Anthropometric Measurements for Prediction of Metabolic Risk among Chinese Adults in Pudong New Area of Shanghai

 

 Buy Article Permissions and Reprints

Abstract

Background: Numerous studies have demonstrated the ability of body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) to predict the risk of type 2 diabetes mellitus (T2DM) and cardiovascular diseases (CVD). This study aimed to evaluate the predictive value of these anthropometries for metabolic abnormalities and related diseases in Chinese adults.

Material & Methods: A cross-sectional study was conducted in 2 477 men and 3 107 women at 20–79 years old who were randomly selected from Pudong New Area of Shanghai, China, through a multistage sampling process. Anthropometric variables and blood pressure were measured according to a standardized protocol, and a fasting blood sample was collected from each subject for biochemical analysis.

Results: Prevalence of the metabolic syndrome was observed to increase with increasing BMI, WC, WHR and WHtR in both sexes. Participants with any metabolic abnormality had a higher body size than those without. The associations of anthropometries with each metabolic factor were significant and equal for BMI, WC, WHR and WHtR. Areas under the receiver operating characteristic curves (AUC) ranged from 0.59 to 0.72 across the 4 anthropometries in predicting individual and clusters of metabolic factors. However, none of the 4 anthropometries identified newly-diagnosed T2DM or hypertension with a high sensitivity or specificity.

Conclusion: Our findings suggest that the independent use of BMI, WC, WHR, or WHtR may not be an effective tool to predict metabolic factors and related chronic diseases in Chinese adults.

