Background

There have been scant reports on the cumulative effects of atherosclerotic risk factors on steatohepatitis.

Methods

We defined cases of steatohepatitis (n = 124) from one health examination center at National Taiwan University Hospital from January to December 2002. We selected controls, matched by age, gender and drinking status. Metabolic syndrome was defined by the modified ATP-III guidelines. High-dimensional interactions of risk factors for steatohepatitis were evaluated.

Results

Steatohepatitis cases had the highest C-reactive protein, lymphocytes, Framingham scores and predicted coronary risks. The odds ratio (OR) of metabolic syndrome for steatohepatitis was the highest (OR = 9.9), followed by high glucose status (OR = 4.5) and obesity (OR = 3.6). The highest area under the ROC curve was metabolic syndrome (area = 0.80), followed by obesity (0.75) and high glucose level (0.73). Metabolic syndrome was the highest population-attributable risk factor (0.59). Significant interaction was found with a three-factor model, including obesity, metabolic syndrome and Framingham risk status, with lesser average prediction error (22.6%), higher average cross-validation consistency (6.3) and lower average prediction error (24.3%). Compared with persons with no risk factors, OR increased as the number of risk factors increased (OR = 3.0 with one risk factor, 17.5 with two risk factors, 10.8 with three risk factors, respectively).

Conclusion

Metabolic syndrome, inflammation markers and atherosclerotic risk scores are significantly related to steatohepatitis status among the healthy examinee population in Taiwan.

Background

Evidence of predictive power of various fatty acids on the risk of metabolic syndrome was scanty. We evaluated the role of various fatty acids, including saturated fat, monounsaturated fat, transfat, n-6 fatty acid, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), for the risk of the metabolic syndrome in Taiwan.

Results

A nested case-control study based on 1000 cases of metabolic syndrome and 1:1 matched control subjects. For saturated fat, monounsaturated fat and transfat, the higher the concentration the higher the risk for metabolic syndrome: participants in the highest quintile had a 2.22-fold (95% confidence interval [CI], 1.66 to 2.97) higher risk of metabolic syndrome. In addition, the participants in higher EPA quintiles were less likely to have the risk of metabolic syndrome (adjusted risk, 0.46 [0.34 to 0.61] for the fifth quintile). Participants in the highest risk group (low EPA and high transfat) had a 2.36-fold higher risk of metabolic syndrome (95% CI, 1.38 to 4.03), compared with those in the lowest risk group (high EPA and low transfat). For prediction power, the area under ROC curves increased from 0.926 in the baseline model to 0.928 after adding fatty acids. The net reclassification improvement for metabolic syndrome risk was substantial for saturated fat (2.1%, P = 0.05).

Conclusions

Plasma fatty acid components improved the prediction of the metabolic syndrome risk in Taiwan.