Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Fairoosa, Pathima, Lanerolle, Pulani, De Lanerolle-Dias, Maduka, Wickramasinghe, V. Pujitha, Waidyatilaka, Indu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7840262/
https://www.ncbi.nlm.nih.gov/pubmed/33542730
http://dx.doi.org/10.1155/2021/4170137
_version_ 1783643542108766208
author Fairoosa, Pathima
Lanerolle, Pulani
De Lanerolle-Dias, Maduka
Wickramasinghe, V. Pujitha
Waidyatilaka, Indu
author_facet Fairoosa, Pathima
Lanerolle, Pulani
De Lanerolle-Dias, Maduka
Wickramasinghe, V. Pujitha
Waidyatilaka, Indu
author_sort Fairoosa, Pathima
collection PubMed
description 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.
format Online
Article
Text
id pubmed-7840262
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-78402622021-02-03 Development of a New Equation for the Prediction of Resting Metabolic Rate in Sri Lankan Adults Fairoosa, Pathima Lanerolle, Pulani De Lanerolle-Dias, Maduka Wickramasinghe, V. Pujitha Waidyatilaka, Indu Int J Endocrinol Research Article 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. Hindawi 2021-01-20 /pmc/articles/PMC7840262/ /pubmed/33542730 http://dx.doi.org/10.1155/2021/4170137 Text en Copyright © 2021 Pathima Fairoosa et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Fairoosa, Pathima
Lanerolle, Pulani
De Lanerolle-Dias, Maduka
Wickramasinghe, V. Pujitha
Waidyatilaka, Indu
Development of a New Equation for the Prediction of Resting Metabolic Rate in Sri Lankan Adults
title Development of a New Equation for the Prediction of Resting Metabolic Rate in Sri Lankan Adults
title_full Development of a New Equation for the Prediction of Resting Metabolic Rate in Sri Lankan Adults
title_fullStr Development of a New Equation for the Prediction of Resting Metabolic Rate in Sri Lankan Adults
title_full_unstemmed Development of a New Equation for the Prediction of Resting Metabolic Rate in Sri Lankan Adults
title_short Development of a New Equation for the Prediction of Resting Metabolic Rate in Sri Lankan Adults
title_sort development of a new equation for the prediction of resting metabolic rate in sri lankan adults
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7840262/
https://www.ncbi.nlm.nih.gov/pubmed/33542730
http://dx.doi.org/10.1155/2021/4170137
work_keys_str_mv AT fairoosapathima developmentofanewequationforthepredictionofrestingmetabolicrateinsrilankanadults
AT lanerollepulani developmentofanewequationforthepredictionofrestingmetabolicrateinsrilankanadults
AT delanerollediasmaduka developmentofanewequationforthepredictionofrestingmetabolicrateinsrilankanadults
AT wickramasinghevpujitha developmentofanewequationforthepredictionofrestingmetabolicrateinsrilankanadults
AT waidyatilakaindu developmentofanewequationforthepredictionofrestingmetabolicrateinsrilankanadults