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.     

健康老年人静息能量消耗

目的 :　探讨老年人 REE与性别、年龄 ,人体测量学指标的相关性。方法 :　用间接能量测定仪测试 82名 (男 3 0、女 5 2 )平均年龄 80岁的中国健康汉族老年人的静息能量消耗 (rest-ing energy expenditure,REE)的水平 ,并将 REE测试值与根据 Harris- Benedict公式算出的基础能量消耗值 (basal energy expenditure,BEE)进行比较。同时应用生物电阻抗分析法 (bioelectricalimpedance analysis,BIA)测定去脂体重 (fatfree mass,FFM)和体脂重量 (fat mass,FM)等人体测量学数据。结果 :　 82名健康老人的 REE平均值为 (4.44± 0 .5 2 ) MJ/2 4 h,与公式计算的 BEE比无统计学差异 ,但比 FAO/WHO/UNU(1 985 )公式值低 9% ,比 Owen公式值低 1 9%。本研究观察到我国健康老年人的 REE与去脂体重、体重、体表面积 (body surface area,BSA)、年龄、身高、性别和体重指数 (body mass index,BMI)之间有相关性。老年男女的每公斤体重、每公斤去脂体重和单位体表面积所产生的 REE间无统计学差异。结论 :　 Harris- Benedict公式、FAO/WHO/UNU(1 985 )公式与 Owen公式都过高估计了我国健康老年人的基础能量消耗。由于老年人的REE存在较大的个体差异 ,其 REE值宜实测而不宜用公式预测。我国健康老年人的 REE与去脂体重、体?     

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 in frail elderly people: a review of the literature

This review collates studies of healthy, sick, underweight (BMI < or = 21 kg/m2) and very elderly people (> or = 90 yr), in whom resting energy expenditure (REE) was measured using indirect calorimetry. We have observed the following: (1) REE, when adjusted for differences in both body weight and fat-free mass (FFM), is similar in healthy and in sick elderly people being 20 and 28 kcal/kg of FFM per day, respectively, (2) their nutritional status influences their energy requirements given that weight-adjusted REE increases in line with a decrease in BMI, (3) total energy expenditure is lower in sick elderly people given that their physical activity level, i.e. the ratio of total energy expenditure to REE, is reduced during disease averaging at 1.36, (4) energy intake (EI) being only 1.23 x REE is insufficient to cover energy requirements in sick elderly patients, whereas the EI of healthy elderly people appears sufficient to cover requirements, and finally, (5) gender ceases to be a determinant of REE in people aged 60 yr or over, with the Harris & Benedict equation capable of accurately predicting mean REE in this population, whether healthy or sick.     

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.     

Reliable bioelectrical impedance analysis estimate of fat-free mass in liver, lung, and heart transplant patients

BACKGROUND: Bioelectrical impedance analysis (BIA) can be valuable in evaluating the fat-free (FFM) and fat masses (FM) in patients, provided that the BIA equation is valid in the subjects studied. The purpose of the clinical evaluation was to evaluate the applicability of a single BIA equation to predict FFM in pre- and posttransplant patients and to compare FFM and FM in transplant patients with healthy controls. METHODS: Pre- and posttransplant liver, lung, and heart patients (159 men, 86 women) were measured by two methods-50-kHz BIA-derived FFM (FFM(BIA)) by Xitron instrument and DXA-derived FFM (FFM(DXA)) by Hologic QDR-4500 instrument-and compared with healthy controls (196 men, 129 women), aged 20 to 79 years. RESULTS: The high correlation coefficient (r = .974), small bias (0.3 +/- 2.3 kg), and small SEE (2.3 kg) suggest that BIA using the GENEVA equation is able to predict FFM in pre- and posttransplant patients. The study shows that the lower weight seen in transplant men and women than in controls was due to lower FFM, which was partially offset by higher FM in men but not in women. Furthermore, the higher weights in posttransplant than in pretransplant patients were due to higher FM and % FM that was confirmed by lower FFM/FM ratio in posttransplant patients. CONCLUSIONS: Single 50-kHz frequency BIA permits measurement of FFM in pre- and posttransplant patients.     

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.     

Sleeping metabolic rate in relation to body composition and the menstrual cycle.

The relationship between sleeping metabolic rate (SMR) measured from 0300 to 0600 h in a respiration chamber and body composition was studied in 47 healthy adult subjects (23 men and 24 women). The effect of the menstrual cycle on SMR was examined in 16 of the 24 women. SMR increased in the postovulation phase of the menstrual cycle (estimated as days 18-29 after last menstruation) 7.7% on average (P less than 0.001). A stepwise regression showed that both fat-free mass (FFM), fat mass (FM), and the phase of the menstrual cycle contributed significantly to SMR. After adjustment for FFM and FM, no sex differences in SMR (men vs preovulation women) remained. The inclusion of FM in this model is an improvement that eliminates the sex difference in SMR/FFM that is usually found. A prediction equation is given that explains 85% of the variance in SMR among individuals.     

