Pediatric obesity-related non-alcoholic fatty liver disease: waist-to-height ratio best anthropometrical predictor

Analysis of risk factors for fatty liver disease in children with Wilson's disease

BACKGROUND AND AIMS

Many children with Wilson's disease are complicated with dyslipidemia. The aim of this study was to investigate the risk factors for the development of fatty liver disease (FLD) in children with Wilson's disease.

METHODS

We evaluated sex, age, weight, the disease course, treatment course, clinical classification, alanine transaminase (ALT), aspartate transaminase, γ-glutamyl transpeptidase, total biliary acid, triglyceride, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, homocysteine, uric acid, fibrinogen (FBG), creatinine, procollagen III N-terminal propeptide, laminin, hyaluronic acid, type IV collagen, and performed receiver operating characteristic curve analysis to investigate the forecast value of individual biochemical predictors and combined predictive indicators to evaluate FLD in Wilson's disease.

RESULTS

The multivariate logistic regression analysis revealed that ALT [odds ratio (OR), 1.011; 95% confidence interval (CI), 1.004-1.02; P  = 0.006], uric acid (OR, 1.01; 95% CI, 1.002-1.018; P  = 0.017), FBG (OR, 3.668; 95% CI, 1.145-13.71; P  = 0.037), creatinine (OR, 0.872; 95% CI, 0.81-0.925; P  < 0.001), and laminin (OR, 1.01; 95% CI, 1.002-1.018; P  = 0.017) acted as independent risk factors in Wilson's disease complicated with FLD. The receiver operating characteristic curves for combined predictive indicators demonstrated an area under the curve values of 0.872, which was found to be a significant predictors for FLD in Wilson's disease.

CONCLUSIONS

We screened out the most important risk factors, namely ALT, uric acid, creatinine, FBG, and laminin for Wilson's disease complicated with FLD. The joint prediction achieved is crucial for identifying children with Wilson's disease complicated with FLD.

Evaluation of the ability of insulin resistance and lipid-related indices to predict the presence of NAFLD in obese adolescents

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) has become an important health issue in adolescents. Although several parameters and indices have been investigated for the evaluation of NAFLD in adults, these indices are limited in adolescents. In this study, body mass index, waist circumference, triponderal mass index, HbA1c, homeostatic model assessment insulin resistance (HOMA-IR), triglyceride/high-density lipoprotein (Tg/HDL), the lipid accumulation product (LAP) index, the triglyceride-glucose (TyG) index and the aminotransferase (AT) index were examined together, and their diagnostic values in the clinical treatment of NAFLD were compared.

MATERIALS AND METHODS

Seventynine adolescents (10-19 years old) with obesity who were admitted to a pediatric clinic between January and August 2022 and who were diagnosed with exogenous obesity without any comorbidities were included in the study. The presence of NAFLD was evaluated by liver magnetic resonance imaging. The laboratory findings were obtained retrospectively from system records. Parameters were compared between the NAFLD (+) and NAFLD (-) groups. Logistic regression analysis was used to determine the most effective factors for NAFLD treatment. Receiver operating characteristic (ROC) analysis was performed with significant indices. Sex, HOMA-IR, TyG and AT indices were evaluated together with multivariate analysis to design a diagnostic scale.

RESULTS

HbA1c, HOMA-IR, AT indices and TyG indices were greater in the NAFLD (+) group (P = 0.012; P = 0.001; P = 0.012; P = 0.002, respectively). There was a positive correlation between liver fat percentage and HOMA-IR, the TyG index, the AT index, and Tg/HDL. According to the regression analysis, male sex and elevated HOMA-IR were determined to be significant risk factors for the presence of NAFLD. A probability scale with 4 parameters [sex, HOMA-IR, the TyG index, and alanine aminotransferase (ALT)] was designed with 82.5% specificity and 80% sensitivity.

CONCLUSION

Evaluation of the HOMA-IR and TyG indices, especially in high-risk patients, will support the diagnosis of NAFLD via ultrasonography. A probability scale with ALT, HOMA-IR, TyG, and sex data with a diagnostic accuracy of 80% may aid in the diagnosis of NAFLD in adolescents with obesity.

