Email Alert | RSS

Journal of Peking University (Health Sciences) ›› 2024, Vol. 56 ›› Issue (2): 247-252. doi: 10.19723/j.issn.1671-167X.2024.02.007

Previous Articles     Next Articles

Characteristics of resting energy expenditure and evaluation of prediction formulas in young men with different body mass indexes

Yifan WU,Yingxiang YU,Lan XIE,Zhida ZHANG,Cuiqing CHANG*()   

  1. Department of Sports Medicine, Peking University Third Hospital; Institute of Sports Medicine of Peking University; Beijing Key Laboratory of Sports Injuries; Beijing 100191, China
  • Received:2021-12-29 Online:2024-04-18 Published:2024-04-10
  • Contact: Cuiqing CHANG E-mail:changcuiqing@126.com
  • Supported by:
    the Key Technologies Research and Development Program(2019YFF0301700)

RICH HTML

 0   

PDF (PC)

60

Abstract:

Objective: To compare the resting energy expenditure (REE) characteristics among young men with different body mass indexes (BMI). Methods: Thirty young men [average age was (26.93±4.16) years] were enrolled in this study. They underwent resting metabolism tests in the Department of Sports Medicine of Peking University Third Hospital from December 2017 to June 2021. The resting metabolic rate (RMR) was measured by indirect calorimetry, the body composition was measured by bioresistance antibody component analyzer. The REE characteristics were analyzed, and 11 predictive equations were used to estimate RMR and compared with the measured value. The differences were analyzed by paired t-test and intra-class correlation coefficient (ICC). Results: The RMR of the overall 30 young men was (1 960.17±463.11) kcal/d (1 kcal=4.186 8 kJ). Including (1 744.33±249.62) kcal/d in those with normal BMI, which was significantly lower than that in those who were overweight or obese [(2 104.06± 520.32) kcal/d, P < 0.01], but the weight-corrected RMR in those with normal BMI was significantly higher than that in those who were overweight or obese [(24.02±2.61) kcal/(kg·d) vs. (19.98±4.38) kcal/(kg·d), P < 0.01]. The RMR was significantly and positively correlated with body weight, adiposity, lean body mass, body surface area, and extracellular fluid in the subjects with diffe-rent BMI (all P < 0.05). The predicted values of the 11 prediction equations were not in good agreement with the measured values (all ICC < 0.75), with relatively high agreement between the predicted and measured values of the World Health Organization (WHO) equation in overweight obese young men (ICC=0.547, P < 0.01). Conclusion: There were significant differences in RMR among young men with different BMI, and the RMR after weight correction should be considered for those who were overweight or obese. The consistency between the predicted values of different prediction equations and the actual measured values of RMR was relatively poor, and it is recommended to accurately measure RMR by indirect calorimetry. For overweight or obese young men, the WHO prediction equation can be considered to calculate RMR, but it is necessary to establish an RMR prediction equation applicable to different BMI populations.

Key words: Resting metabolic rate, Body mass index, Young adult, Male, Overweight or obese

CLC Number: 

  • R151.44

Table 1

Predictive equations of RMR of young men"

Equation source Age/years Equation/(kcal/d) Data source
Harris, et al[10] All 66+13.7×weight (kg)+5×height (cm)-6.8×age (years) 136 men, American
Schofield[11] 18-30 15.057×weight (kg)+692.2 Meta analysis of Western countries data
WHO[12] 18-30 15.3×weight (kg)+679 Meta analysis of Western countries data
Mifflin, et al[13] NA 9.99×weight (kg)+6.25×height (cm)-4.92×age (years)+166×gender (male, 1; female, 0)-161 498 healthy subjects, American
Henry[14] 18-30 14.4×weight (kg)+3.13×height (cm)+113 Include 10 552 subjects, meta analysis
Cunningham[15] All 21.6×FFM (kg)+501.6 Meta analysis
de Lorenzo, et al[16] 18-59 [53.284×weight (kg)+20.957×height (cm)-23.859×age (years)+487]×0.239 320 healthy subjects, Italian
Owen, et al[17] 18-82 290+22.3×FFM (kg) 60 men (include obese subjects), American
Liu, et al[18] NA 13.88×weight (kg)+4.16×height (cm)-3.43×age (years)-112.40×gender (male=0; female=1)+54.34 223 healthy subjects, Chinese
Camps, et al[19] All [52.6×weight (kg)+2 788]×0.239 232 subjects (BMI: 16-41 kg/m2), Singaporean Chinese subjects
Xue, et al[20] NA 13.9×weight (kg)+247-5.39×age (years)+855 315 healthy subjects, Chinese

