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Pan X, Xie X, Peng H, Cai X, Li H, Hong Q, Wu Y, Lin X, Xu S, Peng XE. Risk Prediction for Non-alcoholic Fatty Liver Disease Based on Biochemical and Dietary Variables in a Chinese Han Population. Front Public Health 2020; 8:220. [PMID: 32714888 PMCID: PMC7346601 DOI: 10.3389/fpubh.2020.00220] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 05/13/2020] [Indexed: 12/15/2022] Open
Abstract
Nonalcoholic fatty liver disease (NAFLD) is a common liver disease globally, but there are no optimal methods for its prediction or diagnosis. The present cross-sectional study proposes a non-invasive tool for NAFLD screening. The study included 2,446 individuals, of whom 574 were NAFLD patients. Multivariable logistic regression analysis was used to identify risk factors for NAFLD and incorporate them in a risk prediction nomogram model; the variables included both clinical and lifestyle-related variables. Following stepwise regression, BMI, waist circumference, serum triglyceride, high-density lipoprotein cholesterol, alanine aminotransferase, presence of diabetes and hyperuricemia, tuber and fried food consumption were identified as significant risk factors and used in the model. The final nomogram was found to have good discrimination ability (area under the receiver operating characteristic curve = 0.843 [95% CI: 0.819-0.867]), and reasonable accuracy for the prediction of NAFLD risk. A cut-off score of <180 for the nomogram was found to have high sensitivity and predictivity for the exclusion of individuals from screening. The model can be used as a non-invasive tool for mass screening.
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Affiliation(s)
- Xinting Pan
- Fujian Provincial Key Laboratory of Environment Factors and Cancer, Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Xiaoxu Xie
- Fujian Provincial Key Laboratory of Environment Factors and Cancer, Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Hewei Peng
- Fujian Provincial Key Laboratory of Environment Factors and Cancer, Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Xiaoling Cai
- Fujian Provincial Key Laboratory of Environment Factors and Cancer, Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Huiquan Li
- Fujian Provincial Key Laboratory of Environment Factors and Cancer, Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Qizhu Hong
- Fujian Provincial Key Laboratory of Environment Factors and Cancer, Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Yunli Wu
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
| | - Xu Lin
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
| | - Shanghua Xu
- Department of Cardiology, Affiliated Nanping First Hospital, Fujian Medical University, Nanping, China
| | - Xian-E Peng
- Fujian Provincial Key Laboratory of Environment Factors and Cancer, Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China.,Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China
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