Family caregivers of people living with dementia (PLWD) may experience mental and physical health issues. The purpose of this study was to examine factors associated with family caregiver outcomes and to describe their interrelationships. Methods: Grounded in the stress process model, path analysis was conducted using secondary data from 178 dyads of community-dwelling PLWD and family caregivers in Korea. Caregiver outcome was assessed through caregivers’ health status and stress due to behavioral and psychological symptoms of dementia (BPSD). Agitation and depression were specified as primary stressors, and PLWD factors were included as background factors associated with BPSD, with separate symptom models. Results: Agitation and depression showed the strongest associations with family caregiver stress related to BPSD. Agitation explained 45.1% of caregiver stress related to BPSD variance (β=.66, p<.001), while depression explained 41.5% (β=.63, p<.001). Agitation and depression were related to caregiver health status (β=.17, p=.006; β=.18, p=.017). In both agitation and depression models, female caregivers (β=.19, p=.008, in both models), older age (β=.21, p=.007, in both models), and lower economic status (β=.32, p<.001, in both models) were associated with poorer caregiver health status. Dementia severity and patient age showed indirect associations with caregiver stress related to BPSD through agitation and depression. Conclusion: Agitation and depression were associated with caregiver stress related to BPSD, while caregiver characteristics were associated with health status. These findings highlight the need for tailored interventions to address BPSD and support caregivers. Family-centered and system-level approaches are essential for improving outcomes for PLWD and their families.

BACKGROUND/OBJECTIVES: Obesity is a complex metabolic disorder characterized by excessive adipose tissue accumulation, dysregulated lipid metabolism, and insulin resistance, leading to an increased risk of metabolic disease. While Withania somnifera (AS) and Chrysanthemum zawadskii Herbich var. latilobum (Maxim.) Kitamura (C) have traditionally been used for their metabolic regulatory properties, their combined effects on adipogenesis, lipogenesis, lipolysis, and insulin signaling remain unexplored. Therefore, this study aimed to evaluate the anti-obesity effects of AS, C, and their optimal combination (ASC) in 3T3-L1 adipocytes by investigating their impact on lipid metabolism and glucose homeostasis.MATERIALS/METHODS: Following adipogenic differentiation, 3T3-L1 adipocytes were treated with AS, C, and ASC at different concentrations. RESULTS: AS, C, and ASC significantly inhibited adipogenesis by downregulating cyclic adenosine monophosphate (cAMP) response element-binding protein, peroxisome proliferator-activated receptor gamma, CCAAT/enhancer-binding proteins alpha and beta phosphorylation, thereby reducing lipid accumulation in adipocytes. They also suppressed lipogenesis by downregulating the expression of dephosphorylated acetyl-CoA carboxylase, fatty acid synthase, and lipoprotein lipase. In contrast, they markedly enhanced lipolysis, as evidenced by increased hormone-sensitive lipase and protein kinase A expression, along with elevated glycerol release and cAMP levels. Furthermore, AS, C, and ASC activated energy metabolism pathways, as indicated by the upregulation of AMP-activated protein kinase, uncoupling protein 1, and carnitine palmitoyltransferase 1A, suggesting a transition toward enhanced mitochondrial fatty acid oxidation. Notably, AS, C, and ASC significantly improved insulin signaling by restoring insulin receptor substrate 1, phosphoinositide 3-kinase, and Akt phosphorylation, while upregulating glucose transporter type 4 expression, indicating enhanced glucose uptake. Among all treatments, ASC showed relatively greater efficacy compared to AS or C alone, suggesting a potential additive effect. CONCLUSION These findings demonstrate that ASC effectively modulates multiple metabolic pathways in adipocytes, including adipogenesis, lipogenesis, lipolysis, energy metabolism, and insulin signaling, to exert its anti-obesity effects.

The population attributable fraction (PAF) indicates the proportion of disease cases in a given population that can be attributed to a specific factor, assuming a causal relationship. In other words, it quantifies the extent to which that factor contributes to disease occurrence. PAF calculation methods have been applied to studies factors and several, studies have reported PAFs for dietary contributors to overall or specific cancer risks. Our team has conducted several PAF studies and presents findings on the contributions of dietary factors to cancer risk in the Korean population.Current Concepts: For colorectal cancer, the PAF of dietary factors is 34.9%, with insufficient whole grain intake contributing the largest share (16.6%). For gastric cancer, dietary factors have a PAF of 18.6%, with excessive intake of salted vegetables contributing the most (16.0%). Notably, the PAFs for inadequate whole grain and milk consumption were higher than those reported in previous studies, while the PAFs for other dietary factors fell within the expected range. These findings emphasize the need to prioritize interventions that effectively reduce the diet-attributable cancer burden.Discussion and Conclusion: Country-specific PAF estimates are crucial for developing effective cancer prevention strategies tailored to the Korean population. To better apply dietary PAF estimates, future studies should (1) integrate data from existing and ongoing cohort studies to determine Korea-specific relative risks, (2) estimate dietary prevalence using assessment tools that capture long-term dietary habits, and (3) establish optimal intake levels specific to the Korean context.

