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.     

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.     

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.     

Use of bioelectrical impedance to assess body composition changes at high altitude.

This study determined the feasibility of using bioelectrical impedance analysis (BIA) to assess body composition alterations associated with body weight (BW) loss at high altitude. The BIA method was also evaluated relative to anthropometric assessments. Height, BW, BIA, skinfold (SF, 6 sites), and circumference (CIR, 5 sites) measurements were obtained from 16 males (23-35 yr) before, during, and after 16 days of residence at 3,700-4,300 m. Hydrostatic weighings (HW) were performed pre- and postaltitude. Results of 13 previously derived prediction equations using various combinations of height, BW, age, BIA, SF, or CIR measurements as independent variables to predict fat-free mass (FFM), fat mass (FM), and percent body fat (%Fat) were compared with HW. Mean BW decreased from 84.74 to 78.84 kg (P less than 0.01). As determined by HW, FFM decreased by 2.44 kg (P less than 0.01), FM by 3.46 kg (P less than 0.01), and %Fat by 3.02% (P less than 0.01). The BIA and SF methods overestimated the loss in FFM and underestimated the losses in FM and %Fat (P less than 0.01). Only the equations utilizing the CIR measurements did not differ from HW values for changes in FFM, FM, and %Fat. It was concluded that the BIA and SF methods were not acceptable for assessing body composition changes at altitude.     

Relationships of resting energy expenditure with body fat distribution and abdominal fatness in Japanese population

Body fat distribution and abdominal fatness are indicators of risks for coronary heart disease. However, the relationships between resting energy expenditure (REE) and the body fat distribution or the abdominal fatness are unclear. We examined the relationships of REE with whole-body fat distribution (waist, hip and waist-to-hip ratio: WHR) and abdominal fatness (intra-abdominal fat: IF and subcutaneous fat: SF) after adjustment for body composition. 451 men and 471 women were subdivided into two groups, 40-59 years: middle-aged group and 60-79 years: elderly group. REE was measured by an indirect calorimetry system. Percentage of fat mass (%FM), fat mass (FM) and fat-free mass (FFM) were assessed by a dual-energy x-ray absorptiometry method. The IF area (IFA) and SF area (SFA) at the level of the umbilicus were measured using computed tomography. Circumference of waist and hip were measured in a standing position. The WHR, waist circumference and SFA did not significantly (p>0.05) associate with the REE after adjusting for FM, FFM and age in any of the groups. The adjusted REE was significantly and inversely correlated with hip (r=-0.159, p<0.05) and IFA (r=-0.131, p<0.05) in the elderly men. These results suggest that lower REE may contribute to greater hip and IFA rather than WHR and waist in elderly men.     

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.     

Dual-energy X-ray absorptiometry (DXA) can accurately and nondestructively measure the body composition of small, free-living rodents

Dual-energy x-ray absorptiometry (DXA) is a nondestructive technique that can potentially measure specific components of whole-body composition in free-living and lab-raised animals. Our aim was to test the ability of DXA to measure the composition of a common arvicoline rodent, the northern red-backed vole (Clethrionomys rutilus). We used a DXA apparatus to obtain measurements of fat mass (FM), lean mass (LM),bone mineral content, bone mineral density, and fat-free mass(FFM) in carcasses of free-living and lab-raised voles. We then used chemical carcass analysis to derive predictive algorithms for actual values of FM, total body water, total protein, total mineral, LM, and FFM. Unexplained error in the equations for all voles grouped collectively ranged from R(2) = 0.82 to R(2) = 0.98. The DXA FM measurement had the highest coefficient of variation, and it was higher for free-living voles than for lab-raised voles. However, FM can be determined by difference with excellent precision by using the FFM equation (R(2) = 0.98). We also derived corrective terms for passive integrated transponder-tagged animals. Thus, DXA is a nonlethal, nondestructive tool capable of precisely and accurately measuring many specific parameters of whole-body composition in small free-living and lab-raised rodents.     

