Purpose: This study was to examine whether a health care model that provides comprehensive medical services based on population groups to members of the medical cooperative is applicable as a policy alternative in terms of medical use and cost. Methods: Data were derived from National Health Insurance claim data in 2019. We compared the medical volume and expenses of patients who visited social cooperative-type medical clinics with other patients, control group who visited other clinics in a local area. Results: The average number of visit days was 25.3 days in social cooperative-type medical clinics, more than 24.2 days in the control group (p=.004). However, the average medical cost per visit was KRW 46 thousand in social cooperative-type medical clinics, which was significantly lower than KRW 51 thousand in the control group (p<.001), and the total medical cost was also KRW 16.1 billion in social cooperative-type medical clinics and KRW 16.9 billion in the control group. Conclusion: We identified that a population-based health care model might change patients' behaviors to health care services and decrease total medical cost. Further population based experiment is needed to develop alternative healthcare model.
Objectives: Photochemical ozone pollution is associated with increased mortality risk. This study aims to assess the population exposure to ozone according to population characteristics for high ozone days in the Busan metropolitan region (BMR). Methods: The ozone exposure assessment in this study was performed using the WRF-CMAQ simulated ozone concentrations and the population data in the BMR. The settled and daytime population and their activity were considered to conduct the static and dynamic ozone exposure assessment. Results: Applying a static exposure assessment, in case that high ozone occurred throughout Busan area, the highest exposure levels were evaluated in urban neighborhoods. In case of ozone pollution in outer Busan, because sensitive groups have been relatively higher exposure, this case was also evaluated as part of that should not be overlooked. The dynamic exposure was higher than static exposure because the number of population exposed to ozone of high concentration is increased. This approach is important in a regard consider that daytime population distribution when high ozone occur. Conclusion: This study shows the different population exposure according to various ozone distributions for each episode day. Considering demographic characteristic such as population density and activity should be important to understanding the population exposure assessment when ozone pollution occurs.
Health promotion programs are becoming a vital component of comprehensive health care services worldwide for individuals and population, and health promotion activities have been a major component in advancing overall health of population. Promoting the health of individuals is akin to promoting the health of the community as these are closely linked to each other. Likewise, the health of every community in every state determines the overall health status of the Nation.(omitted)
Background: The coronavirus disease (COVID-19) has caused changes in human activity, and these changes may possibly increase or decrease exposure to fine dust (PM2.5). Therefore, it is necessary to evaluate the exposure to PM2.5 in relation to the outbreak of COVID-19. Objectives: The purpose of this study was to compare and evaluate the exposure to PM2.5 concentrations by the variation of dynamic populations before and after the outbreak of COVID-19. Methods: This study evaluated exposure to PM2.5 concentrations by changes in the dynamic population distribution in Guro-gu, Seoul, before and after the outbreak of COVID-19 between Jan and Feb, 2020. Gurogu was divided into 2,204 scale standard grids of 100 m×100 m. Hourly PM2.5 concentrations were modeled by the inverse distance weight method using 24 sensor-based air monitoring instruments. Hourly dynamic population distribution was evaluated according to gender and age using mobile phone network data and time-activity patterns. Results: Compared to before, the population exposure to PM2.5 decreased after the outbreak of COVID-19. The concentration of PM2.5 after the outbreak of COVID-19 decreased by about 41% on average. The variation of dynamic population before and after the outbreak of COVID-19 decreased by about 18% on average. Conclusions: Comparing before and after the outbreak of COVID-19, the population exposures to PM2.5 decreased by about 40%. This can be explained to suggest that changes in people's activity patterns due to the outbreak of COVID-19 resulted in a decrease in exposure to PM2.5.
Few public health researchers have paid research attention to the location of medical institutions in Korea. Previous studies were published in geography journals, and relied on limited data in terms of geographic regions and the type of medical institutions. This study utilized nationwide data covering 8 types of medical institutions. We obtained data from Health Insurance Review and Assessment Service and National Population and Housing Census. The correlation coefficients of resident, daytime, university-graduate population, and the population of different age groups (fewer than 15, 15~64, 65 or more) were compared to understand their relative association with the location of medical institutions. Medical clinic, dental clinic, oriental medical clinic, and pharmacy, all of which are almost completely operated by private sector, showed strong positive correlation with population. Hospital-level medical institutions, which are operated by both public and private sector, had moderate positive correlation. Daytime population and university-graduate population, rather than resident population, were more correlated with the location of medical clinics. The correlation coefficients of the population of 15~64 age group and the location of medical institutions were greater than that of other age groups. The results showed that daytime and university-graduate population are more important than resident population to explain the location of medicalrelated facilities. The results also suggests that the population of age groups (especially, 15~64) might be one of important influence factors in the location of medical institutions.
Purpose: There is increasing prevalence of psychiatric disorders among inflammatory bowel Disease (IBD) population. Further, presence of psychiatric disorders has been shown as an independent predictor of quality of life among patients with IBD. We intended to explore the prevalence of various psychiatric disorders among pediatric and young adult population with IBD as a population-based analysis. Methods: We did a retrospective case control analysis using a deidentified cloud-based database including health care data across 26 health care networks comprising of more than 360 hospitals across USA. Data collected across different hospitals were classified and stored according to Systematized Nomenclature of Medicine-Clinical Terms. We preidentified 10 psychiatric disorders and the queried the database for the presence of at least one of the ten psychiatric disorders among IBD patients between 5 and 24 years of age and compared with controls. Results: Total of 11,316,450 patients in the age group between 5 and 24 years and the number of patients with a diagnosis of IBD, Crohn's disease or ulcerative colitis were 58,020. The prevalence of psychiatric disorders was 21.6% among IBD mainly comprising of depression and anxiety disorder. Multiple logistic regression analysis showed, IBD is 5 times more likely associated with psychiatric disorders than controls, p<0.001). We showed a steady increasing trend in the incidence of psychiatric disorders among IBD patients (2% in 2006 to 15% in 2017). Conclusion: Largest population-based analysis demonstrated an increased prevalence of psychiatric disorders among IBD patients. Our study emphasizes the need for psychological and mental health services to be incorporated as a part of the routine IBD clinic.
