Weight loss and resting energy expenditure in male patients with newly diagnosed esophageal cancer

ObjectivesCancer cachexia is associated with impaired nutritional status and systemic inflammation. The goal of this study was to evaluate the nutritional status and resting energy expenditure (REE) changes in patients with newly detected esophageal cancer, and the influence of weight loss on REE.MethodsFifty-six patients and 30 healthy controls were prospectively enrolled, and patients were further divided into weight-stable (WS) and weight-loss (WL) subgroups. Body composition, measured REE (mREE), and the ratio of mREE to predicted REE (pREE) by Harris-Benedict formula were assessed. Blood levels of hemoglobin, albumin, prealbumin, high-sensitivity C-reactive protein (hs-CRP), tumor necrosis factor-alpha (TNF-α), and interleukin (IL)-6 were measured in patients.ResultsCancer patients had lower body mass index (BMI) and percentage of fat mass, but higher mREE and percentage of mREE/pREE compared with healthy controls (P < 0.05). WS (n = 32) and WL patients (n = 24) had similar BMI and body composition indices, but the latter had obviously higher mREE, mREE per kilogram body weight (mREE/BW), percentage of mREE/pREE, hs-CRP and IL-6 levels, and lower albumin and prealbumin levels. Percentage of weight loss was positively correlated with REE/BW, hs-CRP, and IL-6 level (r = 0.238, P = 0.044; r = 0.446, P = 0.01; r = 0.196, P = 0.047, respectively).ConclusionImpaired nutrition status, elevated energy expenditure, and higher inflammation status tend to be apparent in weight-losing patients with newly diagnosed esophageal cancer, which suggested that early recognition of body weight change and routine nutritional risk screening followed by adequate nutrition intervention should be applied in these patients.     

Changes in Resting Energy Expenditure Following Orthotopic Liver Transplantation

Background:There is no consensus whether resting energy expenditure (REE) following orthotopic liver transplantation (OLT) is altered. Methods: The objectives of this investigation were to describe changes in measured REE (mREE) using indirect calorimetry in 25 OLT patients on days 5, 10, and 15 after baseline (within 72 hours following OLT) and compare mREE changes with those calculated with 2 predicted equations for energy expenditure (pREE): the Harris‐Benedict and Schofield equations. Results: Patients were 57 ± 5.4 years of age, 44% were male, 36% were black, and 72% had liver disease of viral etiology. Measured REE (at baseline and days 5, 10, and 15, per kcal/d: 1832 ± 952, 1565 ± 383, 1538 ± 345, 1578 ± 418) and kcal per kilogram of body weight (22.7 ± 12.8, 18.4 ± 4, 18.7 ± 3.8, 21 ± 6.5) did not change over time. In contrast, changes in pREE based on either the Harris‐Benedict (P < .001) or Schofield (P = .006) equation using measured weights at each corresponding time point and lowest body weight during the study to estimate dry weight were significant. Conclusions: Wide ranges in both mREE and mREE expressed per kilogram of body weight at each study time point were observed in contrast to pREE, which declined by day 15. The observed differences in mREE over time suggest indirect calorimetry is indicated if available following OLT. Additional research is warranted to determine the most appropriate predictive equation with suitable stress factors to use when indirect calorimetry is not available.     

Lack of adaptation to severe malnutrition in elderly patients

BACKGROUND & AIMS: Sarcopenia is a common feature in the healthy elderly. However, little is known on age-related modifications of body composition in malnourished patients. The aims of this cross-sectional study were to evaluate the effects of aging per se on body composition and resting energy expenditure (REE) in malnourished patients. METHODS: Ninety-seven non-stressed patients referred for chronic malnutrition (C-reactive protein <5 mg/l) were separated into two groups: middle-aged (26 female, 19 male, 48+/-15 yr), and elderly (26 female, 26 male, 79+/-6 yr). Body composition was assessed by bioelectrical impedance analysis and REE by indirect calorimetry. RESULTS: In middle-aged patients, body composition remained stable between moderate (body-mass index [BMI; in kg/m(2)] 16-18.5) and severe (BMI < 16) malnutrition, with similar values of fat-free mass (FFM), body cell mass (BCM) and fat mass (FM) as percentages of body weight, whereas in elderly patients malnutrition occurred at the expense of FFM and BCM, with unchanged FM absolute values. REE/FFM values remained stable in middle-aged patients at every stage of malnutrition, whereas they increased in elderly patients along with their degree of malnutrition. In multivariate analysis, both body composition and REE/FFM were influenced by sex, age, BMI and mid-arm circumference. CONCLUSION: Compared to younger patients, weight loss in the elderly leads to cachexia, with a preferential loss of FFM and BCM that may participate in the more severe outcomes observed in these patients. They also show elevated REE/FFM values that induce higher energy needs.     

