Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

Clinical Studies and Practice

Smaller size of high metabolic rate organs explains lower resting energy expenditure in Asian-Indian Than Chinese men

International Journal of Obesity volume 40, pages 633–638 (2016)Cite this article

Subjects

Abstract

Background:

In Singapore, the obesity prevalence is disproportionately higher in the Asian-Indians and Malays than the Chinese. Lower resting energy expenditure (REE) may be a contributory factor.

Objective:

We explored the association between ethnicity and REE in Chinese, Asian-Indian and Malay men living in Singapore and determined the influence of body composition, mass/volume of high metabolic rate organs, represented by brain volume and trunk fat-free mass (FFM), and physical activity on ethnic differences.

Design:

Two hundred and forty-four men from Singapore (n=100 Chinese, 70 Asian-Indians and 74 Malays), aged 21–40 years and body mass index of 18.5–30.0 kg m−2, were recruited in this cross-sectional study. REE was assessed by indirect calorimetry and body composition by dual-energy X-ray absorptiometry. Brain volume was measured by magnetic resonance imaging. Physical activity was assessed by the Singapore Prospective Study Program Physical Activity Questionnaire.

Results:

REE was significantly lower in Asian-Indians compared with that in Chinese after adjusting for body weight. FFM (total, trunk and limb) and total fat mass were important predictors of REE across all ethnic groups. Brain volume was positively associated with REE only in Malays. Moderate and vigorous physical activity was positively associated with REE only in Asian-Indians and Malays. The difference in REE between Asian-Indians and Chinese was attenuated but remained statistically significant after adjustment for total FFM (59±20 kcal per day), fat mass (67±20 kcal per day) and brain volume (54±22 kcal per day). The association between REE and ethnicity was no longer statistically significant after total FFM was replaced by trunk FFM (which includes heart, liver, kidney and spleen) but not when it was replaced by limb FFM (skeletal muscle).

Conclusions:

We have demonstrated a lower REE in Asian-Indians compared with Chinese who may contribute to the higher rates of obesity in the former. This difference could be accounted for by differences in metabolically active organs.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Similar content being viewed by others

References

  1. WHO. Report on a WHO Consultation on Obesity, 3–5 June 1997. World Health Organization: Geneva, Switzerland, 1998.

  2. Kelly T, Yang W, Chen CS, Reynolds K, He J . Global burden of obesity in 2005 and projections to 2030. Int J Obes (Lond) 2008; 32: 1431–1437.

    Article  CAS  Google Scholar 

  3. MOH. National Health Survey 2010, Singapore. Epidemiology and Disease Control Division, Ministry of Health, Singapore, 2010.

  4. Ong SK, Fong CW, Ma S, Lee J, Heng D, Deurenberg-Yap M et al. Longitudinal study of the socio-demographic determinants of changes in body weight and waist circumference in a multi-ethnic Asian population. Int J Obes (Lond) 2009; 33: 1299–1308.

    Article  CAS  Google Scholar 

  5. Galgani J, Ravussin E . Energy metabolism, fuel selection and body weight regulation. Int J Obes (Lond) 2008; 32 (Suppl 7): S109–S119.

    Article  CAS  Google Scholar 

  6. Report of the National Nutrition Survey. Singapore: Health Promotion Board, Division RaSP; 2004.

  7. Ravussin E, Lillioja S, Anderson TE, Christin L, Bogardus C . Determinants of 24-hour energy expenditure in man. Methods and results using a respiratory chamber. J Clin Invest 1986; 78: 1568–1578.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Tataranni PA, Harper IT, Snitker S, Del Parigi A, Vozarova B, Bunt J et al. Body weight gain in free-living Pima Indians: effect of energy intake vs expenditure. Int J Obes Relat Metab Disord 2003; 27: 1578–1583.

    Article  CAS  PubMed  Google Scholar 

  9. Ravussin E, Lillioja S, Knowler WC, Christin L, Freymond D, Abbott WG et al. Reduced rate of energy expenditure as a risk factor for body-weight gain. N Engl J Med 1988; 318: 467–472.

    Article  CAS  PubMed  Google Scholar 

  10. Foster GD, Wadden TA, Vogt RA . Resting energy expenditure in obese African American and Caucasian women. Obes Res 1997; 5: 1–8.

    Article  CAS  PubMed  Google Scholar 

  11. Albu J, Shur M, Curi M, Murphy L, Heymsfield SB, Pi-Sunyer FX . Resting metabolic rate in obese, premenopausal black women. Am J Clin Nutr 1997; 66: 531–538.

