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.     

Quantitative Magnetic Resonance (QMR) for Longitudinal Evaluation of Body Composition Changes With Two Dietary Regimens

We have recently reported a validation study of a prototype low‐field strength quantitative magnetic resonance (QMR) instrument for measurement of human body composition (EchoMRI‐AH). QMR was very precise, but underreported fat mass (FM) by 2–4 kg when compared to a 4‐compartment (4C) model in this cross‐sectional study. Here, we report the performance of an updated instrument in two longitudinal studies where FM was decreasing. Healthy obese volunteers were given a modest energy deficit diet for 8 weeks (study A) and obese patients with heart failure and/or at high cardiovascular risk were prescribed a low energy liquid diet for 6 weeks (study B). FM was measured at the start and end of these periods by QMR, dual‐energy X‐ray absorptiometry (DXA) and 4C. A higher proportion of the weight lost came from fat in study A compared with study B, where loss of total body water (TBW) played a greater part. The intraclass correlation between QMR and 4C estimates of FM loss (ΔFat) was 0.95, but 20 of 22 estimates of ΔFat by QMR were lower than the corresponding estimate by the 4C model. Bland–Altman analysis demonstrated that estimates of FM loss by QMR were ～1.0 and 0.7 kg lower than those obtained with 4C (P = 0.0008) and DXA (P = 0.049), respectively. Measurement precision remained high. QMR measurement should prove valuable for quantifying modest changes of FM in small trials.     

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.     

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.     

Regional Body Composition: Cross‐calibration of DXA Scanners—QDR4500W and Discovery Wi

Differences exist in body composition assessed by dual‐energy X‐ray absorptiometers (DXAs) between devices produced by different manufacturers and different models from the same manufacturer. Cross‐calibration is needed to allow body composition results to be compared in multicenter trials or when scanners are replaced. The aim was to determine reproducibility and extent of agreement between two fan‐beam DXA scanners (QDR4500W, Discovery Wi) for body composition of regional sites. The sample was: 39 women 50.6 ± 9.6 years old with BMI 26.8 ± 5.5 kg/m², body fat 33 ± 7%. Four whole body scans (two on each device) were performed over 3 weeks. Major variables were fat mass, nonosseous lean mass, and bone mineral content (BMC) for the truncal and appendicular regions. Extent of agreement was assessed using Bland and Altman plots. Both devices demonstrated good precision with mean test–retest differences close to zero for fat mass, nonosseous lean mass, and BMC of the truncal and appendicular regions. Evaluation of interdevice agreement revealed significant differences for truncal and appendicular BMC, nonosseous lean mass, and fat mass. The greatest interdevice difference was for truncal fat mass (0.69 ± 0.60 kg). Differences in truncal and appendicular fat mass increased in magnitude at higher mean values. Furthermore, differences in truncal and appendicular fat mass were strongly related to BMI (R = ?0.61, R = ?0.55, respectively). In conclusion, in vivo cross‐calibration is important to ensure comparability of regional body composition data between scanners, especially for truncal fat mass and for subjects with higher BMI.     

Orlistat 60 mg reduces visceral adipose tissue: a 24-week randomized, placebo-controlled, multicenter trial

It is well established that abdominal obesity or upper body fat distribution is associated with increased risk of metabolic and cardiovascular disease. The purpose of the present study was to determine if a 24 week weight loss program with orlistat 60 mg in overweight subjects would produce a greater change in visceral adipose tissue (VAT) as measured by computed tomography (CT) scan, compared to placebo. The effects of orlistat 60 mg on changes in total fat mass (EchoMRI‐AH and BIA), ectopic fat (CT) and glycemic variables were assessed. One‐hundred thirty‐one subjects were randomized into a multicenter, double‐blind placebo controlled study in which 123 subjects received at least one post baseline efficacy measurement (intent‐to‐treat population). Both orlistat‐and placebo‐treated subjects significantly decreased their VAT at 24 weeks with a significantly greater loss of VAT by orlistat treated subjects (?15.7% vs. ?9.4%, P < 0.05). In addition, orlistat‐treated subjects had significantly greater weight loss (?5.93 kg vs. ?3.94 kg, P < 0.05), total fat mass loss (?4.65 kg vs. ?3.01 kg, P < 0.05) and trended to a greater loss of intermuscular adipose tissue and content of liver fat compared with placebo‐treated subjects. This is the first study to demonstrate that orlistat 60 mg significantly reduces VAT in addition to total body fat compared to placebo treated subjects after a 24 week weight loss program. These results suggest that orlistat 60 mg may be an effective weight loss tool to reduce metabolic risk factors associated with abdominal obesity.     

