Correlation Between Anthropometric Measurements and Non-alcoholic Fatty Liver Disease in Individuals With Obesity Undergoing Bariatric Surgery: Cross-Sectional Study

Waist-to-hip ratio and nonalcoholic fatty liver disease: a clinical observational and Mendelian randomization analysis

Background

Obesity often coincides with non-alcoholic fatty liver disease (NAFLD), yet a significant portion of NAFLD patients exhibit normal body mass index (BMI) but have abdominal obesity. Recognizing this discrepancy, we aimed to delve deeper into this phenomenon through observational studies coupled with two-sample Mendelian randomization (MR) analysis, with waist-to-hip ratio (WHR) serving as the indicator for abdominal obesity. Our objective was to ascertain whether WHR correlates with an increased risk of NAFLD development.

Methods

This study utilized data from the National Health and Nutrition Examination Survey (NHANES) 2017-2018 to examine the association between WHR and NAFLD through weighted multivariate logistic regression models. On this basis, subgroup analyses were performed to further explore the correlation between WHR and NAFLD. Subsequently, a two-sample MR analysis was conducted using genome-wide association studies (GWAS) data to investigate the potential causal relationship between WHR and NAFLD. Sensitivity analyses were also employed to ensure the robustness of our findings.

Results

A total of 3,732 eligible participants were included in the analysis. Weighted multivariable-adjusted logistic regression models revealed a positive association between WHR and the risk of NAFLD (Q2vsQ1: OR = 1.94 [95% CI: 1.55-2.44]; Q3vsQ1: OR = 2.08 [95% CI: 1.51-2.85]; Q4vsQ1: OR = 3.70 [95% CI: 2.13-6.43], p < 0.05). The results of the subgroup analysis suggested that there was an interaction in the correlation between WHR and NAFLD in normal weight, overweight, and obese populations (p < 0.05). The RCS curves indicated that there was a nonlinear relationship between WHR and NAFLD in populations with BMI in the normal versus obese categories. Furthermore, MR analysis provided additional support for the causal relationship between WHR and NAFLD. Using inverse variance weighting (IVW), the MR analysis yielded an OR of 2.062 (95% CI: 1.680-2.531, p<0.05). Consistent results were obtained with the other four MR methods, all supporting the same direction of causality. Sensitivity analyses were performed to assess the robustness of the findings (p > 0.5), further reinforcing the reliability of the observed associations.

Conclusion

WHR elevation heightens the susceptibility to NAFLD.

DIAGNOSTIC ACCURACY OF THE NON-INVASIVE MARKERS NFLS, NI-NASH-DS, AND FIB-4 FOR ASSESSMENT OF DIFFERENT ASPECTS OF NON-ALCOHOLIC FATTY LIVER DISEASE IN INDIVIDUALS WITH OBESITY: CROSS-SECTIONAL STUDY

BACKGROUND

Non-invasive markers have been developed to assess the presence and severity of liver abnormalities related to non-alcoholic fatty liver disease (NAFLD).

OBJECTIVE

To analyze the diagnostic accuracy of non-invasive NAFLD markers (NAFLD liver fat score [NLFS], non-invasive non-alcoholic steatohepatitis detection score [NI-NASH-DS] and fibrosis score based on four variables [FIB-4]) in individuals with obesity undergoing bariatric surgery.

METHODS

A descriptive retrospective cross-sectional study was carried out enrolling 91 individuals who underwent bariatric surgery at a tertiary-level public university hospital. Non-invasive NAFLD markers were calculated using laboratory tests, clinical and anthropometric variables and diagnostic accuracy tests were calculated comparing them in relation to the gold-standard test for this analysis (histopathological evaluation).

RESULTS

A total of 85.7% of the participants were female and mean age was 39.1±9.8 years. The average body mass index was 38.4±3.6 kg/m2. At histopathological examination, 84 (92.3%) patients presented with steatosis, 82 (90.1%) with some type of fibrosis; 21 (23.1%) patients were diagnosed with NASH according to the NAFLD activity score criteria. The overall accuracy of NLFS score was 58.2% for general hepatic steatosis and 61.5% for moderate to severe steatosis. The overall accuracy of FIB-4 was 95.4% for advanced fibrosis. NI-NASH-DS had a 74.7% overall accuracy for NASH.

