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© 2004 The American Society for Nutritional Sciences J. Nutr. 134:1412-1416, June 2004

Human Nutrition and Metabolism

Energy Expenditure Is Very High in Extremely Obese Women1

Sai Krupa Das*,2, Edward Saltzman*,{dagger}, Megan A. McCrory*, L. K. George Hsu{dagger}, Scott A. Shikora{dagger}, Gregory Dolnikowski*, Joseph J. Kehayias* and Susan B. Roberts*

* Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA 02111 and {dagger} Tufts-New England Medical Center Hospital, Boston, MA 02111

2To whom correspondence should be addressed. E-mail: sai.das{at}tufts.edu.


   ABSTRACT
TOP
 ABSTRACT
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED
 
To test the hypothesis that total energy expenditure (TEE) and resting energy expenditure (REE) are low in extremely obese individuals, factors that could contribute to maintenance of excess weight, a cross-sectional study was conducted in 30 weight stable, extremely obese women [BMI (mean ± SEM) 48.9 ± 1.7 kg/m2]. TEE was measured over 14 d using the doubly labeled water method, REE and the thermic effect of feeding (TEF) were measured using indirect calorimetry, and activity energy expenditure (AEE) was calculated as TEE – (REE + TEF). Body composition was determined using a 3-compartment model. Subjects were divided into tertiles of BMI (37.5–45.0; 45.1–52.0; and 52.1–77.0 kg/m2) for data analysis. TEE and REE increased with increasing BMI tertile: TEE, 12.80 ± 0.5, 14.67 ± 0.5, and 16.10 ± 0.9 MJ/d (P < 0.01); REE, 7.87 ± 0.2, 8.78 ± 0.3, and 9.94 ± 0.6 MJ/d (P < 0.001), and these values were 29–38% higher than published means of measured TEE in nonobese individuals. No significant differences were observed among BMI tertiles for AEE, TEF, or physical activity level (PAL = TEE/REE, overall mean 1.64 ± 0.16). The Harris-Benedict and WHO equations provided the closest estimates of REE (within 3%), whereas the obese-specific equations of Ireton-Jones overpredicted (40%) and Bernstein underpredicted (21%) REE. Extremely obese individuals have high absolute values for TEE and REE, indicating that excess energy intake contributes to the maintenance of excess weight. Standard equations developed for nonobese populations provided the most accurate estimates of REE for the obese individuals studied here. REE was not accurately predicted by equations developed in obese populations.

KEY WORDS: • extreme obesity • energy expenditure • fat-free mass • prediction equations

The prevalence of extreme obesity, as defined by BMI >= 40 kg/m2, is now 5% in U.S. adults (1), representing a 3-fold increase over the last 40 years. This previously rare condition is associated with profound adverse health consequences; however, very little is known about factors that promote and maintain extreme obesity. Studies using doubly labeled water indicated that individuals with higher than recommended body weight (BMI >= 25 kg/m2) have high absolute total energy expenditure (TEE)3 compared with individuals of lower BMI (2–4). This implies that a high energy intake is required to maintain the excess weight. However, most of those studies were conducted in overweight or marginally obese individuals, and there is very little information available on the extremely obese individuals who may be more likely to have metabolic abnormalities that could predispose to low energy requirements.

The aim of the present study was to test the hypothesis that the weight maintenance energy expenditure of extremely obese individuals is low relative to both published data for nonobese individuals (3) and TEE predicted by the equations of the U.S. Dietary Reference Intakes (DRIs) (5). In addition, the accuracy of equations for predicting resting energy expenditure (REE) was assessed using prediction equations developed for use with nonobese (5–7) individuals and equations developed for use in obese individuals (8,9).


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 LITERATURE CITED
 
    Subjects. The subjects were 30 women who were awaiting gastric bypass (GBP) surgery for weight reduction at the Tufts-New England Medical Center Hospital (Table 1). Individuals were ineligible for the study if they had diabetes, cancer, coronary heart disease, endocrine disorders, other acute or chronic diseases, or medication use known to influence energy expenditure. Measurements were conducted at the Clinical Study Unit (CSU) of the Tufts-New England Medical Center Hospital and at the Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University. The study was approved by the Human Investigation Review Committee of Tufts-New England Medical Center Hospital. All subjects gave written, informed consent before participating.


