The policies of response to and prevention of heat waves in France in 2003 and in South Korea in 2018 were compared and reviewed to see how public health policy orientation was being expanded in connection with urban and social policies. The statistics of the patients with heat illness and resulted death in France in 2003 and South Korea in 2018 were analyzed. The results and limitations of the French and Korean responses to heat waves were compared and discussed. The heat wave in France in 2003 caused an excess death of 14,802. The 2018 heat wave in South Korea resulted in 4,526 cases of heat illness and 48 deaths. France’s National Heat wave Plan established in 2004 introduced the warning system and strengthened support for the vulnerable. The heat wave in South Korea in 2018 revealed the success and limitations of the national measures that have been gradually implemented since the mid-2000s. Both France and South Korea are making efforts in preventing heat illness and managing health risk through the warning systems, providing public and social support for the vulnerable, and expanding urban infrastructure. Paris puts priority on the long-term prevention of heat wave, in the wider context of climate change response, while Seoul shows a relatively strong point in immediate infrastructural expansion. In order to respond to the climate crisis and the following health risk, public health policies need to be contrived with deeper connection with urban social policies for sustainable development.
This study analyzes how climate change affects the economy, society, and environment in South Korea. Then, the study explores the ways to strengthen capabilities that can alleviate climate change impacts. To find them, the study employs a system dynamics simulation method and builds a model with several sectors including the urban, rural, population, and social-environmental sectors. The study compares the size of climate change damages in rural and urban areas. The results with representative concentration path (RCP) 8.5 show that the size of climate change damage will continue to increase by 2050. The projected damages from the reduced industrial outputs in urban areas will be larger than that in rural areas. The results also show that the service sector will face stronger impacts from climate change than the manufacturing and agricultural sectors. However, the total size of damage in the rural areas will be bigger than that of the urban areas. It is because the size of reduced industrial outputs per capita in the rural areas is twice bigger than that of the urban areas. The climate change damage in the social and environmental sectors (including a loss of biodiversity and an increase in health costs) account for the largest part of the total damage. The study finally provides suggestions and policies that can improve the capabilities to reduce the climate change damages. One of the major suggestions of this study is that the increase in the climate change budget corresponding to the GDP growth can minimize the size of climate change impacts.
This study investigated how changes in weather factors affect the prevalence of conjunctivitis using public big data in South Korea. A total of 1,428 public big data entries from January 2013 to December 2019 were collected. Disease data and basic climate/air pollutant concentration records were collected from nationally provided big data. Meteorological factors affecting eye diseases were identified using multiple linear regression and machine learning analysis methods such as extreme gradient boosting (XGBoost), decision tree, and random forest. The prediction model with the best performance was XGBoost (1.180), followed by multiple regression (1.195), random forest (1.206), and decision tree (1.544) when using root mean square error (RMSE) values. With the XGBoost model, province was the most important variable (0.352), followed by month (0.289) and carbon monoxide exposure (0.133). Other air pollutants including sulfur dioxide, PM(10), nitrogen dioxides, and ozone showed low associations with conjunctivitis. We identified factors associated with conjunctivitis using traditional multiple regression analysis and machine learning techniques. Regional factors were important for the prevalence of conjunctivitis as well as the atmosphere and air quality factors.
This study aimed to analyze the association between temperature and precipitation and the incidence of hepatitis A in Seoul, Korea, as meteorological factors may have different effects on specific diseases depending on the lifestyle in each region. Weekly cases of hepatitis A, weekly mean daily precipitation, and temperature data from 2016 to 2020 were analyzed. Quasi-Poisson-generalized linear models with time variable adjusted by spline function were used considering 0-6-week lags. The association of each variable and hepatitis A incidence was assessed by the single lag and the constrained distributed lag model. Multivariable distributed lag linear and non-linear models were used to develop models with significant independent variables. Weekly mean of daily mean temperature (Tmean) and maximum temperature (Tmax) were negatively associated with hepatitis A in the 6-week lag. Precipitation was negatively associated with hepatitis A in the 5- and 6-week lags. The multivariable model showed the negative association of Tmax, precipitation and hepatitis A in the 5- and 6-week lags. In the non-linear models, the incidence rate ratio (IRR) was the highest at a Tmax of 11 °C and decreased thereafter. IRR was the highest at 12 mm of precipitation and showed decrease pattern to 25 mm and then gradually increased in the 5- and 6-week lags. Identifying the impact of climate factors on hepatitis A incidence would help in the development of strategies to prevent diseases and indirectly estimate the impact of climate change on hepatitis A epidemiology.
Hepatitis A is a water-borne infectious disease that frequently occurs in unsanitary environments. However, paradoxically, those who have spent their infancy in a sanitary environment are more susceptible to hepatitis A because they do not have the opportunity to acquire natural immunity. In Korea, hepatitis A is prevalent because of the distribution of uncooked seafood, especially during hot and humid summers. In general, the transmission of hepatitis A is known to be dynamically affected by socioeconomic, environmental, and weather-related factors and is heterogeneous in time and space. In this study, we aimed to investigate the spatio-temporal variation of hepatitis A and the effects of socioeconomic and weather-related factors in Korea using a flexible spatio-temporal model. We propose a Bayesian Poisson regression model coupled with spatio-temporal variability to estimate the effects of risk factors. We used weekly hepatitis A incidence data across 250 districts in Korea from 2016 to 2019. We found spatial and temporal autocorrelations of hepatitis A indicating that the spatial distribution of hepatitis A varied dynamically over time. From the estimation results, we noticed that the districts with large proportions of males and foreigners correspond to higher incidences. The average temperature was positively correlated with the incidence, which is in agreement with other studies showing that the incidences in Korea are noticeable in spring and summer due to the increased outdoor activity and intake of stale seafood. To the best of our knowledge, this study is the first to suggest a spatio-temporal model for hepatitis A across the entirety of Korean. The proposed model could be useful for predicting, preventing, and controlling the spread of hepatitis A.
To provide a nationwide representative dataset for the study on health impact of air pollution, we combined the data from the Korea National Health and Nutrition Examination Survey with the daily air quality and weather data by matching the date of examination and the residential address of the participants. The database of meteorological factors and air quality as sources of exposure data were estimated using the Community Multiscale Air Quality model. The linkage dataset was merged by three ways; administrative district, si-gun-gu (city, county, and district), and geocode (in latitude and longitude coordinate units) based on the participants’ residential address, respectively. During the study period, the exposure dataset of 85,018 individuals (38,306 men and 46,712 women) whose examination dates were recorded were obtained. According to the definition of exposure period, the dataset was combined with the data on short-term, mid-term, and long-term exposure to air pollutants and the meteorological indices. Calculation of the daily merged dataset’s average air pollution linked by si-gun-gu and geocode units showed similar results. This study generated a daily average of meteorological indices and air pollution exposure dataset for all regions including rural and remote areas in Korea for 11 years. It is expected to provide a platform for the researchers studying the health impact of air pollution and climate change on the representative population and area, which may facilitate the establishment of local health care plans by understanding the residents’ health status at the local as well as national level.
Rapid industrialization of Korea’s economy has brought with it environmental pollution that threatens human health. Among various other pollutants, ambient fine particulate matter known to endanger human health often exceeds air quality standards in Seoul, South Korea’s capital. The goal of this research is to find the impact of meteorological extremes and particle levels on human health. The analysis was conducted using hourly air pollutant concentrations, meteorological variables, and the daily mortality from cerebrovascular disease. Results show that the effect of fine particulate matter on mortality from cerebrovascular disease was more noticeable during meteorological extremes. The linkage between extreme weather conditions and mortality was more apparent in winter than in summer. Comprehensive studies of various causes of diseases should be continued to more accurately analyze the effects of fine particulate matter on human health and meteorological extremes, and to further minimize the public health impact of air pollution and meteorological conditions.
