Predicting basal metabolic rates in Malaysian adult elite athletes

Introduction This study aimed to measure the basal metabolic rate (BMR) of elite athletes and develop a genderspecific predictive equation to estimate their energy requirements. Method s 92 men and 33 women (aged 18-31 years) from 15 sports, who had been training six hours daily for at least one yea...

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Published in:Singapore Medical Journal
Main Author: Wong J.E.; Poh B.K.; Nik Shanita S.; Izham M.M.; Chan K.Q.; De Tai M.; Ng W.W.; Ismail M.N.
Format: Article
Language:English
Published: 2012
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870500180&partnerID=40&md5=77a1e716783126753a040dd8a6fbd027
id 2-s2.0-84870500180
spelling 2-s2.0-84870500180
Wong J.E.; Poh B.K.; Nik Shanita S.; Izham M.M.; Chan K.Q.; De Tai M.; Ng W.W.; Ismail M.N.
Predicting basal metabolic rates in Malaysian adult elite athletes
2012
Singapore Medical Journal
53
11

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870500180&partnerID=40&md5=77a1e716783126753a040dd8a6fbd027
Introduction This study aimed to measure the basal metabolic rate (BMR) of elite athletes and develop a genderspecific predictive equation to estimate their energy requirements. Method s 92 men and 33 women (aged 18-31 years) from 15 sports, who had been training six hours daily for at least one year, were included in the study. Body composition was measured using the bioimpedance technique, and BMR by indirect calorimetry. The differences between measured and estimated BMR using various predictive equations were calculated. The novel equation derived from stepwise multiple regression was evaluated using Bland and Altman analysis. Results The predictive equations of Cunningham and the Food and Agriculture Organization/World Health Organization/United Nations University either over- or underestimated the measured BMR by up to ± 6%, while the equations of Ismail et al, developed from the local non-athletic population, underestimated the measured BMR by 14%. The novel predictive equation for the BMR of athletes was BMR (kcal/day) = 669 + 13 (weight in kg) + 192 (gender: 1 for men and 0 for women) (R2 0.548; standard error of estimates 163 kcal). Predicted BMRs of elite athletes by this equation were within 1.2% ± 9.5% of the measured BMR values. Conclusion The novel predictive equation presented in this study can be used to calculate BMR for adult Malaysian elite athletes. Further studies may be required to validate its predictive capabilities for other sports, nationalities and age groups.

375675
English
Article

author Wong J.E.; Poh B.K.; Nik Shanita S.; Izham M.M.; Chan K.Q.; De Tai M.; Ng W.W.; Ismail M.N.
spellingShingle Wong J.E.; Poh B.K.; Nik Shanita S.; Izham M.M.; Chan K.Q.; De Tai M.; Ng W.W.; Ismail M.N.
Predicting basal metabolic rates in Malaysian adult elite athletes
author_facet Wong J.E.; Poh B.K.; Nik Shanita S.; Izham M.M.; Chan K.Q.; De Tai M.; Ng W.W.; Ismail M.N.
author_sort Wong J.E.; Poh B.K.; Nik Shanita S.; Izham M.M.; Chan K.Q.; De Tai M.; Ng W.W.; Ismail M.N.
title Predicting basal metabolic rates in Malaysian adult elite athletes
title_short Predicting basal metabolic rates in Malaysian adult elite athletes
title_full Predicting basal metabolic rates in Malaysian adult elite athletes
title_fullStr Predicting basal metabolic rates in Malaysian adult elite athletes
title_full_unstemmed Predicting basal metabolic rates in Malaysian adult elite athletes
title_sort Predicting basal metabolic rates in Malaysian adult elite athletes
publishDate 2012
container_title Singapore Medical Journal
container_volume 53
container_issue 11
doi_str_mv
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870500180&partnerID=40&md5=77a1e716783126753a040dd8a6fbd027
description Introduction This study aimed to measure the basal metabolic rate (BMR) of elite athletes and develop a genderspecific predictive equation to estimate their energy requirements. Method s 92 men and 33 women (aged 18-31 years) from 15 sports, who had been training six hours daily for at least one year, were included in the study. Body composition was measured using the bioimpedance technique, and BMR by indirect calorimetry. The differences between measured and estimated BMR using various predictive equations were calculated. The novel equation derived from stepwise multiple regression was evaluated using Bland and Altman analysis. Results The predictive equations of Cunningham and the Food and Agriculture Organization/World Health Organization/United Nations University either over- or underestimated the measured BMR by up to ± 6%, while the equations of Ismail et al, developed from the local non-athletic population, underestimated the measured BMR by 14%. The novel predictive equation for the BMR of athletes was BMR (kcal/day) = 669 + 13 (weight in kg) + 192 (gender: 1 for men and 0 for women) (R2 0.548; standard error of estimates 163 kcal). Predicted BMRs of elite athletes by this equation were within 1.2% ± 9.5% of the measured BMR values. Conclusion The novel predictive equation presented in this study can be used to calculate BMR for adult Malaysian elite athletes. Further studies may be required to validate its predictive capabilities for other sports, nationalities and age groups.
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