scholarly journals Accuracy of Predictive Resting-Metabolic-Rate Equations in Chinese Mainland Adults

2019 ◽  
Vol 16 (15) ◽  
pp. 2747 ◽  
Author(s):  
Jingjing Xue ◽  
Shuo Li ◽  
Yong Zhang ◽  
Ping Hong
Keyword(s):  
Metabolic Rate ◽  
Indirect Calorimetry ◽  
Resting Metabolic Rate ◽  
Chinese Mainland ◽  
Fat Free Mass ◽  
Rate Equations ◽  
Validation Group ◽  
Anthropometric Characteristics ◽  
Development And Validation ◽  
Anthropometric Assessment

Accurate measurement of the resting metabolic rate (RMR) is necessary when we make energy requirements and nutrition suggestions in clinical. However, indirect calorimetry is not always available. The objectives of this study were to make a comparison between RMR measured by indirect calorimetry and RMR predicted by different kinds of equations, and to develop new predictive equations for Chinese mainland adults. In this study, 315 Chinese mainland adults from different provinces all over China were recruited. Subjects underwent half a day of testing, which consisted of anthropometric assessment and RMR measurement. Measured and predicted RMR were compared; new optimal equations for Chinese mainland adults were developed and tested by splitting the subjects into a development and validation group. The measured RMR was in the range of 831–2776 kcal/day (mean 1651 ± 339 kcal/day). Our findings indicated that, except for the Harris–Benedict and Schofield equations, three Chinese equations and two fat-free mass (FFM) modeling equations all significantly underestimated RMR compared to the measured value (all p < 0.01). There were no significant differences between predicted and measured RMR using the new equations for females and males. Of the pre-existing equations, Schofield’s is the most suitable for Chinese mainland adults. However, the two new equations developed in this study seem to be more effective for predicting the RMR of Chinese mainland adults, and need to be validated by a larger independent sample with different physiological and anthropometric characteristics.

scholarly journals Adherence to a Low Carbohydrate Diet may Modify Resting Metabolic Rate among Overweight and Obese Women

2020 ◽  
Author(s):  
Seyedeh Forough Sajjadi ◽  
Atieh Mirzababaei ◽  
nasim Ghodoosi ◽  
Sara Pooyan ◽  
Hana Arghavani ◽  
...  
Keyword(s):  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Fat Free Mass ◽  
Obese Women ◽  
Carbohydrate Diet ◽  
Cross Sectional ◽  
Low Carbohydrate Diet ◽  
Low Carbohydrate ◽  
Carb Diet ◽  
Adjusted Model

Abstract Objective Resting metabolic rate (RMR) accounts for most of the daily energy expenditure. The low-carb diet attenuates decreases in RMR. This study aims to investigate the relationship between a low-carb diet and resting metabolic rate status. Methods We enrolled 304 overweight and obese women in this cross-sectional study. BMI, fat mass, fat-free mass, visceral fat, insulin level were assessed. RMR was measured using indirect calorimetry. A low carbohydrate diet score was measured using a validated semi-quantitative food frequency questionnaire (FFQ). Results Our results showed no relationship between LCDS and DNR even after adjust for confounders (Inc. RMR: OR: 0.97; 95% CI: 0.92–1.01, P = 0.20; Dec. RMR: OR: 0.97; 95% CI: 0.94-1.00, P = 0.14). Some components of LCDS had significant differences with DNR, such as carbohydrate and Dec. RMR in adjusted model (OR: 1.62; 95% CI: 0.98–1.37, P = 0.08), MUFA and Dec. RMR in adjusted model (OR: 0.48; 95% CI: 0.21–1.10, P = 0.08) and refined grain and Inc. RMR in crude model (OR: 0.87; 95% CI: 0.77–0.99, P = 0.04). Conclusion Our study showed that there is no association between a low-carb diet and RMR status but carbohydrate, MUFA, and refined grain had a significant relationship.

