title: Estimation of basal metabolic rate in Chinese: are the current prediction equations applicable?
abstract: Measurement of basal metabolic rate (BMR) is suggested as a tool to estimate energy requirements. Therefore, BMR prediction equations have been developed in multiple populations because indirect calorimetry is not always feasible. However, there is a paucity of data on BMR measured in overweight and obese adults living in Asia and equations developed for this group of interest. The aim of this study was to develop a new BMR prediction equation for Chinese adults applicable for a large BMI range and compare it with commonly used prediction equations.
  
  
  
  Subjects were 121 men and 111 women (age: 21-67 years, BMI: 16-41 kg/m(2)). Height, weight, and BMR were measured. Continuous open-circuit indirect calorimetry using a ventilated hood system for 30 min was used to measure BMR. A regression equation was derived using stepwise regression and accuracy was compared to 6 existing equations (Harris-Benedict, Henry, Liu, Yang, Owen and Mifflin). Additionally, the newly derived equation was cross-validated in a separate group of 70 Chinese subjects (26 men and 44 women, age: 21-69 years, BMI: 17-39 kg/m(2)).
  
  
  
  The equation developed from our data was: BMR (kJ/d) = 52.6 x weight (kg) + 828 x gender + 1960 (women = 0, men = 1; R(2) = 0.81). The accuracy rate (within 10 % accurate) was 78 % which compared well to Owen (70 %), Henry (67 %), Mifflin (67 %), Liu (58 %), Harris-Benedict (45 %) and Yang (37 %) for the whole range of BMI. For a BMI greater than 23, the Singapore equation reached an accuracy rate of 76 %. Cross-validation proved an accuracy rate of 80 %.
  
  
  
  To date, the newly developed Singapore equation is the most accurate BMR prediction equation in Chinese and is applicable for use in a large BMI range including those overweight and obese.
authors: Clinical Nutrition Research Centre (CNRC), Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Drive, Singapore, 117609, Singapore.
authors: Stefan G
authors: SG
authors: Camps
authors: Clinical Nutrition Research Centre (CNRC), Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Drive, Singapore, 117609, Singapore.
authors: Nan Xin
authors: NX
authors: Wang
authors: Clinical Nutrition Research Centre (CNRC), Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Drive, Singapore, 117609, Singapore.
authors: Wei Shuan Kimberly
authors: WS
authors: Tan
authors: Clinical Nutrition Research Centre (CNRC), Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Drive, Singapore, 117609, Singapore. jeya_henry@sics.a-star.edu.sg.|Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. jeya_henry@sics.a-star.edu.sg.
authors: C Jeyakumar
authors: CJ
authors: Henry
mesh_terms: D000328:Adult; D000368:Aged; D044466:Asian People; D001481:Basal Metabolism; D015992:Body Mass Index; D001835:Body Weight; D002153:Calorimetry, Indirect; D003430:Cross-Sectional Studies; D015444:Exercise; D005215:Fasting; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000378:metabolism; D050177:Overweight / Q000378:metabolism; D015203:Reproducibility of Results; D012846:Singapore; D055815:Young Adult