Sensitivity of bioelectrical impedance to detect changes in human body composition

The purpose of this study was to compare the estimates of lean body mass (LBM) and percent body fat (%BF), as predicted by bioelectrical impedance (BIA) and sum of skinfolds (SF), with those derived by hydrostatic weighing (HW) obtained before and after a 10-wk diet and exercise regimen. The experimental (E) group consisted of 17 healthy male subjects; 20 healthy males served as the control (C) group. Post hoc Scheffé contrasts computed on E group data indicated that, for both LBM and %BF, the Lukaski and Segal BIA equations, as well as the Durnin SF equation, derived mean values that were not significantly different (0.05 significance level) from HW in both pre- and postregimen conditions. For LBM, the same equations derived the following significant (P less than 0.01) correlation coefficients for both pre- and postregimen data: Lukaski, 0.87 and 0.85; Segal, 0.89 and 0.87; and Durnin, 0.90 and 0.88. For %BF, the correlation coefficients were slightly lower but remained statistically significant (P less than 0.01). The findings of this study suggest that the BIA method, by use of either the Lukaski or Segal prediction equations, is a valid means of predicting changes in human body composition as measured by the Siri transformation of body density.     

Validity of the BOD POD for assessing body composition in athletic high school boys

The purpose of this study was to validate the percentage of body fat (%BF) values estimated from the BOD POD (BP) with those obtained from hydrostatic weighing (HW) in athletic American high school boys. Additionally, the %BF values measured via near-infrared interactance (NIR), bioelectrical impedance (BIA), and skinfold (SF) were compared to HW to determine the validity of these measures. Thirty white boys (mean age +/- SD = 15.8 +/- 1.0 years) who where currently participating in organized sports volunteered to have their %BF estimated. Measurements were obtained from NIR, BP, BIA, and SF in random order and concluded with HW. The findings from the present study indicated that the NIR and BIA instruments produced significant (P < 0.008) constant error (CE) and total error (TE) values that were too large to be of practical value (TE > 4.0%BF). The BP produced a significantly (P < 0.008) higher CE with acceptable TE values compared to HW, but compared to all three SF estimations, the BP TE values were higher. Two of the SF equations were nonsignificant (P > 0.008) and had the lowest TE values compared to HW. These data suggest that the BP can produce acceptable body fat measures for athletic white boys but is not superior to estimates made by the SF equations used in this study.     

Effect of intense military training on body composition

Individuals in a structural physical training program can show beneficial changes in body composition, such as body fat reduction and muscle mass increase. This study measured body composition changes by using 3 different techniques-skinfold thickness (SF) measurements, air displacement plethysmography (BOD-POD), and dual-energy x-ray absorptiometry (DXA)-during 9 months of intense training in healthy young men engaged in military training. Twenty-seven young men were recruited from a special faction of the Italian Navy. The program previewed three phases: ground combat, sea combat, and amphibious combat. Body composition was estimated at the beginning, in the middle, and at the end of the training. After the subjects performed the ground combat phase, body composition variables significantly decreased: body weight (P < 0.05), fat-free mass (FFM) (P < 0.001), and fat mass (FM) (P < 0.03). During the amphibious combat phase, body weight increased significantly (P < 0.01), mainly because of an increase in FFM (P < 0.001) and a smaller mean decrease in FM. There was a significant difference (P < 0.05) in circumferences and SF at various sites after starting the training course. Bland-Altman analysis did not show any systematic difference between FM and FFM measured with the 3 different techniques on any occasion. On any visit, FFM and FM correlation measured by BOD-POD (P = 0.90) and DXA was significantly greater than measured by SF. A significant difference was found in body mass index (BMI) measured during the study. BOD-POD and SF, compared with DXA, provide valid and reliable measurement of changes in body composition in healthy young men engaged in military training. In conclusion, the findings suggest that for young men of normal weight, changes in body weight alone and in BMI are not a good measure to assess the effectiveness of intense physical training programs, because lean mass gain can masquerade fat weight loss.     

