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The BMI–adiposity conundrum in South Asian populations: need for further research

Published online by Cambridge University Press:  04 April 2019

Nitin Kapoor Open the ORCID record for Nitin Kapoor [Opens in a new window] ,
John Furler ,
Thomas V. Paul ,
Nihal Thomas  and
Brian Oldenburg
Nitin Kapoor*
Affiliation:
Department of Endocrinology, Diabetes and Metabolism, Christian Medical College & Hospital, Vellore, Tamil Nadu, India Melbourne School of Population and Global Health, Faculty of Medicine, Dentistry and Health Science, University of Melbourne, Australia
John Furler
Affiliation:
Department of General Practice, Faculty of Medicine, Dentistry and Health Science, University of Melbourne, Australia
Thomas V. Paul
Affiliation:
Department of Endocrinology, Diabetes and Metabolism, Christian Medical College & Hospital, Vellore, Tamil Nadu, India
Nihal Thomas
Affiliation:
Department of Endocrinology, Diabetes and Metabolism, Christian Medical College & Hospital, Vellore, Tamil Nadu, India
Brian Oldenburg
Affiliation:
Melbourne School of Population and Global Health, Faculty of Medicine, Dentistry and Health Science, University of Melbourne, Australia
*
*Corresponding author. Email: nitin.kapoor@cmcvellore.ac.in
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Abstract

High body fat in apparently lean individuals is a commonly described phenotype in individuals of Asian descent, but very limited consolidated scientific literature is available on this topic. This phenotype is known as ‘normal-weight obesity’ and may explain the large disparity between the prevalence of obesity (as measured by BMI) and diabetes that occurs in these individuals. Routine use of obesity indicators that best predict body fat content would help to identify these individuals in clinical practice. In this debate, we would like to highlight that even though fat and BMI have a good correlation, as suggested by Kryst et al. (2019), clinicians, public health researchers and policymakers should consider the use of these indicators in conjunction with each other rather than individually. Future research is needed on pathogenic mechanisms, diagnostic modalities and therapeutic options in these individuals which will help to further characterize and manage these patients appropriately.

Keywords

Normal-weight obesityBody mass indexBody composition
Type
Debate
Information
Journal of Biosocial Science , Volume 51 , Issue 4 , July 2019 , pp. 619 - 621
Copyright
© Cambridge University Press, 2019 

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References

Anand, SS, Tarnopolsky, MA, Rashid, S, Schulze, KM, Desai, D, Mente, A et al. (2011) Adipocyte hypertrophy, fatty liver and metabolic risk factors in South Asians: the Molecular Study of Health and Risk in Ethnic Groups (mol-SHARE). PLoS One 6(7), e22112–e22112.Google Scholar
Franco, LP, Morais, CC and Cominetti, C (2016) Normal-weight obesity syndrome: diagnosis, prevalence, and clinical implications. Nutrition Review 74(9), 558–570.Google Scholar
Jia, A, Xu, S, Xing, Y, Zhang, W, Yu, X, Zhao, Y, Ming, J and Ji, Q (2018) Prevalence and cardiometabolic risks of normal weight obesity in Chinese population: a nationwide study. Nutrition, Metabolism & Cardiovascular Diseases, doi: 10.1016/j.numecd.2018.06.015.Google Scholar
Kapoor, N, Chapla, A, Furler, J, Paul, TV, Harrap, S, Oldenburg, B and Thomas, N (2019) Genetics of obesity in consanguineous populations – a road map to provide novel insights in the molecular basis and management of obesity. EBioMedicine, doi: https://doi.org/10.1016/j.ebiom.2019.01.004.Google Scholar
Kim, MK, Han, K, Kwon, HS, Song, KH, Yim, HW, Lee, WC and Park, YM (2014) Normal weight obesity in Korean adults. Clinical Endocrinology 80(2), 214–220.Google Scholar
Kryst, L, Zeglen, M, Wronka, I, Woronkowicz, A, Bilinska-Pawlak, I, Das, R et al. (2019) Anthropometric variations in different BMI and adiposity levels among children, adolescents and young adults in Kolkata, India. Journal of Biosocial Science, doi: 10.1017/s0021932018000354.Google Scholar
Kurpad, AV, Varadharajan, KS and Aeberli, I (2011) The thin-fat phenotype and global metabolic disease risk. Current Opinion in Clinical Nutrition & Metabolic Care 14(6), 542–547.Google Scholar
Thomas, N, Grunnet, L, Poulsen, P, Christopher, S, Spurgeon, R, Inbakumari, M et al. (2012) Born with low birth weight in rural Southern India: what are the metabolic consequences 20 years later? European Journal of Endocrinology 166(4), 647–655.Google Scholar
Yajnik, CS and Yudkin, JS (2004) The Y–Y paradox. The Lancet 363(9403), 163.Google Scholar
Yoon, KH, Lee, JH, Kim, JW, Cho, JH, Choi, YH, Ko, SH et al. (2006) Epidemic obesity and type 2 diabetes in Asia. The Lancet 368(9548), 1681–1688.Google Scholar