Weight loss and elevated gluconeogenesis from alanine in lung cancer patients

BACKGROUND: The role of gluconeogenesis from protein in the pathogenesis of weight loss in lung cancer is unclear. OBJECTIVE: Our aim was to study gluconeogenesis from alanine in lung cancer patients and to analyze its relation to the degree of weight loss. DESIGN: In this cross-sectional study, we used primed-constant infusions of [6,6-(2)H(2)]-D-glucose and [3-(13)C]-L-alanine to assess whole-body glucose and alanine turnover and gluconeogenesis from alanine in weight-losing (WL, n = 9) and weight-stable (WS, n = 10) lung cancer patients and healthy control (n = 15) subjects. RESULTS: Energy intake and plasma alanine concentrations did not differ significantly among the subject groups. Mean (+/-SEM) whole-body glucose production was significantly higher in WL than in WS and control subjects (0.74 +/- 0.06 compared with 0.55 +/- 0.04 and 0.51 +/- 0.04 mmol*kg(-)(1)*h(-)(1), respectively, P < 0.01). Alanine turnover was significantly elevated in WL compared with WS and control subjects (0.57 +/- 0.04 compared with 0.42 +/- 0.05 and 0.40 +/- 0.03 mmol*kg(-)(1)*h(-)(1), respectively, P < 0.01). Gluconeogenesis from alanine was significantly higher in WL than in WS and control subjects (0.47 +/- 0.04 compared with 0.31 +/- 0.04 and 0.29 +/- 0.04 mmol*kg(-)(1)*h(-)(1), respectively, P < 0.01). The degree of weight loss was positively correlated with glucose and alanine turnover and with gluconeogenesis from alanine (r = 0.45 for all, P < 0.01). CONCLUSIONS: Aberrant glucose and alanine metabolism occurred in WL lung cancer patients. These changes were related to the degree of weight loss and not to the presence of lung cancer per se.     

Low validity of predictive equations for calculating resting energy expenditure in overweight and obese women with polycystic ovary syndrome

Background

Predictive equations are the main clinical tools for determining resting energy expenditure (REE ). However, their adequate use in overweight and obese individuals is unclear. Thus, we investigated the best predictive equations for estimating REE in overweight and obese women with polycystic ovary syndrome (PCOS ).

Methods

Eleven analyses were performed with prediction equations (pREE ) based on anthropometric parameters in 30 overweight or obese women with PCOS without other chronic diseases. The measured REE (mREE ) was calculated by indirect calorimetry. The validity of the equations was investigated by comparison, accuracy and agreement tests between pREE and mREE at both the individual and group level.

Results

Four analyses were similar to those of mREE , and smallest mean differences were observed for the World Health Organization/Food and Agriculture Organization of the United Nations/United Nations University (WHO /FAO /UNU ) considering weight (W) [0.07 (1.13) MJ (16 [270] kcal)]. Individual accuracy was greater than 50% for Harris and Benedict, Müller and Lazzer equations. The percentage of REE underestimation ranged between 16.7% and 73.3%, whereas higher rates of overestimation were observed in the De Luis (66.7%) and Ireton‐Jones (43.3%) equations. Mean bias at the group level was lowest in the WHO /FAO /UNU W and WHO /FAO /UNU considering weight and height (WH ), Müller and Lazzer equations (–2.8 to 0.5). The WHO /FAO /UNU W and WHO /FAO /UNU WH formulas were optimal in individual agreement (33.3%).

Conclusions

FAO /WHO /UNU W equations may estimate the REE in overweight and obese women with PCOS . However, the low individual accuracy and agreement in relation to mREE suggest caution regarding when to use the formula to perform an individual nutritional plan.

