Assessment of body composition by bioelectrical impedance in a population aged greater than 60 y

Body composition was measured in a group of 35 healthy men and 37 healthy women aged 60-83 y. Body mass index (BMI) in men was 25.0 +/- 2.2 kg/m2 (means +/- SD) and in women, 25.9 +/- 3.2 kg/m2. BMI was low in relation to body fat percentage as determined by skinfold-thickness measurements or densitometry in comparison with the relation found in younger adults. Mean body fat percentage of the male subjects (aged 70.4 +/- 5.2 y) as determined by densitometry was 31.0 +/- 4.5%, whereas in women (aged 68.0 +/- 5.2 y) it was 43.9 +/- 4.3%. Body impedance correlated with fat-free mass (FFM). The best prediction formulas for the FFM from body impedance and anthropometric variables were 1) FFM (kg) = (0.671 x 10(4) x H2/R) + 3.1S + 3.9 where H is body height (m), R is resistance (omega), and S is gender (females, 0; males, 1) (r = 0.94; SEE = 3.1 kg) and 2) FFM (kg) = (0.360 x 10(4) x H2/R) + 0.359BW + 4.5S - 20T + 7.0 where BW is body weight (kg) and T is thigh circumference (m) (r = 0.96; SEE = 2.5 kg). The prediction equations from the literature, generally determined in younger populations, overestimated FFM in elderly subjects by approximately 6 kg and are not applicable to elderly subjects.     

Estimation of body fatness from body mass index and bioelectrical impedance: comparison of New Zealand European, Maori and Pacific Island children

OBJECTIVE: To compare percentage body fat (%BF) for a given body mass index (BMI) among New Zealand European, Maori and Pacific Island children. To develop prediction equations based on bioimpedance measurements for the estimation of fat-free mass (FFM) appropriate to children in these three ethnic groups. DESIGN: Cross-sectional study. Purposive sampling of schoolchildren aimed at recruiting three children of each sex and ethnicity for each year of age. Double cross-validation of FFM prediction equations developed by multiple regression. SETTING: Local schools in Auckland. SUBJECTS: Healthy European, Maori and Pacific Island children (n=172, 83 M, 89 F, mean age 9.4+/-2.8(s.d.), range 5-14 y). MEASUREMENTS: Height, weight, age, sex and ethnicity were recorded. FFM was derived from measurements of total body water by deuterium dilution and resistance and reactance were measured by bioimpedance analysis. RESULTS: For fixed BMI, the Maori and Pacific Island girls averaged 3.7% lower %BF than European girls. For boys a similar relation was not found since BMI did not significantly influence %BF of European boys (P=0.18). Based on bioimpedance measurements a single prediction equation was developed for all children: FFM (kg)=0.622 height (cm)(2)/resistance+0.234 weight (kg)+1.166, R(2)=0.96, s.e.e.=2.44 kg. Ethnicity, age and sex were not significant predictors. CONCLUSIONS: A robust equation for estimation of FFM in New Zealand European, Maori and Pacific Island children in the 5-14 y age range that is more suitable than BMI for the determination of body fatness in field studies has been developed.     

Single prediction equation for bioelectrical impedance analysis in adults aged 20--94 years

Existing equations for bioelectrical impedance analysis (BIA) are of limited use when subjects age or become overweight because these equations were developed in young, normal-weight subjects and are not valid in elderly or overweight people. The purpose of this study was to validate a single BIA equation in healthy white subjects aged 22--94 y with a body mass index between 17.0 and 33.8 kg/m(2). Healthy subjects (202 men and 141 women) aged 20--94 y were measured by two methods: fat-free mass (FFM) was measured by dual-energy x-ray absorptiometry (Hologic QDR-4500) and by a bioelectrical impedance analyzer (Xitron 4000B). Validity of BIA was assessed by double cross validation. Because correlations were high (r = 0.986--0.987) and prediction errors low, a single equation was developed using all subjects, as follows: FFM = -4.104 + (0.518 x height(2)/resistance) + (0.231 x weight) + (0.130 x reactance) + (4.229 x sex: men = 1, women = 0). FFM predicted with dual-energy x-ray absorptiometry was 54.0 +/- 10.7 kg. BIA-predicted FFM was 54.0 +/- 10.5 kg (r = 0.986, standard error of the estimate = 1.72 kg, technical error = 1.74 kg). In conclusion, the new Geneva BIA equation was valid for prediction of FFM in healthy adults aged 22--94 y with body mass indexes between 17.0 and 33.8 kg/m(2). Inclusion of reactance in the single prediction equation appeared to be essential for use of BIA equations in populations with large variations in age or body mass.     

