Background: Health literacy (HL) is an important factor in improving health inequalities in poor and marginalized groups. Assessing comprehensive HL is critical. In this study, we validated the use of a comprehensive short-form HL survey tool (HLS-SF12) and examined the determinants of HL among people in rural areas. Methods: A cross-sectional study was conducted in July 2019 on 440 people residing in mountainous areas in Vietnam. Health literacy was measured using the HLS-SF12. Personal characteristics were also collected. We analyzed data using confirmatory factor analysis, internal consistency analysis, and regression analysis. Results: The questionnaire demonstrated a good construct validity with satisfactory goodness-of-fit indices and item-scale convergent validity. The tool was reliable and homogeneous with Cronbach’s alpha = 0.79, with no floor/ceiling effects. People who were married had lower HL (regression coefficient B = −3.12; 95% confidence interval (CI) = −5.69, −0.56; p = 0.017) compared with those who never married. Higher education attainment (B = 3.41 to 10.44; p < 0.001), a better ability to pay for medication (B = 4.17 to 9.89; p < 0.001), and a tendency to view health-related TV/radio more often (B = 5.23 to 6.15; p < 0.001) were associated with higher HL. Conclusions: The HLS-SF12 is a valid survey tool for the evaluation of HL in rural populations. A number of personal characteristics were strongly associated with HL.

Background: In Taiwan, there is a high incidence of breast cancer and a high prevalence of viral hepatitis. In this case-control study, we used a population-based insurance dataset to evaluate whether breast cancer in women is associated with chronic viral hepatitis infection.Methods: From the claims data, we identified 1,958 patients with newly diagnosed breast cancer during the period 2000-2008. A randomly selected, age-matched cohort of 7,832 subjects without cancer was selected for comparison. Multivariable logistic regression models were constructed to calculate odds ratios of breast cancer associated with viral hepatitis after adjustment for age, residential area, occupation, urbanization, and income. The age-specific (<50 years and ≥50 years) risk of breast cancer was also evaluated.Results: There were no significant differences in the prevalence of hepatitis C virus (HCV) infection, hepatitis B virus (HBV), or the prevalence of combined HBC/HBV infection between breast cancer patients and control subjects (p= 0.48). Multivariable logistic regression analysis, however, revealed that age <50 years was associated with a 2-fold greater risk of developing breast cancer (OR = 2.03, 95% CI = 1.23-3.34).Conclusions: HCV infection, but not HBV infection, appears to be associated with early onset risk of breast cancer in areas endemic for HCV and HBV. This finding needs to be replicated in further studies.

This paper discusses using computer-aided diagnosis (CAD) to distinguish between hepatocellular carcinoma (HCC), i.e., the most common type of primary liver malignancy and a leading cause of death in people with cirrhosis worldwide, and liver abscess based on ultrasound image texture features and a support vector machine (SVM) classifier. Among 79 cases of liver diseases including 44 cases of liver cancer and 35 cases of liver abscess, this research extracts 96 features including 52 features of the gray-level co-occurrence matrix (GLCM) and 44 features of the gray-level run-length matrix (GLRLM) from the regions of interest (ROIs) in ultrasound images. Three feature selection models—(i) sequential forward selection (SFS), (ii) sequential backward selection (SBS), and (iii) F-score—are adopted to distinguish the two liver diseases. Finally, the developed system can classify liver cancer and liver abscess by SVM with an accuracy of 88.875%. The proposed methods for CAD can provide diagnostic assistance while distinguishing these two types of liver lesions.

Diabetes and obesity are globally prevalent metabolic disorders posing significant public health challenges. The effective management of these conditions requires integrated and personalized strategies. This study conducted a systematic literature review, identifying 335 relevant papers, with 129 core articles selected after screening for duplicates and irrelevant studies. The focus of the study is on the synergistic roles of functional foods, microbiotics, and nutrigenomics. Functional foods, including phytochemicals (e.g., polyphenols and dietary fibers), zoochemicals (e.g., essential fatty acids), and bioactive compounds from macrofungi, exhibit significant potential in enhancing insulin sensitivity, regulating lipid metabolism, reducing inflammatory responses, and improving antioxidant capacity. Additionally, the critical role of gut microbiota in metabolic health is highlighted, as its interaction with functional foods facilitates the modulation of metabolic pathways. Nutrigenomics, encompassing nutrigenetics and genomics, reveals how genetic variations (e.g., single-nucleotide polymorphisms (SNPs)) influence dietary responses and gene expression, forming a feedback loop between dietary habits, genetic variations, gut microbiota, and metabolic health. This review integrates functional foods, gut microbiota, and genetic insights to propose comprehensive and sustainable personalized nutrition interventions, offering novel perspectives for preventing and managing type 2 diabetes and obesity. Future clinical studies are warranted to validate the long-term efficacy and safety of these strategies.