Evaluation of a Quantitative Magnetic Resonance Method for Mouse Whole Body Composition Analysis

Objective: To evaluate applicability, precision, and accuracy of a new quantitative magnetic resonance (QMR) analysis for whole body composition of conscious live mice. Research Methods and Procedures: Repeated measures of body composition were made by QMR, DXA, and classic chemical analysis of carcass using live and dead mice with different body compositions. Caloric lean and dense diets were used to produce changes in body composition. In addition, different strains of mice representing widely diverse populations were analyzed. Results: Precision was found to be better for QMR than for DXA. The coefficient of variation for fat ranged from 0.34% to 0.71% compared with 3.06% to 12.60% for DXA. Changes in body composition in response to dietary manipulation were easily detected using QMR. An increase in fat mass of 0.6 gram after 1 week (p < 0.01) was demonstrated in the absence of hyperphagia or a change in mean body weight. Discussion: QMR and DXA detected similar fat content, but the improved precision afforded by QMR compared with DXA and chemical analysis allowed detection of a significant difference in body fat after 7 days of consuming a diet rich in fat even though average body weight did not significantly change. QMR provides a very precise, accurate, fast, and easy‐to‐use method for determining fat and lean tissue of mice without the need for anesthesia. Its ability to detect differences with great precision should be of value when characterizing phenotype and studying regulation of body composition brought about by pharmacological and dietary interventions in energy homeostasis.     

PIXImus DXA with Different Software Needs Individual Calibration to Accurately Predict Fat Mass

Objective: To validate GE PIXImus2 DXA fat mass (FM) estimates by chemical analysis, to compare previously published correction equations with an equation from our machine, and to determine intermachine variation. Research Methods and Procedures: C57BL/6J (n = 16) and Aston (n = 14) mice (including ob/ob), Siberian hamsters (Phodopus sungorus) (n = 15), and bank voles (Clethrionomys glareolus) (n = 37) were DXA scanned postmortem, dried, then fat extracted using a Soxhlet apparatus. We compared extracted FM with DXA‐predicted FM corrected using an equation designed using wild‐type animals from split‐sample validation and multiple regression and two previously published equations. Sixteen animals were scanned on both a GE PIXImus2 DXA in France and a second machine in the United Kingdom. Results: DXA underestimated FM of obese C57BL/6J by 1.4 ± 0.19 grams but overestimated FM for wild‐type C57BL/6J (2.0 ± 0.11 grams), bank voles (1.1 ± 0.09 grams), and hamsters (1.1 ± 0.13 grams). DXA‐predicted FM corrected using our equation accurately predicted extracted FM (accuracy 0.02 grams), but the other equations did not (accuracy, ?1.3 and ?1.8 grams; paired Student's t test, p < 0.001). Two similar DXA instruments gave the same FM for obese mutant but not lean wild‐type animals. Discussion: DXA using the same software could use the same correction equation to accurately predict FM for obese mutant but not lean wild‐type animals. PIXImus machines purchased with new software need validating to accurately predict FM.     

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.     

Use of balance methods for assessment of short-term changes in body composition

Balance methods reveal changes in body energy, nitrogen, macro‐ and micronutrients as well as fluid in response to different feeding regimens. Under metabolic ward conditions, where physical activity is restricted and activity and food intake are controlled, the errors of estimates of energy intake, energy expenditure, and energy losses are about 2, 4, and 2%, respectively. Balance techniques can be used to validate techniques of in vivo body composition analysis (BCA). This is necessary since immediate and transient changes in body composition in response to a change in diet adversely affect the validity of techniques by violating the assumptions underlying standard methods (i.e., a constant composition or hydration of lean mass). Using two compartment reference methods, like densitometry, dual X‐ray absorptiometry (DXA) or deuterium dilution, changes in fat mass with caloric restriction and overfeeding can be measured with a minimal detectable change (MDC) of 1.0–2.0 kg. However, when compared against balance data, the validity of these techniques to measure short‐term changes in body composition is poor. The noninvasive and rapid new quantitative magnetic resonance (QMR) technique has a high precision with a MDC of 0.18 kg of fat mass. The validity of QMR to assess short‐term changes in fat mass is challenged by comparison to balance data. Today, techniques used for in vivo BCA should be related to steady state conditions only, while in the nonsteady state, the use of balance methods is recommended to assess short‐term changes in body composition.     