The population attributable fraction (PAF) indicates the proportion of disease cases in a given population that can be attributed to a specific factor, assuming a causal relationship. In other words, it quantifies the extent to which that factor contributes to disease occurrence. PAF calculation methods have been applied to studies factors and several, studies have reported PAFs for dietary contributors to overall or specific cancer risks. Our team has conducted several PAF studies and presents findings on the contributions of dietary factors to cancer risk in the Korean population.Current Concepts: For colorectal cancer, the PAF of dietary factors is 34.9%, with insufficient whole grain intake contributing the largest share (16.6%). For gastric cancer, dietary factors have a PAF of 18.6%, with excessive intake of salted vegetables contributing the most (16.0%). Notably, the PAFs for inadequate whole grain and milk consumption were higher than those reported in previous studies, while the PAFs for other dietary factors fell within the expected range. These findings emphasize the need to prioritize interventions that effectively reduce the diet-attributable cancer burden.Discussion and Conclusion: Country-specific PAF estimates are crucial for developing effective cancer prevention strategies tailored to the Korean population. To better apply dietary PAF estimates, future studies should (1) integrate data from existing and ongoing cohort studies to determine Korea-specific relative risks, (2) estimate dietary prevalence using assessment tools that capture long-term dietary habits, and (3) establish optimal intake levels specific to the Korean context.

The population attributable fraction (PAF) indicates the proportion of disease cases in a given population that can be attributed to a specific factor, assuming a causal relationship. In other words, it quantifies the extent to which that factor contributes to disease occurrence. PAF calculation methods have been applied to studies factors and several, studies have reported PAFs for dietary contributors to overall or specific cancer risks. Our team has conducted several PAF studies and presents findings on the contributions of dietary factors to cancer risk in the Korean population.Current Concepts: For colorectal cancer, the PAF of dietary factors is 34.9%, with insufficient whole grain intake contributing the largest share (16.6%). For gastric cancer, dietary factors have a PAF of 18.6%, with excessive intake of salted vegetables contributing the most (16.0%). Notably, the PAFs for inadequate whole grain and milk consumption were higher than those reported in previous studies, while the PAFs for other dietary factors fell within the expected range. These findings emphasize the need to prioritize interventions that effectively reduce the diet-attributable cancer burden.Discussion and Conclusion: Country-specific PAF estimates are crucial for developing effective cancer prevention strategies tailored to the Korean population. To better apply dietary PAF estimates, future studies should (1) integrate data from existing and ongoing cohort studies to determine Korea-specific relative risks, (2) estimate dietary prevalence using assessment tools that capture long-term dietary habits, and (3) establish optimal intake levels specific to the Korean context.

Purpose: This study aimed to develop a fall prediction model for community-dwelling older adults using machine learning. Methods: The present study was conducted with a secondary data analysis that used data from the 2020 national survey of older Koreans. Among 10,097 participants, data 177 were excluded due to incompleteness and 9,920 were included in the final analysis. Because of data imbalance, upsampling was performed to increase the number of individuals who fell. Forty-five independent variables for fall prediction were selected based on the fall risk factors from previous studies and univariate statistical analysis. The data were split into training and testing sets at an 80:20 ratio. Three machine learning algorithms—logistic regression, random forest, and artificial neural network—were used to develop a fall prediction model. Results: The random forest model outperformed the others, with an area under the curve of .91, accuracy of .94, precision of .94, recall of .74, and F1 score of .83. An analysis of feature importance revealed that satisfaction with health condition, visual difficulty, instrumental activities of daily living, performance of 400m walk, and cognitive ability were the top five features for fall prediction. Conclusion The fall prediction model developed using machine learning demonstrated high model performance, implying its suitability for use as a primary screening tool for fall risk. Subjective satisfaction with one’s health should be considered as an important factor in predicting falls in community-dwelling older adults. It is necessary for community health nurses to reinforce positive health awareness by continuous disease management and physical function improvement for older adults to prevent falls.

Conjugate upward and downward gaze palsy related to unilateral midbrain infarction is a rare neurological symptom, as there were few reported cases worldwide. Here, we report a case of 55-year-old male patient presenting with conjugate vertical gaze palsy. In this case, diffusion-weighted magnetic resonance images demonstrated a localized infarction in the right rostral midbrain.

A pulmonary artery periadventitial hematoma is a rare complication of a Stanford type A intramural hematoma. As the proximal ascending aorta and pulmonary artery share a common adventitial layer, extravasated blood from the intramural hematoma in the ascending thoracic aorta may extend to beneath the adventitia of the pulmonary artery. The authors describe a case involving a 66-year-old male with acute chest pain who presented with a pulmonary artery periadventitial hematoma associated with a Stanford type A intramural hematoma.

The Korean Triage and Acuity Scale (KTAS) Committee under the Korean Society of Emergency Medicine developed a Korean pre-hospital emergency patient classification tool (Pre-hospital Korean Triage and Acuity Scale [Pre-KTAS]) under contract from the Ministry of Health and Welfare, Korea. The classification tool was developed separately for adults and children. The patient’ s emergency level is classified into five distinct levels and is the same as the KTAS classification system, which is a hospital-level emergency patient classification tool.

While the Korean Triage and Acuity Scale (KTAS) was introduced in 2016 as a tool to identify patients at risk of catastrophic events, including death in the ED, the triage system for the pre-hospital stage still lacks evidence. The pre-hospital stage is characterized by time-sensitive and complex scenarios, where rapid and accurate decision-making is paramount to optimize patient outcomes. Despite the vital role of pre-hospital care providers, the invalidated and subjective current triage system consisting of 4-stages is still used at the pre-hospital stage, and hence, it needs to be modified to be more objective, standardized, and reliable. To improve the Korean emergency medical system, the pre-hospital KTAS (Pre-KTAS) was developed in 2020, and then two pilot projects were conducted in 2022 and 2023. This paper not only reveals the results of the first and second pilot projects for Pre-KTAS but also highlights the potential benefits of using this newly developed triage tool in the pre-hospital setting. Furthermore, this paper suggests ways to improve the emergency medical system (EMS) in Korea by improving patient safety, resource allocation, and overall emergency response efficiency.