Background: The elderly are a population group that is particularly vulnerable to nutritional and digestive problems due to age-related physiological changes. In the hospital setting, where the elderly are treated as inpatients, gastrointestinal symptoms can become more complicated due to the impact of many factors related to the hospital environment such as changes in diet and use of multiple medications. In Vietnam, the population is aging rapidly, with the proportion of people over 60 years old increasing. This is a major challenge for the health system, especially in nutritional management and improving the quality of life of the elderly. Objectives: The study aims to describe the nutritional status, common gastrointestinal symptoms and the association between gastrointestinal symptoms disorders and nutritional status in elderly individuals receiving inpatient treatment. Methods: A cross-sectional descriptive study was conducted on 264 elderly patients at Hanoi Medical University Hospital from March 2023 to May 2024. Nutritional status was assessed using the BMI (WHO) and MNA, with ROME IV criteria employed to determine gastrointestinal symptoms, including functional dyspepsia, belching disorders, nausea, and vomiting disorders. Related factors considered were age, gender, and comorbidities. Results: The average age of the participants was 69.4±7.2 years. The rate of malnutrition or risk of malnutrition in the study subjects according to MNA was quite high, 12.5% and 70.1%, respectively. The prevalence of common digestive symptoms in elderly patients includes: 60.2% of elderly patients have symptoms of functional dyspepsia; 33.7% have symptoms of belching disorder; nausea and vomiting disorders account for 16.4%. According to MNA assessment, the proportion of elderly patients at risk of malnutrition and malnutrition with symptoms of gastrointestinal disorder was higher than the non-malnutrition group, the difference was statistically significant with p<0.05. Female participants often have digestive symptoms more often than male participants (p<0.05). Conclusion: Digestive symptoms are common in the elderly treated in a hospital. The incidence of gastrointestinal symptoms in the elderly is related to malnutrition.

Objectives: Type 2 diabetes is a growing public health concern, especially among the elderly. Understanding the nutritional status of this population is essential for effective disease management. This study describes the nutritional status and some related factors in elderly patients with type 2 diabetes at the National Hospital Of Endocrinology in 2023-2024. Methods: A cross-sectional descriptive study was conducted on 209 elderly individuals with type 2 diabetes receiving treatment at the Clinical Nutrition & Dietetics Department, National Hospital Of Endocrinology. Results: The average age was 70.63 (±6.64) years, with 54.07% being female. According to WHO classification, 19.62% were overweight, and 2.39% were obese. Based on the World Health Organization's Western Pacific Regional Office (WPRO) classification, the prevalence of overweight and obesity was 24.88% and 22.01%, respectively. High waist circumference (WC) was found in 71.29% of participants. Overweight and obesity were significantly associated with comorbidities: patients with lipid metabolism disorders had a 2.07-fold higher risk (95% CI: 1.06–6.88, p<0.05), and those with cardiovascular disease/hypertension had a 2.21-fold higher risk (95% CI: 1.01–4.81, p<0.05). A slower eating pace was linked to a 0.34-fold lower risk of overweight/obesity (95% CI: 0.29–0.84, p<0.05). Conclusion: Elderly diabetic patients had a high prevalence of overweight, obesity, and central adiposity, which were influenced by comorbidities and dietary habits. Targeted nutritional interventions were crucial for improving their health outcomes.

OBJECTIVES: Health-related quality of life is crucial for people dealing with chronic illness. This study investigated the quality of life in individuals with 5 common chronic conditions in Korea. We also analyzed socioeconomic factors such as education, income, occupation, and urbanization to identify determinants of inequality. METHODS: Using 2016 Korea Community Health Survey data, we examined individuals aged 30 or older with chronic diseases (diabetes, hypertension, cardiovascular disease, hyperlipidemia, arthritis) using the EuroQol 5-Dimension 3 Level tool. We analyzed the associations between socioeconomic factors (education, income, occupation, urbanization) and quality of life using descriptive statistics and regression analysis. Inequality indices (relative inequality index, absolute inequality index) were used to measure inequality in quality of life. RESULTS: Individuals with higher income levels showed a 1.95-fold higher likelihood of a better quality of life than those with the lowest income. The lowest income group had higher odds of mobility (adjusted odds ratio [aOR], 2.2), self-care (aOR, 2.1), activity limitations (aOR, 2.4), pain/discomfort (aOR, 1.8), and anxiety/depression (aOR, 2.3). Educational disparities included a 3-fold increase in mobility and daily activity problems for those with elementary or lower education. Well-educated participants had a 1.94 times higher quality of life, with smaller differences in anxiety/depression and self-management. The income gap accounted for 14.1% of variance in quality-of-life disparities. CONCLUSIONS Addressing socioeconomic disparities in the quality of life for individuals with chronic diseases necessitates tailored interventions and targeted health policies. This research informs policymakers in developing focused initiatives to alleviate health inequities. It emphasizes the importance of mental health support and ensuring affordable, accessible healthcare services.

OBJECTIVES: We investigated the prevalence and determinants of unhealthy living by gender, age, and comorbidities across Korean districts. METHODS: For 806,246 men and 923,260 women from 245 districts who participated in the 2010-2017 Korean Community Health Surveys, risk scores were calculated based on obesity, physical inactivity, smoking, and high-risk alcohol consumption, each scored from 0 (lowest risk) to 2 (highest risk). A risk score ≥4 was defined as indicating unhealthy living, and weighted proportions were calculated for each district. Using multivariate regression, an ecological model including community socioeconomic, interpersonal, and neighborhood factors was examined by gender, age, and comorbidities. RESULTS: The mean age-standardized rate of unhealthy living was 24.05% for men and 4.91% for women (coefficients of variation, 13.94% and 29.51%, respectively). Individuals with chronic diseases more frequently exhibited unhealthy lifestyles. Unhealthy lifestyles were associated with educational attainment (β-coefficients: men, -0.21; women, -0.15), high household income (β=0.08 and 0.03, respectively), pub density (β=0.52 and 0.22, respectively), and fast-food outlet density (β=2.81 and 1.63, respectively). Negative associations were observed with manual labor, social activity participation, and hospital bed density. Unhealthy living was positively associated with living alone among women and with being unemployed among middle-aged men. Access to parks was negatively associated with unhealthy living among young men and women. The ecological model explained 32% of regional variation in men and 41% in women. CONCLUSIONS Improving the neighborhood built and socioeconomic environment may reduce regional disparities in lifestyle behaviors; however, the impacts may vary according to socio-demographic traits and comorbidities.