Validation of BIA in Obese Children and Adolescents and Re‐evaluation in a Longitudinal Study

Decrease in fat mass (FM) is a one of the aims of pediatric obesity treatment; however, measurement techniques suitable for routine clinical assessment are lacking. The objective of this study was to validate whole‐body bioelectrical impedance analysis (BIA; TANITA BC‐418MA) against the three‐component (3C) model of body composition in obese children and adolescents, and to test the accuracy of our new equations in an independent sample studied longitudinally. A total of 77 white obese subjects (30 males) aged 5–22 years, BMI‐standard deviation score (SDS) 1.6–3.9, had measurements of weight, height (HT), body volume, total body water (TBW), and impedance (Z). FM and fat‐free mass (FFM) were calculated using the 3C model or predicted from TANITA. FFM was predicted from HT²/Z. This equation was then evaluated in 17 other obese children (5 males) aged 9–13 years. Compared to the 3C model, TANITA manufacturer's equations overestimated FFM by 2.7 kg (P < 0.001). We derived a new equation: FFM = ?2.211 + 1.115 (HT²/Z), with r² of 0.96, standard error of the estimate 2.3 kg. Use of this equation in the independent sample showed no significant bias in FM or FFM (mean bias 0.5 ± 2.4 kg; P = 0.4), and no significant bias in change in FM or FFM (mean bias 0.2 ± 1.8 kg; P = 0.7), accounting for 58% (P < 0.001) and 55% (P = 0.001) of the change in FM and FFM, respectively. Our derived BIA equation, shown to be reliable for longitudinal assessment in white obese children, will aid routine clinical monitoring of body composition in this population.     

Are Ethnic and Gender Specific Equations Needed to Derive Fat Free Mass from Bioelectrical Impedance in Children of South Asian,Black African-Caribbean and White European Origin? Results of the Assessment of Body Composition in Children Study

Background

Bioelectrical impedance analysis (BIA) is a potentially valuable method for assessing lean mass and body fat levels in children from different ethnic groups. We examined the need for ethnic- and gender-specific equations for estimating fat free mass (FFM) from BIA in children from different ethnic groups and examined their effects on the assessment of ethnic differences in body fat.

Methods

Cross-sectional study of children aged 8–10 years in London Primary schools including 325 South Asians, 250 black African-Caribbeans and 289 white Europeans with measurements of height, weight and arm-leg impedance (Z; Bodystat 1500). Total body water was estimated from deuterium dilution and converted to FFM. Multilevel models were used to derive three types of equation {A: FFM = linear combination(height+weight+Z); B: FFM = linear combination(height²/Z); C: FFM = linear combination(height²/Z+weight)}.

Results

Ethnicity and gender were important predictors of FFM and improved model fit in all equations. The models of best fit were ethnicity and gender specific versions of equation A, followed by equation C; these provided accurate assessments of ethnic differences in FFM and FM. In contrast, the use of generic equations led to underestimation of both the negative South Asian-white European FFM difference and the positive black African-Caribbean-white European FFM difference (by 0.53 kg and by 0.73 kg respectively for equation A). The use of generic equations underestimated the positive South Asian-white European difference in fat mass (FM) and overestimated the positive black African-Caribbean-white European difference in FM (by 4.7% and 10.1% respectively for equation A). Consistent results were observed when the equations were applied to a large external data set.

Conclusions

Ethnic- and gender-specific equations for predicting FFM from BIA provide better estimates of ethnic differences in FFM and FM in children, while generic equations can misrepresent these ethnic differences.     

