the results gained by means of the DEXA method. Two measurement modes (standard and athletic) have been considered.
Materials and methods. The group investigated consisted of 74 individuals (45 males, 29 females). The average age was 20.2 (males) and 19.5 (females). The DEXA method and BIA method were applied to measure body composition. So as to assess the validity of measurements the regression functions model was used. A level of significance α = 0.05 was applied to all statistical tests.
Results. The acquired value of the Pearson correlation was r = 0.753 (females) and r = 0.837 (males – athletic mode) and r = 0.817 (males – standard mode). The value dmax = ± 2 sy/x was found to be ± 4.42% for females, and ± 2.38 for males (athletic mode) and ± 3.40 for males (standard mode), which is an error of objective significance.
Conclusion. The relatively high coefficient of correlation r cannot be considered as a guarantee of accurate measurements. When considering the accuracy of measurements, it is necessary to base the judgment on the value of dmax. It is not possible to combine the applied methods and to compare the acquired results with each other.
Present studies dealing with body composition focus on a representation of particular body fractions  concerning mainly the proportion of the lipoid fraction and the muscular fraction. Factors which have an essential influence on body composition are: motion activity and the choice of physical training. This is why information regarding body composition is considered to be a significant diagnostic item of the training process [2, 3, 4, 5, 6, 7, 8, 9]. The most investigated factor is the value of body fat, as it is known that an extremely high value leads to a decrease in athletic efficiency in many athletic activities.
Body composition represents one of the most important components of health-based abilities, as it relates to nutrition and the state of health of each individual [10, 11, 12, 13]. Data concerning body composition are used in medicine (diabetology, obesitology and osteoporosis diagnostics and treatment) [14, 15, 16, 17].
Various methods are used to estimate the fat fraction in body composition. These methods differ in the demands of professional servicing, organization (amount of time) and financial costs. The most frequently used methods are bioelectrical impedance analysis (BIA) and dual energy X-ray absorptiometry (DEXA). The principle of the BIA method is based on the differing electrical impedance when an electrical current of low intensity is passed through various biological structures, i.e. the principle of the different electrical features of tissues, fat and body water [18, 19]. The DEXA method, which is considered to be the "gold standard”, uses the difference in X-ray absorption when two X-ray beams with differing energy levels are passed through the body. [20, 21, 18]
If the DEXA method is regarded to be more reliable , its results can serve as an empiric criterion for verification of the validity of other methods. Our paper deals with the BIA method. We used the Tanita BC-418 MA device. Although a number of studies have been published in this field, we did not manage to find any comparison of the tetrapolar weight Tanita and the measurement modes (standard and athletic). In those studies other devices are also used (Quadscan, Tanita BIA 101 SC, Tanita TBF-300A). However, these do not enable the measurement mode to be chosen.
The aim of this study is to verify the validity of measuring body composition by means of the BIA Method (Tanita BC-418 MA device) and to compare the results obtained with the results acquired by means of the DEXA method. Two measurement modes (standard and athletic) have been considered.
Materials and methods
The group investigated consisted of 74 university students of Physical Education and Sports at the Pedagogical Faculty of Ostrava University (45 males, 29 females). The average age was 20.2 (males) and 19.5 (females). To find out the body composition by means of the DEXA method, a third generation Denzitometer Holgic QDR was used. Results were also found by means of the BIA method, using the tetrapolar bioimpedance weight Tanita BC-418 MA. All the measurements of a subject were taken on the same day. The data concerning the amount of physical activity of the individual tested were acquired from a record of his/her physical activity over one week. .
To evaluate the validity of the BIA method, we used the modelling of the relationship between the variables investigated by means of various models of regression functions. The independent variables were represented by the Tanita (athletic and standard measurement modes) and the dependant variables by the DEXA method. When verifying the mode of Tanita measurements, we followed the manufacturer´s recommendations, which means that the choice of mode depends on the amount of physical activity (less than 10 hours/week – STANDARD, more than 10 hours/week – ATHLETIC).
The statistical processing was done by means of the statistics program SPSS 16.0. All statistical tests were carried out at a level of significance α = 0.05.
