Diabetes Care, Vol 19, Issue 9 953-959, Copyright © 1996 by American Diabetes Association

ARTICLES

The metabolic syndrome in Hong Kong Chinese. The interrelationships among its components analyzed by structural equation modeling

JC Chan, JC Cheung, EM Lau, J Wooa, AY Chan, R Swaminathan and CS Cockrama
Department of Clinical Pharmacology, Chinese University of Hong Kong, Hong Kong.

OBJECTIVE: To examine the pattern of the metabolic syndrome in Chinese and the causal relationships among its components, including aging, obesity, hyperglycemia, hypertension, hypertriglyceridemia, and hyperinsulinemia in these subjects. RESEARCH DESIGN AND METHODS: Based on a 75-g oral glucose tolerance test, the World Health Organization criteria were used for the diagnosis of glucose intolerance in a population-based study involving 1.513 Chinese subjects in two work sites. Demographic data including age, family history of diabetes, BMI, waist-to-hip ratio (WHR), and sitting blood pressure (BP) were documented. Fasting plasma glucose, triglyceride (TG) and insulin concentrations, and spot urinary albumin concentration (Ualb) were also measured. Structural equation modeling incorporating factor analysis and path analysis was performed to examine the causal relationships among these variables and their interactions. RESULTS: Subjects who were treated with antidiabetic and/or antihypertensive drugs or who had a plasma creatinine level > or = 150 mumol/l were excluded (n = 52). The prevalence of diabetes and impaired glucose tolerance (IGT) were 3.9% (n = 34) and 7.2% (n = 63) in men (n = 881) and 3.1% (n = 18) and 6.7% (n = 39) in women (n = 580), respectively. In both groups, glucose intolerance was associated with increasing age, higher BMI, WHR, BP, Ualb, serum TG, and insulin levels as well as higher prevalence rates of positive family history of diabetes. Structural equation modeling showed that age was a significant determinant for both BMI and WHR. Age and obesity accounted for most of the variance of BP, Ualb, plasma glucose, insulin and TG levels either directly or indirectly. Plasma glucose was determined by a positive family history of diabetes, age, and BMI while TG was dependent on BMI and WHR. Serum insulin was mainly determined by a positive family history of diabetes, obesity, plasma glucose, and TG levels. Apart from age and obesity, BP was also determined by serum insulin, both of which had causal effects on Ualb. CONCLUSIONS: This model emphasizes the centrality of aging and obesity as well as a positive family history of diabetes as major determinants of the components of the metabolic syndrome. These components in turn had causal effects upon one another. Apart from a familial tendency, a central neurohormonal mechanism may account for these abnormalities mediated primarily through obesity and in close association with aging.
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