BIA impedance analysis software -
The determined BCM is in the upper range of normal and the measurement point in the BIVA nomogram is above the line of normal BCM values. The position of the measurement point in the nomogram provides an indication for the suspected diagnosis of oedema.
For the general differential diagnosis of underweight we present a female patient with anorexia: female, The measurement point in the BIVA nomogram Figure 6 lies almost on the line of normal BCM values long axis and far above the line of normal TBW values short axis outside the 95 th tolerance ellipse.
The position of the measurement point in the upper right quadrant points to the presence of anorexia.
Anorexia as illustrated in the BIVA nomogram. The position of the measurement point in the BIVA nomogram is almost on the line of normal BCM values long axis and far above the line of normal TBW values short axis outside the 95 th tolerance ellipse. The position in the upper right quadrant points to the presence of anorexia.
The BIA parameter values listed in table 5 can be interpreted as follows: Body fat mass is reduced in line with the low BMI. TBW is markedly reduced and BCM also is decreased. With the reduced BCM it needs to be kept in mind here that BCM is dependent on the patient's fluid status TBW.
This means that a lower BCM may also appear reduced due to a lower TBW. This indicates that BCM is normal and that the calculated value was too low only because of the low TBW.
BIVA confirms the suspicion raised by the BIA values that the calculated BCM was too low because of the reduced TBW. Again, the suspected diagnosis of anorexia can be established more efficiently and more reliably by BIVA. Conclusion: The patient exhibits a markedly reduced BMI, decreased body water and a normal BCM in the form of anorexia.
The position of the measurement point in the nomogram in the upper right quadrant outside the 95 th tolerance ellipse provides an indication for the suspected diagnosis of anorexia.
Bioelectrical impedance analysis BIA , particularly in combination with bioelectrical impedance vector analysis BIVA , provides a viable opportunity for evaluating body composition in humans. As the examples suggest the interpretation of BIA results is often complex and a suspected diagnosis can be established more efficiently and more reliably by integrating BIVA into the patient assessment process.
Engelen MP, Schols AM, Baken WC, Wesseling GJ, Wouters EF: Nutritional depletion in relation to respiratory and peripheral skeletal muscle function in out-patients with COPD. Eur Respir J. Article CAS PubMed Google Scholar. Schols AM, Broekhuizen R, Weling-Scheepers CA, Wouters EF: Body composition and mortality in chronic obstructive pulmonary disease.
Am J Clin Nutr. CAS PubMed Google Scholar. Engelen MP, Schols AM, Does JD, Wouters EF: Skeletal muscle weakness is associated with wasting of extremity fat-free mass but not with airflow obstruction in patients with chronic obstructive pulmonary disease.
King DA, Cordova F, Scharf SM: Nutritional aspects of chronic obstructive pulmonary disease. Proc Am Thorac Soc. Article PubMed PubMed Central Google Scholar. Shoup R, Dalsky G, Warner S, Davies M, Connors M, Khan M, Khan F, ZuWallack R: Body composition and health-related quality of life in patients with obstructive airways disease.
Hallin R, Koivisto-Hursti UK, Lindberg E, Janson C: Nutritional status, dietary energy intake and the risk of exacerbations in patients with chronic obstructive pulmonary disease COPD. Respir Med. Article PubMed Google Scholar. Schols AM: Nutrition in chronic obstructive pulmonary disease.
Curr Opin Pulm Med. Soeters PB, Schols AM: Advances in understanding and assessing malnutrition. Curr Opin Clin Nutr Metab Care. Global Initiative for Chronic Obstructive Lung Disease: Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease updated com ].
Vestbo J, Prescott E, Almdal T, Dahl M, Nordestgaard BG, Andersen T, Sørensen TI, Lange P: Body mass, fat-free body mass, and prognosis in patients with chronic obstructive pulmonary disease from a random population sample: findings from the Copenhagen City Heart Study.
Am J Respir Crit Care Med. PubMed Google Scholar. Ischaki E, Papatheodorou G, Gaki E, Papa I, Koulouris N, Loukides S: Body mass and fat-free mass indices in COPD: relation with variables expressing disease severity.
