Modelo 4C ico

El modelo de 4-Compartimentos es un método GOLD STÁNDAR para valorar la composición corporal bajo muchas condiciones como la supra o infra nutrición, hidratación, obesidad y sarcopenia.


Professor Angelo Pietrobelli
Verona University Medical School.
TMAB Member.

Tanita continúa ofreciendo la estimación más precisa disponible de la MASA GRASA, MASA MAGRA/MUSCULO, y densidad del MINERAL OSEO, pero con la monitorización 4C vamos aún más allá, ofreciendo una incomparable medición de los 4 compartimentos.

Este nuevo método 4C permite entender completamente los niveles de grasa corporal, proteína, densidad del mineral óseo y agua. Y debido a que cada método utilizado es el “gold standard” para esa medición concreta, se garantiza la mayor precisión para cada compartimento.

Método anterior

Validación de composición corporal total y criterio de precisión de chequeo

Método 4C 1

Método mejorado

Validación de composición corporal total y criterio de precisión de chequeo

Método 4C 3

Precisión mejorada del BIA bifrecuencia en las mediciones de cuerpo entero

Se corrigen los errores de los resultados debido a la “anchura del cuerpo” o “edema”.

Método 4C 5
Old Equation
Método 4C 6
New Equation

Resultado de la validación TANITA-BIA 4C

Todos los grupos étnicos (incluidos los datos Asiáticos. "Recomendado por el Prof. Pietrobelli")

Método 4C 7
Old Equation
Método 4C 8
New Equation

Precisión de la Composición Corporal de TANITA-BIA Gráficos de validación


Método 4C 9
Método 4C 10
Método 4C 11
Método 4C 12
Método 4C 13
Método 4C 14

ALGUNOS TRABAJOS PUBLICADOS


Tanita BIA technology: A scientific overview of methods and accuracy.

Tanita BIA technology was first introduced in 1992. Since then we have strived to establish the most accurate technology and will always look for ways and methods to improve accuracy through dedicated research and development.
The Tanita algorithm is the cornerstone of precision body composition measurements in different body types, ages and gender. This has been repeatedly shown in independent scientific publications from researchers and clinicians worldwide.
There are various parameters within the algorithm to ensure the highest accuracy. These include AGE, GENDER and ETHNICITY. By incorporating these parameters, Tanita BIA technology can provide more consistent and reliable body composition measurements for anyone who steps on.
These factors are incorporated into most BIA technology manufacturers within the medical and research fields and has proven to be the foundation of strong validation.
This is shown in scientific publications and highlights the importance of including AGE, GENDER and ETHNICITY when calculating body composition of individuals.
In addition, Tanita has developed algorithms for adults with a higher level of physical activity – athlete mode.
This feature allows higher accuracy of assessing individuals muscle mass.

Recent publications showing the importance of incorporating the different parameters in the scientific literature:

EDAD Y SEXO

The following papers highlight the importance of incorporating age and gender into BIA technology algorithms and the impact on accuracy when they are not included:

• Völgyi E, Tylavsky FA, Lyytikäinen A, Suominen H, Alén M, Cheng S. Assessing body composition with DXA and bioimpedance: effects of obesity, physical activity, and age. Obesity 2008;16(3):700-5.
Conclusion: Compared to DXA, both BIA devices provided on average 2-6% lower values for FM% in normal BMI men, in women in all BMI categories, and in both genders in both HPA and LPA groups.In obese men, the differences were smaller. The two BIA devices provided similar means for groups. Differences between the two BIA devices with increasing FM% were a result of the InBody (720) not including age in their algorithm for estimating body composition.

• Faria SL, Faria OP, Cardeal MD, Ito MK. Validation study of multi-frequency bioelectrical impedance with dual-energy X-ray absorptiometry among obese patients. Obes Surg 2014; 24(9):1476.80.
Conclusion: BIA proved to be a safe alternative for assessing BC in clinically severely obese patients and thus provides a more accessible evaluation tool for this population. But, consideration should be given to the formula added to the BIA measurement, adjusting the values to differences observed in order to reduce errors when compared with the DXA easurements

• Karelis AD, Chamberland G, Aubertin-Leheudre M, Duval C; Ecological mobility in Aging and Parkinson (EMAP) group. Validation of a portable bioelectrical impedance analyzer for the assessment of body composition. Appl Physiol Nutr Metab. 2013 Jan;38(1):27-32.
Conclusion: the present study indicated that the portable Inbody 230 may be an acceptable device to measure fat mass, % body fat, and total FFM (except for women) in healthy adults. In addition, there appears to be a systematic bias for the estimation of trunk and appendicular FFM with the Inbody 230 in men and women.

• Sillanpää E, Cheng S, Häkkinen K, Finni T, Walker S, Pesola A, Ahtiainen J, Stenroth L, Selänne H, Sipilä S. Body composition in 18- to 88-year-old adults--comparison of multifrequency bioimpedance and dual-energy X-ray absorptiometry. Obesity 2014; 22(1):101-9

Authors note: “we also found that age was a significant predictor in all body composition estimates both in women and in men. Although age and sex are often employed in BIA algorithms because of an increase in measurement accuracy”.