References

• 1 1999 World Health Organization – International Society of Hypertension Guidelines for the Management of Hypertension . Guidelines Subcommittee.  J Hypertens. 1999;  17 151-183
  Google Scholar
• 2 Ajlouni K, Khader YS, Batieha A. et al . An increase in prevalence of diabetes mellitus in Jordan over 10 years.  J Diabetes Complications. 2008;  22 317-324
  Google Scholar
• 3 Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation.  Diabet Med. 1998;  15 539-553
  Google Scholar
• 4 Alberti KG, Zimmet P, Shaw J. IDF Epidemiology Task Force Consensus Group . The metabolic syndrome – a new worldwide definition.  Lancet. 2005;  366 1059-1062
  Google Scholar
• 5 Alberti KG, Eckel RH, Grundy SM. et al . International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; International Association for the Study of Obesity .  Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention, National Heart, Lung, and Blood Institute, American Heart Association, World Heart Federation, International Atherosclerosis Society, and International Association for the Study of Obesity.  Circulation. 2009;  120 1640-1645
  Google Scholar
• 6 Ashwell M, Hsieh SD. Six reasons why the waist-to-height ratio is a rapid and effective global indicator for health risks of obesity and how its use could simplify the international public health message on obesity.  Int J Food Sci Nutr. 2005;  56 303-307
  Google Scholar
• 7 Bosy-Westphal A, Geisler C, Onur S. et al . Value of body fat mass vs.anthropometric obesity indices in the assessment of metabolic risk factors.  Int J Obes. 2006;  30 475-483
  Google Scholar
• 8 Can AS, Bersot TP, Gönen M. Anthropometric indices and their relationship with cardiometabolic risk factors in a sample of Turkish adults.  Public Health Nutr. 2009;  12 538-546
  Google Scholar
• 9 Cassani RS, Nobre F, Pazin-Filho A. et al . Relationship between blood pressure and anthropometry in a cohort of Brazilian men: a cross-sectional study.  Am J Hypertens. 2009;  22 980-984
  Google Scholar
• 10 Chan JC, Malik V, Jia W. et al . Diabetes in Asia: epidemiology, risk factors, and pathophysiology.  JAMA. 2009;  301 2129-2140
  Google Scholar
• 11 Churilla JR, Fitzhugh EC, Thompson DL. The Metabolic Syndrome: How Definition Impacts the Prevalence and Risk in U.S. Adults: 1999–2004 NHANES.  Metab Syndr Relat Disord. 2007;  5 331-342
  Google Scholar
• 12 Dalton M, Cameron AJ, Zimmet PZ. et al . AusDiab Steering Committee .  Waist circumference, waist-hip ratio and body mass index and their correlation with cardiovascular disease risk factors in Australian adults.  J Intern Med. 2003;  254 555-563
  Google Scholar
• 13 Denke MA, Pasternak RC. Defining and Treating the Metabolic Syndrome: A Primer from the Adult Treatment Panel III.  Curr Treat Options Cardiovasc Med. 2001;  3 251-253
  Google Scholar
• 14 Deurenberg P, Deurenberg-Yap M, Guricci S. Asians are different from Caucasians and from each other in their body mass index/body fat per cent relationship.  Obes Rev. 2002;  3 141-146
  Google Scholar
• 15 Dobbelsteyn C, Joffres M, MacLean D. et al . The Canadian Heart Health Surveys Research Group .  A comparative evaluation of waist circumference, waist-to hip ratio and body mass index as indicators of cardiovascular risk factors. The Canadian Heart Health Surveys.  Int J Obes. 2001;  25 652-661
  Google Scholar
• 16 Gu D, Reynolds K, Duan X. et al . InterASIA Collaborative Group .  Prevalence of diabetes and impaired fasting glucose in the Chinese adult population: International Collaborative Study of Cardiovascular Disease in Asia (InterASIA).  Diabetologia. 2003;  46 (9) 1190-1198
  Google Scholar
• 17 Ho SC, Chen YM, Woo JLF. et al . Association between simple anthropometric indices and cardiovascular risk factors.  Int J Obes. 2001;  25 1689-1697
  Google Scholar
• 18 Ho S, Lam T, Janus ED. for the Hong Kong Cardiovascular Risk Factor Prevalence Study Steering Committee . Waist to statue ratio is more strongly associated with cardiovascular risk factors than other simple anthropometric indices.  Ann Epidemiol. 2003;  13 683-691
  Google Scholar
• 19 Hsieh SD, Muto T. Metabolic syndrome in Japanese men and women with special reference to the anthropometric criteria for the assessment of obesity: Proposal to use the waist-to-height ratio.  Prev Med. 2006;  42 135-139
  Google Scholar
• 20 Hsieh SD, Yoshinaga H. Waist/height ratio as a simple and useful predictor of coronary heart disease risk factors in women.  Intern Med. 1995;  34 1147-1152
  Google Scholar
• 21 Hwu CM, Fuh JL, Hsiao CF. et al . Waist circumference predicts metabolic cardiovascular risk in postmenopausal Chinese women.  Menopause. 2003;  10 73-80
  Google Scholar
• 22 Jeong SK, Seo MW, Kim YH. et al . Does waist indicate dyslipidemia better than BMI in Korean adult population?.  J Korean Med Sci. 2005;  20 7-12
  Google Scholar
• 23 Kagawa M, Kerr D, Uchida H. et al . Differences in the relationship between BMI and percentage body fat between Japanese and Australian-Caucasian young men.  Br J Nutr. 2006;  95 1002-1007
  Google Scholar
• 24 Lear SA, Toma M, Birmingham CL. et al . Modification of the relationship between simple anthropometric indices and risk factors by ethnic background.  Metabolism. 2003;  52 1295-1301
  Google Scholar
• 25 Lee CMY, Huxley RR, Wildman RP. et al . Indices of abdominal obesity are better discriminators of cardiovascular risk factors than BMI: a meta-analysis.  J Clin Epidemiol. 2008;  61 646-653
  Google Scholar
• 26 Li R, Lu W, Jia J. et al . Relationships between indices of obesity and its cardiovascular comorbidities in a Chinese population.  Circ J. 2008;  72 (6) 973-978
  Google Scholar
• 27 Pan XR, Yang WY, Li GW. et al . Prevalence of diabetes and its risk factors in China, 1994 .  National Diabetes Prevention and Control Cooperative Group.  Diabetes Care. 1997;  20 1664-1669
  Google Scholar
• 28 Perkins NJ, Schisterman EF. The inconsistency of “optimal” cutpoints obtained using two criteria based on the receiver operating characteristic curve.  Am J Epidemiol. 2006;  163 670-675
  Google Scholar
• 29 Rush EC, Freitas I, Plank LD. Body size, body composition and fat distribution: comparative analysis of European, Maori, Pacific Island and Asian Indian adults.  Br J Nutr. 2009;  102 632-641
  Google Scholar
• 30 Ryan MC, Fenster Farin HM, Abbasi F. et al . Comparison of waist circumference versus body mass index in diagnosing metabolic syndrome and identifying apparently healthy subjects at increased risk of cardiovascular disease.  Am J Cardiol. 2008;  102 40-46
  Google Scholar
• 31 Schneider HJ, Glaesmer H, Klotsche J. et al . DETECT Study Group .  Accuracy of anthropometric indicators of obesity to predict cardiovascular risk.  J Clin Endocrinol Metab. 2007;  92 589-594
  Google Scholar
• 32 Shiwaku K, Anuurad E, Enkhmaa B. et al . Predictive values of anthropometric measurements for multiple metabolic disorders in Asian populations.  Diabetes Res Clin Pract. 2005;  69 52-62
  Google Scholar
• 33 Thomas MC, Hardoon SL, Papacosta AO. et al . Evidence of an accelerating increase in prevalence of diagnosed type 2 diabetes in British men, 1978–2005.  Diabet Med. 2009;  26 766-772
  Google Scholar
• 34 Wannamethee SG, Shaper AG, Morris RW. et al . Measures of adiposity in the identification of metabolic abnormalities in elderly men.  Am J Clin Nutr. 2005;  81 1313-1321
  Google Scholar
• 35 Wang F, Wu S, Song Y. et al . Waist circumference, body mass index and waist to hip ratio for prediction of the metabolic syndrome in Chinese.  Nutr Metab Cardiovasc Dis. 2009;  19 542-547
  Google Scholar
• 36 Xu WH, Ruan XN, Fu XJ. et al . Prevalence of the metabolic syndrome in Pudong New Area of Shanghai using three proposed definitions among Chinese adults.  BMC Public Health. 2010;  10 246
  Google Scholar
• 37 Yajnik CS, Yudkin JS. The Y-Y paradox.  Lancet. 2004;  363 163
  Google Scholar
• 38 Yang W, Lu J, Weng J. et al . China National Diabetes and Metabolic Disorders Study Group .  Prevalence of diabetes among men and women in China.  N Engl J Med. 2010;  362 1090-1101
  Google Scholar

Correspondence

W. H. Xu

Department of Epidemiology

School of Public Health

Fudan University

138 Yi Xue Yuan RD

200032 Shanghai

P. R. C

Phone: + 86/21/54237 679

Fax: + 86/21/54237 334

Email: wanghong.xu@fudan.edu.cn

X. N. Ruan

Department of Chronic Disease

Prevention

Pudong New Area Centers for

Disease Control and Prevention

3039 Zhang Yang Road

200136 Shanghai

P. R. C

Phone: + 86/21/5034 2541

Email: ruan_118@hotmail.com