A Weight Reduction Program Preserves Fat‐Free Mass but Not Metabolic Rate in Obese Adolescents

Objective: To determine the effects of a multidisciplinary weight reduction program on body composition and energy expenditure (EE) in severely obese adolescents. Research Methods and Procedures: Twenty‐six severely obese adolescents, 12 to 16 years old [mean BMI: 33.9 kg/m²; 41.5% fat mass (FM)] followed a 9‐month weight reduction program including moderate energy restriction and progressive endurance and resistance training. Body composition was assessed by DXA, basal metabolic rate by indirect calorimetry, and EE by whole‐body indirect calorimetry with the same activity program over 36‐hour periods before starting and 9 months after the weight reduction period. Results: Adolescents gained (least‐square mean ± SE) 2.9 ± 0.2 cm in height, lost 16.9 ± 1.3 kg body weight (BW), 15.2 ± 0.9 kg FM, and 1.8 ± 0.5 kg fat‐free mass (FFM) (p < 0.001). Basal metabolic rate, sleeping, sedentary, and daily EE were 8% to 14% lower 9 months after starting (p < 0.001) and still 6% to 12% lower after adjustment for FFM (p < 0.05). Energy cost of walking decreased by 22% (p < 0.001). The reduction in heart rate during sleep and sedentary activities (?10 to ?13 beats/min), and walking (?20 to ?25 beats/min) (p < 0.001) resulted from both the decrease in BW and physical training. Discussion: A weight reduction program combining moderate energy restriction and physical training in severely obese adolescents resulted in great BW and FM losses and improvement of cardiovascular fitness but did not prevent the decline in EE even after adjustment for FFM.     

Muscularity and the density of the fat-free mass in athletes.

The purpose of this study was to use estimates of body composition from a four-component model to determine whether the density of the fat-free mass (D(FFM)) is affected by muscularity or musculoskeletal development in a heterogenous group of athletes and nonathletes. Measures of body density by hydrostatic weighing, body water by deuterium dilution, bone mineral by whole body dual-energy X-ray absorptiometry (DXA), total body skeletal muscle estimated from DXA, and musculoskeletal development as measured by the mesomorphy rating from the Heath-Carter anthropometric somatotype were obtained in 111 collegiate athletes (67 men and 44 women) and 61 nonathletes (24 men and 37 women). In the entire group, D(FFM) varied from 1.075 to 1.127 g/cm3 and was strongly related to the water and protein fractions of the fat-free mass (FFM; r = -0.96 and 0.89) and moderately related to the mineral fraction of the FFM (r = 0.65). Skeletal muscle (%FFM) varied from 40 to 68%, and mesomorphy varied from 1.6 to 9.6, but neither was significantly related to D(FFM) (r = 0.11 and -0.14) or to the difference between percent fat estimated from the four-component model and from densitometry (r = 0.09 and -0.16). We conclude that, in a heterogeneous group of young adult athletes and nonathletes, D(FFM) and the accuracy of estimates of body composition from body density using the Siri equation are not related to muscularity or musculoskeletal development. Athletes in selected sports may have systematic deviations in D(FFM) from the value of 1.1 g/cm3 assumed in the Siri equation, resulting in group mean errors in estimation of percent fat from densitometry of 2-5% body mass, but the cause of these deviations is complex and not simply a reflection of differences in muscularity or musculoskeletal development.     

QDR 4500A DXA overestimates fat-free mass compared with criterion methods.

This study evaluated the accuracy with which the dual-energy X-ray absorptiometer (Hologic QDR 4500A) measured fat-free mass (FFM), fat mass (FM), and hydration of FFM. In a study of 58 men and women (ages 70-79 yr), the QDR 4500A was found to provide a systematically higher estimate of FFM and lower estimate of FM than a four-component model of body composition. A correction factor from this study was developed and applied to two other samples (n = 13 and 37). We found mean corrected levels of FFM and FM to be equivalent to that obtained by the four-component model or total body water. In addition, the hydration of the corrected FFM was closer to the established hydration level in adult samples and that obtained from the four-component model. These findings suggest that the current calibration of the fan-beam system of the Hologic QDR 4500A provides an overestimate of FFM and underestimate of FM compared with reference methods.     

