Identification of reciprocal causality between non-alcoholic fatty liver disease and metabolic syndrome by a simplified Bayesian network in a Chinese population. Issue 9 (22nd September 2015)

• Record Type: Journal Article
• Authors: Zhang, Yongyuan; Zhang, Tao; Zhang, Chengqi; Tang, Fang; Zhong, Nvjuan; Li, Hongkai; Song, Xinhong; Lin, Haiyan; Liu, Yanxun; Xue, Fuzhong
• Is Part Of: BMJ open. Volume 5:Issue 9(2015)
• Publication Date: 2015-09-22
• Subjects: Nonalcolic Fatty Liver Disease -- Metabolic Syndrome -- Bi-directional Longitudinal Cohort -- Reciprocal Causality -- Generalized Estimating Equation -- Bayesian Network; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2015-008204
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : Objectives: It remains unclear whether non-alcoholic fatty liver disease (NAFLD) is a cause or a consequence of metabolic syndrome (MetS). We proposed a simplified Bayesian network (BN) and attempted to confirm their reciprocal causality. Setting: Bidirectional longitudinal cohorts (subcohorts A and B) were designed and followed up from 2005 to 2011 based on a large-scale health check-up in a Chinese population. Participants: Subcohort A (from NAFLD to MetS, n=8426) included the participants with or without NAFLD at baseline to follow-up the incidence of MetS, while subcohort B (from MetS to NAFLD, n=16 110) included the participants with or without MetS at baseline to follow-up the incidence of NAFLD. Results: Incidence densities were 2.47 and 17.39 per 100 person-years in subcohorts A and B, respectively. Generalised estimating equation analyses demonstrated that NAFLD was a potential causal factor for MetS (relative risk, RR, 95% CI 5.23, 3.50 to 7.81), while MetS was also a factor for NAFLD (2.55, 2.23 to 2.92). A BN with 5 simplification strategies was used for the reciprocal causal inference. The BN's causal inference illustrated that the total effect of NAFLD on MetS (attributable risks, AR%) was 2.49%, while it was 19.92% for MetS on NAFLD. The total effect of NAFLD on MetS components was different, with dyslipidemia having the greatest (AR%, 10.15%), followed by obesity (7.63%), diabetes (3.90%) and hypertension (3.51%). Similar patterns were inferred for MetS components on NAFLD, with obesity having the greatest (16.37%) effect, followed by diabetes (10.85%), dyslipidemia (10.74%) and hypertension (7.36%). Furthermore, the most important causal pathway from NAFLD to MetS was that NAFLD led to elevated GGT, then to MetS components, while the dominant causal pathway from MetS to NAFLD began with dyslipidaemia. Conclusions: The findings suggest a reciprocal causality between NAFLD and MetS, and the effect of MetS on NAFLD is significantly greater than that of NAFLD on MetS.