Prediction equations for resting energy expenditure in overweight and normal-weight black and white children

BACKGROUND: Accurate estimation of children's resting energy expenditure (REE) is important for planning dietary therapy. OBJECTIVE: Our objective was to compare the utility of 5 REE prediction equations in a diverse sample of young children. DESIGN: REE was obtained in 502 black and white girls and boys aged 6-11 y by using indirect calorimetry at 4 US sites. Measured REE and REE predicted from the equations were compared. RESULTS: None of the equations provided both accurate and unbiased estimates of REE. Two new sets of sex-specific equations including race as a factor were generated and evaluated. One set used easily measured variables-females: REE = 0.046 x weight - 4.492 x 1/height(2) - 0.151 x race + 5.841; males: REE = 0.037 x weight - 4.67 x 1/height(2) - 0.159 x race + 6.792-and accounted for 72% and 69%, respectively, of REE variance. The other set used body-composition variables-females: REE = 0.101 x fat-free mass + 0.025 x fat mass + 0.293 x height(3) - 0.185 x race + 1.643; males: REE = 0.078 x fat-free mass + 0.026 x fat mass - 2.646 x 1/height(2) - 0.244 x race + 4.8-and accounted for 75% and 71%, respectively, of REE variance. When split by race and adiposity, the small bias generated could be corrected to within 0.25 MJ (60 kcal) of the mean measured value. CONCLUSION: Sex-specific equations must take race into account to predict REE adequately in children.     

Growth velocity, fat-free mass and energy intake are inversely related to viral load in HIV-infected children

The study objectives were to assess the relationships among human immunodeficiency virus (HIV) replication, energy balance, body composition and growth in children with HIV-associated growth failure (GF). Energy intake and expenditure, body composition and level of HIV RNA were measured in 16 HIV-infected children with growth failure (HIV+/GF+), defined as a 12-mo height velocity 相似文献   

Time trends in cancer mortality in central Serbia

Summary. Objective To examine cancer mortality trends in Central Serbia (1985–2002). Methods Cancer mortality rates were based on the official death certificates (n = 192849). They were standardized for age and sex. Results In the observed period, mortality rates showed a tendency to increase in both males (y = 118.54 + 2.27x, p = 0.0001) and females (y = 83.32 + 1.02x, p = 0.0001). Mortality of lung cancer increased in both sexes (y = 32.38 + 0.86x, p < 0.001 for males, y = 6.25 + 0.25y, p < 0.001 for females), as did colorectal cancer (y = 10.87 + 033x, p < 0.001 for males, y = 8.51 + 0.09x, p < 0.05 for females). Breast cancer mortality rates increased (y = 14.48 + 0.35x, p = 0.0001), and so did cervical cancer (y = 5.14 + 0.14x, p < 0.01). Mortality of gastric cancer in males has been moderately decreasing after 1990s (y_(1990-2002) = 13.67–0.20x, p < 0.01), while prostate cancer mortality remained relatively stable. Conclusions Increasing cancer mortality trends in the last 18 years in Central Serbia indicate the extremely urgent needs for health authorities to adopt measures of cancer prevention that proved effective in other countries. Submitted: 30 March, 2005 Accepted: 28 November, 2005     

Estimating geriatric patient's body weight using the knee height caliper and mid-arm circumference in Hong Kong Chinese