Miller A, Strauss BJ, Mol S, Kyoong A, Holmes PH, Finlay P, Bardin PG, Guy P: Dual-energy X-ray absorptiometry is the method of choice to assess body composition in COPD. Lerario MC, Sachs A, Lazaretti-Castro M, Saraiva LG, Jardim JR: Body composition in patients with chronic obstructive pulmonary disease: which method to use in clinical practice?.
Br J Nutr. Lee SY, Gallagher D: Assessment methods in human body composition. Curr Opin Clin Nutr Metabol Care. Article Google Scholar. Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, Gómez JM, Heitmann BL, Kent-Smith L, Melchior JC, Pirlich M, Scharfetter H, Schols AM, Pichard C: Bioelectrical impedance analysis-part I: review of principles and methods.
Clin Nutr. Matthie JR: Bioimpedance measurements of human body composition: critical analysis and outlook. Expert Rev Med Devices. Mattsson S, Thomas BJ: Development of methods for body composition studies.
Phys Med Biol. Kushner RF: Bioelectrical impedance analysis: a review of principles and applications. J Am Coll Nutr. Kuzma AM, Meli Y, Meldrum C, Jellen P, Butler-Labair M, Koczen-Doyle D, Rising P, Stavrolakes K, Brogan F: Multidisciplinary care of the patient with chronic obstructive pulmonary disease.
The BIA compendium. de ]3. Bosy-Westphal A, Danielzik S, Dörhöfer RP, Piccoli A, Müller MJ: Patterns of bioelectrical impedance vector distribution by body mass index and age: implications for body-composition analysis.
Erratum in: Am J Clin Nutr , Piccoli A: Bioelectric impedance vector distribution in peritoneal dialysis patients with different hydration status. Kidney Int. Dehghan M, Merchant AT: Is bioelectrical impedance accurate for use in large epidemiological studies?.
Nutr J. Barbosa-Silva MC, Barros AJ: Bioelectrical impedance analysis in clinical practice: a new perspective on its use beyond body composition equations. Buchholz AC, Bartok C, Schoeller DA: The validity of bioelectrical impedance models in clinical populations.
Nutr Clin Pract. Bozzetto S, Piccoli A, Montini G: Bioelectrical impedance vector analysis to evaluate relative hydration status.
Pediatr Nephrol. Creutzberg EC, Wouters EF, Mostert R, Weling-Scheepers CA, Schols AM: Efficacy of nutritional supplementation therapy in depleted patients with chronic obstructive pulmonary disease. Download references. Nutritional Consulting Practice, Emil-Schüller-Straße, Koblenz, , Germany.
Pneumology Practice, Emil-Schüller-Straße, Koblenz, , Germany. KG, Binger Straße, Ingelheim, , Germany. Department of Pulmonary Disease, III. Medical Clinic, Johannes Gutenberg-University, Langenbeckstraße, Mainz, , Germany.
You can also search for this author in PubMed Google Scholar. Correspondence to Thomas Glaab. The authors declare that they have no competing interests. TG and MMG were employees of Boehringer Ingelheim at the time of manuscript submission. AWK and TG conceived of the review, drafted and coordinated the manuscript.
MMG and AK critically discussed and helped to draft the manuscript. All authors read and approved the final manuscript. The contents of this original manuscript have not been previously presented or submitted elsewhere. Open Access This article is published under license to BioMed Central Ltd.
Reprints and permissions. Walter-Kroker, A. et al. A practical guide to bioelectrical impedance analysis using the example of chronic obstructive pulmonary disease. Nutr J 10 , 35 Download citation.
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Skip to main content. Search all BMC articles Search. Download PDF. Download ePub. Abstract Bioelectrical impedance analysis BIA is a simple, inexpensive, quick and non-invasive technique for measuring body composition.
Introduction Loss of body weight and depletion of fat free muscle mass are common and serious problems in patients with chronic obstructive pulmonary disease COPD irrespective of the degree of airflow limitation [ 1 — 3 ].
Basic principles Bioelectrical impedance analysis BIA BIA is a method for estimating body composition. From the determined impedance a number of BIA parameters can be estimated [ 20 ]: Body cell mass BCM consists of all cells that have an effect on metabolism e.
extracellular water retention e. extracellular loss of water e. high portion of muscle, water retention e.
