Body Composition at 6 months of Life: Comparison Of Air Displacement Plethysmography and Dual‐Energy X‐Ray Absorptiometry

Body composition assessment during infancy is important because it is a critical period for obesity risk development, thus valid tools are needed to accurately, precisely, and quickly determine both fat and fat‐free mass. The purpose of this study was to compare body composition estimates using dual‐energy x‐ray absorptiometry (DXA) and air displacement plethysmography (ADP) at 6 months old. We assessed the agreement between whole body composition using DXA and ADP in 84 full‐term average‐for‐gestational‐age boys and girls using DXA (Lunar iDXA v11–30.062; Infant whole body analysis enCore 2007 software, GE, Fairfield, CT) and ADP (Infant Body Composition System v3.1.0, COSMED USA, Concord, CA). Although the correlations between DXA and ADP for %fat (r = 0.925), absolute fat mass (r = 0.969), and absolute fat‐free mass (r = 0.945) were all significant, body composition estimates by DXA were greater for both %fat (31.1 ± 3.6% vs. 26.7 ± 4.7%; P < 0.001) and absolute fat mass (2,284 ± 449 vs. 1,921 ± 492 g; P < 0.001), and lower for fat‐free mass (5,022 ± 532 vs. 5,188 ± 508 g; P < 0.001) vs. ADP. Inter‐method differences in %fat decreased with increasing adiposity and differences in fat‐free mass decreased with increasing infant age. Estimates of body composition determined by DXA and ADP at 6 months of age were highly correlated, but did differ significantly. Additional work is required to identify the technical basis for these rather large inter‐method differences in infant body composition.     

Bioelectrical impedance underestimates total and truncal fatness in abdominally obese women

Objective: To compare estimates of total and truncal fatness from eight‐electrode bioelectrical impedance analysis equipment (BIA₈) with those from DXA in centrally obese women. The secondary aim was to examine BMI and waist circumference (WC) as proxy measures for percentage total body fat (%TBF) and truncal body fat percentage (tr%BF). Research Methods and Procedures: This was a cross‐sectional study of 136 women (age, 48.1 ± 7.7 years; BMI, 30.4 ± 2.9 kg/m²; %TBF_DXA, 46.0 ± 3.7%; WC, 104 ± 8 cm). Fatness was measured by DXA and Tanita BC‐418 equipment (Tanita Corp., Tokyo, Japan). Agreement among methods was assessed by Bland‐Altman plots, and regression analysis was used to evaluate anthropometric measures as proxies for total and abdominal fatness. Results: The percentage of overweight subjects was 41.9%, whereas 55.9% of the subjects were obese, as defined by BMI, and all subjects had a WC exceeding the World Health Organization cut‐off point for abdominal obesity. Compared with DXA, the BIA₈ equipment significantly underestimated total %BF (?5.0; ?3.6 to ?8.5 [mean; 95% confidence interval]), fat mass (?3.6; ?3.9 to ?3.2), and tr%BF (?8.5; ?9.1 to ?7.9). The discrepancies between the methods increased with increasing adiposity for both %TBF and tr%BF (both p < 0.001). Variation in BMI explained 28% of the variation in %TBF_DXA and 51% of %TBF_BIA8. Using WC as a proxy for truncal adiposity, it explained only 18% of tr%BF_DXA variance and 27% of tr%BF_BIA8 variance. The corresponding figures for truncal fat mass were 49% and 35%, respectively. No significant age effects were observed in any of the regressions. Discussion: BIA₈ underestimated both total and truncal fatness, compared with DXA, with higher dispersion for tr%BF than %TBF. The discrepancies increased with degree of adiposity, suggesting that the accuracy of BIA is negatively affected by obesity.     