Resting Energy Expenditure and the Effects of Muscle Wasting in Patients With Chronic Heart Failure: Results From the Studies Investigating Comorbidities Aggravating Heart Failure (SICA-HF)

Objectives

Muscle wasting is common in patients with chronic heart failure (HF) and worsens functional status. Protein catabolism is characteristic of muscle wasting and contributes to resting energy expenditure (REE). Glucagonlike peptide 1 (GLP-1) is linked to REE in healthy individuals. We aimed to evaluate (1) whether REE is elevated in patients with HF with muscle wasting, and (2) whether basal GLP-1 levels are linked to REE in HF.

Design

Cross-sectional study.

Setting

Ambulatory patients with HF were recruited at the Charité Medical School, Campus Virchow-Klinikum, Berlin, Germany.

Participants

A total of 166 patients with HF and 27 healthy controls participating in the Studies Investigating Co-morbidities Aggravating Heart Failure (SICA-HF) were enrolled. GLP-1 was measured in 55 of these patients.

Measurements

Body composition was measured by dual-energy X-ray absorptiometry (DEXA). Muscle wasting was defined as appendicular lean mass of at least 2 SDs below values of a healthy young reference group. REE was measured by indirect calorimetry. GLP-1 was assessed by ELISA.

Results

Thirty-four of 166 patients (mean age 67.4 ± 10.2 years, 77.7% male, New York Heart Association class 2.3 ± 0.6) presented with muscle wasting. REE in controls and patients with muscle wasting was significantly lower than in patients without muscle wasting (1579 ± 289 and 1532 ± 265 vs 1748 ± 359 kcal/d, P = .018 and P = .001, respectively). REE normalized for fat-free mass (FFM) using the ratio method (REE/FFM) and analysis of covariance was not different (P = .23 and .71, respectively). GLP-1 did not significantly correlate with REE (P = .49), even not after controlling for FFM using multivariable regression (P = .15).

Conclusions

Differences in REE are attributable to lower FFM. GLP-1 does not relate to REE in patients with HF, possibly because of HF-related effects on REE.     

Cancer cachexia: measured and predicted resting energy expenditures for nutritional needs evaluation

OBJECTIVE: Cancer cachexia is associated with weight loss, poor nutritional status, and systemic inflammation. Accurate nutritional support for patients is calculated on resting energy expenditure (REE) measurement or prediction. The present study evaluated the agreement between measured and predicted REE (mREE and pREE, respectively) and the influence of acute phase response (APR) on REE. METHODS: Thirty-six patients with cancer were divided into weight-stable (WS; weight loss <2%) and weight-losing (WL; weight loss >5%) patients. Measured REE was measured by indirect calorimetry and adjusted for fat-free mass (FFM). The Bland-Altman approach was used to assess the agreement between mREE and pREE from the Harris-Benedict equations (HBE). Blood levels of C-reactive protein were assessed. RESULTS: There was no difference in mREE between groups (WS 1677 +/- 273, WL 1521 +/- 305) even when mREE was adjusted for FFM (WS 1609 +/- 53, WL 1589 +/- 53). In WL patients, FFM-adjusted REE correlated with blood C-reactive protein levels (r = 0.471, P = 0.048). HBEs tend to underestimate REE in both groups. CONCLUSION: WL and WS patients with cancer had similar REEs but were different in terms of APR. APR could contribute to weight loss through enhancing REE. In a clinical context, HBE was in poor agreement with mREE in both groups.     

Changes in body composition in men and women with advanced nonsmall cell lung cancer (NSCLC) undergoing chemotherapy

Background Men with nonsmall cell lung cancer (NSCLC) are more susceptible to weight loss than women. The composition and aetiology of these gender specific weight changes are not known. Methods Measurements of body mass, body composition and energy balance (resting energy expenditure and energy intake) were made in 15 men and six women before and after chemotherapy for NSCLC. Results Over the course of chemotherapy minimal weight change was observed in both men and women. Men increased body fat from 25.0 ± 5.5 to 27.9 ± 7.9% (P < 0.05) whereas fat free mass (FFM) tended to decrease (P = 0.063). There was no change in body fat or FFM in the women. In the men resting energy expenditure decreased over the course of chemotherapy from 113.2 ± 15.9 to 105.1 ± 10.1% of the value predicted from the Harris Benedict equation (P < 0.05). In the women resting energy expenditure (REE) did not alter. Conclusion Over the course of chemotherapy for NSCLC, men and women appear to have different patterns of change in body composition and in energy expenditure.     