Comparison of three bioelectrical impedance methods with DXA in overweight and obese men

Objective: To compare bioelectrical impedance analysis (BIA) of body composition using three different methods against DXA in overweight and obese men. Research Methods and Procedures: Forty‐three healthy overweight or obese men (ages 25 to 60 years; BMI, 28 to 43 kg/m²) underwent BIA assessment of body composition using the ImpediMed SFB7 (version 6; ImpediMed, Ltd., Eight Mile Plains, Queensland, Australia) in multifrequency mode (Imp‐MF) and DF50 single‐frequency mode (Imp‐SF) and the Tanita UltimateScale (Tanita Corp., Tokyo, Japan). Validity was assessed by comparison against DXA using linear regression and limits of agreement analysis. Results: All three BIA methods showed good relative agreement with DXA [Imp‐MF: fat mass (FM), r² = 0.81; fat‐free mass (FFM), r² = 0.81; percentage body fat (BF%), r² = 0.69; Imp‐SF: FM, r² = 0.65; FFM, r² = 0.76; BF%, r² = 0.40; Tanita: BF%, r² = 0.44; all p < 0.001]. Absolute agreement between DXA and Imp‐MF was poor, as indicated by a large bias and wide limits of agreement (bias, ±1.96 standard deviation; FM, ?6.6 ± 7.7 kg; FFM, 8.0 ± 7.1 kg; BF%, ?7.0 ± 6.6%). Imp‐SF and Tanita exhibited a smaller bias but wide limits of agreement (Imp‐SF: FM, ?1.1 ± 8.5 kg; FFM, 2.5 ± 7.9 kg; BF%, ?1.7 ± 7.3% Tanita: BF%, 1.2 ± 9.5%). Discussion: Compared with DXA, Imp‐MF produced large bias and wide limits of agreement, and its accuracy estimating body composition in overweight or obese men was poor. Imp‐SF and Tanita demonstrated little bias and may be useful for group comparisons, but their utility for assessment of body composition in individuals is limited.     

Serial Measurements of Body Composition in Obese Subjects During a Very-Low-Energy Diet (VLED) Comparing Bioelectrical Impedance with Hydrodensitometry

Bioelectrical impedance analysis (BIA) is a convenient, inexpensive, and noninvasive technique for measuring body composition. BIA has been strongly correlated with total body water (TBW) and also has been validated against hydrodensitometry (HD). The accuracy and clinical utility of BIA and HD during periods of substantial weight loss remain controversial. We measured body composition in moderately and severely obese patients serially using both methods during a very-low-energy diet (VLED). Mean initial weight in these patients was 116 (± 30) kg (range, 74–196 kg). Mean weight loss was 24 (± 13) kg with a decrease in fat mass (FM) by HD of 20 kg (p<0.001) and a decrease in fat-free mass (FFM) of 3.6 kg (p<0.05). Loss of FFM is best predicted by the rate (kg/wk) of weight loss (r² = 0.86, p<0.0001). FFM, as predicted from BIA equations, was highly correlated with FFM as estimated by HD during all testing sessions (r=0.92-0.98). Although highly correlated, BIA overestimated FFM relative to HD and this difference appeared to be more pronounced for taller patients with greater truncal obesity. Although the discrepancy was no greater during weight-loss treatment, the level of disagreement was considerable. Therefore, the two methods cannot be used interchangeably to monitor relative changes in body composition in patients with obesity during treatment with VLED. The discrepancy between BIA and HD may be caused by body mass distribution considerations and by perturbations in TBW which affect the hydration quotient for FFM (BIA) and/or which affect the density constants for FFM and FM (HD).     

Assessing Body Composition among 3‐ to 8‐Year‐Old Children: Anthropometry,BIA, and DXA

Objective: To examine the inter‐relationships of body composition variables derived from simple anthropometry [BMI and skinfolds (SFs)], bioelectrical impedance analysis (BIA), and dual energy x‐ray (DXA) in young children. Research Methods and Procedures: Seventy‐five children (41 girls, 34 boys) 3 to 8 years of age were assessed for body composition by the following methods: BMI, SF thickness, BIA, and DXA. DXA served as the criterion measure. Predicted percentage body fat (%BF), fat‐free mass (FFM; kilograms), and fat mass (FM; kilograms) were derived from SF equations [Slaughter (SL)1 and SL2, Deurenberg (D) and Dezenberg] and BIA. Indices of truncal fatness were also determined from anthropometry. Results: Repeated measures ANOVA showed significant differences among the methods for %BF, FFM, and FM. All methods, except the D equation (p = 0.08), significantly underestimated measured %BF (p < 0.05). In general, correlations between the BMI and estimated %BF were moderate (r = 0.61 to 0.75). Estimated %BF from the SL2 also showed a high correlation with DXA %BF (r = 0.82). In contrast, estimated %BF derived from SFs showed a low correlation with estimated %BF derived from BIA (r = 0.38); likewise, the correlation between DXA %BF and BIA %BF was low (r = 0.30). Correlations among indicators of truncal fatness ranged from 0.43 to 0.98. Discussion: The results suggest that BIA has limited utility in estimating body composition, whereas BMI and SFs seem to be more useful in estimating body composition during the adiposity rebound. However, all methods significantly underestimated body fatness as determined by DXA, and, overall, the various methods and prediction equations are not interchangeable.     

