Which REE prediction equation should we use in normal-weight, overweight and obese women?

Siervo, Mario; Boschi, V.; Falconi, C

doi:10.1054/clnu.2002.0625

Cited by 75 publications

(75 citation statements)

References 19 publications

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“…However, the limits of agreement for individual predictive accuracy were wide. These results have confirmed previous findings in patients with cancer and healthy subjects (Taaffe et al, 1995;Siervo et al, 2003).…”

Section: Discussionsupporting

confidence: 92%

“…The standard measurement that we used to compare with the MG did not include a 24-h urine collection to adjust energy expenditure for the incomplete oxidation of protein. Recent studies of short-term measurements of energy expenditure in patients do not commonly adjust for nitrogen excretion (Barak et al, 2002;Siervo et al, 2003), which produces a negligible error of 1-2% (Weir, 1949;Bursztein et al, 1989). So that measurements were directly comparable, REE was calculated from VO 2 measured by the MG without adjustment for nitrogen excretion.…”

Section: Discussionmentioning

confidence: 99%

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Clinical accuracy of the MedGem™ indirect calorimeter for measuring resting energy expenditure in cancer patients

et al. 2005

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Objective: To compare, in patients with cancer and in healthy subjects, measured resting energy expenditure (REE) from traditional indirect calorimetry to a new portable device (MedGemt) and predicted REE. Design: Cross-sectional clinical validation study. Setting: Private radiation oncology centre, Brisbane, Australia. Subjects: Cancer patients (n ¼ 18) and healthy subjects (n ¼ 17) aged 37-86 y, with body mass indices ranging from 18 to 42 kg/m 2 . Interventions: Oxygen consumption (VO 2 ) and REE were measured by VMax229 (VM) and MedGem (MG) indirect calorimeters in random order after a 12-h fast and 30-min rest. REE was also calculated from the MG without adjustment for nitrogen excretion (MGN) and estimated from Harris-Benedict prediction equations. Data were analysed using the Bland and Altman approach, based on a clinically acceptable difference between methods of 5%. Results: The mean bias (MGN-VM) was 10% and limits of agreement were -42 to 21% for cancer patients; mean bias À5% with limits of À45 to 35% for healthy subjects. Less than half of the cancer patients (n ¼ 7, 46.7%) and only a third (n ¼ 5, 33.3%) of healthy subjects had measured REE by MGN within clinically acceptable limits of VM. Predicted REE showed a mean bias (HB-VM) of À5% for cancer patients and 4% for healthy subjects, with limits of agreement of À30 to 20% and À27 to 34%, respectively. Conclusions: Limits of agreement for the MG and Harris Benedict equations compared to traditional indirect calorimetry were similar but wide, indicating poor clinical accuracy for determining the REE of individual cancer patients and healthy subjects.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Clinical accuracy of the MedGem™ indirect calorimeter for measuring resting energy expenditure in cancer patients

et al. 2005

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“…Furthermore, there is a direct correlation between BMI and bias of predictive equations. Thus, to minimize such bias ( Siervo et al, 2003), we selected subjects with BMI in the normal range. In addition, RMR for female subjects was measured in the same phase of the menstrual cycle in order to minimize any effects of menstruation on RMR.…”

Section: Discussionmentioning

confidence: 99%

FAO/WHO/UNU equations overestimate resting metabolic rate in Vietnamese adults

et al. 2005

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Objective: To evaluate the FAO/WHO/UNU equations for predicting resting metabolic rate (RMR) in Vietnamese adults. Design: A cross-sectional study with healthy subjects was carried out at the Basic Nutrition Department, National Institute of Nutrition, Vietnam. RMR was measured by indirect calorimetry, and anthropometric indices were recorded. Equations derived by linear regression of RMR vs body weight were compared to the FAO/WHO/UNU 1985 predictive equations. Subjects: A total of 188 subjects (98 males and 90 females) had a normal body mass index (BMI) and were divided into four groups by sex and age (male and female subjects 18-29 and 30-60 y old). Results: Mean RMR (MJ/kg/day) in males was lightly significant by higher than that in female subjects in the 18-29 y old age group (0.107470.0100 vs 0.096570.0123) and the same result was seen in the 30-60 y old group (0.101870.0114 vs 0.092270.0129). However, differences were not statistically significant in the two age groups. Compared to the FAO/WHO/ UNU equation, our findings were 7.4, 9.0, 11.7, and 13.5% lower in the four groups, respectively (Po0.001). Conclusion: Our findings suggest that the FAO/WHO/UNU equations may overestimate RMR in Vietnamese adults. Further studies examining the relationship between body weight and RMR are needed, and establishing new predictive equations for RMR in Vietnamese should be a priority.

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“…This discrepancy for the Dutch than for the United States adults could be explained by the difference about weight and height values, even within sex and BMI subgroups, thus limiting the validity of this equation in similar taller populations. Numerous studies contributed to further evaluate the currently available predictive equations in overweight and obese subjects [52][53][54][55] and/or in extremely obese subjects [56][57][58][59][60][61] . There is some evidences supporting the Mifflin [59] , the FAOw [56,58] and the Harris Benedict [60] , the Siervo equations [61] in extremely obese subjects.…”

Section: Beyond the Adipose Tissue Excess: The Importance Of Muscle Mmentioning

confidence: 99%

Measurement of body composition as a surrogate evaluation of energy balance in obese patients

Rotella

Dicembrini

2015

WJM

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In clinical practice obesity is primarily diagnosed through the body mass index. In order to characterize patients affected by obesity the use of traditional anthropometric measures appears misleading. Beyond the body mass index, there are overwhelming evidences towards the relevance of a more detailed description of the individual phenotype by characterizing the main body components as free-fat mass, muscle mass, and fat mass. Among the numerous techniques actually available, bioelectrical impedance analysis seems to be the most suitable in a clinical setting because it is simple, inexpensive, noninvasive, and highly reproducible. To date, there is no consensus concerning the use of one preferred equation for the resting energy expenditure in overweight and/or obese population. Energy restriction alone is an effective strategy to achieve an early and significant weight loss, however it results in a reduction of both fat and lean mass therefore promoting or aggravating an unfavourable body composition (as sarcobesity) in terms of mortality and comorbidities. Therefore the implementation of daily levels of physical activity should be simultaneously promoted. The major role of muscle mass in the energy balance has been recently established by the rising prevalence of the combination of two condition as sarcopenia and obesity. Physical exercise stimulates energy expenditure, thereby directly improving energy balance, and also promotes adaptations such as fiber type, mitochondrial biogenesis, improvement of insulin resistance, and release of myokines, which may influence different tissues, including muscle. Core tip: There are overwhelming evidences towards the relevance of a more detailed description of the individual phenotype by characterizing the main body components as free-fat mass, muscle mass, and fat mass. Among the numerous techniques actually available, bioelectrical impedance analysis seems to be the most suitable in a clinical setting because it is simple, inexpensive, noninvasive, and highly reproducible. To date, there is no consensus concerning the use of one preferred equation for the resting energy expenditure in overweight and/or obese population. REVIEW

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Which REE prediction equation should we use in normal-weight, overweight and obese women?

Cited by 75 publications

References 19 publications

Clinical accuracy of the MedGem™ indirect calorimeter for measuring resting energy expenditure in cancer patients

Clinical accuracy of the MedGem™ indirect calorimeter for measuring resting energy expenditure in cancer patients

FAO/WHO/UNU equations overestimate resting metabolic rate in Vietnamese adults

Measurement of body composition as a surrogate evaluation of energy balance in obese patients

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