BACKGROUND: Although changes in skin depend on the external environment, researchers have performed only a few studies on effect of the actual environment. Most studies have researched skin characterization based on changes in the humidity or temperature. AIM/OBJECTIVE: This study aimed to evaluate changes in the skin based on the difference in indoor and outdoor temperatures and humidity during summer in South Korea and Southeast Asia. METHODS: Twenty-two female participants aged 25-39 years were included. Skin hydration, sebum (cheek, forehead), colour, transparency and pores of the participants were measured after a 30-min exposure to high temperature and high humidity (HTHH) environment and a 30-min exposure to low temperature and low humidity (LTLH) environment. Subsequently, exposure to HTHH environment for 30 min +LTLH environment for 30 min was performed after a total of 1 h and repeated. RESULTS: Repeated exposure to HTHH and LTLH environments increased the skin’s sebum content and haemoglobin index. Additionally, skin elasticity was significantly reduced, with patients in their 30 s showing greater changes than those in their 20 s. CONCLUSION: Repeated differences in temperature and humidity cause skin ageing, loosen skin vessels and reduce skin elasticity, thereby leading to skin ageing.
Managing information at city level has become increasingly important owing to the introduction of smart cities and the increasing severity of disasters due to climate change. A data collection framework, model construction, and information management must be established to systematically manage information at the city level. This study developed an urban model generation method using detailed attributes within the City Geography Markup Language (CityGML), a standard data schema for 3D representation of cities based on different types of publicly available information within Korea. The generated model was used to develop a method for simulating flooding status, degree of flooding, and level of building damage after heavy rainfall, in Korea. Furthermore, we developed a method to estimate the loss of human life and property damage by combining the results of the flood analysis with the city model. The proposed methodology supports the creation of standard-based models for flood analysis and exhibits strong interoperability for application to different areas of analysis.
Background: Preterm birth contributes to the morbidity and mortality of newborns and infants. Recent studies have shown that maternal exposure to particulate matter and extreme temperatures results in immune dysfunction, which can induce preterm birth. This study aimed to evaluate the association between fine particulate matter (PM(2.5)) exposure, temperature, and preterm birth in Seoul, Republic of Korea. Methods: We used 2010-2016 birth data from Seoul, obtained from the Korea National Statistical Office Microdata. PM(2.5) concentration data from Seoul were generated through the Community Multiscale Air Quality (CMAQ) model. Seoul temperature data were collected from the Korea Meteorological Administration (KMA). The exposure period of PM(2.5) and temperature were divided into the first (TR1), second (TR2), and third (TR3) trimesters of pregnancy. The mean PM(2.5) concentration was used in units of ×10 µg/m(3) and the mean temperature was divided into four categories based on quartiles. Logistic regression analyses were performed to evaluate the association between PM(2.5) exposure and preterm birth, as well as the combined effects of PM(2.5) exposure and temperature on preterm birth. Result: In a model that includes three trimesters of PM(2.5) and temperature data as exposures, which assumes an interaction between PM(2.5) and temperature in each trimester, the risk of preterm birth was positively associated with TR1 PM(2.5) exposure among pregnant women exposed to relatively low mean temperatures (<3.4 °C) during TR1 (OR 1.134, 95% CI 1.061-1.213, p < 0.001). Conclusions: When we assumed the interaction between PM(2.5) exposure and temperature exposure, PM(2.5) exposure during TR1 increased the risk of preterm birth among pregnant women exposed to low temperatures during TR1. Pregnant women should be aware of the risk associated with combined exposure to particulate matter and low temperatures during TR1 to prevent preterm birth.
This study aims to quantitatively identify the economic value of the comprehensive improvement of environmental degradations caused by climate change. The research method applied to that is the choice experiment. Fine particulate matter, algae bloom, and heat waves were selected as individual attributes constituting environmental problems. It was found that the willingness to pay could not be induced for any level of improvement in algal bloom. It was concluded that if heat waves improved to the medium level where the number of heat-related illnesses and estimated deaths decreased by 50% compared to the current level, there would be a loss in value by USD 13.33. The value of improving environmental problems is USD 7.69 per household per year, and the improvement of fine particulate matter was the highest value attributed by consumers. This study is significant in that it comprehensively evaluates severe environmental problems, reflects their priorities and importance, and assesses the value for each level. It provides important foundational data for establishing effective budget input strategies to maximize consumer benefits and aids in the preparation of effective policies by establishing more detailed goals to achieve net-zero carbon emissions and the Sustainable Development Goals.
BACKGROUND: Given that low income worsens health outcomes, income differences may affect health disparities in weather-related illnesses. The aim of this study was to investigate the association between income levels and prevalence of heat- and cold-related illnesses among Korean adults. METHODS: The current study comprised 535,186 participants with all variables on income and health behaviors. Patients with temperature-related illnesses were defined as individuals with outpatient medical code of heat- and cold-related illnesses. We categorized individual income into three levels: “low” for the fourth quartile (0-25%), “middle” for the second and the third quartiles (25-75%), and “high” for the first quartile (75-100%). To examine income-related health disparities, Cox proportional hazard regression was performed. Hazard ratios (HRs) and 95% CI (confidence interval) for heat- and cold-related illnesses were provided. The model adjusted for age, sex, smoking status, alcohol drinking, exercise, body mass index, hypertension, hyperglycemia, and local income per capita. RESULTS: A total of 5066 (0.95%) and 3302 (0.62%) cases identified patients with heat- and cold-related illnesses, respectively. Compared with high income patients, the adjusted HR for heat-related illnesses was significantly increased in the low income (adjusted HR = 1.103; 95% CI: 1.022-1.191). For cold-related illnesses, participants with low income were likely to have 1.217 times greater likelihood than those with high income (95% CI: 1.107-1.338), after adjusting for other covariates. In the stratified analysis of age (20-64 years and over 65 years) and sex, there was no difference in the likelihood of heat-related illnesses according to income levels. On the other hand, an HR for cold-related illnesses was higher in patients aged 20 to 64 years than in those aged over 65 years. Male with low income had also a higher HR for cold-related illnesses than female with low income. CONCLUSIONS: Our results showed that heat- or cold-related illnesses were more prevalent in Koreans with low income than those with high income. Strategies for low-income subgroups were needed to reduce greater damage due to the influence of extreme temperature events and to implement effective adaptation.
Changes of thermal environment can lead to unfavorable impacts such as a decrease of thermal stratification, increase of energy consumption, and increase of thermal health risk. Investigating changes in outdoor thermal environments can provide meaningful information for addressing economic and social issues and related challenges. In this study, thermal environment changes in South Korea were investigated using a nonstationary two-component Gaussian mixture model (NSGMM) for air temperature and two thermal comfort indices. For this, the perceived temperature (PT) and universal thermal climate index (UTCI) were employed as the thermal comfort index. Thermal comfort indices were computed using observed meteorological data at 26 weather stations for 37 years in South Korea. Meanwhile, trends of thermal comforts in the warm and cool seasons were simultaneously modeled by the NSGMM. The results indicate significant increasing trends in thermal comfort indices for South Korea. The increasing trends in thermal comfort indices both the warm and cool seasons were detected while the magnitudes of the trends are significantly different. This difference between the magnitude of trends led to an increase in mean and inter-annual variability of thermal comfort indices based on PT, while an increase of mean and decrease of inter-annual variability were observed based on the UTCI. Moreover, the annual proportion of the category referring to days in comfort based on the results of PT has decreased due to the different trends of thermal comfort indices in the warm and cool seasons. This decrease may lead to an increase of thermal health risk that is larger than what would be expected from the results considering the increasing trend of the annual mean temperature in South Korea. From this result, it can be inferred that the thermal health risk in South Korea may be more adverse than what we originally expected from the current temperature trend.
Extreme heat exposure has severe negative impacts on humans, and the issue is exacerbated by climate change. Estimating spatial heat stress such as mean radiant temperature (MRT) is currently difficult to apply at city scale. This study constructed a method for estimating the MRT of street canyons using Google Street View (GSV) images and investigated its large-scale spatial patterns at street level. We used image segmentation using deep learning to calculate the view factor (VF) and project panorama into fisheye images. We calculated sun paths to estimate MRT using panorama images from Google Street View. This paper shows that regression analysis can be used to validate between estimated short-wave, long-wave radiation and the measurement data at seven field measurements in the clear-sky (0.97 and 0.77, respectively). Additionally, we compared the calculated MRT and land surface temperature (LST) from Landsat 8 on a city scale. As a result of investigating spatial patterns of MRT in Seoul, South Korea, we found that a high MRT of street canyons (>59.4 degrees C) is mainly distributed in open space areas and compact low-rise density buildings where the sky view factor is 0.6-1.0 and the building view factor (BVF) is 0.35-0.5, or west-east oriented street canyons with an SVF of 0.3-0.55. However, high-density buildings (BVF: 0.4-0.6) or high-density tree areas (Tree View Factor, TVF: 0.6-0.99) showed low MRT (<47.6). The mapped MRT results had a similar spatial distribution to the LST; however, the MRT was lower than the LST in low tree density or low-rise high-density building areas. The method proposed in this study is suitable for a complex urban environment consisting of buildings, trees, and streets. This will help decision makers understand spatial patterns of heat stress at the street level.