Relationship between fat-to-fat-free mass ratio and decrements in leg strength after downhill running.

The purpose of this study was to determine whether greater body fat mass (FM) relative to lean mass would result in more severe muscle damage and greater decrements in leg strength after downhill running. The relationship between the FM-to-fat-free mass ratio (FM/FFM) and the strength decline resulting from downhill running (-11% grade) was investigated in 24 male runners [age 23.4 +/- 0.7 (SE) yr]. The runners were divided into two groups on the basis of FM/FFM: low fat (FM/FFM = 0.100 +/- 0.008, body mass = 68.4 +/- 1.3 kg) and normal fat (FM/FFM = 0.233 +/- 0.020, body mass = 76.5 +/- 3.3 kg, P < 0.05). Leg strength was reduced less in the low-fat (-0.7 +/- 1.3%) than in the normal-fat individuals (-10.3 +/- 1.5%) 48 h after, compared with before, downhill running (P < 0.01). Multiple linear regression analysis revealed that the decline in strength could be predicted best by FM/FFM (r2 = 0.44, P < 0.05) and FM-to-thigh lean tissue cross-sectional area ratio (r2 = 0.53, P < 0.05), with no additional variables enhancing the prediction equation. There were no differences in muscle glycogen, creatine phosphate, ATP, or total creatine 48 h after, compared with before, downhill running; however, the change in muscle glycogen after downhill running was associated with a higher FM/FFM (r = -0.56, P < 0.05). These data suggest that FM/FFM is a major determinant of losses in muscle strength after downhill running.     

Free carnitine and acetyl carnitine plasma levels and their relationship with body muscular mass in athletes

Summary The purpose of the present study was to investigate the relationship between plasma carnitine concentration and body composition variation in relation to muscular and fat masses since there is no experimentally proved correlation between plasma carnitine and body masses. We used bioelectric impedance analysis (BIA), to determine body composition and to have a complete physical fitness evaluation. The post-absorptive plasma free carnitine and acetyl carnitine plasma levels, body composition as Fat-Free Mass (FFM) and Fat Mass (FM) in kg, as well as in percent of body mass, were analysed in 33 healthy subjects. A significant negative correlation was found between plasma acetyl carnitine and FFM in weight (kg) as well as in percent of body mass (respectively p < 0.0001; p < 0.01); a significant positive correlation was found only between FM in percent and plasma acetyl carnitine (p < 0.01). The observed negative correlation between plasma acetyl carnitine and muscular mass variation might reflect an oxidative metabolic muscle improvement in relation to muscular fat free mass increment and might be evidence that muscle metabolism change is in relation to plasma acetyl carnitine concentration.     