Table 2

Subjects characteristics"

Indicator Normal BMI (n=12), $\bar x \pm s$ Overweight or obese (n=18), $\bar x \pm s$ P
Age/years 26.50±2.32 27.22±5.08 0.649
Height/cm 175.66±3.56 174.79±6.39 0.674
Weight/kg 72.52±4.66 107.68±27.30 < 0.001
BMI/(kg/m2) 23.51±1.43 35.19±8.44 < 0.001
Fat mass/kg 12.70±1.91 39.92±21.24 < 0.001
Body fat rate/% 17.44±1.84 35.13±9.18 < 0.001
FFM/kg 59.83±3.25 67.76±8.09 0.003
TBW/kg 41.70±2.98 44.94±6.60 0.123
Body water/% 57.51±2.23 43.06±7.27 < 0.001
Intracellular fluid/kg 26.32±2.21 27.09±4.37 0.579
Extracellular fluid/kg 15.38±0.82 17.85±2.50 0.001
BMR/(kcal/d) 1 705.42±98.02 2 022.39±296.13 < 0.001
mRMR/(kcal/d) 1 744.33±249.62 2 104.06±520.32 < 0.001
Weight-corrected RMR/[kcal/(kg·d)] 24.02±2.61 19.98±4.38 < 0.001
FFM-corrected RMR/[kcal/(kg·d)] 29.11±3.45 30.96±6.24 0.359

Table 3

Resting metabolism of subjects and the consumption of nutrients"

Indicator Normal BMI (n=12), $\bar x \pm s$ Overweight or obese (n=18), $\bar x \pm s$ P
EE/(kcal/d) 1 744.33±249.62 2 104.06±520.32 < 0.001
Carbohydrate
  g 196.10±136.52 157.17±56.20 0.416
  kcal/d 819.80±571.04 657.00±234.69 0.416
  % 37.50±15.69 38.00±13.76 0.937
Fat
  g 85.10±32.48 82.17±24.87 0.813
  kcal/d 804.50±307.59 777.75±234.04 0.819
  % 41.60±12.89 44.17±11.33 0.629
Protein
  g 92.20±26.91 71.83±25.98 0.088
  kcal/d 397.80±115.99 309.75±112.72 0.088
  % 21.00±8.61 17.83±6.19 0.346
npRER 0.84±0.05 0.84±0.04 0.917
UN/(g/d) 14.73±4.29 11.47±4.18 0.089

Table 4

Correlation analysis between mRMR and body composition (r value)"

Indicator Normal BMI (n=12) Overweight or obese (n=18)
Height 0.231 0.140
Weight 0.670* 0.560*
Body fat 0.617* 0.503*
FFM 0.600* 0.569*
BSA 0.630* 0.554*
Body water 0.523 0.529
Intracellular fluid 0.480 0.438
Extracellular fluid 0.603* 0.631**

Table 5

Comparison of the subject's mRMR and the predicted value of the equations"

Predictive equationNormal BMI (n=12) Overweight or obese (n=18)
Value/(kcal/d), $\bar x \pm s$ P Value/(kcal/d), $\bar x \pm s$ P
mRMR 1 744.33±249.62 2 104.06±520.32
BMR 1 705.42±98.02 0.529 2 022.39±296.13 0.433
Harris, et al[10] 1 762.84±71.30 0.771 2 236.99±385.60 0.230
Schofield[11] 1 784.21±70.20 0.523 2 313.50±411.09 0.063
WHO[12] 1 788.63±71.33 0.477 2 326.47±417.73 0.051
Mifflin, et al[13] 1 697.01±58.47 0.476 2 039.23±286.89 0.542
Henry[14] 1 707.17±72.44 0.551 2 210.67±399.88 0.324
Cunningham[15] 1 793.91±70.24 0.441 1 965.18±174.68 0.203
de Lorenzo, et al[16] 1 768.70±66.98 0.704 2 207.92±358.02 0.337
Owen, et al[17] 1 624.19±72.52 0.078 1 801.01±180.34 0.010
Liu, et al[18] 1 700.83±70.55 0.493 2 182.68±387.24 0.466
Camps, et al[19] 1 578.11±58.61** 0.021 2 020.04±343.24 0.423
Xue, et al[20] 1 967.26±61.84** 0.004 2 451.99±378.67** 0.004

