TY - JOUR
T1 - Accuracy of resting metabolic rate prediction in overweight and obese Australian adults
AU - Wright, Thomas Graeme
AU - Dawson, Brian
AU - Jalleh, G.
AU - Guelfi, Kym J.
PY - 2016/9/1
Y1 - 2016/9/1
N2 - © 2015 Asia Oceania Association for the Study of ObesityObjectives Predictive resting metabolic rate (RMR) equations in Australian populations are at least 10 years old, focused on males and do not commonly use overweight and obese weight categorisation. The aim of this study was to measure RMR via indirect calorimetry in overweight and obese Australian adults to develop population specific predictive equations and compare with other well-known international equations (Mifflin–St. Jeor, Owen and WHO/FAO/UNU). Methods Retrospective data from 278 participants (154 males, 124 females: 37% overweight, 63% obese) who had attended a weight management clinic were used to develop predictive RMR equations. These were then validated against another sample (from the same clinic) of 297 participants (150 males, 147 females: 47% overweight, 53% obese), and their accuracy compared with known standard equations. Results For the prediction sample, weight, BMI, resting VO2 and measured RMR were significantly greater in the obese than overweight. Using the validation sample, the predictive equations met a ±10% of measured RMR criterion 42% (females), 41% (total sample) and 40% (males) of the time. Prediction accuracy was not improved by using specific overweight and obese weight category equations, or by applying the known standard equations from the literature. Conclusions In our sample of overweight and obese adults, RMR prediction to within ±10% of the measured value was only accurate ~40% of the time, regardless of gender and weight classification. In clinical weight management settings direct measures of RMR should be made wherever possible.
AB - © 2015 Asia Oceania Association for the Study of ObesityObjectives Predictive resting metabolic rate (RMR) equations in Australian populations are at least 10 years old, focused on males and do not commonly use overweight and obese weight categorisation. The aim of this study was to measure RMR via indirect calorimetry in overweight and obese Australian adults to develop population specific predictive equations and compare with other well-known international equations (Mifflin–St. Jeor, Owen and WHO/FAO/UNU). Methods Retrospective data from 278 participants (154 males, 124 females: 37% overweight, 63% obese) who had attended a weight management clinic were used to develop predictive RMR equations. These were then validated against another sample (from the same clinic) of 297 participants (150 males, 147 females: 47% overweight, 53% obese), and their accuracy compared with known standard equations. Results For the prediction sample, weight, BMI, resting VO2 and measured RMR were significantly greater in the obese than overweight. Using the validation sample, the predictive equations met a ±10% of measured RMR criterion 42% (females), 41% (total sample) and 40% (males) of the time. Prediction accuracy was not improved by using specific overweight and obese weight category equations, or by applying the known standard equations from the literature. Conclusions In our sample of overweight and obese adults, RMR prediction to within ±10% of the measured value was only accurate ~40% of the time, regardless of gender and weight classification. In clinical weight management settings direct measures of RMR should be made wherever possible.
U2 - 10.1016/j.orcp.2015.07.008
DO - 10.1016/j.orcp.2015.07.008
M3 - Article
C2 - 26277698
SN - 1871-403X
VL - 10
SP - S74-S83
JO - Obesity Research and Clinical Practice
JF - Obesity Research and Clinical Practice
IS - 1
ER -