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Comparison of Bioelectrical Impedance Analysis and Dual Energy X-ray Absorptiometry for Total and Segmental Bone Mineral Content with a Three-Compartment Model.

ABSTRACT: Modern bioelectrical impedance analysis (BIA) provides a wide range of body composition estimates such as fat mass (FM), lean body mass (LBM), and body water, using specific algorithms. Assuming that the fat free mass (FFM) and LBM can be accurately estimated by the 8-electrode BIA analyzer (BIA8MF; InBody230, Biospace), the bone mineral content (BMC) may be calculated by subtracting the LBM from the FFM estimates based on the three-compartment (3C) model. In this cross-sectional study, 239 healthy Taiwanese adults (106 male and 133 female) aged 20-45 years were recruited for BIA and dual-energy X-ray absorptiometry (DXA) measurements of the whole body and body segments, with DXA as the reference. The results showed a high correlation between BIA8MF and DXA in estimating total and segmental LBM, FM and percentage body fat (r = 0.909-0.986, 0.757-0.964, and 0.837-0.936, respectively). For BMC estimates, moderate to high correlations (r = 0.425-0.829) between the two methods were noted. The percentage errors and pure errors for BMC estimates between the methods ranged from 33.9% to 93.0% and from 0.159 kg to 0.969 kg, respectively. This study validated that BIA8MF can accurately assesses LBM, FM and body fat percentage (BF%). However, the estimation of segmental BMC based on the difference between FFM and LBM in body segments may not be reliable by BIA8MF.

SUBMITTER: Liao YS

PROVIDER: S-EPMC7177846 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Comparison of Bioelectrical Impedance Analysis and Dual Energy X-ray Absorptiometry for Total and Segmental Bone Mineral Content with a Three-Compartment Model.

Liao Yu-San YS Li Hung-Chou HC Lu Hsueh-Kuan HK Lai Chung-Liang CL Wang Yue-Sheng YS Hsieh Kuen-Chang KC

International journal of environmental research and public health 20200410 7

Modern bioelectrical impedance analysis (BIA) provides a wide range of body composition estimates such as fat mass (FM), lean body mass (LBM), and body water, using specific algorithms. Assuming that the fat free mass (FFM) and LBM can be accurately estimated by the 8-electrode BIA analyzer (BIA<sub>8MF</sub>; InBody230, Biospace), the bone mineral content (BMC) may be calculated by subtracting the LBM from the FFM estimates based on the three-compartment (3C) model. In this cross-sectional stud ...[more]

PMID: 32290133

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Project description:Background:The 4-component (4C) model is a criterion method for human body composition that separates the body into fat, water, mineral, and protein, but requires 4 measurements with significant cost and time requirements that preclude wide clinical use. A simplified model integrating only 2 measurements-dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA)-and 10 min of patient time has been proposed. Objective:We aimed to validate a rapid, simplified 4C DXA + BIA body composition model in a clinical population. Design:This was a cross-sectional observational study of 31 healthy adults. Participants underwent whole-body DXA, segmental BIA, air displacement plethysmography (ADP), and total body water (TBW) measurement by deuterium (D2O) dilution. 4C composition was calculated through the use of the Lohman model [DXA mineral mass, D2O TBW, ADP body volume (BV), scale weight] and the simplified model (DXA mineral mass and BV, BIA TBW, scale weight). Accuracy of percentage of fat (%Fat) and protein measurements was assessed via linear regression. Test-retest precision was calculated with the use of duplicate DXA and BIA measurements. Results:Of 31 participants, 23 were included in the analysis. TBWBIA showed good test-retest precision (%CV = 5.2 raw; 1.1 after outlier removal) and high accuracy to TBWD2O [TBWD2O = 0.956*TBWBIA, R2= 0.92, root mean squared error (RMSE) = 2.2 kg]. %Fat estimates from DXA, ADP, D2O, and BIA all showed high correlation with the Lohman model. However, only the 4C simplified model provides high accuracy for both %Fat (R2 = 0.96, RMSE = 2.33) and protein mass (R2= 0.76, RMSE = 1.8 kg). %Fat precision from 4C DXA + BIA was comparable with DXA (root mean square-SD = 0.8 and 0.6 percentage units, respectively). Conclusions:This work validates a simplified 4C method that measures fat, water, mineral, and protein in a 10-min clinic visit. This model has broad clinical application to monitor many conditions including over/dehydration, malnutrition, obesity, sarcopenia, and cachexia.

Project description:IntroductionMethods of body composition estimation such as dual-energy X-ray absorptiometry (DXA), anthropometry, and bioimpedance (BIA) are used for the estimation of skeletal muscle mass (SMM) and lean body mass (LBM). No previous studies have examined whether these methods generate comparable results, or whether they are valid by using DXA as the reference. The aims of the present investigation were: (a) to assess the differences between DXA, anthropometry, and BIA in the estimation of SMM and LBM, taking into consideration the impact of sex and hydration status; and (b) to examine the agreement of anthropometry and BIA as compared to DXA for the estimation of SMM and LBM.MethodsA descriptive cross-sectional design was followed with 262 healthy young adults (159 males and 103 females). LBM and SMM were assessed by anthropometry with the formulas from Lee et al. and Kulkarni et al. for LBM; and Kerr (opt a), Kerr (opt b), Lee et al., Poortmans, Matiegka, Martin et al., Drinkwater and Ross, and Heymsfield et al. for SMM; by BIA with the formula reported by the TANITA MC-780-MA software for LBM and SMM; and DXA with the formula reported by the Hologic Horizon software for LBM, and the conversion by Kim et al. for SMM.ResultsSignificant differences were found for both SMM and LBM in kg, and percentages between most methods and formulas for the overall sample (p < 0.001-0.003) and divided by sex (p < 0.001-0.035). Hydration status did not have a significant effect on the differences between methods and formulas (p = 0.058-0.870). Lin's coefficient revealed limited agreement among the majority of formulas and methods (CCC = 0.007-0.880). The Bland-Altman analysis showed significant differences in most methods and formulas, both in the overall sample and divided by sex, when using SMM and LBM with DXA as the reference (p < 0.001-0.030).ConclusionThere is a lack of agreement between methods and formulas for assessing SMM and LBM. Sex was found to be a significant factor in this analysis. Furthermore, significant differences were observed between most formulas and methods as compared to DXA, except for the equations to estimate SMM with anthropometry by Poortmans.