Measurement of arthropod body composition using quantitative magnetic resonance

Quantitative magnetic resonance (QMR) is a new technology for measuring the body composition (wet lean mass, fat mass, and total body water mass) of unrestrained and unanesthetized animals. We conducted a validation study using two species of crayfish (mass range 5.5–27 g), American lobsters (680–732 g), and Madagascar hissing cockroaches (6.5–14 g) to assess the utility of QMR for quantifying the body composition of crustaceans and other large arthropods. A comparison of crayfish, lobster, and cockroach wet lean, fat, and body water masses calculated by QMR with those obtained from the traditional chemical extraction method demonstrates that QMR is a valid technology for analysis of wet lean mass and body water. Fat mass could not be accurately predicted, although this might be improved with the use of a QMR analyzer designed specifically for animals of low fat content. QMR analysis allows rapid (<4 min) and non‐destructive determination of body composition in field and lab environments, enabling researchers to conduct longitudinal studies and to increase the ethicality and practicality of studying rare or threatened species.     

Quantitative magnetic resonance analysis and a morphometric predictive model reveal lean body mass changes in migrating Nearctic–Neotropical passerines

Most studies of lean mass dynamics in free-living passerine birds have focused on Old World species at geographical barriers where they are challenged to make the longest non-stop flight of their migration. We examined lean mass variation in New World passerines in an area where the distribution of stopover habitat does not require flights to exceed more than a few hours and most migrants stop flying well before fat stores near exhaustion. We used either quantitative magnetic resonance (QMR) analysis or a morphometric model to measure or estimate, respectively, the fat and lean body mass of migrants during stopovers in New York, USA. With these data, we examined (1) variance in total body mass explained by lean body mass, (2) hourly rates of fat and lean body mass change in single-capture birds, and (3) net changes in fat and lean mass in recaptured birds. Lean mass contributed to 50% of the variation in total body mass among white-throated sparrows Zonotrichia albicollis and hermit thrushes Catharus guttatus. Lean mass of refueling gray catbirds Dumetella carolinensis and white-throated sparrows, respectively, increased 1.123 and 0.320 g h⁻¹. Lean mass of ovenbirds Seiurus aurocapillus accounted for an estimated 33–40% of hourly gains in total body mass. On average 35% of the total mass gained among recaptured birds was lean mass. Substantial changes in passerine lean mass are not limited to times when birds are forced to make long, non-stop flights across barriers. Protein usage during migration is common across broad taxonomic groups, migration systems, and migration strategies.     

The influence of body composition, fat distribution, and sustained weight loss on left ventricular mass and geometry in obesity