The use of the knee height caliper is a convenient way to estimate a patient's body weight. However, the equation devised to estimate an individual's body weight was specifically designed for Caucasians and Blacks. Therefore, this study is to assess the suitability of the knee height caliper among Chinese geriatric patients residing in Hong Kong. Over a six-month period, all geriatric patients from an acute care hospital and private nursing home in the Kwun Tong were recruited into the study. Only patients/residents that were considered unstable with ascites; low blood pressure; on cardiac monitors or had respiratory difficulties were excluded. Measurements from the knee height caliper and mid-arm muscle circumference of the patients were necessary for estimating their body weights. The actual body weights measured with calibrated bed, chair or portable scales was compared with the calculated body weights from the equation. A comparison of the mean and linear regression was performed for analysis of the results. A total of 300 geriatric patients (200 females and 100 males) were recruited. The mean MAC and knee height results were as follows: 25.1 cm (SD 3.9) for females and 26.2 cm (SD 3.2) for males; and 45.75 cm (SD 2.09) for females and 48.98 cm (SD 2.09) for males respectively. The mean difference among the male group was 0.4222 (95% CI: -0.54, 1.39) with a mean estimated body weight of 58.1 kg (SD 10.1) and a mean actual body weight of 57.7 kg (SD 9.9). The mean difference among the female group was 2.9649 (95% CI: 2.30, 3.63) with a mean estimated body weight of 51.6 kg (SD 10.9) and a mean actual body weight of 48.6 kg (SD 10.1). A new equation devised from the data is as follows: Chinese males (over 60 years of age) (R-square -0.81) Weight = [knee height (cm) x 0.928 + mid-arm circumference (cm) x 2.508 - age (years) x 0.144] - 42.543 +/-9.9kg of actual weight for 95% of Chinese males; Chinese females (over 60 years of age) (R-square - 0.82) Weight (kg) = [knee height (cm) x 0.826 + mid-arm circumference (cm) x 2.116 - age (years) x 0.133] - 31.486 +/-10.1kg of actual weight for 95% of Chinese females. The results showed that the mean estimated body weight calculated from the knee height equation (for Caucasians) was significantly larger than the mean actual body weight for the Chinese subjects. This study suggests that the knee height caliper is a useful tool for estimating the body weights. However, a multi-center study is necessary to validate the new equation for the elderly Chinese population.     

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.     

A longitudinal comparison of body composition by total body water and bioelectrical impedance in adolescent girls

Previous studies have assessed the ability of bioelectrical impedance analysis (BIA) to estimate body composition cross-sectionally, but less is known about the ability of BIA to detect changes in body composition longitudinally over the adolescent growth period. Body composition was assessed by isotopic dilution of H(2)(18)O and BIA in 196 initially nonobese girls enrolled in a longitudinal study. Two prediction equations for use in our population of girls were developed, one for use premenarcheally and one for use postmenarcheally. We compared estimates from our equation with those derived from several published equations. Using longitudinal data analysis techniques, we estimated changes in fat-free mass (FFM) and percentage body fat (%BF) over time from BIA, compared with changes in FFM and % BF estimated by H(2)(18)O. A total of 422 measurements from 196 girls were available for analysis. Of the participants, 26% had one measurement of body composition, 43% had two measurements of body composition and 31% had three or more measurements of body composition. By either H(2)(18)O or BIA, the mean %BF at study entry was 23% (n = 196) and the mean %BF at 4 y postmenarche was 27% (n = 133). In our cohort, the best predictive equations to estimate FFM by BIA were: PREMENARCHE: FFM = -5.508 + (0.420 x height(2)/resistance) + (0.209 x weight) + (0.08593 x height) + (0.515 x black race) - (0.02273 x other race). POSTMENARCHE: FFM = -11.937 + (0.389 x height(2)/resistance) + (0.285 x weight) + (0.124 x height) + (0.543 x black race) + (0.393 x other race). Overall, we found that BIA provided accurate estimates of the change in both FFM and %BF over time.     

Body movement and physical activity energy expenditure in children and adolescents: how to adjust for differences in body size and age