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  		TABLE 1 Subject characteristics by tertiles of BMI in 30 weight stable, extremely obese women1

 
    Study design. All subjects were monitored for weight stability for 1 mo before the study and only those who were weight stable (defined as body weight maintained within ± 2.3 kg of starting weight) were allowed to participate. Two subjects whose BMI was slightly below 40 kg/m2 and who were eligible for GBP surgery were included in the study population. The study was conducted over a 15-d period. Subjects were free-living except for 2 overnight inpatient stays for measurements of REE and the thermic effect of feeding (TEF), and an additional 36-h period for other testing. Subjects were admitted to the CSU the day before the start of the study. After an overnight fast, measurement of TEE by doubly labeled water was started and REE was determined followed by a 4-h TEF measurement. Body composition was also measured as described below. Subjects then returned home with instructions on how to collect daily urine samples for the measurement of TEE. They were readmitted on d 7–8 for additional body composition and other measurements and then returned home for the rest of the week and continued urine collections at home. Subjects returned to the CSU on the evening of d 14, and a second REE measurement was conducted on the morning of d 15. Other measures during the study period included collection of blood samples from fasting subjects and the administration of food frequency and physical activity questionnaires.

    Measurements. A 15-d doubly labeled water study was conducted to measure TEE. REE and TEF were measured using indirect calorimetry (Deltatrac portable metabolic cart, Sensor Medics). The Siri 3-compartment model was used to estimate the percentage of body fat and body composition, and standard anthropometric measures were also obtained. Biochemical measures such as thyroid function tests and leptin were determined in blood from fasting subjects. Insulin and glucose were also measured in fasting subjects, and the homeostasis model assessment for insulin sensitivity (HOMA) was calculated using these values (10,11). Self-reported leisure time activity during the previous 12-mo period was determined by a structured interview using the Minnesota Leisure Time Physical Activity (LTPA) questionnaire; occupational activity over the previous 12 mo was also assessed using the self-administered Tecumseh Occupational Activity Questionnaire. All of the above methods were detailed and referenced previously (12,13).

    Statistics. Statistical analyses were performed using SPSS 10.0.7 and SYSTAT 9.0.1 (SPPS) and SAS (version 8, SAS Institute). Values are expressed as means ± SEM unless otherwise specified. Given the wide BMI range (37.5–77 kg/m2) in our study subjects, BMI was divided into tertiles to examine trends across different BMI levels. Baseline characteristics were compared among tertiles using 1-way ANOVA, and energy expenditure variables were compared using both ANOVA and analysis of covariance (ANCOVA), adjusting for fat-free mass (FFM). Tukey’s Honestly Significant Difference (HSD) test for multiple comparisons was used to determine significance among groups. Linear multiple regression analysis was performed to determine the best predictors of energy expenditure and suitable models to predict TEE, REE, and activity energy expenditure (AEE).

To test the hypothesis that TEE was low, measured TEE was compared with published TEE data for nonobese individuals (3) and data for nonobese from our own laboratory (14) using a 1-sample t test. Using ANOVA and Tukey’s HSD test, measured TEE was also compared with TEE predicted using the equations of the U.S. DRIs (5). ANOVA with Dunnett’s post-hoc test was used to determine whether predicted REE using the WHO equations (6), the Harris-Benedict equation (7), and with 2 equations developed or recommended for use in the obese (8,9) were significantly different from measured REE. In addition, the sum of squared differences between measured and predicted REE was used to assess the accuracy of the predictions. For all tests, differences were considered significant at P < 0.05.


   RESULTS
TOP
 ABSTRACT
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 LITERATURE CITED
 
All subjects were weight stable during the 1-mo period preceding the study [{Delta} body weight (mean ± SD), 1.46 ± 0.35 kg of starting weight] and were weight stable during the study period ({Delta} body weight, 4.2 ± 26 g/d). Physical characteristics of the subjects except for body weight after fasting and BMI were similar among the tertiles of BMI in these extremely obese women (Table 1), and values of all biochemical variables were within normal range for all subjects. Glucose was significantly higher in fasting subjects in the highest BMI tertile compared with the middle tertile (P < 0.05), and leptin was elevated in fasting subjects in the middle BMI tertile (P < 0.05) compared with the lowest tertile.