Death is one of the population movement phenomena used as an important health index in most society. Especially it is regarded as group phenomenon in a specific group rather than individual one and considered important in public health field because the level and cause of death is related to health of public. The auther examined the changes of the Korean mortality pattern to evaluate the status of the Korean public health by studying mortality indicator using the population census and other materials from 1930 to 1980. The results are as follows: First, the Korean crude death rate was reduced to one third in 1980 compared to that in 1930, but the crude birth rate was constant from 1930 to 1960 causing the increase of population. So the population pattern is changing from the classic pyramic shape to bell shape and the dependency ratio was reduced from 78 in 1930 to 61 in 1980. Second, the infant mortality rate decrease rapidly. In 1980 it was one seventh of that in 1930 which was proved by the change of the age-specific death rate curve from U to J shape. Third, the male mortality reduction after the age of forty was much less than that of female, which explained the specific death pattern of high mortality in Korean middle and oldaged males. Fourth, the main cause of death was changed from infectious, parasitic, respiratory and digestive system disease to circulatory of tumorous diseases. Considering the above results, Korean health problem is now changing from the infant infection to geriatric chronic regressive disease. That naturally the direction of health service should be turned from the infant stage maternal and child health to the health problems of old people.
Background: PM2.5 pollution has been a persistent problem in South Korea, with concentrations consistently exceeding World Health Organization (WHO) guidelines. The aging of the population in the country further exacerbates the health impacts of PM2.5 since older adults are more susceptible to the adverse effects of air pollution. Objectives: This study aims to evaluate how the health impact (premature death) due to long-term exposure to PM2.5 in South Korea could change in the future according to the trend of change in the country's population structure. Methods: The study employs a relative risk function, which accounts for age-specific relative risks, to assess the changes in premature deaths by age and region at the average annual PM2.5 concentration for 2022 and at PM2.5 concentration improvement levels. Premature deaths were estimated using the Global Exposure Mortality Model (GEMM). Results: The findings indicate that the increase in premature deaths resulting from the projected population structure changes up to 2050 would significantly outweigh the health benefits (reduction in premature deaths) compared to 2012. This is primarily attributed to the rising number of premature deaths among the elderly due to population aging. Furthermore, the study suggests that the effectiveness of the current domestic PM2.5 standard would be halved by 2050 due to the increasing impact of population aging on PM2.5-related mortality. Conclusions: The study highlights the importance of considering trends in population structure when evaluating the health benefits of air pollution reduction measures. By comparing and evaluating the health benefits in reflection of changes in population structure to the predicted PM2.5 concentration improvements at the provincial level, a more comprehensive assessment of regional air quality management strategies can be achieved.
Purpose: The purpose of this study was to estimate income-related health inequalities among adolescent population across regions in Korea. Methods: Data of 8,456 adolescents from 1998, 2001, 2005, 2007 Korean Health and Nutrition Examination Survey were used for the analysis. True health status was proxied by self-rated health and overweight status. Per capita income was computed from household monthly average income adjusted by consumer price with base year 2005. Adolescent health inequalities were estimated by Concentration Index (CI) across income and space. Results: Ill health score was related with age (p<0.0001), gender (p=0.0155) and income (p<0.0001). Negative relationship between income and ill-health indicated that higher income group tended to enjoy better health and less overweight. These evidences suggested ill health were accumulated on the economically disadvantaged adolescents. The size of health inequalities (ill-health score) were estimated as CI=-0.057 and CI=-0.030 across income groups and regions, respectively. Comparable measures of within region health disparities were also observed. Conclusion: Since health disparity among adolescent population was small compared to adult population, lessening adolescent health inequality could be a helpful way of mitigating health disparities in later stage. Considering life stage of adolescents, school system and local communities could play important roles toward adolescent health distribution. Although health disparity between regions existed, health disparity within a region should not be neglected.
Objectives: As in many low-income and middle-income countries, out-of-pocket (OOP) payments by patients or their families are a key healthcare financing mechanism in Bangladesh that leads to economic burdens for households. The objective of this study was to identify whether and to what extent socioeconomic, demographic, and behavioral factors of the population had an impact on OOP expenditures in Bangladesh. Methods: A total of 12 400 patients who had paid to receive any type of healthcare services within the previous 30 days were analyzed from the Bangladesh Household Income and Expenditure Survey data, 2010. We employed regression analysis for identify factors influencing OOP health expenditures using the ordinary least square method. Results: The mean total OOP healthcare expenditures was US dollar (USD) 27.66; while, the cost of medicines (USD 16.98) was the highest cost driver (61% of total OOP healthcare expenditure). In addition, this study identified age, sex, marital status, place of residence, and family wealth as significant factors associated with higher OOP healthcare expenditures. In contrary, unemployment and not receiving financial social benefits were inversely associated with OOP expenditures. Conclusions: The findings of this study can help decision-makers by clarifying the determinants of OOP, discussing the mechanisms driving these determinants, and there by underscoring the need to develop policy options for building stronger financial protection mechanisms. The government should consider devoting more resources to providing free or subsidized care. In parallel with government action, the development of other prudential and sustainable risk-pooling mechanisms may help attract enthusiastic subscribers to community-based health insurance schemes.
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