Abstract
Aim
This study aimed to examine the influence of central obesity on the clustering patterns of adverse levels of metabolic syndrome (MetS) risk variables among adults with normal weight in a low-income rural Chinese cohort.
Subject and methods
The study cohort consisted of 1,821 adults, aged 35–74 years. Central obesity was defined as a waist to height ratio ≥ 0.5 among adults with normal weight (body mass index = 18.5–24.9). MetS risk variables included blood pressure (BP), fasting triglycerides and glucose, and high-density lipoprotein cholesterol (HDL-C).
Results
Centrally obese subjects had significantly higher levels of all the MetS risk variables than those without central obesity. The central obesity group had a higher prevalence of MetS (clustering of three or more variables) than the control group (13.9 vs 5.8%, p < 0.001). Importantly, the cluster of high triglycerides, low HDL-C, and high BP showed the greatest difference (p < 0.001) between the two groups. In multivariable logistic regression analyses, adjusting for age, sex, smoking, and alcohol drinking, the centrally obese group vs the control group was 2.25 times more likely to have MetS (p < 0.01). Among the four types of three variable clusterings, central obesity was significantly associated with the cluster of high triglycerides, low HDL-C, and high BP (odds ratio = 3.51, p < 0.01).
Conclusion
These findings indicate that the central obesity detected by the waist to height ratio plays a pivotal role in the clustering of MetS risk variables among normal-weight Chinese adults, suggesting the importance of prevention of MetS by reducing central obesity in a population with a lower prevalence of obesity.
Similar content being viewed by others
References
Chang CJ, Wu CH, Chang CS et al (2003) Low body mass index but high percent body fat in Taiwanese subjects: implications of obesity cutoffs. Int J Obes Relat Metab Disord 27(2):253–259
Chen W, Bao W, Begum S et al (2000) Age-related patterns of the clustering of cardiovascular risk variables of syndrome X from childhood to young adulthood in a population made up of black and white subjects: the Bogalusa Heart Study. Diabetes 49(6):1042–1048
Cheng TO (2004) The current state of cardiology in China. Int J Cardiol 96(3):425–439
Conus F, Allison DB, Rabasa-Lhoret R et al (2004) Metabolic and behavioral characteristics of metabolically obese but normal-weight women. J Clin Endocrinol Metab 89(10):5013–5020
DeFronzo RA, Ferrannini E (1991) Insulin resistance. A multifaceted syndrome responsible for NIDDM, obesity, hypertension, dyslipidemia, and atherosclerotic cardiovascular disease. Diabetes Care 14(3):173–194
Després JP, Lemieux I, Bergeron J et al (2008) Abdominal obesity and the metabolic syndrome: contribution to global cardiometabolic risk. Arterioscler Thromb Vasc Biol 28(6):1039–1049
Deurenberg P, Yap M, van Staveren WA (1998) Body mass index and percent body fat: a meta analysis among different ethnic groups. Int J Obes Relat Metab Disord 22(12):1164–1171
Deurenberg P, Deurenberg-Yap M, Guricci S (2002) Asians are different from Caucasians and from each other in their body mass index/body fat per cent relationship. Obes Rev 3(3):141–146
Deurenberg-Yap M, Chew SK, Deurenberg P (2002) Elevated body fat percentage and cardiovascular risks at low body mass index levels among Singaporean Chinese, Malays and Indians. Obes Rev 3(3):209–215
Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (2001) Executive summary of the third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 285(19):2486–2497
Flegal KM, Carroll MD, Ogden CL et al (2002) Prevalence and trends in obesity among US adults, 1999–2000. JAMA 288(14):1723–1727
Ford ES, Giles WH, Dietz WH (2002) Prevalence of the metabolic syndrome among US adults: findings from the third National Health and Nutrition Examination Survey. JAMA 287(3):356–359
Fujimoto WY, Bergstrom RW, Boyko EJ et al (1995) Susceptibility to development of central adiposity among populations. Obes Res 3(Suppl 2):179S–186S
Gurrici S, Hartriyanti Y, Hautvast JG et al (1998) Relationship between body fat and body mass index: differences between Indonesians and Dutch Caucasians. Eur J Clin Nutr 52(11):779–783
Hsieh SD, Muto T (2005) The superiority of waist-to-height ratio as an anthropometric index to evaluate clustering of coronary risk factors among non-obese men and women. Prev Med 40(2):216–220
Hsieh SD, Yoshinaga H (1995a) Waist/height ratio as a simple and useful predictor of coronary heart disease risk factors in women. Intern Med 34(12):1147–1152
