Triglyceride: A mediator of the association between waist-to-height ratio and non-alcoholic fatty liver disease: A second analysis of a population-based study

Association between serum hypertriglyceridemia and hematological indices: data mining approaches

BACKGROUND

High triglyceride (TG) affects and is affected of other hematological factors. The determination of serum fasted triglycerides concentrations, as part of a lipid profile, is crucial key point in hematological factors and significantly affect various systemic diseases. This study was carried out to assess the potential relation between the concentration of TG and hematological factors.

METHOD

Our sample size was 9704 participants beginning in 2007 and ending in 2020 aged between 35 and 65 years, sourced from the MASHAD cohort (northeastern Iran). Machine learning methodologies, specifically logistic regression, decision tree, and random forest algorithms, were utilized for data analysis in the investigation of individuals with normal and high TG levels.

RESULTS

The highest Gini score belongs to RLR (Red cell distribution width/Lymphocyte) (236.10), RPR (Red cell distribution width/Platelets) (215.78), and PHR (Platelets/high-density lipoprotein) (273.66). We also found that factors such as age are statistically associated with the level of TG in women probably due to the drop in menopausal estrogen. RF model showed to have higher accuracy in predicting the TG level in both males and females.

CONCLUSION

Our model assessed the association between serum TG with several hematological factors like RLR, RPR, and PHR. Other hematological factors also have been reported to be related to the TG level. As these results give us new insights into the association of TG on various hematological factors and their possible interactions with each other. future studies are needed to provide sufficient data for the mechanism and the pathophysiology of the findings.

LASSO-derived model for the prediction of lean-non-alcoholic fatty liver disease in examinees attending a routine health check-up

BACKGROUND

Lean individuals with non-alcohol fatty liver disease (NAFLD) often have normal body size but abnormal visceral fat. Therefore, an alternative to body mass index should be considered for prediction of lean-NAFLD. This study aimed to use representative visceral fat links with other laboratory parameters using the least absolute shrinkage and selection operator (LASSO) method to construct a predictive model for lean-NAFLD.

METHODS

This retrospective cross-sectional analysis enrolled 2325 subjects with BMI < 24 kg/m2 from medical records of 51,271 examinees who underwent a routine health check-up. They were randomly divided into training and validation cohorts at a ratio of 1:1. The LASSO-derived prediction model used LASSO regression to select 23 clinical and laboratory factors. The discrimination and calibration abilities were evaluated using the Hosmer-Lemeshow test and calibration curves. The performance of the LASSO model was compared with the fatty liver index (FLI) model.

RESULTS

The LASSO-derived model included four variables-visceral fat, triglyceride levels, HDL-C-C levels, and waist hip ratio-and demonstrated superior performance in predicting lean-NAFLD with high discriminatory ability (AUC, 0.8416; 95% CI: 0.811-0.872) that was comparable with the FLI model. Using a cut-off of 0.1484, moderate sensitivity (75.69%) and specificity (79.86%), as well as high negative predictive value (95.9%), were achieved in the LASSO model. In addition, with normal WC subgroup analysis, the LASSO model exhibits a trend of higher accuracy compared to FLI (cut-off 15.45).

CONCLUSIONS

We developed a LASSO-derived predictive model with the potential for use as an alternative tool for predicting lean-NAFLD in clinical settings.

Impact of smoking cessation on non-alcoholic fatty liver disease prevalence: a systematic review and meta-analysis

OBJECTIVES

The negative effects of smoking on numerous cardiovascular and metabolic diseases have been widely acknowledged. However, the potential effect of smoking cessation is relatively unelucidated. The objective of this study is to explore whether the prevalence of non-alcoholic fatty liver disease (NAFLD) in former smokers differs from the prevalence in current smokers.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

Four databases, that is, PubMed, Web of Science, Journal@Ovid and Scopus were searched from inception to 31 January 2023.

ELIGIBILITY CRITERIA

Population-based cross-sectional studies, including the baseline data of cohort studies with identified NAFLD diagnostic methods, and smoking status (current smoker or former smoker) of participants were included.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently extracted the data including cigarette smoking status, country/region of studies, NAFLD diagnostic methods, sex, the average age and body mass index (BMI) of NAFLD participants and assessed the risk of bias with Agency for Healthcare Research and Quality (AHRQ) methodology checklist. Risk ratio (RR) of NAFLD prevalence in former smokers was pooled using the random-effects model.

RESULTS

28 studies involving 4 465 862 participants were included. Compared with current smokers, the RR of overall NAFLD prevalence in former smokers was 1.13 (95% CI: 1.08 to 1.19, prediction interval: 0.92-1.39). This result persisted after adjustment for diagnostic methods, country/region, sex, age and BMI. Sensitivity analysis and risk of bias assessment indicated a stable conclusion.

CONCLUSIONS

NAFLD prevalence in former smokers was at least not lower than that in current smokers and was partially related to increased BMI after smoking cessation, indicating that smoking cessation was possibly not a protective factor against NAFLD. Although the meta-analysis based on cross-sectional studies cannot conclude the causal relationships between smoking cessation and NAFLD onset, the potential onset of NAFLD associated with smoking cessation should be highlighted.

PROSPERO REGISTRATION NUMBER

CRD42023394944.