Relationship of Body Composition to Body‐Fatness Estimation in Japanese University Students

Objective: To examine the relationship between self‐estimated whole body size and fatness and whole body and regional composition, and the relationship between self‐estimated whole body fatness and self‐estimated regional fatness in Japanese university students. Research Methods and Procedures: This was a cross‐sectional study using Japanese university students (110 men and 79 women). The percentage of body fat, fat mass (FM), and fat‐free mass (FFM) were measured by underwater weighing and used as body composition variables. Subcutaneous fat thicknesses were determined at seven sites by ultrasonography to estimate regional body composition, and six circumferences and four breadths to estimate regional size. Relative body size and fatness were self‐estimated using a questionnaire. Results: Only women tended to estimate themselves as being fatter than they actually were. Self‐estimated body fatness moderately correlated with the percentage of body fat (men, r = 0.41; women, r = 0.40) FM (men, r = 0.50; women, r = 0.51), and body mass index (r = 0.56 for men and 0.56 for women). After adjusting for the percentages of body fat and FM, self‐estimated fatness correlated with body mass index (r = 0.31 for men and r = 0.37 for women). Among self‐estimated regional fatness, self‐estimated abdominal fatness had the strongest correlation with self‐estimated whole body fatness in both genders. Discussion: The low correlation between estimated and actual body fatness in both genders indicates that Japanese university students, especially women, inaccurately estimate their percentage of body fat. In fact, both men and women primarily estimate their whole body fatness by body weight relative to height.     

Energy imbalance underlying the development of childhood obesity

Objective: To develop a model based on empirical data and human energetics to predict the total energy cost of weight gain and obligatory increase in energy intake and/or decrease in physical activity level associated with weight gain in children and adolescents. Research Methods and Procedures: One‐year changes in weight and body composition and basal metabolic rate (BMR) were measured in 488 Hispanic children and adolescents. Fat‐free mass (FFM) and fat mass (FM) were measured by DXA and BMR by calorimetry. Model specifications include the following: body mass (BM) = FFM + FM, each with a specific energy content, cff (1.07 kcal/g FFM) and cf (9.25 kcal/g FM), basal energy expenditure (EE), kff and kf, and energetic conversion efficiency, eff (0.42) for FFM and ef (0.85) for FM. Total energy cost of weight gain is equal to the sum of energy storage, EE associated with increased BM, conversion energy (CE), and diet‐induced EE (DIEE). Results: Sex‐ and Tanner stage–specific values are indicated for the basal EE of FFM (kff) and the fat fraction in added tissue (fr). Total energy cost of weight gain is partitioned into energy storage (24% to 36%), increase in EE (40% to 57%), CE (8% to 13%), and DIEE (10%). Observed median (10th to 90th percentile) weight gain of 6.1 kg/yr (2.4 to 11.4 kg/yr) corresponds at physical activity level (PAL) = 1.5, 1.75, and 2.0 to a total energy cost of weight gain of 244 (93 to 448 kcal/d), 267 (101 to 485 kcal/d), and 290 kcal/d (110 to 527 kcal/d), respectively, and to a total energy intake of 2695 (1890 to 3730), 3127 (2191 to 4335), and 3551 (2487 to 4930) kcal/d, respectively. If weight gain is caused by a change in PAL alone and PAL₀ = 1.5 at baseline t = 0, the model indicates a drop in PAL of 0.22 (0.08 to 0.34) units, which is equivalent to 60 (18 to 105) min/d of walking at 2.5 mph. Discussion: Halting the development or progression of childhood obesity, as observed in these Hispanic children and adolescents, by counteracting its total energy costs will require a sizable decrease in energy intake and/or reciprocal increase in physical activity.     

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.     