     

Resting energy expenditure in patients with chronic obstructive pulmonary disease

Resting energy expenditure (REE) was measured in 68 patients with stable chronic obstructive pulmonary disease (COPD) and in 34 weight-stable, age-matched (65 +/- 8 y; means +/- SD) healthy control subjects. Fat-free mass (FFM) determined by bioelectrical resistance explained 84% of the variation in REE in the control group but only 34% in the COPD patients. REE could not reliably be predicted from regression equations either developed in healthy subjects or in COPD patients. REE adjusted for FFM was significantly higher (P less than 0.05) in weight-losing (n = 34) than in weight-stable (n = 34) patients (6851 +/- 781 and 6495 +/- 650 kJ/d, respectively). Pulmonary function was more compromised in weight-losing patients. Adjusted REE in weight-stable patients was significantly higher (P less than 0.01) than in the healthy control group (6131 +/- 405 kJ/d). In patients with COPD, factors in addition to FFM are important determinants of REE. A disease-related increase in REE develops, which may contribute to weight loss in COPD in combination with a lack of an adaptive response to undernutrition in weight-losing patients.     

The effect of a high protein-low calorie diet on the energy expenditure of obese adolescents.

Resting energy expenditure (REE), and body composition, as fat-free mass (FFM) and fat mass, were determined in seven obese adolescents before and after weight loss of a mean 13.5 kg on an approximately 800 kcal/d (3349 kJ), high protein reducing diet regimen. Ideal body weight decreased from 166% to 142% in 8 weeks. There were no significant changes in total body potassium (TBK), extracellular water (ECW), intracellular water (ICW) or total body water (TBW) with weight loss. The REE (kcal/d) fell from 2034 +/- 392 (8514 +/- 1641 kJ) to 1762 +/- 453 (7376 +/- 1896 kJ) with weight loss (P < 0.05). However, when the REE was expressed as kcal/body weight there was no difference between before and after weight loss, 21.4 +/- 2.8 (90 +/- 21 kJ) and 21.6 +/- 4.5 (90 +/- 19 kJ). Similarly, when REE was examined in relation to FFM (kcal/kg) before and after weight loss, there were also no significant differences: 34.6 +/- 5.1 (145 +/- 21 kJ) and 32.1 +/- 7.9 (134 +/- 33 kJ).     

Total and regional body composition and energy expenditure in multiple symmetric lipomatosis

AIMS: The aim of the present study was to investigate possible alterations in body composition and resting energy expenditure (REE) in type 1 multiple symmetric lipomatosis (MSL). SUBJECTS AND METHODS: Thirteen men aged from 40 to 78 years affected by type I MSL were compared with 13 healthy control subjects. Fat mass (FM) and fat-free mass (FFM) were determined by DEXA using both standard analysis and specifically for the lipomatous region. REE was measured by indirect calorimetry. RESULTS: FM was higher in MSL subjects at proximal arm level, but significantly lower at distal leg level than in controls (left 1.63+/-0.55 vs. 2.26+/-0.49 kg, P<0.05; right 1.63+/-0.53 vs. 2.40+/-0.54 kg, P<0.01). Arm FFM was similar in the two groups, while distal leg FFM was significantly lower in MSL cases (left: 7.8+/-1.3 vs. 8.7+/-0.8 kg, P<0.05; right: 8.0+/-1.5 vs. 9.2+/-0.9 kg, P<0.05). FFM strongly correlated with REE (r:0.86;P<0.001). REE, expressed as an absolute value and adjusted for FFM (1830+/-215 vs. 1675+/-120 kcal, P<0.05) was higher in MSL patients. CONCLUSION: In conclusion, MSL patients had a marked FFM and FM atrophy in the lower segments of the legs and an altered energy expenditure (hypermetabolism).     

Simple kcal/kg formula is comparable to prediction equations for estimating resting energy expenditure in older cognitively impaired long term care residents

Objective

Assessment of energy needs is a critical step in developing the nutrition care plan, especially for individuals unable to modulate their own energy intakes. The purpose of this study was to assess precision and accuracy of commonly used prediction equations in comparison to measured resting energy expenditure in a sample of “oldest old” adults residing in long term care (LTC).

Subjects and Design

Resting energy expenditure (mREE) was measured by indirect calorimetry in 45 residents aged 86.1 ± 7.3 years, and compared to frequently used prediction equations (pREE): Mifflin St.Jeor, Harris Benedict, World Health Organization and Owen. Precision and accuracy were determined by concordance correlation coefficients and number of individuals within ± 10% of mREE. Bland Altman plots with linear dependence trends were constructed to visualize agreement. To complete analyses, the common 25 kcal/kg formula was assessed and alternative formulas were determined for best fit by regressing adjusted mREE on body weight.