BACKGROUND: Although urbanization is often an important topic in climate change studies, the complex effect of urbanization on heat vulnerability in urban and rural areas has rarely been studied. We investigated the disparate effects of urbanization on heat vulnerability in urban and rural areas, using nationwide data. METHODS: We collected daily weather data for all 229 administrative districts in South Korea (2011-17). Population density was applied as an urbanization indicator. We calculated the heat-mortality risk using a distributed lag nonlinear model and analysed the relationship with population density. We also examined district characteristics that can be related to the spatial heterogeneity in heat-mortality risk. RESULTS: We found a U-shaped association between population density and heat-mortality risk, with the highest risk for rural populations; in urban areas, risk increases with increasing population density. Higher heat-mortality risk was associated with a lower number of hospital beds per person and higher percentage of people requiring recuperation. The association between hospital beds and heat-mortality risk was prominent in high-density urban areas, whereas the association between the percentage of people requiring recuperation and heat-mortality risk was pronounced in rural areas. CONCLUSIONS: Our findings indicate that the association between population density and heat-mortality risk is different in urban and rural areas, and that district characteristics related to heat-mortality risk also differ by urbanicity. These results can contribute to understanding the complex role of urbanization on heat vulnerability and can provide evidence to policy makers for prioritizing resources.
Access to urban greenspace has many benefits such as improved health and social cohesion. If access differs by population, these benefits make access to greenspace an environmental justice issue, but little is known regarding accessibility of parks among different sub-groups in Seoul, South Korea. We explored potential socioeconomic inequities for access to parks in Seoul measuring two park provision metrics: total park area per capita (TPPC), and park accessibility index determined by size and proximity of parks. We assessed correlations between a deprivation index for the 25 Gus (administrative unit equivalent to the US borough) and each park provision metric. Regression analyses were applied for the associations between eight socioeconomic indicators of the 424 Dongs (equivalent to the US neighborhood) and each park provision metric. An interquartile range (IQR) increase in percent elderly (> 65 years) (3.2%) was significantly associated with larger TPPC (1.6 m(2)/person, 95% CI: 0.8, 2.4). Park accessibility index was associated with more socioeconomic variables than was TPPC. An IQR increase in percent elderly and divorce rates (1.2/1000 population) was associated with increased park accessibility by 3571 km (95% CI: 1103, 6040) and decreased park accessibility by 1387 (95% CI: -2706, -67), respectively. An IQR increase in percentage of the population receiving social low-income support aid (2.2%) was associated with increased park accessibility (reflecting park size and proximity of parks) of residential parks near residential areas by 1568 (95% CI: 15, 3120). Results suggest higher park access for socioeconomically disadvantaged regions. Findings indicate that measures of detailed park access considering spatial proximity and park size may more accurately measure park inequity compared to more basic metrics (e.g. TPPC), which may bias estimation of park inequity by capturing only one characteristic of parks. Detailed park measures should be considered in urban planning and health studies of greenspace.
We analyzed the relationship between the temperature and traffic accidents in Seoul-Incheon, Busan, Daegu, Daejeon, and Gwangju by the time-of-day (06:00 to 22:00, divided into segments of 4 h) and age of casualties between 2012 and 2017 for the summer season (June to August). A generalized additive model and meta-analysis were employed to analyze this relationship. We found that the threshold temperatures was observed to be approximately 30 degrees C. Above this temperature, traffic accidents increased in four urban areas, except Busan, which is a popular tourist location. In total, traffic accidents increased by approximately 0.59% (95% confidence interval of 0.41-0.75) per 1 degrees C increase in the daily maximum temperature, with substantial differences between the different areas, ranging from 0.12% (CI = – 0.26-0.50) in Busan to 1.08% (CI = 0.45-1.71) in Gwangju. The morning and evening hours showed a greater increase in traffic accidents than other timeframes. The increase in traffic accidents for young casualties was statistically significant at all times, and that for elderly casualties was observed at 10:00-14:00 and 18:00-22:00. The results of this study could provide information for developing customized traffic accident reduction policies considering time-of-day, age of casualties, and type of city.
Many countries are operating a heatwave warning system (HWWS) to mitigate the impact of heatwaves on human health. The level of heatwave warning is normally determined by using the threshold temperature of heat-related morbidity or mortality. However, morbidity and mortality threshold temperatures have not been used together to account for the severity of health impacts. In this study, we developed a heatwave warning system with two different warning levels: Level-1 and Level-2, by analyzing the severity and likelihood of heat-related morbidity and mortality using the generalized additive model. The study particularly focuses on the cases in Seoul, South Korea, between 2011 and 2018. The study found that the threshold temperature for heat-related morbidity and mortality are 30 °C and 33 °C, respectively. Approximately 73.1% of heat-related patients visited hospitals when temperature was between 30 °C and 33 °C. We validated the developed HWWS by using both the threshold temperatures of morbidity and mortality. The area under curves (AUCs) of the proposed model were 0.74 and 0.86 at Level-1 and Level-2, respectively. On the other hand, the AUCs of the model using only the mortality threshold were 0.60 and 0.86 at Level-1 and Level-2, respectively. The AUCs of the model using only the morbidity threshold were 0.73 and 0.78 at Level-1 and Level-2, respectively. The results suggest that the updated HWWS can help to reduce the impact of heatwaves, particularly on vulnerable groups, by providing the customized information. This also indicates that the HWWS could effectively mitigate the risk of morbidity and mortality.
BACKGROUND: Due to climate change, days with high temperatures are becoming more frequent. Although the effect of high temperature on the kidneys has been reported in research from Central and South America, Oceania, North America and Europe, evidence from Asia is still lacking. This study aimed to examine the association between short-term exposure to high temperatures and acute kidney injury (AKI) in a nationwide study in South Korea. METHODS: We used representative sampling data from the 2002-2015 National Health Insurance Service-National Sample Cohort in South Korea to link the daily mean temperatures and AKI cases that occurred in the summer. We used a bidirectional case-crossover study design with 0-7 lag days before the emergency room visit for AKI. In addition, we stratified the data into six income levels to identify the susceptible population. RESULTS: A total of 1706 participants were included in this study. The odds ratio (OR) per 1°C increase at 0 lag days was 1.051, and the ORs per 1°C increase at a lag of 2 days were both 1.076. The association between exposure to high temperatures and AKI was slightly greater in the low-income group (OR = 1.088; 95% CI: 1.049-1.128) than in the high-income group (OR = 1.065; 95% CI: 1.026-1.105). CONCLUSIONS: In our study, a relationship between exposure to high temperatures and AKI was observed. Precautions should be taken at elevated temperatures to minimize the risk of negative health effects.
Many studies have shown that heat waves can cause both death and disease. Considering the adverse health effects of heat waves on vulnerable groups, this study highlights their impact on workers. The present study thus investigated the association between heat exposure and the likelihood of hospitalization and death, and further identified the risk of heat-related diseases or death according to types of heat and dose-response modeling with heat threshold. Workers were selected from the Korean National Health Insurance Service-National Sample Cohort 2002-2015, and regional data measured by the Korea Meteorological Administration were used for weather information. The relationship between hospitalization attributable to disease and weather variables was analyzed by applying a generalized additional model. Using the Akaike information criterion, we selected a model that presented the optimal threshold. Maximum daily temperature (MaxT) was associated with an increased risk of death and outdoor mortality. The association between death outdoors and MaxT had a threshold of 31.2 °C with a day zero lag effect. History of medical facility visits due to the health effects of heat waves was evident in certain infectious and parasitic diseases (A and B), cardio and cerebrovascular diseases (I20-25 and I60-69), injury, poisoning, and other consequences of external causes (S, T). The study demonstrated that heat exposure is a risk factor for death and infectious, cardio-cerebrovascular, and genitourinary diseases, as well as injuries or accidents among workers. The finding that heat exposure affects workers’ health has future implications for decision makers and researchers.