Considering the fact that none of the women exceeded the limit of 10 hours per week of physical activity, we used the Tanita standard mode for comparison with the results of DEXA. Table 1 presents the basic characteristics of measurements of the percentage of fat in the body composition of females.
Table 1. Basic characteristics of measurements – females.
n – frequency, M – mean, SD – standard deviation
A normal distribution is expected in a majority of human organism characteristics. We verified them by Kolmogorov-Smirnov and Shapiro-Wilk tests in both measurements. They did not reject the hypothesis of a normal distribution in the basic group (Physical Education female students).
For an estimation of the regression function we used linear, quadratic, logarithmic and exponential models and their R square is in Table 2. All indices of regression are statistically significant, but the Tanita measurement explains the dispersion of the DEXA measurement of females in normal mode of approximately 60%. None of the chosen regression functions creates significantly better conditions for criterion estimation.
Table 2. R Square of the chosen regression functions – female.
|Linear|| Quadratic ||Logarithmic ||Exponential|
I2xy - R Square
For a better illustration we present the graphical expression of empirical values by chosen models of regression functions (Figure 1).
Fig. 1. Graphs of the selected regression functions of Dexa estimate from the Tanita - mode Standard (females)
If we ask whether there is empirical validity of body composition measured by the Tanita BC 418 MA compared with the DEXA measurement, then we get a Pearson correlation r = 0.753 from the previous results.
Standard error of estimate (Sy/x = SEE) (measured by DEXA) was 2.21%. The value of dmax = ± 2 sy/x was ± 4.42%.
Powyżej zamieściliśmy fragment artykułu, do którego możesz uzyskać pełny dostęp.
Mam kod dostępu
- Aby uzyskać płatny dostęp do pełnej treści powyższego artykułu albo wszystkich artykułów (w zależności od wybranej opcji), należy wprowadzić kod.
- Wprowadzając kod, akceptują Państwo treść Regulaminu oraz potwierdzają zapoznanie się z nim.
- Aby kupić kod proszę skorzystać z jednej z poniższych opcji.
- dostęp do tego artykułu
- dostęp na 7 dni
uzyskany kod musi być wprowadzony na stronie artykułu, do którego został wykupiony
- dostęp do tego i pozostałych ponad 7000 artykułów
- dostęp na 30 dni
- najpopularniejsza opcja
- dostęp do tego i pozostałych ponad 7000 artykułów
- dostęp na 90 dni
- oszczędzasz 28 zł
1. Riegerová J, Přidalová M, Ulbrichová M: Aplikace fyzické antropologie v tělesné výchově a sportu (příručka funkční antropologie). Olomouc, Hanex 2006. 2. Soric M, Misigoj-Durakovic M, Pedisic Z: Dietary Intake and Body Composition of Prepubescent Female Aesthetic Athletes. International Journal of Sport Nutrition & Exercise Metabolism, 2008; 18: 343-354. 3. Fruth J, Morgan A, Darby L, Tobar D: Evaluation of three skinfold equations by using the bod pod as the criterion in Caucasian female athletes. Journal of Exercise Physiology, 2008; 11: 28-37. 4. Williams AG, Wilkinson M: Simple anthropometric and physical performance test to predict maxima box – lifting ability. Journal of Strength & Conditioning Research, 2007; 21: 638-642. 5. Vasques DG, de Fátima da Silva Duarte M, da Silva Lopes A: Brazilian Journal of Kineanthropometry & Human Performance, 2007; 9: 127-133. 6. Rahimi R: Effect of moderate and high intensity weight training on the body composition of overweight men. Facta Universitatis: Series Physical Education & Sport, 2006; 4: 93 - 101 7. Neuymayer G: Physical and Physiological Factors Associated with Success in Professional Alpine Skiing. International Journal of Sports Medicíně, 2003; 24: 571-575. 