BACKGROUND: Physical activity data in children and adolescents who differ in body size and age are influenced by whether physical activity is expressed in terms of body movement or energy expenditure. OBJECTIVE: We examined whether physical activity expressed as body movement (ie, accelerometer counts) differs from physical activity energy expenditure (PAEE) as a function of body size and age. DESIGN: This was a cross-sectional study in children [n = 26; (+/-SD) age: 9.6 +/- 0.3 y] and adolescents (n = 25; age: 17.6 +/- 1.5 y) in which body movement and total energy expenditure (TEE) were simultaneously measured with the use of accelerometry and the doubly labeled water method, respectively. PAEE was expressed as 1) unadjusted PAEE [TEE minus resting energy expenditure (REE); in MJ/d], 2) PAEE adjusted for body weight (BW) (PAEE. kg(-1). d(-1)), 3) PAEE adjusted for fat-free mass (FFM) (PAEE. kg FFM(-1). d(-1)), and 4) the physical activity level (PAL = TEE/REE). RESULTS: Body movement was significantly higher (P = 0.03) in children than in adolescents. Similarly, when PAEE was normalized for differences in BW or FFM, it was significantly higher in children than in adolescents (P = 0.03). In contrast, unadjusted PAEE and PAL were significantly higher in adolescents (P < 0.01). CONCLUSIONS: PAEE should be normalized for BW or FFM for comparison of physical activity between children and adolescents who differ in body size and age. Adjusting PAEE for FFM removes the confounding effect of sex, and therefore FFM may be the most appropriate body-composition variable for normalization of PAEE. Unadjusted PAEE and PAL depend on body size.     

Small organs with a high metabolic rate explain lower resting energy expenditure in African American than in white adults

BACKGROUND: African Americans have a lower resting energy expenditure (REE) relative to fat-free mass (FFM) than do whites. Whether the composition of FFM at the organ-tissue level differs between African Americans and whites and, if so, whether that difference could account for differences by race in REE are unknown. OBJECTIVE: The objectives were to quantify FFM in vivo in women and men at the organ-tissue level and to ascertain whether the mass of specific high-metabolic-rate organs and tissues differs between African Americans and whites and, if so, whether that difference can account for differences in REE. DESIGN: The study was a cross-sectional evaluation of 64 women (n = 34 African Americans, 30 whites) and 35 men (n = 8 African Americans, 27 whites). Magnetic resonance imaging measures of liver, kidney, heart, spleen, brain, skeletal muscle, and adipose tissue and dual-energy X-ray absorptiometry measures of fat and FFM were acquired. REE was measured by using indirect calorimetry. RESULTS: The mass of selected high-metabolic-rate organs (sum of liver, heart, spleen, kidneys, and brain) after adjustment for fat, FFM, sex, and age was significantly (P < 0.001) smaller in African Americans than in whites (3.1 and 3.4 kg, respectively; x +/- SEE difference: 0.30 +/- 0.06 kg). In a multiple regression analysis with fat, FFM, sex, age, and race as predictors of REE, the addition of the total mass rendered race nonsignificant. CONCLUSIONS: Racial differences in REE were reduced by >50% and were no longer significant when the mass of specific high-metabolic-rate organs was considered. Differences in FFM composition may be responsible for the reported REE differences.     

Sex differences in resting energy expenditure and their relation to insulin resistance in children (EarlyBird 13)

BACKGROUND: Insulin resistance is believed to be the process underlying type 2 diabetes and premature cardiovascular disease. We have established that a relation between body mass and insulin resistance calculated by homeostasis model assessment (HOMA-IR) exists by 5 y of age in contemporary UK children. Resting energy expenditure (REE) is variable among individuals and is one of many factors controlling body mass. OBJECTIVE: The objective was to investigate the relations between REE, body mass, and HOMA-IR in young children. DESIGN: EarlyBird is a nonintervention prospective cohort study of 307 healthy 5-y-olds that asks the question: Which children develop insulin resistance and why? REE by indirect calorimetry and HOMA-IR were measured in addition to total body mass, fat-free mass (FFM) by bioimpedance, body mass index (BMI; in kg/m(2)), and skinfold thickness when the mean age of the cohort was 5.9 +/- 0.2 y. RESULTS: Whereas the BMI of the boys was lower than that of the girls (x +/- SD: boys, 15.9 +/- 1.9; girls, 16.5 +/- 1.9; P = 0.03), their REE was higher by 6% (x +/- SD: 4724 +/- 615 compared with 4469 +/- 531 kJ/d; P = 0.002). This difference persisted after adjustment for FFM and other anthropometric variables (P = 0.04). In boys, there was a weak, although significant, inverse correlation between REE and HOMA-IR, independent of fat mass and FFM (boys: r = -0.21, P = 0.03; girls: r = 0.12, P = 0.34). CONCLUSION: There is a sex difference in REE at 6 y of age that cannot be explained by body composition. The difference appears to be intrinsic, and its contribution to sex differences in adiposity and HOMA-IR in children merits further exploration.     