scholarly journals Dietary Intake and Energy Expenditure in Breast Cancer Survivors: A Review

Nutrients ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 3394
Author(s):  
Sarah A. Purcell ◽  
Ryan J. Marker ◽  
Marc-Andre Cornier ◽  
Edward L. Melanson
Keyword(s):  
Breast Cancer ◽  
Physical Activity ◽  
Energy Balance ◽  
Energy Expenditure ◽  
Dietary Intake ◽  
Metabolic Rate ◽  
Cancer Survivors ◽  
Breast Cancer Survivors ◽  
Resting Metabolic Rate ◽  
Fat Free Mass

Many breast cancer survivors (BCS) gain fat mass and lose fat-free mass during treatment (chemotherapy, radiation, surgery) and estrogen suppression therapy, which increases the risk of developing comorbidities. Whether these body composition alterations are a result of changes in dietary intake, energy expenditure, or both is unclear. Thus, we reviewed studies that have measured components of energy balance in BCS who have completed treatment. Longitudinal studies suggest that BCS reduce self-reported energy intake and increase fruit and vegetable consumption. Although some evidence suggests that resting metabolic rate is higher in BCS than in age-matched controls, no study has measured total daily energy expenditure (TDEE) in this population. Whether physical activity levels are altered in BCS is unclear, but evidence suggests that light-intensity physical activity is lower in BCS compared to age-matched controls. We also discuss the mechanisms through which estrogen suppression may impact energy balance and develop a theoretical framework of dietary intake and TDEE interactions in BCS. Preclinical and human experimental studies indicate that estrogen suppression likely elicits increased energy intake and decreased TDEE, although this has not been systematically investigated in BCS specifically. Estrogen suppression may modulate energy balance via alterations in appetite, fat-free mass, resting metabolic rate, and physical activity. There are several potential areas for future mechanistic energetic research in BCS (e.g., characterizing predictors of intervention response, appetite, dynamic changes in energy balance, and differences in cancer sub-types) that would ultimately support the development of more targeted and personalized behavioral interventions.

Effect of age on body composition and resting metabolic rate

1990 ◽  
Vol 259 (2) ◽  
pp. E233-E238 ◽  
Author(s):  
N. K. Fukagawa ◽  
L. G. Bandini ◽  
J. B. Young
Keyword(s):  
Body Composition ◽  
Metabolic Rate ◽  
Isotope Dilution ◽  
Resting Metabolic Rate ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Open Circuit ◽  
Fat Free Mass ◽  
The Difference ◽  
Old Men

The relationship between fat-free mass (FFM) and resting metabolic rate (RMR) was compared in young men (n = 24; age 18-33 yr), old men (n = 24; 69-89 yr), and old women (n = 20; 67-75 yr). Body composition was assessed using anthropometry, bioelectrical impedance analysis (BIA), and isotope dilution with 18O-labeled water. RMR was measured at least twice using an open-circuit indirect calorimetry system with a ventilated hood. The results indicate that the different methods for assessing body composition vary substantially and should not be used interchangeably. Anthropometry was not adequate to assess group differences in body fatness, although skinfold measures may be appropriate for within-group comparisons. BIA correlated well with the isotope-dilution technique and may be a useful measure of FFM. Finally, RMR was lower in the old men than the young (1.04 +/- 0.02 vs. 1.24 +/- 0.03 kcal/min, P less than 0.001) and remained lower even when adjusted for FFM estimated by isotope dilution (P less than 0.001). RMR in the women was also lower (0.84 +/- 0.02 kcal/min), but in contrast to the difference between young and old men, RMR adjusted for FFM did not differ (P = 0.16) between old men and women. Therefore, it is clear that differences in FFM cannot fully account for the lower RMR in the old, suggesting that aging is associated with an alteration in tissue energy metabolism.