Energy expenditure variables by tertile of BMI are shown unadjusted for body composition (Table 2) and therefore illustrate the effect of increasing BMI on energy expenditure. Both TEE and REE were significantly higher in the highest BMI tertile compared with the lowest BMI tertile. However, when energy expenditure variables such as TEE and REE were adjusted for FFM, there were no significant differences among tertiles. This indicated that the differences in energy expenditure between the highest and lowest tertiles were due to differences in FFM.


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  		TABLE 2 Summary of energy expenditure data by tertiles of BMI in 30 weight stable, extremely obese women1

 
TEE values for all BMI tertiles were significantly higher than the mean TEE (9.51–10.21 MJ/d; P < 0.001) in nonobese women from a published summary (3). Measured TEE was also significantly higher (14.3 MJ/d) than the mean U.S. DRIs estimates of dietary energy needs using the subjects’ actual weight in 1) equations developed in normal weight women (11.69 MJ/d; P < 0.001), 2) the combined equation for normal, overweight and obese women (12.42 MJ/d; P < 0.001), or 3) the equation for overweight and obese women (12.77 MJ/d; P < 0.001) (5).

No significant differences were observed among BMI tertiles for AEE, TEF, physical activity level (PAL), or food quotient (FQ). In addition, the respiratory quotient (RQ) in fasting subjects was significantly higher in the lowest BMI tertile compared with the highest BMI tertile, but postprandial RQ (averaged over the 4 h TEF) did not differ significantly among BMI tertiles. There were no significant differences among BMI tertiles for self-reported physical activity when expressed in min/d or MJ/d (data for the latter not shown) or for any of the activity categories (data also not shown). In addition, there was no significant relation between measured AEE and energy expenditure calculated from LTPA and occupational activities (r = 0.04; P = 0.8). PAL was also not predicted by LTPA, occupational, or total activity in the 3 activity categories i.e., light, moderate, or heavy activity (P = 0.14–0.76).

Regression analyses (Table 3) showed that TEE was best predicted by FFM (adjusted R2 = 0.56; P < 0.001). Although FFM alone significantly predicted REE (adjusted R2 = 0.63; P < 0.001), the addition of fat mass to the regression model substantially improved the prediction for REE (adjusted R2 = 0.71; P < 0.001). AEE was also significantly predicted by FFM (adjusted R2 = 0.12; P < 0.05).


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  		TABLE 3 Regression models showing predictors of TEE, REE, and AEE in 30 weight stable, extremely obese women1

 
TEE and PAL (mean ± SD), obtained in our study were contrasted with values from published energy expenditure data compiled by Prentice et al. (3) (Fig. 1). TEE increased with increasing BMI (P < 0.0001) in the Prentice et al. data set (3). In our own data set, mean TEE in the highest BMI tertile was significantly higher than mean TEE in the lowest tertile of BMI. In contrast, values for PAL did not differ with increasing BMI in the women in the Prentice et al. study (3) or in our extremely obese women.



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  		FIGURE 1 TEE (A) and PAL (B) (mean ± SD) by BMI (kg/m2) in normal weight, overweight, obese, and extremely obese BMI groups [Prentice et al. (3)] and in 30 weight stable, extremely obese women in this study according to BMI tertiles.

 
Measured REE was compared with REE predicted using several published equations, i.e., the WHO prediction equation (6), the Harris-Benedict equation (7) for normal weight individuals, and 2 equations developed for use in the obese (8,9) (Fig. 2). Both the WHO equation (–0.12 MJ/d; adjusted P = 0.97) and the Harris-Benedict equation (0.23 MJ/d; adjusted P = 0.79) showed nonsignificant mean differences from measured REE. The Harris-Benedict equation underpredicted, and the WHO equation overpredicted REE by only 3%. The sum of squared differences between measured and predicted REE was larger for the WHO equation (69 vs. 53) than for the Harris-Benedict equation, indicating that the Harris-Benedict equation was more precise. When equations developed in obese populations were used, measured REE was significantly different from that predicted using the Ireton-Jones equation (–3.30 MJ/d; adjusted P < 0.001) and the Bernstein equation (1.87 MJ/d; adjusted P < 0.001). The Ireton-Jones equation overpredicted REE by 40% and the Bernstein equation underpredicted REE by 18%. In addition, the sum of squared differences between measured and predicted REE was very large for both equations (122, for the Bernstein equation and 458, for the Ireton-Jones equation), indicating that the obese-specific equations were poor predictors of REE.



