Non-alcoholic fatty liver disease (NAFLD) is a significant public health concern worldwide with a complex etiology attributed to behavioural, environmental, and genetic causes. The worldwide prevalence of NAFLD is estimated to be 32.4% and constantly rising. Global data, however, indicate considerable heterogeneity among studies for both NAFLD prevalence and incidence. Identifying variables that affect the estimated epidemiological measures is essential to all stakeholders, including patients, researchers, healthcare providers, and policymakers. Besides helping with the research on disease etiology, it helps to identify individuals at risk of the disease, which in turn will outline the focus of the preventive measures and help to fittingly tailor individualized treatments, targeted prevention, screening, or treatment programs. Several studies suggest differences in the prevalence and severity of NAFLD by race or ethnicity, which may be linked to differences in lifestyle, diet, metabolic comorbidity profile, and genetic background, among others. Race/ethnicity research is essential as it can provide valuable information regarding biological and genetic differences among people with similar cultural, dietary, and geographical backgrounds. In this review, we examined the existing literature on race/ethnicity differences in susceptibility to NAFLD and discussed the contributing variables to such differences, including diet and physical activity, the comorbidity profile, and genetic susceptibility. We also reviewed the limitations of race/ethnicity studies in NAFLD.

Nonalcoholic fatty liver disease (NAFLD) is a rising epidemic worldwide and will be the leading cause of cirrhosis, hepatocellular carcinoma, and liver transplant within the next decade. NAFLD is considered as the hepatic manifestation of metabolic syndrome. Behaviors, such as a sedentary lifestyle and consuming a Western diet, have led to substantial challenges in managing NAFLD patients. With no curative pharmaceutical therapies, lifestyle modifications, including dietary changes and exercise, that ultimately lead to weight loss remain the only effective therapy for NAFLD. Multiple diets, including low-carbohydrate, low-fat, Dietary Approaches to Stop Hypertension (DASH), and Mediterranean (MD) diets, have been evaluated. NAFLD patients have shown better outcomes with a modified diet, such as the MD diet, where patients are encouraged to increase the consumption of fruits and vegetables, whole grains, and olive oil. It is increasingly clear that a personalized approach to managing NAFLD patients, based on their preferences and needs, should be implemented. In our review, we cover NAFLD management, with a specific focus on dietary patterns and their components. We emphasize the successful approaches highlighted in recent studies to provide recommendations that health care providers could apply in managing their NAFLD patients.

Background: Acetaminophen overdose is the most common cause of acute liver failure (ALF). Our objective was to develop coding algorithms using administrative data for identifying patients with acetaminophen overdose and hepatic complications. Methods: Patients hospitalized for acetaminophen overdose were identified using population-based administrative data (1995–2004). Coding algorithms for acetaminophen overdose, hepatotoxicity (alanine aminotransferase >1,000 U/L) and ALF (encephalopathy and international normalized ratio >1.5) were derived using chart abstraction data as the reference and logistic regression analyses. Results: Of 1,776 potential acetaminophen overdose cases, the charts of 181 patients were reviewed; 139 (77%) had confirmed acetaminophen overdose. An algorithm including codes 965.4 (ICD-9-CM) and T39.1 (ICD-10) was highly accurate (sensitivity 90% [95% confidence interval 84–94%], specificity 83% [69–93%], positive predictive value 95% [89–98%], negative predictive value 71% [57–83%], c-statistic 0.87 [0.80–0.93]). Algorithms for hepatotoxicity (including codes for hepatic necrosis, toxic hepatitis and encephalopathy) and ALF (hepatic necrosis and encephalopathy) were also highly predictive (c-statistics = 0.88). The accuracy of the algorithms was not affected by age, gender, or ICD coding system, but the acetaminophen overdose algorithm varied between hospitals (c-statistics 0.84–0.98; P = 0.003). Conclusion: Administrative databases can be used to identify patients with acetaminophen overdose and hepatic complications. If externally validated, these algorithms will facilitate investigations of the epidemiology and outcomes of acetaminophen overdose.