Factors impacting BIA results [ 16 , 18 , 20 , 23 , 25 ]: 1. weight and height should be measured directly by the investigator 2. position of the body and limbs supine position, arms abducted at least 30°, legs abducted at approximately 45° 3. consumption of food and beverages no beverages for at least 12 hours previously, fasted state for at least 2 hours 4.
medical conditions and medication that have an impact on the fluid and electrolyte balance; infection and cutaneous disease that may alter the electrical transmission between electrode and skin 6. environmental conditions e. ambient temperature 7.
individual characteristics e. skin temperature, sex, age, race 8. ethnic variation 9. non-adherence of electrodes, use of wrong electrodes, loosening of cable clip, interchanging of electrodes BIA parameters are largely dependent on the patient's hydration status. BIVA bioelectrical impedance vector analysis BIVA as an integrated part of BIA measurement is a simple, quick and clinically valuable method for assessing fluid status TBW and body cell mass BCM.
Figure 1. Full size image. Figure 2. Table 1 Normal finding. Full size table. Figure 3. Table 2 Malnutrition in an obese COPD patient Full size table.
Figure 4. Table 3 Cachexia Full size table. Figure 5. Table 4 Oedema due to right heart failure Full size table. Figure 6. Table 5 Anorexia Full size table. Summary Bioelectrical impedance analysis BIA , particularly in combination with bioelectrical impedance vector analysis BIVA , provides a viable opportunity for evaluating body composition in humans.
Abbreviations ATS: American Thoracic Society BCM: body cell mass BIA: bioelectrical impedance analysis BIVA: bioelectrical impedance vector analysis BMI: body mass index COPD: chronic obstructive pulmonary disease ECM: extra cellular mass ERS: European Respiratory Society FFM: fat free mass FM: fat mass GOLD: Global Initiative for Chronic Obstructive Lung Disease TBW: total body water.
References Engelen MP, Schols AM, Baken WC, Wesseling GJ, Wouters EF: Nutritional depletion in relation to respiratory and peripheral skeletal muscle function in out-patients with COPD. Article CAS PubMed Google Scholar Schols AM, Broekhuizen R, Weling-Scheepers CA, Wouters EF: Body composition and mortality in chronic obstructive pulmonary disease.
CAS PubMed Google Scholar Engelen MP, Schols AM, Does JD, Wouters EF: Skeletal muscle weakness is associated with wasting of extremity fat-free mass but not with airflow obstruction in patients with chronic obstructive pulmonary disease.
CAS PubMed Google Scholar King DA, Cordova F, Scharf SM: Nutritional aspects of chronic obstructive pulmonary disease. Article PubMed PubMed Central Google Scholar Shoup R, Dalsky G, Warner S, Davies M, Connors M, Khan M, Khan F, ZuWallack R: Body composition and health-related quality of life in patients with obstructive airways disease.
Article CAS PubMed Google Scholar Hallin R, Koivisto-Hursti UK, Lindberg E, Janson C: Nutritional status, dietary energy intake and the risk of exacerbations in patients with chronic obstructive pulmonary disease COPD.
Article PubMed Google Scholar Schols AM: Nutrition in chronic obstructive pulmonary disease. Article CAS PubMed Google Scholar Soeters PB, Schols AM: Advances in understanding and assessing malnutrition.
About About the DAPA Measurement Toolkit What's New Other resources Toolkit Team Contact. Introduction Validity Reliability Error and bias Feasibility Data processing Statistical assessment of reliability and validity Harmonisation. Introduction Subjective methods Objective methods Harmonisation Videos Dietary assessment decision matrix.
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Bioelectric impedance analysis. What is assessed? How is the measurement conducted? When is this method used? How are estimates of body composition derived? Populations Further considerations Resources required Instrument library References. Impedance comprises both resistance and reactance: The resistance R reflects the opposition of the tissue to the flow of electrons.
It is related to the amount of water present in tissues. The reactance Xc by contrast reflects the capacitive losses caused by cell membranes. Single-frequency BIA SF-BIA SF-BIA frequency of 50 kHz also known as tetrapolar impedance is the most commonly used BIA instrument, based on 4 contact electrodes 2 injecting and 2 sensing electrodes.
Multi-frequency BIA MF-BIA MF-BIA frequencies up to kHz allows differentiation of intracellular and extracellular components of total body water.
