Validation of Equations for the Prediction of Resting Metabolic Rate in Sri Lankan Adults

2019 ◽  
Vol 9 (10) ◽  
pp. p9462
Author(s):  
Pathima Fairoosa ◽  
Indu Waidyatilaka ◽  
Maduka de Lanerolle-Dias ◽  
Pujitha Wickramasinghe ◽  
Pulani Lanerolle
Keyword(s):  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Sri Lankan

scholarly journals Development of a New Equation for the Prediction of Resting Metabolic Rate in Sri Lankan Adults

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Pathima Fairoosa ◽  
Pulani Lanerolle ◽  
Maduka De Lanerolle-Dias ◽  
V. Pujitha Wickramasinghe ◽  
Indu Waidyatilaka
Keyword(s):  
Metabolic Rate ◽  
Indirect Calorimetry ◽  
Cross Validation ◽  
Resting Metabolic Rate ◽  
Prediction Equation ◽  
Sri Lankan ◽  
Study Objective ◽  
Individual Measurement ◽  
Independent Variables ◽  
New Equation

Resting metabolic rate (RMR) is the key determinant of the energy requirement of an individual. Measurement of RMR by indirect calorimetry is not feasible in field settings and therefore equation-based calculations are used. Since a valid equation is not available for Sri Lankans, it is important to develop a new population-specific equation for field use. The study objective was to develop a new equation for the prediction of RMR in healthy Sri Lankans using a reference method, indirect calorimetry. RMR data were collected from fifty-seven (male 27) adults aged 19 to 60 years. They were randomly assigned to validation (n = 28) and cross-validation (n = 19) groups using the statistical package R (version 3.6.3). Height, weight, and RMR were measured. Multivariable fractional polynomials (MFP) were used to determine explanatory variables and their functional forms for the model. A variable shrinkage method was used to find the best fit predictor coefficients of the equation. The developed equation was cross-validated on an independent group. Weight and sex code (male = 1; female = 0) were identified as reliable independent variables. The new equation developed was RMR (kcal/day) = 284.5 + (13.2 x weight) + (133.0 x sex code). Independent variables of the prediction equation were able to predict 88.5% of the variance. Root mean square error (RMSE) of the prediction equation in validation and cross-validation was 88.11 kcal/day and 79.03 kcal/day, respectively. The equation developed in this study is suitable for predicting RMR in Sri Lankan adults.

Nutrient pattern of unsaturated fatty acids and vitamin E increase resting metabolic rate of overweight and obese women

2020 ◽  
pp. 1-9
Author(s):  
Habib Yarizadeh ◽  
Leila Setayesh ◽  
Caroline Roberts ◽  
Mir Saeed Yekaninejad ◽  
Khadijeh Mirzaei
Keyword(s):  
Vitamin E ◽  
Metabolic Rate ◽  
Unsaturated Fatty Acids ◽  
Resting Metabolic Rate ◽  
Blood Parameters ◽  
Cross Sectional Study ◽  
Obese Women ◽  
Cross Sectional ◽  
Dietary Nutrients ◽  
Nutrient Patterns

Abstract. Objectives: Obesity plays an important role in the development of chronic diseases including cardiovascular disease and diabetes. A low resting metabolic rate (RMR) for a given body size and composition is a risk factor for obesity, however, there is limited evidence available regarding the association of nutrient patterns and RMR. The aim of this study was to determine the association of nutrient patterns and RMR in overweight and obese women. Study design: This cross-sectional study was conducted on 360 women who were overweight or obese. Method: Dietary intake was assessed using a semi-quantitative standard food frequency questionnaire (FFQ). Nutrient patterns were also extracted by principal components analysis (PCA). All participants were evaluated for their body composition, RMR, and blood parameters. Result: Three nutrient patterns explaining 64% of the variance in dietary nutrients consumption were identified as B-complex-mineral, antioxidant, and unsaturated fatty acid and vitamin E (USFA-vit E) respectively. Participants were categorized into two groups based on the nutrient patterns. High scores of USFA-vit E pattern was significantly associated with the increase of RMR (β = 0.13, 95% CI = 0.79 to 68.16, p = 0.04). No significant associations were found among B-complex-mineral pattern (β = −0.00, 95% CI = −49.67 to 46.03, p = 0.94) and antioxidant pattern (β = 0.03, 95% CI −41.42 to 22.59, p = 0.56) with RMR. Conclusion: Our results suggested that the “USFA-vit E” pattern (such as PUFA, oleic, linoleic, vit.E, α-tocopherol and EPA) was associated with increased RMR.