OBJECTIVE: This study aimed to determine the association between maximum daily temperature and work-related injuries according to employment status in South Korea. METHODS: Data on workers’ compensation claims and daily maximum temperature between May 20 and September 10, 2017-2018, were collected and analyzed. The absolute temperature risk effect (ATR) was evaluated by comparing the risk effect at 2 temperatures (30°C vs 33°C) across all communities using 2-stage time-series analysis. RESULTS: The association between high temperatures and work-related injuries was statistically significant in the construction sector (ATR, 1.129; 95% confidence interval [CI], 1.010-1.261). In addition, the findings of this study also demonstrated a higher risk effect among nonpermanent workers (ATR, 1.109; 95% CI, 1.013-1.214) at 33°C versus 30°C when compared with permanent workers (ATR, 0.963; 95% CI, 0.891-1.041). CONCLUSIONS: This study found a significant association between high temperatures and work-related injuries among nonpermanent workers in South Korea.
Out-of-hospital cardiac arrest (OHCA) is a notable public health issue with negative outcomes, such as high mortality and aftereffects. Additionally, the adverse effects of extreme temperatures on health have become more important under climate change; however, few studies have investigated the relationship between temperature and OHCA. In this study, we examined the association between temperature and OHCA and its underlying risk factors. We conducted a two-stage time-series analysis using a Poisson regression model with a distributed lag non-linear model (DLNM) and meta-analysis, based on a nationwide dataset from South Korea (2008-2018). We found that 17.4% of excess OHCA was attributed to cold, while 0.9% was attributed to heat. Based on central estimates, excess OHCA attributed to cold were more prominent in the population with hypertension comorbidity (31.0%) than the populations with diabetes (24.3%) and heart disease (17.4%). Excess OHCA attributed to heat were larger in the populations with diabetes (2.7%) and heart disease comorbidity (2.7%) than the population with hypertension (1.2%) based on central estimates. Furthermore, the time-varying excess OHCA attributed to cold have decreased over time, and although those of heat did not show a certain pattern during the study period, there was a weak increasing tendency since 2011. In conclusion, we found that OHCAs were associated with temperature, and cold temperatures showed a greater impact than that of hot temperatures. The effects of cold and hot temperatures on OHCA were more evident in the populations with hypertension, diabetes, and heart diseases, compared to the general population. In addition, the impacts of heat on OHCA increased in recent years, while those of cold temperatures decreased. Our results provide scientific evidence for policymakers to mitigate the OHCA burden attributed to temperature.
BACKGROUND: Emerging evidence supports an association between heat exposure and acute kidney injury (AKI). However, there is a paucity of studies on the association between cold exposure and AKI. OBJECTIVE: We aimed to investigate the associations of cold exposure with hospital admission and mortality due to AKI and to explore whether these associations were influenced by age and sex. METHODS: Information on daily counts of hospital admission and mortality due to AKI in 16 regions of Korea during the cold seasons (2010-2019) was obtained from the National Health Insurance Service (a single national insurer providing universal health coverage) and Statistics Korea. Daily mean temperature and relative humidity were calculated from hourly data obtained from 94 monitoring systems operated by the Korean Meteorological Administration. Associations of low temperatures (<10th percentile of daily mean temperature) and cold spells (≥2 consecutive days with <5th percentile of daily mean temperature) up to 21 days with AKI were estimated using quasi-Poisson regression models adjusted for potential confounders (e.g., relative humidity and air pollutants) with distributed lag models and univariate meta-regression models. RESULTS: Low temperatures were associated with hospital admission due to AKI [relative risk (RR) = 1.12, 95 % confidence interval (CI): 1.09, 1.16]. Cold spells were associated with hospital admission (RR = 1.87, 95 % CI: 1.46, 2.39) and mortality due to AKI (RR = 4.84, 95 % CI: 1.30, 17.98). These associations were stronger among individuals aged ≥65 years than among those aged <65 years. CONCLUSION: Our results underscore the need for the general population, particularly the elderly, physicians, and other healthcare providers to be more vigilant to cold exposure, given the risk of AKI. Government agencies need to develop specific strategies for the prevention and early detection of cold exposure-related AKI.
BACKGROUND: Climate change is predicted to increase the frequency, intensity, and duration of extreme cold events in the mid-latitudes. However, although diabetes is one of the most critical metabolic diseases due to its high and increasing prevalence worldwide, few studies have investigated the short-term association between cold exposure and diabetes-related outcomes. OBJECTIVE: The aim of this study was to investigate the associations between cold spells and their characteristics (intensity, duration, and seasonal timing) and hospital admission and mortality due to diabetes. METHODS: This study used claims data from the National Health Insurance Service and cause-specific mortality data from Statistics Korea (2010-2019). Cold spells were defined as ≥2 consecutive days with a daily mean temperature lower than the region-specific 5th percentile during the cold season (November-March). Quasi-Poisson regressions combined with distributed lag models were used to assess the associations between exposures and outcomes in 16 regions across the Republic of Korea. Meta-analyses were conducted to pool the region-specific estimates. RESULTS: Exposure to cold spells was associated with an increased risk of hospital admission [relative risk (RR) = 1.45, 95% confidence interval (CI): 1.26, 1.66] and mortality (RR = 2.02, 95% CI: 1.37, 2.99) due to diabetes. The association between cold spells and hospital admission due to diabetes was stronger for cold spells that were more intense, longer, and occurred later during the cold season. The association between cold spells and diabetes-related mortality was stronger for more intense and longer cold spells. CONCLUSION: This study emphasizes the importance of developing effective interventions against cold spells, including education on the dangers of cold spells and early alarm systems. Further studies are needed to create real-world interventions and evaluate their effectiveness in improving diabetes-related outcomes.
BACKGROUND: Despite concerns regarding increasingly frequent and intense heat waves due to global warming, there is still a lack of information on the effects of extremely high temperatures on the adult abundance of mosquito species that are known to transmit vector-borne diseases. This study aimed to evaluate the effects of extremely high temperatures on the abundance of mosquitoes by analyzing time series data for temperature and mosquito abundance in Incheon Metropolitan City (IMC), Republic of Korea, for the period from 2015 to 2020. METHODS: A generalized linear model with Poisson distribution and overdispersion was used to model the nonlinear association between temperature and mosquito count for the whole study area and for its constituent urban and rural regions. The association parameters were pooled using multivariate meta-regression. The temperature-mosquito abundance curve was estimated from the pooled estimates, and the ambient temperature at which mosquito populations reached maximum abundance (TMA) was estimated using a Monte Carlo simulation method. To quantify the effect of extremely high temperatures on mosquito abundance, we estimated the mosquito abundance ratio (AR) at the 99th temperature percentile (AR(99th)) against the TMA. RESULTS: Culex pipiens was the most common mosquito species (51.7%) in the urban region of the IMC, while mosquitoes of the genus Aedes (Ochlerotatus) were the most common in the rural region (47.8%). Mosquito abundance reached a maximum at 23.5 °C for Cx. pipiens and 26.4 °C for Aedes vexans. Exposure to extremely high temperatures reduced the abundance of Cx. pipiens mosquitoes {AR(99th) 0.34 [95% confidence interval (CI) 0.21-0.54]} to a greater extent than that of Anopheles spp. [AR(99th) 0.64 (95% CI 0.40-1.03)]. When stratified by region, Ae. vexans and Ochlerotatus koreicus mosquitoes showed higher TMA and a smaller reduction in abundance at extreme heat in urban Incheon than in Ganghwa, suggesting that urban mosquitoes can thrive at extremely high temperatures as they adapt to urban thermal environments. CONCLUSIONS: We confirmed that the temperature-related abundance of the adult mosquitoes was species and location specific. Tailoring measures for mosquito prevention and control according to mosquito species and anticipated extreme temperature conditions would help to improve the effectiveness of mosquito-borne disease control programs.
