Value of waist circumference, body mass index and hyperinsulinaemia in identifying metabolic syndrome

Abstract

To investigate the significance of waist circumference (WC), body mass index (BMI) and hyperinsulinaemia A (HIns) in evaluating metabolic syndrome (MS). Clinical data from middle-aged and senile individuals (middle-senile group) who received glucose tolerance test after diabetes mellitus screening and a group of subjects who received annual oral glucose tolerance test (OGTT) for diabetes mellitus screening (adult group) were collected. Data were collected by use of special messengers, input into a computer data base and analyzed using SAS 5.0 software by expert staff. Abnormal WC and BMI were determined according to International Diabetes Federation (IDF) and Chinese Diabetes Society (CDS) criteria. HIns was ascertained if fasting insulin (FIns) ≥ 15 mU/L, and/or 2-hour insulin after a glucose challenge was (2hPIns) ≥ 80 mU/L. Abnormalities in WC, BMI and HIns were all found to be risk factors for abnormal glucose metabolism, hypertension and dyslipidemia. In the middle-senile group, the abnormality rate of WC and HIns as well as the overall insulin level were significantly higher than those in the adult group. The abnormality rate of BMI was higher in the adult group, and HIns was mostly seen in impaired glucose test (IGT) and normal glucose test (NGT). The concordance rate of WC and BMI diagnostic criteria for evaluating obesity in the middle-senile and adult groups were 77.5% and 74.3%, respectively. When only the WC criterion was used for evaluating the existence of insulin resistance, there was a 28.2% missed diagnosis rate for MS patients. WC, BMI and HIns were all risk factors for abnormal glucose metabolism, hypertension and dyslipidemia. There was differing prevalence in the different populations. The combination of WC, BMI and HIns might be more helpful in identifying MS at early stage.

References

1. Reaven G M . Role of insulin resistance in human disease. Diabetes, 1988, 37: 1595–1599. doi:10.2337/diabetes.37.12.1595 2. Rennert N J, Charney P . Preventing cardiovasculardisease in diabetes and glucose intolerance: evidence and implicationsfor care. Prim-Care, 2003, 30(3): 569–574 3. Mainous A G 3rd, Everett C J, Liszka H, King D E, Egan B M . Prehypertension and mortality in a nationallyrepresentative cohort. Am J Cardiol, 2004, 94(12):1496–1500. doi:10.1016/j.amjcard.2004.08.026 4. Csernus K, Lanyi E, Erhardt E, Molnar D . Effect of childhoodobesity and obesity-related cardiovascular risk factors on glomerularand tubular protein excretion. Eur J Pediatr, 2005, 164(1): 44–49. doi:10.1007/s00431-004-1546-2 5. International Diabetes Federation: The IDF consensusworldwide definition of the metabolic syndrome. 6. World Health Organization. . Definition,diagnosis and classification of diabetes mellitus and its complications:report of a WHO consultation. Part 1. Diagnosis and classificationof diabetes mellitus. Geneva: World health Organization, 1999 7. Co-operation groupof diabetes branch of Chinese Medical Association for study of metabolicsyndrome. . Suggestion about metabolic syndrome by diabetes branchof Chinese Medical Association. ZhongguoTangniaobing Zazhi, 2004, 12(3): 156–159 (in Chinese) 8. Hirschler V, Roque M I, Calcagno M L, Gonzalez C, Aranda C . Maternal waist circumferenceand the prediction of children's metabolic syndrome. Arch Pediatr Adolesc Med, 2007, 161(12): 1205–1210. doi:10.1001/archpedi.161.12.1205 9. Hirschler V, Maccallini G, Calcagno M, Aranda C, Jadzinsky M . Waist circumference identifies primaryschool children with metabolic syndrome abnormalities. Diabetes Technol Ther, 2007, 9(2): 149–157. doi:10.1089/dia.2006.0017 10. Qiu D Y, Hu Y, Lu J, Cai Y Y, Wu L, Zhu J Y . Body massindex, waist-to-hip ratio and waist circumference are indicators forimpaired glucose tolerance/type 2 diabetes mellitus in the elderly. Di'er Junyi Daxue Xuebao, 2006, 27(1): 58–61 (in Chinese) 11. Xie X D, Zhuang X Y . Detection of metabolic syndromein general health examination. Riben YixueJinzhan, 2005, 26(5): 218–221 (in Chinese) 12. Arai H, Yamamoto A, Matsuzawa Y, Saito Y, Yamada N, Oikawa S, Mabuchi H, Teramoto T, Sasaki J, Nakaya N, Itakura H, Ishikawa Y, Ouchi Y, Horibe H, Shirahashi N, Kita T . Prevalenceof Metabolic Syndrome in the General Japanese Population in 2000. J Atheroscler Thromb, 2006, 13(4): 202–208 13. Cheng Y, Pan C Y, Tian H, Lu J M . A pilot evaluationof the diagnostic value of body mass index in elderly men with metabolicsyndrome. Zhonghua Nei Ke Za Zhi, 2006, 45(2): 100–103 (in Chinese) 14. Tian H, Yao C . Investigation on the prevalenceof obesity in adult of Beijing city. ZhonghuaLiu Xing Bing Xue Za Zhi, 1993, 14(S): 307–309 (in Chinese) 15. Mei B Y, Chen J Y, Yang W S, Chi Y C, Liou Y J, Lin C C, Wang Y C, Lin C Y, Su T P, Chou P . Adiponectin as a potential biomarkerfor the metabolic syndrome in Chinese patients taking clozapine forschizophrenia. J Clin Psychiatry, 2007, 68(12): 1834–1839