The principle of BIA is that the different tissues in the body will act as conductors, semiconductors, or dielectrics insulators.

Lean tissues are highly-conductive, as they contain large quantities of water. In contrast, bone and adipose tissue are dielectric substances and are poor conductors [4].

BIA assumes that the human body is composed of a series of cylinders, uniform in shape, length, cross-sectional area, and with constant conductivity. Total body water TBW is estimated, and this estimation is used to calculate fat-free mass. Fat mass is then calculated as the difference between fat-free mass and body mass.

Several methods have been used to assess body composition in humans, each with advantages and drawbacks surrounding cost, validity, reliability , and accessibility. It is unclear how many frequencies would be needed for a BIA device to be considered a BIS device, however, the principles behind how the devices work are the same.

Therefore, for this review, BIA will be used to denote all bioelectrical impedance assessments. Hand-held BIA Different types of BIA analysers are available, such as hand-held and leg-to-leg devices. Hand-held BIA machines assess the conductance of a small alternating current through the upper body and use built-in software to calculate body composition after it has been calibrated with the following variables: weight, height, age, and gender [6].

This method may be of benefit in a field setting, due to its convenience. Leg-to-Leg BIA Similar to hand-held methods, leg-to-leg BIA involves an individual standing on scales with four electrodes situated at each footplate, with a low-level current passed through the lower body.

The path of the electrical current may differ between this method and the hand-held method, and could potentially influence body composition results; though this issue is discussed later in the article.

Hand-to-Foot BIA Hand-to-foot BIA uses electrodes in a mounted footplate, as well as electrodes in hand grips, to determine whole-body measurements. As hand-held and leg-to-leg methods may not account for the resistance of the lower- or upper body, respectively, it is logical to assume that hand-to-foot measurements may better reflect whole-body composition than the alternatives.

Estimates of body composition using BIA are facilitated using empirically validated equations, which consider variables including gender, race, height, weight, and age. Consequently, it is important the correct equation is used for the population measured to ensure that any results are valid.

It is also important to understand the reference assessment method used to validate these equations. For example, many BIA equations are validated against assessment methods such as hydrostatic weighing and Dual-energy X-ray Absorptiometry DEXA.

From the results of this assessment method, the manufacturer constructs an equation using the individual variables mentioned previously to determine what the body fat would be.

These equations will have an error rate when compared to the hydrostatic weighing method, and thus, this error is multiplied by the original error of the reference method to provide a body composition assessment that may be somewhat distant from the actual values reported using a four-compartment model.

The validity the agreement between the true value and a measurement value of body composition is key to determining the precision of BIA measurement, and its suitability for clinical use.

The criterion method for determining body composition is the four-compartment model 1] fat mass, 2] total body water, 3] bone mineral mass, and 4] residual mass , and should be used when assessing the validity of BIA measurements. BIA has been compared to the four-compartment model in several studies using various populations.

Sun et al. It is important to note that this analysis utilised DEXA as the reference method, which may also lead to further error, as eluded to earlier in this review read my article on the use of DEXA scanning for body composition assessment HERE.

The validity of BIA for one-off measures of body composition Despite studies showing promising effects of BIA on body composition , this has not been found in a large body of research.

BIA has been shown to underestimate fat mass and overestimate fat-free mass by 1. This finding is supported by other research on bodybuilders, showing that BIA underestimated fat mass, and overestimated fat-free mass when compared to the four-compartment model [10].

Research conducted by Jebb et al. The authors subsequently developed a novel prediction equation to estimate fat mass from the same Tanita bioimpedance analyser, with the four-compartment method as a reference.

However, later research found that this equation also failed to outperform the Tanita manufacturer equation, and resulted in wide limits of agreement [12]. Potentially of greater concern to practitioners considering the use of BIA to determine body composition in the applied setting, are the individual error rates of BIA, rather than data on group means.

The study mentioned previously on obese subjects [9] reported that in 12 of the 50 participants, BIA underestimated fat mass by 5 kg or more. This is supported by the findings of Van Marken Lichtenbelt et al. This suggests that BIA may provide data that is not sufficiently accurate for the determination of individual body composition.

The validity of using BIA to measure changes over time A further consideration for the use of BIA is the validity of its use in measuring changes in fat mass and fat-free mass over time, as this may indicate the efficacy of a nutritional or training intervention looking to manipulate body composition.