Results

mREE averaged 976.2 ± 190.3 kcal/day for females and 1260.0 ± 275.9 kcal/d for males. The strength of the relationships between pREE and mREE were only moderate (r = 0.41–0.72). In examining linear trends in the Bland Altman plots, significant systematic deviation from mREE was detected for all pREE. Two kcal/kg formulas were generated: 20.6 kcal/kg for females and 22.7 kcal/kg for males, which were not significantly different.

Conclusion

None of the prediction equations adequately estimated energy needs in this sample of the “oldest old.” A simple formula using 21–23 kcal/kg may be a more practical and reliable method to determine energy needs in the LTC setting.     

Energy balance in relation to cancer cachexia

The aim of the current study was to determine the contribution of increased resting energy expenditure (REE) and/or decreased energy intake (EI) to the development of weight loss in gastric and colorectal (GCR) and lung cancer patients. REE was measured in 22 GCR cancer patients and 17 lung cancer patients and was compared with REE values in 40 apparently healthy controls. REE in lung cancer patients expressed per kg fat free mass (REE/FFM) was significantly increased when compared to healthy controls (33.5 +/- 5.4 and 29.6 +/- 2.9 kcal, respectively; p < 0.01). GCR cancer patients had no elevated REE compared to these healthy controls. No significant differences in EI were established between the three groups. Eight GCR cancer patients reported a decrease in food intake compared to pre-disease intake, in contrast to only one lung cancer patient. Semi-starving GCR cancer patients showed a significant weight loss (8.7 +/- 8.1%), a low respiratory quoteint (RQ) (0.76 +/- 0.04) and a high beta-hydroxybutyrate level (259 +/- 192 mumol/l), but they showed no difference in REE compared to patients with a normal EI. The current study suggests that weight loss in GCR cancer patients is initiated by decreased food intake, whereas weight loss in lung cancer patients represents a combination of an increased REE and a relatively low EI.     

Energy requirements of urban Chinese adults with manual or sedentary occupations,determined using the doubly labeled water method

OBJECTIVE: To examine total energy expenditure (TEE) in relation to occupation and reported leisure time activities in free-living Chinese adults, and to determine whether measured TEE values differ from current international dietary energy recommendations. SETTING AND SUBJECTS: Seventy three weight-maintaining adults aged 35-49 y, leading unrestricted lives in urban Beijing, with a wide variety of occupations. DESIGN AND METHODS: A cross-sectional study in which TEE was determined by doubly labeled water, body composition by deuterium oxide ((2)H(2)O) dilution, resting energy expenditure (pREE) by prediction equations, and occupational and leisure time activities by questionnaire. RESULTS: For men and women respectively, TEE averaged 12.10+/-0.32 and 9.53+/-0.23 MJ/day (P<0.001), and physical activity level (PAL=TEE/pREE) was 1.77+/-0.04 and 1.66+/-0.02 (P<0.05). Fat-free mass (FFM) was the single best predictor of TEE (adjusted r(2)=0.71, P<0.001). Occupational category (light, moderate and heavy) further predicted TEE, independent of FFM (adjusted multiple r(2)=0.82, P<0.001). Both TEE adjusted for weight and PAL increased with occupational category. Measured TEE was slightly but significantly higher than the 1985 FAO/WHO/UNU estimates for women with light occupations, but did not differ from estimates for men with light occupations, or for adults with moderate or heavy occupations. CONCLUSION: Level of occupational activity, but not duration or type of leisure activity, significantly predicted TEE in free-living urban Chinese adults. Current energy requirement recommendations slightly underestimated the energy needs of women with light occupations but were accurate for men and women with moderate and heavy occupations. SPONSORSHIP: NIH grants DK53404 and F32-DK09747.     

Pilot Study to Explore the Accuracy of Current Prediction Equations in Assessing Energy Needs of Patients with Newly Diagnosed Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is rare, yet it is the most common brain malignancy and has a poor prognosis. In regard to GBM, there is a dearth of research on resting energy expenditure (REE) and the accuracy of extant prediction equations. The aim of this cross-sectional study was to compare measured REE (mREE) to commonly used prediction equations in newly diagnosed GBM patients. REE was collected by indirect calorimetry in 20 GBM patients. Calculated REE was derived from Harris-Benedict (again with weight adjusted for obesity), Mifflin-St Jeor, and the 20 kcal/kg body weight ratio method. Paired t-tests and Bland-Altman analyses were used to compare group means, evaluate the bias, and find the limits of agreement. Clinical accuracy was assessed by determining the percentage of patients with predicted REE within ±10% of mREE. Subjects were evenly distributed with regard to gender, primarily Caucasian, and largely overweight or obese and had a mean age of 57 years. All equations overestimated mREE. Mifflin-St Jeor and adjusted Harris-Benedict had the narrowest limits of agreement and accurately predicted 60% and 65% of subjects, respectively. Clinicians should be aware of the discrepancy between commonly used prediction equations and REE. More research is needed to verify these findings and decipher the cause and significance in the GBM population.     

