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Lower BMI cut-off value to define obesity in Hong Kong Chinese: an analysis based on body fat assessment by bioelectrical impedance

Published online by Cambridge University Press:  09 March 2007

Gary T.C. Ko ,
Joyce Tang ,
Juliana C.N. Chan ,
Rita Sung ,
Morris M. F. Wu ,
Hendena P.S. Wai  and
Raymond Chen
Gary T.C. Ko*
Affiliation:
Department of Medicine, Alice Ho Miu Ling Nethersole Hospital, 11, Chuen On Road, Tai Po, Hong Kong
Joyce Tang
Affiliation:
United Christian Nethersole Community Health Service, Hong Kong
Juliana C.N. Chan
Affiliation:
Department of Medicine and Therapeutics, Prince of Wales Hospital, Chinese University of Hong Kong, Hong Kong
Rita Sung
Affiliation:
Department of Paediatrics, Prince of Wales Hospital, Chinese University of Hong Kong, Hong Kong
Morris M. F. Wu
Affiliation:
Pamela Youde Nethersole Eastern Hospital, Hong Kong
Hendena P.S. Wai
Affiliation:
Pamela Youde Nethersole Eastern Hospital, Hong Kong
Raymond Chen
Affiliation:
Department of Medicine, Alice Ho Miu Ling Nethersole Hospital, 11, Chuen On Road, Tai Po, Hong Kong
*
*Corresponding author: Gary T. C. Ko, fax (852) 2689-2785, email: [email protected]
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Abstract

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There is increasing evidence suggesting that the cut-off values for defining obesity used in the Western countries cannot be readily applied to Asians, who often have smaller body frames than Caucasians. We examined the BMI and body fat (BF) as measured by bioelectrical impedance in 5153 Hong Kong Chinese subjects. We aimed to assess the optimal BMI reflecting obesity as defined by abnormal BF in Hong Kong Chinese. Receiver operating characteristic curve (ROC) analysis was used to assess the optimal BMI predicting BF at different levels. The mean age and SD OF THE 5153 SUBJECTS (3734 WOMEN AND 1419 MEN) WAS 51.5 (sd 16.3) years (range: 18.0–89.5 years, median: 50.7 years). Age-adjusted partial correlation (r) between BMI and BF in women and men were 0.899 (P<0.001) and 0.818 (P<0.001) respectively. Using ROC analysis, the BMI corresponding to the conventional upper limit of normal BF was 22.5–23.1 kg/m2, and the BMI corresponding to the 90 percentiles of BF was 25.4–26.1 kg/m2. Despite similar body fat contents, the BMI cut-off value used to define obesity in Hong Kong Chinese should be lower as compared to Caucasians. We suggest a BMI of 23 kg/m2 and 26 kg/m2 as the cut-off values to define overweight and obesity respectively in Hong Kong Chinese.

Keywords

ObesityBMIBody fatChinese
Type
Research Article
Information
British Journal of Nutrition , Volume 85 , Issue 2 , February 2001 , pp. 239 - 242
Copyright
Copyright © The Nutrition Society 2001