Assessment of energy expenditure by indirect calorimetry in healthy subjects and patients with liver cirrhosis

The reliability of resting energy expenditure (REE) measurements by indirect calorimetry with a ventilated hood was investigated in 50 healthy controls and 10 patients with liver cirrhosis. In each subject basal energy expenditure (BEE) was determined once and REE three times (morning REE1, noon REE2, afternoon REE3). In controls and patients the first 5-minute BEE and first 5-minute REE (controls also second 5-minute REE) were higher than in the remainder of the 30-minute recording. Only the last 20 minutes of recordings were used to calculate BEE (1645 +/- 315, mean +/- SD, in kilocalories per day), REE1 (1880 +/- 365), REE2 (1782 +/- 384), and REE3 (1775 +/- 316) in controls, and in cirrhotics: BEE (1530 +/- 235), REE1 (1714 +/- 267), REE2 (1715 +/- 238), and REE3 (1779 +/- 275). REE was higher than BEE in controls and cirrhotics (p less than 0.05). The REE variation coefficient was 5 +/- 3% in controls and 5 +/- 2% in cirrhotics. No systematic difference between REE1, REE2, and REE3 was found. Energy expenditure predicted by the Harris-Benedict equation differed up to 21% from measured BEE in individual controls; group mean BEE, however, was correctly predicted. In cirrhotics differences between measured and predicted BEE up to 26% occurred, while measured BEE was higher than predicted BEE (p = 0.06). It is concluded that REE can be reliably assessed by indirect calorimetry with a ventilated hood system in controls and patients at any time of the day, when values obtained in the first 10 minutes are deleted.(ABSTRACT TRUNCATED AT 250 WORDS)     

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 in patients with solid tumors undergoing anticancer therapy

OBJECTIVE: Few studies have investigated the resting energy expenditure (REE) of, or determined the individual predictive accuracy of prediction equations in, cancer patients undergoing anticancer therapy. This study compared the measured REE of patients with cancer undergoing anticancer therapy with (1) healthy subjects and (2) REE estimated from commonly used prediction methods. METHODS: Resting energy expenditure was measured in 18 cancer patients and 17 healthy subjects by using indirect calorimetry under standard conditions and was estimated from seven prediction methods. Fat-free mass (FFM) was measured by bioelectrical impedance analysis. Data were analyzed with regression modeling to adjust REE for FFM. Agreement between measured and predicted REE values was analyzed using the Bland-Altman approach. RESULTS: There was no significant difference in FFM-adjusted REE between cancer patients and healthy subjects (mean difference 10%). Limits of agreement were wide for all prediction methods in estimating REE as much as 40% below and up to 30% above measured REE. CONCLUSIONS: REE in cancer patients undergoing anticancer therapies does not appear to be as high as commonly thought. None of the prediction equations examined were acceptable for predicting REE of individual cancer patients or healthy subjects.     

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.     

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.     

Energy balance in children and young adults receiving haemodialysis for chronic renal failure

This study was designed to determine the contribution of energy expenditure to the energy imbalance seen in uraemic children. Resting energy expenditure (REE) was measured using open-circuit indirect calorimetry in eight uraemic haemodialysed subjects aged 9.3-20.4 years and in 10 healthy children. Linear correlations between REE and both body weight and fat-free mass as measured by anthropometry were found in both controls and uraemic subjects (respectively: r = 0.76 and r = 0.88 for body weight and r = 0.73 and r = 0.90 for fat-free mass). Measured REE in uraemic patients was not different from the value predicted by using actual body weight and fat-free mass in the regression equation of REE on body weight and fat-free mass in controls (paired t test: p = 0.70 and p = 0.19 respectively). These data suggest that the energy imbalance seen in uraemic children is not due to increased energy expenditure and is therefore probably due to decreased food intake.     

Energy balance in children and young adultsreceiving haernodialysis for chronic renal failure

This study was designed to determine the contribution of energy expenditure tothe energy imbalance seen in uraemic children. Resting energy expenditure (REE) was measured using open-circuit indirect calorimetry in eight uraemic haemodialysed subjects aged 9.3–20.4 years and in 10 healthy children. Linear correlations between REE and both body weight and fat-free mass as measured by anthropometry were found in both controls and uraemic subjects (respectively: r = 0.76 and r = 0.88 for body weight and r = 0.73 and r = 0.90 for fat-free mass). Measured REE in uraemic patients was not different from the value predicted by using actual body weight and fat-free mass in the regression equation of REE on body weight and fat-free mass in controls (paired t test: p = 0.70 and p = 0.19 respectively). These data suggest that the energy imbalance seen in uraemic children is not due to increased energy expenditure and is therefore probably due to decreased food intake.     

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.     

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.