Comparison of Methods to Assess Body Composition Changes during a Period of Weight Loss

Objective: To assess the accuracy of body composition measurements by air displacement plethysmography and bioelectrical impedance analysis (BIA) compared with DXA during weight loss. Research Methods and Procedures: Fifty‐six healthy but overweight participants, 34 women and 22 men (age, 52 ± 8.6 years; weight, 92.2 ± 11.6 kg; BMI, 33.3 ± 2.9 kg/m²) were studied in an outpatient setting before and after 6 months of weight loss (weight loss, 5.6 ± 5.5 kg). Subjects were excluded if they had initiated a new drug therapy within 30 days of randomization, were in a weight loss program, or took a weight loss drug within 90 days of randomization. Subjects were randomly assigned either to a self‐help program, consisting of two 20‐minute sessions with a nutritionist and provision of printed materials and other self‐help resources, or to attendance at meetings of a commercial program (Weight Watchers). Body composition was examined by each of the methods before and after weight loss. Results: BIA (42.4 ± 5.8%) underestimated percentage fat, whereas the BodPod (Siri = 51.7 ± 6.9%; Brozek = 48.5 ± 6.5%) overestimated percentage fat compared with DXA (46.1 ± 7.9%) before weight loss. Correlation coefficients for detecting changes in body composition between DXA and the other methods were relatively high, with Brozek Δfat mass (FM; r² = 0.63), Siri FM (r² = 0.65), tetrapolar BIA percentage fat (r² = 0.57), and Tanita FM (r² = 0.61) being the highest. Discussion: In conclusion, all of the methods were relatively accurate for assessing body composition compared with DXA, although there were biases. Furthermore, each of the methods was sensitive enough to detect changes with weight loss.     

Comparison of body composition methods in overweight and obese children.

The objective of the present study was to investigate the accuracy of percent body fat (%fat) estimates from dual-energy X-ray absorptiometry, air-displacement plethysmography (ADP), and total body water (TBW) against a criterion four-compartment (4C) model in overweight and obese children. A volunteer sample of 30 children (18 male and 12 female), age of (mean +/- SD) 14.10 +/- 1.83 yr, body mass index of 31.6 +/- 5.5 kg/m, and %fat (4C model) of 41.2 +/- 8.2%, was assessed. Body density measurements were converted to %fat estimates by using the general equation of Siri (ADPSiri) (Siri WE. Techniques for Measuring Body Composition. 1961) and the age- and gender-specific constants of Lohman (ADPLoh) (Lohman TG. Exercise and Sport Sciences Reviews. 1986). TBW measurements were converted to %fat estimates by assuming that water accounts for 73% of fat-free mass (TBW73) and by utilizing the age- and gender-specific water contents of Lohman (TBWLoh). All estimates of %fat were highly correlated with those of the 4C model (r > or = 0.95, P < 0.001; SE < or = 2.14). For %fat, the total error and mean difference +/- 95% limits of agreement compared with the 4C model were 2.50, 1.8 +/- 3.5 (ADPSiri); 1.82, -0.04 +/- 3.6 (ADPLoh); 2.86, -2.0 +/- 4.1 (TBW73); 1.90, -0.3 +/- 3.8 (TBWLoh); and 2.74, 1.9 +/- 4.0 DXA (dual-energy X-ray absorptiometry), respectively. In conclusion, in overweight and obese children, ADPLoh and TBWLoh were the most accurate methods of measuring %fat compared with a 4C model. However, all methods under consideration produced similar limits of agreement.     

Comparison of body adiposity index (BAI) and bmi with estimations of % body fat in clinically severe obese women

Objective:

Body adiposity index (BAI), a new surrogate measure of body fat (hip circumference/(height^1.5 – 18)), has been proposed as an alternative to body mass index (BMI). We compared BAI with BMI, and each of them with laboratory measures of body fat‐derived from bioimpedance analysis (BIA), air displacement plethysmography (ADP), and dual‐energy X‐ray absorptiometry (DXA) in clinically severe obese (CSO) participants.

Design and Methods:

Nineteen prebariatric surgery CSO, nondiabetic women were recruited (age = 32.6 ± 7.7 SD; BMI = 46.5 ± 9.0 kg/m²). Anthropometrics and body fat percentage (% fat) were determined from BIA, ADP, and DXA. Scatter plots with lines of equality and Bland–Altman plots were used to compare BAI and BMI with % fat derived from BIA, ADP, and DXA. BAI and BMI correlated highly with each other (r = 0.90, P < 0.001).