An interpretable predictive deep learning platform for pediatric metabolic diseases

OBJECTIVES

Metabolic disease in children is increasing worldwide and predisposes a wide array of chronic comorbid conditions with severe impacts on quality of life. Tools for early detection are needed to promptly intervene to prevent or slow the development of these long-term complications.

MATERIALS AND METHODS

No clinically available tools are currently in widespread use that can predict the onset of metabolic diseases in pediatric patients. Here, we use interpretable deep learning, leveraging longitudinal clinical measurements, demographical data, and diagnosis codes from electronic health record data from a large integrated health system to predict the onset of prediabetes, type 2 diabetes (T2D), and metabolic syndrome in pediatric cohorts.

RESULTS

The cohort included 49 517 children with overweight or obesity aged 2-18 (54.9% male, 73% Caucasian), with a median follow-up time of 7.5 years and mean body mass index (BMI) percentile of 88.6%. Our model demonstrated area under receiver operating characteristic curve (AUC) accuracies up to 0.87, 0.79, and 0.79 for predicting T2D, metabolic syndrome, and prediabetes, respectively. Whereas most risk calculators use only recently available data, incorporating longitudinal data improved AUCs by 13.04%, 11.48%, and 11.67% for T2D, syndrome, and prediabetes, respectively, versus models using the most recent BMI (P < 2.2 × 10-16).

DISCUSSION

Despite most risk calculators using only the most recent data, incorporating longitudinal data improved the model accuracies because utilizing trajectories provides a more comprehensive characterization of the patient's health history. Our interpretable model indicated that BMI trajectories were consistently identified as one of the most influential features for prediction, highlighting the advantages of incorporating longitudinal data when available.

Which obesity index is the most useful marker for predicting hepatic steatosis in children and adolescents with obesity? A cross-sectional study using quantitative magnetic resonance imaging

INTRODUCTION

We aimed to evaluate the relationships between hepatic steatosis and various indices of obesity, and to identify the most useful index for the prediction of hepatic steatosis in children and adolescents with obesity.

METHODS

A total of 226 children and adolescents with a mean body mass index (BMI) z-score of 2.65 and a mean age of 11.4 years were subjected to anthropometric and body composition measurements, laboratory testing, abdominal fat mass assessment, and hepatic fat accumulation by magnetic resonance imaging-derived proton density fat fraction (MRI-PDFF). The participants were divided into quartiles according to the severity of their hepatic steatosis, and the presence of hepatic steatosis was defined using an MRI-PDFF ≥ 5%.

RESULTS

The multivariate ordinal regression analysis showed that the severity of hepatic steatosis was positively associated with BMI, waist circumference, waist-to-hip ratio, waist-to-height ratio, fat mass, fat-free mass, visceral adiposity, and abdominal subcutaneous adiposity. Higher activities of liver enzymes and higher concentrations of triglyceride, C-reactive protein, fasting insulin, and leptin were associated with more severe hepatic steatosis, whereas high-density lipoprotein-cholesterol and adiponectin were negatively associated with hepatic steatosis. The indices of obesity with areas under the receiver operating characteristic curves (AUCs) > 0.8 for the prediction of hepatic steatosis were liver enzymes, visceral adipose tissue area, waist-to-hip ratio, and waist-to-height ratio.

CONCLUSION

The severity of hepatic steatosis significantly correlated with various indices of obesity and cardiometabolic markers in children and adolescents with obesity. The indices of abdominal obesity would be the most useful for the prediction of hepatic steatosis.

Dietary fiber intake and non-alcoholic fatty liver disease: The mediating role of obesity

Background and aims

Dietary pattern rich in fiber is negatively associated with the risk of non-alcoholic fatty liver disease (NAFLD). Meanwhile, obesity is a known predisposing factor for NAFLD. Nutrient-focused research can enhance the mechanistic understanding of dietary effects. We thus hypothesized that higher dietary fiber intake was associated with lower risk of NAFLD through the mediating role of obesity.

