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Developing and Validating an Age-Independent Equation Using Multi-Frequency Bioelectrical Impedance Analysis for Estimation of Appendicular Skeletal Muscle Mass and Establishing a Cutoff for Sarcopenia.

ABSTRACT: Background: Appendicular skeletal muscle (or lean) mass (ALM) estimated using dual-energy X-ray absorptiometry (DXA) is considered to be a preferred method for sarcopenia studies. However, DXA is expensive, has limited portability, and requires radiation exposure. Bioelectrical impedance analysis (BIA) is inexpensive, easy to use, and portable; thus BIA might be useful in sarcopenia investigations. However, a large variety of models have been commercially supplied by different companies, and for most consumer products, the equations estimating ALM are not disclosed. It is therefore difficult to use these equations for research purposes. In particular, the BIA equation is often age-dependent, which leads to fundamental difficulty in examining age-related ALM loss. The aims of the current study were as follows: (1) to develop and validate an equation to estimate ALM using multi-frequency BIA (MF-BIA) based on theoretical models, and (2) to establish sarcopenia cutoff values using the equation for the Japanese population. Methods: We measured height (Ht), weight, and ALM obtained using DXA and a standing-posture 8-electrode MF-BIA (5, 50, 250 kHz) in 756 Japanese individuals aged 18 to 86-years-old (222 men and 301 women as developing equation group and 97 men and 136 women as a cross validation group). The traditional impedance index (Ht²/Z50) and impedance ratio of high and low frequency (Z250/Z₅) of hand to foot values were calculated. Multiple regression analyses were conducted with ALM as dependent variable in men and women separately. Results: We created the following equations: ALM = (0.6947 × (Ht²/Z50)) + (-55.24 × (Z250/Z₅)) + (-10,940 × (1/Z50)) + 51.33 for men, and ALM = (0.6144 × (Ht²/Z50)) + (-36.61 × (Z250/Z₅)) + (-9332 × (1/Z50)) + 37.91 for women. Additionally, we conducted measurements in 1624 men and 1368 women aged 18 to 40 years to establish sarcopenia cutoff values in the Japanese population. The mean values minus 2 standard deviations of the skeletal muscle mass index (ALM/Ht²) in these participants were 6.8 and 5.7 kg/m² in men and women, respectively. Conclusion: The current study established and validated a theoretical and age-independent equation using MF-BIA to estimate ALM and provided reasonable sarcopenia cutoff values.

SUBMITTER: Yamada Y

PROVIDER: S-EPMC5551247 | biostudies-other | 2017 Jul

REPOSITORIES: biostudies-other

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Project description:BACKGROUND:The loss of muscle mass, known as sarcopenia, is a natural process of aging that is associated with adverse health outcomes regardless of age. Because cancer is a disease of aging, interest in sarcopenia and its potential impact in multiple cancer populations has increased significantly. Bioelectrical impedance analysis (BIA) is a guideline-accepted method for sarcopenia detection. This systematic review assesses the literature pertaining to BIA use in the detection of sarcopenia in adults with cancer. MATERIALS AND METHODS:In this systematic review, a search of the literature for randomized controlled trials and observational studies was conducted using MEDLINE, Cochrane CENTRAL, and EMBASE, through July 15, 2019. The study is registered at Prospero (CRD 42019130707). For study inclusion, patients had to be aged 18 years or older and diagnosed with solid or hematological neoplasia, and BIA had to be used to detect sarcopenia. RESULTS:Through our search strategy, 5,045 articles were identified, of which 24 studies were selected for inclusion in the review (total number of 3,607 patients). In five studies, BIA was rated comparable to axial computed tomography (CT) scan, calf circumference, or grip strength for sarcopenia screening. In 14 studies, BIA-identified sarcopenia was associated with adverse clinical outcomes. CONCLUSION:BIA is an accurate method for detecting sarcopenia in adults with cancer prior to treatment and is a viable alternative to CT, dual-energy x-ray absorptiometry, and magnetic resonance imaging in oncology clinical practice. IMPLICATIONS FOR PRACTICE:Bioelectrical impedance analysis (BIA) is an attractive method for identifying sarcopenic patients in clinical practice because it provides an affordable, noninvasive test that can be completed within a few minutes during a clinic visit. BIA does not require highly skilled personnel, and results are immediately available. This systematic review summarizes the literature pertaining to BIA assessment of sarcopenia in adults with cancer, with a focus on its use in diverse cancer populations.

