Title: Metabolic syndrome predicts the incidence of hepatic steatosis in Koreans
Abstract: It has not been well elucidated whether the development of metabolic syndrome and its components predicts the incidence of hepatic steatosis. A cohort of 1705 apparently healthy Korean adults (954 men and 751 women, 43.6 ± 8.5 years old) without ultrasonographically defined hepatic steatosis and with normal serum gamma-glutamyl-transpeptidase and alanine aminotransferase was followed from 2004 to 2007. Metabolic syndrome was defined as the presence of at least three of the following components: obesity (BMI ≥ 25.0 kg/m2), high blood pressure, elevated levels of triglycerides and fasting glucose, and low level of high-density lipoprotein cholesterol. The outcome was ultrasonographically diagnosed hepatic steatosis. The analyses were conducted using the Cox proportional hazards model and time-dependent Cox model. A total of 226 individuals developed hepatic steatosis during 3716 person–years of follow-up. The presence of one to two metabolic syndrome components at baseline significantly predicted the development of hepatic steatosis. Metabolic syndrome itself, having ≥1 metabolic syndrome components, and maintenance of metabolic syndrome during follow-up significantly increased the risk (hazard ratio 2.0–4.1 for men, 3.4–10.8 for women) after adjustment for the follow-up period, age and BMI at baseline or updated during follow-up. Occurrence of obesity, high triglycerides or high fasting glucose during follow-up significantly predicted the development of hepatic steatosis, even after adjustment for metabolic syndrome components at baseline. The presence at baseline and the development of metabolic syndrome during follow-up were risk factors for ultrasonographically detected hepatic steatosis.
Publication Year: 2010
Publication Date: 2010-03-03
Language: en
Type: article
Indexed In: ['crossref', 'pubmed']
Access and Citation
Cited By Count: 8
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot