Non-alcoholic fatty liver disease (NAFLD) encompasses a group of hepatic diseases that range in severity. NAFLD is increasingly recognized as an epidemic among different populations, including those in Africa and the Middle East. The objective of this narrative review is to document the prevalence of and risk factors for NAFLD in Africa and the Middle East and the potential implications on the healthcare systems. An in-depth search on Google Scholar, Medline and PubMed was conducted using the terms "non-alcoholic fatty liver disease" and "non-alcoholic steatohepatitis", in addition to "prevalence and risk factors for NAFLD", with special emphasis on Africa and the Middle East countries. There were three types of epidemiological studies that included prevalence, risk factors and management/complications of NAFLD. There was noticeable variation in the prevalence of NAFLD among different countries, based on the variation in the prevalence of risk factors (type 2 diabetes, obesity, metabolic syndrome and dyslipidemia) and the diagnostic tool used in the study. However, the highest prevalence rate was reported in some Middle East countries. In Africa, there were few studies about NAFLD and most reported variable prevalence rates. There is an increasing prevalence of NAFLD as a result of the increasing risk factors, particularly in the Middle East, while in Africa, the situation is still unclear. Health providers in these regions are faced with many challenges that need urgent plans.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5667692 | PMC |
http://dx.doi.org/10.14740/gr913w | DOI Listing |
Sci Rep
December 2024
Department of Applied Mathematics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran.
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran.
No study has examined the association between dietary insulin load (DIL) and insulin index (DII) with developing gestational diabetes mellitus (GDM) during pregnancy. This study aimed to investigate the association between DIL and DII and risk of GDM in a group of pregnant women in Iran. In this prospective cohort study, 812 pregnant in their first trimester were recruited and followed.
View Article and Find Full Text PDFJ Community Psychol
January 2025
Nursing Faculty, Public Health Nursing Department, Atatürk University, Yakutiye Erzurum, Turkey.
This study aimed to investigate the resilience, stress levels, coping styles, and the impact of related factors among nurses working in primary healthcare during the COVID-19 pandemic. Designed as a cross-sectional study, the research included 86 volunteer nurses employed in primary healthcare institutions in Bitlis provincial center and its districts in Turkey. Data were collected between March and June 2022 using a sociodemographic information form, the Resilience Scale for Adults, and the Ways of Coping Questionnaire.
View Article and Find Full Text PDFMycoses
January 2025
Mycology Reference Laboratory, Isfahan University of Medical Sciences, Isfahan, Iran.
Background: Trichophyton indotineae, formerly described as T. mentagrophytes rDNA-ITS genotype VIII, has recently been identified as a novel species within the T. mentagrophytes complex.
View Article and Find Full Text PDFClin Transplant
January 2025
Rehabilitation Research Center (REVAL), Faculty of Rehabilitation Sciences, Hasselt University, Diepenbeek, Belgium.
Introduction: Currently, there is little evidence on the prevalence and factors associated with sarcopenia risk or frailty risk in patients post heart transplantation (HTx). The objective of this study was to analyze the influence of sociodemographic, lifestyle, physical, and psychological factors on sarcopenia and frailty risk in patients post-HTx.
Methods: 133 patients post-HTx (59.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!