Reliability of resting metabolic rate measurements in young adults: Impact of methods for data analysis

Sánchez-Delgado, Guillermo; Alcantara, Juan M. A.; Ortiz-Alvarez, Lourdes; Xu, Huiwen; Martínez-Téllez, Borja; Labayen, Idoia; Ruiz, Jonatan R.

doi:10.1016/j.clnu.2017.07.026

Cited by 56 publications

(63 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the present study, all RMR measurements were included in the analysis because the conclusion of the findings remains unchanged when we stratified the data by the participants with and without a steady state. This is in line with a previous study in healthy adults which suggested that participants who do not achieve steady state should not be excluded from data analysis (47) . There is no universal definition for steady state as it varies by measurement time, the CV and combination of gas-exchange variables (VO 2 and VCO 2 ) (13) .…”

Section: Discussionsupporting

confidence: 92%

The use of a portable metabolic monitoring device for measuring RMR in healthy adults

et al. 2020

View full text Add to dashboard Cite

Objective measurement of resting metabolic rate (RMR) may be important for optimal nutritional care but is hindered by the price and practicality of the metabolic monitoring device. This study compared two metabolic monitoring devices for measuring RMR and oxygen consumption (VO2) and compared the measured RMR with the predicted RMR calculated from equations. RMR was measured using QUARK RMR (reference device) and Fitmate GS (COSMED) in a random order for 30 minutes, each on fasted participants. In total, 68 adults participated (median age 22 years, interquartile range 21-32). Pearson correlation showed that RMR (r=0.86) and VO2 (r=0.86) were highly correlated between the two devices (p<0.05). Intraclass Correlation Coefficients (ICC) showed good relative agreements regarding RMR (ICC=0.84) and VO2 (ICC=0.84) (p<0.05). RMR measured by QUARK RMR was significantly higher (155±180 kcal/day) than Fitmate GS. Equations significantly overpredicted RMR. Accurate RMR (i.e. within ±10% of the RMR measured by QUAR RMR) was found among 38% of the participants for Fitmate GS, and among 46-68% depending on the equations. Bland-Altman analysis showed a low absolute agreement with QUARK RMR at an individual level for both Fitmate GS (limits of agreement (LOA): -198 to +508 kcal/day) and equations (LOA ranged from -473 to +449 kcal/day). In conclusion, both Fitmate GS and predictive equations had low absolute agreements with QUARK RMR at an individual level. Therefore, these limitations should be considered when determining RMR using Fitmate GS or equations.

show abstract

Section: Discussionsupporting

confidence: 92%

The use of a portable metabolic monitoring device for measuring RMR in healthy adults

et al. 2020

View full text Add to dashboard Cite

show abstract

“…However, as STS is not always achieved, other methods for data analysis have been proposed, such as predefined time interval selection [5]. Sanchez-Delgado et al [6] recently showed that REE is consistently lower when following STS approach than when following time interval methods in healthy young adults. This suggests that achieving STS could provide a more valid REE measurement, given that REE is considered the lowest energy expenditure in an awake person [5].…”

Section: Methodology Of Indirect Calorimetry: What Is New?mentioning

confidence: 99%

“…However, further studies are needed to assess the best method for analyzing indirect calorimetry measurements if STS is not achieved. According to Sanchez Delgado et al [6], the selection of the five most stable minutes should be the method of choice for analyzing indirect calorimetry measures in healthy young adults. Indeed, although no significant differences were found between different durations of STS (3, 4, 5 and 10 min), 5 min STS presented the lowest REE [6].…”

Section: Methodology Of Indirect Calorimetry: What Is New?mentioning

confidence: 99%

Innovations in energy expenditure assessment

Achamrah

Oshima

Genton

2018

Current Opinion in Clinical Nutrition &Amp; Metabolic Care

View full text Add to dashboard Cite

show abstract

“…The most stable 5-min period that met steady-state criteria (i.e., coefficient of variation <10% in VO 2 , CO 2 , and minute ventilation, and coefficient of variation <10% in respiratory exchange ratio (RER)) was considered for further analysis [4,5,27,28]. Participants with an RER lower than 0.7 and/or higher than 1.0 were excluded from the final analysis.…”

Section: Basal Metabolic Rate and Basal Nutrients Oxidationmentioning

confidence: 99%

Association of Basal Metabolic Rate and Nutrients Oxidation with Cardiometabolic Risk Factors and Insulin Sensitivity in Sedentary Middle-Aged Adults

et al. 2020

Self Cite

View full text Add to dashboard Cite

This cross-sectional study aimed to examine the association of basal metabolic rate (BMR) and basal fat and carbohydrate oxidation (BFox and BCHox, respectively) with cardiometabolic risk factors and insulin sensitivity in sedentary middle-aged adults. A total of 71 healthy sedentary adults (37 women) aged 40-65 years participated in the current study. Data were collected during the baseline assessments of the FIT-AGEING randomized controlled trial. BMR was measured via indirect calorimetry, and BFox and BCHox estimated by stoichiometric equations. Blood pressure, glucose, insulin, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides plasma levels were selected as cardiometabolic risk factors and assessed following standard procedures. We observed positive associations of BMR with plasma insulin and the homeostatic model assessment of insulin resistance index (HOMA; all p < 0.05) which were attenuated or disappeared after controlling by sex, age, and/or lean mass. There were positive associations between BFox and the quantitative insulin sensitivity check index (QUICKI; p < 0.015), while negative associations were noted between BFox and plasma insulin and HOMA (p < 0.015). There was a significant negative association between BCHox with QUICKI (p < 0.01), whereas significant positive relationships were obtained when BCHox was associated with plasma insulin and HOMA (p < 0.01). These associations persisted in almost all cases when controlling by sex, age and/or lean mass. No further relationships were found when BMR, BFox, and BCHox were associated with other cardiometabolic risk factors. In conclusion, our study findings support that greater BFox and lower BCHox are related to improved insulin sensitivity, whereas BMR seems to be not associated with neither cardiometabolic risk nor insulin sensitivity in sedentary middle-aged adults. Further intervention studies are necessary to well-understand the physiological mechanism implied in this relationship.

show abstract

Reliability of resting metabolic rate measurements in young adults: Impact of methods for data analysis

Abstract: The 5 min SSt approach should be the method of choice for analyzing IC measures with metabolic carts. However, achieving SS should not be an inclusion criterion in an IC study with young healthy adults.

Cited by 56 publications

References 25 publications

The use of a portable metabolic monitoring device for measuring RMR in healthy adults

The use of a portable metabolic monitoring device for measuring RMR in healthy adults

Innovations in energy expenditure assessment

Association of Basal Metabolic Rate and Nutrients Oxidation with Cardiometabolic Risk Factors and Insulin Sensitivity in Sedentary Middle-Aged Adults

Contact Info

Product

Resources

About