To revisit the study by Ritz et al. Fat mass was underestimated by 1. Individual error rates were greater than at baseline, with BIA underestimating fat mass by 7.

A further study on obese populations [13] showed individual disagreement in body fat measurement between BIA and the four-compartment model was high. Individual measures of body fat ranged from There are a limited amount of comparisons between BIA and the reference four-compartment model in athletic populations.

There is disagreement amongst the limited research available, with only one study suggesting that BIA is suitable for assessing body composition in athletes [15], whereas other research suggests that body fat estimates are much higher in athletes when using the BIA method [16]. The discrepancies between the studies may be due to various issues including differences in methodology, equations, and athletic population.

There are currently no BIA equations for athletes that have been derived from the criterion four-compartment method fat mass, total body water, bone mineral mass, residual mass. This makes the application of BIA in this population difficult, as athletes are likely to possess substantially different quantities of fat and fat-free mass when compared to the general population or diseased populations that current equations are based on.

The reliability of BIA The reliability of BIA the reproducibility of the observed value when the measurement is repeated is also important to determine single-measurement precision, as well as the ability to track changes over time. A plethora of research has indicated the importance — and potentially the inability — of standardising BIA measures to sufficiently account for various confounders.

The mean coefficient of variation for within-day, intra-individual measurements, has ranged from 0. Standard measurement conditions may vary depending on the machine type e. hand-to-hand, leg-to-leg, supine vs. standing, etc. Other factors which may impact the BIA measurement and should therefore also be standardised are [16]:.

The standardisation of hydration status is clearly of importance for BIA, as the method is reliant on estimations of total body water to ascertain fat-free mass. For female athletes, difference in hydration status during menses may significantly alter impedance [17] and should be a consideration when assessing female athletes with BIA.

Saunders et al. hyperhydrated or hypohydrated , indicating that even small changes in fluid balance that occur with endurance training may be interpreted as a change in body fat content.

In addition, eating and strenuous exercise hours prior to assessment have also previously been shown to decrease impedance; ultimately affecting the accuracy of the measurement [19].

The need to standardise eating, exercise, and both acute and chronic hydration changes are clearly important to provide valid body composition estimations. As mentioned previously, there are several issues with BIA measurement that may limit its use in an applied setting.

Methodological limitations of BIA may affect the ability of the method to accurately determine body composition. The primary issues with BIA are:. Sensor Placement One such limitation is the placement of the sensors, and their ability to give readings of total body composition. As electrical current follows the path of least resistance, some scales may send current through the lower body only, missing the upper body entirely.

Similarly, hand-held instruments may only assess the body composition of the upper extremities. As females typically have a higher proportion of adipose tissue in the gluteal-femoral region [20], it is possible that this would not be represented using hand-held BIA devices.

Hand-to-foot BIA devices, however, may allow for greater accuracy, as the current is sent from the upper body to the lower body, and is less likely to be influenced by the distribution of body fat. Hydration and Glycogen Levels Regardless, all devices are still subject to the same limitations that other BIA devices are.

Deurenberg et al. They speculated that changes in glycogen stores, and the loss of water bound to glycogen molecules, may affect BIA estimates of fat-free mass. In athletic populations, where varying glycogen stores are likely throughout a training week, it is likely that this will lead to some variation in the detection of change in fat-free mass in athletes as glycogen is likely to be affected by both diet, as well as the intensity, duration, and modality of previous training sessions — even with protocol standardisation.

Effect of incorrect measures in the applied setting An important consideration when assessing the individual variation of BIA is the potential consequences that an incorrect reading can have.

This can have wide-ranging implications, from assessing the efficacy of previous dietary and training interventions to making decisions on the correct interventions moving forward. For example, an athlete may be singled out for interventions to reduce their body fat based on their BIA assessment and normative values, yet other methods may suggest that their body composition is optimal.

The primary area for future research in this area is clearly the need for validated BIA equations for athletes in a range of sports and with varying body composition. It is important that these equations are validated using a total-body, water-based, four-compartment method, in an attempt to minimise the measurement error that is found when equations are based on the two-compartment model; such as hydrostatic weighing.

As such, the following areas of research are needed to expand current knowledge on this topic:. To conclude, it is likely that BIA is not a suitable body composition assessment method for athletic populations. The lack of a validated equation for this population, combined with the large individual error reported in overweight and obese populations, suggests that BIA does not provide accurate body composition data for both single-measure and repeated measures.