Project description:BackgroundThe present study refers to an anthropometric model, Dahlmann-Body-Analysis (DBA), based on formerly developed weight-height-frame tables. Including the anthropometric variable abdomen circumference (AC), a further differentiation into muscularity and fat mass could be realized. This enables to calculate the individual percentage fat mass (%FM), providing a cost-effective method for epidemiological studies. The present work sets out to investigate, whether %FM computed by the DBA model compares to BIA measurements, notably under conditions of heavy obesity.Subjects/methodsIn 103 adults (37 males, 66 females, age 42.5 ± 12.5 years, BMI 38.2 ± 4.8 kg/m²) %FM was estimated by a tetrapolar BIA device and compared to results derived by the DBA system. Bland-Altman and simple linear regression analyses were used to determine agreement between methods.ResultsThe mean %FM estimates of men (women) ± standard deviation were 36.1 ± 4.8 (49.7 ± 4.5) for BIA and 36.7 ± 4.2 (49.1 ± 4.9) for DBA measurements. Pearson correlation coefficients (r) and Lin's concordance correlation coefficient (CCC) were r = 0.86 and CCC = 0.84 for men and r = 0.85 and CCC = 0.83 for women, respectively. Bland-Altman plot showed limits of agreement between DBA and BIA %FM that ranged from 5.5% to -4.3% for men and 4.6% to- 5.7% for women, respectively. Correlations between values measured by both methods were high and the observed confidence interval (SD of the difference between DBA and BIA result multiplied by 2) was low. No systematic error was found. The DBA system overestimates FM by 0.63 ± 4.98 (2SD) % for men and underestimates FM by -0.56 ± 5.28 (2SD) % for women, respectively, compared to the BIA results. The result for both genders is -0.066 ± 5.17 (2SD) %FM. Over all, there is a strong concordance and reproducibility between the DBA and BIA data sets.ConclusionsThe implementation of the abdomen circumference (AC) into the DBA model as a proxy for body fat (%FM) resulted in a strong concordance with BIA measurements. These findings indicate that the DBA model may reflect the body shape of severely obese white European patients with regard to body composition.

Project description:Background: Patients with chronic kidney disease (CKD) are vulnerable to loss of muscle mass due to several metabolic alterations derived from the uremic syndrome. Reference methods for body composition evaluation are usually unfeasible in clinical settings. Aims: To evaluate the accuracy of predictive equations based on bioelectrical impedance analyses (BIA) and anthropometry parameters for estimating fat free mass (FFM) and appendicular FFM (AFFM), compared to dual energy X-ray absorptiometry (DXA), in CKD patients. Methods: We performed a longitudinal study with patients in non-dialysis-dependent, hemodialysis, peritoneal dialysis and kidney transplant treatment. FFM and AFFM were evaluated by DXA, BIA (Sergi, Kyle, Janssen and MacDonald equations) and anthropometry (Hume, Lee, Tian, and Noori equations). Low muscle mass was diagnosed by DXA analysis. Intra-class correlation coefficient (ICC), Bland-Altman graphic and multiple regression analysis were used to evaluate equation accuracy, linear regression analysis to evaluate bias, and ROC curve analysis and kappa for reproducibility. Results: In total sample and in each CKD group, the predictive equation with the best accuracy was AFFMSergi (men, n = 137: ICC = 0.91, 95% CI = 0.79-0.96, bias = 1.11 kg; women, n = 129: ICC = 0.94, 95% CI = 0.92-0.96, bias = -0.28 kg). AFFMSergi also presented the best performance for low muscle mass diagnosis (men, kappa = 0.68, AUC = 0.83; women, kappa = 0.65, AUC = 0.85). Bias between AFFMSergi and AFFMDXA was mainly affected by total body water and fat mass. None of the predictive equations was able to accurately predict changes in AFFM and FFM, with all ICC lower than 0.5. Conclusion: The predictive equation with the best performance to asses muscle mass in CKD patients was AFFMSergi, including evaluation of low muscle mass diagnosis. However, assessment of changes in body composition was biased, mainly due to variations in fluid status together with adiposity, limiting its applicability for longitudinal evaluations.