Effect of sarcopenia on cardiovascular disease risk factors in obese postmenopausal women

Objective: To compare sarcopenic‐obese and obese postmenopausal women for risk factors predisposing to cardiovascular disease (CVD) and determine whether there may be a relationship between muscle mass and metabolic risk in obese postmenopausal women. Research Methods and Procedures: In this cross‐sectional study, 22 healthy obese postmenopausal women (mean age, 66 ± 5 years; mean BMI, 27 ± 3 kg/m²) were divided into two groups matched for age (±2 years) and fat mass (FM) (±2%). Sarcopenia was defined as a muscle mass index of <14.30 kg fat‐free mass (FFM)/m² (which corresponds to 1 standard deviation below the values of a young reference population), and obesity was defined as an FM of >35% (which corresponds to the World Health Organization guidelines). FM, FFM (measured by DXA), daily energy expenditure (accelerometry), dietary intake (3‐day dietary record), and blood biochemical analyses (lipid profile, insulin, glucose, and C‐reactive protein) were obtained. Visceral fat mass (VFM) was calculated by the equation of Bertin, which estimates VFM from DXA measurements. Results: Obese women had more FFM (p = 0.006), abdominal FM (p = 0.047), and VFM (p = 0.041) and a worse lipid profile [p = 0.040 for triglycerides; p = 0.004 for high‐density lipoprotein (HDL); p = 0.026 for total cholesterol/HDL] than sarcopenic‐obese postmenopausal women. Obese women also ingested significantly more animal (p = 0.001) and less vegetal proteins (p = 0.013), although both groups had a similar total protein intake (p = 0.967). Discussion: Sarcopenia seems to be associated with lower risk factors predisposing to CVD in obese postmenopausal women. With the increase in the number of aging people, the health implications of being sarcopenic‐obese merit more attention.     

Quantitative nuclear magnetic resonance to measure fat mass in infants and children

Quantitative nuclear magnetic resonance (QMR) is being used in human adults to obtain measures of total body fat mass (FM) with high precision. The current study assessed a device specially designed to accommodate infants and children between 3 and 50 kg (EchoMRI-AH). Body composition of 113 infants and children (3.3-49.9 kg) was assessed using dual-energy X-ray absorptiometry (DXA), air displacement plethysmography (ADP, PeaPod for infants ≤ 8 kg and BodPod for children ≥ 6 years) and QMR. Results were compared with the deuterium oxide dilution technique (D(2)O) and a four-compartment model (4-C). The percentages of compliance were: 98% QMR; 75% DXA; 94% BodPod; and 95% PeaPod. Although QMR precision was high (coefficient of variation = 1.42%), it overestimated FM ~10% compared to the 4-C model and underestimated FM by ~4% compared to the deuterium method in children ≥ 6 years. QMR was less concordant with 4-C or D(2)O models for infants ≤ 8 kg. Thus, a piece-wise defined model for mathematically fitting the QMR data to the D(2)O data was employed and this adjustment improved the accuracy relative to D(2)O and 4-C for infants. Our results suggest that the pediatric QMR with appropriate mathematical adjustment provides a fast and precise method for assessing FM longitudinally in infants and in children weighing up to 50 kg.     

Validation of a quantitative magnetic resonance method for measuring human body composition

Objective: To evaluate a novel quantitative magnetic resonance (QMR) methodology (EchoMRI‐AH, Echo Medical Systems) for measurement of whole‐body fat and lean mass in humans. Methods and Procedures: We have studied (i) the in vitro accuracy and precision by measuring 18 kg Canola oil with and without 9 kg water (ii) the accuracy and precision of measures of simulated fat mass changes in human subjects (n = 10) and (iii) QMR fat and lean mass measurements compared to those obtained using the established 4‐compartment (4‐C) model method (n = 30). Results: (i) QMR represented 18 kg of oil at 40°C as 17.1 kg fat and 1 kg lean while at 30°C 15.8 kg fat and 4.7 kg lean were reported. The s.d. of repeated estimates was 0.13 kg for fat and 0.23 kg for lean mass. Adding 9 kg of water reduced the fat estimates, increased misrepresentation of fat as lean, and degraded the precision. (ii) the simulated change in the fat mass of human volunteers was accurately represented, independently of added water. (iii) compared to the 4‐C model, QMR underestimated fat and over‐estimated lean mass. The extent of difference increased with body mass. The s.d. of repeated measurements increased with adiposity, from 0.25 kg (fat) and 0.51 kg (lean) with BMI <25 kg/m² to 0.43 kg and 0.81 kg respectively with BMI >30 kg/m². Discussion: EchoMRI‐AH prototype showed shortcomings in absolute accuracy and specificity of fat mass measures, but detected simulated body composition change accurately and with precision roughly three times better than current best measures. This methodology should reduce the study duration and cohort number needed to evaluate anti‐obesity interventions.     