The Metabolic Theory of Ecology

2017 ◽  
Author(s):  
Andrew Clarke
Keyword(s):  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Effect Of Temperature ◽  
Thermal Ecology ◽  
Model Data ◽  
Metabolic Theory ◽  
Physical Explanation ◽  
Boltzmann Factor ◽  
Scaling Exponents ◽  
Metabolic Theory Of Ecology

The model of West, Brown & Enquist (WBE) is built on the assumption that the metabolic rate of cells is determined by the architecture of the vascular network that supplies them with oxygen and nutrients. For a fractal-like network, and assuming that evolution has minimised cardiovascular costs, the WBE model predicts that s=metabolism should scale with mass with an exponent, b, of 0.75 at infinite size, and ~ 0.8 at realistic larger sizes. Scaling exponents ~ 0.75 for standard or resting metabolic rate are observed widely, but far from universally, including in some invertebrates with cardiovascular systems very different from that assumed in the WBE model. Data for field metabolic rate in vertebrates typically exhibit b ~ 0.8, which matches the WBE prediction. Addition of a simple Boltzmann factor to capture the effects of body temperature on metabolic rate yields the central equation of the Metabolic Theory of Ecology (MTE). The MTE has become an important strand in ecology, and the WBE model is the most widely accepted physical explanation for the scaling of metabolic rate with body mass. Capturing the effect of temperature through a Boltzmann factor is a useful statistical description but too simple to qualify as a complete physical theory of thermal ecology.

scholarly journals Correction to: The effect of moderate intermittent versus continuous energy restriction on body composition and resting metabolic rate in resistance-trained females: A randomized controlled trial

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Madelin R. Siedler ◽  
Eric T. Trexler ◽  
Megan N. Humphries ◽  
Priscila Lamadrid ◽  
Brian Waddell ◽  
...  
Keyword(s):  
Randomized Controlled Trial ◽  
Body Composition ◽  
Metabolic Rate ◽  
Controlled Trial ◽  
Resting Metabolic Rate ◽  
Energy Restriction ◽  
Randomized Controlled ◽  
Continuous Energy

An amendment to this paper has been published and can be accessed via the original article.

Weight change adjusted equations for assessing resting metabolic rate in overweight and obese adults

2021 ◽  
Author(s):  
Moran Nachmani ◽  
Yair Lahav ◽  
Aviva Zeev ◽  
Liza Grosman-Rimon ◽  
Sigal Eilat-Adar
Keyword(s):  
Metabolic Rate ◽  
Weight Change ◽  
Resting Metabolic Rate ◽  
Obese Adults

scholarly journals ENERGY EXPENDITURE AND PHYSICAL ACTIVITY AMONG OLDER PARTICIPANTS FROM THE MULTICENTER AIDS COHORT STUDY (MACS)

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S549-S549
Author(s):  
Jennifer A Schrack ◽  
Todd T Brown ◽  
Joseph B Margolick
Keyword(s):  
Physical Activity ◽  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Functional Decline ◽  
Time Of Day ◽  
Energy Utilization ◽  
Hiv Viral Load ◽  
Cross Sectional ◽  
And Function ◽  
Lower Physical Activity

Abstract Energy utilization becomes more inefficient with age and is linked to low physical activity and functional decline. Persons aging with HIV exhibit accelerated functional decline, but the effect of chronic HIV infection on energy utilization and free-living physical activity remains unclear. We investigated cross-sectional associations between age and: resting metabolic rate, peak walking energy (VO2), and 7-day physical activity by accelerometry in 100 men in the MACS (age: 60.8+/-6.8 years, 35% black, 46.1% HIV+, 94% virally suppressed). In multivariable regression models adjusted for age, BMI, race, chronic conditions, and HIV viral load, HIV+ men had a higher resting metabolic rate (β=103.2 kcals/day, p=0.03) and lower peak walking VO2 (β=-1.8 ml/kg/min, p<0.02) than HIV- men. Moreover, HIV+ men demonstrated lower physical activity, overall and by time of day (p<0.05). These results suggest that energy utilization differs by HIV serostatus, which may contribute to lower physical activity and function with aging.

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