Bioelectrical impedance spectroscopy BIS BIS uses a series of frequencies and it is based on the Cole—Cole plot and Hanai models which characterise the measurement segment with parallel circuits for ECW and ICW, and accounts for a capacitive effect introduced by the non-conducting membrane that separates the ICW and ECW.
Multi-segmental approach The multi-segmental approach which is based on 8 contact electrodes 2 on each hand and foot assumes that the body is made up of a group of cylinders left and right arms, the left and right legs, and the total body are measured and provides body composition values for the trunk and limbs as well as the whole body.
Manufacturers guidelines provide calibration values cut offs. BIA can be performed standing or supine, via hand to foot or arm-leg or foot to foot or leg-leg impedance depending on device. Hand to foot measurements has been shown to be more accurate than foot to foot measurements.
However, foot to foot impedance instruments are more user friendly for those working in the field. Height, weight, gender and physical activity level are typically required by the BIA instruments which then measure the resistance in the majority of BIA devices and reactance for multi-frequency BIA only.
For the ViScan, the participant is supine and the wireless measurement belt is placed directly on the skin at the umbilicus in the sagittal plane.
Participant instructions Reliable BIA requires protocol standardisation and control from the following: Refraining from consuming caffeine tea, coffee and energy drinks and alcohol the day before the test 24 hour prior the test Avoiding vigorous activity 8 hours before testing No eating or drinking within 4 hours of the test No diuretics within 7 days of the test No measurements to be carried out if participant has electrical device such as pacemaker or cochlear implant Shoes, socks, tights to be removed Hands and legs slightly separated from the body If skin is moist or covered with body lotion, clean the area with alcohol wipes.
BIA is a reasonable method to assess and track body composition at population level but not sufficiently accurate to monitor change within an individual due to the error within the measurement. BIA is widely used in clinical medicine, sports medicine and weight reduction programmes.
BIA monitors report a value of resistance R expressed in Ohms Ω. If a multi-frequency device is used, a value of reactance Xc , expressed in Ohms Ω , is also provided. R, or the combination of both R and Xc, are then used in regression equations to estimate body composition together with other population characteristics such as height, weight, gender and activity levels.
Most BIA instruments use in-built manufacturer prediction equations to estimate body composition variables; BIA equations generated by manufacturers are of commercial value and typically not publically available.
The equations are generic and may not be applicable to specific populations. Typically instruments equations are not to be used in children under 7 years of age and in older individuals over 65 years of age.
Numerous prediction equations of varying complexity have been published to derive body composition from BIA. Ideally in a BIA study, it is recommended to develop prediction equations and cross-validate these models against a criterion e.
However, this is not always feasible due to cost and technical constraints; therefore body composition values should be generated from published prediction equations which closely match the study population.
When selecting a BIA prediction equation, ensure they are suitable for the device used foot to foot vs hand to foot and population. Consider the use of multiple BIA equations and then generate the average, which may help control the bias and variation inherent in the measurements.
BIA equations A selection of published BIA equations for predicting FFM, FM, TBW, and ECW, which include description of BIA instruments, the criterion used to validate the equations and standard error of the estimates was published by Kyle et al.
Further information in Wells et al. An overview of the characteristics of BIA is outlined in Table 2. Strengths Non-invasive. Safe to use not recommended for participants with a pacemaker. Can be measured without difficulty in almost any settings. Limited burden to participant.
Limited burden to researcher in terms of collection and analysis. Requires no input by participant and as such no risk of respondent biases. Quick and easy to administer. Easy to use. It can be portable. Relatively inexpensive.
Minimal participant participation required. Estimates of body composition from BIA correlates well with those derived from other methods like DEXA. Multi-frequency BIA may have an added advantage over SF-BIA for evaluating leg skeletal muscle appendicular lean mass.
BIA is a valid and precise method for predicting body composition under controlled conditions in healthy individuals. In normal-weight individuals, BIS can accurately measure TBW and ECW. Percentage body fat by BIS is strongly correlated with a 4C model. High correlations between the limb impedance measured by the segmental BIA system and the appendicular lean soft tissue estimated by DXA in healthy individuals have been observed; therefore, the BIA system is able to derive measurements of this tissue.
Total abdominal fat measured by Viscan is a good predictor of total abdominal adipose tissue measured by MRI in both lean and obese individuals.