Hsieh SD, Yoshinaga H (1995b) Abdominal fat distribution and coronary heart disease risk factors in men-waist/height ratio as a simple and useful predictor. Int J Obes Relat Metab Disord 19(8):585–589
Hsieh SD, Yoshinaga H, Muto T (2003) Waist-to-height ratio, a simple and practical index for assessing central fat distribution and metabolic risk in Japanese men and women. Int J Obes Relat Metab Disord 27(5):610–616
Karelis AD, St-Pierre DH, Conus F et al (2004) Metabolic and body composition factors in subgroups of obesity: what do we know? J Clin Endocrinol Metab 89(6):2569–2575
Kershaw EE, Flier JS (2004) Adipose tissue as an endocrine organ. J Clin Endocrinol Metab 89(6):2548–2556
Ko GT, Chan JC, Woo J et al (1997) Simple anthropometric indexes and cardiovascular risk factors in Chinese. Int J Obes Relat Metab Disord 21(11):995–1001
Lakka HM, Laaksonen DE, Lakka TA et al (2002) The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men. JAMA 288(21):2709–2716
Low S, Chin MC, Ma S et al (2009) Rationale for redefining obesity in Asians. Ann Acad Med Singapore 38(1):66–69
Misra A, Wasir JS, Vikram NK (2005) Waist circumference criteria for the diagnosis of abdominal obesity are not applicable uniformly to all populations and ethnic groups. Nutrition 21(9):969–976
Molarius A, Seidell JC, Sans S et al (1999) Varying sensitivity of waist action levels to identify subjects with overweight or obesity in 19 populations of the WHO MONICA Project. J Clin Epidemiol 52(12):1213–1224
Reaven GM (1997) Banting Lecture 1988. Role of insulin resistance in human disease. Nutrition 13(1):65
Reynolds K, Gu D, Whelton PK et al (2007) Prevalence and risk factors of overweight and obesity in China. Obesity (Silver Spring) 15(1):10–18
Ruderman NB, Berchtold P, Schneider S (1982) Obesity-associated disorders in normal-weight individuals: some speculations. Int J Obes 6(Suppl 1):151–157
Ruderman N, Chisholm D, Pi-Sunyer X et al (1998) The metabolically obese, normal-weight individual revisited. Diabetes 47(5):699–713
Seidell JC, Cigolini M, Charzewska J et al (1990) Fat distribution in European women: a comparison of anthropometric measurements in relation to cardiovascular risk factors. Int J Epidemiol 19(2):303–308
Seidell JC, Cigolini M, Charzewska J et al (1992) Fat distribution in European men: a comparison of anthropometric measurements in relation to cardiovascular risk factors. Int J Obes Relat Metab Disord 16(1):17–22
Srinivasan SR, Myers L, Berenson GS (2002) Predictability of childhood adiposity and insulin for developing insulin resistance syndrome (syndrome X) in young adulthood: the Bogalusa Heart Study. Diabetes 51(1):204–209
Srinivasan SR, Wang R, Chen W et al (2009) Utility of waist-to-height ratio in detecting central obesity and related adverse cardiovascular risk profile among normal weight younger adults (from the Bogalusa Heart Study). Am J Cardiol 104(5):721–724
Wang F, Zhao JB, Zhao YJ et al (2008) A cross-sectional study of impaired fasting glycaemia and diabetes mellitus in rural residents of Lanxi, Heilongjiang. Zhonghua Liu Xing Bing Xue Za Zhi 29(6):530–534
Wen CP, David Cheng TY, Tsai SP et al (2009) Are Asians at greater mortality risks for being overweight than Caucasians? Redefining obesity for Asians. Public Health Nutr 12(4):497–506
WHO Expert Consultation (2004) Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 363(9403):157–163
Wildman RP, Gu D, Reynolds K et al (2005) Are waist circumference and body mass index independently associated with cardiovascular disease risk in Chinese adults? Am J Clin Nutr 82(6):1195–1202
Acknowledgements
This study was supported by the grant D200623 from Heilongjiang Province Natural Science Foundation. This research is a joint effort of investigators and staff members from the Department of Cardiology of the First Affiliated Hospital and Department of Epidemiology, School of Public Health, Harbin Medical University, and Health Bureau and Pingshan Town Hospital, Lanxi. Their contributions are gratefully acknowledged. We especially thank the study participants.
Conflict of interest
The authors declare that they have no conflict of interest.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Fu, S., Xiang, Z., Zhao, Y. et al. Influence of central obesity on clustering of metabolic syndrome risk variables among normal-weight adults in a low-income rural Chinese population. J Public Health 19, 223–229 (2011). https://doi.org/10.1007/s10389-010-0378-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10389-010-0378-y