This study aims to investigate the trends of avoidable mortality and regional inequality from 1995 to 2019 and to provide evidence for policy effectiveness to address regional health disparities in Korea. Mortality and population data were obtained from the Statistics Korea database. Age-standardized all-cause, avoidable, preventable, and treatable mortality was calculated for each year by sex and region. Changes in mortality trends between metropolitan and non-metropolitan areas were compared with absolute and relative differences. Avoidable mortality decreased by 65.7% (350.5 to 120.2/100,000 persons) in Korea, 64.5% in metropolitan areas, and 65.8% in non-metropolitan areas. The reduction in avoidable mortality was greater in males than in females in both areas. The main causes of death that contribute to the reduction of avoidable mortality are cardiovascular diseases, cancer, and injuries. In preventable mortality, the decrease in non-metropolitan areas (−192.4/100,000 persons) was greater than that in metropolitan areas (−142.7/100,000 persons). However, in treatable mortality, there was no significant difference between the two areas. While inequalities in preventable mortality improved, inequalities in treatable mortality worsened, especially in females. Our findings suggest that regional health disparities can be resolved through a balanced regional development strategy with an ultimate goal of reducing health disparities.

OBJECTIVES: While the Korean government’s response to the coronavirus disease 2019 (COVID-19) pandemic is considered effective given the relatively low mortality rate, issues of inequality have been insufficiently addressed. This study explored COVID-19-related health inequalities in Korea.METHODS: Age standardization for various health inequality indices was derived using data from the Korean National Health Insurance Service, the Korea Disease Control and Prevention Agency, and the Microdata Integrated Service of Statistics Korea. The slope index of inequality (SII) and relative index of inequality (RII) were calculated for socioeconomic variables, while absolute difference (AD) and relative difference (RD) were used for gender and disability inequalities.RESULTS: We observed a number of COVID-19-related health outcome inequalities. Gender inequality was particularly noticeable in infection rates, with the rate of women 1.16 times higher than that of men. In contrast, socioeconomic inequality was evident in vaccination rates, with a 4.5-fold (SII, -4.519; 95% confidence interval, -7.403 to -1.634) difference between the highest and lowest household income groups. Regarding clinical progression post-infection, consistent findings indicated higher risk for men (RD for hospitalization, 0.90; severe cases, 0.54; and fatality, 0.65), individuals with disabilities (RD for hospitalization, 2.27; severe cases, 2.29; and fatality, 2.37), and those from lower socioeconomic groups (SII for hospitalization, 1.778; severe cases, 0.089; and fatality, 0.451).CONCLUSIONS: While the infection risk was nearly ubiquitous, not everyone faced the same level of risk post-infection. To prevent further health inequalities, it is crucial to develop a thoughtful policy acknowledging individual health conditions and resources.

As indoor space becomes more important in our daily life, the demand to build digital twins for indoor spaces is increasing accordingly. The properties of indoor spaces, however, differ from those of outdoor spaces, and we need to apply different approaches to build indoor digital twins. In our work, we propose a framework for building an indoor digital twin with a use case for hospitals in general and large hospitals in particular, which may be considered as one of the most complicated types of digital twin. One of our goals is to establish a framework for building indoor digital twins based on standards and our framework starts from OGC IndoorGML, which is a standard for indoor data models and encoding schemes for indoor spatial data. In this paper, each step of the framework is presented for the construction of an indoor hospital digital twin focusing on a use case of epidemic analysis of COVID-19 transmission in a hospital. The use case study covers the entire life cycle of the indoor spatial application from requirement analysis, data modeling, and building indoor spatial data to the development of a COVID-19 transmission analysis. Our work represents a use case for indoor digital twins based on the OGC IndoorGML standard and eventually may serve as a framework and reference for building indoor digital twins. As our work is mainly focused on the construction of hospital digital twins, the study on COVID-19 infection model itself is limited in this paper. Improvement of the infection models and validations will be the next step of our work. As HVAC (heat, ventilation, and air conditioning) was not fully considered in our use case, we also expect that it is possible to strengthen our use case by including HVAC for the analysis of airflow dynamics.

