Indirect calorimetry in obese female subjects: Factors influencing the resting metabolic rate

Hagedorn, T.

doi:10.5493/wjem.v2.i3.58

Cited by 14 publications

(10 citation statements)

References 36 publications

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“…Previous studies also reported that in metabolic syndrome with increasing adipose tissue, especially visceral adipose tissue increases serum vaspin concentrations [36][37][38] and vaspin mRNA expression [4,13]. On the other hand, overweight with insulin resistant subject had higher RMR [39,40] which shows positive association between circulating vaspin and RMR.…”

Section: Discussionmentioning

confidence: 74%

Mediatory effect of circulating vaspin on resting metabolic rate in obese individuals

et al. 2015

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Section: Discussionmentioning

confidence: 74%

Mediatory effect of circulating vaspin on resting metabolic rate in obese individuals

et al. 2015

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“…The BMR was estimated by seven prediction equations commonly used according to sex and age: Harris-Benedict (5), Schofield (6), Mifflin-St. Jeor (7), FAO/WHO/UNO (8), Gougeon (20), Bernstein (29), and Oxford (30). We also evaluated the estimated caloric intake (27) and antihypertensive agents (100%), and 38.1% (n = 8) used lipid-lowering agents.…”

Section: Statistical Analysesmentioning

confidence: 99%

“…The variability of BMR may depend on several factors, such as sex, ethnicity, age, physical activity, genetic factors, the presence of diabetes or obesity, body composition, and caloric intake (7). Several studies have evaluated BMR using prediction equations in different populations (8)(9)(10) and specific ethnic groups, as demonstrated in the US and Dutch (11), Belgian (12), Pima Indians (13), Caucasians (14) and Asian populations (15)(16)(17)(18) In nondiabetic individuals, different studies have demonstrated that the equations described by Harris-Benedict (3), Schofield (4), Mifflin-St. Jeor (5), and the FAO/WHO/UNO (6) can overestimate or underestimate the BMR value as compared with IC.…”

Section: Introductionmentioning

confidence: 99%

Basal metabolic rate in Brazilian patients with type 2 diabetes: comparison between measured and estimated values

Steemburgo¹,

Lazzari²,

Farinha³

et al. 2019

Archives of Endocrinology and Metabolism

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Objectives:The aims of this study are to investigate which of the seven selected predictive equation for estimating basal metabolic rate (BMR) is the best alternative to indirect calorimetry (IC) and to evaluate the dietary energy intake in patients with type 2 diabetes. Subjects and methods: Twentyone patients with type 2 diabetes participated in this diagnostic test study. Clinical and laboratorial variables were evaluated as well as body composition by absorptiometry dual X-ray emission (DXA) and BMR measured by IC and estimated by prediction equations. Dietary intake was evaluated by a quantitative food frequency questionnaire. Data were analyzed using Bland-Altman plots, paired t-tests, and Pearson's correlation coefficients. Results: Patients were 62 (48-70) years old, have had diabetes for 8 (2-36) yeas, and 52.4% were females. The mean body composition comprised a fat-free mass of 49.8 ± 9.4 kg and a fat mass of 28.3 ± 7.2 kg. The energy intake was 2134.3 ± 730.2 kcal/day and the BMR by IC was 1745 ± 315 kcal/day. There was a wide variation in the accuracy of BMR values predicted by equations when compared to IC BMR measurement. Harris-Benedict, Oxford, FAO/WHO/ UNO equations produced the smallest differences to IC, with a general bias of < 8%. The FAO/WHO/ UNO equation provided the best BMR prediction in comparison to measured BMR. Conclusion: In patients with type 2 diabetes, the equation of the FAO/WHO/UNO was the one closest to the BMR values as measured by IC.

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“…In any case, even when the abstention from physical exercise is not indicated in the protocol, laboratory experiments should be initiated after a period of rest (10–20 minutes) in order to minimize possible effects of recent physical activities such as dressing, driving, or walking [ 59 , 60 ]. Furthermore, taking into account the well-known effects of smoking in affecting EE [ 61 , 62 ] and that smoking can affect the measurement of RMR in obese patients [ 63 ], smokers should be excluded from the sample population, or the results should be presented considering the smoking status. This exclusion could be avoided in the case of accelerometers that take into account the smoking status in the equations (i.e., SWA) [ 34 ].…”

Section: Discussionmentioning

confidence: 99%

Validity of Accelerometers for the Evaluation of Energy Expenditure in Obese and Overweight Individuals: A Systematic Review

Pisanu

Deledda

Loviselli

et al. 2020

Journal of Nutrition and Metabolism

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Objective. Even though the validity of accelerometers for the measurement of energy expenditure (EE) has been demonstrated for normal-weight individuals, the applicability of this instrument in obese individuals remains controversial. This review aims to summarize the level of agreement between accelerometers and the gold standards (indirect calorimetry and doubly labelled water) for the measurement of energy expenditure (EE) in obese or overweight individuals. Methods. The literature search was limited to comparison studies assessing agreement in EE determination between accelerometers and indirect calorimetry (IC) or doubly labelled water (DLW). We searched in PubMed and in Scopus until March 1, 2019. The analysis was restricted to obese or overweight adult individuals. The following descriptive information was extracted for each study: sample size, characteristics of participants (sex, age, BMI, fat mass percentage, any pathological conditions, modality of recruitment in the study, and exclusion criteria), accelerometer description (model, type and body position), and type of gold standard and validity protocol (duration, conditions, and requirements during and before the experiment). Three review authors independently screened the obtained results, and the quality of the selected articles was assessed by the QUADAS-2 tool. Results. We obtained seventeen eligible articles, thirteen of which showed concerns for the applicability section, due to the patient selection. Regarding the accelerometers, nine devices were validated in the included studies with the BodyMedia SenseWear® (SWA) being the most frequently validated. Although correlations between accelerometers and the gold standard were high in some studies, agreement between the two methods was low, as shown by the Bland–Altman plots. Conclusions. Most accelerometer estimations of EE were inaccurate for obese/overweight subjects, and authors advise to improve the accuracy of algorithms for SWA software, or the predicted equations for estimating EE from other accelerometers.

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Indirect calorimetry in obese female subjects: Factors influencing the resting metabolic rate

Abstract: Future research should be prompted to optimize the procedure of indirect calorimetry to achieve clinical benefits in obese subjects.

Cited by 14 publications

References 36 publications

Mediatory effect of circulating vaspin on resting metabolic rate in obese individuals

Mediatory effect of circulating vaspin on resting metabolic rate in obese individuals

Basal metabolic rate in Brazilian patients with type 2 diabetes: comparison between measured and estimated values

Validity of Accelerometers for the Evaluation of Energy Expenditure in Obese and Overweight Individuals: A Systematic Review

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