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  		FIGURE 2 Relation between measured REE and REE predicted using the WHO equation (6) and the Harris-Benedict equation (7) for normal weight individuals and the obese-specific Bernstein (8) and Ireton-Jones (9) equations.

 

   DISCUSSION
TOP
 ABSTRACT
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
LITERATURE CITED
 
The major finding of this study was that the TEE of our extremely obese subjects was very high and increased with increasing BMI from (mean ± SEE) 12.79 ± 0.5 MJ/d in the lowest BMI tertile [(mean ± SD), BMI, 40.8 ± 2.1kg/m2] to 16.61 ± 0.76 MJ/d in the highest BMI tertile (mean BMI, 61.2 ± 8.8 kg/m2). We chose to examine and present data using BMI tertiles because we wanted to determine whether energy expenditure increased with increasing body mass over the wide range of BMI in our study. The TEE value for the highest BMI tertile was 41% higher on average than the mean TEE of nonobese women published in a summary of doubly labeled water data (3), and 38% higher than previous measurements of TEE in nonobese women [(mean ± SD), BMI, 20.9 ± 1.9] by our own research group (14), and the predicted TEE using the equations of the U.S. DRIs (5) for nonobese women (BMI <= 30.0 kg/m2). These results indicate that extremely obese individuals have high rather than low rates of TEE, and therefore must consume very high levels of dietary energy to maintain their excess weight. This conclusion is inconsistent with numerous reports of low energy intake in obese individuals (15–18), but is entirely consistent with previous TEE data from smaller studies of extremely obese persons (34 subjects total) (19–26). There are several aspects of our study design that deserve mention. The use of doubly labeled water to measure TEE and a multicompartment model for the measurement of body composition was important. Doubly labeled water is the only recognized accurate method for estimation of TEE in free-living subjects (27,28) and is the only method that is relatively independent of inaccurate dietary reporting (15–18). Although 1 previous study that compared TEE measured in a calorimetric chamber with that of TEE from doubly labeled water measurements indicated that doubly labeled water may underestimate TEE in obese subjects (20), the degree of underestimation in that study was small (mean ± SD, –4.4 ± 5.2{per thousand}). Furthermore, an underestimation of TEE in obese individuals would only strengthen our findings of high TEE in our population.

In addition to finding high TEE in this extremely obese population, we also observed that PAL values (an index of the proportion of TEE attributable to physical activity) were somewhat low compared with published summaries of PAL determined by doubly labeled water in nonobese populations (3). Although differences in measurement errors between laboratories necessarily limit between-laboratory comparisons, all methods were validated against reference techniques in our laboratory and in the published data. It is also interesting to note that the observed PAL values in our study, although apparently substantially lower than those of nonobese individuals (3), were actually higher than anticipated for sedentary adults on the basis of current (5) U.S. DRIs.

In addition to the finding of high levels of TEE, varying degrees of accuracy were found in the prediction of REE in our population with the equations recommended for use in the nonobese and obese (8,9). Contrary to expectation, the widely used WHO equation and Harris-Benedict equations (6,7,29) developed in normal weight individuals provided the closest values to measured REE. The Harris-Benedict equation was the most accurate of all. The 2 obese-specific equations substantially under- or overpredicted REE, indicating that the standard equations provide better predictions of REE in extremely obese individuals.

