Body Bioelectrical Impedance Analysis Research Articles

Evaluation of Change in Body Composition, including Phase Angle, in Post-Myocardial Infarction Patients Rehabilitated under the KOS-Zawał (MC-AMI) Programme.

Background: Ischaemic heart disease, including myocardial infarction, is one of the main causes leading to heart failure as a consequence of ischaemic myocardial damage. In recent years, survival in the acute phase of myocardial infarction has improved significantly, but the high mortality rate within 12 months of hospital discharge (reaching up to 9.8% in Poland) remains a challenge. Therefore, the KOS-Zawał (MC-AMI) comprehensive 12-month post-MI care programme was introduced in Poland in 2017. Aim: This study aimed to assess body composition (including, but not limited to, the phase angle, visceral fat, total body fat, redistribution between intracellular and extracellular fluid in the body, and metabolic age) using a bioelectrical impedance analysis (BIA) in post-MI patients before and after early post-MI rehabilitation who were participating in the KOS-Zawał (MC-AMI) programme. Methods: This study involved an examination (before rehabilitation) of 94 post-myocardial infarction patients who were referred to a cardiology appointment within 7-10 days of hospital discharge, during which a clinical assessment, electrocardiogram, and biochemical blood tests (complete blood count, CRP, and serum creatinine) were performed. For various reasons (death, qualification for device implantation, non-completion of rehabilitation, failure to attend a follow-up BIA), data from 55 patients who were examined twice (before and after rehabilitation) were used for the final analysis. Measurements were taken using a high-grade Tanita MC-780 BIA body composition analyser, which measured the resistance of tissues to a low-intensity electrical impulse (not perceptible to the subject). Results: Participation in rehabilitation as part of the KOS-Zawał (MC-AMI) programme was associated with a decrease in metabolic age in patients, with a reduction in visceral fat levels and levels of adipose tissue in the lower and upper limbs. Moreover, a clinically beneficial reduction in the ratio of extracellular water to total body water was also observed. These changes were statistically significant (p < 0.005). In contrast, there were no statistically significant differences in the change in phase angle values in the subjects before and after the 5-week post-infarction rehabilitation. Conclusions: Participation in early post-myocardial infarction rehabilitation as part of the KOS-Zawał (MC-AMI) programme (25 training sessions) is associated with significant improvements in body composition parameters, such as visceral adipose tissue, limb fat, and water redistribution, and, consequently, a reduction in metabolic age, despite no significant increase in phase angle values. It was hypothesised that the good baseline condition of the subjects might explain the lack of significant change in the phase angle over the short observation period. For further analysis, it would be worthwhile to increase the number of patients with baseline reduced phase angle values and monitor changes in this parameter throughout rehabilitation and the entire MC-AMI programme, because changes in the phase angle may also be influenced by other programme components such as dietary or psychological education. It is worth considering implementing a regular BIA assessment in patients in the programme as a motivating stimulus for diligent exercise and extending rehabilitation to be followed by telerehabilitation or hybrid telerehabilitation.

#5115 8-ZONE LUNG ULTRASOUND AND BIOIMPEDANCE ANALYSIS FOR ASSESSMENT OF HYDRATION STATUS IN HEMODIALYSIS: A PROSPECTIVE SINGLE CENTRE EXPERIENCE