Height reduction, determined using knee height measurement as a risk factor or predictive sign for osteoporosis in elderly women

OBJECTIVE: We assessed the value of height reduction, calculated using knee height measurement, as a risk factor or predictive sign for osteoporosis in healthy elderly women. METHODS: In 181 healthy women 76 +/- 5 y of age, height, weight, and knee height were evaluated. Femoral and spine bone mineral densities and body compositions were measured using dual-energy X-ray absorptiometry. In 76 young women 27 +/- 4 y of age, a regression equation to predict height, based on knee height, was derived. Using this equation, maximum attained height and height loss were calculated in elderly women, which was correlated to bone mineral density. RESULTS: The equation to predict height was height (cm) = knee height (cm) x 2.22 + 50.54. The calculated height loss in elderly women was -6.1 +/- 3.8 cm or -0.08 +/- 0.05 cm/y of age. Height loss and hip circumference were significant predictors of spine bone mineral density. In the case of femoral bone mineral density, to the same predictors, a negative effect of waist circumference was added. Women in the highest quintile of height reduction (>0.199 cm/y) had an odds ratio of 4.5 (95% confidence interval 1.56-13.3, P < 0.02) for femoral osteoporosis. CONCLUSION: Knee height can be used as an accurate measurement of height loss in the elderly, which is a significant predictor of femur and spine bone mineral densities, in addition to hip circumference.     

Equation to estimate resting energy expenditure in adolescents with sickle cell anemia

BACKGROUND: Basal energy requirements are higher in adolescents with sickle cell anemia (SCA) than in healthy control subjects. However, no equation is available to accurately predict their energy needs. OBJECTIVE: Our objective was to develop a clinically useful equation to estimate resting energy expenditure (REE) in adolescents with SCA. DESIGN: REE and other components of total energy expenditure were measured in adolescents with SCA (n = 37) and in control subjects (n = 23) for 24 h in a whole-room indirect calorimeter. Multiple linear regression analysis was used to describe the relations of REE with independent variables such as sex, weight, height, fat-free mass, fat mass, age, and hemoglobin concentration in adolescents with SCA. The Bland-Altman comparison technique was used to compare values predicted by existing equations with measured REE values. RESULTS: Mean (+/-SD) measured REEs were 7746 +/- 974 and 6332 +/- 869 kJ/d in the male and female subjects with SCA, respectively, and these values were 16% higher than those in the healthy control subjects. Standard equations underestimated REE by 12% (P 相似文献   

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.     

Development of bioelectrical impedance analysis prediction equations for body composition with the use of a multicomponent model for use in epidemiologic surveys

BACKGROUND: Previous studies to develop and validate bioelectrical impedance analysis (BIA) equations to predict body composition were limited by small sample sizes, sex specificity, and reliance on reference methods that use a 2-component model. OBJECTIVE: This study was designed to develop sex-specific BIA equations to predict total body water (TBW) and fat-free mass (FFM) with the use of a multicomponent model for children and adults. DESIGN: Data from 5 centers were pooled to create a sample of 1474 whites and 355 blacks aged 12-94 y. TBW was measured by dilution, and FFM was estimated with a multicomponent model based on densitometry, isotope dilution, and dual-energy X-ray absorptiometry. RESULTS: The final race-combined TBW prediction equations included stature(2)/resistance and body weight (R(2) = 0.84 and 0.79 and root mean square errors of 3.8 and 2.6 L for males and females, respectively; CV: 8%) and tended to underpredict TBW in black males (2.0 L) and females (1.4 L) and to overpredict TBW in white males (0.5 L) and females (0.3 L). The race-combined FFM prediction equations contained the same independent variables (R(2) = 0.90 and 0.83 and root mean square errors of 3.9 and 2.9 kg for males and females, respectively; CV: approximately 6%) and tended to underpredict FFM in black males (2.1 kg) and females (1.6 kg) and to overpredict FFM in white males (0.4 kg) and females (0.3 kg). CONCLUSION: These equations have excellent precision and are recommended for use in epidemiologic studies to describe normal levels of body composition.     

