Proximal electrode placement improves the estimation of body composition in obese and lean elderly during segmental bioelectrical impedance analysis

Bioelectrical impedance analysis (BIA) is an affordable, non-invasive, easy-to-operate, and fast alternative method to assess body composition. However, BIA tends to overestimate the percent body fat (%BF) in lean elderly and underestimate %BF in obese elderly people. This study examined whether proximal electrode placement eliminates this problem. Forty-two elderly men and women (64–96 years) who had a wide range of BMI [22.4 ± 3.3 kg/m² (mean ± SD), range 16.8–33.9 kg/m²] and %BF (11.3–44.8%) participated in this study. Using ²H and ¹⁸O dilutions as the criterion for measuring total body water (TBW), we compared various BIA electrode placements; wrist-to-ankle, arm-to-arm, leg-to-leg, elbow-to-knee, five- and nine-segment models, and the combination of distal (wrists or ankles) and proximal (elbows or knees) electrodes. TBW was most strongly correlated with the square height divided by the impedance between the knees and elbows (H ²/Z _proximal; r = 0.965, P < 0.001). In the wrist-to-ankle, arm-to-arm, leg-to-leg, and five-segment models, we observed systematic errors associated with %BF (P < 0.05). After including the impedance ratio of the proximal to distal segments (P/D) as an independent variable, none of the BIA methods examined showed any systematic bias against %BF. In addition, all methods were able to estimate TBW more accurately (e.g., in the wrist-to-ankle model, from R ² = 0.90, SEE = 1.69 kg to R ² = 0.94, SEE = 1.30 kg). The results suggest that BIA using distal electrodes alone tends to overestimate TBW in obese and underestimate TBW in lean subjects, while proximal electrodes improve the accuracy of body composition measurements.     

Measurement of body fluid volume change using multisite impedance measurements

Previous electrical impedance studies that predict body fluid volume and body fat used a single measurement site between the wrist and ankle Calculations based on an electrical model of the thorax suggest that with a single wrist-to-ankle measurement only the electrical characteristics of the legs and arms will contribute significantly to a prediction of the total body fluid volume. In this study, the impedance of the arms, legs and trunk were measured separately at 100 kHz and the values were correlated with weight change that occurred on 11 patients undergoing haemodialysis. Using multiple linear regression analysis combining data from the arms, legs and trunk gave a correlation coefficient of 0·87, whereas the correlation coefficient for measurements between the wrist and the ankle was 0·64. These results suggest that multisite impedance measurements will allow more reliable body fluid and body fat determinations to be made.     

Cross-calibration of eight-polar bioelectrical impedance analysis versus dual-energy X-ray absorptiometry for the assessment of total and appendicular body composition in healthy subjects aged 21-82 years

Aim: To calibrate eight-polar bioelectrical impedance analysis (BIA) against dual-energy X-ray absorptiometry (DXA) for the assessment of total and appendicular body composition in healthy adults. Research design: A cross-sectional study was carried out. Subjects: Sixty-eight females and 42 males aged 21-82 years participated in the study. Methods: Whole-body fat-free mass (FFM) and appendicular lean tissue mass (LTM) were measured by DXA; resistance ( R ) of arms, trunk and legs was measured by eight-polar BIA at frequencies of 5, 50, 250 and 500 kHz; whole-body resistance was calculated as the sum R of arms, trunk and legs. Results: The resistance index (RI), i.e. the height 2 /resistance ratio, was the best predictor of FFM and appendicular LTM. As compared with weight (Wt), RI at 500 kHz explained 35% more variance of FFM ( vs 0.57), 45% more variance of LTM arm ( vs 0.48) and 36% more variance of LTM leg ( vs 0.50) ( p < 0.0001 for all). The contribution of age to the unexplained variance of FFM and appendicular LTM was nil or negligible and the RI &#50 sex interactions were either not significant or not important on practical grounds. The percent root mean square error of the estimate was 6% for FFM and 8% for LTM arm and LTM leg. Conclusion: Eight-polar BIA offers accurate estimates of total and appendicular body composition. The attractive hypothesis that eight-polar BIA is influenced minimally by age and sex should be tested on larger samples including younger individuals.     

