Prevalence and Related Factors of Metabolic Syndrome in Beijing, China (Year 2017)

• Main Authors: Aijuan Ma, Kai Fang, Jing Dong, Zhong Dong
• Format: Article
• Language: English
• Published: Karger Publishers 2020-11-01
• Series: Obesity Facts
• Subjects: metabolic syndrome; obesity; risk factors; waist circumference; beijing
• Online Access: https://www.karger.com/Article/FullText/508842

Objective: Metabolic syndrome (MetS) is one of the major public health problems worldwide. The aim of this study was to investigate the prevalence and associated risk factors of MetS in Beijing to formulate targeted policies. Methods: Data from the 2017 Beijing Chronic Disease and Risk Factors Surveillance were used in this study, in which multistage stratified cluster sampling was adopted to collect a representative sample of 12,597 Beijing residents aged from 18 to 79 years. According to the definition of the International Diabetes Federation, the weighted prevalence of MetS and clustering of MetS components were estimated. The Rao-Scott adjusted χ2 test was used to test differences in MetS and components rates, and complex sampling unconditional logistic regression was used to explore influencing factors of MetS. Results: The prevalence of MetS was 25.59% (95% CI 23.77–27.41), and the proportion of men and women was 30.53% (95% CI 28.32–32.75) and 20.44% (95% CI 18.29–22.58), respectively. The proportion of central obesity, high fasting plasma glucose, high triglyceride, low high-density lipoprotein cholesterol, and high blood pressure (BP) was 42.02, 27.96, 32.87, 27.25, and 43.06%, respectively. A total of 29.60% (95% CI 27.55–31.74) participants presented at least three components of MetS. The results from complex sampling unconditional logistic regression revealed that the risk factors for having MetS included being 45–59 years old, being 60–79 years old, being male, living in a rural area, education with junior middle school level, education with primary school or below level, harmful use of alcohol, inappropriate sleep time, and having an unhealthy waist-to-height ratio (WHtR); the OR values were 1.55 (95% CI 1.32–1.81), 1.94 (95% CI 1.62–2.31), 1.51 (95% CI 1.34–1.70), 1.27 (95% CI 1.06–1.52), 1.38 (95% CI 1.13–1.68), 1.44 (95% CI 1.13–1.84), 1.50 (95% CI 1.14–1.99), 1.23 (95% CI 1.10–1.37), and 238.20 (95% CI 92.54–613.12), respectively. Conclusions: The prevalence of MetS is still in a rising trend in Beijing. Strategies aimed at prevention and control of high BP should be prioritized to reduce the occurrence of MetS. WHtR is more important to evaluate MetS. Health education and personalized lifestyle intervention should be promoted to keep a healthy WHtR and waist circumference. An appropriate sleep time should be kept, and harmful alcohol drinkers should limit or abstain from alcohol.