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.     

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.     

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.     

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.     

Urinary C-peptide is not an accurate bioindicator of energy balance in humans

The apprehension of the factors that affect long term regulation of energy balance is indispensable to understand the rise in obesity prevalence as well as to delineate levers to prevent it. Accurate measurements of energy balance are however challenging during free‐living conditions. Recent studies proposed urinary C‐peptide, a metabolic byproduct of insulin synthesis, as reliable noninvasive assessment of energy balance. These studies were in fact essentially based on correlations between urinary C‐peptide and energy intake and only focused on nonhuman primates. During a bed‐rest study conducted in 16 healthy women in a controlled environment, we tested the existence of a relationship between 24 h‐urinary C‐peptide and energy balance in humans. Daily energy intake and body mass, body composition (dual‐energy X‐ray absorptiometry (DXA)) and total energy expenditure (doubly labeled water (DLW) method) was measured and energy balance was calculated as the difference between energy intake and expenditure. Urinary C‐peptide was positively correlated with bed‐rest‐induced changes in fat mass (r² = 0.285; P = 0.03) and energy balance assessed at the end of the bed‐rest (r² = 0.302; P = 0.027). However, in this tightly controlled environment, urinary C‐peptide only accounted for 30% of variations in energy balance. No relationship was noted between urinary C‐peptide and body or fat mass both at baseline and at the end of the bed‐rest. These results indicate that urinary C‐peptide cannot be used as an accurate biomarker of energy balance in the general human population in free‐living conditions.     

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.     

Strategic Regulation of Body Mass and Singing Behavior in New Zealand Robins

The ‘small bird in winter’ paradigm states that body mass is a balance between the conflicting demands of carrying enough energy to survive nightly fasts while minimizing the risk of predation associated with carrying additional fat reserves. We conducted a short‐term food‐supplementation experiment during which New Zealand robins (Petroica australis) were provided with food on the second day of a 3‐d trial. This allowed us to test two predictions from models of strategic mass regulation in small birds: (1) individual birds reach the same end‐of‐day mass despite differences in their initial morning mass while, (2) using surplus energy for increased singing. As expected, robins gained mass at a higher rate early in the morning on the fed day than they did on either of the two control days, but there was no significant difference in their evening masses across the 3 d of the experiment despite birds on day 3 starting at higher initial masses than birds on day 1. Robins displayed a significantly higher rate of singing when receiving food supplements on day 2, supporting a link between energetic reserves and behavior. Our results suggest that potentially energetically costly behaviors, such as song production, are sensitive to short‐term changes in energy reserves, and that both state and behavioral predictions can be successfully integrated to provide tests of state‐based models of behavior.     

The Trp64Arg Polymorphism of the β3‐Adrenergic Receptor Gene Is Not Associated with Training‐Induced Changes in Body Composition: The HERITAGE Family Study

Objective: To investigate the association between the Trp64Arg polymorphism of the β3‐adrenergic receptor gene and changes in body composition in response to endurance training. Research Methods and Procedures: Adult sedentary white and black subjects participating in the HERITAGE Family Study were measured before and after 20 weeks on endurance training for the body mass index, fat mass, percentage of body fat, fat‐free mass, sum of eight skinfolds, and subcutaneous, visceral, and total abdominal fat areas. The association between the Trp64Arg polymorphism and the response phenotypes, computed as the difference between pre‐ and post‐training values, was tested by analysis of covariance separately in men and women. The gene by race interaction term was also tested. Results: No race differences were observed for allelic and genotype frequencies. Training resulted in significant reduction of body fat in both men and women. No association of the Trp64Arg polymorphism was observed with training‐induced changes for any of the body composition phenotypes in both men and women. Discussion: These results suggest that the Trp64Arg polymorphism of the β3‐adrenergic receptor gene is not related to changes in body composition in response to exercise training.     

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.     

Fat Intake Affects Adiposity,Comorbidity Factors,and Energy Metabolism of Sprague‐Dawley Rats

Objective: Childhood obesity is an emerging health problem. This study assesses the effects of three levels of dietary fat (10%, 32%, and 45% measured by kilocalories) on weight gain, body composition, energy metabolism, and comorbidity factors in rats from weaning through maturation. Research Methods and Procedures: The role of dietary fat on the susceptibility to obesity was assessed by feeding diets containing three levels of dietary fat to rats from weaning through 7 months of age. Body composition was analyzed by DXA after 6 and 12 weeks of dietary treatment. Energy metabolism was measured by indirect calorimetry. Results: Energy intake, weight gain, fat mass, and plasma glucose, cholesterol, triglyceride, free fatty acid, leptin, and insulin levels increased dose‐dependently with increased dietary fat. No difference in absolute lean mass among the three groups was observed. Therefore, the differences in weight gain are accounted for primarily by increased fat accretion. Compared with rats that were relatively resistant to obesity when on a 45% fat diet, diet‐induced obesity‐prone rats were in positive energy balance and had an elevated respiratory quotient, indicating a switch in energy substrate use from fat to carbohydrate, which promotes body‐fat accretion. Discussion: Our data support the hypothesis that administration of increasing amount of dietary fat to very young rats enhances susceptibility to diet‐induced obesity and its comorbidities.     

Changes in body composition with weight loss: obese subjects randomized to surgical and medical programs

Objective: To assess changes in body composition with weight loss in obese subjects randomized to a laparoscopic adjustable gastric band surgical program or a medical program using a very‐low‐energy diet and orlistat. Research Methods and Procedures: Using body composition measurements by DXA, neutron activation for total body nitrogen, and whole body γ counting for total body potassium, we studied changes in fat mass, fat distribution, fat‐free mass, total bone mineral content, total body protein, and body cell mass at 6 (n = 61 paired) and 24 months (n = 53 paired) after randomization. Results: At 24 months, the surgical group had lost significantly more weight (surgical, 20.3 ± 6.5 kg; medical, 5.9 ± 8.0 kg). There was favorable fat‐free mass to fat mass loss ratios for both groups (surgical, 1:5.5; medical, 1:5.9). Changes in total body nitrogen or potassium were favorable in each group. A small reduction in mean bone mineral content occurred throughout the study but was not associated with extent of weight loss or treatment group. At 6 months, weight loss for both groups was similar (surgical, 14.1 ± 4.5 kg; medical, 13.3 ± 7.3 kg). The medical program subjects lost less fat‐free mass and skeletal muscle and had increased total body protein. The proportion of body fat to limb fat remained remarkably constant throughout the study. Discussion: Weight loss programs used in this study induced fat loss without significant deleterious effects on the components of fat‐free mass.     

Starvation survival and body composition in mammals with particular reference toHomo sapiens

A computer model of body mass and composition in relation to gross energy balance is constructed. The model is built using conventional empirical physiological formulae rather than statistical or analytical mathematical techniques. The model is applied to the Minnesota and other experiments and produces as good or better simulations of observed values of changes in body weight than reported for other formulae or models. Alternative physiological mechanisms concerning metabolic adaptions to starvation, changes in time activity budgets and the energy equivalents of weight loss offer equally good simulations of experimental results. The present analysis highlights the survival value of a basal metabolic depression during starvation and indicates an optimal body composition of 10% mobilizable fat for starvation survival for a 70 kg man. Proper quantification of the effects of the physiological mechanisms involved depends on new experimental data, however. Long term continuous monitoring of time activity budgets are a necessary part of such experiments.     

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.     

Body composition of obese subjects by air displacement plethysmography: The influence of hydration

Objective: We investigated whether air displacement plethysmography (ADP) could detect small changes in body composition of obese subjects with alterations in hydration. Research Methods and Procedures: Ten obese subjects (mean BMI, 39.3 ± 2.8 kg/m²) entered the ADP chamber without and with oil (1, 2, or 4 liters), water (1, 2, or 4 liters), or mixed (1 liter oil + 1 liter water or 2 liters oil + 2 liters water) loads. Real and measured changes in body composition were compared by regression analysis and Bland‐Altman procedures. Results: The ADP‐measured changes in volume did not differ from the real values and were strongly correlated with them (r = 0.98). In all cases, loads of differing composition and similar volume led to different values of fat, fat‐free mass, and percentage fat. Water was detected as increased fat‐free mass only with loads of ≥2 liters, most of the water being falsely detected as increased fat mass. The observed changes were correlated with the real ones for fat mass (r = 0.68; p < 0.0001), fat‐free mass (r = 0.66; p < 0.0001), and percentage fat (r = 0.61; p < 0.0001), but fat mass changes were overestimated by ～1 kg, and fat‐free mass changes were underestimated by ～1 kg. This underestimation increased with the highest water loads, as shown by the Bland‐Altman plot (r = ?0.27; p < 0.05). Percentage fat changes were overestimated by 0.8% (p < 0.001); the magnitude of the error was correlated with the weight of the water load (r = 0.62; p < 0.0001). Discussion: ADP accurately measures changes in body volume, discriminating small changes in body composition. It overestimates changes in adiposity, as most of the increased hydration is detected as an enlarged fat mass.     