Methods

In this nationwide cross-sectional study, dietary fiber was surveyed using two 24-h recalls. NAFLD and clinically significant fibrosis (CSF) were determined by vibration-controlled transient elastography. Multivariable logistic and linear regression were applied to investigate the association of dietary fiber with NAFLD, CSF, and liver function parameters. We used counterfactual-based mediation analysis to estimate the direct and indirect effect of dietary fiber on NAFLD.

Results

Of the 3,974 participants, ~36.86% and 7.78% of participants were diagnosed with NAFLD and CSF. Compared with participants among the lowest tertile, the highest tertile of dietary fiber consumption was associated with lower odds of NAFLD (OR = 0.81; 95% CI: 0.66-0.98; P _overall = 0.019). Dietary fiber intake appeared to be linked with lower odds of CSF (OR _{Tertile3vs.Tertile1} = 0.81; 95% CI: 0.58-1.14; P _overall = 0.107). Mediation analysis showed that obesity fully mediated the association of dietary fiber with NAFLD. Dietary fiber was associated with improved hepatic parameters.

Conclusions

The findings indicated that increasing dietary fiber intake could confer a greater benefit to protect against NAFLD. Translating these findings regarding dietary fiber into dietary advice might be an attractive strategy for NAFLD prevention.

Discriminatory capacity of obesity indicators as predictors of high liver fat in US adolescents

BACKGROUND

The aims of this study were to assess the potential of 16 anthropometric, body composition and endocrine indexes as predictors of high liver fat and determine the most appropriate cut-off points in US adolescents.

METHODS

A cross-sectional study was conducted on a population of 816 adolescents aged 12-17 years. The FibroScan^® 502V2 device was used to estimate the controlled attenuation parameter (CAP). Body fat percentage, fat mass, trunk fat percentage and trunk fat mass were measured by dual-energy X-ray absorptiometry. Anthropometric data and metabolic parameters were determined. Receiver operating characteristic curves were analysed to estimate the optimal cut-off points that best identify adolescents with high liver fat (CAP ≥90th percentile).

RESULTS

In boys, triponderal mass index (TMI) had the highest area under curve (AUC) value (0.865) and the optimal cut-off score for TMI was 17.47 kg/m³ , which had 81.32 sensitivity and 82.99 specificity. In girls, trunk fat index (TFI) had the highest AUC value (0.826) and its optimal cut-off score in screening for high liver fat was 3.76 kg/m² , which had 74.04 sensitivity and 88.03 specificity. Fat mass index (FMI) index had the second highest AUC values (0.863 in boys 0.812 in girls) in both sex; the cut-off point for the detection of high liver fat was <8.66 kg/m² for girls and <7.45 kg/m² for boys.

CONCLUSION

Assessment of TMI in boys, TFI in girls, and FMI in both sexes are low-cost and easy-to-use parameters that may be useful as early screening tools for possible high liver fat in adolescents.

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

OBJECTIVE

Increasing evidence suggests that an increased waist-to-height ratio (WHtR) may increase the risk of non-alcoholic fatty liver disease (NAFLD). Whether this association is due to WHtR itself or mediated by WHtR-associated increases in triglyceride (TG) is uncertain. On that account, our research aims to disentangle these relationships.

METHODS

In this cross-sectional study, 14251 participants who participated in the medical examination program were consecutively and non-selectively collected in Murakami Memorial Hospital in Japan from 2004 to 2015. The independent and dependent variables were WHtR and NAFLD, respectively. Triglyceride was the mediating factor. The correlation between WHtR, TG, and NAFLD risk factors was examined using spearman correlation analysis. The association between WHtR or TG and NAFLD was examined using multiple logistic regression. In order to determine whether TG mediated the association between WHtR and NAFLD, a mediation analysis was performed.

RESULTS

The mean age of the included individuals was 43.53 ± 8.89 years old, and 7411 (52.00%) were male. The mean WHtR and TG were 0.46 ± 0.05, 0.89 ± 0.63, respectively. The prevalence rate of NAFLD was 2507 (17.59%). Individuals with NAFLD had significantly higher levels of WHtR and TG than those without NAFLD (P&lt;0.05). After adjusting covariates, the multivariate linear regression analysis showed that WHtR was positively associated with TG. That was, for every 0.1 increase in WHtR, TG increased by 0.226mmol/L (β=0.226, 95%CI: 0.206, 0.247). Multiple logistic regression analysis indicated that WHtR (OR=8.743, 95%CI: 7.528, 10.153) and TG (OR=1.897, 95%CI: 1.732, 2.078) were positively associated with NAFLD. The mediation analysis showed that WHtR had a direct, significant effect on NAFLD (β=0.139, 95%CI: 0.126, 0.148), and TG partially mediated the indirect effect of WHtR on NAFLD (β=0.016, 95% CI: 0.013-0.019). TG contributed to 10.41% of WHtR-related NAFLD development.