Alterations in left ventricular mass and geometry vary along with the degree of obesity, but mechanisms underlying such covariation are not clear. In a case–control study, we examined how body composition and fat distribution relate to left ventricular structure and examine how sustained weight loss affects left ventricular mass and geometry. At the 10‐year follow‐up of the Swedish obese subjects (SOS) study cohort, we identified 44 patients with sustained weight losses after bariatric surgery (surgery group) and 44 matched obese control patients who remained weight stable (obese group). We also recruited 44 matched normal weight subjects (lean group). Dual‐energy X‐ray absorptiometry, computed tomography, and echocardiography were performed to evaluate body composition, fat distribution, and left ventricular structure. BMI was 42.5 kg/m², 31.5 kg/m², and 24.4 kg/m² for the obese, surgery, and lean groups, respectively. Corresponding values for left ventricular mass were 201.4 g, 157.7 g, and 133.9 g (P < 0.001). In multivariate analyses, left ventricular diastolic dimension was predicted by lean body mass (β = 0.03, P < 0.001); left ventricular wall thickness by visceral adipose tissue (β = 0.11, P < 0.001) and systolic blood pressure (β = 0.02, P = 0.019); left ventricular mass by lean body mass (β = 1.23, P < 0.001), total body fat (β = 1.15, P < 0.001) and systolic blood pressure (β = 2.72, P = 0.047); and relative wall thickness by visceral adipose tissue (β = 0.02, P < 0.001). Left ventricular adjustment to body size is dependent on body composition and fat distribution, regardless of blood pressure levels. Obesity is associated with concentric left ventricular remodeling and sustained 10‐year weight loss results in lower cavity size, wall thickness and mass.     

Estimating lipid and lean body mass in small passerine birds using TOBEC,external morphology and subcutaneous fat‐scoring

To assess regression models for lipid and lean body mass in small birds, we recorded live body mass ±0.1 g, total body electrical conductivity (TOBEC; from “third generation” TOBEC machine EM‐SCAN® SA‐3000) or E‐Value, visual fat score (VisFat), and seven body measurements for 52 migratory passerine birds of 13 species (5–40 g). We determined lipid and lean mass of each bird after petroleum‐ether extraction of lipids. We obtained “net”E‐Value (NEV) for each scanned bird by subtracting the E‐Value of the empty bird‐restraining tube, because these showed an inverse temperature dependence (P<0.005). Leave‐one‐out cross validation was used to assess model selection and construct 95% confidence intervals. Although precision of TOBEC increased with bird size (CV of NEV vs. live mass: r=−0.276, P=0.002) and it explained an increasing proportion of variation in lean mass moving from small‐ to medium‐ to large‐bird classes of our data, it did no better than head length in single‐variable prediction of lean or lipid mass and was included in five of the 14 multivariate models we developed. The best multiple regression to predict lean mass included live weight, VisFat, bill length, tarsus and lnNEV (adjusted R²=99.0%); however, the same model lacking only lnNEV yielded aR²=98.9%. A parallel to the above pair of models, but predicting lipid mass, yielded aR²=90.3% and 90.0%, respectively. Subdividing the data by three size classes and three taxa (American redstart Setophaga ruticilla, ovenbird Seiurus aurocapilla, warblers), best‐subset multiple‐regression models predicted lean mass with aR² from 94.7 to 99.6% and lipid mass with aR² from 85.4 to 98.3%. Best models for the size‐ and species‐groups included VisFat and zero to five body measurements, and most included live weight. lnNEV was included only in the models for ovenbird (lipid), warblers (lipid), all birds (both), and large birds (both). Actual lipid mass of all birds was more highly correlated with multiple‐regression‐predicted lipid mass (r=0.955) than with visual subcutaneous fat‐scoring (r=0.683). These multiple‐regression models predicting lipid content using live‐bird measurements and visual fat score as independent variables represent more accurate and precise estimates of actual lipid content in small passerines than any previously published. They are particularly accurate for placing birds into percentage body‐fat classes.     

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 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.     