In conclusion, absolute values for TEE and REE in extremely obese individuals are high and increase with increasing body mass. In addition, TEE and REE in our extremely obese subjects were higher than published values for nonobese individuals (3), and also higher than the U.S. DRI estimates of dietary energy requirements in nonobese individuals (5,6,29). These observations strongly suggest that high energy intakes contribute to the maintenance of excess weight in extremely obese individuals. Finally, the most widely used Harris-Benedict equations and WHO equations provided the closest estimate for predicted REE, and the obese-specific equations were inaccurate for use in our extremely obese individuals


   ACKNOWLEDGMENTS
 
We thank all of the subjects who participated in the study, Marshall Otter for his assistance in the doubly labeled water analysis, and the nursing staff at the General Clinical Research Center, New England Medical Center, for their expert patient care and support.


   FOOTNOTES
 
1 Supported by National Institutes of Health grants MH/DK54092–01A3, M01-RR00054, and P30 DK 46200 and by the U.S. Department of Agriculture, Agricultural Research Service under contract 53–3K06–5-10. Back

3 Abbreviations used: AEE, activity energy expenditure; CSU, clinical studies unit; DRI, dietary reference intakes; FFM, fat-free mass; FQ, food quotient; GBP, gastric bypass; LTPA, leisure time physical activity; PAL, physical activity level; REE, resting energy expenditure; RQ, respiratory quotient; TEE, total energy expenditure; TEF, thermic effect of feeding. Back

Manuscript received 8 December 2003. Initial review completed 4 January 2004. Revision accepted 29 March 2004.


   LITERATURE CITED
TOP
 ABSTRACT
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED
 

1. Flegal, K. M., Carroll, M. D., Ogden, C. L. & Johnson, C. L. (2002) Prevalence and trends in obesity among US adults, 1999–2000. J. Am. Med. Assoc. 288:1723-1727.[Abstract/Free Full Text]

2. Black, A. E., Coward, W. A., Cole, T. J. & Prentice, A. M. (1996) Human energy expenditure in affluent societies: an analysis of 574 doubly-labelled water measurements. Eur. J. Clin. Nutr. 50:72-92.[Medline]

3. Prentice, A. M., Black, A. E., Coward, W. A. & Cole, T. J. (1996) Energy expenditure in overweight and obese adults in affluent societies: an analysis of 319 doubly-labelled water measurements. Eur. J. Clin. Nutr. 50:93-97.[Medline]

4. Schoeller, D. A. (1999) Recent advances from application of doubly labeled water to measurement of human energy expenditure. J. Nutr. 129:1765-1768.[Abstract/Free Full Text]

5. Institute of Medicine (2002) Dietary Reference Intakes: Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids 2002 National Academy Press Washington, DC .

6. National Research Council (1989) Recommended Dietary Allowances 10th ed. 1989 National Academy Press Washington, DC .

7. Harris, J. A. & Benedict, F. G. (1919) Biometric Studies of Basal Metabolism in Man 1919 Carnegie Institute of Washington Washington, DC .

8. Bernstein, R. S., Thornton, J. C., Yang, M. U., Wang, J., Redmond, A. M., Pierson, R. N., Pi-Sunyer, F. X. & Van Itallie, T. B. (1983) Prediction of the resting metabolic rate in obese patients. Am. J. Clin. Nutr. 37:595-602.[Abstract/Free Full Text]

9. Ireton-Jones, C. S. (1989) Evaluation of energy expenditure in obese patients. Nutr. Clin. Pract. 4:127-129.[Medline]

10. Matthews, D. R., Hosker, J. P., Rudenski, A. S., Naylor, B. A., Treacher, D. F. & Turner, R. C. (1985) Homeostasis model assessment: insulin resistance and ß-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28:412-419.[Medline]

11. Bonora, E., Targher, G., Alberiche, M., Bonadonna, R. C., Saggiani, F., Zenere, M. B., Monauni, T. & Muggeo, M. (2000) Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity. Diabetes Care 23:57-63.[Abstract]

12. Das, S. K., Roberts, S. B., Kehayias, J. J., Wang, J., Hsu, G.L.K., Shikora, S. A., Saltzman, E. & McCrory, M. A. (2003) Body composition assessment in extreme obesity and after massive weight loss induced by gastric bypass surgery. Am. J. Physiol. 284:E1080-E1088.