    Article  CAS  PubMed  Google Scholar 

  12. Weyer C, Snitker S, Bogardus C, Ravussin E . Energy metabolism in African Americans: potential risk factors for obesity. Am J Clin Nutr 1999; 70: 13–20.

    Article  CAS  PubMed  Google Scholar 

  13. Sun M, Gower BA, Bartolucci AA, Hunter GR, Figueroa-Colon R, Goran MI . A longitudinal study of resting energy expenditure relative to body composition during puberty in African American and white children. Am J Clin Nutr 2001; 73: 308–315.

    Article  CAS  PubMed  Google Scholar 

  14. Yanovski SZ, Reynolds JC, Boyle AJ, Yanovski JA . Resting metabolic rate in African-American and Caucasian girls. Obes Res 1997; 5: 321–325.

    Article  CAS  PubMed  Google Scholar 

  15. Soares MJ, Piers LS, O'Dea K, Shetty PS . No evidence for an ethnic influence on basal metabolism: an examination of data from India and Australia. Br J Nutr 1998; 79: 333–341.

    Article  CAS  PubMed  Google Scholar 

  16. Wong WW, Butte NF, Ellis KJ, Hergenroeder AC, Hill RB, Stuff JE et al. Pubertal African-American girls expend less energy at rest and during physical activity than Caucasian girls. J Clin Endocrinol Metab 1999; 84: 906–911.

    CAS  PubMed  Google Scholar 

  17. Khoo CM, Leow MK, Sadananthan SA, Lim R, Venkataraman K, Khoo EY et al. Body fat partitioning does not explain the interethnic variation in insulin sensitivity among Asian ethnicity: the Singapore adults metabolism study. Diabetes 2014; 63: 1093–1102.

    Article  CAS  PubMed  Google Scholar 

  18. Song T, Venkataraman K, Gluckman P, Seng CY, Meng KC, Khoo EY et al. Validation of prediction equations for resting energy expenditure in Singaporean Chinese men. Obes Res Clin Pract 2014; 8: e201–e298.

    Article  PubMed  Google Scholar 

  19. Baumgartner RN, Heymsfield SB, Lichtman S, Wang J, Pierson RN Jr . Body composition in elderly people: effect of criterion estimates on predictive equations. Am J Clin Nutr 1991; 53: 1345–1353.

    Article  CAS  PubMed  Google Scholar 

  20. Heymsfield SB, Smith R, Aulet M, Bensen B, Lichtman S, Wang J et al. Appendicular skeletal muscle mass: measurement by dual-photon absorptiometry. Am J Clin Nutr 1990; 52: 214–218.

    Article  CAS  PubMed  Google Scholar 

  21. Hunter GR, Weinsier RL, Darnell BE, Zuckerman PA, Goran MI . Racial differences in energy expenditure and aerobic fitness in premenopausal women. Am J Clin Nutr 2000; 71: 500–506.

    Article  CAS  PubMed  Google Scholar 

  22. Isaac V, Sim S, Zheng H, Zagorodnov V, Tai ES, Chee M . Adverse associations between visceral adiposity, brain structure, and cognitive performance in healthy elderly. Front Aging Neurosci 2011; 3: 12.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Buckner RL, Head D, Parker J, Fotenos AF, Marcus D, Morris JC et al. A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume. NeuroImage. 2004; 23: 724–738.

    Article  PubMed  Google Scholar 

  24. Chee MW, Zheng H, Goh JO, Park D, Sutton BP . Brain structure in young and old East Asians and Westerners: comparisons of structural volume and cortical thickness. J Cogn Neurosci 2011; 23: 1065–1079.

    Article  PubMed  Google Scholar 

  25. Dipietro L, Caspersen CJ, Ostfeld AM, Nadel ER . A survey for assessing physical activity among older adults. Med Sci Sports Exerc 1993; 25: 628–642.

    Article  CAS  PubMed  Google Scholar 

  26. Kriska AM, Knowler WC, LaPorte RE, Drash AL, Wing RR, Blair SN et al. Development of questionnaire to examine relationship of physical activity and diabetes in Pima Indians. Diabetes Care 1990; 13: 401–411.

    Article  CAS  PubMed  Google Scholar 

  27. Taylor HL, Jacobs DR Jr, Schucker B, Knudsen J, Leon AS, Debacker G . A questionnaire for the assessment of leisure time physical activities. J Chronic Dis 1978; 31: 741–755.