Reliability and detecting change following short-term creatine supplementation: comparison of two-component body composition methods

The purpose of the present study was twofold: firstly, to assess the reliability of various body composition methods, and secondly, to determine the ability of the methods to estimate changes in fat-free mass (FFM) following creatine (Cr) supplementation. Fifty-five healthy male athletes (weight 78.3 +/- 10.3 kg, age 21 +/- 1 years) gave informed consent to participate in this study. Subjects' FFM was estimated by hydrostatic weighing (HW), air-displacement plethysmography (ADP), bioelectrical impedance analysis (BIA), near-infrared spectroscopy (NIR), and anthropometric measurements (ANTHRO). Measurements were taken on 2 occasions separated by 7 days to assess the reliability of the methods. Following this, 30 subjects returned to the laboratory for an additional test day following 7 days of Cr supplementation (20 g.d(-1) Cr + 140 g.d(-1) dextrose) to assess each method's ability to detect acute changes in FFM. In terms of reliability, we found excellent test-retest correlations for all 5 methods, ranging from 0.983 to 0.998 (p < 0.001). The mean biases for the 5 methods were close to 0 (range -0.1 to 0.3 kg) and their 95% limits of agreement (LOAs) were within acceptable limits (HW = -1.1 to 1.7 kg; ADP = -1.1 to 1.2 kg; BIA = -1.0 to 1.0 kg; NIR = -1.4 to 1.4 kg); however, the 95% LOAs were slightly wider for ANTHRO (-2.4 to 2.6 kg). Following Cr supplementation there was a significant increase in body mass (from 77.9 +/- 10.1 kg to 78.9 +/- 10.3 kg, p = 0.000). In addition, all 5 body composition techniques detected the change in FFM to a similar degree (mean change: HW = 0.9 +/- 0.6 kg; ADP = 0.9 +/- 0.6 kg; BIA = 0.9 +/- 0.6 kg; NIR = 0.8 +/- 0.5 kg; ANTHRO = 1.0 +/- 0.7 kg; intraclass correlation coefficient = 0.962). We conclude that between-day differences in FFM estimation were within acceptable limits, with the possible exception of ANTHRO. In addition, all 5 methods provided similar measures of FFM change during acute Cr supplementation.     

Effect of race and resistance training status on the density of fat-free mass and percent fat estimates.

The impact of race and resistance training status on the assumed density of the fat-free mass (D(FFM)) and estimates of body fatness via hydrodensitometry (%Fat(D)) vs. a four-component model (density, water, mineral; %Fat(D,W,M)) were determined in 45 men: white controls (W; n = 15), black controls (B; n = 15), and resistance-trained blacks (B-RT; n = 15). Body density by hydrostatic weighing, body water by deuterium dilution, and bone mineral by dual-energy X-ray absorptiometry were used to estimate %Fat(D,W,M). D(FFM) was not different between B and W (or 1.1 g/ml); however, D(FFM) in B-RT was significantly lower (1.091 +/- 0.012 g/ml; P < 0.05). Therefore, %Fat(D) using the Siri equation was not different from %Fat(D,W,M) in W (17.5 +/- 5.0 vs. 18.3 +/- 5.4%) or B (14.9 +/- 5.6 vs. 15.7 +/- 5.7%) but significantly overestimated %Fat(D,W,M) in B-RT (14.0 +/- 5.9 vs. 10.4 +/- 6.0%; P < 0.05). The use of a race-specific equation (assuming D(FFM) = 1.113 g/ml) did not improve the agreement between %Fat(D) and %Fat(D,W,M), resulting in a significantly greater mean (+/-SD) discrepancy for B (1.7 +/- 1.8% fat) and B-RT (6.2 +/- 4.3% fat). Thus race per se does not affect D(FFM) or estimates of %Fat(D); however, B-RT have a D(FFM) lower than 1.1 g/ml, leading to an overestimation of %Fat(D).     

Prediction of Fatness by Standing 8‐Electrode Bioimpedance: A Multiethnic Adolescent Population