Results:

Both BAI and BMI correlated significantly with % fat from BIA and ADP. BAI, however, did not correlate significantly with % fat from DXA (r = 0.42, P = 0.08) whereas BMI did (r = 0.65, P = 0.003). BMI was also the single best predictor of % fat from both BIA (r² = 0.80, P < 0.001) and ADP (r² = 0.65, P < 0.001). The regression analysis showed that the standard error of the estimate (SEE), or residual error around the regression lines, was greater for BAI comparisons than for BMI comparisons with BIA, ADP, and DXA. Consistent with this, the Bland and Altman plots indicated wider 95% confidence intervals for BAI difference comparisons than for BMI difference comparisons for their respective means for BIA, ADP, and DXA.

Conclusions:

Thus, BAI does not appear to be an appropriate proxy for BMI in CSO women.     

Air Displacement Plethysmography: Validation in Overweight and Obese Subjects

Objective: Patients with moderate and severe obesity, because of their physical size, often cannot be evaluated with conventional body composition measurement systems. The BOD POD air displacement plethysmography (ADP) system can accommodate a large body volume and may provide an opportunity for measuring body density (D_b) in obese subjects. D_b can be used in two‐ or three‐compartment body composition models for estimating total body fat in patients with severe obesity. The purpose of this study was to compare D_b measured by ADP to D_b measured by underwater weighing (UWW) in subjects ranging from normal weight to severely obese. Research Methods and Procedures: D_b was measured with UWW and BOD POD in 123 subjects (89 men and 34 women; age, 46.5 ± 16.9 years; BMI, 31.5 ± 7.3 kg/m²); 15, 70, and 10 subjects were overweight (25 ≤ BMI < 30 kg/m²), obese (30 ≤ BMI < 40 kg/m²), and severely obese (BMI ≥ 40 kg/m²), respectively. Results: There was a strong correlation between D_b(kilograms per liter) measured by UWW and ADP (r = 0.94, standard error of the estimate = 0.0073 kg/L, p < 0.001). Similarly, percent fat estimates from UWW and ADP using the two‐compartment Siri equation were highly correlated (r = 0.94, standard error of the estimate = 3.58%, p < 0.001). Bland‐Altman analysis showed no significant bias between D_b measured by UWW and ADP. After controlling for D_b measured by ADP, no additional between‐subject variation in D_b by UWW was accounted for by subject age, sex, or BMI. Discussion: Body density, an important physical property used in human body composition models, can be accurately measured by ADP in overweight and obese subjects.     

Air Displacement Plethysmography versus Dual-Energy X-Ray Absorptiometry in Underweight,Normal-Weight,and Overweight/Obese Individuals

Background

Accurately estimating fat percentage is important for assessing health and determining treatment course. Methods of estimating body composition such as hydrostatic weighing or dual-energy x-ray absorptiometry (DXA), however, can be expensive, require extensive operator training, and, in the case of hydrostatic weighing, be highly burdensome for patients. Our objective was to evaluate air displacement plethysmography via the Bod Pod, a less burdensome method of estimating body fat percentage. In particular, we filled a gap in the literature by testing the Bod Pod at the lower extreme of the Body Mass Index (BMI) distribution.

Findings

Three BMI groups were recruited and underwent both air displacement plethysmography and dual-energy x-ray absorptiometry. We recruited 30 healthy adults at the lower BMI distribution from the Calorie Restriction (CR) Society and followers of the CR Way. We also recruited 15 normal weight and 19 overweight/obese healthy adults from the general population. Both Siri and Brozek equations derived body fat percentage from the Bod Pod, and Bland-Altman analyses assessed agreement between the Bod Pod and DXA. Compared to DXA, the Bod Pod overestimated body fat percentage in thinner participants and underestimated body fat percentage in heavier participants, and the magnitude of difference was larger for underweight BMI participants, reaching 13% in some. The Bod Pod and DXA had smaller discrepancies in normal weight and overweight/obese participants.