13. Das, S. K., Roberts, S. B., McCrory, M. A., Hsu, G.L.K., Shikora, S. A., Kehayias, J. J., Dallal, G. E. & Saltzman, E. (2003) Long-term changes in energy expenditure and body composition after massive weight loss induced by gastric bypass surgery. Am. J. Clin. Nutr. 78:22-30.[Abstract/Free Full Text]

14. Sawaya, A. L., Saltzman, E., Fuss, P., Young, V. R. & Roberts, S. B. (1995) Dietary energy requirements of young and older women determined by using the doubly labeled water method. Am. J. Clin. Nutr. 62:338-344.[Abstract/Free Full Text]

15. Schoeller, D. A. (1990) How accurate is self-reported dietary energy intake?. Nutr. Rev. 48:373-379.[Medline]

16. Schoeller, D. A., Bandini, L. G. & Dietz, W. H. (1990) Inaccuracies in self-reported intake identified by comparison with the doubly labelled water method. Can. J. Physiol. Pharmacol. 68:941-949.[Medline]

17. Westerterp, K. R., Verboeket-van de Venne, W.P.H.G., Meijer, G.A.L. & Ten Hoor, F. (1991) Self-reported intake as a measure for energy intake. A validation against doubly labeled water. Obes. Eur. 91:17-22.

18. Heitmann, B. L. & Lissner, L. (1995) Dietary underreporting by obese individuals—is it specific or non-specific?. Br. Med. J. 311:986-989.[Abstract/Free Full Text]

19. Prentice, A. M., Black, A. E., Coward, W. A., Davies, A. L. & Goldberg, G. R. (1986) High levels of energy expenditure in obese women. Br. Med. J. 292:983-987.

20. Ravussin, E., Harper, I., Rising, R. & Bogardus, C. (1991) Energy expenditure by doubly-labeled water: validation in lean and obese subjects. Am. J. Physiol. 261:E402-E409.

21. Westerterp, K. R., Meijer, G.A.L., Saris, W.H.M., Soeters, P. B., Winantis, Y. & Ten Hoor, F. (1991) Physical activity and sleeping metabolic rate. Med. Sci. Sports Exerc. 23:166-170.[Medline]

22. Westerterp, K. R., Saris, W.H.M., Soeters, P. B. & ten Hoor, F. (1991) Determinants of weight loss after vertical banded gastroplasty. Int. J. Obes. Relat. Metab. Disord. 15:529-534.

23. Buhl, K. M., Gallagher, D., Hoy, K., Matthews, D. E. & Heymsfield, S. B. (1995) Unexplained disturbance in body weight regulation: diagnostic outcome assessed by doubly labeled water and body composition analyses in obese patients reporting low energy intakes. J. Am. Diet Assoc. 95:1393-1400.[Medline]

24. Su, W., Jones, P.J.H., Cleator, I.G.M., Phang, P. T. & Birmingham, C. L. (1996) Determinants of weight loss following ileogastronomy. Int. J. Obes. Relat. Metab. Disord. 20:481-487.[Medline]

25. van Gemert, W. G., Westerterp, K. R., Van Acker, B.A.C., Wagenmakers, A.J.M., Halliday, D., Greve, J. M. & Soeters, P. B. (2000) Energy substrate and protein metabolism in morbid obesity before, during and after massive weight loss. Int. J. Obes. Relat. Metab. Disord. 24:711-718.[Medline]

26. Gibney, E. R., Murgatroyd, P., Wright, A., Jebb, S. & Elida, M. (2003) Measurement of total energy expenditure in grossly obese women: comparison of the bicarbonate-urea method with whole-body calorimetry and free living doubly labeled water. Int. J. Obes. and Relat. Metab. Disord. 27:641-647.

27. Schoeller, D. A. (1988) Measurement of energy expenditure in free-living humans by using doubly labeled water. J. Nutr. 118:1278-1289.

28. Roberts, S. B. (1989) Use of the doubly labeled water method for measurement of energy expenditure, total body water, water intake, and metabolizable energy intake in humans and small animals. Can. J. Physiol. Pharm. 67:1190-1198.[Medline]

29. World Health Organization (1985) Energy and Protein Requirements. Report of a Joint FAO/WHO/UNU Expert Consultation 1985:206 WHO Geneva, Switzerland .




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