Predicting the daily number of patients for allergic diseases using PM10 concentration based on spatiotemporal graph convolutional networks

Air pollution causes and exacerbates allergic diseases including asthma, allergic rhinitis, and atopic dermatitis. Precise prediction of the number of patients afflicted with these diseases and analysis of the environmental conditions that contribute to disease outbreaks play crucial roles in the effective management of hospital services. Therefore, this study aims to predict the daily number of patients with these allergic diseases and determine the impact of particulate matter (PM10) on each disease. To analyze the spatiotemporal correlations between allergic diseases (asthma, atopic dermatitis, and allergic rhinitis) and PM10 concentrations, we propose a multi-variable spatiotemporal graph convolutional network (MST-GCN)-based disease prediction model. Data on the number of patients were collected from the National Health Insurance Service from January 2013 to December 2017, and the PM10 data were collected from Airkorea during the same period. As a result, the proposed disease prediction model showed higher performance (R2 0.87) than the other deep-learning baseline methods. The synergic effect of spatial and temporal analyses improved the prediction performance of the number of patients. The prediction accuracies for allergic rhinitis, asthma, and atopic dermatitis achieved R2 scores of 0.96, 0.92, and 0.86, respectively. In the ablation study of environmental factors, PM10 improved the prediction accuracy by 10.13%, based on the R2 score.

A study on specific factors related to inflammation and autophagy in BEAS-2B cells induced by urban particulate matter (PM, 1648a) and histological evaluation of PM-induced bronchial asthma model in mice

As particulate matter (PM) poses an increasing risk, research on its correlation with diseases is active. However, researchers often use their own PM, making it difficult to determine its components. To address this, we investigated the effects of PM with known constituents on BEAS-2B cells, examining cytokine levels, reactive oxygen species ROS production, DNA damage, and MAPK phosphorylation. Additionally, we evaluated the effects of PM on normal and OVA-induced asthmatic mice by measuring organ weight, cytokine levels, and inflammatory cells in bronchoalveolar lavage fluid, and examining histological changes. PM markedly increased levels of IL-6, GM-CSF, TNF-α, ROS, nitric oxide, and DNA damage, while surprisingly reducing IL-8 and MCP-1. Moreover, PM increased MAPK phosphorylation and inhibited mTOR and AKT phosphorylation. In vivo, lung and spleen weights, IgE, OVA-specific IgE, IL-4, IL-13, total cells, macrophages, lymphocytes, mucus generation, and LC3II were higher in the asthma group. PM treatment in asthmatic mice increased lung weight and macrophage infiltration, but decreased IL-4 and IL-13 in BALF. Meanwhile, PM treatment in the Nor group increased total cells, macrophages, lymphocytes, and mucus generation. Our study suggests that PM may induce and exacerbate lung disease by causing immune imbalance via the MAPK and autophagy pathways, resulting in decreased lung function due to increased smooth muscle thickness and mucus generation.

Association between exposure to traffic-related air pollution and pediatric allergic diseases based on modeled air pollution concentrations and traffic measures in Seoul, Korea: a comparative analysis

BACKGROUND

Pediatric allergic diseases are a major public health concern, and previous studies have suggested that exposure to traffic-related air pollution (TRAP) exposure is a risk factor. These studies have typically assessed TRAP exposure using traffic measures, such as distance to major roads, or by modeling air pollutant concentrations; however inconsistent associations with pediatric allergic diseases have often been found. Using road proximity and density, we previously found an association between TRAP and atopic eczema among approximately 15,000 children living in Seoul, Korea, heavily populated and highly polluted city in which traffic is a major emission source. We aimed to conduct a parallel analysis using modeled air pollution concentrations and thus examine the consistency of the association. Specifically, we examined the associations of individual-level annual-average concentrations of NO₂, PM₁₀, and PM_2.5 with symptoms and diagnoses of three pediatric allergic diseases including asthma, allergic rhinitis, and atopic eczema.

METHODS

The study population included 14,614 children from the Seoul Atopy Friendly School Project Survey in Seoul, Korea, in 2010. To assess individual exposures to TRAP among these children, we predicted annual-average concentrations of NO₂, PM₁₀, and PM_2.5 at the children's home addresses in 2010 using universal kriging and land use regression models along with regulatory air quality monitoring data and geographic characteristics. Then, we estimated odds ratios (ORs) of the three allergic diseases for interquartile increases in air pollution concentrations after adjusting for individual risk factors in mixed effects logistic regression.

RESULTS

Symptoms and diagnoses of atopic eczema symptoms showed an association with NO₂ (OR = 1.07, 95% confidence interval = 1.02-1.13; 1.08, 1.03-1.14) and PM₁₀ (1.06, 1.01-1.12; 1.07, 1.01-1.13). ORs of PM_2.5 were positive but not statistically significant (1.01, 0.95-1.07; 1.04, 0.98-1.10). No association was found between asthma and allergic rhinitis, although PM_2.5 showed a marginal association with allergic rhinitis.

CONCLUSIONS

Our consistent findings regarding the association between TRAP and the prevalence of atopic eczema using traffic measures and surrogate air pollutants suggested the effect of TRAP on children's health. Follow-up studies should elucidate the causal link, to support subsequent policy considerations and minimize adverse health effects in children.

Trends in the Prevalence of Childhood Asthma in Seoul Metropolitan City, Korea: The Seoul Atopy ∙ Asthma-friendly School Project

Objectives

The project Seoul Atopy ∙ Asthma-friendly School investigated the current status of childhood asthma to enable formulation of a preventative policy. We evaluated the current prevalence of childhood asthma in Seoul and its trends and related factors.

Methods

The project was conducted annually from 2011 to 2016 and involved around 35 000 children aged 1-13 years. Based on the International Study of Asthma and Allergies in Childhood guidelines, the survey involved parents. The associations of the particulate matter (PM₁₀) concentration, and the number of days on which the daily air quality guidance level was exceeded in the 25 districts of Seoul, with the prevalence of asthma were assessed.

Results

The age-standardized asthma prevalence in 2011 and 2016 was 6.74 and 4.02%, respectively. The prevalence of lifetime asthma treatment and treatment during the last 12 months tended to decrease from 2011 to 2016. Asthma treatment was significantly correlated with the number of days on which the daily air quality guidance level was exceeded, but not with the PM₁₀ concentration.

Conclusions

This study reports the prevalence of asthma among children in Seoul and confirmed the relationship between childhood asthma and known risk factors in a large-scale survey.