Resting Energy Expenditure Changes With Weight Loss: Racial Differences

It is controversial whether weight loss reduces resting energy expenditure (REE) to a different magnitude in black and white women. This aim of this study was to determine whether changes in REE with weight loss were different between black and white postmenopausal women, and whether changes in body composition (including regional lean and fat mass) were associated with REE changes within each race. Black (n = 26) and white (n = 65) women (age = 58.2 ± 5.4 years, 25 < BMI < 40 kg/m²) completed a 20‐week weight‐loss intervention. Body weight, lean and fat mass (total body, limb, and trunk) via dual‐energy X‐ray absorptiometry, and REE via indirect calorimetry were measured before and after the intervention. We found that baseline REE positively correlated with body weight, lean and fat mass (total, limb, and trunk) in white women only (P < 0.05 for all). The intervention decreased absolute REE in both races similarly (1,279 ± 162 to 1,204 ± 169 kcal/day in blacks; 1,315 ± 200 to 1,209 ± 185 kcal/day in whites). REE remained decreased after adjusting for changes in total or limb lean mass in black (1,302–1,182 kcal/day, P = 0.043; 1,298–1,144 kcal/day, P = 0.006, respectively), but not in white, women. Changes in REE correlated with changes in body weight (partial r = 0.277) and fat mass (partial r = 0.295, 0.275, and 0.254 for total, limb, and trunk, respectively; P < 0.05) independent of baseline REE in white women. Therefore, with weight loss, REE decreased in proportion to the amount of fat and lean mass lost in white, but not black, women.     

Postabsorptive VLDL‐TG Fatty Acid Storage in Adipose Tissue in Lean and Obese Women

Adipose tissue lipoprotein lipase (LPL) is a necessary enzyme for storage of very‐low‐density lipoprotein–triglyceride (VLDL‐TG), but whether it is a rate‐determining step is unknown. To test this hypothesis we included 10 upper‐body obese (UBO), 11 lower‐body obese (LBO), and 8 lean women. We infused ex vivo‐labeled VLDL‐¹⁴C‐TG and then performed adipose tissue biopsies to understand the relationship between VLDL‐TG storage and LPL activity in femoral and upper‐body subcutaneous fat. Both fractional tracer storage and rate of storage of the VLDL‐TG tracer were evaluated. VLDL‐TG storage was also examined as a function of regional adipose tissue blood flow (ATBF), insulin, VLDL‐TG turnover, regional fat mass, fat‐free mass (FFM), and fat cell size. LPL activity per adipocyte was significantly greater in obese than lean women but not significantly different per gram lipid. Both VLDL‐TG fractional tracer storage per kg lipid and VLDL‐TG storage rate per kg lipid were similar in abdominal and femoral fat in all three groups and were not significantly different between groups. Multiple regression analysis identified FFM and femoral fat mass as significant independent predictors of VLDL‐TG fractional tracer storage and insulin as a significant predictor of VLDL‐TG fatty acid storage rate. LPL activity, ATBF, and VLDL‐TG turnover did not predict VLDL‐TG storage. We conclude that lower FFM and greater plasma insulin are associated with greater VLDL‐TG deposition in abdominal subcutaneous and femoral fat. Greater femoral fat mass signals greater femoral VLDL‐TG storage. We suggest that the differences in VLDL‐TG storage in abdominal and femoral fat that occur with progressive obesity are regulated through mechanisms other than LPL activity.     

Quantitative Magnetic Resonance Fat Measurements in Humans Correlate With Established Methods but Are Biased

Precision and accuracy of the quantitative magnetic resonance (QMR) system for measuring fat in phantoms and total body fat (TBF) in humans were investigated. Measurements were made using phantoms: oil, beef with water, beef with oil, and humans with oil and water. TBF_QMR in humans was compared with TBF by a four‐compartment model (TBF_4C). The coefficient of variation (CV) for replicate TBF_QMR was 0.437%. QMR fat was lower at 23 °C vs. 37 °C. The fat increase in QMR phantom studies was consistent with the oil increase. When oil was added with humans, the increase in TBF_QMR was >250 g for the initial 250 g of oil. With additional oil increments, the increase in TBF_QMR was consistent with the amount of oil added. When water was added with humans, the TBF_QMR increased independent of the amount of water added. TBF_QMR was significantly less (mean ± s.e.) than TBF_4C (females: ?0.68 ± 0.27 kg, males: ?4.66 ± 0.62 kg; P = 0.0001), TBF_BV (females: ?1.90 ± 0.40 kg; males: ?5.68 ± 0.75 kg; P = 0.0001), and TBF_D2O for males, but greater for females (1.19 ± 0.43 kg vs. ?3.69 ± 0.81 kg for males; P = 0.0003). TBF_QMR was lower than TBF_iDXA with the difference greater in males (P = 0.001) and decreased with age (P = 0.011). The strong linear relationships between TBF_QMR and TBF_4C, TBF_BV, and TBF_D2O with slopes consistent with unity suggest that modifications are required to improve the accuracy. Should the latter be accomplished, QMR holds promise as a highly precise, rapid, and safe, noninvasive method for estimating the amount of and changes in TBF in overweight and severely obese persons.     