As incidences of food poisoning, especially norovirus-induced diarrhea, are associated with climate change, there is a need for an approach that can be used to predict the risks of such illnesses with high accuracy. In this paper, we predict the winter norovirus incidence rate in Korea compared to that of other diarrhea-causing viruses using a model based on B-spline added to logistic regression to estimate the long-term pattern of illness. We also develop a risk index based on the estimated probability of occurrence. Our probabilistic analysis shows that the risk of norovirus-related food poisoning in winter will remain stable or increase in Korea based on various Representative Concentration Pathway (RCP) scenarios. Our approach can be used to obtain an overview of the changes occurring in regional and seasonal norovirus patterns that can help assist in making appropriate policy decisions.
ABSTRACT: Norovirus food poisoning outbreaks in Korea (South) appeared in the 2000s and have been increasing since then. We aimed to investigate the epidemiological features of norovirus food poisoning outbreaks in Korea from 2002 to 2017, on the basis of official food poisoning statistics and publically reliable reports, and to find any associations with climate factors. Norovirus was the most common cause of food poisoning among known causative substances in Korea during the study period. More than one-third of the outbreaks occurred in group meal service facilities, including school lunch programs. A few of these facilities used groundwater contaminated with noroviruses to wash or cook food, which contributed to outbreaks. Norovirus occurrences showed strong seasonality: cold and relatively dry winter air may help norovirus to flourish. Both norovirus genotypes GI and GII that are infectious to humans were detected, with GII becoming more prevalent than GI. According to our correlation analysis in connection with climate factors, average temperatures, the highest and lowest temperatures, precipitation, the number of rain days, and humidity showed a significant negative correlation with a monthly norovirus occurrence (P < 0.05). The lowest temperature and average temperature had higher coefficients of correlation, -0.377 and -0.376, respectively. The norovirus outbreaks in Korea showed complex etiological characteristics, although more prevailed in wintertime, and are now a major public health problem. The use of groundwater in group meal service settings is a public health issue, as well as a norovirus concern; therefore, groundwater used in food service facilities and businesses should be treated for safety.
Big data can be used to correlate diseases and climatic factors. The prevalence of influenza (flu) virus, accounting for a large proportion of respiratory infections, suggests that the effect of climate variables according to seasonal dynamics of influenza virus infections should be investigated. Here, trends in flu virus detection were analyzed using data from 9,010 tests performed between January 2012 and December 2018 at Dankook University Hospital, Cheonan, Korea. We compared the detection of the flu virus in Cheonan area and its association with climate change. The flu virus detection rate was 9.9% (894/9,010), and the detection rate was higher for flu virus A (FLUAV; 6.9%) than for flu virus B (FLUBV; 3.0%). Both FLUAV and FLUBV infections are considered an epidemic each year. We identified 43.1% (n = 385) and 35.0% (n = 313) infections in children aged < 10 years and adults aged > 60 years, respectively. The combination of these age groups encompassed 78.1% (n = 698/894) of the total data. Flu virus infections correlated with air temperature, relative humidity, vapor pressure, atmospheric pressure, particulate matter, and wind chill temperature (P < 0.001). However, the daily temperature range did not significantly correlate with the flu detection results. This is the first study to identify the relationship between long-term flu virus infection with temperature in the temperate region of Cheonan.
Although dust storms have been associated with adverse health outcomes, studies on the burden of dust storms on deaths are limited. As global warming has induced significant climate changes in recent decades, which have accelerated desertification worldwide, it is necessary to evaluate the burden of dust storm-induced premature mortality using a critical measure of disease burden, such as the years of life lost (YLL). The YLL attributable to dust storms have not been examined to date. This study investigated the association between Asian dust storms (ADS) and the YLL in Seoul, South Korea, during 2002-2013. We conducted a time-series study using a generalized additive model assuming a Gaussian distribution and applied a distributed lag model with a maximum lag of 5 days to investigate the delayed and cumulative effects of ADS on the YLL. We also conducted stratified analyses using the cause of death (respiratory and cardiovascular diseases) and sociodemographic status (sex, age, education level, occupation, and marital status). During the study period, 108 ADS events occurred, and the average daily YLL was 1511 years due to non-accidental causes. The cumulative ADS exposure over the 6-day lag period was associated with a significant increase of 104.7 (95% CI, 31.0-178.5 years) and 34.4 years (4.0-64.7 years) in the YLL due to non-accidental causes and cardiovascular mortality, respectively. Sociodemographic analyses revealed associations between ADS exposure and the YLL in males, both <65 and ≥65 years old, those with middle-level education, and the unemployed, unmarried, and widowed (26.5-83.8 years). This study provides new evidence suggesting that exposure to dust storms significantly increases the YLL. Our findings suggest that dust storms are a critical environmental risk affecting premature mortality. These results could contribute to the establishment of public health policies aimed at managing dust storm exposure and reducing premature deaths.
PURPOSE: The characteristic topography and climate often affect the occurrence of large-scale wildfires in the Eastern Gangwon-do region of Korea. However, there are no studies on the health effects of these wildfires in Korea. This study aimed to analyze the differences in medical use between a wildfire-affected area and an adjacent non-affected area before and after a wildfire in 2019 in Gangwon-do, Korea. MATERIALS AND METHODS: We used medical usage data from the Korean National Health Insurance Corporation. Rates of medical use were determined for citizens of a wildfire-affected area in the Eastern Yeongdong region and a non-affected area in the Western Yeongseo region. Logistic regression analysis was performed considering an increase in medical use per individual as a dependent variable; age, sex, income, smoking, drinking, and exercise were included as confounding variables. RESULTS: The odds ratio for medical use in Yeongdong region increased significantly after 3 days, 3 months, and 1 year after a fire occurred, compared with Yeongseo region. CONCLUSION: The results of this study confirmed that the use of medical care increased for residents of a wildfire-affected area, compared with those of an adjacent non-affected area. This is the first study on the relationship between wildfires and inpatient medical use in Korea.
OBJECTIVES: In April 2000, a series of wildfires occurred simultaneously in five adjacent small cities located on the eastern coast of Korea. These wildfires burned approximately 23,794 hectares of forestland over several days. We investigated the effects of prenatal exposure to the by-products generated by wildfire disasters on birth weight. METHODS: Birth weight data were obtained for 1999-2001 from the birth registration database of the Korean National Statistical Office and matched with the zip code and exposed/unexposed pregnancy week for days of the wildfires. Generalized linear models were then used to assess the associations between birth weight and exposure to wildfires after adjusting for fetal sex, gestational age, parity, maternal age, maternal education, paternal education, and average exposed atmospheric temperature. RESULTS: Compared with unexposed pregnancies before and after the wildfires, mean birth weight decreased by 41.4 g (95% confidence interval [CI], -72.4 to -10.4) after wildfire exposure during the first trimester, 23.2 g (95% CI, -59.3 to 13.0) for exposure during the second trimester, and 27.0 g (95% CI, -63.8 to 9.8) during the third trimester. In the adjusted model for infants exposed in utero during any trimester, the mean birth weight decreased by 32.5 g (95% CI, -53.2 to -11.7). CONCLUSIONS: We observed a 1% reduction in birth weight after wildfire exposure. Thus, exposure to by-products generated during a wildfire disaster during pregnancy may slow fetal growth and cause developmental delays.
South Korea had the highest annual average PM2.5 exposure levels in the Organization for Economic Co-operation and Development (OECD) in 2019, and air pollution is consistently ranked as citizens’ top environmental concern. South Korea is also one of the world’s top ten emitter countries of CO2. Co-benefit mitigation policies can address both air pollution and climate change. Utilizing an alternative co-benefit approach, which views air pollution reduction as the primary goal and climate change mitigation as secondary, this research conducts a scenario analysis to forecast the health and climate benefits of fuel substitution in South Korea’s electricity generation sector. Health benefits are calculated by avoided premature mortality and years of life lost (YLL) due to ischemic heart disease, stroke, chronic obstructive pulmonary disease (COPD), lung cancer, and acute lower respiratory infections (ALRI). The study finds that use of liquefied natural gas (LNG) instead of coal over the 2022-2050 period would result in an average of 116 fewer premature deaths (1152 YLL) and 80.8 MTCO(2)e fewer emissions per year. Over the same period, maintaining and maximizing the use of its nuclear energy capacity, combined with replacing coal use with LNG, would result in an average of 161 fewer premature deaths (1608 YLL) and 123.7 MTCO(2)e fewer emissions per year.