Conclusions

While less burdensome, clinicians should be aware that Bod Pod estimates may deviate from DXA estimates particularly at the lower end of the BMI distribution.     

Effect of Scalp and Facial Hair on Air Displacement Plethysmography Estimates of Percentage of Body Fat

Objective: The objective of this study was to determine the effect of body hair (scalp and facial) on air displacement plethysmography (BOD POD) estimates of percentage of body fat. Research Methods and Procedures: A total of 25 men (31.4 ± 8.0 years, 83.4 ± 12.2 kg, 181.8 ± 6.9 cm) agreed to grow a beard for 3 weeks to participate in the study. Total body density (g/cm³) and percentage of body fat were evaluated by BOD POD. To observe the effect of trapped isothermal air in body hair, BOD POD measures were performed in four conditions: criterion method (the beard was shaven and a swimcap was worn), facial hair and swimcap, facial hair and no swimcap, and no facial hair and no swimcap_. Results: The presence of only a beard (facial hair and swimcap) resulted in a significant underestimation of percentage of body fat (16.2%, 1.0618 g/cm³) vs. the criterion method (17.1%, 1.0597 g/cm³, p < 0.001). The effect of scalp hair (no swim cap worn) resulted in a significant underestimation in percentage of body fat relative to the criterion method, either with facial hair (facial hair and no swimcap; 14.8%, 1.0649 g/cm³) or without facial hair (no facial hair and no swimcap; 14.8%, 1.0650 g/cm³, p < 0.001 for both). Discussion: A significant underestimation of percentage of body fat was observed with the presence of facial hair (～1%) and scalp hair (～2.3%). This underestimation in percentage of body fat may be caused by the effect of trapped isothermal air in body hair on body‐volume estimates. Thus, excess facial hair should be kept to a minimum and a swimcap should be worn at all times to ensure accurate estimates of body fat when using the BOD POD.     

Relationships among body composition measures in community-dwelling older women

Objective: To examine whether simple anthropometric measures provide a good estimate of total and visceral fat in 146 community‐dwelling, older white women (mean age, 74.0 ± 4.1 years). Research Methods and Procedures: Total body fat and visceral fat were measured using electron beam computed tomography (EBT). Anthropometric parameters (height, weight, BMI, sagittal diameter, and waist circumference) were measured using standard techniques. Total percentage body fat was assessed using DXA. Spearman correlations were used to examine the association between the measures. Linear regression, controlling for age, was used to examine the associations between the anthropometric parameters and total and visceral body fat measured by EBT. Results: Correlations among body composition measures ranged from ρ = 0.46 to 0.93 (p < 0.0001). EBT total fat was strongly correlated with both DXA estimates of total percentage fat (ρ = 0.86) and BMI (ρ = 0.89). Separate linear regression models indicated that BMI, waist circumference, sagittal diameter, and DXA total percentage fat were each independently related to EBT total fat. BMI had the strongest linear relationship, explaining 80% of the model variance (p < 0.0001). Linear regression indicated that BMI, waist circumference, and sagittal diameter were each independently related to EBT visceral fat, with BMI and sagittal diameter explaining ～53% of the model variance (p < 0.0001). Discussion: The use of simple anthropometric measures such as BMI, sagittal diameter, and waist circumference may be an appropriate alternative for more expensive techniques when assessing total fat but should be used with caution when estimating visceral body fat.     