Assessment of total and segmental body composition in spinal cord-injured athletes in Okayama prefecture of Japan

This study assessed total and segmental distribution of fat mass (FM) in athletes with spinal cord injury (SCI) and examined the relationships between segmental distribution of fat mass and age, injury level, athletic history, and training load in order to provide useful information for improvements in their physical strength and training. Twenty-five male athletes with SCI participated in the study. The whole bone composition was measured by a dual-energy X-ray absorptiometry (DXA) method for the calculation of bone minerals, FM, and fat-free mass. The percent fat of the trunk, arms, and legs was also calculated. The percent fat in the legs was highest in comparison with that in the trunk and arms (p < 0.001), and the percent fat in the trunk was higher than that in the arms (p < 0.001). The body fat (p < 0.01), waist circumference (p < 0.01), and waist-to-hip ratio (p < 0.0001) were higher in the group aged 40 or older in comparison with that aged 39 or younger. Path analysis revealed that training load was a factor decreasing the percent fat on the arms and trunk (p < 0.01), and athletic history was a factor reducing the percent fat on the arms (p < 0.05). Our study suggests that exercise is effective in reducing the waist circumference, waist-to-hip ratio, and percent body fat of SCI individuals, and that such effects can help to enhance athletic performance and likely to protect against development of metabolic syndromes resulting from a sedentary lifestyle.     

Bio-impedance analysis for estimation of total body potassium,total body water,and fat-free mass in white,black, and Asian adults

Bio-impedance analysis (BIA) measurements have been used to predict components of body composition. Their validation is required for populations varying in race, sex, and age. In 371 Whites, 182 Blacks and 225 Asians, single-frequency BIA at 50 kHz (RJL-100) resistance and reactance measurements were correlated with same-day measurements of total body water (TBW) by THO dilution, total body potassium (TBK) by whole body ⁴⁰K counting, and fat-free mass (FFM) by dual-photon absorptiometry. BIA correlation coefficients with TBW, TBK, FFM, and fat varied by sex and race for all measured body composition components. The highest correlation was for FFM, and the lowest was for fat mass. Prediction equations were further improved by including age, stature, and weight for each of the study cohorts. The SEE for predictions were in the ranges of 5–6, 6–8, and 7–10% of measured FFM, TBW, and TBK, respectively. BIA was effective in predicting body composition when subjects are specified by age, sex, stature, weight, and race for subjects from 18 to 94 years of age. © 1995 Wiley-Liss, Inc.     

Cross-calibration of eight-polar bioelectrical impedance analysis versus dual-energy X-ray absorptiometry for the assessment of total and appendicular body composition in healthy subjects aged 21-82 years

AIM: To calibrate eight-polar bioelectrical impedance analysis (BIA) against dual-energy X-ray absorptiometry (DXA) for the assessment of total and appendicular body composition in healthy adults. RESEARCH DESIGN: A cross-sectional study was carried out. SUBJECTS: Sixty-eight females and 42 males aged 21-82 years participated in the study. METHODS: Whole-body fat-free mass (FFM) and appendicular lean tissue mass (LTM) were measured by DXA; resistance (R) of arms, trunk and legs was measured by eight-polar BIA at frequencies of 5, 50, 250 and 500 kHz; whole-body resistance was calculated as the sum R of arms, trunk and legs. RESULTS: The resistance index (RI), i.e. the height(2)/resistance ratio, was the best predictor of FFM and appendicular LTM. As compared with weight (Wt), RI at 500 kHz explained 35% more variance of FFM (vs 0.57), 45% more variance of LTM(arm) (vs 0.48) and 36% more variance of LTM(leg) (vs 0.50) (p < 0.0001 for all). The contribution of age to the unexplained variance of FFM and appendicular LTM was nil or negligible and the RI x sex interactions were either not significant or not important on practical grounds. The percent root mean square error of the estimate was 6% for FFM and 8% for LTM(arm) and LTM(leg). CONCLUSION: Eight-polar BIA offers accurate estimates of total and appendicular body composition. The attractive hypothesis that eight-polar BIA is influenced minimally by age and sex should be tested on larger samples including younger individuals.     