INTRODUCTION: Children with allergies are at greater risk of becoming sensitized to allergenic pollens in response to environmental changes. This study investigated the relationship between changes in pollination associated with meteorologic changes and the sensitization rates of children to tree pollen allergens in the metropolitan area of Seoul, Korea. METHODS: The study population consisted of 8,295 children who visited the pediatric allergy clinics at Hanyang University Seoul and Guri Hospital for allergy symptoms between January 1, 1998, and December 31, 2019. Pollen was collected at the two hospitals during the study using a Burkard 7-day sampler. Meteorologic data were obtained from the National Weather Service. RESULTS: Among the major tree pollens, the largest increase in allergic sensitization was to oak, hazel, and alder pollens (0.28% annually). The pollen-sensitization rates increased annually within younger age groups. The duration of the pollen season was 98 days in 1998 and 140 days in 2019. Positive correlations were determined between the duration of the pollen season and the rates of sensitization to tree pollens, as well as between the pollen-sensitization rates and increasing temperature. CONCLUSIONS: This study demonstrated the correlation between weather changes and the resulting changes in the pollen season with sensitization rates to allergenic pollens in children living in the Seoul metropolitan area. An annual increase in sensitization rates in younger children was determined. This pattern is expected to continue due to continuing climate change.
Sandstorms and/or duststorms that are affecting the Korean peninsula occur most frequently in the spring season in the arid and semi-arid area of sand deserts including Badainjaran, Tengger, Mu Us, Hunsandakue and Keoeolchin, Gobi region and Loess Plateau in the Asian continent. The area of Asian dust source regions cover most of northern China and Mongolia. Warning is issued when the hourly averaged dust(PM10) concentration is expected to exceed 800 ㎛/㎥ for over 2hours.
Pollen, a major causal agent of respiratory allergy, is mainly affected by weather conditions. In Korea, pollen and weather data are collected by the national observation network. Forecast models and operational services are developed and provided based on the national pollen data base. Using the pollen risk forecast information will help patients with respiratory allergy to improve their lives. Changes in temperature and CO(2) concentration by climate change affect the growth of plants and their capacity of producing more allergenic pollens, which should be considered in making the future strategy on treating allergy patients.
Many studies have been conducted to assess the health effects of climate change in Korea. However, there has been a lack of consideration regarding how the results of these studies can be applied to relevant policies. The current study aims to examine research trends at the agenda-setting stage and to review future ways in which health-related adaptation to climate change can be addressed within national public health policy. A systematic review of previous studies of the health effects of climate change in Korea was conducted. Many studies have evaluated the effect of ambient temperature on health. A large number of studies have examined the effects on deaths and cardio-cerebrovascular diseases, but a limitation of these studies is that it is difficult to apply their findings to climate change adaptation policy in the health sector. Many infectious disease studies were also identified, but these mainly focused on malaria. Regarding climate change-related factors other than ambient temperature, studies of the health effects of these factors (with the exception of air pollution) are limited. In Korea, it can be concluded that studies conducted as part of the agenda-setting stage are insufficient, both because studies on the health effects of climate change have not ventured beyond defining the problem and because health adaptation to climate change has not been set as an important agenda item. In the future, the sharing and development of relevant databases is necessary. In addition, the priority of agenda items should be determined as part of a government initiative.
BACKGROUND: Previous studies have reported that fine particulate matter (PM(2.5)) affects the incidence of premature births. In addition, recent studies have suggested that heat waves have a negative impact on birth outcomes. However, the combined effect of PM(2.5) and heat waves on the incidence of premature birth is controversial. This study investigated the independent and combined effects of PM(2.5) and heat wave exposures during the 1st and 2nd trimesters on premature birth. METHODS: The National Statistical Office of Korea provided birth data from 2010 to 2016. Preterm birth was defined as birth between 22 and 36 weeks. To assess the exposure to PM(2.5) and heat waves, we used PM(2.5) data estimated by the Community Multiscale Air Quality Modeling System (CMAQ) and heat wave warning data provided by the Korea Meteorological Administration. A multivariate logistic regression was used to investigate the risk of preterm birth according to the exposure to PM(2.5) and heat waves during the 1st and 2nd trimesters, and it was adjusted for residential area, year of birth, season of birth, parity, education level of the mother, age of the mother, and sex of the baby. RESULTS: In the 2nd trimester, compared with the 0 h of heat wave exposure (?67 percentile), 62.50-314.00 h (79-88 percentile) and>315.00 h of heat wave exposure (>88 percentile) were both significantly associated with preterm birth (OR for 79-88 percentile, 1.037, 95% CI, 1.003-1.073; OR for > 88 percentile, 1.174, 95% CI, 1.134-1.215). However, PM(2.5) exposure was not significantly associated with preterm birth. On the other hand, in the analysis to evaluate the combined effect of PM(2.5) and heat wave exposures of the 2nd trimester, compared with 0 h of heat wave exposure (?67 percentile) and<11.64 ?g/m(3) (?25 percentile) of PM(2.5), 11.64-22.74 ?g/m(3) (?25 percentile), 22.74-27.58 ?g/m(3) (26-50 percentile), and 27.57-32.39 ?g/m(3) (51-75 percentile) of PM(2.5) exposure combined with>315.00 h of heat wave exposure (>88 percentile) were all significantly associated with preterm birth. In addition, the effect size was increased with an increase of PM(2.5) exposure (OR for ? 25 percentile, 1.148, 95% CI, 1.095-1.203; OR for 26-50 percentile, 1.248, 95% CI, 1.178-1.323; OR for 51-75 percentile, 1.370, 95% CI, 1.245-1.507). CONCLUSION: Our findings suggest that the combined effect of heat wave and PM(2.5) exposure during the 2nd trimester on the risk of preterm birth was greater than that of each exposure alone. In other words, exposure to PM(2.5) increases the impact of heat waves on the risk of preterm birth. These results indicate that control of prenatal exposure to fine particular matter and extreme temperatures is important for the prevention of preterm birth.
BACKGROUND/AIM: Previous studies have suggested that the short-term ambient air pollution and temperature are associated with myocardial infarction. In this study, we aimed to conduct a time-series analysis to assess the impact of fine particulate matter (PM2.5) and temperature on acute myocardial infarction (AMI) among adults over 20 years of age in Korea by using the data from the Korean National Health Information Database (KNHID). METHODS: The daily data of 192,567 AMI cases in Seoul were collected from the nationwide, population-based KNHID from 2005 to 2014. The monitoring data of ambient PM2.5 from the Seoul Research Institute of Public Health and Environment were also collected. A generalized additive model (GAM) that allowed for a quasi-Poisson distribution was used to analyze the effects of PM2.5 and temperature on the incidence of AMI. RESULTS: The models with PM2.5 lag structures of lag 0 and 2-day averages of lag 0 and 1 (lag 01) showed significant associations with AMI (Relative risk [RR]: 1.011, CI: 1.003-1.020 for lag 0, RR: 1.010, CI: 1.000-1.020 for lag 01) after adjusting the covariates. Stratification analysis conducted in the cold season (October-April) and the warm season (May-September) showed a significant lag 0 effect for AMI cases in the cold season only. CONCLUSIONS: In conclusion, acute exposure to PM2.5 was significantly associated with AMI morbidity at lag 0 in Seoul, Korea. This increased risk was also observed at low temperatures.
Rotavirus A is the most common cause of infectious diarrhea worldwide. This study aimed to retrospectively study and analyze 4009 stool samples that were tested for viruses causing diarrhea, using multiplex reverse transcription PCR at Dankook University Hospital between 2010 and 2019. Furthermore, we determined the correlation between these factors and various climatic factors, including wind-chill temperature, relative humidity, rate of sunshine, and particulate matter. Rotavirus A infections occurred frequently in February, March, and April on an annual basis. Furthermore, during the study, the detection rate was highest at 17.0% (n=61/359) in 2011. Based on an analysis of weather big data, patient age, and period-specific infection during the summer, when the wind-chill temperature and relative humidity were high, the Rotavirus A infection rate was very low. Relative humidity (p=0.020) and particulate matter (p=0.049) were associated with the average number of monthly cases of Rotavirus A infection. However, wind chill temperature (p=0.074) and rate of sunshine (p=0.993) were not associated with the average monthly distribution of Rotavirus A cases. These results indicate that Rotavirus A infection was correlated with relative humidity and particulate matter during the study period and further the current understanding of the distribution of Rotavirus A infections resulting from climatic factors and particulate matter. This could help establish climate-related health policies to reduce the incidence of diarrhea and guide the development of vaccines against Rotavirus A.