Project description:INTRODUCTION:BMI is the most commonly used indicator to evaluate overweight and obesity, but it cannot distinguish changes in body composition. Over recent years, it has been demonstrated that bioelectrical impedance analysis (BIA) is a more accurate method for analyzing body composition. Bioelectrical impedance vector analysis (BIVA) has revealed its effectiveness as an indicator of nutritional status and hydration. OBJECTIVE:To assess the usefulness of bioimpedance analysis on the study of body composition in a group of children with overweight and obesity. MATERIALS AND METHODS:Cross-sectional observational study. The anthropometric parameters of 167 (79 were older than 12 years) overweight and obese children were recorded. Their body composition was analyzed using BIA and BIVA, and was classified based on different criteria. Concordance was analyzed (intraclass correlation coefficient, Bland-Altman analysis and weighted Kappa coefficient). The BIVA of the subgroups was compared using the Mahalanobis distance and Hotelling's T2. Statistical significance was considered for p<0.05. RESULTS:The BMI revealed that the majority of the assessed subjects were obese, although 12% had a normal percentage of fat mass (%FM). The classification by Z-BMI and Z-%FM significantly discriminate between subjects with different levels of adiposity. In children over the age of 12, the classification of fat mass index also discriminates significantly between obesity and non-obesity. As anticipated, in the tolerance ellipses, most of the individual vectors were situated in the left lower quadrant. CONCLUSIONS:BIVA reflects differences in the bioelectric patterns of children who are classified as being overweight or obese (BMI) and who have different levels of %FM and FMI. BIVA permits a fast and easy monitoring of the evolution of the nutritional state and changes associated with body composition, and it identifies those children whose body compartments may be precisely estimated using traditional BIA methods.

Project description:BACKGROUND:Visceral fat area (VFA) is a good surrogate marker of obesity-related disorders, such as hypertension, dyslipidemia and glucose intolerance. Although estimating the VFA by X-ray computed tomography (CT) is the primary index for visceral obesity, it is expensive and requires invasive radiation exposure. Dual bioelectrical impedance analysis (BIA) is a simple and reliable method to estimate VFA; however, the clinical usefulness of dual BIA remains unclear in patients with type 2 diabetes (T2D). METHODS:We estimated the VFAs by dual BIA and CT in 98 patients with T2D and assessed anthropometric parameters, blood test results, and the presence of comorbid hypertension and dyslipidemia. We compared the correlation between the VFAs examined by dual BIA and CT. Furthermore, we performed the receiver operating characteristic (ROC) analyses for the VFAs to detect the presence of comorbid hypertension and/or dyslipidemia with T2D, which are major comorbidities of visceral obesity, and estimated the area under the curve (AUC). RESULTS:The measurement error between the VFAs by dual BIA and CT was significantly higher among patients with brain natriuretic peptide (BNP)???100 pg/mL than those with BNP?<?100 pg/mL (39.2%?±?31.1% vs. 24.1%?±?18.6%, P?<?0.05). After excluding patients with BNP???100 pg/mL, the VFA by dual BIA significantly correlated with the VFA by CT (r?=?0.917; P?<?0.0001). The AUC in the ROC analysis for the VFA by dual BIA to detect the presence of comorbid hypertension and/or dyslipidemia with T2D was almost equivalent to that for the VFA by CT. CONCLUSIONS:In patients with T2D without elevated BNP?>?100 pg/mL as indicator for fluid accumulation interfering with BIA, estimation of the VFA by dual BIA significantly correlated with that by CT and also detected comorbid hypertension and/or dyslipidemia with T2D equivalent to those detected by CT. Hence, dual BIA could be an alternative to CT as a standard method for estimating the VFA in patients with diabetes.

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Developing and Validating an Age-Independent Equation Using Multi-Frequency Bioelectrical Impedance Analysis for Estimation of Appendicular Skeletal Muscle Mass and Establishing a Cutoff for Sarcopenia.

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