Relationships between plasma leptin levels and body composition parameters measured by different methods in postmenopausal women

The aim of this study was to determine the effects of body composition measured by different methods with different measurement errors on fasting plasma leptin level in normal body mass and obese postmenopausal women. It was hypothesized that the relationship between plasma leptin concentration and body fat is higher using more sophisticated laboratory methods (dual energy X‐ray absorptiometry, DXA) in comparison with field methods (bioelectrical impedance analysis, BIA, or skinfold thickness) for body fat measurement because of the greater precision of DXA measurements. Thirty‐five postmenopausal (55–83 years of age) healthy Estonian women were divided into two groups: BMI < 27kg/m² as non obese (n = 18) and BMI> 27kg/m² as obese (n = 17). Body composition was determined using DXA (total body, arms, legs, and trunk fat percent, fat mass, and LBM) and BIA methods. Body fat percent was significantly higher using the DXA method. Subcutaneous adipose tissue distribution was determined by measuring nine skinfold thicknesses. Body fat distribution was defined as the ratio of waist‐to‐hip (WHR) and waist‐to‐thigh (WTR) circumferences. Leptin was determined by means of radioimmunoassays. Leptin concentration was not significantly different between groups (19.0 ± 13.3 and 21.5 ± 21.5ng/ml in non obese and obese groups, respectively). Body fat percent and fat weight measured by DXA or BIA methods and all measured skinfold thickness values, except biceps and abdominal, were higher in obese women. Body height did not correlate significantly with leptin concentrations. The relationships between leptin concentration were highest with body weight (r = 0.67) and BMI (r = 0.73) values in the obese group. All measured body fat parameters using DXA or BIA methods correlated significantly with plasma leptin concentration in the obese group. LBM did not influence the leptin concentration in postmenopausal women. Stepwise multiple regression analysis indicated that the body fat percent measured using the DXA method was highly related to plasma leptin concentration in the obese group (63.2%; R² × 100). When absolute fat mass parameters were considered, leptin concentration was related to the mass of arms fat tissue in the obese group of women (62.3%). Body fat percent measured by BIA was highly related to plasma leptin concentration in the obese group (63.3%). Only biceps skinfold thickness was related to leptin concentration (22.5% and 58.9%, in the nonobese and obese groups, respectively) from the nine measured skinfold thicknesses. WHR and WTR did not reflect leptin concentration in different groups of postmenopausal women. It was concluded that different methods of body composition estimation generate different correlations with plasma leptin concentration. Body fat percent and especially fat mass measured by DXA are the main predictors relating to plasma leptin concentration in obese, but not in nonobese, postmenopausal women. In addition, fat mass in arms measured by DXA and biceps skinfold thickness were also highly related to leptin concentration. Am. J. Hum. Biol. 15:628–636, 2003. © 2003 Wiley‐Liss, Inc.     

Relative contribution of aging and menopause to changes in lean and fat mass in segmental regions

Objective: The aim of the study was to investigate the relative contribution of aging and menopause to the changes in lean and fat mass in segmental regions. Materials and methods: Subjects were 365 pre- and 201 postmenopausal Japanese women aged between 20 and 70 years old. Age, height, weight, body mass index (BMI, Wt/Ht²), age at menopause, years since menopause (YSM), and menopausal status were recorded. Lean and fat mass of the arms, trunk, legs, total body, and the ratio of trunk fat mass to leg fat mass amount (trunk–leg fat ratio) were measured by dual-energy X-ray absorptiometry (DEXA). Regional (arms, lumbar spine, pelvis, legs, and total body) bone mineral density (BMD) were measured by DEXA. Results: Total body lean mass and regional BMD decreased (P<0.001), while percentage of body fat, trunk fat mass, and trunk–leg fat ratio increased (P<0.001) with aging and after menopause. On multiple regression analyses, trunk and total body lean mass were inversely correlated with menopausal status (P<0.001 and 0.05, respectively) but not with age. Trunk fat mass, trunk–leg fat ratio, and percentage of body fat were positively correlated with age (P<0.01) but not with menopausal status. Regional BMD were more inversely correlated with menopausal status (P<0.001) than age. Conclusion: Decrease in lean mass and BMD are more menopause-related, while the shift toward upper body fat distribution and overall adiposity are more age-related. Lean tissue is similar to bone tissue from the viewpoint of more undergoing menopausal effect.     

