Accuracy of resting metabolic rate prediction equations among healthy adults in Trinidad and Tobago

2020 ◽  
pp. 026010602096623
Author(s):  
Selby Nichols ◽  
Dennora George ◽  
Patrice Prout ◽  
Nequesha Dalrymple
Keyword(s):  
Metabolic Rate ◽  
Standard Procedure ◽  
Resting Metabolic Rate ◽  
Demographic Variables ◽  
Overweight And Obesity ◽  
Accurate Estimation ◽  
Prediction Equations ◽  
The Caribbean ◽  
The University ◽  
Adult Volunteers

Background: Over 50% of adults in Latin America and the Caribbean have a body mass index (BMI) ≥ 25 suggesting excess energy intakes relative to energy expenditure. Accurate estimation of resting metabolic rate (RMR), the largest component of total energy requirements, is crucial to strategies aimed at reducing the prevalence and incidence of overweight and obesity. Aim: We evaluated the accuracies of established and locally developed RMR prediction equations (RMRP) among adults. Methods: Four hundred adult volunteers ages 20 to 65 years had RMR measured (RMRM) with a MedGem® indirect calorimeter according to recommended procedures. RMRP were compared to RMRM with values ± 10% of RMRM deemed accurate. Anthropometry was measured using standard procedure. Linear regression with bootstrap analyses was used to develop local RMRP equations based on anthropometric and demographic variables. The University of the West Indies Ethics Committee approved the study. Results: Males had higher mean absolute RMR ( p < 0.001) but similar mean age-adjusted measured RMR per kg of body (20.9 vs. 21.5 kcals/day; p = 0.1) to females. The top performing established anthropometry-based RMRP among participants by sex, physical activity (PA) level and BMI status subgroups were Mifflin-St Jeor, Owen, Korth, Harris–Benedict, and Livingston, while Johnstone, Cunningham, Müller (body composition (BC)), Katch and McArdle, Mifflin-St Jeor (BC) were the most accurate BC-based RMRP. Locally developed RMRP had accuracies comparable to their top-ranked established RMRP counterparts. Conclusions: Accuracies of established RMRP depended on habitual PA level, BMI status, BC and sex. Furthermore, locally developed RMRP provide useful alternatives to established RMRP.

Energy Expenditure of Level Overground Walking in Young Adults: Comparison With Prediction Equations

2021 ◽  
pp. 1-8
Author(s):  
Jingjing Xue ◽  
Shuo Li ◽  
Rou Wen ◽  
Ping Hong
Keyword(s):  
Young Adults ◽  
Energy Expenditure ◽  
Metabolic Rate ◽  
Energy Cost ◽  
Sports Medicine ◽  
Resting Metabolic Rate ◽  
Prediction Equations ◽  
Overground Walking ◽  
All Speeds ◽  
Walking Energy Cost

Background: The purpose of this study was to investigate the accuracy of the published prediction equations for determining level overground walking energy cost in young adults. Methods: In total, 148 healthy young adults volunteered to participate in this study. Resting metabolic rate and energy expenditure variables at speeds of 4, 5, and 6 km/h were measured by indirect calorimetry, walking energy expenditure was estimated by 3 published equations. Results: The gross and net metabolic rate per mile of level overground walking increased with increased speed (all P < .01). Females were less economical than males. The present findings revealed that the American College of Sports Medicine and Pandolf et al equations significantly underestimated the energy cost of overground walking at all speeds (all P < .01) in young adults. The percentage mean bias for American College of Sports Medicine, Pandolf et al, and Weyand et al was 12.4%, 16.8%, 1.4% (4 km/h); 21.6%, 15.8%, 7.1% (5 km/h); and 27.6%, 12%, 6.6% (6 km/h). Bland–Altman plots and prediction error analysis showed that the Weyand et al was the most accurate in 3 existing equations. Conclusions: The Weyand et al equation appears to be the most suitable for the prediction of overground walking energy expenditure in young adults.

scholarly journals A VALIDATION OF 4 RESTING METABOLIC RATE PREDICTION EQUATIONS WHICH INCORPORATE DIFFERENT DODY SIZE INDICES

1992 ◽  
Vol 24 (Supplement) ◽  
pp. S10
Author(s):  
J. Morrill ◽  
J. Chronchio ◽  
S. Volpe-Snyder ◽  
P. S. Freedson ◽  
A. F. Maliszcwski
Keyword(s):  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Prediction Equations ◽  
Rate Prediction

scholarly journals Do we need race-specific resting metabolic rate prediction equations?

