Population-based risk factors for elevated alanine aminotransferase in a South Texas Mexican-American population

Background and aims: Elevated alanine aminotransferase (ALT \u3e40 IU/mL) is a marker of liver injury but provides little insight into etiology. We aimed to identify and stratify risk factors associated with elevated ALT in a randomly selected population with a high prevalence of elevated ALT (39%), obesity (49%) and diabetes (30%). Methods: Two machine learning methods, the support vector machine (SVM) and Bayesian logistic regression (BLR), were used to capture risk factors in a community cohort of 1532 adults from the Cameron County Hispanic Cohort (CCHC). A total of 28 predictor variables were used in the prediction models. The recently identified genetic marker rs738409 on the PNPLA3 gene was genotyped using the Sequenom iPLEX assay. Results: The four major risk factors for elevated ALT were fasting plasma insulin level and insulin resistance, increased BMI and total body weight, plasma triglycerides and non-HDL cholesterol, and diastolic hypertension. In spite of the highly significant association of rs738409 in females, the role of rs738409 in the prediction model is minimal, compared to other epidemiological risk factors. Age and drug and alcohol consumption were not independent determinants of elevated ALT in this analysis. Conclusions: The risk factors most strongly associated with elevated ALT in this population are components of the metabolic syndrome and point to nonalcoholic fatty liver disease (NAFLD). This population-based model identifies the likely cause of liver disease without the requirement of individual pathological diagnosis of liver diseases. Use of such a model can greatly contribute to a population-based approach to prevention of liver disease

The association of depression and anxiety with glycemic control among Mexican Americans with diabetes living near the U.S.-Mexico border

BACKGROUND: The prevalence of diabetes is alarmingly high among Mexican American adults residing near the U.S.-Mexico border. Depression is also common among Mexican Americans with diabetes, and may have a negative influence on diabetes management. Thus, the purpose of the current study was to evaluate the associations of depression and anxiety with the behavioral management of diabetes and glycemic control among Mexican American adults living near the border. METHODS: The characteristics of Mexican Americans with diabetes living in Brownsville, TX (N = 492) were compared by depression/anxiety status. Linear regression models were conducted to evaluate the associations of depression and anxiety with BMI, waist circumference, physical activity, fasting glucose, and glycated hemoglobin (HbA1c). RESULTS: Participants with clinically significant depression and/or anxiety were of greater age, predominantly female, less educated, more likely to have been diagnosed with diabetes, and more likely to be taking diabetes medications than those without depression or anxiety. In addition, anxious participants were more likely than those without anxiety to have been born in Mexico and to prefer study assessments in Spanish rather than English. Greater depression and anxiety were associated with poorer behavioral management of diabetes (i.e., greater BMI and waist circumference; engaging in less physical activity) and poorer glycemic control (i.e., higher fasting glucose, HbA1c). CONCLUSIONS: Overall, depression and anxiety appear to be linked with poorer behavioral management of diabetes and glycemic control. Findings highlight the need for comprehensive interventions along the border which target depression and anxiety in conjunction with diabetes management