CONCLUSION

In a population of individuals with obesity, the FIB-4 score had high overall accuracy in assessing the presence of advanced liver fibrosis, whereas the NFLS and NI-NASH-DS had moderate accuracies for the assessment of steatosis and NASH, respectively.

Establishment of a machine learning predictive model for non-alcoholic fatty liver disease: A longitudinal cohort study

BACKGROUND AND AIMS

Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disease, which lacks effective drug treatments. This study aimed to construct an eXtreme Gradient Boosting (XGBoost) prediction model to identify or evaluate potential NAFLD patients.

METHODS AND RESULTS

We conducted a longitudinal study of 22,140 individuals from the Beijing Health Management Cohort. Variable filtering was performed using the least absolute shrinkage and selection operator. Random Over Sampling Examples was used to address imbalanced data. Next, the XGBoost model and the other three machine learning (ML) models were built using balanced data. Finally, the variable importance of the XGBoost model was ranked. Among four ML algorithms, we got that the XGBoost model outperformed the other models with the following results: accuracy of 0.835, sensitivity of 0.835, specificity of 0.834, Youden index of 0.669, precision of 0.831, recall of 0.835, F-1 score of 0.833, and an area under the curve of 0.914. The top five variables with the greatest impact on the onset of NAFLD were aspartate aminotransferase, cardiometabolic index, body mass index, alanine aminotransferase, and triglyceride-glucose index.

CONCLUSION

The predictive model based on the XGBoost algorithm enables early prediction of the onset of NAFLD. Additionally, assessing variable importance provides valuable insights into the prevention and treatment of NAFLD.

Association of sex-specific body mass index and waist circumference trajectories with non-alcoholic fatty liver disease incidence based on growth mixture modeling

BACKGROUND AND AIMS

Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disease. The relationship between the trajectories of obesity indicators and incident NAFLD is unknown. Therefore, this study aims to explore the sex-specific association between the trajectories of obesity indicators and the incidence of NAFLD.

METHODS AND RESULTS

In total, 9067 participants were recruited for this longitudinal study. Obesity indicators use body mass index (BMI) and waist circumference (WC). The trajectory of obesity indicators was analyzed using the growth mixture modeling. The multivariate logistic regression model was used to analyze the association between obesity indicators' trajectories and incident NAFLD. Over a median follow-up of 1.82 years, 1013 (11.74%) participants developed NAFLD. We identified BMI and WC change trajectories as the stable group, increasing group, and decreasing group. After adjusting for baseline level and other confounders, multivariate logistic regression analysis showed that compared with stable group of BMI, the increasing group, and decreasing group odds ratio and 95% confidence interval of NAFLD were 2.10 (1.06-4.15), and 0.25 (0.09-0.67) in men, and 1.82 (1.08-3.04) and 0.32 (0.16-0.64) in women. Compared with stable group of WC, the increasing group was 2.57 (1.39-4.74) in men, the increasing group, and decreasing group were 2.29 (1.70-3.10) and 0.28 (0.12-0.64) in women. Sensitivity analysis showed that the results were stable.

CONCLUSION

The BMI and WC changing trajectories are significantly associated with the incidence of NAFLD in men and women. Populations of real-world health examinations can be categorized based on obesity indicator changes to prevent NAFLD.

Mendelian randomization explores the causal relationships between obesity, diabetes, inflammation and nonalcoholic fatty liver disease

Nonalcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases worldwide. Observational studies have revealed various risk factors associated with NAFLD, while the causal relationships between NAFLD and clinical diseases (including obesity, diabetes and inflammation) remain unclear. In this study, based on the genome-wide association study (GWAS) data, a two-sample Mendelian randomization (MR) analysis was conducted to evaluate the causality between NAFLD and 6 clinical indicators, including body mass index (BMI), waist-to-hip ratio (WHR), C-reactive protein (CRP), fasting blood glucose (FG), fasting insulin (FI), and glycosylated hemoglobin (HbA1c). MR is based on Mendel's law of inheritance, which uses genetic variation as a toll variable to affect the health of a population to infer causal effects in the presence of unobserved confounding. Inverse variance weighted method was the main MR method. In addition, we performed multiple steps of variable screening in the method to ensure that we were conducting the study under the MR assumption. In the MR analysis, a higher WHR (P = .0078; OR = 1.008; 95% CI, 1.002-1.013) was genetically predicted to be causally associated with an increased risk of NAFLD, while patients with higher HbA1c had a lower risk of NAFLD (P = .0437; OR = 0.44; 95% CI, 0.20-0.97). Our results showed that the genetically driven WHR and HbA1c might be potential causal factors for NAFLD, while BMI, FG, FI, and CRP were not causal factors for NAFLD, which explained the promoting role of WHR and HbA1c in the occurrence and development of NAFLD. Our finding hence revealed new insights into how nature and nurture factors underpin NAFLD, providing positive effect on the causes and prevention of this disease.