Abstract Background and Aims Chronic volume overload is a major contributor to cardiovascular mortality in patients receiving maintenance hemodialysis (HD). Hence, accurately assessing volume status in this population is crucial. Bioelectrical impedance analysis (BIA) is a validated, non-invasive, and straightforward bedside technique that estimates total body water (TBW), extracellular water (ECW), intracellular water (ICW), and over hydration (OH). However, it is not suitable for use in patients with limb amputation or metallic medical devices. On the other hand, lung ultrasound (LUS) is used to evaluate extravascular lung water (EVLW) and has been shown to predict all-cause mortality and cardiac events in HD patients. Although a 28-zone LUS is the reference standard for LUS studies, recent studies have shown that an 8-zone LUS protocol can be as accurate. The aim of this study was to compare the performance of an 8-zone LUS protocol with bioelectrical impedance analysis to evaluate hydration status in an outpatient haemodialysis unit. Method Adult patients under thrice-weekly 4h HD sessions using high-flux membrane dialyzers for at least 1 month were prospectively enrolled between June and August 2022. We excluded patients with systemic infections, advanced neoplasia, metallic medical devices, decompensated cirrhosis, and limb amputations. The dry weight (DW) was established by the attending nephrologist, blind to the results. All measurements were performed in the first session of the week. BIA was assessed before HD using a portable whole body BIA device (BCM—Fresenius Medical Care D GmbH) and the OH was normalized to ECW. LUS using 8-zone protocol was performed before and after HD, with patients in the near-to-supine or supine position using a 2–5 MHz convex probe (Acuson X150®, Siemens, Germany), and the total number of B lines was recorded. Results A total of 37 patients with median age of 60 (IQR 15) years, 75% males, 65% with residual diuresis &amp;gt;300 mL/24 h were included. The median HD vintage was 9 (IQR 10) months, and median body mass index (BMI) of 22.7 (IQR 9) Kg/m2. At the beginning of HD, the median systolic blood pressure (BP) was 140 (IQR 24) mmHg and the median diastolic BP was 79 (IQR 16) mmHg. The median interdialytic weight gain was 4.2% (IQR 2.8) and median ultrafiltration (UF) was 2600 (IQR 1300) mL. The BIA showed median TBW of 38.2 (IQR 11) L, ECW 18.2 (IQR 7.73) L, ICW 20.8 (IQR 6.55) L, and normalized OH 0.138 (IQR 0.147). There was a positive correlation between BMI, TBW (r = 0.375, p = 0.045), and ECW (r = 0.486, p = 0.006), but not with ICW (r = 0.061, p = 0.755), nor normalized OH (r = 0.14, p = 0.468). Systolic BP, but not diastolic, was correlated with the water volume measured in both compartments (ECW: r = 0.498, p = 0.005; ICW: r = 0.421, p = 0.023, TBW: r = 0.423, p = 0.022). The 8-zone LUS showed a statistically significative (p&amp;lt;0.001) reduction in the number of B lines between pre and post HD evaluation (16.5 (IQR 17.25) lines to 8.5 (IQR 10.25) lines). Total evaluation time was under 8 minutes. When comparing LUS before HD with BIA assessment we found that the number of B lines correlated with the normalized OH (r = 0.454, p = 0.018), ECW (r = 0.501, p = 0.007), TBW (r = 0.418, p = 0.030), but not ICW (r = 0.239, p = 0.23). The total number of B lines post HD was also correlated with the ECW (r = 0.568, p = 0.002), TBW (r = 0.465, p = 0.017), and normalized OH (r = 0.408, p = 0.039). Conclusion The 8-zone LUS protocol provides a quick and efficient way to evaluate patients prior to HD sessions. Our study reveals a strong correlation between the total number of B lines determined by the 8-zone protocol and BIA parameters such as TBW, ECW, and normalized OH. This demonstrates that the 8-zone protocol can effectively be used in routine evaluations of HD patients. Although these techniques reflect different over-fluid compartments, they have a complementary role for fluid overload determination and dry weight guidance.

Comparison of body fat percentage assessments by bioelectrical impedance analysis, anthropometrical prediction equations, and dual-energy X-ray absorptiometry in older women.

Individuals with high body fat have a higher risk of mortality. Numerous anthropometric-based predictive equations are available for body composition assessments; furthermore, bioelectrical impedance analysis (BIA) estimates are available. However, in older adults, the validity of body fat estimates requires further investigation. To assess the agreement between percentage body fat (BF%) estimates by BIA and five predictive equations based on anthropometric characteristics using dual X-ray absorptiometry (DXA) as reference method. A secondary objective was to identify whether excluding short-stature women improves the agreement of BF% estimates in a group of community-dwelling, older Mexican women. A concordance analysis of BF% was performed. A total of 121 older women participated in the study. Anthropometric information, BIA, and DXA body composition estimates were obtained. Five equations using anthropometric data were evaluated in order to determine body fat percentage (BF%) using DXA as reference method. Paired t-test comparisons and standard error of estimates (SEE) were obtained. The Bland-Altman plot with 95% limits of agreement and the concordance correlation coefficient (CCC) were used to evaluate the BF% prediction equations and BIA estimates. The mean age of the study participants was 73.7 (±5.8) years old. BIA and the anthropometric based equations examined showed mean significant differences when tested in the entire sample. For the taller women (height > 145 cm), no significant difference in the paired comparison was found between DXA and BIA of BF% estimates. The mean BF% was 40.3 (±4.8) and 40.7 (±6.2) for DXA and BIA, respectively. The concordance between methods was good (CCC 0.814), (SEE 2.62). Also, in the taller women subset, the Woolcott equation using waist-to-height ratio presented no significant difference in the paired comparison; however, the error of the estimates was high (SEE 3.37) and the concordance was moderate (CCC 0.693). This study found that BIA yielded good results in the estimation of BF% among women with heights over 145 cm. Also, in this group, the Woolcott predictive equation based on waist circumference and height ratio showed no significant differences compared to DXA in the paired comparison; however, the large error of estimates observed may limit its application. In older women, short stature may impact the validity of the body fat percentage estimates of anthropometric-based predictive equations.

Influence of Upper-Extremity and Lower-Extremity Resistance Exercise on Segmental Body Composition and Body Fluid Estimates.

