Future Blood Debt: Projecting Blood Supply and Demand of Korea Based on Subnational Population Projections (2021-2050).

BACKGROUND: South Korea faces a critical challenge with its rapidly declining fertility rates and an increasingly aging population, which significantly impacts the country's blood supply and demand. Despite these nationwide trends, regional disparities in blood supply and demand have not been thoroughly studied. METHODS: This research utilized blood donation data from the Korean Red Cross and blood transfusion data from the Health Insurance Review and Assessment Service. We analyzed these datasets in conjunction with regional population projections to simulate blood supply and demand from 2021 to 2050 across South Korea. Sensitivity analyses were conducted to assess the impact of various factors, including the number of donors, age eligibility criteria for donations, frequency of donations, and blood discard rates. RESULTS: Our projections indicate a decreasing trend in blood supply, from 2.6 million units in 2021 to 1.4 million units by 2050, while demand is expected to peak at 5.1 million units by 2045 before declining. Metropolitan areas, particularly Gyeonggi Province, are projected to experience the most severe shortages. Sensitivity analyses suggest that increasing the donation frequency of existing donors and relaxing age eligibility criteria are more effective strategies in addressing these imbalances than merely increasing the number of new donors. Blood discard rates showed minimal impact on the overall blood shortage. CONCLUSION: The findings emphasize the urgent need for targeted strategies to mitigate national and regional blood supply shortages in South Korea. Encouraging frequent donations from experienced donors and broadening eligibility criteria are critical steps toward stabilizing the blood supply amidst demographic shifts. These strategies must be prioritized to address the impending regional disparities in blood availability.

Trends in Frailty Prevalence Among Older Adults in Korea: A Nationwide Study From 2008 to 2020.

BACKGROUND: We aimed to evaluate the nationwide trend of the prevalence of frailty in older adults in Korea from 2008 to 2020 to inform future geriatric healthcare policies. METHODS: The study used data of individuals aged 65 years and older from the Korea National Health and Nutrition Examination Survey, a nationwide repeated cross-sectional survey. Frailty was defined using frailty index, classified as non-frail (frailty index ≤ 0.15), pre-frail (0.15 < frailty index ≤ 0.25), or frail (frailty index > 0.25). RESULTS: The study included 17,784 individuals, with the mean age of 72.4 and mean frailty index of 0.2. The prevalence of frailty in older adults in South Korea decreased significantly from 2008 (41.1%) to 2020 (23.1%). The decrease in the frailty index was observed in all age groups (all P < 0.05). As components of frailty index, we found that certain comorbidities, such as dyslipidemia, diabetes mellitus, and cardiovascular disease, have increased over time, while factors such as chewing difficulty, activity limitation, and smoking, have decreased. CONCLUSION: The prevalence of frailty in older adults in South Korea has decreased significantly during the study period. Historical improvements in healthcare access and preventive measures may have contributed to this trend.

Depopulation, super aging, and extreme heat events in South Korea.

South Korea's population is declining and its composition changing, associated with lowest-low fertility rates and rapid aging (super aging). When estimating changes in future exposure to extreme heat events (EHE), events that are predicted to be intensified due to climate change, it is important to incorporate demographic dynamics. We analyze business-as-usual (BAU) population and climate scenarios-where BAU refers to no significant change in current processes and trends in either domain-from 2010 to 2060 for South Korea. Data for both BAU scenarios are spatially linked and used to measure and identify national and sub-national and age-group specific EHE exposure. The results reveal an increasing exposure to EHE over time at the national level, but this varies widely within the country, measured at the municipal level. The most intensive exposure levels will be in the decade ending in 2040 driven by high estimated severe EHE. Sub-nationally, Seoul will be the most vulnerable municipality associated with super aging, while severe EHE not demographic factors will be relevant in Daegu, the second-most vulnerable metropolitan area. By 2060, national estimates suggest the older population will be up to four times more exposed to EHE than today. While the population of South Korea will decline, the rapid aging of the population ensures that specific regions of the country will become exceedingly vulnerable to EHE.

Super Aging in South Korea Unstoppable but Mitigatable: A Sub-National Scale Population Projection for Best Policy Planning.

This research portrays the spatial and temporal progression of super-aging in regions throughout South Korea. Using a single-year population projection considering gross domestic migration, this research identifies which regions will shortly become a super-aged society. A cohort-component method with a migrant pool model is applied. The county-level national population registration data (2000-2018) are aggregated into 37 regions for the model run. In 2020, 16 rural regions will become super-aged societies. By 2029, all 37 regions, including the metropolitan areas, will join the group, with Sejong, the administrative capital, being the last to enter. In brief, the rural areas become super-aged earlier than the metropolitan areas, and within a decade, those 65 years old or older will make up the majority of the national population. Among all the metropolitan areas, Busan, the largest harbor city, will be the first to be super-aged in 2023. Sejong will experience the most radical change between 2020 and 2050. The research outcomes demonstrate that demographic changes in the rural and metropolitan areas are different; hence, the recent population policies, such as promoting fertility, may not work in the rural areas as they have already lost their population momentum due to the extreme and ongoing urbanization throughout the nation. The unstoppable aging will pose adverse effects on future citizens (who are mostly senior) both financially and medically. An increase in health care expenditure and a nationwide blood shortage for transfusion are anticipated, for example.

A Mixed Application of Geographically Weighted Regression and Unsupervised Classification for Analyzing Latex Yield Variability in Yunnan, China.

This paper introduces a mixed method approach for analyzing the determinants of natural latex yields and the associated spatial variations and identifying the most suitable regions for producing latex. Geographically Weighted Regressions (GWR) and Iterative Self-Organizing Data Analysis Technique (ISODATA) are jointly applied to the georeferenced data points collected from the rubber plantations in Xishuangbanna (in Yunnan province, south China) and other remotely-sensed spatial data. According to the GWR models, Age of rubber tree, Percent of clay in soil, Elevation, Solar radiation, Population, Distance from road, Distance from stream, Precipitation, and Mean temperature turn out statistically significant, indicating that these are the major determinants shaping latex yields at the prefecture level. However, the signs and magnitudes of the parameter estimates at the aggregate level are different from those at the lower spatial level, and the differences are due to diverse reasons. The ISODATA classifies the landscape into three categories: high, medium, and low potential yields. The map reveals that Mengla County has the majority of land with high potential yield, while Jinghong City and Menghai County show lower potential yield. In short, the mixed method can offer a means of providing greater insights in the prediction of agricultural production.

The 'Geographic Emission Benchmark' model: a baseline approach to measuring emissions associated with deforestation and degradation.

This paper proposes a new land-change model, the Geographic Emission Benchmark (GEB), as an approach to quantify land-cover changes associated with deforestation and forest degradation. The GEB is designed to determine 'baseline' activity data for reference levels. Unlike other models that forecast business-as-usual future deforestation, the GEB internally (1) characterizes 'forest' and 'deforestation' with minimal processing and ground-truthing and (2) identifies 'deforestation hotspots' using open-source spatial methods to estimate regional rates of deforestation. The GEB also characterizes forest degradation and identifies leakage belts. This paper compares the accuracy of GEB with GEOMOD, a popular land-change model used in the UN-REDD (Reducing Emissions from Deforestation and Forest Degradation) Program. Using a case study of the Chinese tropics for comparison, GEB's projection is more accurate than GEOMOD's, as measured by Figure of Merit. Thus, the GEB produces baseline activity data that are moderately accurate for the setting of reference levels.