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
James Reneau ◽  
Brittaney Obi ◽  
Andrea Moosreiner ◽  
Srividya Kidambi
Keyword(s):  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Prediction Equations ◽  
Rate Prediction

scholarly journals Accuracy of resting metabolic rate prediction equations in female rugby players

2020 ◽  
Vol 79 (OCE2) ◽  
Author(s):  
Jack O'Neill ◽  
Ciara Walsh ◽  
Senan McNulty ◽  
Martha Corish ◽  
Hannah Gantly ◽  
...  
Keyword(s):  
Metabolic Rate ◽  
Muscle Damage ◽  
Resting Metabolic Rate ◽  
Low Energy ◽  
Strenuous Exercise ◽  
Energy Availability ◽  
Prediction Equations ◽  
Individual Level ◽  
Rugby Players ◽  
Low Energy Availability

AbstractThis study aimed to investigate (1) the accuracy of resting metabolic rate (RMR) prediction equations in female rugby players on a group and individual level; and (2) whether individual differences in the accuracy of prediction equations is associated with muscle damage or energy availability.RMR was assessed in 14 female provincial and club rugby players (Age: 20–34 years, FFM: 47–63 kg, FM: 15–37%) training a minimum of twice per week. Participants attended the laboratory following an overnight fast and having avoided strenuous exercise for 24 hours. RMR was measured over 30 minutes by indirect calorimetry, and taken as the 10 minutes with the lowest variation. Body composition was assessed by air displacement plethysmography, muscle damage indicated by creatine kinase (CK) and risk of low energy availability assessed by the Low Energy Availability in Females Questionnaire. Accuracy of RMR prediction equations relevant to the general population and athletes were assessed including the Harris Benedict (1919), Cunningham (1980) and Ten Haaf FFM (2014) based equations.Measured RMR was 1748 ± 146 kcal/day (range: 1474–2010 kcal/day). Predicted RMR determined by the Harris-Benedict equation (1601 ± 120 kcal/day) was significantly lower than measured RMR (p < 0.001), whereas predicted RMR using the Cunningham (1753 ± 146 kcal/day, p = 0.89) and the Ten Haaf (1781 ± 115 kcal/day, p = 0.33) equations did not differ from measured RMR. On an individual level, 50% (n = 7), 86% (n = 12) and 79% (n = 11) of participants fell within 10% of the measured RMR value when RMR was predicted by Harris-Benedict, Cunningham and Ten Haaf equations respectively. CK values were 182 ± 155U/L (range: 25–490U/L). When correlations of the whole group were studied, the difference between predicted and measured RMR was not associated with CK (r = 0.13). However, in the two individuals who fell outside the 10% range of that predicted by the Cunningham equation, one above and one below, CK values were 428U/L and 166U/L respectively. Muscle damage (as indicated by a high CK value) could therefore be one potential explanation for the higher measured RMR in the individual who was above the Cunningham predicted value.In this cohort of female rugby players, the Cunningham equation showed the best accuracy on a group and individual level, suggesting this may be the most suitable prediction equation for this population. Further studies with larger sample sizes and investigating underlying reasons for why RMR measured values may differ from predicted values are needed.

Accuracy of Resting Metabolic Rate Prediction Equations in Athletes

2018 ◽  
Vol 32 (7) ◽  
pp. 1875-1881 ◽  
Author(s):  
Andrew R. Jagim ◽  
Clayton L. Camic ◽  
Jacob Kisiolek ◽  
Joel Luedke ◽  
Jacob Erickson ◽  
...  
Keyword(s):  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Prediction Equations ◽  
Rate Prediction

scholarly journals Variants of the Cry 1 Gene May Influence the Effect of Fat Intake on Resting Metabolic Rate In Overweight and Obese Women: A Cross-sectional Study

2021 ◽  
Author(s):  
Atieh Mirzababaei ◽  
Elnaz Daneshzad ◽  
Farideh Shiraseb ◽  
Sanaz Pourreza ◽  
Leila Setayesh ◽  
...  
Keyword(s):  
Dietary Intake ◽  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Cross Sectional Study ◽  
Overweight And Obesity ◽  
Allele Carrier ◽  
Fat Intake ◽  
Obese Women ◽  
Sectional Study ◽  
Cross Sectional

Abstract Background: Previous studies have shown that the minor allele (C allele) for Cry 1 rs2287161, may be associated with increased risk of cardiovascular diseases (CVDs). Low resting metabolic rate (RMR) caused by the diet has been shown to have, potentially, unfavorable effects on obesity. This study sought to investigate the interactions between the Cry 1 Gene and fat intake on RMR in overweight and obese women.Methods: This comparative cross-sectional study was conducted on 377 Iranian women with overweight and obesity. A food frequency questionnaire (FFQ), with 147 items, was used to assess dietary intake. Individuals were categorized into two groups based on the rs2287161 genotype. Body composition, dietary intake, and RMR were assessed for all participants.Results: There was a significant difference between genotypes for FBS (P=0.04), fat free mass (FFM) (P=0.0009), RMR per FFM (P =0.05), RMR per body mass index (BMI) (P=0.02), and RMR deviation (P=0.01). Our findings also showed significant interactions between total fat and C allele carrier group on RMR per kg, RMR per body surface area (BSA), RMR per FFM, and RMR deviation (P for interaction <0.1), in addition to a significant interaction between CC+CG group genotype and PUFA intake on RMR per BMI (P for interaction =0.009) and RMR per kg (P for interaction=0.02) and RMR per BSA (P=0.07), compared to the GG group, after control for confounder factors.Conclusion: These results highlight that dietary compositions, gene variants, and their interaction, should be acutely considered in lower RMR.

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