Studying relationships between meteorological conditions and respiratory virus infections may help interpret the causality of disease outbreaks and provide a better understanding of the seasonal distribution of viruses. Therefore, in this study, we analyzed the correlations between meteorological data and the trends of infection by human parainfluenza virus-1 (HPIV-1; also known as human respirovirus 1), human parainfluenza virus-2 (human orthorubulavirus 2), and human parainfluenza virus-3 (human respirovirus 3) using 9010 viral samples collected at Dankook University Hospital from January 1, 2012, to December 31, 2018. Infection frequency data were used to detect the seasonal patterns of HPIV-1, HPIV-2, and HPIV-3 infections, and these patterns were compared with local weather data over the same period. We performed descriptive statistical analysis, frequency analysis, t test, and binomial logistic regression analysis to examine the relationships of weather and particulate matter conditions with the incidence of HPIV-1, HPIV-2, and HPIV-3 infections. The highest average infection rate with one of these three viruses (88.17%) was found in children aged 1-9 years. Specifically, the infection rate of HPIV-1 was 91.9% in children aged 1-9 years, whereas that of HPIV-2 and HPIV-3 was 86.3%. HPIV infection exhibited a meaningful relationship with climatic factors, such as temperature, wind-chill temperature, and atmospheric pressure. Our results suggest that climate changes might affect the rate of infection by HPIV. These findings may help in predicting the effectiveness of preventive strategies of HPIV infection.
Constant environmental degradation and increased frequency and severity of natural disasters have been evident over the past few decades worldwide. As such, scientific tools to predict and assess risks keep being developed. Assessing disaster risk is an important task in supporting the transition to a sustainable society. However, as disasters and systems become more complex, disaster models combining diverse aspects including climatic, social, economic, and environmental factors are necessary. For this study, we set a model using the concept of risk by identifying hazards, exposure, and vulnerability. Here, the vulnerability was classified into two domains, sensitivity and adaptive capacity, and two spheres, natural/built environment and human environment. Also, we stressed that controllable geo-spatial indicators should be included in risk assessments to effectively reduce risk and implement adequate spatio-temporal actions. The approach of this study was applied to Kazakhstan and South Korea as a pilot study to develop Agricultural Drought Risk Index (ADRI) and maps. As a result, the agricultural drought risk could be analyzed for South Korea and Kazakhstan. In addition, we performed additional spatial analyses at a reasonable scale for practical use. It was concluded that prioritizing risk areas at administrative and site level could contribute in decision and policy-making for risk reduction. Furthermore, spatial data availability and quality were found to be significant in assessing disaster risk.
BACKGROUND: We assessed the association between multiple meteorological factors and air pollutants and the number of acute myocardial infarction (AMI) cases using a multi-step process. METHODS: Daily AMI hospitalizations matched with 16 meteorological factors and air pollutants in 7 metropolitan provinces of the Republic of Korea from 2002 to 2017 were analyzed. We chose the best fit model after conducting the Granger causality (GC) test and examined the daily lag time effect on the orthogonalized impulse response functions. To define dose-response relationships, we performed a time series analysis using multiple generalized additive lag models based on seasons. RESULTS: A total of 196,762 cases of AMI in patients older than 20 years admitted for hospitalization were identified. The distribution of meteorological factors and air pollutants showed characteristics of a temperate climate. The GC test revealed a complex interaction between meteorological factors, including air pollutants, and AMI. The final selected factors were NO(2) and temperature; these increased the incidence of AMI on lag day 4 during summer (NO(2): population-attributable fraction [PAF], 3.9%; 95% confidence interval [CI], 3.6-4.0; mean temperature: PAF, 3.3%; 95% CI, 2.7-3.9). CONCLUSIONS: This multi-step time series analysis found that average temperature and NO(2) are the most important factors impacting AMI hospitalizations, specifically during summer. Based on the model, we were able to visualize the effect-time association of meteorological factors and air pollutants and AMI.
Owing to global climate change, the global resurgence of vector-borne infectious diseases and their potential to inflict widespread casualties among human populations has emerged as a pivotal burden on public health systems. Tsutsugamushi disease (scrub typhus) in the Republic of Korea is steadily increasing and was designated as a legal communicable disease in 1994. The disease is a mite-borne acute febrile disease most commonly contracted from October to December. In this study, we tried to determine the prevalence of tsutsugamushi disease transmitted by chigger mites living on rodents and investigated their target vector diversity, abundance, and distribution to enable the mapping of hotspots for this disease in 2015. A total of 5 species belonging to 4 genera (109 mites): Leptotrombidium scutellare 60.6%, L. pallidum 28.4% Neotrombicula tamiyai 9.2%, Euschoengastia koreaensis/0.9%), and Neoschoengastia asakawa 0.9% were collected using chigger mite collecting traps mimicking human skin odor and sticky chigger traps from April to November 2015. Chigger mites causing tsutsugamushi disease in wild rodents were also collected in Hwaseong for the zoonotic surveillance of the vector. A total of 77 rodents belonging to 3 genera: Apodemus agrarius (93.5%), Crocidura lasiura (5.2%), and Micromys minutus (1.3%) were collected in April, October, and November 2015. The most common mite was L. pallidum (46.9%), followed by L. scutellare (18.6%), and L. orientale (18.0%). However, any of the chigger mite pools collected from rodent hosts was tested positive for Orientia tsutsugamushi, the pathogen of tsutsugamushi disease, in this survey.
Although several studies have reported that social isolation is one of the important health risk factors in the elderly population living in urban areas, its effects on vulnerability to heatwaves have been studied relatively less than climatic and other socio-economic factors. Thus, we investigated the association between social isolation levels and heatwave-related mortality risk in the elderly population in 119 urban administrative districts in Korea, using a time-series multi-city dataset (2008-2017). We used a two-stage analysis. In the first stage, we estimated the heatwave-related mortality risk in the elderly population (age ? 65) for each district using a time-series regression with a distributed lag model. Subsequently, in the second stage, we applied meta-regressions to pool the estimates across all the districts and estimate the association between social isolation variables and heatwave-related mortality risk. Our findings showed that higher social gathering and mutual aid levels were associated with lower heatwave-related mortality risk. Further, the lower percentage of single elderly households living in detached houses was also related to higher heatwave-related mortality risk. The associations were generally more evident in males compared to females. Our findings suggest that vulnerability to heatwave-related mortality among the urban, city-dwelling, elderly population may be amplified by higher isolation indicators.
BACKGROUND: We purposed to evaluate the seasonality and associated factors of the incidence of gout attacks in Korea. METHODS: We prospectively enrolled patients with gout attacks who were treated at nine rheumatology clinics between January 2015 and July 2018 and followed them for 1-year. Demographic data, clinical and laboratory features, and meteorological data including seasonality were collected. RESULTS: Two hundred-five patients (men, 94.1%) were enrolled. The proportion of patients with initial gout attacks was 46.8% (n = 96). The median age, body mass index, attack duration, and serum uric acid level at enrollment were 50.0 years, 25.4, 5.0 days, and 7.4 mg/dL, respectively. Gout attacks were most common during spring (43.4%, P < 0.001) and in March (23.4%, P < 0.001). A similar pattern of seasonality was observed in the group with initial gout attacks. Alcohol was the most common provoking factor (39.0%), particularly during summer (50.0%). The median diurnal temperature change on the day of the attack was highest in the spring (9.8°C), followed by winter (9.3°C), fall (8.6°C), and summer (7.1°C) (P = 0.027). The median change in humidity between the 2 consecutive days (the day before and the day of the attack) was significantly different among the seasons (3.0%, spring; 0.3%, summer; -0.9%, fall; -1.2%, winter; P = 0.015). One hundred twenty-five (61%) patients completed 1-year follow-up (51% in the initial attack group). During the follow-up period, 64 gout flares developed (21 in the initial attack group). No significant seasonal variation in the follow-up flares was found. CONCLUSION: In this prospective study, the most common season and month of gout attacks in Korea are spring and March, respectively. Alcohol is the most common provoking factor, particularly during summer. Diurnal temperature changes on the day of the attack and humidity changes from the day before the attack to the day of the attack are associated with gout attack in our cohort.