Rodriguez, C, Florez, CM, Prather, J, Zaragoza, J, Tinnin, M, Brennan, KL, Taylor, L, and Tinsley, GM. Influence of upper-extremity and lower-extremity resistance exercise on segmental body composition and body fluid estimates. J Strength Cond Res 37(5): 1042-1051, 2023-The purpose of this analysis was to determine if acute, localized resistance exercise (RE) artificially influences total and regional estimates of body composition from dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA). Recreationally active male ( n = 14) and female ( n = 18) subjects completed 3 testing visits: rest (R), upper-extremity RE (U), and lower-extremity RE (L). Dual-energy X-ray absorptiometry scans were completed before exercise and 60 minutes after exercise. Bioelectrical impedance analysis was completed immediately before and after exercise and at 15, 30, and 60 minutes after exercise. Subjects were not allowed to intake fluid during the exercise session or during the postexercise assessment period. The effects of the acute RE session on DXA and BIA estimates were analyzed using linear mixed-effects models with a random intercept for subject. Condition by time interactions were observed for most BIA outcomes. Relative to the reference model (i.e., R condition at baseline), total body water and fat-free mass estimates were, on average, approximately 1 and approximately 1.2 kg higher, in the U condition. In contrast, lower-extremity RE exerted little or no impact on most BIA variables. Some DXA estimates exhibited time main effects, but the magnitude of changes was negligible. An acute bout of localized RE, particularly upper-extremity RE, can artificially influence BIA body fluid and composition estimates, whereas DXA may be robust to the acute biological error introduced by RE. Although body composition assessments should ideally be conducted under standardized conditions, DXA may be suitable in less standardized situations. In addition, BIA is differentially influenced by upper-extremity and lower-extremity resistance exercise.

Body Muscle Mass Metabolic Data Analysis in Association with Crohn’s Disease Activity

Abstract Malnutrition is a common complication of Crohn’s disease (CD) patients and it is correlated with alterations of the body composition and disease activity. Our prospective pilot study included hospitalised CD patients, age ≥ 18 years. Patients were assessed using the Nutritional Risk Score (NRS2002), the Malnutrition Universal Screening Tool (MUST), and body bioelectrical impedance analysis. Twenty-three hospitalised patients (median age 36.5, interquartile range (IQR): 28.5–51.5 years) were enrolled; the median CD activity index was 128 (IQR = 6.0–207.0). The study group comprised 48% (n = 11) patients with low CD activity and 52% (n = 12) with high disease activity. According to NRS2002 and MUST, 70% (n = 16) CD patients had malnutrition risk and were in need of nutritional support. The median BMI was lower for the CD group (21.10 [IQR = 19.2–23.3]) than for the control group (23.4 [IQR = 21.5–25.8]) (p = 0.014). In terms of deviation from standard weight, 39% (n = 9) of CD patients showed reduced % body fat. Reduced muscle mass was observed in 48% (n = 11) of CD patients. CD patients with high disease activity had a noticeably increased risk of malnutrition. Identification of the reduction in soft lean muscle mass in CD patients can be used as an anticipatory indicator of disease activity.

A Pilot Study Examining Body Composition Classification Differences Between Body Mass Index and Bioelectrical Impedance Analysis in Children With High Levels of Physical Activity.

Background: Body mass index (BMI) is frequently labeled as “flawed” in assessing obesity since it cannot differentiate between muscle and fat leading to misclassifications of healthy individuals. Bioelectrical impedance analysis (BIA) may be a more accurate indicator of obesity since it can distinguish the difference between muscle and fat in children. This pilot study investigated discrepancies between BMI and BIA body composition classifications in children with high levels of physical activity.Methods: Participants were selected from three elementary schools (N = 380, K = 76, 1st = 64, 2nd = 62, 3rd = 61, 4th = 83, and 5th = 34) receiving 60 min of outdoor, unstructured play daily. BIA scales were used to collect each child's body fat percentage and BMI score, then those numbers were categorized by BIA and BMI normative values as either underweight, healthy, overweight, or obese.Results: Overall, 26% of the students were classified differently when using the normative classifications for BMI and BIA, with the largest discrepancy found in the overweight category at 38%. Similar inconsistencies were found when students were divided as younger (42%) vs older students (36%), and males (40%) vs. females (35%).Conclusions: This pilot study demonstrated that there is a significant difference in how BMI and BIA discriminate between the different body composition categories. BIA consistently shows to be a more accurate tool in assessing obesity rates in children since it directly measures body fat.

A comparison of non-invasive methods of measuring body composition in patients with heart failure: a report from SICA-HF.

BackgroundCachexia is common in patients with chronic heart failure and is associated with poor prognosis. How best to measure body composition is not clear.Methods and resultsWe characterized body composition in 120 patients with chronic heart failure: mean (SD) age 70 (10) years, left ventricular ejection fraction 44 (10) %, and median (Q1–Q3) N‐terminal pro B‐type natriuretic peptide 845 (355–1368) ng/L. We measured body composition using dual‐energy X‐ray absorptiometry (DEXA) and a multi‐frequency bioelectrical impedance analysis (BIA) device (Tanita BIA MC‐180MA). Mean (SD) fat mass (FM) was 27.2 (11.7) kg by BIA and 32.3 (12.2) kg by DEXA (mean difference −5.1 kg, 95% limits of agreement: −11.7, 1.5; 4% of values outside limit of agreement); mean (SD) lean mass (LM) was 56.6 (10.9) kg by BIA and 51.1 (9.9) kg by DEXA (mean difference 5.5 kg, 95% limits of agreement: −1.3, 12.3; 6% of values outside limit of agreement); and mean (SD) bone mass (BM) was 3.0 (0.5) kg by BIA and 2.8 (0.6) kg by DEXA (mean difference 0.2 kg, 95% limits of agreement: −0.5, 0.8; 5% of values outside limit of agreement). There was a close correlation between DEXA and BIA for both LM and FM (LM: r = 0.95, P < 0.001; FM: r = 0.96, P < 0.001) but less so for BM (r = 0.84, P < 0.001). Both DEXA and BIA body composition measurements correlated well with other measures of body size (body mass index, hip circumference, and waist circumference).ConclusionsThere are differences in the measurements of FM, LM, and BM between the two techniques, which should not be used interchangeably.