Influence of methods used in body composition analysis on the prediction of resting energy expenditure

OBJECTIVE: There are considerable differences in published prediction algorithms for resting energy expenditure (REE) based on fat-free mass (FFM). The aim of the study was to investigate the influence of the methodology of body composition analysis on the prediction of REE from FFM. DESIGN: In a cross-sectional design measurements of REE and body composition were performed. SUBJECTS: The study population consisted of 50 men (age 37.1+/-15.1 years, body mass index (BMI) 25.9+/-4.1 kg/m2) and 54 women (age 35.3+/-15.4 years, BMI 25.5+/-4.4 kg/m2). INTERVENTIONS: REE was measured by indirect calorimetry and predicted by either FFM or body weight. Measurement of FFM was performed by methods based on a 2-compartment (2C)-model: skinfold (SF)-measurement, bioelectrical impedance analysis (BIA), Dual X-ray absorptiometry (DXA), air displacement plethysmography (ADP) and deuterium oxide dilution (D2O). A 4-compartment (4C)-model was used as a reference. RESULTS: When compared with the 4C-model, REE prediction from FFM obtained from the 2C methods were not significantly different. Intercepts of the regression equations of REE prediction by FFM differed from 1231 (FFM(ADP)) to 1645 kJ/24 h (FFM(SF)) and the slopes ranged between 100.3 kJ (FFM(SF)) and 108.1 kJ/FFM (kg) (FFM(ADP)). In a normal range of FFM, REE predicted from FFM by different methods showed only small differences. The variance in REE explained by FFM varied from 69% (FFM(BIA)) to 75% (FFM(DXA)) and was only 46% for body weight. CONCLUSION: Differences in slopes and intercepts of the regression lines between REE and FFM depended on the methods used for body composition analysis. However, the differences in prediction of REE are small and do not explain the large differences in the results obtained from published FFM-based REE prediction equations and therefore imply a population- and/or investigator specificity of algorithms for REE prediction.     

Energy cost of physical activity in cystic fibrosis

OBJECTIVE: The purpose of this study was to compare the energy cost of standardized physical activity (ECA) between patients with cystic fibrosis (CF) and healthy control subjects. DESIGN: Cross-sectional study using patients with CF and volunteers from the community. SETTING: University laboratory. SUBJECTS: Fifteen patients (age 24.6+/-4.6 y) recruited with consent from their treating physician and 16 healthy control subjects (age 25.3+/-3.2) recruited via local advertisement. INTERVENTIONS: Patients and controls walked on a computerised treadmill at 1.5 km/h for 60 min followed by a 60 min recovery period and, on a second occasion, cycled at 0.5 kp (kilopond), 30 rpm followed by a 60 min recovery. The ECA was measured via indirect calorimetry. Resting energy expenditure (REE), nutritional status, pulmonary function and genotype were determined. RESULTS: The REE in patients was significantly greater than the REE measured in controls (P=0.03) and was not related to the severity of lung disease or genotype. There was a significant difference between groups when comparing the ECA for walking kg radical FFM (P=0.001) and cycling kg radical FFM (P=0.04). The ECA for each activity was adjusted (ECA(adj)) for the contribution of REE (ECA kJ kg radical FFM 120 min(-1)--REE kJ kg radical FFM 120 min(-1)). ECA(adj) revealed a significant difference between groups for the walking protocol (P=0.001) but no difference for the cycling protocol (P=0.45). This finding may be related to the fact that the work rate during walking was more highly regulated than during cycling. CONCLUSIONS: ECA in CF is increased and is likely to be explained by an additional energy-requiring component related to the exercise itself and not an increased REE.     