Calcium and body fat in peripubertal girls: cross-sectional and longitudinal observations

Objective: The objective was to investigate whether calcium intake is independently associated with body fat in peripubertal girls. Research Methods and Procedures: A total of 45 healthy premenarcheal girls (initially 10.5 ± 0.6 years of age) completed a 2‐year prospective observational study. Percent body fat and trunk fat (by DXA), height, weight, maturational stage, and eating attitudes (children's Eating Attitudes Test [EAT]) were measured at baseline and at 1 and 2 years. Physical activity (by questionnaire) and calcium intake (by calcium‐specific food frequency questionnaire and 3‐day food records) were assessed at 6‐month intervals. Results: Girls with 2‐year mean calcium intake below and above the median had similar age, height, lean mass, and maturational stage at baseline, but girls below the median had significantly higher baseline percentage body fat (29.3 ± 10.3% vs. 22.0 ± 6.8%, p < 0.01) and trunk fat (24.2 ± 10.6% vs. 15.8 ± 6.8%, p < 0.01). However, differences were no longer significant when covariates (most notably children's EAT dieting score) were considered. Regression analysis revealed that dieting score was a consistent positive predictor of percentage body and trunk fat at all cross‐sectional time‐points, accounting for >20% of the variance, but did not predict 2‐year change in percentage fat. Calcium intake did not enter longitudinal regression equations for 2‐year change in percentage fat. Discussion: In this group of girls, an inverse cross‐sectional association between calcium intake and body fat appeared to result from avoidance of foods high in calcium by girls who were concerned about their body weight or shape. Calcium intake was not associated with change in fat over time.     

Comparison of Two Software Versions for Assessment of Body‐Composition Analysis by DXA

Objective: To compare two software versions provided by Lunar Co. for assessment of body composition analysis by DXA. Research Methods and Procedures: Soft‐tissue phantoms for lean tissue (water) and fat tissue (methanol) were repeatedly scanned using DXA machines (DPX‐L; Lunar Co., Madison, WI) and analyzed using software version 1.33 and the updated year 2000‐compatible version 1.35. For the intersoftware comparison, the phantoms were scanned 10 times (each scan was analyzed once) with both software versions using all three scanning modes (slow, medium, and fast) for a total of 60 scans and analyses. For the intermachine comparison, the same phantoms were scanned three times (each scan was analyzed once) with a second machine from the same manufacturer using all three scanning modes and version 1.35 only. Percentage of fat was the variable of interest. Results: For version 1.33, fat was 9.9 ± 0.4%, 10.0 ± 0.5%, and 11.0 ± 0.5% (mean ± SD) for the lean‐tissue phantom and 50.8 ± 0.3%, 50.9 ± 0.5%, and 51.1 ± 0.6% for the fat‐tissue phantom using the slow, medium, and fast scanning modes, respectively. For version 1.35, the respective fat values were 9.8 ± 0.7%, 9.9 ± 0.4%, and 10.3 ± 0.7%, and 50.6 ± 0.5%, 50.9 ± 0.6%, and 50.8 ± 0.8%, respectively. For the lean‐tissue phantom, the estimation of percentage of fat was significantly (p < 0.05) affected by scanning mode but not by software version. For the fat‐tissue phantom, the estimation of percentage of fat was not affected by either scanning mode or software version. The use of version 1.35 did not effect intermachine variability. Discussion: Versions 1.33 and 1.35 of the Lunar body composition software appear to be comparable. Soft‐tissue phantoms, such as the ones described in this paper, may be useful in monitoring the reproducibility of body composition analyses within and between DXA machines, particularly in longitudinal studies.     

Validation of DXA Body Composition Estimates in Obese Men and Women

The aim of this study was to determine the accuracy of dual‐energy X‐ray absorptiometry (DXA)‐derived percentage fat estimates in obese adults by using four‐compartment (4C) values as criterion measures. Differences between methods were also investigated in relation to the influence of fat‐free mass (FFM) hydration and various anthropometric measurements. Six women and eight men (age 22–54 years, BMI 28.7–39.9 kg/m², 4C percent body fat (%BF) 31.3–52.6%) had relative body fat (%BF) determined via DXA and a 4C method that incorporated measures of body density (BD), total body water (TBW), and bone mineral mass (BMM) via underwater weighing, deuterium dilution, and DXA, respectively. Anthropometric measurements were also undertaken: height, waist and gluteal girth, and anterior‐posterior (A‐P) chest depth. Values for both methods were significantly correlated (r² = 0.894) and no significant difference (P = 0.57) was detected between the means (DXA = 41.1%BF, 4C = 41.5%BF). The slope and intercept for the regression line were not significantly different (P > 0.05) from 1 and 0, respectively. Although both methods were significantly correlated, intraindividual differences between the methods were sizable (4C‐DXA, range = ?3.04 to 4.01%BF) and significantly correlated with tissue thickness (chest depth) or most surrogates of tissue thickness (body mass, BMI, waist girth) but not FFM hydration and gluteal girth. DXA provided cross‐sectional %BF data for obese adults without bias. However, individual data are associated with large prediction errors (±4.2%BF). This error appears to be associated with tissue thickness indicating that the DXA device used may not be able to accurately account for beam hardening in obese cohorts.     