The objective of this study was to validate an 8‐electrode bioimpedance analysis (BIA₈) device (BC‐418; Tanita, Tokyo, Japan) for use in populations of European, Maori, Pacific Island, and Asian adolescents. Healthy adolescents (215 M, 216 F; 129 Pacific Island, 120 Asian, 91 Maori, and 91 European; age range 12–19 years) were recruited by purposive sampling of high schools in Auckland, New Zealand. Weight, height, sitting height, leg length, waist circumference, and whole‐body impedance were measured. Fat mass (FM) and fat‐free mass (FFM) derived from the BIA₈ manufacturer's equations were compared with measurements by dual‐energy X‐ray absorptiometry (DXA). DXA‐measured FFM was used as the reference to develop prediction equations based on impedance. A double cross‐validation technique was applied. BIA₈ underestimated FM by 2.06 kg (P < 0.0001) and percent body fat (%BF) by 2.84% (P < 0.0001), on average. However, BIA₈ tended to overestimate FM and %BF in lean and underestimate FM and %BF in fat individuals. Sex‐specific equations developed showed acceptable accuracy on cross‐validation. In the total sample, the best prediction equations were, for boys: FFM (kg) = 0.607 height (cm)²/impedance (Ω) + 1.542 age (y) + 0.220 height (cm) + 0.096 weight (kg) + 1.836 ethnicity (0 = European or Asian, 1 = Maori or Pacific) ? 47.547, R² = 0.93, standard error of estimate (SEE) = 3.09 kg; and, for girls: FFM (kg) = 0.531 height (cm)²/impedance (Ω) + 0.182 height (cm) + 0.096 weight (kg) + 1.562 ethnicity (0 = non‐Pacific, 1 = Pacific) ? 15.782, R² = 0.91, SEE = 2.19 kg. In conclusion, equations for fatness estimation using BIA₈ developed for our sample perform better than reliance on the manufacturer's estimates. The relationship between BIA and body composition in adolescents is ethnicity dependent.     

Physique, body composition and maximum oxygen consumption of selected soccer players of Kunimi High School, Nagasaki, Japan

This study evaluates the physical and physiological ability of selected soccer players of Kunimi High School in Nagasaki Prefecture, Japan. The Kunimi team is famous for its intensive training, and had won the championship of the All Japan High School Soccer Tournament six times by 2003. We measured physique, body composition, and maximal oxygen uptake of 72 members aged between 16 and 18 years old between 1986 and 1994. They consisted of 66 outfield players (12 forward players, 23 midfielders, 31 defenders) and 6 goalkeepers. Body density was measured by the under-water weighing method, and Brozek's equation was applied to calculate percentage body fat (%Fat, %), fat-free mass (FFM, kg), FFM/height (FFM/Ht, kg.m(-1)), and FFM index (FFM/Ht(3), kg.m(-3)). The following results were obtained: 1. The average of 66 outfield players was 172.7 cm of height, 64.6 kg of weight, 54.0 cm of girth of thigh, and 90.0 cm of girth of hip, 9.3% of %Fat, 58.6 kg of FFM, 33.9 kg.m(-1) of FFM/Ht and 113.8 kg.m(-3) of FFM index. The mean vital capacity was 4.25 L and total lung capacity was 5.58 L. The mean maximal ventilation was 138.7 L.min(-1), VO(2)max was 3.95 L.min(-1), and VO(2)max/Wt was 61.4 ml.kg(-1).min(-1). 2. Goalkeepers were taller and heavier than outfielders, and had a smaller mean value of VO(2)max/Wt than outfielders (p<0.01). 3. For 23 out of the 72 players measured twice with an interval of about one year, FFM increased and %Fat reduced significantly, while V(E)max, VO(2)max and VO(2)max/Wt did not change. Kunimi players of the present study had as large a VO(2)max/Wt as local players, and a similar or slightly smaller VO(2)max/Wt than national-level players. They had similar %Fat and a similar VO(2)max/Wt with professional soccer players in England (Davis et al., 1992) while they had much smaller physiques.     