Effect of position and exercise on measurement of muscle quantity and quality: towards a standardised pragmatic protocol for clinical practice

BackgroundUltrasonography is an emerging non-invasive bedside tool for muscle quantity/quality assessment; Bioelectrical Impedance Analysis (BIA) is an alternative non-invasive bedside measure of body composition, recommended for evaluation of sarcopenia in clinical practice. We set out to assess impact of position and exercise upon measures towards protocol standardisation.MethodsHealthy volunteers aged 18–35 were recruited. Bilateral Anterior Thigh Thickness (BATT; rectus femoris and vastus intermedius), BATT: Subcutaneous Ratio (BATT:SCR), and rectus femoris echogenicity were measured using ultrasound and BIA was performed; 1) lying with upper body at 45° (Reclined), 2) lying fully supine at 180o (Supine), 3) sat in a chair with upper body at 90o (Sitting), and 4) after exercise Reclined. Variability of Skeletal Muscle Mass (SMM) by two different equations from BIA (SMM-Janssen, SMM-Sergi), phase angle, fat percentage, and total body (TBW), extracellular (ECW), and intracellular water (ICW) were assessed.ResultsForty-four participants (52% female; mean 25.7 years-old (SD 5.0)) were recruited. BATT increased from Reclined to Sitting (+ 1.45 cm, 1.27–1.63), and after exercise (+ 0.51, 0.29–0.73). Echogenicity reduced from Reclined to Sitting (− 2.1, − 3.9 – -0.26). SMM-Sergi declined from Reclined to Supine (− 0.65 kg, − 1.08 – − 0.23) and after exercise (− 0.70 kg, − 1.27 – -0.14). ECW increased from Reclined to Sitting (+ 1.19 L, 0.04–2.35). There were no other statistically significant changes.ConclusionStandardisation of protocols is especially important for assessment of muscle quantity by ultrasonography; BIA measurements may also vary dependent on the equations used. Where possible, participants should be rested prior to muscle ultrasonography and BIA, and flexion of the knees should be avoided.

The role of body muscle mass as an indicator of activity in inflammatory bowel disease patients

Malnutrition is an objective disease activity parameter for patients with inflammatory bowel disease (IBD), particularly Crohn's Disease (CD), and is an indicator of lesion expansion or inflammatory activity. Active disease is correlated with the systemic response of the body's immune system, activating a hypermetabolic state and protein degradation (Argiles JM, 2015). These conditions lead to malnutrition, which significantly increases the risk of impaired clinical outcomes, such as delayed recovery or increased mortality (Landi F, 2019). Our aim was to identify malnutrition parameters associated with more pronounced metabolic status changes in IBD patients (i.e., classified as by low and high clinical activity) as an indicator of disease activity. This prospective pilot study included hospitalised patients aged ≥18 years, with an established diagnosis of IBD, with no medical history of surgical interventions. IBD patients were divided into those with low clinical activity indexes (CD activity index [CDAI] <150 for CD and Mayo <4 for ulcerative colitis [UC]) and those with high clinical activity indexes (CDAI >150 for CD and Mayo >4 for UC). Patients were assessed twice using the Nutritional Risk Score (NRS2002) and Malnutrition Universal Screening Tool (MUST) and 48 body bioelectrical impedance analysis (BIA) measurements were taken. A control group consisting of heathy age- and sex-matched individuals was used for comparison. Fifty hospitalised patients (median age, 36.5 IQR: 28.5-51.5 years) were enrolled, of which 44% (n=21) were female and 56% (n=27) were male. Of these, 48% (n=23) patients were diagnosed with CD and 52% (n=25) with UC. The median CDAI was 128 (IQR=6.0-207.0) and Mayo score was >4 (IQR=1.0-8.0). The study group comprised 48% (n=23) patients with low IBD activity and 52% (n=25) of patients with high IBD activity. According to the NRS2002, 31% (n=15) patients were nutritionally at risk and in need of nutritional support and an additional 24% (n=12) had low-risk requiring observation, without necessity for additional nutritional care. According to the MUST score, 40% (n=19) of patients had a high-risk of malnutrition requiring a nutritional care plan and 19% (n=9) were of low-risk. Overall, 31% (n=17) of patients received enteral oral feeding and 10% (n=4) required additional parenteral feeding. The group with low IBD activity showed a considerably lower score on both screening tools (NRS2002 p=0.007; MUST p<0.001). Comparing BIA results between IBD patients and the control group, the median BMI was lower for the CD (21.10 [IQR=19.2-23.3]) than for the control group (23.4 [IQR=21.5-25.8]) (p=0.014). In addition, visceral fat mass was lower in CD (-4,00 [IQR=-12.1 to 5.6]) than in the control group (7.85 [IQR=-0.9-18.2]) (p=0.003). In terms of deviation from standard weight, 39% (n=9) of CD patients showed reduced %body fat, while this was observed in only 19% (n=5) of UC patients. Reduced muscle mass was observed in 48% (n=11) of CD patients and in 19% (n=4) of UC patients, while only 13% (n=6) of all IBD patients had reduced BMI. IBD patients with high disease activity indices had a noticeably increased risk for malnutrition (according to NRS2002 scores), taking into consideration not only IBD activity, but also increased weight loss and loss of appetite. Most CD patients in both the low and high disease activity groups had reduction in muscle mass, which was not evaluated in UC patients. Identification of the reduction in soft lean muscle mass in CD patients can be used as an anticipatory indicator of disease activity.