Twenty-four hour urinary creatinine: A simple technique for estimating resting energy expenditure in normal population and the hospitalised patients

This study was designed to determine the relationship between resting energy expenditure (REE) and 24h urinary creatinine excretion. A total of 61 normal males and females and hospital patients had their REE and 24 h urinary creatinine measured. A statistically significant correlation between measured REE (in kcal) and 24 h urinary creatinine (in mg) was noted, (y = 0.488 × + 964; r = 0.81, P 0.0001, SD of the residuals 156). If 24 h urinary creatinine is in mmol, then the equation would be 55 × + 964. Creatinine coefficients (creatinine excretion in mg/day/kg body weight) of 25 (.221 mmol) for males and 20 (.176 mmol) for females were found.These findings suggest that an equation based on 24 h urinary creatinine excretion will be a more accurate estimate of energy expenditure than conventional methods based on height, weight, age and sex and will be applicable to a normal population as well as hospitalised patients.     

An evaluation of resting energy expenditure in hospitalized, severely underweight patients.

A prospective trial was conducted with 14 hospitalized patients who were severely underweight with a mean weight of 40.9+/-5.1 kg and 70.7+/-7.8% of ideal body weight, to compare estimates of resting energy expenditure (REE) with measured values. The 9 women and 3 men, whose mean age was 66.5+/-13.9 y, underwent nutritional assessment and measurement of their REE by indirect calorimetry using the Sensormedics Deltatrac MBM100 indirect calorimeter. Their REE was also estimated by the Harris-Benedict formula (mean 1032+/-66 kcal/d) as well as a previously established empirical formula where REE = 25 x body weight in kg (mean 1023+/-129 kcal/d). Results by both estimates were significantly lower than the measured resting energy expenditure (MREE) in this group of patients (P<0.0001). The percentage difference between MREE and estimated REE by the Harris-Benedict formula was 18.4+/-9.4% and 20.9+/-7.5% by the empirical formula. The MREE exceeded the estimated REE in each individual. The correlation between MREE and body weight (r2 = 0.558, r = 0.005) was better than that between MREE and estimated REE by Harris-Benedict formula (r2 = 0.275, P = 0.08) suggesting that weight was the principal determinant rather than the other components (height, age, sex) of the Harris-Benedict formula. Our data shows that commonly employed formulae routinely underestimate the energy needs of severely underweight patients below 50 kg in body weight. The Harris-Benedict equation had limited predictive value for the individual, explaining approximately 25% of the variance in energy expenditure. Given the particular importance of matching energy intake to needs in this group of patients with limited reserves, many of whom are critically ill, we suggest an empirical equation using 30-32 kcal/kg be used to estimate the energy requirements of severely underweight patients when direct measurements are unavailable or clinically less imperative.     

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.     

Resting energy expenditure can be assessed by fat-free mass in female athletes regardless of body size

Energy requirements can be estimated from resting energy expenditure (REE). However, little is known about factors influencing REE in Japanese female athletes. This study was performed to evaluate the relationship between REE and body composition in Japanese female athletes with a wide range of body sizes. Ninety-three athletes (age 20.3±1.2 y, height 162.8±6.4 cm, body weight (BW) 57.0±9.2 kg, fat-free mass (FFM) 45.4±6.2 kg) were classified into three groups according to BW: small-size (S) (n=34), medium-size (M) (n=34), and large-size (L) (n=25). Systemic and regional body compositions (skeletal muscle (SM), fat mass (FM), bone mass (BM), and residual mass (RM)) were estimated by dual energy X-ray absorptiometry (DXA). Measured resting energy expenditure (REEm) was evaluated by indirect calorimetry. Marked differences were found in REEm (S: 1,111±150, M: 1,242±133, L: 1,478±138 kcal/d), and systemic and regional body compositions among the three groups. REEm was strongly correlated with FFM, and absolute values of RM and SM increased significantly according to body size. There was good agreement between REEm and estimated REE (REEe) from the specific metabolic rates of four major organ tissue level compartments. These data indicate that REE for female athletes can be attributed to changes in organ tissue mass, and not changes in organ tissue metabolic rate. That is, change in REE can be explained mainly by the change in FFM, and REE can be assessed by FFM in female athletes regardless of body size.