Body composition in urban South Asian women; development of a bioelectrical impedance analysis prediction equation

Abstract

Background: Assessment of body composition plays a significant role in combating chronic disease among South Asians. Accurate assessment of body composition by bioelectrical impedance analysis (BIA) requires population-specific equations which are currently unavailable for urban South Asian women.

Aim: To assess validity of direct BIA assessment and selected equations for prediction of total body water (TBW), against Deuterium (²H₂O) dilution and develop and validate a population-specific TBW equation for urban South Asian women.

Subjects and method: Data of 80 urban Sri Lankan women (30–45 years) were used for this analysis. Body composition was assessed by ²H₂O dilution (reference) and BIA. Available BIA equations were assessed for validity. A new TBW equation was generated and validated.

Results: Direct BIA measurements and other equations did not meet validation criteria in predicting TBW. TBW by the new equation (TBW?=?3.443?+?0.342?×?(height²/impedance)?+?0.176?×?weight) correlated (p?<?0.001) with TBW by reference method. TBW using the new equation was not significantly different (25.30?±?2.4?kg) from the reference (25.32?±?2.7?kg).

Conclusion: Direct use of TBW by instrument and existing equations are less suitable for this population. The new TBW equation is suitable for body composition assessment in urban South Asian women.     

一种新的人体成分分析分段模型——检测系统设计及初步实验

目的针对全身阻抗测量方法和传统分段阻抗测量法存在的问题,优化生物电阻抗人体成分分析（BIA）的分段模型,研制基于新模型的测量系统,进行初步实验。方法分析人体胸部和腹部对脂肪测量的不同影响,提出新的躯干细分模型;对新模型进行理论分析,构建基于躯干细分模型BIA系统,进行多层螺旋CT（MSCT）法与新方法的人体成分测量对照实验。结果以人体躯干部分为检测重点,基于躯干细分模型的BIA法能有效区分躯干上段和下段的阻抗值,从而得到人体的胸部和腹部脂肪含量。2种方法的对照试验结果显示出良好的相关性。结论基于躯干细分模型的新方法,弥补了全身和传统5段分段法的缺陷,是对传统人体成分分析方法的有效改进,更符合临床上人体成分测量的要求和目标,更具生理学意义。     

The determination of three subcutaneous adipose tissue compartments in non-insulin-dependent diabetes mellitus women with artificial neural networks and factor analysis.

The optical device LIPOMETER allows for non-invasive, quick, precise and safe determination of subcutaneous fat distribution, so-called subcutaneous adipose tissue topography (SAT-Top). In this paper, we show how the high-dimensional SAT-Top information of women with type-2 diabetes mellitus (non-insulin-dependent diabetes mellitus (NIDDM)) and a healthy control group can be analysed and represented in low-dimensional plots by applying factor analysis and special artificial neural networks. Three top-down sorted subcutaneous adipose tissue compartments are determined (upper trunk, lower trunk, legs). NIDDM women provide significantly higher upper trunk obesity and significantly lower leg obesity ('apple' type), as compared with their healthy control group. Further, we show that the results of the applied networks are very similar to the results of factor analysis.     

A comparison of dual energy X-ray absorptiometry and bioelectrical impedance analysis to measure total and segmental body composition in healthy young adults

The aim of this study was to investigate the accuracy of BIA in the measurement of total body composition and regional fat and the fat free mass in the healthy young adults. Four hundred and three healthy young adults (167 women and 236 men) aged 18–29 years were recruited from the Mid-West region of Ireland. Multi frequency, eight-polar bioelectrical impedance analysis (BIA) and dual energy X-ray absorptiometry (DXA) were used to measure the total body and segmental (arm, leg and trunk) fat mass and the fat free mass. BIA was found to underestimate the percentage total body fat in men and women (p < 0.001). This underestimate increased in men with >24.6% body fat and women with >32% body fat (p < 0.001). Fat tissue mass in the trunk segment was overestimated by 2.1 kg (p < 0.001) in men and underestimated by 0.4 kg (p < 0.001) in women. BIA was also found to underestimate the fat free mass in the appendages by 1.0 kg (p < 0.001) in men and 0.9 kg (p < 0.001) in women. Compared to dual energy X-ray absorptiometry, bioelectrical impedance analysis underestimates the total body fat mass and overestimates fat free mass in healthy young adults. BIA should, therefore, be used with caution in the measurement of total body composition in women and men with >25% total body fat. Though statistically significant, the small difference (~ 4%) between the methods indicates that the BIA may be used interchangeably with DXA in the measurement of appendicular fat free mass in healthy young adults.     