A Field-based Three-Compartment Model Derived from Ultrasonography and Bioimpedance for Estimating Body Composition Changes.

The purpose of this study was to assess the agreement between a field-based three-compartment (3CFIELD) model and a laboratory-based three-compartment (3CLAB) model for tracking body composition changes over time. Resistance-trained males completed a supervised nutrition and resistance training intervention. Before and after the intervention, assessments were performed via air displacement plethysmography (ADP), bioimpedance spectroscopy (BIS), portable ultrasonography (US), and bioelectrical impedance analysis (BIA). ADP body density and BIS body water were used within the reference 3CLAB model, whereas US-derived body density and BIA body water were used within the 3CFIELD model. Two-compartment model body composition estimates provided by US and BIA were also examined. Changes in fat-free mass and fat mass were analyzed using repeated-measures ANOVA, equivalence testing, Bland-Altman analysis, linear regression, and related validity analyses. Significant increases in fat-free mass (3CLAB, 4.0 ± 4.5 kg; 3CFIELD, 3.9 ± 4.2 kg; US, 3.2 ± 4.3 kg; BIA, 3.9 ± 4.2 kg) and fat mass (3CLAB, 1.3 ± 2.2 kg; 3CFIELD, 1.4 ± 2.2 kg; US, 2.1 ± 2.6 kg; BIA, 1.4 ± 2.9 kg) were detected by all methods. However, only the 3CFIELD model demonstrated equivalence with the 3CLAB model. In addition, the 3CFIELD model exhibited superior performance to US and BIA individually, as indicated by the total error (3CFIELD, 1.0 kg; US, 1.8 kg; BIA, 1.6 kg), 95% limits of agreement (3CFIELD, ±2.1 kg; US, ±3.3 kg; BIA, ±3.1 kg), correlation coefficients (3CFIELD, 0.79-0.82; US, 0.49-0.55; BIA, 0.61-0.72), and additional metrics. The present study demonstrated the potential usefulness of a 3CFIELD model incorporating US and BIA data for tracking body composition changes over time, as well as its superiority to US or BIA individually. As such, this accessible multicompartment model may be suitable for implementation in field or limited-resource settings.

Physiological And Anthropometric Predictors Of Discrepancies Between Bioelectrical Impedance Analysis And Dual-energy X-ray Absorptiometry

Assessment methods such as dual-energy x-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA) are commonly used to determine molecular-level body composition estimates in both healthy and clinical populations. Though discrepancies in body composition estimates between BIA and DXA have been previously reported, virtually no investigations have explored potential predictor variables that may explain the disagreement between these methods. PURPOSE: To explore the physiological and anthropometric predictors of discrepancies between DXA and BIA total body composition estimates. METHODS: During a single visit, 103 female participants (Mean ± SD; 33.4 ± 15.9 years; 65.6 ± 12.1 kg; 165.5 ± 6.3 cm; 32.2 ± 7.4 DXA body fat percentage [BF%]) and 76 male participants (33.8 ± 14.5 years; 83.9 ± 15.1 kg; 178.8 ± 6.6 cm; 22.9 ± 8.0 DXA BF%) underwent body composition assessment via DXA and 8-point single-frequency BIA. Potential predictors of the discrepancies between DXA and BIA body composition estimates were obtained during the same visit using air displacement plethysmography, bioimpedance spectroscopy, and 3-dimensional optical scanning. Select DXA variables were also utilized as predictors. Ordinary least squares regression was conducted to predict the differences in total fat mass (FM) and total lean soft tissue (LST) between DXA and BIA. Standardized model coefficients (β), p-values for coefficients, and R2 values were generated. RESULTS: For FM estimates, significant predictors (p ≤ 0.01) of the differences between DXA and BIA were hydration of LST (TBW:LST; β = -0.82), height (β = -0.78), percentage of TBW as extracellular fluid (%ECF; β = -0.36), and the male sex (β = 0.26). For LST, significant predictors of the errors between DXA and BIA were TBW:LST (β = 0.85), height (β = 0.77), %ECF (β = 0.40), the male sex (β = -0.22), and racial identification as Black (β = -0.09). The R2 values for regression models predicting differences between DXA and BIA were 0.80 to 0.86 for FM and 0.73 to 0.87 for LST. CONCLUSION: Hydration variables and height are primary predictors of discrepancies between DXA and BIA total body composition estimates.

