Cutoff Points of Waist Circumference for Predicting Incident Non-Alcoholic Fatty Liver Disease in Middle-Aged and Older Korean Adults

Assessment of the appropriate cutoff points for anthropometric indices and their relationship with cardio-metabolic indices to predict the risk of metabolic associated fatty liver disease

BACKGROUND

Research on Metabolic Associated Fatty Liver Disease (MAFLD) is still in its early stages, with few studies available to identify and predict effective indicators of this disease. On the other hand, early diagnosis and intervention are crucial to reduce the burden of MAFLD. Therefore, the aim of this research was to investigate the effectiveness of eleven anthropometric indices and their appropriate cut-off values as a non-invasive method to predict and diagnose MAFLD in the Iranian population.

METHODS

In this cross-sectional study, we analyzed baseline data from the Hoveyzeh Cohort Study, a prospective population-based study conducted in Iran that enrolled a total of 7836 subjects aged 35 to 70 years from May 2016 through August 2018.

RESULTS

The optimal cut-off values of anthropometric indices for predicting MAFLD risk were determined for waist circumference(WC) (102.25 cm for males and 101.45 cm for females), body mass index (BMI) (27.80 kg/m2 for males and 28.75 kg/m2 for females), waist-to-hip ratio (WHR) (0.96 for both males and females), waist-to-height ratio (WHtR) (0.56 for males and 0.63 for females), body adiposity index (BAI) (23.24 for males and 32.97 for females), visceral adiposity index (VAI) (1.64 for males and 1.88 for females), weight-adjusted waist index (WWI) (10.63 for males and 11.71 for females), conicity index (CI) (1.29 for males and 1.36 for females), body roundness index (BRI) (4.52 for males and 6.45 for females), relative fat mass (RFM) (28.18 for males and 44.91 for females) and abdominal volume index (AVI) (18.85 for males and for 21.37 females). VAI in males (sensitivity: 77%, specificity: 60%, Youden's Index: 0.37) and RFM in females (sensitivity: 76%, specificity: 59%, Youden's Index: 0.35) were found to have higher sensitivity and specificity compared to other anthropometric indices. Furthermore, anthropometric indices demonstrated statistically significant correlations with various hepatic and cardiometabolic indices. Among these, the strongest positive correlations were observed between WC, BMI, BAI, BRI, and AVI with the Hepatic Steatosis Index (HSI), TyG-BMI, and TyG-WC, as well as between VAI and the Atherogenic Index of Plasma (AIP), Lipid Accumulation Product (LAP), Cardiometabolic Index (CMI), and the Triglyceride and Glucose (TyG) Index.

CONCLUSION

Anthropometric indices are effective in predicting MAFLD risk among Iranian adults, with WWI, VAI, and RFM identified as the strongest predictors. The proposed cutoff values could serve as a straightforward and non-invasive methods for the early diagnosis of MAFLD.

Changes in nonalcoholic fatty liver disease and M2BPGi due to lifestyle intervention in primary healthcare

BACKGROUND

A healthy lifestyle is the most important method for managing nonalcoholic fatty liver disease (NAFLD). Mac-2-binding protein glycosylated isomer (M2BPGi) has been suggested as a biomarker for NAFLD. This study aimed to determine the efficacy of personalized lifestyle interventions on NAFLD remission.

METHODS

This single-arm intervention study recruited participants with NAFLD who underwent health checkups at seven health-promotion centers in five South Korean cities. Fatty liver diagnosis was based on ultrasonography (US). The 109 individuals were recruited for personalized lifestyle interventions of hypocaloric diets and exercise. The participants attended the lifestyle intervention programs once per month for the first 3 months, and once every 3 months for the subsequent 6 months. In addition to sessions through center visits, phone-based intervention and self-monitoring at 4-, 5-, 7-, and 8-month were provided during the 9-month intervention period. And phone-based self-monitoring were also provided monthly during the 3-month follow-up period. The primary outcome was NAFLD remission at month 12 as measured on US and magnetic resonance elastography. The secondary outcomes were the changes in metabolic factors and M2BPGi.

RESULTS

The 108 individuals (62 males and 46 females; age 51.1±12.4 years, mean±standard deviation) were finally analyzed after the 12month intervention. Body mass index, waist circumference (WC), blood pressure, blood lipids (total cholesterol, triglycerides, and HDL-C), and fasting blood sugar levels were improved relative to baseline (all P<0.05). Fatty liver at or above the moderate grade according to US was decreased at month 12 relative to baseline (67.6% vs 50.9%) (P = 0.002). M2BPGi levels decreased during the 12-month study period (P<0.001). M2BPGi levels were moderately correlated with hepatic fat fraction by magnetic resonance imaging (r = 0.33, P = 0.05). WC (OR = 0.82, 95% CI = 0.67-1.00, P = 0.05) and HDL-C (OR = 1.17, 95% CI = 1.03-1.32, P = 0.014) were associated with remission of fatty liver in the multivariate analysis.