Table 6

The consistency between the predicted value and the measured value of RMR"

Predictive equationNormal BMI (n=12) Overweight or obese (n=18)
ICC F P ICC F P
BMR 0.402 2.346 0.086 0.482 2.859 0.018
Harris, et al[10] 0.313 1.912 0.149 0.511 3.092 0.013
Schofield[11] 0.349 2.074 0.121 0.545 3.397 0.008
WHO[12] 0.354 2.097 0.118 0.547 3.416 0.008
Mifflin, et al[13] 0.250 1.666 0.205 0.448 2.624 0.027
Henry[14] 0.352 2.084 0.119 0.539 3.339 0.009
Cunningham[15] 0.313 1.911 0.149 0.343 2.046 0.075
de Lorenzo, et al[16] 0.298 1.849 0.161 0.501 3.005 0.015
Owen, et al[17] 0.322 1.948 0.142 0.352 2.087 0.070
Liu, et al[18] 0.329 1.981 0.136 0.523 3.197 0.011
Camps, et al[19] 0.298 1.850 0.161 0.515 3.125 0.012
Xue, et al[20] 0.299 1.853 0.160 0.517 3.139 0.012
1 Speakman JR , Selman C .Physical activity and resting metabolic rate[J].Proc Nutr Soc,2003,62(3):621-634.
doi: 10.1079/PNS2003282
2 中国营养学会.中国居民膳食营养素参考摄入量(2013版)[M].北京: 科学出版社,2014:83.
3 Mtaweh H , Tuira L , Floh AA , et al.Indirect calorimetry: History, technology, and application[J].Front Pediatr,2018,6,257.
doi: 10.3389/fped.2018.00257
4 McMurray RG , Soares J , Caspersen CJ , et al.Examining variations of resting metabolic rate of adults: A public health perspective[J].Med Sci Sports Exerc,2014,46(7):1352-1358.
doi: 10.1249/MSS.0000000000000232
5 Ocagli H , Lanera C , Azzolina D , et al.Resting energy expenditure in the elderly: Systematic review and comparison of equations in an experimental population[J].Nutrients,2021,13(2):458.
doi: 10.3390/nu13020458
6 中国医疗保健国际交流促进会营养与代谢管理分会, 中国营养学会临床营养分会, 中华医学会糖尿病学分会, 等.中国超重/肥胖医学营养治疗指南(2021)[J].中国医学前沿杂志: 电子版,2021,13(11):1-55.
7 赵松山, 刘友梅, 姚家邦, 等.中国成年男子体表面积的测量[J].营养学报,1984,6(2):87-95.
8 Compher C , Frankenfield D , Keim N , et al.Best practice methods to apply to measurement of resting metabolic rate in adults: A systematic review[J].J Am Diet Assoc,2006,106(6):881-903.
doi: 10.1016/j.jada.2006.02.009
9 Weir JB .New methods for calculating metabolic rate with special reference to protein metabolism[J].J Physiol,1949,109(1/2):1-9.
10 Harris JA , Benedict FG .A biometric study of human basal meta-bolism[J].Proc Natl Acad Sci USA,1918,4(12):370-373.
doi: 10.1073/pnas.4.12.370
11 Schofield WN .Predicting basal metabolic rate, new standards and review of previous work[J].Hum Nutr Clin Nutr,1985,39(Suppl 1):5-41.
12 Energy and protein requirements .Report of a joint FAO/WHO/UNU expert consultation[J].World Health Organ Tech Rep Ser,1985,724,1-206.
13 Mifflin MD , St Jeor ST , Hill LA , et al.A new predictive equation for resting energy expenditure in healthy individuals[J].Am J Clin Nutr,1990,51(2):241-247.
doi: 10.1093/ajcn/51.2.241
14 Henry CJ .Basal metabolic rate studies in humans: measurement and development of new equations[J].Public Health Nutr,2005,8(7A):1133-1152.
doi: 10.1079/PHN2005801
15 Cunningham JJ .A reanalysis of the factors influencing basal metabolic rate in normal adults[J].Am J Clin Nutr,1980,33(11):2372-2374.
doi: 10.1093/ajcn/33.11.2372
16 de Lorenzo A , Tagliabue A , Andreoli A , et al.Measured and predicted resting metabolic rate in Italian males and females, aged 18-59 y[J].Eur J Clin Nutr,2001,55(3):208-214.
doi: 10.1038/sj.ejcn.1601149