Body Composition Assessment in Male and Female Bodybuilders: A 4-Compartment Model Comparison of Dual-Energy X-Ray Absorptiometry and Impedance-Based Devices.

Graybeal, AJ, Moore, ML, Cruz, MR, and Tinsley, GM. Body composition assessment in male and female bodybuilders: a 4-compartment model comparison of dual-energy x-ray absorptiometry and impedance-based devices. J Strength Cond Res 34(6): 1676-1689, 2020-The purpose of this study was to examine the group and individual accuracy of body composition estimates obtained from multicompartment models, dual-energy x-ray absorptiometry (DXA), and several impedance-based devices in male and female bodybuilders. Twenty-seven male (n = 17; 4-compartment [4C] model fat-free mass index [FFMI]: 25.1 ± 1.8 kg·m; 4C body fat: 11.8 ± 4.4%) and female (n = 10; 4C FFMI: 18.3 ± 1.4 kg·m; 4C body fat: 19.7 ± 4.9%) bodybuilders underwent duplicate assessments using DXA, bioimpedance spectroscopy (BIS), electrical impedance myography (EIM), and 3 bioelectrical impedance analysis (BIA) devices. In addition to utilizing standard output, multicompartment models were generated. For each method, body fat %, FFM, and fat mass were compared with the reference 4C model for the evaluation of group and individual errors. The 3-compartment model with a BIS body water estimate produced the lowest standard error of the estimate, total error (TE), and 95% limits of agreement (LOA) for all variables, although some alternative methods had lower constant error (CE). In general, multicompartment models with BIS or multifrequency BIA body water estimates produced more accurate body composition estimates than single assessment techniques (i.e., DXA, BIS, EIM, and BIA). Single assessment techniques produced low CE and TE for some body composition variables. However, proportional bias was observed for DXA and BIS. All single assessment techniques produced LOA large enough to make the utility of these methods questionable in individual athletes. Appropriate caution should be used when interpreting and utilizing body composition estimates in muscular physique athletes, particularly at the individual level.

Explaining Discrepancies Between Total and Segmental DXA and BIA Body Composition Estimates Using Bayesian Regression

Introduction/Background: Few investigations have sought to explain discrepancies between dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA) body composition estimates. The purpose of this analysis was to explore physiological and anthropometric predictors of discrepancies between DXA and BIA total and segmental body composition estimates. Methodology: Assessments via DXA (GE Lunar Prodigy) and single-frequency BIA (RJL Systems Quantum V) were performed in 179 adults (103 F, 76 M, age: 33.6 ± 15.3 yr; BMI: 24.9 ± 4.3 kg/m2). Potential predictor variables for differences between DXA and BIA total and segmental fat mass (FM) and lean soft tissue (LST) estimates were obtained from demographics and laboratory techniques, including DXA, BIA, bioimpedance spectroscopy, air displacement plethysmography, and 3-dimensional optical scanning. To determine meaningful predictors, Bayesian robust regression models were fit using a t-distribution and regularized hierarchical shrinkage “horseshoe” prior. Standardized model coefficients (β) were generated, and leave-one-out cross validation was used to assess model predictive performance. Results: LST hydration (i.e., total body water:LST) was a predictor of discrepancies in all FM and LST variables (|β|: 0.20–0.82). Additionally, extracellular fluid percentage was a predictor for nearly all outcomes (|β|: 0.19–0.40). Height influenced the agreement between whole-body estimates (|β|: 0.74–0.77), while the mass, length, and composition of body segments were predictors for segmental LST estimates (|β|: 0.23–3.04). Predictors of segmental FM errors were less consistent. Select sex-, race-, or age-based differences between methods were observed. The accuracy of whole-body models was superior to segmental models (leave-one-out cross-validation-adjusted R2 of 0.83–0.85 for FMTOTAL and LSTTOTAL vs. 0.20–0.76 for segmental estimates). For segmental models, predictive performance decreased in the order of: appendicular lean soft tissue, LSTLEGS, LSTTRUNK and FMLEGS, FMARMS, FMTRUNK, and LSTARMS. Conclusions: These findings indicate the importance of LST hydration, extracellular fluid content, and height for explaining discrepancies between DXA and BIA body composition estimates. These general findings and quantitative interpretation based on the presented data allow for a better understanding of sources of error between 2 popular segmental body composition techniques and facilitate interpretation of estimates from these technologies.