CONCLUSION

Findings suggest a mediation link between WHtR and TG and the risk of NAFLD. The significance of TG as a mediator deserves recognition and consideration.

Clinical spectrum transition and prediction model of nonalcoholic fatty liver disease in children with obesity

OBJECTIVE

This study aims to outline the clinical characteristics of pediatric NAFLD, as well as establish and validate a prediction model for the disease.

MATERIALS AND METHODS

The retrospective study enrolled 3216 children with obesity from January 2003 to May 2021. They were divided into obese without NAFLD, nonalcoholic fatty liver (NAFL), and nonalcoholic steatohepatitis (NASH) groups. Clinical data were retrieved, and gender and chronologic characteristics were compared between groups. Data from the training set (3036) were assessed using univariate analyses and stepwise multivariate logistic regression, by which a nomogram was developed to estimate the probability of NAFLD. Another 180 cases received additional liver hydrogen proton magnetic resonance spectroscopy (1H-MRS) as a validation set.

RESULTS

The prevalence of NAFLD was higher in males than in females and has increased over the last 19 years. In total, 1915 cases were NAFLD, and the peak onset age was 10-12 years old. Hyperuricemia ranked first in childhood NAFLD comorbidities, followed by dyslipidemia, hypertension, metabolic syndrome (MetS), and dysglycemia. The AUROC of the eight-parameter nomogram, including waist-to-height ratio (WHtR), hip circumference (HC), triglyceride glucose-waist circumference (TyG-WC), alanine aminotransferase (ALT), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A1(ApoA1), insulin sensitivity index [ISI (composite)], and gender, for predicting NAFLD was 0.913 (sensitivity 80.70%, specificity 90.10%). Calibration curves demonstrated a great calibration ability of the model.

CONCLUSION AND RELEVANCE

NAFLD is the most common complication in children with obesity. The nomogram based on anthropometric and laboratory indicators performed well in predicting NAFLD. This can be used as a quick screening tool to assess pediatric NAFLD in children with obesity.

Nonalcoholic fatty liver disease in children with obesity- observations from one clinical centre in the Western Pomerania region

Nonalcoholic fatty liver disease (NAFLD) is a growing health problem in the pediatric population, due to the constantly increasing percentage of children with obesity. The objective of the study was to assess the occurrence of NAFLD based on ultrasound (USG) analysis and the use of alanine aminotransferase (ALT) in children with overweight and obesity depending on glucose tolerance. Medical records of 228 consecutive patients aged 2-18 years with overweight and obesity were reviewed retrospectively. Based on the oral glucose tolerance test children were divided into groups according to the severity of carbohydrate metabolism disorders. ALT, lipid parameters and insulin sensitivity indices HOMA, Matsuda and Quicki were analyzed. NAFLD was diagnosed (based on the USG) in 51 patients (23.61%) - the incidence in the impaired glucose tolerance (IGT) and type 2 diabetes (T2DM) group was significantly higher when compared to ones without glucose intolerance. Because of extreme values of metabolic parameters in TDM2 children being outliers, they were not considered in the statistical analysis of the study. 22 (11.58%) patients had elevated ALT values, of which 12 (54.55%) had hepatic steatosis features on ultrasound. 72.73% (n=32) patients with fatty liver features on USG had ALT values considered normal with cut-off point 42 U/l accepted in this study. Almost every fourth obese child in the study group presents features of fatty liver in ultrasound examination. Although ultrasound is not recommended by North American Society For Pediatric Gastroenterology, Hepatology &Nutrition(NASPGHAN) for the diagnosis of NAFLD in children, it allows identifying a high percentage of children with features of fatty liver. This percentage increases significantly in children with glucose intolerance.