Effects of Obesity on Substrate Utilization during Exercise

Objective: The capacity for lipid and carbohydrate (CHO) oxidation during exercise is important for energy partitioning and storage. This study examined the effects of obesity on lipid and CHO oxidation during exercise. Research Methods and Procedures: Seven obese and seven lean [body mass index (BMI), 33 ± 0.8 and 23.7 ± 1.2 kg/m², respectively] sedentary, middle‐aged men matched for aerobic capacity performed 60 minutes of cycle exercise at similar relative (50% Vo _2max) and absolute exercise intensities. Results: Obese men derived a greater proportion of their energy from fatty‐acid oxidation than lean men (43 ± 5% 31 ± 2%; p = 0.02). Plasma fatty‐acid oxidation determined from recovery of infused [0.15 μmol/kg fat‐free mass (FFM) per minute] [1‐¹³C]‐palmitate in breath CO₂ was similar for obese and lean men (8.4 ± 1.1 and 29 ± 15 μmol/kg FFM per minute). Nonplasma fatty‐acid oxidation, presumably, from intramuscular sources, was 50% higher in obese men than in lean men (10.0 ± 0.6 versus 6.6 ± 0.8 μmol/kg FFM per minute; p < 0.05). Systemic glucose disposal was similar in lean and obese groups (33 ± 8 and 29 ± 15 μmol/kg FFM per minute). However, the estimated rate of glycogen‐oxidation was 50% lower in obese than in lean men (61 ± 12 versus 90 ± 6 μmol/kg FFM per minute; p < 0.05). Discussion: During moderate exercise, obese sedentary men have increased rates of fatty‐acid oxidation from nonplasma sources and reduced rates of CHO oxidation, particularly muscle glycogen, compared with lean sedentary men.     

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.     

Normal vs. high‐protein weight loss diets in men: Effects on body composition and indices of metabolic syndrome

Objective:

This study assessed the effectiveness of a prescribed weight‐loss diet with 0.8 versus 1.4 g protein·kg^?1 day^?1 on changes in weight, body composition, indices of metabolic syndrome, and resting energy expenditure (REE) in overweight and obese men.

Design and Methods:

Men were randomized to groups that consumed diets containing 750 kcal day^?1 less than daily energy needs for weight maintenance with either normal protein (NP, n = 21) or higher protein (HP, n = 22) content for 12 weeks. The macronutrient distributions of the NP and HP diets were 25:60:15, and 25:50:25 percent energy from fat, carbohydrate, and protein, respectively. Assessments were made pre and post intervention. The subjects were retrospectively subgrouped into overweight and obese groups.

Results and Conclusion:

Both diet groups lost comparable body weight and fat. The HP group lost less lean body mass than the NP group (?1.9 ± 0.3 vs. ?3.0 ± 0.4 kg). The effects of protein and BMI status on lean body mass loss were additive. The reductions in total cholesterol, HDL‐C, triacylglycerol, glucose, and insulin, along with LDL‐C, total cholesterol‐to‐HDL‐C ratio, and HOMA‐IR, were not statistically different between NP and HP. Likewise, macronutrient distributions of the diet did not affect the reductions in REE, and blood pressure. In conclusion, energy restriction effectively improves multiple clinical indicators of cardiovascular health and glucose control, and consumption of a higher‐protein diet and accomplishing weight loss when overweight versus obese help men preserve lean body mass over a short period of time.