Percentage of total body fat as estimated by three automatic bioelectrical impedance analyzers

The present study aimed to compare the accuracy of estimating the percentage of total body fat (%TBF) among three bioelectrical impedance analysis (BIA) devices: a single-frequency BIA with four tactile electrodes (SF-BIA4), a single-frequency BIA with eight tactile electrodes (SF-BIA8) and a multi-frequency BIA with eight tactile electrodes (MF-BIA8). Dual-energy x-ray absorptiometry (DXA) and hydrostatic weighing (HW) were used as references for the measured values. Forty-five healthy college student volunteers (21 males: 172.9 +/- 5.5 cm and 65.8 +/- 9.1 kg and 24 females: 160.7 +/- 6.6 cm, 52.6 +/- 6.2 kg) were the subjects. Correlation coefficients between the BIA measurements and the references were calculated. The standard error of estimation (SEE) was calculated by regression analysis when estimating the reference measures (DXA and HW) from the predictor (SF-BIA4, SF-BIA8 and MF-BIA8). The differences in %TBF between the reference and the predictor, calculated by the reference minus the predictor, were plotted against the %TBF measured by the references. The MF-BIA 8 here showed the highest correspondence to the reference and the least estimation error compared with the other BIA methods. It is considered that there is a limit to directly estimate FFM from a regression equation using impedance, weight, height and age as independent variables, and that %TBF can be more accurately estimated by measuring segmental impedances using eight electrodes and multi-frequency electric currents and then estimating total body water from these impedances.     

Body composition and sleeping metabolic rate in response to a 5-month endurance-training programme in adults

This study examined the effect of exercise training on body composition and sleeping metabolic rate (SMR) in 15 men and 13 women who participated in a 20-week training programme aimed at running a half marathon. Body mass (BM) was measured after waking up, fasted and with an empty bladder. Body composition was assessed using densitometry. The SMR was measured from 0300-0600 hours during an overnight sleep in a respiration chamber. Assessment of SMR was at least 36 h after the last period of exercise training. After 20 weeks of endurance training no change in BM was observed. However, body composition changed significantly. On average men lost 2.4 kg body fat (P less than 0.01) and gained 1.7 kg fat free mass (FFM) (P less than 0.01). In women fat loss averaged 0.9 kg after 20 weeks (P less than 0.01), while FFM increased by 1.0 kg (P less than 0.05). Loss of fat mass was significantly larger in males (P less than 0.05). No changes in SMR were found, either in absolute terms, or when normalised for BM or FFM. Therefore, we have concluded that exercise training has no chronic, long-term effect on SMR. A possible explanation for this outcome in view of the different findings in similar studies is discussed.     

Adipose tissue distribution in relation to insulin resistance in type 2 diabetes mellitus

Insulin resistance (IR) is typically more severe in obese individuals with type 2 diabetes (T2DM) than in similarly obese non-diabetics but whether there are group differences in body composition and whether such differences contribute to the more severe IR of T2DM is uncertain. DEXA and regional CT imaging were conducted to assess adipose tissue (AT) distribution and fat content in liver and muscle in 67 participants with T2DM (F39/M28, age 60 +/- 7 yr, BMI 34 +/- 3 kg/m(2)) and in 35 similarly obese, non-DM volunteers (F20/M15, age 55 +/- 8 yr, BMI 33 +/- 2 kg/m(2)). A biopsy of subcutaneous abdominal AT was done to measure adipocyte size. A glucose clamp was performed at an insulin infusion of 80 mU x min(-1) x m(-2). There was more severe IR in T2DM (6.1 +/- 2.3 vs. 9.9 +/- 3.3 mg x min(-1) x kg FFM(-1); P < 0.01). Group comparisons of body composition parameters was performed after adjusting for the effect of age, gender, race, height and total fat mass (FM). T2DM was associated with less leg FM (-1.2 +/- 0.4 kg, P < 0.01), more trunk FM (+1.1 +/- 0.4 kg, P < 0.05), greater hepatic fat (P < 0.05), and more subfascial adipose tissue around skeletal muscle (P < 0.05). There was a significant group x sex interaction for VAT (P < 0.01), with greater VAT in women with T2DM (P < 0.01). Mean adipocyte size (AS) did not significantly differ across groups, and smaller AS was associated with increased leg FM, whereas larger AS was related to more trunk FM (both P < 0.05). Group differences in IR were less after adjusting for group differences in leg FM, trunk FM, and hepatic fat, but these adjustments only partially accounted for the greater severity of IR in T2DM. In summary, T2DM, compared with similarly obese nondiabetic men and women, is associated with less leg FM and greater trunk FM and hepatic fat.     