References

Deurenberg, P & Yap, M (1999) The assessment of obesity: methods for measuring body fat and global prevalence of obesity. Baillière's Clinical Endocrinology and Metabolism 13, 1–11.Google ScholarPubMed
Deurenberg, P, Yap, M & van Staveren, WA (1998) Body mass index and percent body fat: a meta-analysis among different ethnic groups. International Journal of Obesity 22, 1164–1171.CrossRefGoogle ScholarPubMed
Harris, MI, Flegal, KM, Cowie, CC, Eberhardt, MS, Goldstein, DE, Little, RR, Wiedmeyer, HM & Byrd-Holt, DD (1998) Prevalence of diabetes, impaired fasting glucose, and impaired glucose tolerance in US adults Diabetes Care 21, 518–524.CrossRefGoogle Scholar
Higgins, M, Kannel, W, Garrison, R, Pinsky, J & Stokes, J (1988) Hazards of obesity–the Framingham experience Acta Medica Scandinavica Supplement 723, 23–36.Google ScholarPubMed
Hodge, AM & Zimmet, PZ (1994) The epidemiology of obesity Baillière' Clinical Endocrinology and Metabolism 8, 577–599.CrossRefGoogle ScholarPubMed
Jousilahti, P, Tuomilehto, J, Vartiainen, E, Pekkanen, J & Puska, P (1996) Body weight, cardiovascular risk factors, and coronary mortality. 15-year follow-up of middle-aged men and women in eastern Finland Circulation 93, 1372–1379.CrossRefGoogle ScholarPubMed
Ko, GTC, Chan, JCN, Woo, J, Lau, E, Yeung, VTF, Chow, CC, Wai, HPS, Li, JKY, So, WY & Cockram, CS(1997) Simple anthropometric indexes and cardiovascular risk factors in Chinese. International Journal of Obesity 21, 995–1001.CrossRefGoogle ScholarPubMed
Ko, GTC, Chan, JCN & Cockram, CS (1998) The association between dyslipidaemia and obesity in Chinese men after adjustment for insulin resistance Atherosclerosis 138, 153–161.CrossRefGoogle ScholarPubMed
Ko, GTC, Chan, JCN, Cockram, CS & Woo, J (1999) Prediction of hypertension, diabetes, dyslipidaemia or albuminuria using simple anthropometric indexes in Hong Kong Chinese. International Journal of Obesity 23, 1136–1142.CrossRefGoogle ScholarPubMed
Ko, GTC, Cockram, CS, Critchley, JA & Chan, JCN (1999) Obesity: definition, aetiology and complications. Medical Progress 26, 10–14.Google Scholar
Ko, GTC, Wu, MMF, Wai, HPS, Tang, J, Chan, CHS, Kan, ECY & Chen, R (1999) Rapid increase in the prevalence of undiagnosed diabetes and impaired fasting glucose in asymptomatic Hong Kong Chinese. Diabetes Care 22, 1751–1752.CrossRefGoogle ScholarPubMed
Kuczmarski, RJ, Flegal, KM, Campbell, SM & Johnson, CL (1994) Increasing prevalence of obesity among US adults. The National Health and Nutrition Examination Surveys, 1960 to 1991 JAMA 272, 205–211.CrossRefGoogle ScholarPubMed
Lean, MEJ, Han, TS & Morrison, CE (1995) Waist circumference as a measure for indicating need for weight management. British Medical Journal 311, 158–161.CrossRefGoogle ScholarPubMed
Lohman, TG, Houtkoper, L & Going, SB (1997) Body fat measurements goes high tech. Not all are created equal. ACSM's Health & Fitness Journal 1, 30–35.Google Scholar
Nunez, C, Gallagher, D, Russell-Aulet, M & Heymsfield, SB (1994) Impedance analysis of body composition: a new measurement approach. In Proceedings of the 7th International Congress on Obesity, pp. 498 [Landignon, N & Stock, MJ,editors]. Toronto, Ontario, Canada.Google Scholar
Sakamoto, Y, Miura, J, Yamaguchi, Y, Ohno, M & Ikeda, Y (1994) Usefulness of bioelectrical impedance analysis for measurement of body fat. In Proceedings of the 7th International Congress on Obesity, pp. 501 [N Landignon and MJ Stock, editors]. Toronto, Ontario, Canada.Google Scholar
Seidell, JC & Flegal, KM (1997) Assessing obesity: classification and epidemiology. British Medical Bulletin 53, 238–252.CrossRefGoogle ScholarPubMed
Seidell, JC, Verschuren, WM, van Leer, EM & Kromhout, D (1996) Overweight, underweight, and mortality. A prospective study of 48 287 men and women. Archive of Internal Medicine 156, 958–963.CrossRefGoogle Scholar
Siri, WE (1961) Body composition from fluid spaces and density: analysis of methods. In Techniques for Measuring Body Composition, 223–244. [J, Brozek and AHenschel, editors Henschel, editors]. Washington, DC: National Academy of Sciences.Google Scholar
Solomons, NW & Mazariegos, M (1995) Low-cost appropriate technologies for body composition assessment: a field researcher's view Asia Pacific Journal of Clinical Nutrition 4, 19–22.Google ScholarPubMed
Srinivasan, SR, Bao, W, Wattigney, WA & Berenson, GS (1996) Adolescent overweight is associated with adult overweight and related multiple cardiovascular risk factors: the Bogalusa Heart Study. Metabolism 45, 235–240.CrossRefGoogle ScholarPubMed
World Health Organisation (1995) Physical Status: The use and interpretation of anthropometry. Technical Report Series 854, Geneva.Google Scholar
World Health Organisation (1998) Obesity: Preventing and managing the global epidemic. Report on a WHO Consultation on Obesity, Geneva, 3–5 June 1997 WHO/NUT/NCD/98. 1, Geneva.Google Scholar
Yap, M, Schmidt, G, van Staveren, WA & Deurenberg, P (2000) The paradox of low body mass index and high body fat percentage among Chinese, Malays and Indians in Singapore International Journal of Obesity and Related Metabolic Disorders 24, 1011–1017.Google Scholar
Zimmet, P(1992) Challenges in diabetes epidemiology–from West to the rest. Diabetes Care 15, 232–252.CrossRefGoogle Scholar