     

The effect of pioglitazone and resistance training on body composition in older men and women undergoing hypocaloric weight loss

Age‐related increases in ectopic fat accumulation are associated with greater risk for metabolic and cardiovascular diseases, and physical disability. Reducing skeletal muscle fat and preserving lean tissue are associated with improved physical function in older adults. PPARγ‐agonist treatment decreases abdominal visceral adipose tissue (VAT) and resistance training preserves lean tissue, but their effect on ectopic fat depots in nondiabetic overweight adults is unclear. We examined the influence of pioglitazone and resistance training on body composition in older (65–79 years) nondiabetic overweight/obese men (n = 48, BMI = 32.3 ± 3.8 kg/m²) and women (n = 40, BMI = 33.3 ± 4.9 kg/m²) during weight loss. All participants underwent a 16‐week hypocaloric weight‐loss program and were randomized to receive pioglitazone (30 mg/day) or no pioglitazone with or without resistance training, following a 2 × 2 factorial design. Regional body composition was measured at baseline and follow‐up using computed tomography (CT). Lean mass was measured using dual X‐ray absorptiometry. Men lost 6.6% and women lost 6.5% of initial body mass. The percent of fat loss varied across individual compartments. Men who were given pioglitazone lost more visceral abdominal fat than men who were not given pioglitazone (?1,160 vs. ?647 cm³, P = 0.007). Women who were given pioglitazone lost less thigh subcutaneous fat (?104 vs. ?298 cm³, P = 0.002). Pioglitazone did not affect any other outcomes. Resistance training diminished thigh muscle loss in men and women (resistance training vs. no resistance training men: ?43 vs. ?88 cm³, P = 0.005; women: ?34 vs. ?59 cm³, P = 0.04). In overweight/obese older men undergoing weight loss, pioglitazone increased visceral fat loss and resistance training reduced skeletal muscle loss. Additional studies are needed to clarify the observed gender differences and evaluate how these changes in body composition influence functional status.     

Percent Body Fat and Lean Mass Explain the Gender Difference in Leptin: Analysis and Interpretation of Leptin in Hispanic and Non‐Hispanic White Adults

Objective: To reassess the relationship between body fat and fasting leptin concentrations comparing plasma vs. serum assessments of leptin; ratios vs. regression adjustment for body composition; fat and lean mass vs. percent body fat; and gender‐, ethnic‐, and age‐related variations. Research Methods and Procedures: Subjects included 766 adults from the nondiabetic cohort of the San Luis Valley Diabetes Study examined at follow up (1997 to 1998). Body composition was determined by dual energy X‐ray absorptiometry. Leptin concentrations were determined after an overnight fast. Results: Fasting serum and plasma assessments of leptin were correlated with percent body fat to the same degree. Women had significantly higher serum leptin concentrations than men when leptin concentrations were divided by body mass index, fat mass in kilograms or percent body fat. The methodological problem inherent in interpreting these ratio measures is pictorially demonstrated. In regression analysis, fat mass alone did not explain the gender difference. However, lean body mass was inversely related to leptin concentrations (p < 0.0001) and explained 71% of the gender difference at a given fat mass. Percent body fat explained all of the gender difference in leptin concentrations in both Hispanics and non‐Hispanic whites. Similar to findings about gender differences, ethnic‐ and age‐related variations in the leptin‐body fat association were minimized when percent body fat was employed as the body fat measure. Discussion: Regression analysis and percent body fat measured with dual energy X‐ray absorptiometry are recommended when assessing the relationship between leptin and body fat. Gender differences in leptin concentrations were accounted for by percent body fat in free living (no diet control), Hispanic and non‐Hispanic white adults.