Fat Mass Measured by DXA Varies with Scan Velocity

Objective: To study the influence of scan velocities of DXA on the measured size of fat mass, lean body mass, bone mineral content and density, and total body weight. Research Methods and Procedures: The subjects were 71 healthy white adults, 38 women and 33 men. The mean age was 41.7 ± 13.5 years and body mass index was 28.6 ± 5.6 kg/m². The subjects were scanned consecutively in slow, medium, and fast scan mode by a Lunar DPX-IQ DXA scanner. Results: Throughout the body mass index and sagittal height ranges, scanned lean body mass significantly decreased with higher scan velocity and lean body mass was 2.7% lower in fast than in medium mode (p < 0.0001). In contrast, fat mass, percentage of body fat, and bone mineral contents were higher with increasing scan velocity. Areas not analyzed by the scanner, so called blue spots, increased with scan velocity and sagittal height, and their presence significantly enhanced the error. Body weight estimated by DXA in slow mode was −0.8% lower than scale weight in the women (p < 0.001) and −0.2% in men (not significant), and the difference was greater with increasing scan velocity. Discussion: Scan velocity significantly influences the measured fat mass size, lean body mass, bone mineral content, and body weight. To obtain the most accurate results, slow mode is preferable and fast scans should be avoided. Future studies should report and take scan velocity into consideration.     

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.     

Total and Regional Fat and Serum Cardiovascular Disease Risk Factors in Lean and Obese Children and Adolescents

Objective: This study was conducted to evaluate the association of total and central adiposity with serum cardiovascular disease (CVD) risk factors in lean and obese Portuguese children and adolescents. Research Methods and Procedures: A total of 87 girls (13.2 ± 1.6 years old, 29.9 ± 6.4% body fat [mean ± SD]) and 72 boys (13.2 ± 1.6 years old, 20.8 ± 9.9% body fat) volunteered for the study. Whole‐body composition and fat distribution, from DXA and anthropometry, and serum lipids, lipoproteins, and apolipoproteins were evaluated. Results: The sum of three trunk skinfolds (STS) was highly correlated with total trunk fat mass measured by DXA (p < 0.001). Body mass index, DXA‐measured percentage of body fat, trunk fat mass, STS, and the waist‐to‐height ratio were generally found to be associated with triacylglycerol, the ratio of total cholesterol (TC) to high density lipoprotein‐cholesterol (HDL‐C), low density lipoprotein‐cholesterol (LDL‐C), and apolipoprotein B levels, (significant age‐adjusted r between 0.16 and 0.27, p < 0.05). Body mass index, STS, and the waist circumference were also associated with HDL‐C (p < 0.05), whereas no body composition variable significantly correlated with TC or apolipoproteins A‐I. The STS was significantly correlated with HDL‐C (p < 0.01), TC/HDL‐C (p < 0.05), and apolipoproteins A‐I (p < 0.05) independently of whole‐body fatness. Obese subjects (n = 73) had higher TC, LDL‐C, TC/HDL‐C, and apolipoprotein B than did non‐obese subjects (n = 86), and significant associations between central adiposity and some lipid variables (triacylglycerol and HDL‐C) were found in obese children and adolescents that were not present in leaner individuals. Discussion: DXA‐ and anthropometry‐based whole‐body and central fat measures are associated with serum CVD risk factors in Portuguese boys and girls. Obese children and adolescents have a poorer lipid profile than do their leaner counterparts. Trunk skinfolds, which are easy to obtain even in large samples, predict CVD risk factors to the same extent as DXA‐based variables, in some cases, independently of total fatness.     