Prediction of daily energy expenditure during a feeding trial using measurements of resting energy expenditure, fat-free mass, or Harris-Benedict equations

BACKGROUND: During feeding trials, it is useful to predict daily energy expenditure (DEE) to estimate energy requirements and to assess subject compliance. OBJECTIVE: We examined predictors of DEE during a feeding trial conducted in a clinical research center. DESIGN: During a 28-d period, all food consumed by 26 healthy, nonobese, young adults was provided by the investigators. Energy intake was adjusted to maintain constant body weight. Before and after this period, fat-free mass (FFM) and fat mass were assessed by using dual-energy X-ray absorptiometry, and DEE was estimated from the change (after - before) in body energy (DeltaBE) and in observed energy intake (EI): DEE = EI - DeltaBE. We examined the relation of DEE to pretrial resting energy expenditure (REE), FFM, REE derived from the average of REE and calculated from FFM [REE = (21.2 x FFM) + 415], and an estimate of DEE based on the Harris-Benedict equation (HB estimate) (DEE = 1.6 REE). RESULTS: DEE correlated (P < 0.001) with FFM (r = 0.78), REE (r = 0.73), average REE (r = 0.82), and the HB estimate (r = 0.81). In a multiple regression model containing all these variables, R(2) was 0.70. The mean (+/-SEM) ratios of DEE to REE, to average REE, and to the HB estimate were 1.86 +/- 0.06, 1.79 +/- 0.04, and 1.02 +/- 0.02, respectively. CONCLUSIONS: Although a slightly improved prediction of DEE is possible with multiple measurements, each of these measurements suggests that DEE equals 1.60-1.86 x REE. The findings are similar to those of previous studies that describe the relation of REE to DEE measured directly.     

Resting energy expenditure is increased in stable, malnourished HIV-infected patients

Resting energy expenditure (REE) was measured by reference to body composition in 50 malnourished patients with human immunodeficiency virus (HIV) infection and compared with that of 14 healthy subjects. Among HIV patients, 40 had acquired immune deficiency syndrome (AIDS) and 10 had AIDS-related complex (ARC). All were in stable condition and had a previous history of progressive wasting, ie, a mean body weight loss of 14.2 +/- 8.1 kg over 16.6 mo (range 2-49 ms). The mean REE was 14% higher than estimated basal energy expenditure (EBEE), according to the Harris and Benedict formula. Thirty-four patients (68%) were classified as hypermetabolic (REE greater than 110% EBEE). The best predictable variable for REE was fat-free mass (FFM), as determined by an anthropometric method (r = 0.72; P less than 0.001). The mean REE was 12% higher in HIV patients than in the control group FFM (156 +/- 19 vs 124 +/- 17 kJ.kg FFM-1.d-1). We concluded that in stable and malnourished HIV patients, the progressive wasting may be partly related to an increase in REE. The mechanism of this hypermetabolic state remains to be established.     

The age-related decline in resting energy expenditure in humans is due to the loss of fat-free mass and to alterations in its metabolically active components

There is conflicting evidence as to whether the age-related decline in resting energy expenditure (REE) can be attributed to i) absolute changes in fat-free mass (FFM), ii) alterations in the composition of FFM or iii) decreasing organ metabolic rates. This study directly addressed the first and second hypotheses by quantification of metabolically active components of FFM assuming constant tissue respiration rates to calculate REE (REEc). REE was measured (REEm) in 26 young (13 females, 13 males, age 22-31 y) and 26 elderly subjects (15 females, 11 males, age 60-82 y) by indirect calorimetry and detailed body composition analysis was obtained using bioelectrical impedance analysis (BIA), dual energy X-ray absorptiometry (DXA), and MRI. Specific organ metabolic rates were taken from the literature. REEm adjusted for differences in FFM was lower in older subjects than in younger control subjects (5.43 +/- 0.61 MJ/d compared with 6.37 +/- 0.48 MJ/d; P < 0.001). Skeletal muscle mass plus liver mass accounted for 86% and 48% of the variance in REE in young and elderly subjects, respectively. The difference between REEm and REEc was 0.03 +/- 0.40 MJ/d and -0.36 +/- 0.70 MJ/d in young and elderly subjects, respectively. In the elderly 58% of the difference in variance was attributed to heart mass. REEm - REEc was -1.40 +/- 0.44 MJ/d in subjects with hypertensive cardiac hypertrophy, i.e., heart mass > 500 g, suggesting a decrease in heart metabolic rate with increasing heart mass. Excluding five elderly subjects with cardiac hypertrophy resulted in agreement between REEm and REEc in the elderly (-0.10 +/- 0.48 MJ/d). We concluded that the age-related decline in REE is attributed to a reduction in FFM as well as in proportional changes in its metabolically active components. There is no evidence for a decreasing organ metabolic rate in healthy aging.     