Evaluation of a Quantitative Magnetic Resonance Imaging System for Whole Body Composition Analysis in Rodents

We evaluated the EchoMRI‐900 combination rat and mouse quantitative magnetic resonance (QMR) body composition method in comparison to traditional whole‐body chemical carcass composition analysis (CCA) for measurements of fat and fat‐free mass in rodents. Live and postmortem (PM) QMR fat and lean mass measurements were obtained for lean, obese and outbred strains of rats and mice, and compared with measurements obtained using CCA. A second group of rats was measured before and after 18 h food or water deprivation. Significant positive correlations between QMR and CCA fat and lean mass measurements were shown for rats and mice. Although all live QMR fat and lean measurements were more precise than CCA for rats, values obtained for mice significantly differed from CCA for lean mass only. QMR performed PM slightly overestimated fat and lean values relative to live QMR but did not show lower precision than live QMR. Food deprivation reduced values for both fat and lean mass; water deprivation reduced estimates of lean mass only. In summary, all measurements using this QMR system were comparable to those obtained by CCA, but with higher overall precision, similar to previous reports for the murine QMR system. However, PM QMR measurements slightly overestimated live QMR values, and lean and fat mass measurements in this QMR system are influenced by hydration status and animal size, respectively. Despite these caveats, we conclude that the EchoMRI QMR system offers a fast in vivo method of body composition analysis, well correlated to but with greater overall precision than CCA.     

Body Composition Measured by Dual‐energy X‐ray Absorptiometry Half‐body Scans in Obese Adults

Dual‐energy X‐ray absorptiometry (DXA) has become a common measurement of human body composition. However, obese subjects have been understudied largely due to weight and scan area restrictions. Newer DXA instruments allow for heavier subjects to be supported by the DXA scanner, but the imaging area is still smaller than the body size of some obese subjects. In this study, we determined the validity of an automated half‐scan methodology by comparing to the standard whole‐body scans in a cohort of obese volunteers. Fifty‐two subjects whose BMI >30 kg/m² completed whole‐body iDXA (GE Lunar) scans. The resulting scans were analyzed in three ways: the standard whole‐body scan, total body estimated from the left side, and from the right side. Fat mass, nonbone lean mass, bone mineral content (BMC), and percent fat derived from each half scan were compared to the whole‐body scans. Total fat mass, nonbone lean mass, or percent fat was comparable for the whole‐body scans, left, and right side scans (>97% within individuals and >99.9% for the group). The BMC estimate using the right side scan was slightly but statistically higher than the whole‐body BMC (～30 g or 1%, P < 0.001), while the left side scan BMC estimate was lower than the whole‐body BMC by the same magnitude. No significant magnitude bias was found for any of the composition variables. We conclude that the new iDXA half‐body analysis in obese subjects appears to be closely comparable to whole‐body analysis for fat mass, nonbone lean mass, and percent fat.     

Precision and Accuracy of Dual‐Energy X‐ray Absorptiometry for Determining in Vivo Body Composition of Mice

Objective: To evaluate the precision and accuracy of dual‐energy X‐ray absorptiometry (DXA) for the measurement of total‐bone mineral density (TBMD), total‐body bone mineral (TBBM), fat mass (FM), and bone‐free lean tissue mass (LTM) in mice. Research Methods and Procedures: Twenty‐five male C57BL/6J mice (6 to 11 weeks old; 19 to 29 g) were anesthetized and scanned three times (with repositioning between scans) using a peripheral densitometer (Lunar PIXImus). Gravimetric and chemical extraction techniques (Soxhlet) were used as the criterion method for the determination of body composition; ash content was determined by burning at 600°C for 8 hours. Results: The mean intraindividual coefficients of variation (CV) for the repeated DXA analyses were: TBMD, 0.84%; TBBM, 1.60%; FM, 2.20%; and LTM, 0.86%. Accuracy was determined by comparing the DXA‐derived data from the first scan with the chemical carcass analysis data. DXA accurately measured bone ash content (p = 0.942), underestimated LTM (0.59 ± 0.05g, p < 0.001), and overestimated FM (2.19 ± 0.06g, p < 0.001). Thus, DXA estimated 100% of bone ash content, 97% of carcass LTM, and 209% of carcass FM. DXA‐derived values were then used to predict chemical values of FM and LTM. Chemically extracted FM was best predicted by DXA FM and DXA LTM [FM = ?0.50 + 1.09(DXA FM) ? 0.11(DXA LTM), model r² = 0.86, root mean square error (RMSE) = 0.233 g] and chemically determined LTM by DXA LTM [LTM = ?0.14 + 1.04(DXA LTM), r² = 0.99, RMSE = 0.238 g]. Discussion: These data show that the precision of DXA for measuring TBMD, TBBM, FM, and LTM in mice ranges from a low of 0.84% to a high of 2.20% (CV). DXA accurately measured bone ash content but overestimated carcass FM and underestimated LTM. However, because of the close relationship between DXA‐derived data and chemical carcass analysis for FM and LTM, prediction equations can be derived to more accurately predict body composition.     

