Comparison of Carotid Intima-Media Thickness in Children and Adults With and Without Obesity: A Hysteresis Model.

OBJECTIVE: To describe a third-degree polynomial function (hysteresis) of the effect size of age, obesity, and insulin sensitivity over the carotid intima-media thickness (c-IMT), in the pediatric and adult groups. METHODS: A quasi-experimental study with fixed factor analysis of age (children aged 8-12 years, n = 73; adults aged 21-45 years, n = 82) and obesity (yes, n = 76; no, n = 79) was conducted to analyze the effect on the c-IMT and Matsuda insulin sensitivity index values. This quasi-experimental design was analyzed with robust regression modeling. RESULTS: The additive effect of obesity, independent of age, was evident in the case of the c-IMT values. There was no interaction effect, but a significant difference between participants with normal weight and those with obesity was found (P < .0001). The difference between adults and children was also significant, but the effect size was smaller. A model was created based on age, Tanner stage, and obesity using the c-IMT and Matsuda insulin sensitivity index values. A linear function fit as R2, and the cubic function estimated parameters like a polynomial model. CONCLUSION: This practical study design showed that children with obesity displayed the same levels of carotid intima-media abnormalities as adults with obesity. The polynomial shape of the model suggests potentially poor outcomes that resemble the hysteresis process and may predict chronic cardiometabolic events during early adulthood.

Gender-specific differences in clinical and metabolic variables associated with NAFLD in a Mexican pediatric population.

INTRODUCTION AND OBJECTIVES: Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease in children and it is more prevalent in Hispanic males. The gender differences can be explained by body fat distribution, lifestyle, or sex hormone metabolism. We evaluated anthropometric and metabolic differences by gender in children with and without NAFLD. METHODS: We included 194 participants (eutrophic, overweight, and individuals with obesity). The presence of NAFLD was determined using ultrasonography, and we evaluated the association between this disease with metabolic and anthropometric variables by gender. RESULTS: The mean age was 10.64±2.54 years. The frequency of NAFLD in boys was 24.51% and in girls was 11.96% (OR=2.39; 95%CI=1.10-5.19; p=0.025). For girls, NAFLD was significantly associated with triglycerides (p=0.012), homeostatic model assessment of insulin resistance (HOMA-IR) (p=0.048), and the visceral adiposity index (VAI) (p=0.024). The variables related to NAFLD in a gender-specific manner were body mass index (BMI) (p=0.001), waist circumference (WC) (p<0.001), HDL cholesterol (p=0.021), alanine aminotransferase (ALT) (p<0.001), and aspartate aminotransferase (AST) (p=0.002). CONCLUSIONS: In our study NAFLD is more frequent in boys, only ALT, and no other clinical or metabolic variables, were associated with NAFLD in these patients. HOMA-IR, VAI, triglyceride levels, and ALT were associated with NAFLD only in girls. The ALT cut-off points for the development of NAFLD in our study were 28.5U/L in females and 27.5U/L in males. Our findings showed that NAFLD should be intentionally screened in patients with obesity, particularly in boys.

Correction: Family history and obesity in youth, their effect on acylcarnitine/aminoacids metabolomics and non-alcoholic fatty liver disease (NAFLD). Structural equation modeling approach.

[This corrects the article DOI: 10.1371/journal.pone.0193138.].

Family history and obesity in youth, their effect on acylcarnitine/aminoacids metabolomics and non-alcoholic fatty liver disease (NAFLD). Structural equation modeling approach.

BACKGROUND: Structural equation modeling (SEM) can help understanding complex functional relationships among obesity, non-alcoholic fatty liver disease (NAFLD), family history of obesity, targeted metabolomics and pro-inflammatory markers. We tested two hypotheses: 1) If obesity precedes an excess of free fatty acids that increase oxidative stress and mitochondrial dysfunction, there would be an increase of serum acylcarnitines, amino acids and cytokines in obese subjects. Acylcarnitines would be related to non-alcoholic fatty disease that will induce insulin resistance. 2) If a positive family history of obesity and type 2 diabetes are the major determinants of the metabolomic profile, there would be higher concentration of amino acids and acylcarnitines in patients with this background that will induce obesity and NAFLD which in turn will induce insulin resistance. METHODS/RESULTS: 137 normoglycemic subjects, mean age (SD) of 30.61 (8.6) years divided in three groups: BMI<25 with absence of NAFLD (G1), n = 82; BMI>30 with absence of NAFLD (G2), n = 24; and BMI>30 with NAFLD (G3), n = 31. Family history of obesity (any) was present in 53%. Both models were adjusted in SEM. Family history of obesity predicted obesity but could not predict acylcarnitines and amino acid concentrations (effect size <0.2), but did predict obesity phenotype. CONCLUSION: Family history of obesity is the major predictor of obesity, and the metabolic abnormalities on amino acids, acylcarnitines, inflammation, insulin resistance, and NAFLD.

Nonalcoholic fatty liver disease can be predicted by retinal vascular changes in patients with obesity without hypertension or diabetes.

OBJECTIVE: To evaluate the utility of predicting nonalcoholic fatty liver disease (NAFLD) and obesity by retinal vascular changes (RVC) found in fundoscopy and to determine whether this is related to a low-grade inflammatory process. METHODS: We carried out a cross-sectional analysis that included 152 (ages 18-45 years) patients divided into four groups: NAFLD and BMI less than 25, absence of NAFLD and BMI less than 25, NAFLD and BMI more than 30, and absence of NAFLD and BMI more than 30. Retinal fundoscopy, hepatic ultrasound, metabolic profile, and cytokine measurement were performed. We calculated odds ratio [95% confidence interval (CI)], performed diagnostic utility tests, and carried out a 2 factorial analysis. RESULTS: Obesity was associated with RVC (odds ratio: 21.25; 95% CI: 8.79-51.4) and NAFLD [25 (9.07-72.6)]. NAFLD was associated with RVC [11.24 (4.98-26.48)], and the prediction of NAFLD showed a sensitivity of 75% (95% CI: 68-82) and a specificity of 81% (75-86); when RVC-obesity were combined, sensitivity increased to 90% (88-91.7), with a specificity of 85% (84-85.8). C-reactive protein was associated with the three factors, suggesting an independent contribution. Thin patients with RVC and NAFLD had higher concentrations of interleukin-2, interleukin-6, tumor necrosis factor-α, and interferon-γ. CONCLUSION: NAFLD in patients with obesity without diabetes or hypertension can be predicted by RVC, a noninvasive technique carried out by eye fundoscopy. NAFLD alone can drive inflammatory conditions in the absence of obesity that manifests as RVC.