Project description:Background/objectivesQuantile-dependent expressivity occurs when a gene's phenotypic expression depends upon whether the trait (e.g., BMI) is high or low relative to its distribution. We have previously shown that the obesity effects of a genetic risk score (GRSBMI) increased significantly with increasing quantiles of BMI. However, BMI is an inexact adiposity measure and GRSBMI explains <3% of the BMI variance. The purpose of this paper is to test BMI for quantile-dependent expressivity using a more inclusive genetic measure (h2, heritability in the narrow sense), extend the result to other adiposity measures, and demonstrate its consistency with purported gene-environment interactions.Subjects/methodsQuantile-specific offspring-parent regression slopes (?OP) were obtained from quantile regression for height (ht) and computed tomography (CT), dual-energy x-ray absorptiometry (DXA), anthropometric, and bioelectrical impedance (BIA) adiposity measures. Heritability was estimated by 2?OP/(1?+?rspouse) in 6227 offspring-parent pairs from the Framingham Heart Study, where rspouse is the spouse correlation.ResultsCompared to h2 at the 10th percentile, genetic heritability was significantly greater at the 90th population percentile for BMI (3.14-fold greater, P?<?10-15), waist girth/ht (3.27-fold, P?<?10-15), hip girth/ht (3.12-fold, P?=?6.3?×?10-14), waist-to-hip ratio (1.75-fold, P?=?0.01), sagittal diameter/ht (3.89-fold, P?=?3.7?×?10-7), DXA total fat/ht2 (3.62-fold, P?=?0.0002), DXA leg fat/ht2 (3.29-fold, P?=?2.0?×?10-11), DXA arm fat/ht2 (4.02-fold, P?=?0.001), CT-visceral fat/ht2 (3.03-fold, P?=?0.002), and CT-subcutaneous fat/ht2 (3.54-fold, P?=?0.0004). External validity was suggested by the phenomenon's consistency with numerous published reports. Quantile-dependent expressivity potentially explains precision medicine markers for weight gain from overfeeding or antipsychotic medications, and the modifying effects of physical activity, sleep, diet, polycystic ovary syndrome, socioeconomic status, and depression on gene-BMI relationships.ConclusionsGenetic heritabilities of anthropometric, CT, and DXA adiposity measures increase with increasing adiposity. Some gene-environment interactions may arise from analyzing subjects by characteristics that distinguish high vs. low adiposity rather than the effects of environmental stimuli on transcriptional and epigenetic processes.

Project description:ObjectiveThis study examined the association of whole-body composition and segmental bioimpedance variables with cold pattern (CP) in different sexes.MethodsWe assigned 667 older individuals to a CP group (n = 488) and a non-CP group (n = 179) by using an eight-item self-administered questionnaire. Seven body composition variables and three pairs of segmental bioimpedance variables for the upper and lower extremities, which were obtained from a segmental multifrequency bioimpedance analyzer, were employed to investigate their association with CP. Participants' characteristics were first described. Then we compared the selected body composition and bioimpedance variables between the CP and non-CP groups. Finally, their association with CP was investigated using univariate and multivariate regression analyses. All analyses were performed separately for women and men.ResultsBoth women and men exhibited a comparable mean age in the CP and non-CP groups; however, women with CP had significantly lower blood pressures, whereas men with CP showed a higher proportion of osteoarthritis than those without CP. Compared with the non-CP group, individuals with CP exhibited significantly smaller body sizes indicated by shorter height and smaller weight, lower body mass index, and smaller volume-to-body surface area ratio in both sexes. After controlling for age, height, weight, and other covariates, we found significant reductions in body lean mass such as fat-free mass and body cell mass, basal metabolic rate per unit mass, total body water, and intra-to-extracellular water ratio in the CP group. With regard to segmental bioimpedance analysis, the resistance ratios and phase angles in the upper and lower extremities yield significant associations with CP incidence, as demonstrated by the odds ratio (95% confidence interval) of 1.72 (1.16-2.57), 1.69 (1.18-2.48), 0.60 (0.40-0.89), and 0.57 (0.39-0.82), respectively. However, these results did not emerge in men.ConclusionAbnormal cellular water distribution and deterioration in body cell mass and/or cell strength are associated with CP prevalence, regardless of age, height, weight. These findings are similar in the upper and lower extremities and are more pronounced in women. The abovementioned patterns may be considered effective indicators for identifying CP in the older adult population.

Dataset Information

Comparison of Bioelectrical Impedance Analysis and Dual Energy X-ray Absorptiometry for Total and Segmental Bone Mineral Content with a Three-Compartment Model.

Publications

Comparison of Bioelectrical Impedance Analysis and Dual Energy X-ray Absorptiometry for Total and Segmental Bone Mineral Content with a Three-Compartment Model.

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