Limitations It is based on the assumptions of the 2 component model. As the method relies upon regression equations for estimating body composition variables, BIA is only as good as the equation used.
Validity of BIA is also influenced by body size, gender, age, disease state, race or ethnicity. Measurements are affected by hydration status. Vigorous exercise, excessive caffeine and alcohol use which stimulate urine production possibly leading to dehydration will result in overestimation of fat mass.
The disproportionality of the body in terms of shape, size and composition between limbs and trunk can affect BIA measurements. Poor ability to predict body fat in severely obese individuals as they tend to have higher level of body mass and water accounted by the trunk, the hydration of FFM and the ratio of ECW to ICW are also increased in obesity.
There is a tendency for BIA to overestimate percent body fat in very lean individuals and underestimate body fat in obese participants. Not useful in detecting short term changes after a dietary of physical activity interventions in individuals.
ViScan prediction of visceral fat may be limited, especially in abdominally obese individuals. Table 2 Characteristics of bioelectric impedance analysis. Consideration Comment Number of participants Large Relative cost Low Participant burden Low Researcher burden of data collection Low Researcher burden of coding and data analysis Low Risk of reactivity bias No Risk of recall bias No Risk of social desirability bias No Risk of observer bias No Space required Low Availability High Suitability for field use High Participant literacy required No Cognitively demanding No.
Table 3 Anthropometry by BIA in different populations. Population Comment Pregnancy BIA may not be suitable to estimate fat-free mass FFM and fat mass FM due to the hydration status throughout pregnancy.
BIA predictions will be limited in their ability to account for this variation. However, it has been used to monitor TBW changes. Some manufactures recommend not using their devices during pregnancy. Infancy and lactation There is a large variation in the different body components water, protein, minerals from birth to adulthood due to growth and biological maturation.
This variation can significantly affect the estimate of FM and FFM, in two-compartment models like the BIA method. BIA predictions will be limited to account for these variations.
Lack of valid regression equations to predict body fat make this method not suitable for these populations. Lack of standardisation of electrode placement in infants is also an issue. Toddlers and young children There is large variation in the different body components water, protein, minerals from birth to adulthood due to growth and biological maturation.
There is lack of standardisation of electrode placement in studies. Many of those monitors are not recommended in children below 7 years of age. Adolescents Suitable Adults Suitable Older adults Suitable, but presence of oedema may affect estimates. Ethnic groups Suitable Athletes Suitable but tend to overestimate fatness in lean individuals.
Other obesity Suitable but tendency to underestimate fatness in those individuals. Further considerations. Resources required. Standard operating procedures for data collection. Data entry form in either paper or electronic form. Scale to measure weight some BIA devices can also measure weight.
Stadiometer to measure height. BIA equations. Training of staff. Instrument library. A method specific instrument library is being developed for this section. In the meantime, please refer to the overall instrument library page by clicking here to open in a new page.
Bohm A, Heitmann BL. The use of bioelectrical impedance analysis for body composition in epidemiological studies. Eur J Clin Nutr.
JavaScript seems to Functional training adaptations disabled in anaysis browser. BIA impedance analysis software anqlysis best experience on wnalysis site, be sure to turn on Javascript in your browser. Understanding your measurements. Japanese Technology. Available to all. TANITA BIA technology has been more extensively validated against alternative body composition techniques than any other company and the findings have been published in international medical journals.BIA impedance analysis software -
Moderate exercise before BIA measurements lead to an overestimation of fat-free mass and an underestimation of body fat percentage due to reduced impedance. body fat is significantly underestimated. BIA is considered reasonably accurate for measuring groups, of limited accuracy for tracking body composition in an individual over a period of time, but is not considered sufficiently accurate for recording of single measurements of individuals.
Consumer grade devices for measuring BIA have not been found to be sufficiently accurate for single measurement use, and are better suited for use to measure changes in body composition over time for individuals.
Multiple electrodes, typically eight, may be used located on the hands and feet allowing measurement of the impedance of the individual body segments - arms, legs and torso. The advantage of the multiple electrode devices is that body segments may be measured simultaneously without the need to relocate electrodes.
Results for some impedance instruments tested found poor limits of agreement and in some cases systematic bias in estimation of visceral fat percentage, but good accuracy in the prediction of resting energy expenditure REE when compared with more accurate whole-body magnetic resonance imaging MRI and dual-energy X-ray absorptiometry DXA.