A new BIA equation estimating the body composition of young children

Bioelectric impedance analyses (BIA) provides a valid and reliable measure of body composition in field, clinical, and research settings if standard protocol procedures are followed, and population-specific equations are available and utilized. The objective of this study was to create and cross-validate a new BIA body composition equation with representative healthy weight (HW), overweight (OW), and obese (OB) young children. Participants were 436 children who were 5-11 years of age. Dual-energy absorptiometry fat-free mass (FFM) was used as the criterion measure and a single frequency tetra-polar BIA device was used to create the new BIA equation. The new BIA equation explained 95.2% of the variance in FFM with no statistical shrinkage upon cross-validation. The use of this equation may help to identify effective intervention strategies to prevent or combat childhood obesity, and may assist in additional conditions or treatments where information concerning body composition measures would provide greater accuracy and sensitivity measures for preventing or combating disease.     

Segmental body composition assessment for obese Japanese adults by single-frequency bioelectrical impedance analysis with 8-point contact electrodes

This study aimed to determine the accuracy of segmental body composition variables estimated by single-frequency BIA with 8-point contact electrodes (SF-BIA8), compared with dual-energy X-ray absorptiometry (DXA). Subjects were 72 obese Japanese adults (43 males and 29 females) aged 30 to 66 years. Segmental body composition variables (fat free mass: FFM, fat mass: FM, and percent fat mass: %FAT) were measured by these techniques. The correlations between impedance values and FFM measured by DXA were calculated. To examine the consistency in predicted values (SF-BIA8) with the reference (DXA), significant mean differences were tested by t-test and the degree of the difference was assessed by effect size. Correlations between the reference and predicted values were calculated. Additionally, the standard error of estimation (SEE) when estimating the reference from the predictor and the relative value of the SEE to the mean value of the DXA measurement (%SEE) were calculated. Systematic error was examined by Bland-Altman plots. High correlations were found between impedance and FFM measured by SF-BIA8. FFM in the extremities showed high correlations with the reference values, but systematic error was found. SF-BIA8 tended to overestimate FFM in the trunk. The consistencies in %FAT and FM with the reference value are inferior to those for FFM, and SEE values in %FAT and FM were greater than those for FFM. The accuracy of the estimated values in the trunk (FFM, %FAT, and FM) are inferior to those of the total body and extremities.     

Effect of high contents of dietary animal-derived protein or carbohydrates on canine faecal microbiota

Background

Few equations have been developed in veterinary medicine compared to human medicine to predict body composition. The present study was done to evaluate the influence of weight loss on biometry (BIO), bioimpedance analysis (BIA) and ultrasonography (US) in cats, proposing equations to estimate fat (FM) and lean (LM) body mass, as compared to dual energy x-ray absorptiometry (DXA) as the referenced method. For this were used 16 gonadectomized obese cats (8 males and 8 females) in a weight loss program. DXA, BIO, BIA and US were performed in the obese state (T0; obese animals), after 10% of weight loss (T1) and after 20% of weight loss (T2). Stepwise regression was used to analyze the relationship between the dependent variables (FM, LM) determined by DXA and the independent variables obtained by BIO, BIA and US. The better models chosen were evaluated by a simple regression analysis and means predicted vs. determined by DXA were compared to verify the accuracy of the equations.

Results

The independent variables determined by BIO, BIA and US that best correlated (p?<?0.005) with the dependent variables (FM and LM) were BW (body weight), TC (thoracic circumference), PC (pelvic circumference), R (resistance) and SFLT (subcutaneous fat layer thickness). Using Mallows??Cp statistics, p value and r ² , 19 equations were selected (12 for FM, 7 for LM); however, only 7 equations accurately predicted FM and one LM of cats.

Conclusions

The equations with two variables are better to use because they are effective and will be an alternative method to estimate body composition in the clinical routine. For estimated lean mass the equations using body weight associated with biometrics measures can be proposed. For estimated fat mass the equations using body weight associated with bioimpedance analysis can be proposed.