17 Owen OE , Holup JL , D'Alessio DA , et al.A reappraisal of the caloric requirements of men[J].Am J Clin Nutr,1987,46(6):875-885.
doi: 10.1093/ajcn/46.6.875
18 Liu HY , Lu YF , Chen WJ .Predictive equations for basal metabolic rate in Chinese adults: A cross-validation study[J].J Am Diet Assoc,1995,95(12):1403-1408.
doi: 10.1016/S0002-8223(95)00369-X
19 Camps SG , Wang NX , Tan WS , et al.Estimation of basal metabolic rate in Chinese: Are the current prediction equations applicable?[J].Nutr J,2016,15(1):79.
20 Xue J , Li S , Zhang Y , et al.Accuracy of predictive resting-metabolic-rate equations in Chinese mainland adults[J].Int J Environ Res Public Health,2019,16(15):2747.
doi: 10.3390/ijerph16152747
21 Mao Q , Wu JH , Huang CY , et al.Basal Energy Expenditure of Chinese healthy adults: Comparison of measured and predicted values[J].Biomed Environ Sci,2020,33(8):566-572.
22 刘燕萍, 陈伟, 毛德倩, 等.间接测热法测定北京成年居民基础代谢率及与身体成分的相关性[J].协和医学杂志,2013,4(1):11-14.
23 张莹, 吴景欢, 洪平, 等.北京市超重和肥胖成人基础代谢率的研究[J].卫生研究,2016,45(5):739-742.
24 中华人民共和国中央人民政府. 国务院新闻办就《中国居民营养与慢性病状况报告(2020年)》有关情况举行发布会[EB/OL]. (2020-12-24)[2021-12-22]. http://www.gov.cn/xinwen/2020-12/24/content_5572983.htm.
25 许晓丽, 李淑娟, 卓勤, 等.2010—2012年中国不同工作强度在职人员能量和宏量营养素摄入状况[J].卫生研究,2021,50(3):415-420.
26 谢海雁, 于康, 安奇志, 等.代谢车间接测热法、公式推测法及人体成分测定法用于测定静息能量消耗的比较[J].中华临床营养杂志,2018,26(2):90-93.
27 汪锡, 王远, 许杨, 等.非肥胖健康成人静息代谢率预测公式准确性研究[J].北京生物医学工程,2017,36(6):607-613.
[1] Zi-kai WANG,Jia-li MO,Meng ZHANG,Ji-ping LIAO. Epidemiology and hospitalization costs analysis of female inpatients with acute exacerbation of chronic obstructive pulmonary disease in Beijing from 2013 to 2020 [J]. Journal of Peking University (Health Sciences), 2023, 55(6): 1074-1081.
[2] Jing-feng ZHANG,Yin-ji JIN,Hui WEI,Zhong-qiang YAO,Jin-xia ZHAO. Correlation analysis between body mass index and clinical characteristics of rheumatoid arthritis [J]. Journal of Peking University (Health Sciences), 2023, 55(6): 993-999.
[3] Zi-xuan XUE,Shi-ying TANG,Min QIU,Cheng LIU,Xiao-jun TIAN,Min LU,Jing-han DONG,Lu-lin MA,Shu-dong ZHANG. Clinicopathologic features and prognosis of young renal tumors with tumor thrombus [J]. Journal of Peking University (Health Sciences), 2023, 55(5): 802-811.
[4] Xue-zhao JI,Shan LIU,Wan-zhou WANG,Ye-tong ZHAO,Lu-yi LI,Wen-lou ZHANG,Guo-feng SHEN,Fu-rong DENG,Xin-biao GUO. Associations between indoor volatile organic compounds and nocturnal heart rate variability of young female adults: A panel study [J]. Journal of Peking University (Health Sciences), 2023, 55(3): 488-494.
[5] Hao LIN,Jing-hua LI,Xiao YANG,Xiao-ting CHEN,Yu-hui SHI,Chun CHANG,Yuan-tao HAO,Wang-nan CAO. Discrepancy between behavioral-indicated and perceived candidacy for HIV pre-exposure prophylaxis among men who have sex with men in Chengdu, China [J]. Journal of Peking University (Health Sciences), 2023, 55(3): 511-520.
[6] Xi-ya SUN,Yi-lu CHEN,Lin ZENG,Li-ying YAN,Jie QIAO,Rong LI,Xu ZHI. Correlation analysis of vitamin D level and anti-Müllerian hormone in infertile female and the role in predicting pregnancy outcome [J]. Journal of Peking University (Health Sciences), 2023, 55(1): 167-173.
