Introduction: Metabolic syndrome (MetS) had been known as clustering of risk factors for cardiovascular disease and diabetes. Over the years, clinical criteria had been revised to highlight importance of various risk factors in defining MetS. Studies had reported different clustering of factors based on different population characteristics.
Objective: Our study aimed to identify the clustering factors among our Malaysian population based on sexes and 4 major ethnic groups namely Malay, Chinese, Indian and other minor ethnic
Methods: A national cross sectional study was done covering both Peninsular and East Malaysia. Subjects’ sociodemographic, body mass index (BMI), waist, hip and neck circumference, blood pressure, fasting triglycerides (TG) and HDL-cholesterol and glucose, urine microalbumin and serum insulin were taken. Principal component factor analysis with Varimax rotation was done to identify the clustering based on sex and ethnic groups.
Results: One thousand two hundred and sixty eight male and 2355 female subjects were recruited. Majority of subjects were Malays (63.0%) followed by Chinese (13.3%), Indian (7.4%) and other ethnic groups (13.8%) which followed the population composition in Malaysia. Four factors were identified for both men and women. The factors were anthropometry, glycemia, blood pressure and dyslipidemia given the cumulative percent of variance of 69.4 and 65.9 respectively. There are 4 factors identified for Malay, Chinese and Aborigines but 5 factors for Indian ethnic groups given cumulative percent of variance explained ranged from 65.1 to 77.7.
Discussion and Conclusion: BMI, neck circumference, blood pressure, Fasting TG and HDL had a high factor loading in both sexes suggesting that for field screening, diagnostic criteria would be adequate criteria. These factors also showed a similar pattern of loading by different ethnic groups. In conclusion, in Malaysian population, at least one measurement from each components namely anthropometric, blood pressure, glycemia and dyslipidemia is adequate to diagnose MetS.