ETNIA Y SEXO

The following papers conclude Ethnicity increases accuracy of adult and children’s body composition measurements using BIA technology:

• Nightingale CM, Rudnicka AR, Owen CG, Donin AS, Newton SL, Furness CA, Howard EL, Gillings RD, Wells JC, Cook DG, Whincup PH. 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 assessment of body composition in children study. Plos One 2013; 18, 8(10):e76426.

• Kumar S, Khosravi M, Massart A, Potluri M, Davenport A. The effects of racial differences on body composition and total body water measured by multifrequency bioelectrical impedance analysis influence delivered Kt/V dialysis dosing. Nephron Clin Pract. 2013;124(1-2):60-6.

• Aglago KE, Menchawy IE, Kari KE, Hamdouchi AE, Barkat A, Bengueddour R, Haloui NE, Mokhtar N, Aguenaou H. Development and validation of bioelectrical impedance analysis equations for predicting total body water and fat-free mass in North-African adults. Eur J Clin Nutr 2013; 67(10):1081-6.

• Nightingale CM, Rudnicka AR, Owen CG, Cook DG, Whincup PH. Patterns of body size and adiposity among UK children of South Asian, black African-Caribbean and white European origin: Child Heart And health Study in England (CHASE Study). Int J Epidemiol 2011; 40(1):33–44.

• Haroun D, Taylor SJ, Viner RM, Hayward RS, Darch TS, Eaton J, Cole TJ, WellsJC. Validation of Bioelectrical Impedance Analysis in Adolescents Across Different Ethnic Groups. Obesity 2010; 18(6):1252-59.

• Gibson AL, Holmes JC, Desautels RL, Edmonds LB, Nuudi L Ability of new octapolar bioimpedance spectroscopy analyzers to predict 4-component-model percentage body fat in Hispanic, black, and white adults. Am J Clin Nutr 2008; 87(2):332-8.

• Zhu S, Heymsfield SB, Toyoshima H, Wang Z, Pietrobelli A, Heshka S. Race ethnicity-specific waist circumference cutoffs for identifying cardiovascular disease risk factors. Am J Clin Nutr 2005; 81(2):409–415.

• Deurenberg P, Deurenberg-Yap M, Schouten FJ. Validity of total and segmental impedance measurements for prediction of body composition across ethnic population groups. Eur J Clin Nutr 2002; 56:214–220.

• Jakicic JM, Wing RR, Lang W. Bioelectrical impedance analysis to assess body composition in obese adult women: the effect of ethnicity. Int J Obes 1998; 22:243–249.

• McKeigue PM, Shah B, Marmot MG. Relation of central obesity and insulin resistance with high diabetes prevalence and cardiovascular risk in South Asians. Lancet 1991; 337:382–386.

To summarize the key findings related to ethnicity and gender:

Previous articles have demonstrated a need for ethnic-and gender-specific prediction equations both in adults and in adolescents. Having in the equation control for ethnicity we reduced the underestimation of fat mass in Asian population.

Ethnic differences in the optimal equations for the prediction of FFM from BIA are likely to reflect the marked ethnic differences in body composition in children of different ethnic groups (Deurenberg P, Deuremberg-Yap, 2002).
These include differences in stature, black African-Caribbean children are taller and in particular have greater leg length than white Europeans and South Asians, and lean mass, particularly muscle mass, which tends to be lower among South Asians (Nightngale et al, 2011)
In addition, the amount and distribution of body fat varies appreciably between ethnic groups, with South Asians having a higher proportion of total fat in their abdomen (McKeigue et al 1991), while black African-Caribbeans may have a lower proportion compared to white Europeans (Zhu et al, 2005).

ACTIVIDAD FÍSICA

In addition, Tanita has created Athlete mode to account for differences in muscle mass hydration of standard and more active individuals.

• Verney J, Schwartz C, Amiche S, Pereira B, Thivel D. Comparisons of a Multi-Frequency Bioelectrical Impedance Analysis to the Dual-Energy X-Ray Absorptiometry Scan in Healthy Young Adults Depending on their Physical Activity Level. J Hum Kinet. 2015;14(47):73-80.

• Gába A, Kapuš O, Cuberek R, Botek M. Comparison of multi- and single-frequency bioelectrical impedance analysis with dual-energy X-ray absorptiometry for assessment of body composition in postmenopausal women: effects of body mass index and accelerometerdetermined physical activity. J Hum Nutr Diet. 2015; 28(4):390-400.

COMENTARIOS

Several articles, see references above and also the references in the two articles mentioned (Verney et al, 2015; Gaba et al, 2015) where they underlined the accuracy of BIA depends on level of physical activity. In other words hydration of fat free mass is influenced by physical activity. In light of this, it is fundamental to know physical activity level and having an equation that “control” for physical activity.


SI TE INTERESA...

Contáctanos sin compromiso y te informaremos.

Mientras tanto, puedes bajarte el Catálogo General 2018-2019 haciendo clic sobre la imagen

Catálogo 
			General Tanita 2018