Risk Factors of Non-alcoholic Fatty Liver Disease in the Iranian Adult Population: A Systematic Review and Meta-analysis

Context: Non-alcoholic fatty liver disease (NAFLD) is progressing considerably worldwide. Identifying the risk factors of NAFLD is a critical step in preventing its progression. Methods: In November 2022, two independent researchers studied seven databases, including PubMed, ISI/WoS, ProQuest, Scopus, SID, Magiran, and Google Scholar, and reference list of relevant articles, searching studies that assessed NAFLD risk factors in the Iranian adult population. Heterogeneity between studies was assessed by Cochran’s test and its composition using I2 statistics. A random-effects model was used when heterogeneity was observed; otherwise, a fixed-effects model was applied. Egger’s regression test and Trim-and-Fill analysis were used to assess publication bias. Comprehensive Meta-analysis software (version 3) was used for the analyses of the present study. Results: The results of this study showed significant associations between NAFLD with age (n = 15, odds ratio (OR) = 2.12, 95% CI: 1.79 - 2.51), body mass index (n = 46, OR = 5.00, 95% CI: 3.34 - 7.49), waist circumference (n = 20, OR = 6.37, 95% CI: 3.25 - 12.48), waist-to-hip ratio (n = 17, OR = 4.72, 95% CI: 3.93 - 5.66), total cholesterol (n = 39, OR = 1.80, 95% CI: 1.52 - 2.13), high-density lipoprotein (n = 37, OR = 0.53, 95% CI: 0.44 - 0.65), low-density lipoprotein (n = 31, OR = 1.68, 95% CI: 1.38 - 2.05), triglyceride (n = 31, OR = 3.21, 95% CI: 2.67 - 3.87), alanine aminotransferase (n = 26, OR = 4.06, 95% CI: 2.94 - 5.62), aspartate aminotransferase (n = 27, OR = 2.16, 95% CI: 1.50 - 3.12), hypertension (n = 13, OR = 2.53, 95% CI: 2.32 - 2.77), systolic blood pressure (n = 13, OR = 1.83, 95% CI: 1.53 - 2.18), diastolic blood pressure (n = 14, OR = 1.80, 95% CI: 1.48 - 2.20), fasting blood sugar (n = 31, OR = 2.91, 95% CI: 2.11- 4.01), homeostatic model assessment for insulin resistance (n = 5, OR = 1.92, 95% CI: 1.48 - 2.59), diabetes mellitus (n = 15, OR = 3.04, 95% CI: 2.46 - 3.75), metabolic syndrome (n = 10, OR = 3.56, 95% CI: 2.79 - 4.55), and physical activity (n = 11, OR = 0.32, 95% CI: 0.24 - 0.43) (P < 0.05). Conclusions: In conclusion, several factors are significantly associated with NAFLD. However, anthropometric indices had the strongest relationship with NAFLD in the Iranian adult population.

Correlation between CT Abdominal Anthropometric Measurements and Liver Density in Individuals with Non-Alcoholic Fatty Liver Disease

Background: With a growing frequency, nonalcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease worldwide. NAFLD has a strong correlation with other metabolic disorders, such as obesity, particularly abdominal obesity, even though the underlying causes or risk factors are not entirely understood. This study aims to investigate correlations between abdominal anthropometric measurements and the presence and intensity of liver steatosis as assessed by unenhanced computed tomography (CT). Methods: One hundred and nineteen patients (male/female, 66/53; mean age 54.54 +/− 12.90 years) underwent abdominal non–contrast-enhanced CT. CT images were examined to determine the attenuation of liver parenchyma, subcutaneous fat depth, and waist circumference (WC). Results: Among all patients, WC (r = −0.78, p < 0.0001), infraumbilical subcutaneous fat thicknesses (r = −0.51, p < 0.0001), right paraumbilical subcutaneous fat thicknesses (r = −0.62, p < 0.0001), and left paraumbilical subcutaneous fat thicknesses (r = −0.53, p < 0.0001) had a high inverse correlation with the liver attenuation values. The presence of T2D (OR: 2.40, p = 0.04), WC (OR: 11.45, p < 0.001), right paraumbilical (OR: 10.09, p < 0.001), left paraumbilical (OR: 2.81, p = 0.01), and infraumbilical (OR: 3.06, p = 0.007) were strongly independent predictors of NAFLD risk. Moreover, regarding the laboratory parameters, only the higher value of GGT (OR: 2.84, p = 0.009) is a predictor of NAFLD risk. Conclusions: Our data show that higher baseline values of all abdominal anthropometric measurements are correlated with liver attenuation and act as predictors of NAFLD risk.

