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Association between triglyceride glucose-body mass index and non-alcoholic fatty liver disease in the non-obese Chinese population with normal blood lipid levels: a secondary analysis based on a prospective cohort study

BACKGROUND: Both triglyceride glucose-body mass index (TyG-BMI) and non-alcoholic fatty liver disease (NAFLD) are linked to insulin resistance (IR). Prospective studies linking TyG-BMI to NAFLD have been limited by short follow-up. This study investigated the longitudinal association between TyG-BMI...

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Detalles Bibliográficos
Autores principales: Li, Yaling, Zheng, Rui, Li, Jie, Feng, Shuyi, Wang, Li, Huang, Zhiming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7592551/
https://www.ncbi.nlm.nih.gov/pubmed/33109219
http://dx.doi.org/10.1186/s12944-020-01409-1
Descripción
Sumario:BACKGROUND: Both triglyceride glucose-body mass index (TyG-BMI) and non-alcoholic fatty liver disease (NAFLD) are linked to insulin resistance (IR). Prospective studies linking TyG-BMI to NAFLD have been limited by short follow-up. This study investigated the longitudinal association between TyG-BMI and NAFLD occurrence in the non-obese Chinese individuals. METHODS: This study determined TyG-BMI at baseline and the incidence of NAFLD at follow-up and performed a post hoc analysis of a prospective cohort study that involved assessing the risk of NAFLD in non-obese Chinese residents from January 2010 to December 2014. The incidence of NAFLD during the 5-year follow-up was identified as the endpoint. Cox proportional hazards regression analysis was used to evaluate hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the incidence of NAFLD. Receiver operating characteristic (ROC) curve analysis was conducted to estimate the predictive power of TyG-BMI and its components for NAFLD. Subgroup analysis was performed to better understand other factors that may affect the association between TyG-BMI and NAFLD to identify potential special populations. RESULTS: During the follow-up period, 841 (8.61%) of 9767 non-obese subjects who met the screening criteria were diagnosed with NAFLD. After confounding factors were fully adjusted for, the HR of NAFLD was 3.09 (95% CI 2.63–3.63) per standard deviation (SD) increase in TyG-BMI. Furthermore, TyG-BMI had a strong predictive value (area under ROC = 0.85; 95% CI 0.84–0.86) for the incidence of NAFLD, with a specificity of 0.73 and sensitivity of 0.82. Additionally, in the male population, each SD increase in TyG-BMI was linked to an increased risk of NAFLD (HR = 2.85, 95% CI 2.30–3.53), but the risk was higher in the female population (HR = 3.58, 95% CI 2.80–4.60). Gender and TyG-BMI interacted significantly with NAFLD incidence (P < 0.0001). CONCLUSION: In the normolipidaemic and non-obese subset of the Chinese population, an increase in TyG-BMI is related to an increased incidence of NAFLD. TyG-BMI may have clinical significance in identifying groups at high risk of NAFLD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12944-020-01409-1.