Effects of silicone breast prostheses on the assessment of body composition by dual-energy X-ray absorptiometry.

We examined the influence of silicone breast prostheses on body composition as assessed by dual-energy X-ray absorptiometry (DXA). Eighteen women were measured with and without a pair of silicone breast prostheses placed on the upper part of the trunk simulating endogenous implants. Bone area, bone mineral content (BMC), areal bone mineral density (BMD), lean tissue mass (LTM) and fat tissue mass (FTM) of the total body and of the subregions of the body, i.e. the head, trunk, arms and legs, were measured by a Norland XR-36 DXA scanner. After application of the silicone prostheses, bone area, BMC and BMD of the total body significantly increased by an average of 3.7, 6.6 and 3.4% (P<0.0001), respectively. Total body LTM and FTM were not affected. In the trunk region, changes were more pronounced. Trunk BMC, for example, was overestimated by 17.9% (P<0. 0001). The prostheses also influenced measurements of truncal soft tissue composition, with a small but statistically significant overestimation of both LTM (1.1%) and FTM (2.1%) (P<0.05). No changes in bone mass and soft tissue composition were seen in the head, arms and legs. Activation of a high-density detection software utility provided by the manufacturer had no influence on any of the measurements. We conclude that silicone breast prostheses affect the assessment of body composition by DXA.     

The effect of menopause on regional and total body lean mass

Objectives: To investigate the effect of menopause on regional and total body lean mass. Methods: Evaluation of 123 healthy premenopausal women (40.6±10.8 years) and 123 healthy postmenopausal women (61.8±7.5 years). All subjects were right side dominant. Regional (head, bilateral arms, trunk, and bilateral legs) and total body lean mass were measured using whole-body scanning by dual-energy X-ray absorptiometry. Baseline characteristics including age, height, weight, and menopausal state were recorded. These variables were compared between pre- and postmenopausal women. In all subjects, correlations between regional or total body lean mass and baseline characteristics were investigated using univariate and multiple regression analyses. Results: Height, and lean mass of the trunk, bilateral legs and total body were significantly lower in postmenopausal women than in premenopausal women, while lean mass of the bilateral arms did not differ between the two groups. On univariate regression analysis, bilateral arms lean mass was positively correlated with height (P<0.001). Trunk, bilateral legs, and total body lean mass were inversely correlated with age and menopausal state (P<0.001), but were positively correlated with height (P<0.001). After adjusting for age and height, trunk lean mass was still correlated with menopausal state (P<0.01). Conclusions: Menopause induces lean mass loss, independent of aging and height. Trunk lean mass is more prone to decline with menopause than lean mass of other sites.     

Prospective evaluation of body weight and body fat distribution in early postmenopausal women with and without hormonal replacement therapy

AIMS: In order to assess the effects of menopause and hormonal replacement therapy (HRT) on body weight and body fat distribution (determined by dual energy X-ray), early postmenopausal women were given either oral calcium (500 mg/day, control group, n=13) or HRT, a combination of estradiol valerate (EV, 2 mg/day for 21 days) with cyproterone acetate (CPA, 1 mg/day in the last 10 days of the treatment cycle, n=18; Climen, Schering). RESULTS: There were no differences in basal body weight and body fat distribution in the two groups before the study. In control group, a significant (P<0.05) increase in body weight (from 63.5+/-2.0 to 68.7+/-2.0 kg after 36 months) paralleled a shift to a prevalent central, android fat distribution with a slight but significant (P<0.05) increase in total body fat mass (from 23.4+/-2.1 to 29.1+/-2.1 kg), an increase in trunk (from 10.1+/-0.4 to 12.7+/-0.4 kg, P<0.05), arms (from 2.4+/-0.2 to 2.9+/-0.2 kg, P<0.05) and legs (from 6.5+/-0.4 to 7.8+/-0.4 kg, P<0.05) fat. In the HRT group total body bone mineral showed a significant increase (from 1086+/-21 to 1128+/-19 mg/cm(2), P<0.05) increase after 36 months, with no significant increase in body weight (from 62.6+/-1.8 to 65.0+/-1.9 kg), and no modifications in trunk (from 10.0+/-0.2 to 10.1+/-0.2 kg) and arms (from 2.4+/-0.1 to 2.6+/-0.1 kg) fat, but a significant increase in legs fat (from 6.9+/-0.3 to 9.9+/-0.4 kg, P<0.05). CONCLUSION: Present results demonstrate that menopause is associated with an accelerated increase in body weight and body fat, with a prevalent central, android fat distribution, that can be counteracted at least in part by oral HRT.     