Accuracy and precision of dual-energy X-ray absorptiometry for body composition measurements in rhesus monkeys

Accuracy of body composition measurements by dual-energy X-ray absorptiometry (DXA) was compared with direct chemical analysis in 10 adult rhesus monkeys. DXA was highly correlated (r-values > 0.95) with direct analyses of body fat mass (FM), lean mass (LM) and lumbar spine bone mineral content (BMC). DXA measurements of total body BMC were not as strongly correlated (r-value = 0.58) with total carcass ash content. DXA measurements of body FM, LM and lumbar spine BMC were not different from data obtained by direct analyses (P-values > 0.30). In contrast, DXA determinations of total BMC (TBMC) averaged 15%, less than total carcass ash measurements (P = 0.002). In conclusion, this study confirms the accurate measurement of fat and lean tissue mass by DXA in rhesus monkeys. DXA also accurately measured lumbar spine BMC but underestimated total body BMC as compared with carcass ash determinations.     

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.     

Cross-Validation of Fat-Free Mass Estimated From Body Density Against Bioelectrical Resistance: Effects of Obesity and Gender

GORAN, MICHAEL I AND M ABU KHALED. Cross-validation of fat-free mass estimated from body density against bioelectrical resistance: effects of obesity and gender. Obes Res. The major purpose of this study was to examine whether estimates of body composition from bioelectrical resistance were systematically biased by obesity and/or gender (using hydrodensitometry as a comparison method). We compared fat-free mass (FFM) by bioelectrical resistance (BR) using 5 equations (Lukaski, Kushner, Rising, Khaled, and Segal) to FFM by hydrodensitometry (HD) in 20 lean men, 30 lean women, 33 obese men and 22 obese women. None of the BR equations was successfully cross-validated against FFM by HD in all 4 sub-groups. The Lukaski equation significantly underestimated FFM in all 4 groups by 2.7 to 4.7 kg; the Kushner equation significantly underestimated FFM by 2.0 to 2.9 kg except in obese women; the Rising equation significantly overestimated FFM in obese women (5.3 kg) and men (2.9 kg); the Khaled equation successfully predicted FFM in all groups except obese men; and the Segal equation successfully predicted FFM in all groups except lean men. In some groups, a portion of the discrepancy could be explained by bias originating from body fat. Analysis of our data by forward regression analysis demonstrated that height²/resistance, body weight, gender and suprailiac skinfold thickness provide the most accurate estimates of FFM (R²=0.92; SEE = 3.58kg) that are free of bias originating from gender and body fat. We conclude that the estimation of fat-free mass by BR is significantly influenced by gender and obesity. An alternative equation is proposed for estimating fat-free mass based on measurement of height²/resistance, body weight, gender and suprailiac skinfold thickness.     

Accuracy of body composition measurements by dual energy x-ray absorptiometry in underweight patients with chronic intestinal disease and in lean subjects

BACKGROUND: To assess the accuracy of Dual-energy X-ray absorptiometry (DXA) in underweight patients with chronic gastrointestinal disease, we investigated the ability of DXA to detect variations in body composition induced by infusion of parenteral nutrition (PN). Furthermore, the influence of a low body weight per se on the accuracy of DXA was studied by placing packets of lard on lean healthy subjects. METHODS: The hydration study included 11 patients with short bowel syndrome on long-term home parenteral nutrition (9 women and 2 men), and (mean +/- SD) 49.5 +/- 17.1 yr., 19.3 +/- 3.1 kg/m2. The lard study, where packets of lard were placed either over the thighs or the trunk region, was performed in 8 healthy lean male volunteers, 26.4 +/- 7.4 yr., and 21.0 + 0.9 kg/m2. Body composition, including measures of the total mass (TM), soft tissue mass (STM), lean tissue mass (LTM), fat mass (FM), and total body mineral content (TBBMC), was assessed by DXA. The fat fraction of the lard packets (3.49 kg), measured in triplicate by chemical fat extraction, was 52.2%. RESULTS: Hydration study; The increase in scale weight (BW) of approximately 0.90 kg due to infusion of PN correlated significantly to the increase in TM (R-square = 0.72, SEE 0.36 kg, p < 0.01), and the increase in STM (R-square = 0.69, SEE 0.38 kg, p < 0.01), however not with the increase LTM (R-square = 0.30, SEE 1.06 kg, p = 0.08). Mean changes in TM (0.88 kg), STM (0.88 kg), and LTM (0.81 kg) were not significantly different from changes in BW (p > 0.05). Lard study; Regardless of position, measurements of FM and LTM of the added lard were not significantly different from expected values. However, the composition of the lard packets into FM and LTM was more accurately detected when the packets were placed over the thighs than over the trunk region. The accuracy of DXA in individual subjects, expressed as the SD of the difference between expected and measured values, was 1.03 kg and 1.06 kg for the detection of changes in LTM and FM, respectively, and 0.18 kg for the detection of changes in STM and TM. CONCLUSIONS: On a group level, DXA provided sufficient accuracy to detect small changes in body composition in underweight patients with chronic gastrointestinal disease. However, the accuracy errors were higher than reported in normal weight subjects. The accuracy was not influenced by a low body weight per se.     