CONCLUSION

The personalized lifestyle intervention was effective in improving fatty liver and metabolic factors, but not hepatic stiffness, in NAFLD.

TRIAL REGISTRATION

ICTRP, cris.nih.go.kr (KCT0006380).

Development and Validation of a Risk Prediction Model for NAFLD: A Study Based on a Physical Examination Population

Purpose

To construct and validate a precise and personalized predictive model for non-alcoholic fatty liver disease (NAFLD) to enhance NAFLD screening and healthcare administration.

Patients and Methods

A total of 730 participants' clinical information and outcome measurements were gathered and randomly divided into training and validation sets in a ratio of 3:7. Using the least absolute shrinkage and selection operator (LASSO) regression and multiple logistic regression, a nomogram was established to select risk predictor variables. The NAFLD prediction model was validated through the receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis (DCA).

Results

After random grouping, the cohort comprised 517 in the training set and 213 in the validation set. The prediction model employed nine of the 20 selected variables, namely gender, hypertension, waist circumference, body mass index, blood platelet, triglycerides, high-density lipoprotein cholesterol, plasma glucose, and alanine aminotransferase. ROC curve analysis yielded an area under the curve values of 0.877 (95% Confidence Interval [CI]: 0.848-0.907) for the training set and 0.871 (95% CI: 0.825-0.917) for the validation set. Optimal critical values were determined as 0.472 (0.786, 0.825) in the training set and 0.457 (0.743, 0.839) in the validation set. Calibration curves for both sets showed proximity to the ideal diagonal, with P-values of 0.972 and 0.370 for the training and validation sets, respectively (P > 0.05). DCA indicated favorable clinical applicability of the model.

Conclusion

We constructed a nomogram model that could complement traditional NAFLD detection methods, aiding in individualized risk assessment for NAFLD.

The Efficacy of Anthropometric Indicators in Predicting Non-Alcoholic Fatty Liver Disease Using FibroScan® CAP Values among the Taiwanese Population

The controlled attenuation parameter (CAP) measurement obtained from FibroScan® is a low-risk method of assessing fatty liver. This study investigated the association between the FibroScan® CAP values and nine anthropometric indicators, including the abdominal volume index (AVI), body fat percentage (BFP), body mass index (BMI), conicity index (CI), ponderal index (PI), relative fat mass (RFM), waist circumference (WC), waist-hip ratio (WHR), and waist-to-height ratio (WHtR), and risk of non-alcoholic fatty liver disease (fatty liver). We analyzed the medical records of adult patients who had FibroScan® CAP results. CAP values <238 dB/m were coded as 0 (non- fatty liver) and ≥238 dB/m as 1 (fatty liver). An individual is considered to have class 1 obesity when their body mass index (BMI) ranges from 30 kg/m2 to 34.9 kg/m2. Class 2 obesity is defined by a BMI ranging from 35 kg/m2 to 39.9 kg/m2, while class 3 obesity is designated by a BMI of 40 kg/m2 or higher. Out of 1763 subjects, 908 (51.5%) had fatty liver. The BMI, WHtR, and PI were found to be more strongly correlated with the CAP by the cluster dendrogram with correlation coefficients of 0.58, 0.54, and 0.54, respectively (all p < 0.0001). We found that 28.3% of the individuals without obesity had fatty liver, and 28.2% of the individuals with obesity did not have fatty liver. The BMI, CI, and PI were significant predictors of fatty liver. The BMI, PI, and WHtR demonstrated better predictive ability, indicated by AUC values of 0.72, 0.68, and 0.68, respectively, a finding that was echoed in our cluster group analysis that showed interconnected clustering with the CAP. Therefore, of the nine anthropometric indicators we studied, the BMI, CI, PI, and WHtR were found to be more effective in predicting the CAP score, i.e., fatty liver.

Association between waist circumference trajectories and incident non-alcoholic fatty liver disease

PURPOSE

Waist circumference (WC) is linked to non-alcoholic fatty liver disease (NAFLD) incidence. However, the impact of longitudinal WC changes on NAFLD remains unclear. We investigated WC trajectories and NAFLD incidence in a large population-based cohort.