[7] Yang-yang CHEN,Yu-bo ZHOU,Jing YANG,Yu-meng HUA,Peng-bo YUAN,Ai-ping LIU,Yuan WEI. Effects of gestational weight on the association between serum high sensitivity C reaction protein and gestational diabetes mellitus among twin gestations: A cohort study [J]. Journal of Peking University (Health Sciences), 2022, 54(3): 427-433.
[8] DU Qiang,HONG Kai,PAN Bo-chen. Comparison of two methods for detection of Chlamydia trachomatis and Ureaplasma urealyticum in male reproductive tract [J]. Journal of Peking University (Health Sciences), 2021, 53(4): 785-788.
[9] SHI Xin-ran,AN Mei-jing,CHEN Tian-jiao,Ma jun. Mediating effect of milk intake between family socioeconomic status and body mass index of children and adolescents [J]. Journal of Peking University (Health Sciences), 2021, 53(2): 308-313.
[10] Tao WANG,Ke-xin XU,Wei-yu ZHANG,Hao HU,Xiao-wei ZHANG,Huan-rui WANG,Xian-hui LIU,Jing-wen CHEN,Xiao-peng ZHANG. Urodynamic classification of male patients with symptoms of overactive bladder and the outcome classification [J]. Journal of Peking University(Health Sciences), 2019, 51(6): 1048-1051.
[11] Wei-yu ZHANG,Qiu-xiang XIA,Hao HU,Jing-wen CHEN,Yi-ran SUN,Ke-xin XU,Xiao-peng ZHANG. Analysis of urodynamic study of female outpatients with lower urinary tract symptoms and follow-up of the patients with detrusor underactive [J]. Journal of Peking University(Health Sciences), 2019, 51(5): 856-862.
[12] Xin-yan CHE,Shi-liang WU,Yu-ke CHEN,Yan-bo HUANG,Yang YANG. A survey of risk factors and quality of life in female medical staff with urinary incontinence [J]. Journal of Peking University(Health Sciences), 2019, 51(4): 706-710.
[13] DAI Xiao-wei, XU Ying, ZHENG Lian-wen, LI Ling-yun, LI Dan-dan1 TAN Xin, GAO Fei, WANG Yan, WU Gui-jie. Analysis of chromosome in 1 324 patients with oligozoospermia or azoosperm [J]. Journal of Peking University(Health Sciences), 2018, 50(5): 774-777.
[14] WU Gui-jie, MA Shuai, ZHENG Lian-wen, XU Ying, MENG Fan-he, DAI Xiao-wei. A complex chromosome translocation with male infertility of karyotype analysis and literature review [J]. Journal of Peking University(Health Sciences), 2018, 50(4): 729-731.
[15] WANG Dan-dan, GAN Ye-hua, MA Xu-chen, MENG Juan-hong. Association between ADAMTS14 gene polymorphism and the temporomandibular joint osteoarthritis in Chinese Han females [J]. Journal of Peking University(Health Sciences), 2018, 50(2): 279-283.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] . [J]. Journal of Peking University(Health Sciences), 2009, 41(2): 135 -140 .
[2] . [J]. Journal of Peking University(Health Sciences), 2009, 41(2): 158 -161 .
[3] . [J]. Journal of Peking University(Health Sciences), 2009, 41(2): 217 -220 .
[4] . [J]. Journal of Peking University(Health Sciences), 2009, 41(1): 52 -55 .
[5] . [J]. Journal of Peking University(Health Sciences), 2009, 41(1): 109 -111 .
[6] . [J]. Journal of Peking University(Health Sciences), 2009, 41(3): 297 -301 .
[7] . [J]. Journal of Peking University(Health Sciences), 2009, 41(4): 459 -462 .
[8] . [J]. Journal of Peking University(Health Sciences), 2009, 41(5): 505 -515 .
[9] . [J]. Journal of Peking University(Health Sciences), 2009, 41(5): 599 -601 .
[10] . [J]. Journal of Peking University(Health Sciences), 2009, 41(5): 516 -520 .
Copyright © Journal of Peking University (Health Sciences), All Rights Reserved.
Powered by Beijing Magtech Co. Ltd