    Article  CAS  PubMed  Google Scholar 

  28. Nang EE, Gitau Ngunjiri SA, Wu Y, Salim A, Tai ES, Lee J et al. Validity of the International Physical Activity Questionnaire and the Singapore Prospective Study Program physical activity questionnaire in a multiethnic urban Asian population. BMC Med Res Methodol 2011; 11: 141.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Ainsworth BE, Haskell WL, Herrmann SD, Meckes N, Bassett DR Jr, Tudor-Locke C et al. 2011 Compendium of physical activities: a second update of codes and MET values. Med Sci Sports Exerc 2011; 43: 1575–1581.

    Article  PubMed  Google Scholar 

  30. Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc 2000; 32 (9 Suppl): S498–S504.

    Article  CAS  PubMed  Google Scholar 

  31. Physical Activity Guidelines Advisory Committee. Physical Activity Guidelines Advisory Committee Report, 2008. Department of Health and Human Services: Washington, DC, USA, 2008.

  32. IBM Corp IBM SPSS Statistics for Windows VA. IBM Corp: Armonk, NY, USA, 2011.

  33. Henry CJ, Rees DG . New predictive equations for the estimation of basal metabolic rate in tropical peoples. Eur J Clin Nutr 1991; 45: 177–185.

    CAS  PubMed  Google Scholar 

  34. Swinburn BA, Sacks G, Lo SK, Westerterp KR, Rush EC, Rosenbaum M et al. Estimating the changes in energy flux that characterize the rise in obesity prevalence. Am J Clin Nutr 2009; 89: 1723–1728.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Redman LM, Heilbronn LK, Martin CK, de Jonge L, Williamson DA, Delany JP et al. Metabolic and behavioral compensations in response to caloric restriction: implications for the maintenance of weight loss. PLoS One 2009; 4: e4377.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Joosen AMCP, Bakker AHF, Westerterp KR . Metabolic efficiency and energy expenditure during short-term overfeeding. Physiol Behav 2005; 85: 593–597.

    Article  CAS  PubMed  Google Scholar 

  37. Roberts SB, Young VR, Fuss P, Fiatarone MA, Richard B, Rasmussen H et al. Energy expenditure and subsequent nutrient intakes in overfed young men. Am J Physiol Regul Integr Compar Physiol 1990; 259: R461–R469.

    Article  CAS  Google Scholar 

  38. Siervo M, Frühbeck G, Dixon A, Goldberg GR, Coward WA, Murgatroyd PR et al. Efficiency of autoregulatory homeostatic responses to imposed caloric excess in lean men. Am J Physiol Endocrinol Metab 2008; 294: E416–E424.

    Article  CAS  PubMed  Google Scholar 

  39. Bingham SA, Goldberg GR, Coward WA, Prentice AM, Cummings JH . The effect of exercise and improved physical fitness on basal metabolic rate. Br J Nutr 1989; 61: 155–173.

    Article  CAS  PubMed  Google Scholar 

  40. Van Etten LMLA, Westerterp KR, Verstappen FTJ, Boon BJB, Saris WHM . Effect of an 18-wk weight-training program on energy expenditure and physical activity. J Appl Physiol 1997; 82: 298–304.

    Article  CAS  PubMed  Google Scholar 

  41. Westerterp KR, Plasqui G . Physically active lifestyle does not decrease the risk of fattening. PLoS One 2009; 4: e4745.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Johnstone AM, Murison SD, Duncan JS, Rance KA, Speakman JR . Factors influencing variation in basal metabolic rate include fat-free mass, fat mass, age, and circulating thyroxine but not sex, circulating leptin, or triiodothyronine. Am J Clin Nutr 2005; 82: 941–948.

    Article  CAS  PubMed  Google Scholar 

  43. Gallagher D, Allen A, Wang Z, Heymsfield SB, Krasnow N . Smaller organ tissue mass in the elderly fails to explain lower resting metabolic rate. Ann NY Acad Sci 2000; 904: 449–455.

    Article  CAS  PubMed  Google Scholar 

  44. Cunningham JJ . A reanalysis of the factors influencing basal metabolic rate in normal adults. Am J Clin Nutr 1980; 33: 2372–2374.

    Article  CAS  PubMed  Google Scholar 

  45. Ravussin E, Bogardus C . Relationship of genetics, age, and physical fitness to daily energy expenditure and fuel utilization. Am J Clin Nutr 1989; 49 (5 Suppl): 968–975.

    Article  CAS  PubMed  Google Scholar 

  46. Dore C, Hesp R, Wilkins D, Garrow JS . Prediction of energy requirements of obese patients after massive weight loss. Hum Nutr Clin Nutr 1982; 36C: 41–48.