A Mini-Review of Pediatric Anthropometrics as Predictors of Future Insulin Resistance

The impact of rising rates of childhood obesity is far reaching. Metabolic syndrome in children is increasing, yet for most children the consequences of excess adiposity will manifest in adulthood. Excess early fat accrual is a risk factor for future insulin resistance. However, certain types of fat and patterns of fat distribution are more relevant than others to metabolic risk. Therefore, adiposity measures are important. The link between childhood obesity and future insulin resistance was initially established with body mass index (BMI), but BMI is an in imperfect measure of adiposity. It is worthwhile to evaluate other anthropometrics as they may more accurately capture metabolic risk. While measures such as waist to height ratio are established as superior screening measures in adulthood - the findings are not as robust in pediatrics. Emerging evidence suggests that alternative anthropometrics may be slightly superior to BMI in identifying those youth most at risk of developing insulin resistance, but the clinical significance of that superiority appears limited. Increasing study is needed in longitudinal and varied cohorts to identify which pediatric anthropometric best predicts adult insulin resistance. We review alternative anthropometrics as predictors of future insulin resistance and identify current gaps in knowledge and potential future directions of inquiry.

Bikes for Life: Measuring the effects of a bicycle distribution program on 6 to 12-year-old children's BMI and health behaviors

Treating pediatric obesity is challenging. The objective was to evaluate effect of receiving a bicycle on (a) physical activity, (b) sedentary activity, (c) Body Mass Index (BMI), and (d) eating habits. A stepped-wedge randomized controlled trial of 6- to 12-year-old patients with overweight/obesity was conducted April 2012-2018. Participants were randomized to wait 0, 2, 4, or 6 months for a bicycle. Outcomes on activity, BMI and eating were collected at 3, 6, 9- and 12-months after children received a bicycle. A total of 525 participants with 387 (74%) completed 3-month follow-up questionnaire, and 346 (66%) completed 12-month follow-up visit. Participants were mostly Latino/a (71%) and low income (58%), and 31% had never ridden a bicycle. Median baseline BMI was 98th percentile. At 3 months, 62% reported bicycle use last week, on average 3.6 days. Time spent on sedentary activities decreased by 48 min/day (p = 0.04), and time spent playing sports increased by 1.7 h/week (p < 0.01). No reduction in BMI was seen. Consumption of sugary drinks decreased (by 0.59 servings/week, p < 0.01), and consumption of vegetables increased (0.71 servings/week, p = 0.04). At 12 months, sedentary time, sugary drink and vegetable consumption remained significantly more favorable than at enrollment (p < 0.01, p < 0.01, p = 0.04 respectively), but not significantly different (p = 0.47 for sedentary, p = 0.73 for sugary drink) and significantly less favorable (p < 0.01 for vegetables) than at the time of intervention. Participants reported riding bicycle, improved activity and dietary habits, though reversion towards baseline behavior was seen by one year and no change in BMI from enrollment.

Tri-Ponderal Mass Index as a Screening Tool for Identifying Body Fat and Cardiovascular Risk Factors in Children and Adolescents: A Systematic Review

Because of the limitation of body mass index (BMI) in distinguishing adipose mass from muscle, the tri-ponderal mass index (TMI) has been proposed as a new indicator for better assessing adiposity in children and adolescents. However, it remains unclear whether TMI performs better than BMI or other adiposity indices in predicting obesity status in childhood and obesity-related cardiovascular risk factors (CVRFs) in childhood or adulthood. We searched PubMed, Cochrane Library, and Web of Science for eligible publications until June 15, 2021. A total of 32 eligible studies were included in this systematic review. We found that TMI had a similar or better ability to predict body fat among children and adolescents than BMI. However, most of the included studies suggested that TMI was similar to BMI in identifying metabolic syndrome although TMI was suggested to be a useful tool when used in combination with other indicators (e.g., BMI and waist circumference). In addition, limited evidence showed that TMI did not perform better than BMI for identifying specific CVRFs, including insulin resistance, high blood pressure, dyslipidemia, and inflammation in children and adolescents, as well as CVRFs in adults.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero, CRD42021260356.