A Machine Learning-Based Study of the Effects of Air Pollution and Weather in Respiratory Disease Patients Visiting Emergency Departments

Background. To date, investigating respiratory disease patients visiting the emergency departments related with fined dust is limited. This study aimed to analyze the effects of two variable-weather and air pollution on respiratory disease patients who visited emergency departments. Methods. This study utilized the National Emergency Department Information System (NEDIS) database. The meteorological data were obtained from the National Climate Data Service. Each weather factor reflected the accumulated data of 4 days: a patient’s visit day and 3 days before the visit day. We utilized the RandomForestRegressor of scikit-learn for data analysis. Result. The study included 525,579 participants. This study found that multiple variables of weather and air pollution influenced the respiratory diseases of patients who visited emergency departments. Most of the respiratory disease patients had acute upper respiratory infections [J00–J06], influenza [J09–J11], and pneumonia [J12–J18], on which PM10 following temperature and steam pressure was the most influential. As the top three leading causes of admission to the emergency department, pneumonia [J12–J18], acute upper respiratory infections [J00–J06], and chronic lower respiratory diseases [J40–J47] were highly influenced by PM10. Conclusion. Most of the respiratory patients visiting EDs were diagnosed with acute upper respiratory infections, influenza, and pneumonia. Following temperature, steam pressure and PM10 had influential relations with these diseases. It is expected that the number of respiratory disease patients visiting the emergency departments will increase by day 3 when the steam pressure and temperature values are low, and the variables of air pollution are high. The number of respiratory disease patients visiting the emergency departments will increase by day 3 when the steam pressure and temperature values are low, and the variables of air pollution are high.

[An Exploratory Study on the Policy for Facilitating of Health Behaviors Related to Particulate Matter: Using Topic and Semantic Network Analysis of Media Text]

PURPOSE

This study aimed to analyze the mass and social media contents and structures related to particulate matter before and after the policy enforcement of the comprehensive countermeasures for particulate matter, derive nursing implications, and provide a basis for designing health policies.

METHODS

After crawling online news articles and posts on social networking sites before and after policy enforcement with particulate matter as keywords, we conducted topic and semantic network analysis using TEXTOM, R, and UCINET 6.

RESULTS

In topic analysis, behavior tips was the common main topic in both media before and after the policy enforcement. After the policy enforcement, influence on health disappeared from the main topics due to increased reports about reduction measures and government in mass media, whereas influence on health appeared as the main topic in social media. However semantic network analysis confirmed that social media had much number of nodes and links and lower centrality than mass media, leaving substantial information that was not organically connected and unstructured.

CONCLUSION

Understanding of particulate matter policy and implications influence health, as well as gaps in the needs and use of health information, should be integrated with leadership and supports in the nurses' care of vulnerable patients and public health promotion.

Effects of Particulate Respirator Use on Cardiopulmonary Function in Elderly Women: a Quasi-Experimental Study

BACKGROUND

Individual particulate respirator use may offer protection against exposure to particulate matter < 2.5 μm in diameter (PM2.5). Among elderly Korean women, we explored individual particulate respirator use and cardiopulmonary function.

METHODS

Recruited in Seoul, Korea, 21 elderly, non-smoking women wore particulate respirators for six consecutive days (exlcuding time spent eating, sleeping, and bathing). We measured resting blood pressure before, during, and after respirator use and recorded systolic and diastolic blood pressure, mean arterial blood pressure, pulse pressure, and lung function. We also measured 12-hour ambulatory blood pressure at the end of the 6-day long experiment and control periods. Additionally, we examined physiological stress (heart rate variability and urinary 8-hydroxy-2'-deoxyguanosine) while wearing the particulate respirators. Person- and exposure-level covariates were also considered in the model.

RESULTS

After the 6-day period of respirator use, resting blood pressure was reduced by 5.3 mmHg for systolic blood pressure (P = 0.013), 2.9 mmHg for mean arterial blood pressure (P = 0.079), and 3.6 mmHg for pulse pressure (P = 0.024). However, particulate respirator use was associated with changes in physiological stress markers. A parasympathetic activity marker (high frequency) significantly decreased by 24.0% (P = 0.029), whereas a sympathetic activity marker (ratio of low-to-high frequency) increased by 50.3% (P = 0.045). An oxidative stress marker, 8-hydroxy-2'-deoxyguanosine, increased by 3.4 ng/mg creatinine (P = 0.021) during the experimental period compared with that during the control period. Lung function indices indicated that wearing particulate respirators was protective; however, statistical significance was not confirmed.

CONCLUSION

Individual particulate respirator use may prevent PM2.5-induced blood-pressure elevation among elderly Korean women. However, the effects of particulate respirator use, including physiological stress marker elevation, should also be considered.

TRIAL REGISTRATION

Clinical Research Information Service Identifier: KCT0003526.

Reactive oxygen species (ROS) activity of ambient fine particles (PM2.5) measured in Seoul, Korea

Substantial increase in level of particulate matter has raised concerns in South Korea recently. Ambient particulate matter is classified as Group I carcinogen (IARC, 2013) and multiple epidemiological studies has demonstrated adverse health effects due to exposure of particulate matter. Fine particulate matter (PM_2.5) which has a diameter <2.5 μm is likely to penetrate deeply into lung and is known to be eliciting adverse health effects. A number of epidemiological studies have been conducted on adverse health effects of PM-related diseases and mortality rate, yet particulate matter (PM)-induced reactive oxygen species (ROS) activity at the cellular level has not been actively studied in Korea. This study assessed PM-induced oxidative potential by exposure of collected ambient PM_2.5 samples to the rat alveolar macrophage cell line. The characteristics of PM_2.5 in Korea were further characterized by linking chemical constituents and contributing sources to ROS. PM_2.5 mass concentration during the cold season was relatively higher than mass concentration during the warm season and chemical constituents except for Secondary Organic Carbon (SOC) and SO₄^2- which both showed similar trends in both the cold and cold seasons. The concentration of crustal elements was especially high during the cold season which can be an indication of long range transport of Asian dust. Water soluble organic carbon and water soluble transition metals (Cr and Zn) were also shown to be correlated to oxidative potential and metals such as As and V were shown to have a high contribution to ROS activity according to stepwise multiple linear regression. Principal Component Analysis (PCA) results identified six factors that can be interpreted as soil, mobile, industry, secondary inorganic aerosol, secondary organic aerosol and oil combustion. Moreover, through Principal Component Regression (PCR), industry, soil, mobile and SIA were shown to be statistically significant sources in a relation to ROS activity.