The accuracy of commercially available upper and lower body bioelectrical impedance analyzers in men and women

Objective: The purpose of this study was to determine if upper body (UB) and lower body (LB) bioelectrical impedance analysis (BIA) devices yield similar estimates of BF% as whole body (WB) BIA. Approach: Ninety-four men and women had their body composition evaluated using a Baseline 12-1190 Body Fat Scale (Fabrication Enterprises Inc.) as the LB BIA device, an Omron HBF-306C Handheld Body Fat Loss Monitor (Omron Healthcare, Inc.) as the UB BIA device, and a Seca Medical Body Composition Analyzer 514 (Seca North America) as the WB BIA device as well as via air displacement plethysmography (ADP; BodPod; Life Measurement Inc.). Main results: in women, the BF% was greater for WB BIA compared to UB BIA and LB BIA (28.9 ± 5.0 versus 23.8 ± 4.4 versus 20.4 ± 5.9%; p < 0.001) with no differences between the WB BIA and ADP BF% (28.9 ± 5.0 versus 28.3 ± 7.5%; p = 0.982). In men, BF% was greater for WB BIA compared to UB BIA and LB BIA (19.1 ± 6.7 versus 15.5 ± 5.3 versus 14.9 ± 4.0; p < 0.001) with no differences between the WB BIA and ADP BF% (19.1 ± 6.7 versus 17.6 ± 7.8; p = 0.394). Significance: Our findings suggest that the UB and LB BIA devices used in this study underestimate BF% compared to a WB BIA device and ADP in men and women.

Role of Bioelectrical Impedance Analysis in the Evaluation of Patients with Upper Limb Lymphedema.

Background: Monofrequency bioelectrical impedance analysis (BIA) protocols seek to further quantify changes in lymphedema compared with traditional circumferential evaluations. Complex decongestive therapy (CDT) is an effective method of reducing unilateral upper limb lymphedema secondary to breast cancer treatments. Comparing lymphedema measurements between segmental tetrapolar BIA, total body BIA, and circumferential measurements during therapeutic changes can improve our quantitative assessment ability for this prevalent medical complication. Methods and Results: Twenty-two patients with breast-cancer-related unilateral upper limb lymphedema participated in this prospective observational study. Circumferential measurements, segmental tetrapolar BIA, and total body BIA were obtained and compared before CDT, immediately after 10 sessions of CDT, and 30 days post-CDT to assess lymphedema. The segmental tetrapolar BIA correlated well with improvements in circumferential measurements of the limb. We found that the resistance value cutoff point of 237 Ω could indicate a recurrence of lymphedema. Conclusions: Segmental, tetrapolar monofrequency BIA provides a simple method to monitor and evaluate the efficacy of therapy in the outpatient setting by operators with minimal training. This protocol could aid quantitative evaluations of unilateral upper limb lymphedema.

Leg electrical resistance predicts venous blood viscosity and hematocrit.

We previously reported that whole body bioelectrical impedance analysis (BIA) measurements are correlated to some hemorheologic factors, suggesting a relationship between viscosity factors and electric properties of flowing blood not only in vitro but also in vivo. Recently we reported that with segmental BIA (analyzing the body considered as composed of 5 cylinders) predictive equations for various determinants of blood viscosity were closer than for the wole body. Another widely used BIA technique uses leg-to-leg impedance measurements so that two cylinders (the two legs) are analyzed. We investigated whether impedance measured with this technique (Tanita TBF-300) is also a predictor of blood viscosity factors. From viscometric measurements performed on venous blood drawn in recreative athletes over the range of shear rates 1 to 6000 s-1 (RHEOMETRE Anton Paar CP 50-1), we found a correlation between leg-leg resistance at 50 kHz (Rx[50 kHz]) and blood viscosity at 1000 s-1 (η1000= 0.0051 Rx[50 kHz] + 1.3265; r = 0.521 p = 0.028 yielding a prediction of η1000 (Bland Altman plot: bias 0.05 [RANGE - 0.24; 0.34]. Neither plasma viscosity nor the red cell rheology index «k» of Quemada's model are correlated with Rx[50 kHz], but hematocrit (Hct) does (Hct (%) = 0.0217 Rx[50 kHz] + 33.783; r = 0.480 p = 0.044) yielding a prediction of Hct (Bland Altman plot: bias - 0.11, [range - 1.67; 1.45]. The discrepancy between actual and predicted Hct is also correlated with resistance at 50 kHz (r = 0.575 p = 0.031) as does the discrepancy between actual and predicted Hct/viscosity ratio (r = -0.651 p = 0.006). Therefore, as other previously studied methods, leg to leg BIA predicts viscosity, suggesting that blood rheology may influence the passage of an electric current in the legs.

Effect of a Precompetition and Postcompetition Training Regime on Body Composition of Soccer Players

The purpose of this investigation was to document the body composition elements’ changes, preparing an initialprecompetition and postcompetition training programme of soccer players. Body composition measurements weretaken 10 weeks prior to competition, at 2 hours before competition and 4 weeks after competition period (week 14).There were investigated: body height (BH), body mass (BM), body mass index (BMI), body fat mass (BFM), fat freebody mass (FFBM), fat free body mass index (FFBMI), body water mass (BWM), water free body mass (WFBM), waterfree body mass index (WFBMI). Body mass, the percent age of BFM and BWM at all body mass was calculated usingthe whole body bioelectrical impedance analysis (BIA) with “Tanita” monitor (Japan).Body mass and body composition values of soccer players varied at precompetition, competition and postcompetitionperiods. The decreased body mass at competition period by 8.16% is the result of lost body fat mass and body watermass. Fat free body mass index (FFBMI) and water free body mass index (WFBMI) indicate, that soccer players atprecompetition and competition period did not use lean tissue, that positively related to the restoration of bodycomposition and water balance at postcompetition period.Keywords: body composition, body mass, body fat mass, body water mass.