Distal versus proximal electrode placement in the prediction of total body water and extracellular water from multifrequency bioelectrical impedance

In 48 normal weight subjects, 25 females and 23 males, body impedance was measured at multiple frequencies. Two different electrode placements were used, one the commonly used distal electrode placement, in which the source electrodes are on the dorsal sides of the hand and foot and the sensor electrodes are on ankle and wrist, and a second placement, in which the sensor electrodes are placed more proximally, at the knee and elbow. Theoretically a proximal electrode placement could result in more precise estimates of body water compartments. Total body water (TBW) and extracellular water (ECW) were determined using deuterium oxide dilution and bromide dilution, respectively. The aim of the study was to investigate whether proximal electrode placement results in a more precise estimation of TBW and ECW using multifrequency impedance analysis. Correlation coefficients of impedance and the impedance index stature²/impedance) with TBW and ECW were not or were only slightly higher using proximal impedance values, resulting in slight improvement of the estimation error for TBW (0.13 kg) and ECW (0.04 kg). The differences between measured and predicted values (residuals) of TBW and ECW were not correlated with TBW and ECW, but they were correlated with body fat and body water distribution (ECW/TBW). These correlations did not differ between distal and proximal impedance measurements. It is concluded that proximal impedance measurements do not substantially improve the prediction of body water compartments. © 1995 Wiley-Liss, Inc.     

Development of anthropometry-based equations for the estimation of the total body water in Koreans

For developing race-specific anthropometry-based total body water (TBW) equations, we measured TBW using bioelectrical impedance analysis (TBW(BIA)) in 2,943 healthy Korean adults. Among them, 2,223 were used as a reference group. Two equations (TBW(K1) and TBW(K2)) were developed based on age, sex, height, and body weight. The adjusted R2 was 0.908 for TBW(K1) and 0.910 for TBW(K2). The remaining 720 subjects were used for the validation of our results. Watson (TBW(W)) and Hume-Weyers (TBW(H)) formulas were also used. In men, TBW(BIA) showed the highest correlation with TBW(H), followed by TBW(K1), TBW(K2) and TBW(W). TBW(K1) and TBW(K2) showed the lower root mean square errors (RMSE) and mean prediction errors (ME) than TBW(W) and TBW(H). On the Bland-Altman plot, the correlations between the differences and means were smaller for TBW(K2) than for TBW(K1). On the contrary, TBW(BIA) showed the highest correlation with TBW(W), followed by TBW(K2), TBW(K1), and TBW(H) in females. RMSE was smallest in TBW(W), followed by TBW(K2), TBW(K1) and TBW(H). ME was closest to zero for TBW(K2), followed by TBW(K1), TBW(W) and TBW(H). The correlation coefficients between the means and differences were highest in TBW(W), and lowest in TBW(K2). In conclusion, TBW(K2) provides better accuracy with a smaller bias than the TBW(W) or TBW(H) in males. TBW(K2) shows a similar accuracy, but with a smaller bias than TBW(W) in females.     