The association of dietary inflammatory index (DII) and central obesity with non-alcoholic fatty liver disease (NAFLD) in people with diabetes (T2DM)

Background & Objective

High prevalence of non-alcoholic fatty liver disease (NAFLD) in patients with type 2 diabetes mellitus results in deleterious complications and morbidities related to both diseases. Thus, we aimed to investigate dietary and anthropometric risk factors for progression of Non-alcoholic Fatty Liver Disease (NAFLD) in diabetic people.

Methods

Anthropometric, and dietary intakes, and hepatic steatosis and fibrosis were assessed in two hundred participants with type two diabetes (T2DM). Subjects with CAP score of more than 270 dB/m were considered to have NAFLD. Multivariable-adjusted ORs and 95% CIs were used to investigate the association between NAFLD and dietary inflammatory index (DII) score and anthropometric indices.

Results

Participants in the highest tertile of DII had 2.41 (95% CI:1.16-4.97), 2,53 (95% CI: 1.04-6.16), 2.78 (95% CI: 1.09-7.13) times higher odds of developing NAFLD in comparison to the lowest tertile in crude, adjusted model 1 and 2, respectively. Among those with the highest relative to the lowest tertile of trunk-to-leg fat ratio (TLR), ORs and 95% CI were OR = 1.88, 95% CI = 0.9-3.91, and OR = 7.99, 95% CI = 2.43-26.26 in crude and full-adjusted models. Odds of NAFLD in the third tertile of metabolic score for visceral fat (METS-VF) was higher than the first tertile in crude (OR = 9.5, 95% CI = 4.01-22.46) and full-adjusted models (OR = 4.55, 95% CI = 1.46-14.2).

Conclusions

In conclusion, this study highlighted an association between greater DII (pro-inflammatory diet) and higher NAFLD risk. Moreover, TLR and METS-VF are known as novel estimators of central obesity as a risk factor for NAFLD in diabetes.

The value of combining the simple anthropometric obesity parameters, Body Mass Index (BMI) and a Body Shape Index (ABSI), to assess the risk of non-alcoholic fatty liver disease

Background

Body mass index (BMI) and A Body Shape Index (ABSI) are current independent risk factors for non-alcoholic fatty liver disease (NAFLD). The aim of this study was to explore the value of combining these two most common obesity indexes in identifying NAFLD.

Methods

The subjects in this study were 14,251 individuals from the NAfld in the Gifu Area, Longitudinal Analysis (NAGALA) cohort who underwent routine health examination. We integrated BMI with WC and with ABSI to construct 6 combined obesity indicators—obesity phenotypes, the combined anthropometric risk index (ARI) for BMI and ABSI, optimal proportional combination O_BMI+WC and O_BMI+ABSI, and multiplicative combination BMI*WC and BMI*ABSI. Several multivariable logistic regression models were established to evaluate the relationship between BMI, WC, ABSI, and the above six combined indicators and NAFLD; receiver operating characteristic (ROC) curves were drawn to compare the ability of each obesity indicator to identify NAFLD.

Results

A total of 2,507 (17.59%) subjects were diagnosed with NAFLD. BMI, WC, ABSI, and all other combined obesity indicators were significantly and positively associated with NAFLD in the current study, with BMI*WC having the strongest correlation with NAFLD in female subjects (OR per SD increase: 3.13) and BMI*ABSI having the strongest correlation in male subjects (OR per SD increase: 2.97). ROC analysis showed that ARI and O_BMI+ABSI had the best diagnostic performance in both sexes, followed by BMI*WC (area under the curve: female 0.8912; male 0.8270). After further age stratification, it was found that ARI and multiplicative indicators (BMI*WC, BMI*ABSI) and optimal proportional combination indicators (O_BMI+WC, O_BMI+ABSI) significantly improved the NAFLD risk identification ability of the basic anthropometric parameters in middle-aged females and young and middle-aged males.