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.     

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.     

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.     

Low Resting and Sleeping Energy Expenditure and Fat Use Do Not Contribute to Obesity in Women

Objective: Determine whether sleeping and resting energy expenditure and sleeping, resting, and 24‐hour fuel use distinguish obesity‐prone from obesity‐resistant women and whether these metabolic factors explain long‐term weight gain. Research Methods and Procedures: Forty‐nine previously overweight but currently normal‐weight women were compared with 49 never‐overweight controls. To date, 87% of the 98 women have been re‐evaluated after 1 year of follow‐up, without intervention, and 38% after 2 years. Subjects were studied at a General Clinical Research Center after 4 weeks of tightly controlled conditions of energy balance and macronutrient intake. Forty‐nine obesity‐prone weight‐reduced women were group‐matched with 49 never‐overweight obesity‐resistant controls. All were premenopausal, sedentary, and normoglycemic. Energy expenditure and fuel use were assessed using chamber calorimetry. Body composition was assessed using DXA. Results: At baseline, percent body fat was not different between the obesity‐prone and control women (33 ± 4% vs. 32 ± 5%, respectively; p = 0.22). Analysis of covariance results show that after adjusting for lean and fat mass, sleeping and resting energy expenditure of obesity‐prone women was within 2% of controls. Neither sleeping nor resting energy expenditure nor sleeping, resting, or 24‐hour fuel use was significantly different between the groups (p > 0.25). None of the metabolic variables contributed significantly to patterns of weight gain at 1 or 2 years of follow‐up. Discussion: The results suggest that when resting and sleeping energy expenditure and fuel use are assessed under tightly controlled conditions, these metabolic factors do not distinguish obesity‐prone from obesity‐resistant women or explain long‐term weight changes.     

Does avian winter fat storage integrate temperature and resource conditions? A long‐term study

Theoretical models of short‐term avian behaviour suggest that small birds adaptively balance the ecological costs and benefits of winter fat to maximize survival probability. When low starvation risk eliminates benefit but not cost of fat, birds are leaner than when under high starvation risk. Most models focus on single factors affecting starvation risk and subsequent choice of adaptive body mass; however, in complex environments, more than one factor affects starvation risk. To test for multiple interacting factors affecting fat reserves, long‐term geographical data on winter fat in a ground‐feeding finch, the dark‐eyed junco Junco hyemalis were analyzed. Two measures of fat were used: (1) visible subcutaneous fat class, and (2) body mass residuals left after age, sex and wing length effects were factored out. Site means for fat measures were obtained from juncos visiting supplemental feeding sites in midwest and northwest North America. In backward elimination regression of fat class, the temperature‐snowfall interaction term and its constituent variables, proximate temperature (averaged over capture day and the preceding ten days) and snowfall (frequency over the same time interval) were significant explanators of variation. Snowfall frequency is considered to be a surrogate measure of resource deterioration. The interaction term, also found in backward regression of body mass residuals, showed that as temperature declined at low snowfall frequency, less fat was deposited than when temperature declined at high snowfall frequency. Thus, in a recently cold environment suggesting relatively high resource predictability, perceived starvation risk is low, and less costly fat is needed to reduce starvation risk compared to a cold and unpredictable resource environment. The analysis of mass residuals also yielded a significant effect of daylength, suggesting an underlying fattening programme independent of proximate environmental conditions. A longitudinal study of junco fat stores indicated that individual environmental responses contributed significantly to midwinter fat peaks. These results agree with predictions of a synergistic model of adaptive fat regulation in small birds by suggesting that a ground‐feeding bird may maximize winter survival probability by integrating multiple environmental factors affecting starvation risk.