Impact of Acute Dietary Manipulations on DXA and BIA Body Composition Estimates.

To examine the effects of acute preassessment diets on body composition estimates obtained by dual-energy x-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA). In a counterbalanced design, 48 males and females were provided with two 1-d diets: high-carbohydrate diet (9 g CHO·kg) and very low-carbohydrate diet (1 to 1.5 g CHO·kg). For each condition, body composition was assessed in the morning after an overnight fast, in the afternoon after feeding, and the following morning after a second overnight fast. Acute food ingestion, regardless of macronutrient content, altered DXA and BIA body composition estimates, and both sexes responded similarly. DXA total and regional lean soft tissue estimates increased up to 1.7% and 3% on average in response to feeding, with individual increases of over 4.5% and 9%. DXA total and trunk fat mass estimates decreased by up to 3% on average. All DXA-derived measures of body composition returned to baseline values after the second overnight fast. Impedance measured by BIA decreased by 4.4% in response to feeding, leading to a 2% increase in total body water and fat-free mass, with individual increases up to 4.5%. BIA fat mass estimates decreased 1.4% to 2.4%, with individual decreases of up to 10%. Unlike DXA, most BIA-derived estimates did not return to baseline values after a second overnight fast. Acute food and fluid intake can artificially influence body composition estimates, regardless of macronutrient content. An overnight fast is likely sufficient preassessment dietary control for DXA and possibly sufficient for BIA.

Role of bioelectric impedance phase angle in ovarian malignancy: A hospital-based study

Background: A woman's risk at birth of having ovarian cancer at some point in her lifetime is 1-1.5% and mortality due to the disease is almost 0.5%. It accounts for 3% of all cancers in females. Despite a low contributory percentage, it remains the fifth leading cause of cancer related death. This is because most ovarian cancers are detected when they have spread beyond the ovary. Bioelectric Impedance Analysis (BIA) affords an emerging opportunity to assess prognosis because of its ability to non invasively assess cell and plasma membrane structure and function by means of phase angle. Aims: To compare the Phase Angle between patients of Ovarian Cancer and their matched control with the help of BIA. Settings and Design: After taking clearance from ethical committee a total of 33 female cases of histological proven serous cyst adenocarcinoma were included from the surgery in Patient Department, Department of surgery. Equal numbers of matched controls were recruited from the friends and relatives of cases. Subjects and Methods: BIA BODY STAT QUAD SCAN 4000 was used to measure resistance (R) and reactance (Xc) by recording a voltage drop in applied current. Phase angle is the ratio of reactance to resistance and is a measure of cell vitality. Statistical Analysis Used: Unpaired t-test and One Way ANOVA were applied. Results: In control group Phase angle showed a mean ± SEM 5.073 (0.0698) while in test group it showed a mean value ± SEM 3.536 (0.0616). Mean of stage I was 3.800 (0.1154) while that of stage II was 3.620 (0.2588). Means of stage III and IV are 3.275 (0.158) and 2.90 (0.141) respectively. One Way ANOVA was applied to see any significant differences among the phase angle values of all stages. The results were statistically significant. The smaller the phase angle values higher was the Malignant Tumours (TNM) staging. Conclusions: The phase angles differed significantly from the healthy age matched control values and also among the stages. This study demonstrated that phase angle is a strong predictor of severity and prognosis of ovarian cancer and differed significantly between the groups. Further studies are required to validate its role as a screening and prognostic tool.

Bioelectrical impedance analysis in the assessment of pre-eclampsia.

Aim of this prospective investigation was to assess pre-eclampsia by bioelectrical impedance analysis (BIA). A total of 22 pre-eclamptic as well as matched (patients' age, gestational age, parity, gravidity) healthy pregnant women underwent whole body BIA on admission and then, pre-eclamptic patients, every 2days until childbirth. For all measured BIA single values and their corresponding reference value mean, standard deviation, minimum and maximum were calculated to compare pre-eclamptic women with corresponding reference values. Furthermore a paired t test and an ANOVA of repeated measurements were performed to detect differences of intraindividual measurements. Subsequently an analysis of variance was accomplished to analyse general changes in the course of time of investigated patients, who were measured more than once. Except for the phase angle, BIA parameters of pre-eclamptic women compared to corresponding reference values were significantly different, suggesting an increase of total body water in pre-eclampsia. Repeated measurements did not reveal statistically significant intra- or interindividual differences in the course of time. Bioelectrical impedance analysis allows differentiating healthy from pre-eclamptic women. Further investigations are needed to analyse if BIA is capable to serve as a prognostic diagnostic tool in the detection of deterioration of pre-eclampsia.