Four‐Compartment Cellular Level Body Composition Model: Comparison of Two Approaches**

Objective: The aim of this study was to develop and compare two DXA‐based four‐compartment [body weight = body cell mass (BCM) + extracellular fluid (ECF) + extracellular solids (ECS) + fat] cellular level models. Research Methods and Procedures: Total body potassium (TBK) model: BCM from TBK by whole‐body counting—ECF_TBK = LST ? [BCM_TBK + 0.73 × osseous mineral (Mo)]. Bromide model: ECF from sodium bromide dilution—BCM_BROMIDE = LST ? (ECF_BROMIDE + 0.73 × Mo); Mo and LST measurements came from DXA. The two approaches were evaluated in 99 healthy men and 118 women. Results: BCM estimates were highly correlated (r = 0.97, p < 0.001), as were ECF estimates (r = 0.87, p < 0.001); a small statistically significant mean difference was present (mean ± SD; BCM_TBK model, 30.4 ± 8.9 kg; BCM_BROMIDE, 31.4 ± 9.3 kg; Δ = 1.0 ± 2.8 kg; p < 0.001; ECF_TBK, 18.5 ± 4.2 kg; ECF_BROMIDE, 17.5 ± 3.6 kg; Δ = 1.0 ± 2.8 kg; p < 0.001). A high correlation (r = 0.97, p < 0.001) and good agreement (38.9 ± 9.5 vs. 38.9 ± 9.5 kg; Δ = 0.0 ± 2.4 kg; p = 0.39) were present between TBW, derived as the sum of intracellular water from TBK and ECW from bromide, and measured TBW by ²H₂O dilution. Discussion: Two developed four‐compartment cellular level DXA models, one of which is appropriate for use in most clinical and research settings, provide comparable results and are applicable for BCM and ECF estimation of subject groups with hydration disturbances.     

Association between television in bedroom and adiposity throughout adolescence

Objective: The objective was to determine if having a television (TV) in the bedroom is associated with physical activity (PA), TV/video viewing, and adiposity throughout adolescence. Research Methods and Procedures: Longitudinal data (September 2002 through June 2005) were analyzed of 379 initially 12‐year‐old French adolescents participating as controls in the Intervention Centered on Adolescents’ Physical activity and Sedentary behavior (ICAPS). Presence of a TV set in the bedroom (TV_bedroom) and leisure activities were obtained by questionnaire. There was annual assessment of BMI, waist circumference, and body fat by bioimpedance. Results: In boys but not girls, baseline TV_bedroom was associated with higher TV/video viewing over time [odds ratio (OR) of high TV/video = 1.87; 95% confidence interval, 1.2 to 2.8] and less no‐sport club participation (OR = 0.59; 95% confidence interval, 0.35 to 1.0). Both boys and girls with baseline TV_bedroom had lower reading time (p < 0.0001 in boys; p = 0.04 in girls), while PA did not differ according to TV_bedroom for boys or for girls. For boys only, baseline TV_bedroom was associated with higher BMI (mean BMI over time 20.5 ± 0.5 vs. 19.0 ± 0.5 kg/m²; p = 0.001), waist circumference (70.9 ± 0.9 vs. 67.2 ± 0.8 cm; p < 0.001), and body fat (15.9 ± 0.9% vs. 13.5 ± 0.9%; p < 0.001), without interaction with time. These relationships remained significant after adjustment for socioeconomic status. TV/video viewing explained 26%, 42%, and 36% of the relationships of TV_bedroom with BMI, waist circumference, and body fat, respectively, while addition of other leisure activities in the models only marginally reduced the effects. Discussion: These results suggest the importance of keeping TV out of an adolescent's bedroom from an obesity prevention perspective but show gender differences.     