Best method for estimating urea volume of distribution: comparison of single pool variable volume kinetic modeling measurements with bioimpedance and anthropometric methods

The urea volume of distribution (Vurea) is a key component of the Kt/V parameter calculated during urea kinetic modeling. The Vurea parameter has been approximated empirically using total body water (TBW) estimates derived from anthropometric formulas or measured by bioelectric impedance analysis (BIA). The author compared TBW values derived using various anthropometric formulas (Watson, Hume, Randall, Tzamaloukas, Chertow) and BIA to the Vurea parameter calculated using three point variable volume single pool urea kinetic modeling. A total of 127 chronic hemodialysis patients were studied (mean age 66 +/- 13 years; 42% female; 37% black; 47% diabetic). Agreement between anthropometric formulas, BIA, and Vurea values was assessed by linear regression and Bland Altman analyses. The closest correlations were obtained with the BIA (r = 0.972), Chertow (r = 0.917), and Tzamaloukas (r = 0.905) methods. When compared with Vurea, 95% confidence intervals by Bland Altman analysis were lowest with BIA (4L) and highest with the Watson method (8L). These results indicate that BIA best approximates Vurea in dialysis patients.     

Difference in segmental lean and fat mass components between pre- and postmenopausal women

OBJECTIVE: To investigate the differences in segmental body composition (lean and fat mass components) between pre- and postmenopausal women. DESIGN: Participants were 413 premenopausal women aged 20 to 53 years old and 229 postmenopausal women aged 50 to 75 years old with right-side dominance. Age, height, weight, body mass index, age at menopause, and years since menopause were recorded. The percentages of fat mass in the arms, trunk, legs, and total body were measured by dual-energy x-ray absorptiometry. The ratio of trunk to leg fat mass (trunk-leg fat mass ratio) was also measured by dual-energy x-ray absorptiometry. RESULTS: The percentage of trunk fat mass and the trunk-leg fat mass ratio were significantly higher in postmenopausal women, but the percentages of leg fat mass did not differ. In the two groups, percentage of trunk fat mass and trunk-leg fat mass ratio were similarly and positively correlated with age. However, percentage of leg fat mass did not correlate with age. The percentage of fat mass at each segmental site and the trunk-leg fat mass ratio did not differ between premenopausal women aged 50 to 53 years old (n=52) and age-matched postmenopausal women (n=43, years since menopause=2.8+/-1.8). CONCLUSIONS: Aging rather than menopause contributes to the increase in the percentage of trunk fat mass. However, the percentage of leg fat mass does not change with aging. Upper body fat distribution in postmenopausal women may be more attributable to aging than to menopause.     

Assessment of the composition of major body regions by dual-energy X-ray absorptiometry (DEXA), with special reference to limb muscle mass.

Dual-energy X-ray absorptiometry (DEXA) has been used to assess and compare the composition of whole body and major body regions in 12 female (weight, 56.9 +/- 6.2 kg; BMI, 17-25 kg m-2) and 16 male (weight, 73.1 +/- 9.6 kg; BMI, 20-28 kg m-2) healthy subjects. Standard deviations (and % coefficients of variation) of the differences between repeated measurements of fat ranged from 0.11 kg (9.0%) for arms to 0.42 kg (3.0%) for whole body; for arm bone mineral, 0.01 kg (2.0%), and for fat-free soft tissue of the whole body, 0.42 kg (0.8%). Limb muscle mass was estimated using a new theoretical model of body composition, and the corresponding precision ranged from 0.15 kg (3.8%) to 0.27 kg (1.5%) for arms and total limb muscle mass, respectively. Proportions of each region consisting of fat were greater in females than in males (range, 20-31% vs. 16-18%), respectively, but the ratio of trunk to leg fat was lower (34:49% vs. 46:38%, respectively). Regional proportions of bone were similar between the sexes (all in the range 2.9-5.6%, for both females and males). Mean total limb muscle masses were 14.2 kg (arms, 2.8 kg; legs, 11.4 kg) for females and 22.2 kg (arms, 4.8 kg; legs, 17.4 kg) for males, which were 33.6% and 36.0% of fat-free mass, respectively. The correlation coefficients between limb muscle (DEXA) and other indices of muscle mass were: for DEXA vs. total body potassium, 0.90 (SEE 1.1 kg muscle mass) to 0.94 (1.6 kg); and for DEXA vs. anthropometry, 0.43 (1.2 kg) to 0.85 (1.3 kg). Those for limb volume (DEXA) vs. anthropometric volume, 0.91 (0.78 1) to 0.94 (1.91 1). It is concluded that DEXA enables the valid and reproducible estimation of fat, fat-free soft tissue, bone, and limb muscle mass.