The impact of parenteral nutrition on the body composition of patients with acute pancreatitis

BACKGROUND: Nutrition support by the enteral route is now the preferred modality in patients with severe acute pancreatitis. Parenteral nutrition is now required to supplement enteral nutrition when the latter is not able to provide the full nutritional requirement. We report the changes in body composition, plasma proteins, and resting energy expenditure (REE) during 14 days of parenteral nutrition (PN) in patients with acute pancreatitis. METHODS: Total body protein (TBP), total body water (TBW), and total body fat (TBF) were measured by neutron activation analysis and tritium dilution before and after PN. Fat-free mass (FFM) was derived as the difference between body weight and TBF. REE was measured by indirect calorimetry. Protein index (PI) was the ratio of measured TBP to TBP, calculated from healthy volunteers. RESULTS: Fifteen patients with acute pancreatitis (11 men, 4 women; median age 56, range 30-80 years) were studied. Thirteen patients had severe acute pancreatitis (Atlanta criteria), and 1 patient died. The gains in body weight (1.05 +/- 0.77 kg), TBW (0.49 +/- 0.87 kg), TBP (0.20 +/- 0.22 kg), FFM (0.73 +/- 0.92 kg), TBF (0.32 +/- 0.95 kg), and REE (146 +/- 90 kcal/d) after 14 days of PN were not significant. Plasma prealbumin increased by 46.5% (p = .020). When patients (n = 6) with intercurrent sepsis and recent surgery were excluded, there were significant increases in TBP (0.65 +/- 0.17 kg, p = .005) and PI (0.060 +/- 0.011, p = .0006). CONCLUSIONS: Body composition is preserved in acute pancreatitis during 14 days of PN. In patients without sepsis or recent surgery, PN is able to significantly increase body protein stores.     

Controlled trial of the metabolic effects of a very-low-calorie diet: short- and long-term effects

Resting energy expenditure (REE), weight, and body composition were measured up to seven times in 13 obese women during a 24-wk study. Patients were randomly assigned to a very-low-calorie diet (VLCD, 500 kcal/d) or a balanced-deficit diet (BDD, 1200 kcal/d). After 8 wk of supplemented fasting, REE of the VLCD patients decreased by 17% whereas that of the BDD patients was virtually unchanged. REE of the VLCD patients increased during 12 subsequent weeks of realimentation such that differences in REE between the two groups were not statistically significant at week 24 (VLCD = -11%, BDD = -2%). Reductions in weight and fat-free mass (FFM) were 12.1% and 3.6% for the VLCD patients and 10.6% and 4.1% for the BDD patients, respectively. There were no significant differences between the groups in pre- to posttreatment changes in REE normalized to FFM. Results suggest that REE recovers partially after consumption of a VLCD. They also provide evidence of a possible metabolic advantage of weight loss by a more moderate restriction.     

A new predictive equation for resting energy expenditure in healthy individuals

A predictive equation for resting energy expenditure (REE) was derived from data from 498 healthy subjects, including females (n = 247) and males (n = 251), aged 19-78 y (45 +/- 14 y, mean +/- SD). Normal-weight (n = 264) and obese (n = 234) individuals were studied and REE was measured by indirect calorimetry. Multiple-regression analyses were employed to drive relationships between REE and weight, height, and age for both men and women (R2 = 0.71): REE = 9.99 x weight + 6.25 x height - 4.92 x age + 166 x sex (males, 1; females, 0) - 161. Simplification of this formula and separation by sex did not affect its predictive value: REE (males) = 10 x weight (kg) + 6.25 x height (cm) - 5 x age (y) + 5; REE (females) = 10 x weight (kg) + 6.25 x height (cm) - 5 x age (y) - 161. The inclusion of relative body weight and body-weight distribution did not significantly improve the predictive value of these equations. The Harris-Benedict Equations derived in 1919 overestimated measured REE by 5% (p less than 0.01). Fat-free mass (FFM) was the best single predictor of REE (R2 = 0.64): REE = 19.7 x FFM + 413. Weight also was closely correlated with REE (R2 = 0.56): REE = 15.1 x weight + 371.