8. Colombo M: Alpine skiiand body mass. Rigidita di Kultura Spletiva, 2002; 21: 59-63. 9. White AT, Jonson SC: Physiological aspect and injury in elite Alpine skiers. Sports. Med. 1993; 15: 170-178. 10. Lohman T et al.: Relationships among Fitness, Body Composition, and Physical Activity. Medicine & Science in Sports & Exercise, 2008; 40: 1163-1168. 11. Buyukyazi G: The effects of eight-week walking programs of two different intensities on serum lipids and circulating markers of collagen remodelling in humans. Science & Sports, 2008; 23: 162-168. 12. Buffart LM, Van Den Berg-Emons RJG, Van Wijlen-Hempel MS, Stam HJ, Roebroeck ME: Health-related physical fitness of adolescents and young adults with myelomeningocele. European Journal of Applied Physiology, 2008; 103: 181-188. 13. Carrel AL et al.: Measuring aerobic cycling power as an assessment of childhood fitness. Journal of Strength & Conditioning Research, 2007; 21: 685-688. 14. Pravn P et al.: Low Body mass Is an Important Risk Factor for Low Bone Mass and Increased Bone Loss in Early Postmenopausal Women. Journal of Bone and Mineral Research, 1999; 14: 1622-1627. 15. Parikh SJ et al.: The Relationship between Obesity and Serum 1,25 – Dihydroxy Vitamin D Concentrations in Healthy Adults. The Journal of Clinical Endocrinology & Metabolism, 2004; 89: 1196-1199. 16. Misra M et al.: Alterations in Growth Hormone Secretory Dynamics in Adolescent Girls with Anorexia Nervosa and Effects on Bone Metabolism. The Journal of Clinical Endocrinology & Metabolism, 2003; 88: 5615-5623. 17. Plujim SMF et al.: Determinants of Bone Mineral Density in Older Men and Women: Body Composition as Mediator. Journal of Bone and Mineral Research, 2001; 16: 2142-2151. 18. McArdle W D, Katch FI, Katch VL: Exercise Physiology. Energy, Nutrition, & Human Performance. Philadelphia, Lippincott Williams & Wilkins 2007. 19. Heymsfield SB et al.: Human Body Composition. Champaign, IL, Human Kinetics 2005. 20. Stewart AD, Hannan WJ: Prediction of fat and fat-free mass in male athletes using dual X-ray absorptimetry as the reference method. Journal of Sports Science, 2000; 18: 263 – 274. 21. Heyward VH, Wagner DR: Applied body composition assessment. Champaign, IL, Human Kinetics 2004. 22. De Lorenzo A et al.: Body composition measurement in highly trained male athletes: a comparison of three methods. Journal of Sports Medicine & Physical Fitness, 2000; 40: 178-183. 23. Kilduff LP et al.: Reliability and detecting change following short-term creatine supplementation: comparison of two-component body composition methods. Journal of Strength & Conditioning Research, 2007; 21: 378-384. 24. Wilmerding MV, Gibson AL, Mermier CM, Bivins KA: Body composition analysis in dancers: methods and recommendations. Journal of Dance Medicine & Science, 2003; 7: 24 -31. 25. Frömel K, Novosad J, Svozil Z: Pohybová aktivita a sportovní zájmy mládeže. Olomouc, Univerzita Palackého1999. 26. Lohman TG: Advances in Body Composition Assessment. Champaign, IL, Human Kinetice 1992. 27. Norton KI, Craig NP, Withers RT, Whitingham NO: Assessing the body fat of athletes. Australian Journal of Science & Medicine in Sport, 1994; 26: 6-13. 28. Bunc V, Psota R: Physiological profile of very young soccer players. Journal of Sports Medicine & Physical Fitness, 2001; 41: 337-341. 29. Dostálová I, Přidalová M, Kudrna Z: Evaluation of body constitution and body fractions of water polo players. Slovenská antropológia, 2005; 8: 46-49. 30. Bandyopadhyay A: Body Composition, Hematological Profiles and Cardiorespiratory Fitness in Female Swimmers of West Bengal, India. International Journal of Applied Sports Sciences, 2008; 20: 10-21. 31. Clark RR et al.: Minimum Weight Prediction Methods Cross – Validated by the Four-Component Model. Medicine & Science in Sports & Exercise, 2004; 36: 639-647.