Comparison of body composition methods in obese African-American women

Objective : To compare the accuracy of percentage body fat (%BF) estimates between bioelectrical impedance analysis (BIA) and DXA in obese African‐American women. Research Methods and Procedures : Fifty‐five obese African‐American women (mean age, 45 years; mean BMI, 38; mean %BF, 48%) were studied. BF was assessed by both BIA (RJL Systems BIA 101Q; RJL Systems, Clinton Township, MI) and DXA (Hologic QDR‐2000 Bone Densitometer; Hologic Inc., Bedford, MA). Generalized and ethnicity‐ and obese‐specific equations were used to calculate %BF from the BIA. Bland‐Altman analyses were used to compare the agreement between the BIA and the DXA, with the DXA serving as the criterion measure. Results : Two of the generalized equations provided consistent estimates across the weight range in comparison with the DXA estimates, whereas most of the other equations increasingly underestimated %BF as BF increased. One of the generalized and one of the ethnicity‐specific equations had mean differences that were not significantly different from the DXA value. Discussion : The findings show that the Lukaski equation provided the most precise and accurate estimates of %BF in comparison with the QDR 2000 and provide preliminary support for the use of this equation for obese African‐American women.     

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.     

Differences in daily energy expenditure in lean and obese women: the role of posture allocation

Objective: A low resting metabolic rate (RMR) is considered a risk factor for weight gain and obesity; however, due to the greater fat‐free mass (FFM) found in obesity, detecting an impairment in RMR is difficult. The purposes of this study were to determine the RMR in lean and obese women controlling for FFM and investigate activity energy expenditure (AEE) and daily activity patterns in the two groups. Methods and Procedures: Twenty healthy, non‐smoking, pre‐menopausal women (10 lean and 10 obese) participated in this 14‐day observational study on free‐living energy balance. RMR was measured by indirect calorimetry; AEE and total energy expenditure (TEE) were calculated using doubly labeled water (DLW), and activity patterns were investigated using monitors. Body composition including FFM and fat mass (FM) was measured by dual energy X‐ray absorptiometry (DXA). Results: RMR was similar in the obese vs. lean women (1601 ± 109 vs. 1505 ± 109 kcal/day, respectively, P = 0.12, adjusting for FFM and FM). Obese women sat 2.5 h more each day (12.7 ± 3.2 h vs. 10.1 ± 2.0 h, P < 0.05), stood 2 h less (2.7 ± 1.0 h vs. 4.7 ± 2.2 h, P = 0.02) and spent half as much time in activity than lean women (2.6 ± 1.5 h vs. 5.4 ± 1.9 h, P = 0.002). Discussion: RMR was not lower in the obese women; however, they were more sedentary and expended less energy in activity than the lean women. If the obese women adopted the activity patterns of the lean women, including a modification of posture allocation, an additional 300 kcal could be expended every day.     