METHODS

We analyzed data from 2666 participants without NAFLD, who underwent biennial check-ups for 16 years, divided into a 6-year exposure period and a 10-year event accrual period. Participants were classified into increasing and decreasing WC trajectory groups during the median 5.9-year exposure period by group-based trajectory modeling. Multiple Cox proportional hazard regression analysis estimated the hazard ratio (HR) and 95 % confidence interval (CI) for incident NAFLD.

RESULTS

During the median 9.7-year event accrual period, 799 participants developed NAFLD. The increasing WC trajectory group had a higher NAFLD risk than the decreasing group, with an HR of 1.20 (95 % CI: 1.02-1.42). After adjusting for confounders, the adjusted-HR was 1.28 (95 % CI: 1.07-1.53). Subgroup analyses revealed significant findings for groups, regardless of abdominal obesity status.

CONCLUSION

An increasing WC trend was associated with a higher NAFLD risk, independent of abdominal obesity status. Monitoring WC changes may facilitate early detection of NAFLD risk groups and promote lifestyle modifications to prevent NAFLD onset.

Gender Differences in the Risk for Incident Non-Alcoholic Fatty Liver Disease According to the Transition of Abdominal Obesity Status: A 16-Year Cohort Study

Waist circumference (WC) is an important predictor of long-term adverse outcomes. We aimed at assessing the correlation between abdominal obesity (AO) patterns and non-alcoholic fatty liver disease (NAFLD). Data from 4467 adults aged 40-69 years and without NAFLD who participated in the Korean Genome and Epidemiology Study were analyzed. Participants were classified according to two-year WC pattern into four groups: persistent lean WC, improved AO, progressed to AO, and persistent AO. NAFLD was defined as NAFLD-liver fat score >-0.640. Multiple Cox proportional hazards regression analysis revealed that the fully adjusted hazard ratio (HR) (95% confidence intervals (CIs)) for NAFLD in persistent AO, progressed to AO, and improved AO groups compared to the persistent lean WC group was 1.33 (1.13-1.57), 1.73 (1.48-2.02), and 1.06 (0.84-1.33), respectively. Women in persistent AO or progressed to AO groups had significantly higher risk for NAFLD than those in persistent lean WC or improved AO groups. Men who had progressed to an AO event over two years had significantly higher risk for NAFLD than those without any AO event over two years. Maintaining lean WC and improving AO would be successful strategies for preventing NAFLD in women, while maintaining lean WC would be more effective in men.

Associations between body circumference and testosterone levels and risk of metabolic dysfunction-associated fatty liver disease: a mendelian randomization study

Backgroud

Body circumference and testosterone levels have been reported as associated with metabolic dysfunction-associated fatty liver disease (MAFLD) risk. However, whether body circumference and testosterone levels play a role in the development of MAFLD remains inconclusive.

Methods

Using a large database of genome-wide association studies, genetic loci that are independent of each other and strongly associated with body circumference and testosterone levels were selected as instrumental variables, the causal relationship between body circumference and testosterone and risk of MAFLD was investigated by two-sample Mendelian randomization methods such as inverse variance weighted (IVW), MR-Egger regression, and weighted median estimator (WME), using the odds ratios (ORs) as evaluation indicators.

Results

A total of 344 SNPs were included as instrumental variables in this study, including 180 for waist circumference, 29 for waist-to-hip ratio, and 135 for testosterone levels. Using the above two-sample Mendelian Randomization method to derive the causal association between exposure and outcome. The results of this study showed that three exposure factors were causally associated with the risk of MAFLD. Waist circumference obtained three statistically significant results for IVW, WME and Weighted mode (IVW: OR = 3.53, 95%CI: 2.23–5.57, P < 0.001; WME: OR = 3.88, 95%CI: 1.81–8.29, P < 0.001; Weighted mode: OR = 3.58, 95%CI: 1.05–12.16, P = 0.043). Waist-to-hip ratio obtained one statistically significant result for IVW (OR = 2.29, 95%CI: 1.12–4.66, P = 0.022). Testosterone levels obtained one statistically significant result for IVW (OR = 1.93, 95%CI: 1.30–2.87, P = 0.001). Waist circumference, waist-to-hip ratio and testosterone level were considered as risk factors for MAFLD. The Cochran Q test for IVW and MR-Egger method indicated that there was no intergenic heterogeneity in SNPs. The test for pleiotropy indicated that the possibility of pleiotropy in the causal analysis was weak.

Conclusion

The results of the two-sample Mendelian randomization analysis showed that waist circumference was the exact risk factor for MAFLD, waist-to-hip ratio and testosterone levels were potential risk factors for MAFLD, the risk of developing MAFLD increases with these three exposure factors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-023-15467-4.