Patients with osteoporosis are asymptomatic and are at risk for fractures. Therefore, early detection and interventions are important. We found that a population with a low socioeconomic status living in rural areas was reported to have a high osteoporosis prevalence but a relatively low diagnosis rate. Research on the disparity of osteoporosis prevalence and treatment from the socioeconomic perspective was conducted. This study aimed to investigate the influence of residence area and basic livelihood conditions on osteoporosis prevalence and diagnosis in postmenopausal women aged over 50 years. The cross-sectional data of 1477 postmenopausal women aged over 50 years obtained from the Korea National Health and Nutrition Examination Survey V-2 were analyzed. Univariate analyses were performed to calculate the prevalence and diagnosis rate according to risk factor categories. A multivariate logistic regression analysis was performed to identify the influence of residence area and basic livelihood conditions after controlling for other factors. The osteoporosis prevalence in basic livelihood beneficiaries (53.7%) and rural area residents (41.9%) was higher than that in non-beneficiaries (33.1%) and urban area residents (31.8%). There was no significant difference in the diagnosis rates in relation to the basic livelihood conditions or residence areas. The adjusted odds ratio for the prevalence among the beneficiaries living in rural areas was 2.08 (95% confidence interval: 1.06–4.10). However, the odds ratio for diagnosis was not significantly different. Earlier screening examination policies for osteoporosis in postmenopausal women with a low socioeconomic status living in rural areas are needed.

People of low socioeconomic status are vulnerable to health problems during disasters such as the COVID-19 pandemic. Using data from the 2019 and 2021 Korea Community Health Survey, this study analyzed the associations between Korean adults’ mental health and their national and regional-level household incomes during the pandemic. The prevalence of perceived stress and depression experience for each risk factor category was calculated through univariate analyses. A multivariate logistic regression analysis helped identify the association between two types of income levels (national or regional) and perceived stress and experience of depression. Additionally, we investigated the effect of income levels by subgroup (gender and residential area) on perceived stress and the experience of depression. During the pandemic, the crude prevalence of an experience of depression was higher (6.24% to 7.2%) but that of perceived stress remained unchanged. Regarding regional-income based mental health disparities, even after adjusting for each independent variable, perceived stress (2019 odds ratio (OR): 1.26, 95% confidence interval (CI):1.26–1.27, 2021 OR: 1.32, 95% CI: 1.32–1.32) and experience of depression (2019 OR: 1.56, 95% CI: 1.55–1.56, 2021 OR: 1.63, 95% CI: 1.63–1.64) increased as the income level decreased. The perceived stress based on the two income levels was higher in women than in men. For both income levels, the experience of depression of women was higher than that of men before COVID-19 and vice versa during the COVID-19 period. National income had a more pronounced effect on mental health in urban areas than in rural areas. Contrarily, the effect of regional income level on mental health was not consistent across residential areas (urban and rural areas). Our findings demonstrated that mental health disparities based on income level were more likely to occur during the COVID-19 pandemic and are better reflected through disparities in regional income levels.

This study aimed to identify the risk factors for non-traumatic rotator cuff tears in Korean adult patients who underwent surgical treatment, focusing on socioeconomic factors. A retrospective study was conducted with 659 patients who were diagnosed with a full rotator cuff tear and underwent surgical treatment. The outcome variable was the rotator cuff tear size (mm), as indicated by preoperative magnetic resonance imaging. Socioeconomic variables included occupation, education level, insurance type, and residential area. Univariate analyses were used to evaluate the relation between tear size and independent variables, and multivariate regression was used to estimate the effects of socioeconomic factors on tear size after adjusting for other variables. Significant differences were found in mean tear size according to age, occupation, residence area, and symptom duration (p < 0.05) in multivariate regression analysis. Rural residents had a 2.12 mm larger tear size than urban residents. Compared to National Health Insurance patients, the tear size of Medicaid beneficiaries was significantly larger (6.79 mm) in urban areas. The larger the rotator cuff tear, the greater the risk of retear and poor shoulder function. Therefore, policy efforts are required to expand access to medical care for the vulnerable.