Very low-carbohydrate versus isocaloric high-carbohydrate diet in dietary obese rats

Objective: The effects of a very low‐carbohydrate (VLC), high‐fat (HF) dietary regimen on metabolic syndrome were compared with those of an isocaloric high‐carbohydrate (HC), low‐fat (LF) regimen in dietary obese rats. Research Methods and Procedures: Male Sprague‐Dawley rats, made obese by 8 weeks ad libitum consumption of an HF diet, developed features of the metabolic syndrome vs. lean control (C) rats, including greater visceral, subcutaneous, and hepatic fat masses, elevated plasma cholesterol levels, impaired glucose tolerance, and fasting and post‐load insulin resistance. Half of the obese rats (VLC) were then fed a popular VLC‐HF diet (Weeks 9 and 10 at 5% and Weeks 11 to 14 at 15% carbohydrate), and one‐half (HC) were pair‐fed an HC‐LF diet (Weeks 9 to 14 at 60% carbohydrate). Results: Energy intakes of pair‐fed VLC and HC rats were less than C rats throughout Weeks 9 to 14. Compared with HC rats, VLC rats exhibited impaired insulin and glycemic responses to an intraperitoneal glucose load at Week 10 and lower plasma triacylglycerol levels but retarded loss of hepatic, retroperitoneal, and total body fat at Week 14. VLC, HC, and C rats no longer differed in body weight, plasma cholesterol, glucose tolerance, or fasting insulin resistance at Week 14. Progressive decreases in fasting insulin resistance in obese groups paralleled concomitant reductions in hepatic, retroperitoneal, and total body fat. Discussion: When energy intake was matched, the VLC‐HF diet provided no advantage in weight loss or in improving those components of the metabolic syndrome induced by dietary obesity and may delay loss of hepatic and visceral fat as compared with an HC‐LF diet.     

Usefulness of Anthropometry and DXA in Predicting Intra‐abdominal Fat in Obese Men and Women

Objective: To investigate the usefulness of anthropometry and DXA in predicting intra‐abdominal fat (IAF) in obese men and women. Research Methods and Procedures: Observational, cross sectional study of 22 women and 18 men with a body mass index of 30 or above. IAF from 20 cm above and 10 cm below the L4 to L5 intervertebral disc was measured by magnetic resonance imaging (MRI) as a reference method. Central abdominal fat was measured from the upper border of L2 to the lower border of L4 by DXA. Waist and hip circumferences were also measured. Results: In obese women DXA, waist circumference and waist‐hip ratio were equally well correlated with IAF (r = 0.74, 0.75, and 0.70, respectively). In obese men DXA was moderately correlated with IAF measured by MRI (r = 0.46), whereas waist circumference and waist‐hip ratio were not significantly correlated with IAF. Discussion: The prediction of IAF in obese subjects was highly dependent on sex more than in non‐obese persons. Anthropometry and DXA were equally useful in obese women, whereas anthropometry had no predictive power and DXA was the only acceptable predictor of IAF in obese men.     

Diet‐Induced Changes in Stearoyl‐CoA Desaturase 1 Expression in Obesity‐Prone and ‐Resistant Mice

Objective: To investigate stearoyl‐coenzyme A desaturase (SCD) 1 expression in obesity‐prone C57BL/6 mice and in obesity‐resistant FVB mice to explore the relationship of SCD1 expression and susceptibility to diet‐induced obesity. Research Methods and Procedures: Nine‐week‐old C57BL/6 and FVB mice were fed either a high‐ or low‐fat diet for 8 weeks. Body weight and body composition were measured before and at weeks 4 and 8 of the study. Energy expenditure was measured at weeks 1 and 5 of the study. Hepatic SCD1 mRNA was measured at 72 hours and at the end of study. Plasma leptin and insulin concentrations were measured at the end of study. Results: When C57BL/6 mice were switched to a calorie‐dense high‐fat diet, animals gained significantly more body weight than those maintained on a low‐calorie density diet primarily due to increased fat mass accretion. Fat mass continued to accrue throughout 8 weeks of study. Increased calorie intake did not account for all weight gain. On the high‐fat diet, C57BL/6 mice decreased their energy expenditure when compared with mice fed a low‐fat diet. In response to 8 weeks of a high‐fat diet, SCD1 gene expression in liver increased >2‐fold. In contrast, feeding a high‐fat diet did not change body weight, energy expenditure, or SCD1 expression in FVB mice. Discussion: Our study showed that a high‐fat hypercaloric diet increased body adiposity first by producing hyperphagia and then by decreasing energy expenditure of mice susceptible to diet‐induced obesity. Consumption of a high‐fat diet in species predisposed to obesity selectively increased SCD1 gene expression in liver.     