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Bioelectrical Impedance Analysis BIA Bioelectrical Impedance Analysis BIA can estimate body composition e. Contents of Article Summary What is Bioelectrical Impedance Analysis? Types of Bioelectrical Impedance Analysis What are the Bioelectrical Impedance Analysis equations?

Is Bioelectrical Impedance Analysis valid and reliable? Are there issues with Bioelectrical Impedance Analysis? Is future research needed with Bioelectrical Impedance Analysis? Conclusion References About the Author. Figure 1.

The difference in bioelectrical conductivity between muscle and fat. References Buccholz, C. Bartok and D. Franssen, E. Rutten, M.

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Management group of the BIA International Database: AMS, LCW, ESC, AB-W, SBH, HL, LBS, JCW, EM. Present address: Section for general Practice, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.

Exercise and Health Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, , Lisbon, Portugal. Department of Biomedical Science, University of Padova, , Padova, Italy. Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria, Monserrato, , Cagliari, Italy.

Skeletal Muscle Assessment Laboratory, Physical Education Department, School of Technology and Science, São Paulo State University, Presidente Prudente, , Brazil. Department for Life Quality Studies, University of Bologna, , Rimini, Italy.

Research Center of Kinanthropometry and Human Performance, Sports Center, Universidade Federal de Santa Catarina, Florianópolis, Brazil. Growth and Development Laboratory, Center for Investigation in Pediatrics CIPED , School of Medical Sciences, University of Campinas UNICAMP , Campinas, , Brazil.

Ezequiel M. Gonçalves, Raquel D. Laboratory of Kinanthropometry and Human Performance, School of Physical Education and Sport of Ribeirão Preto, University of São Paulo, , São Paulo, Brazil.

Faculty of Health and Sport Sciences, University of Tsukuba, Ibaraki, , Japan. National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, , Japan. Yokohama Sports Medical Center, Yokohama Sport Association, Kanagawa, , Japan.

Postgraduate Program in Nutrition and Food, Federal University of Pelotas, Pelotas, Brazil. Nutrition Department, Federal University of Pelotas, , Pelotas, Brazil.

Nutrition Institute, State University of Rio de Janeiro, , Rio de Janeiro, Brazil. Centre of Excellence for Nutrition, North-West University, Potchefstroom, , South Africa. School of Population Health, University of New South Wales, The George Institute for Global Health, Sydney, NSW, Australia.

Hospital General de México, Dr. Eduardo Liceaga, Ciudad de México, Mexico. National Institute of Physical Education of Catalonia INEFC , University of Barcelona UB , Barcelona, Spain. School of Health Sciences, TecnoCampus, Pompeu Fabra University, Barcelona, Spain.

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Department of Physical and Health Education, Faculty of Educational Sciences, Al-Ahliyya Amman University, Al-Salt, Jordan. Department of Expertise and Advocacy, Action contre la Faim, , Montreuil, France.

Department of Medicine DIMED , Geriatrics Division, University of Padova, Padova, , Italy. School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD, , Australia. Research Unit for Dietary Studies, The Parker Institute, Frederiksberg and Bispebjerg Hospital, Copenhagen, Denmark.

Department of Physical Education, Research Group in Physical Activity and Health, Federal University of Rio Grande do Norte, Natal, Brazil.

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All authors contributed to the drafting and editing of the manuscript and to construction of the BIA International database. Correspondence to Analiza M. Springer Nature or its licensor e. a society or other partner holds exclusive rights to this article under a publishing agreement with the author s or other rightsholder s ; author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

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nature european journal of clinical nutrition articles article. Subjects Biomarkers Scientific community. Abstract Background Bioelectrical impedance analysis BIA is a technique widely used for estimating body composition and health-related parameters.

Methods The Exercise and Health Laboratory of the Faculty of Human Kinetics, University of Lisbon has agreed to host the database using an online portal.

Conclusion The BIA International Database represents a key resource for research on body composition. Access through your institution. Buy or subscribe. Change institution. Learn more. References Aleman-Mateo H, Rush E, Esparza-Romero J, Ferriolli E, Ramirez-Zea M, Bour A.

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Acknowledgements Faculdade Motricidade Humana-Universidade de Lisboa kindly hosted the BIA database in the website for which we are thankful.