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.     

Familial resemblance of body composition,physical activity,and resting metabolic rate in pre-school children

Background:

Although parental obesity is a well-established predisposing factor for the development of obesity, associations between regional body compositions, resting metabolic rates (RMR), and physical activity (PA) of parents and their pre-school children remain unknown. The objective of this study was to investigate parent-child correlations for total and regional body compositions, resting energy expenditures, and physical activity.

Methods:

Participants were 89 children aged 2-6 years and their parents, consisting of 61 families. Resting metabolic rate was assessed using indirect calorimetry. Total and regional body compositions were measured by both dual energy X-ray absorptiometry (DXA) and deuterium dilution. Physical activity was assessed by an accelerometer.

Results:

There was a significant parent-offspring regression for total fat free mass (FFM) between children and their mothers (P=0.02), fathers (P=0.02), and mid-parent (average of father and mother value) (P=0.002) when measured by DXA. The same was true for fat mass (FM) between children and mothers (P<0.01), fathers (P=0.02), and mid-parent (P=0.001). There was no significant association between children and parents for physical activity during the entire week, weekend, weekdays, and different parts of days, except for morning activity, which was positively related to the mothers’ morning activities (P<0.01) and mid-parent (P=0.009). No association was found between RMR of children and parents before and after correction for FFM and FM.

Conclusion:

These data suggest a familial resemblance for total body composition between children and their parents. Our data showed no familial resemblance for PA and RMR between children and their parents. Key Words: Obesity, Familial resemblance, Children, Resting metabolic rate, Physical activity     

Age and sex variation in measures of body composition among the elderly Bengalee Hindus of Calcutta, India

In the present cross-sectional study we examined 332 (171 men and 161 women) elderly (60 years and above) urban Bengalee Hindu resident in south Calcutta, India. Individuals were selected by random sampling procedure using local voter's registration list. Skin folds measures were used to compute body composition measures among them. There existed significant sex differences in various anthropometric body composition measures. Age had significant (p < 0.001) negative association with all anthropometric body composition measures namely percentage of body fat (PBF), fat mass (FM), arm muscle circumference (AMC), arm muscle area (AMA) and arm fat area (AFA) in both sexes. Fat free mass (FFM) in contrast had negative but not significant age impact. Regression analyses demonstrated that age had explained substantial amount of variance of PBF (men = 32%; women = 18.2%), FM (men = 18.2%; women = 12.8%), AMC (men = 23.4%; women = 19.2%), AMA (men = 22.2%; women = 10.2%) and AFA (men = 34%; women = 31%) in both sexes. Two-way ANOVA revealed age-sex interaction only had significant effect on FFM. The present investigation vindicated that there is a significant inverse age trends in anthropometric body composition measures among the Bengalee Hindus. Moreover, there existed sexual dimorphism in the effect of age on various anthropometric body composition measures.