Comparison of DXA and CT in the Assessment of Body Composition in Premenopausal Women With Obesity and Anorexia Nervosa

Accurate methods for assessing body composition in subjects with obesity and anorexia nervosa (AN) are important for determination of metabolic and cardiovascular risk factors and to monitor therapeutic interventions. The purpose of our study was to assess the accuracy of dual‐energy X‐ray absorptiometry (DXA) for measuring abdominal and thigh fat, and thigh muscle mass in premenopausal women with obesity, AN, and normal weight compared to computed tomography (CT). In addition, we wanted to assess the impact of hydration on DXA‐derived measures of body composition by using bioelectrical impedance analysis (BIA). We studied a total of 91 premenopausal women (34 obese, 39 with AN, and 18 lean controls). Our results demonstrate strong correlations between DXA‐ and CT‐derived body composition measurements in AN, obese, and lean controls (r = 0.77–0.95, P < 0.0001). After controlling for total body water (TBW), the correlation coefficients were comparable. DXA trunk fat correlated with CT visceral fat (r = 0.51–0.70, P < 0.0001). DXA underestimated trunk and thigh fat and overestimated thigh muscle mass and this error increased with increasing weight. Our study showed that DXA is a useful method for assessing body composition in premenopausal women within the phenotypic spectrum ranging from obesity to AN. However, it is important to recognize that DXA may not accurately assess body composition in markedly obese women. The level of hydration does not significantly affect most DXA body composition measurements, with the exceptions of thigh fat.     

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.     

Anthropometrics Do Not Influence Dual X-ray Absorptiometry (DXA) Measurement of Fat in Normal to Obese Adults: A Comparison with In Vivo Neutron Activation Analysis (IVNA)

Dual-energy X-ray absorptiometry (DXA) is now a commonly used method for the determination of bone mineral status and body composition in humans. The purposes of this study were to compare fat mass by in vivo neutron activation analysis (FM_IVNA) with that by DXA (FM_DXA) in an anthropometrically heterogeneous sample of healthy adult men (n=33) and women (n=36) (19=≤BMI≤39), and to determine whether differences in fat mass estimates between the two methods (ΔFM) were attributable to subject anthropometry as defined by several circumference (waist, iliac crest, thigh) and skinfold thickness (umbilical, suprailiac, abdominal) measurements. No significant differences between FM_DXA and FM_IVNA were observed in men (p=0.46) or women (p=0.09). The two methods were very highly correlated in both sexes (women r²=0.97, p<0.001, men r²=0.91, p<0.001), although the regression line for men was significantly different from the line of identity (p=0.043). These results suggest modest trends toward underestimation of FM_DXA in men when FM_IVNA<18 kg, and overestimation in men when FM_IVNA>18 kg. ΔFM (IVNA-DXA) was not significantly related to any combination of skinfold thicknesses and circumferences in either gender. Age explained 27% of the variance in ΔFM for the men (p=0.008). Furthermore, ΔFM was not significantly related to inter-method disparity in total-body bone mineral measurements in men or women (p<0.05). The present study demonstrates strong correlation in fat measurements between IVNA and DXA in men and women ranging from normal to markedly obese. Correction for subject anthropometry does not significantly improve this relationship.     

Effect of calorie restriction on resting metabolic rate and spontaneous physical activity

Objective: It is unclear if resting metabolic rate (RMR) and spontaneous physical activity (SPA) decrease in weight‐reduced non‐obese participants. Additionally, it is unknown if changes in SPA, measured in a respiratory chamber, reflect changes in free‐living physical activity level (PAL). Research Methods and Procedures: Participants (N = 48) were randomized into 4 groups for 6 months: calorie restriction (CR, 25% restriction), CR plus structured exercise (CR+EX, 12.5% restriction plus 12.5% increased energy expenditure via exercise), low‐calorie diet (LCD, 890 kcal/d supplement diet until 15% weight loss, then weight maintenance), and control (weight maintenance). Measurements were collected at baseline, Month 3, and Month 6. Body composition and RMR were measured by DXA and indirect calorimetry, respectively. Two measures of SPA were collected in a respiratory chamber (percent of time active and kcal/d). Free‐living PAL (PAL = total daily energy expenditure by doubly labeled water/RMR) was also measured. Regression equations at baseline were used to adjust RMR for fat‐free mass and SPA (kcal/d) for body weight. Results: Adjusted RMR decreased at Month 3 in the CR group and at Month 6 in the CR+EX and LCD groups. Neither measure of SPA decreased significantly in any group. PAL decreased at Month 3 in the CR and LCD groups, but not in the CR+EX group, who engaged in structured exercise. Changes in SPA in the chamber and free‐living PAL were not related. Discussion: Body weight is defended in non‐obese participants during modest caloric restriction, evidenced by metabolic adaptation of RMR and reduced energy expenditure through physical activity.