Resting Metabolic Rate and Thermic Effect of a Meal in Low- and Adequate-Energy Intake Male Endurance Athletes

1993 ◽  
Vol 3 (2) ◽  
pp. 194-206 ◽  
Author(s):  
Janice Thompson ◽  
Melinda M. Manore ◽  
James S. Skinner
Keyword(s):  
Metabolic Rate ◽  
Energy Intake ◽  
Weight Maintenance ◽  
Resting Metabolic Rate ◽  
Activity Level ◽  
Low Energy ◽  
Fat Free Mass ◽  
Endurance Athletes ◽  
Male Athletes ◽  
Thermic Effect

The resting metabolic rate (RMR) and thermic effect of a meal (TEM) were determined in 13 low-energy intake (LOW) and 11 adequate-energy intake (ADQ) male endurance athletes. The LOW athletes reported eating 1,490 kcal·day-1less than the ADQ group, while the activity level of both groups was similar. Despite these differences, both groups had a similar fat-free mass (FFM) and had been weight stable for at least 2 years. The RMR was significantly lower (p<0.05) in the LOW group compared to the values of the ADQ group (1.19 vs. 1.29 kcal·FFM-1·hr-l, respectively); this difference represents a lower resting expenditure of 158 kcal·day-1. No differences were found in TEM between the two groups. These results suggest that a lower RMR is one mechanism that contributes to weight maintenance in a group of low- versus adequate-energy intake male athletes.

New Predictive Resting Metabolic Rate Equations for High-Level Athletes

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Raul Freire ◽  
Glauber Pereira ◽  
Juan MA Alcantara ◽  
Ruan Santos ◽  
Matheus Hausen ◽  
...  
Keyword(s):  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Rate Equations ◽  
High Level

Percent relative cumulative frequency analysis in indirect calorimetry: application to studies of transgenic mice

2004 ◽  
Vol 82 (12) ◽  
pp. 1075-1083 ◽  
Author(s):  
Marc Riachi ◽  
Jean Himms-Hagen ◽  
Mary-Ellen Harper
Keyword(s):  
Oxygen Consumption ◽  
Energy Expenditure ◽  
Metabolic Rate ◽  
Indirect Calorimetry ◽  
Uncoupling Protein ◽  
Resting Metabolic Rate ◽  
Large Data ◽  
Cumulative Frequency ◽  
And Control ◽  
Deficient Mice

Indirect calorimetry is commonly used in research and clinical settings to assess characteristics of energy expenditure. Respiration chambers in indirect calorimetry allow measurements over long periods of time (e.g., hours to days) and thus the collection of large sets of data. Current methods of data analysis usually involve the extraction of only a selected small proportion of data, most commonly the data that reflects resting metabolic rate. Here, we describe a simple quantitative approach for the analysis of large data sets that is capable of detecting small differences in energy metabolism. We refer to it as the percent relative cumulative frequency (PRCF) approach and have applied it to the study of uncoupling protein-1 (UCP1) deficient and control mice. The approach involves sorting data in ascending order, calculating their cumulative frequency, and expressing the frequencies in the form of percentile curves. Results demonstrate the sensitivity of the PRCF approach for analyses of oxygen consumption ([Formula: see text]02) as well as respiratory exchange ratio data. Statistical comparisons of PRCF curves are based on the 50th percentile values and curve slopes (H values). The application of the PRCF approach revealed that energy expenditure in UCP1-deficient mice housed and studied at room temperature (24 °C) is on average 10% lower (p < 0.0001) than in littermate controls. The gradual acclimation of mice to 12 °C caused a near-doubling of [Formula: see text] in both UCP1-deficient and control mice. At this lower environmental temperature, there were no differences in [Formula: see text] between groups. The latter is likely due to augmented shivering thermogenesis in UCP1-deficient mice compared with controls. With the increased availability of murine models of metabolic disease, indirect calorimetry is increasingly used, and the PRCF approach provides a novel and powerful means for data analysis.Key words: thermogenesis, oxygen consumption, metabolic rate, uncoupling protein, UCP.

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