Impedance is frequency sensitive; at low frequency the electric current flows preferentially through extracellular water ECW only while at high frequency the current can cross cell membranes and hence flows through total body water TBW.
In bioimpedance spectroscopy devices BIS resistance at zero and infinite frequency can be estimated and, at least theoretically, should provide the optimal predictors of ECW and TBW and hence body fat-free mass respectively.
In practice, the improvement in accuracy is marginal. The use of multiple frequencies or BIS in specific BIA devices has been shown to have high correlation with DXA when measuring body fat percentage. The electrical properties of tissues have been described since These properties were further described for a wider range of frequencies on a larger range of tissues, including those that were damaged or undergoing change after death.
In , Thomasset conducted the original studies using electrical impedance measurements as an index of total body water TBW , using two subcutaneously inserted needles. In , Hoffer concluded that a whole-body impedance measurement could predict total body water.
The equation the squared value of height divided by impedance measurements of the right half of the body showed a correlation coefficient of 0. This equation, Hoffer proved, is known as the impedance index used in BIA. In , Nyober validated the use of whole body electrical impedance to assess body composition.
By the s the foundations of BIA were established, including those that underpinned the relationships between the impedance and the body water content of the body. A variety of single-frequency BIA analyzers then became commercially available, such as RJL Systems and its first commercialized impedance meter.
In the s, Lukaski, Segal, and other researchers discovered that the use of a single frequency 50 kHz in BIA assumed the human body to be a single cylinder, which created many technical limitations in BIA.
The use of a single frequency was inaccurate for populations that did not have the standard body type. To improve the accuracy of BIA, researchers created empirical equations using empirical data gender, age, ethnicity to predict a user's body composition.
In , Lukaski published empirical equations using the impedance index, body weight, and reactance. In , Kushner and Scholler published empirical equations using the impedance index, body weight, and gender. However, empirical equations were only useful in predicting the average population's body composition and was inaccurate for medical purposes for populations with diseases.
The use of multiple frequencies would also distinguish intracellular and extracellular water. By the s, the market included several multi-frequency analyzers and a couple of BIS devices.
The use of BIA as a bedside method has increased because the equipment is portable and safe, the procedure is simple and noninvasive, and the results are reproducible and rapidly obtained. More recently, segmental BIA has been developed to overcome inconsistencies between resistance R and the body mass of the trunk.
In , an eight-polar stand-on BIA device, InBody , that did not utilize empirical equations was created and was found to "offer accurate estimates of TBW and ECW in women without the need of population-specific formulas.
In , AURA Devices brought the fitness tracker AURA Band with built-in BIA. In BIA became available for Apple Watch users with the accessory AURA Strap with built-in sensors.
The impedance of cellular tissue can be modeled as a resistor representing the extracellular path in parallel with a resistor and capacitor in series representing the intracellular path, the resistance that of intracellular fluid and the capacitor the cell membrane.
This results in a change in impedance versus the frequency used in the measurement. Use profiles to select personalised content. Measure advertising performance. Measure content performance. Understand audiences through statistics or combinations of data from different sources.
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Thank analyais for visiting nature. You are using BIA impedance analysis software browser version with anlaysis support for Fishing Knots for Beginners. To obtain the best Optimize immune health, we recommend impedancd use a more up to date browser BIA impedance analysis software turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Aging and type 2 diabetes T2DM are associated with an increased risk of sarcopenia. Diagnosis of sarcopenia is commonly done using dual-energy X-ray absorptiometry DXA in specialized settings. Another available method for assessing body composition is direct segmental multi-frequency bioelectrical impedance analysis DSMF-BIA. Bioelectrical anqlysis analysis Recovery nutrition for triathletes is Fishing Knots for Beginners method for estimating body impedancrin impedanc body fat and muscle mass, where a weak electric current flows through softwware body and ikpedance voltage Fishing Knots for Beginners measured in order to calculate impedance resistance and Nutrient-rich energy supplement of the body. Most body water is stored in muscle. Therefore, if a person is more muscular there is a high chance that the person will also have more body water, which leads to lower impedance. Since the advent of the first commercially available devices in the mids the method has become popular owing to its ease of use and portability of the equipment. It is familiar in the consumer market as a simple instrument for estimating body fat.
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