Conclusion

In the general population, BMI combined with ABSI best identified obesity-related NAFLD risk and was significantly better than BMI or WC, or ABSI. We find that ARI and the multiplicative combined indicators BMI*WC and BMI*ABSI further improved risk prediction and may be proposed for possible use in clinical practice.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-022-01717-8.

Associations between neck circumference and markers of dysglycemia, non-alcoholic fatty liver disease, and dysmetabolism independent of Body Mass Index in an Emirati population

AIM

Neck circumference (NC) is quick and easy to measure and may be a useful surrogate marker for body composition. We investigated NC as a potential marker of dysglycemia, MetS, and NAFLD.

METHODS

674 individuals were recruited at the Imperial College London Diabetes Centre in a study of sleep apnea prevalence. Of these, 547 (Age 46 ± 11.4 years, Body Mass Index (BMI) 31 ± 6 kg/m², 279 (51%) female, 113 normal glucose tolerance (NGT), 108 Prediabetes, 326 Type 2 diabetes (T2DM)) met all inclusion criteria for analysis. NC was measured at the thyroid cartilage, and collar size was recorded. Analysis was performed using univariate and multivariate linear regression.

RESULTS

Adjusted for BMI, sex, and age, NC was 0.65 ± 0.3 cm greater in prediabetes (p = 0.0331), and 1.07 ± 0.28 cm greater in T2DM, compared with NGT (p = 0.0002). Adjusting for BMI, sex, and glycemic status, 1-cm increase in NC was associated with a 1.04 ± 1.01 U/L (p <0.0001) increase in ALT and, additionally, correcting for statin use, a 0.03 ± 0.01 mmol/L reduction in HDL (p <0.0001) and a 0.1 ± 0.02 increase in TC : HDL. A 1 cm increase in NC was associated with a 1.15 ± 1.02% (p <0.0001) increase in 10-year AHA cardiovascular risk in individuals over 40 years old and a 0.16 ± 0.02 (p <0.0001) increase in NAFLD fibrosis score. The neck circumference was associated with the hazard of new onset of deranged ALT adjusted for age, sex, glycemic status, and BMI (hazard ratio 1.076 (95% CI 1.015-1.14, p = 0.0131) and with the incidence of Fatty Liver Index associated with high probability of NAFLD (hazard ratio 1.153 (95% CI 1.019-1.304), p = 0.0239).

CONCLUSION

NC is associated with dysglycemia, components of the MetS, and factors predictive of NAFLD, but does not appear to independently predict subsequent progression to high risk of liver fibrosis in this predominantly diabetic population.

Correlation Between Sex Hormones and Non-alcoholic Fatty Liver Disease Before and After Laparoscopic Sleeve Gastrectomy

OBJECTIVES

To investigate the cross-sectional and longitudinal correlation between sex hormones and non-alcoholic fatty liver disease (NAFLD) in patients with obesity before and after laparoscopic sleeve gastrectomy (LSG).

METHODS

A total of 360 patients with obesity aged 16-48 years (170 men and 190 women) were enrolled between May 2017 and March 2021. Among them, 132 patients (55 men and 77 women) who underwent LSG had follow-up data. Anthropometric parameters, metabolic variables, and sex hormones were measured. NAFLD was assessed by FibroScan with controlled attenuation parameter (CAP) and liver stiffness measurement (LSM).

RESULTS

In the preoperative cohort, levels of CAP and LSM were significantly higher in men than women. Lower total testosterone (TT) was associated with higher CAP and LSM in men, whereas higher TT was associated with higher CAP in women. In the postoperative cohort, TT levels and NAFLD were significantly modified after LSG in both genders. Changes in TT levels at 3 months after surgery were negatively correlated with changes in CAP levels in men, and changes in TT levels at 6 months after surgery were positively correlated with changes in CAP levels in women. After adjusting possible confounders, the changes in TT levels were independently correlated with CAP variation in both genders.

CONCLUSIONS

LSG significantly modified TT levels and NAFLD in both genders. The correlation between TT levels and NAFLD at baseline as well as the changes after surgery suggested TT levels play an important role in the development and regression of NAFLD in both genders.