Prediction of Visceral Adipose Tissue Using Air Displacement Plethysmography in Children

Objective: To determine the ability of air displacement plethysmography (ADP) to predict visceral adipose tissue (VAT) volume in children. Research Methods and Procedures: Fifty‐five (33 boys/22 girls) white children 13 to 14 years old were studied. Anthropometric measures were collected for body mass, stature, BMI, and waist‐to‐hip ratio (WHR), and body fat percentage was estimated from triceps and subscapular skinfolds, bioelectrical impedance analysis, and ADP. VAT volume was determined using magnetic resonance imaging, using a multiple slice protocol at levels L1 to L5. Results: Boys had significantly (p ≤ 0.05) less VAT volume than girls [645.1 (360.5) cm³ vs. 1035.8 (717.3) cm³]. ADP explained the greatest proportion of the variance in VAT volume compared with the other anthropometric measures. Multiple regression analysis indicated that VAT volume was best predicted by ADP body fat percentage in boys [r² = 0.81, SE of the estimate (SEE) = 160.1, SEE coefficient of variation = 25%] and by WHR and BMI in girls (r² = 0.80, SEE = 337.71, SEE coefficient of variation = 33%). Discussion: Compared with the other anthropometric measures, ADP explains the greatest proportion of the variance in VAT volume in children 13 to 14 years old. For boys, ADP is the tool of choice to predict VAT volume, yet using the more simply collected measures of BMI and WHR is recommended for girls. However, large SE of the estimates remained, suggesting that if precision is needed, there is no surrogate for direct imaging of VAT.     

Validity of Six Field and Laboratory Methods for Measurement of Body Composition in Boys

Objective: To determine the validity of the following six body composition methods against a reference method (three‐component model): air displacement plethysmography (BODPOD); estimation from body density using BODPOD; skinfold thickness using the Slaughter equations; bioelectrical impedance, both leg‐leg (TANITA) and hand—foot (Bodystat) approaches; and total body water. Research Methods and Procedures: Forty‐two healthy white 10‐ to 14‐year‐old boys (mean age, 12.9 ± 1.0 years) were enrolled in this study. Measures of body fat percentage and body fat mass derived from the three‐component model were used as the reference method. Validity of all of the other methods was assessed by comparison against the reference by calculation of biases and limits of agreement. Results: Mean body fatness measured using the reference method was 16.4 ± 11.6% and 8.7 ± 7.0 kg. Estimates of fatness from total body water had the narrowest limits of agreement relative to the reference (+0.9 ± 5.0% body fat; +0.5 ± 2.9 kg fat mass). For all other methods tested, we observed large biases and very wide limits of agreement. Discussion: This study suggests that the validity of newer field and laboratory methods for estimation of body composition is poor in adolescent boys. For applications where high accuracy of estimation at the individual level is essential, only reference methods would be acceptable.     

Body Composition of African American and White Children: A 2‐Year Follow‐Up of the BAROC Study

Objective: To evaluate the 2‐year changes in body composition of white and African American boys and girls. Research Methods and Procedures: A total of 114 boys and girls ages 12 to 14 years with equal sex and ethnic distribution between African American and white races participated in measurements of body composition using DXA, underwater weighing (densitometry), skinfold thickness, corporal diameters, circumferences, isotope dilution (H₂¹⁸O), and bioelectric impedance. Results: Sixty‐eight of the 114 children advanced from Tanner Stages 1 and 2 to Tanner Stages 3 to 5 over a 2‐year period. More than 50% of the children were in the top 15th percentile according to normative data for body mass index but not for triceps skinfold. All measures except for percentage of fat, density, and four of the six skinfolds increased significantly during the 2 years, with no differences between races, genders, or fat group. The boys who advanced in Tanner Stage reduced their percentage of fat and a number of skinfolds and increased their lean body mass, but the girls did not. The percentage of water was significantly higher in the fatter children and declined significantly over 2 years. Most children remained in the same quartile of body fat, lean body mass, and bone mineral content over 2 years. Discussion: The data are consistent with the hypothesis that over 2 years, growth is the major determinant of changing body composition, with body‐fat group and sexual maturation being additional variables.