Michelle T Long1,2, Alison Pedley2,3, Joseph M Massaro2,4, Udo Hoffmann5, Jiantao Ma2,6, Rohit Loomba7,8,9, Raymond T Chung10, Emelia J Benjamin2,11,12. 1. Section of Gastroenterology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA. 2. Framingham Heart Study, Framingham, MA, USA. 3. Merck Research Labs, Kenilworth, NJ, USA. 4. Department of Mathematics and Statistics, Boston University, Boston, MA, USA. 5. Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. 6. Population Sciences Branch, National Heart, Lung, and Blood Institute, Framingham, MA, USA. 7. NAFLD Research Center, Department of Medicine, University of California at San Diego, La Jolla, CA, USA. 8. Division of Epidemiology, Department of Family and Preventive Medicine, University of California at San Diego, La Jolla, CA, USA. 9. Division of Gastroenterology, Department of Medicine, University of California at San Diego, La Jolla, CA, USA. 10. Liver Center, Gastrointestinal Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. 11. Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA. 12. Cardiology and Preventive Medicine Sections, Evans Department of Medicine, Boston University School of Medicine, Boston, MA, USA.
Abstract
BACKGROUND AND AIMS: The factors associated with incident hepatic steatosis are not definitively known. We sought to determine factors associated with incident hepatic steatosis, as measured on computed tomography, in the community. METHODS: We studied Framingham Heart Study participants without heavy alcohol use or baseline hepatic steatosis who underwent computed tomography scans between 2002-2005 (baseline) and 2008-2011 (follow-up). We performed a stepwise logistic regression procedure to determine the predictors associated with incident hepatic steatosis. RESULTS: We included 685 participants (mean age: 45.0 ± 6.2 years, 46.8% women). The incidence of hepatic steatosis in our sample was 17.1% over a mean 6.3 years of follow-up. Participants who developed hepatic steatosis had more adverse cardiometabolic profiles at baseline compared to those free of hepatic steatosis at follow-up. Multivariable stepwise regression analysis showed that a simple clinical model including age, sex, body mass index, alcohol consumption and triglycerides was predictive of incident hepatic steatosis (C statistic = 0.791, 95% CI: 0.748-0.834). A complex clinical model, which included visceral adipose tissue volume and liver phantom ratio added to the simple clinical model, and had improved discrimination for predicting incident hepatic steatosis (C statistic = 0.826, 95% CI: 0.786-0.866, P < .0001). CONCLUSIONS: The combination of demographic, clinical and imaging characteristics at baseline was predictive of incident hepatic steatosis. The use of our predictive model may help identify those at increased risk for developing hepatic steatosis who may benefit from risk factor modification although further investigation is warranted.
BACKGROUND AND AIMS: The factors associated with incident hepatic steatosis are not definitively known. We sought to determine factors associated with incident hepatic steatosis, as measured on computed tomography, in the community. METHODS: We studied Framingham Heart Study participants without heavy alcohol use or baseline hepatic steatosis who underwent computed tomography scans between 2002-2005 (baseline) and 2008-2011 (follow-up). We performed a stepwise logistic regression procedure to determine the predictors associated with incident hepatic steatosis. RESULTS: We included 685 participants (mean age: 45.0 ± 6.2 years, 46.8% women). The incidence of hepatic steatosis in our sample was 17.1% over a mean 6.3 years of follow-up. Participants who developed hepatic steatosis had more adverse cardiometabolic profiles at baseline compared to those free of hepatic steatosis at follow-up. Multivariable stepwise regression analysis showed that a simple clinical model including age, sex, body mass index, alcohol consumption and triglycerides was predictive of incident hepatic steatosis (C statistic = 0.791, 95% CI: 0.748-0.834). A complex clinical model, which included visceral adipose tissue volume and liver phantom ratio added to the simple clinical model, and had improved discrimination for predicting incident hepatic steatosis (C statistic = 0.826, 95% CI: 0.786-0.866, P < .0001). CONCLUSIONS: The combination of demographic, clinical and imaging characteristics at baseline was predictive of incident hepatic steatosis. The use of our predictive model may help identify those at increased risk for developing hepatic steatosis who may benefit from risk factor modification although further investigation is warranted.
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