Here, we develop a dry eye syndrome (DES) incidence rate prediction model using air pollutants (PM10, NO2, SO2, O-3, and CO), meteorological factors (temperature, humidity, and wind speed), population rate, and clinical data for South Korea. The prediction model is well fitted to the incidence rate (R-2= 0.9443 and 0.9388,p< 2.2 x 10(-16)). To analyze regional deviations, we classify outpatient data, air pollutant, and meteorological factors in 16 administrative districts (seven metropolitan areas and nine states). Our results confirm NO(2)and relative humidity are the factors impacting regional deviations in the prediction model.
Severe fever with thrombocytopenia syndrome (SFTS), a tick-borne infectious disease, is difficult to differentiate from other common febrile diseases. Clinically distinctive features and climate variates associated with tick growth can be useful predictors for SFTS. This retrospective study (2013-2019) demonstrated the role of climatic factors as predictors of SFTS and developed a clinical scoring system for SFTS using climate variables and clinical characteristics. The presence of the SFTS virus was confirmed using reverse transcription polymerase chain reaction (RT-PCR) tests. In the univariate analysis, the SFTS-positive group was significantly associated with higher mean ambient temperature and humidity compared with the SFTS-negative group (22.5 °C vs. 18.9 °C; 77.9% vs. 70.7%, all p < 0.001). In the multivariate analysis, poor oral intake (Odds ratio [OR] 5.87, 95% CI: 2.42-8.25), lymphadenopathy (OR 7.20, 95% CI: 6.24-11.76), mean ambient temperature ? 20 °C (OR 4.62, 95% CI: 1.46-10.28), absolute neutrophil count ? 2000 cells/?L (OR 8.95, 95% CI: 2.30-21.25), C-reactive protein level ? 1.2 mg/dL (OR 6.42, 95% CI: 4.02-24.21), and creatinine kinase level ? 200 IU/L (OR 5.94, 95% CI: 1.42-24.92) were significantly associated with the SFTS-positive group. This study presents the risk factors, including ambient temperature and clinical characteristics, that physicians should consider when suspecting SFTS.
The flaviviruses are small single-stranded RNA viruses that are typically transmitted by mosquitoes or tick vectors and are etiological agents of acute zoonotic infections. The viruses are found around the world and account for significant cases of human diseases. We investigated population of culicine mosquitoes in central region of Korean Peninsula, Incheon Metropolitan City and Hwaseong-si. Aedes vexans nipponii was the most frequently collected mosquitoes (56.5%), followed by Ochlerotatus dorsalis (23.6%), Anopheles spp. (10.9%), and Culex pipiens complex (5.9%). In rural regions of Hwaseong, Aedes vexans nipponii was the highest population (62.9%), followed by Ochlerotatus dorsalis (23.9%) and Anopheles spp. (12.0%). In another rural region of Incheon (habitat of migratory birds), Culex pipiens complex was the highest population (31.4%), followed by Ochlerotatus dorsalis (30.5%), and Aedes vexans vexans (27.5%). Culex pipiens complex was the predominant species in the urban region (84.7%). Culicine mosquitoes were identified at the species level, pooled up to 30 mosquitoes each, and tested for flaviviral RNA using the SYBR Green-based RT-PCR and confirmed by cDNA sequencing. Three of the assayed 2,683 pools (989 pools without Anopheles spp.) were positive for Culex flaviviruses, an insect-specific virus, from Culex pipiens pallens collected at the habitats for migratory birds in Incheon. The maximum likelihood estimation (the estimated number) for Culex pipiens pallens positive for Culex flavivirus was 25. Although viruses responsible for mosquito-borne diseases were not identified, we encourage intensified monitoring and long-term surveillance of both vector and viruses in the interest of global public health.
The risk levels of heat-related extreme events need to be estimated for prediction and real-time monitoring to mitigate their impacts on air quality, public health, the ecosystem, and critical infrastructure. Many countries have adopted meteorological variable base thresholds for assessing the risk level of heat-related extreme events. These thresholds provide an approximate risk level for a specific event but do not consider its intensity and duration in the risk assessment. The current study provides a statistical tool to assess the risk of heat-related extreme events while concurrently considering their intensities and durations based on the wet-bulb globe temperature (WBGT). To this end, the intensity-duration-frequency (IDF) relationship of the extreme WBGT in South Korea was derived. Regional frequency analysis was employed to understand the IDF relationship. Return levels of heat-related extreme events in South Korea were calculated and their characteristics were investigated based on the annual maximum WBGT observations. The results showed that the IDF relationship could provide the risks of heat-related extreme events while concurrently considering their intensities and durations. The extreme WBGT in South Korea was used to categorize two regions such as coastal and inland based on their statistical characteristics. The return levels of the annual maximum WBGT events were found to vary largely by location. The return levels corresponding to 32 °C with 3-h duration for stations in the coastal and inland regions ranged from 1- to 100-years and 3- to 1000-years, respectively. Mean values of return levels for heatwave events in Seoul, Incheon, Daejon, Gwangju, Daegu, and Busan were 2.8-, 8.4-, 15.3-, 2.8-, 1.6-, and 2.2-years, respectively. The return levels of heatwaves for the warmer cities are smaller than those for cooler cities. The return levels of the heatwave events in South Korea showed a significant increasing trend in several cities, supporting the notion that the impact of heatwave events on South Korea might become more severe in the future.
Climate change has led to increases in global temperatures, raising concerns regarding the threat of lethal heat waves and deterioration of the thermal environment. In the present study, we adopted two methods for spatial modelling of the thermal environment based on sensible heat and temperature. A vulnerability map reflecting daytime temperature was derived to plot thermal vulnerability based on sensible heat and climate change exposure factors. The correlation (0.73) between spatial distribution of sensible heat vulnerability and mortality rate was significantly greater than that (0.30) between the spatial distribution of temperature vulnerability and mortality rate. These findings indicate that deriving thermally vulnerable areas based on sensible heat are more objective than thermally vulnerable areas based on existing temperatures. Our findings support the notion that the distribution of sensible heat vulnerability at the community level is useful for evaluating the thermal environment in specific neighbourhoods. Thus, our results may aid in establishing spatial planning standards to improve environmental sustainability in a metropolitan community.
Climate change increases the frequency and intensity of heatwaves, causing significant human and material losses every year. Big data, whose volumes are rapidly increasing, are expected to be used for preemptive responses. However, human cognitive abilities are limited, which can lead to ineffective decision making during disaster responses when artificial intelligence-based analysis models are not employed. Existing prediction models have limitations with regard to their validation, and most models focus only on heat-associated deaths. In this study, a random forest model was developed for the weekly prediction of heat-related damages on the basis of four years (2015-2018) of statistical, meteorological, and floating population data from South Korea. The model was evaluated through comparisons with other traditional regression models in terms of mean absolute error, root mean squared error, root mean squared logarithmic error, and coefficient of determination (R-2). In a comparative analysis with observed values, the proposed model showed an R-2 value of 0.804. The results show that the proposed model outperforms existing models. They also show that the floating population variable collected from mobile global positioning systems contributes more to predictions than the aggregate population variable.
Studies on the pattern of heatwave mortality using nationwide data that include rural areas are limited. This study aimed to assess the risk of heatwave-related mortality and evaluate the health risk-based definition of heatwave. We collected data on daily temperature and mortality from 229 districts in South Korea in 2011-2017. District-specific heatwave-related mortality risks were calculated using a distributed lag model. The estimates were pooled in the total areas and for each urban and rural area using meta-regression. In the total areas, the threshold point of heatwave mortality risk was estimated at the 93rd percentile of temperature, and it was lower in urban areas than in rural areas (92nd percentile vs. 95th percentile). The maximum risk of heatwave-related mortality in the total area was 1.11 (95% CI: 1.01-1.22), and it was slightly greater in rural areas than in the urban areas (RR: 1.23, 95% CI: 0.99-1.53 vs. RR: 1.10, 95% CI: 1.01-1.20). The results differ by age- and cause-specific deaths. In conclusion, the patterns of heatwave-related mortality risk vary by area and sub-population in Korea. Thus, more target-specific heatwave definitions and action plans should be established according to different areas and populations.