    CAS  PubMed  Google Scholar 

  47. Deriaz O, Fournier G, Tremblay A, Despres JP, Bouchard C . Lean-body-mass composition and resting energy expenditure before and after long-term overfeeding. Am J Clin Nutr 1992; 56: 840–847.

    Article  CAS  PubMed  Google Scholar 

  48. Karhunen L, Franssila-Kallunki A, Rissanen A, Kervinen K, Kesaniemi YA, Uusitupa M . Determinants of resting energy expenditure in obese non-diabetic caucasian women. Int J Obes Relat Metab Disord 1997; 21: 197–202.

    Article  CAS  PubMed  Google Scholar 

  49. Javed F, He Q, Davidson LE, Thornton JC, Albu J, Boxt L et al. Brain and high metabolic rate organ mass: contributions to resting energy expenditure beyond fat-free mass. Am J Clin Nutr 2010; 91: 907–912.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Gallagher D, Albu J, He Q, Heshka S, Boxt L, Krasnow N et al. Small organs with a high metabolic rate explain lower resting energy expenditure in African American than in white adults. Am J Clin Nutr 2006; 83: 1062–1067.

    Article  CAS  PubMed  Google Scholar 

  51. Elia M . Organ and Tissue Contribution to Metabolic Rate. Raven Press: New York, NY, USA, 1992. contract no. 61–79.

    Google Scholar 

  52. Gilliat-Wimberly M, Manore MM, Woolf K, Swan PD, Carroll SS . Effects of habitual physical activity on the resting metabolic rates and body compositions of women aged 35 to 50 years. J Am Diet Assoc 2001; 101: 1181–1188.

    Article  CAS  PubMed  Google Scholar 

  53. Smith DA, Withers RT, Brinkman M, Tucker RC, Chatterton BE, Schultz CG et al. Resting metabolic rate, body composition and aerobic fitness comparisons between active and sedentary 54–71 year old males. Eur J Clin Nutr 1999; 53: 434–440.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The participation of the subjects in this study is highly appreciated. We thank Dr Paul Deurenberg for his technical assistance in the project. We also thank the Singapore Adult Metabolism Study (SAMS) team for their help in the measurements. The study was funded by a Translational and Clinical Research Flagship programme from the National Medical Research Council Singapore. Tai E Shyong and Khoo Chin Meng are also supported by Clinician Scientist Awards from the National Medical Research Council in Singapore. Peter Gluckman, Chong Yap Seng, Tai E Shyong, Lee Yung Seng, Melvin Khee-Shing Leow, Khoo Chin Meng and Khoo Yin Hao Eric were involved in project conception, development of overall research plan and study oversight. Michael Chee designed and implemented the protocols for assessing brain volume. Tammy Song aided the SAMS team in the collection of anthropometry and energy expenditure measurements and drafted the manuscript. Kavita Venkataraman and Tammy Song performed statistical analysis of data. Tai E Shyong and Khoo Yin Hao Eric had primary responsibility for final content.

Author information

Authors and Affiliations

  1. Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore

    L L T Song, C M Khoo, E S Tai & E Y H Khoo

  2. Saw Swee Hock School of Public Health, National University of Singapore, Singapore

    K Venkataraman & E S Tai

  3. Singapore Institute for Clinical Sciences, Singapore

    P Gluckman & Y S Lee

  4. Department of Obstetrics and Gynaecology, National University of Singapore, Singapore

    Y S Chong

  5. Center for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Graduate Medical School, Singapore

    M-W L Chee

  6. Duke-National University of Singapore Graduate Medical School, Singapore

    C M Khoo & E S Tai

  7. Division of Endocrinology, National University Health System, Singapore

    C M Khoo, E S Tai & E Y H Khoo

  8. Office of Clinical Sciences, Duke-National University of Singapore Graduate Medical School, Singapore

    M-KS Leow

  9. Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore

    Y S Lee

  10. Division of Paediatric Endocrinology and Diabetes, Khoo Teck Puat-National University Children’s Medical Institute, National University Health System, Singapore

    Y S Lee

Authors
  1. L L T Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. K Venkataraman
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. P Gluckman
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Y S Chong
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. M-W L Chee
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. C M Khoo
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. M-KS Leow
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Y S Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. E S Tai
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. E Y H Khoo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to E Y H Khoo.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Song, L., Venkataraman, K., Gluckman, P. et al. Smaller size of high metabolic rate organs explains lower resting energy expenditure in Asian-Indian Than Chinese men. Int J Obes 40, 633–638 (2016). https://doi.org/10.1038/ijo.2015.233

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ijo.2015.233

This article is cited by

Search

Advanced search

Quick links