Air pollution exposure and the burden of paediatric upper respiratory tract infections in Emergency Departments

Air pollution exposure and the burden of paediatric upper respiratory tract infections in Emergency Departments | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Air pollution exposure and the burden of paediatric upper respiratory tract infections in Emergency Departments Ewelina Wawryk-Gawda, Nadia Miga-Orczykowska, Joanna Matusiak, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7280297/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Nov, 2025 Read the published version in European Journal of Pediatrics → Version 1 posted 11 You are reading this latest preprint version Abstract Upper respiratory tract infections (URTI) are a major public health problem and a leading cause of pediatric Emergency Department (ED) visits. Approximately 81% of emergency outpatient visits in children are due to URTI, and respiratory diseases account for 12% of all deaths worldwide. Air pollution is considered an important factor contributing to the increased incidence of respiratory infections. The aim of this study was to examine the association between ambient air pollutant concentrations and the number of pediatric ED admissions for URTI. Methods . We conducted a retrospective analysis including 2,572 children admitted to the ED between 2015 and 2020 with a diagnosis of URTI. Daily concentrations of particulate matter (PM2.5 and PM10), carbon monoxide (CO), nitrogen oxides (NOx and NO2), ozone (O3), and sulfur dioxide (SO2) were obtained from a certified environmental monitoring station. Results . The highest number of URTI-related visits was observed in winter 2019, coinciding with the peak levels of air pollutants. In univariate analyses, higher concentrations of PM2.5, PM10, CO, and SO2 were significantly associated with increased ED admissions. After adjusting for seasonality in multivariable models, only CO and SO2 remained independent predictors of higher URTI incidence. Conclusion . Our findings indicate that air pollution is strongly associated with the frequency of pediatric URTI-related ED visits. While seasonality plays an important role, CO and SO2 appear to be key independent factors driving this association. air pollution Emergency Department upper respiratory tract infections pediatrics children hospitalization Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Upper respiratory tract infections (URTI) are among the most common reasons for Emergency Department (ED) visits in children and have become a significant public health concern. These infections, predominantly of viral origin, are influenced by multiple factors, including age, staying in large groups, anatomical and immunological predisposition and exposure to both household and outdoor air pollution (Wawryk-Gawda et al. 2021 ; Silva et al. 2013 ). Air pollutants comprise a complex mixture of chemical and biological substances released into the atmosphere, forming dynamic blends of gases and particulate matter. Their sources and composition vary considerably across regions and over time (Silva et al. 2013 ; Dondi et al. 2023 ; Choo et al. 2023 ; Li et al. 2018 ). Exposure to particulate matter with diameters of 2.5 µm and 10 µm (PM2.5, PM10), carbon monoxide (CO), nitrogen oxides (NOx, NO2), ozone (O3), and sulfur dioxide (SO2) is known to pose significant health risks. The World Health Organization’s Global Air Quality Guidelines provide reference thresholds and recommended limits for these substances (WHO 2021 ; Wiesner et al. 2021 ; WHO 2022 ). Children are particularly vulnerable to the effects of air pollution. They spend more time outdoors engaged in physical activities, which increases their exposure to higher doses of pollutants. Due to their shorter stature, children inhale air closer to the ground, where concentrations of many toxicants are greater. Physiological characteristics such as higher rates of mouth breathing, higher minute ventilation relative to body size, and less effective filtration in the nasal passages further facilitate pollutant penetration into the respiratory tract. In addition, children’s smaller airways, underdeveloped mucociliary clearance, and immature immune and detoxification systems amplify the potential for harm and can interfere with normal respiratory development (Wawryk-Gawda et al. 2021 ; Li et al. 2018 ; Goldizen et al. 2016 ; Rodríguez-Fernández et al. 2019 ). Although the relationship between air pollution and respiratory infections has been extensively studied in some regions, data specific to European pediatric populations remain limited (Ziou et al. 2022 ; HEI 2010 ; Bielska et al. 2015). While parents and healthcare professionals often focus on medications, vaccinations, nutrition, and supplementation to prevent infections, less attention is given to environmental exposures. In some households, children continue to be exposed to passive smoking, further compounding respiratory risks (Bielska et al. 2015; Peden 2024 ). The present study aimed to investigate the association between ambient air pollutant levels and the number of paediatric ED admissions due to upper respiratory tract infections. We hypothesized that higher concentrations of PM2.5, PM10, CO, NOx, NO2, O3, and SO2 would be significantly associated with an increased frequency of ED visits for URTI, independently of seasonal variation. Methods This retrospective observational study focused on key ambient air pollutants, including particulate matter (PM2.5 and PM10), carbon monoxide (CO), nitrogen oxides (NOx and NO2), ozone (O3), and sulphur dioxide (SO2). Data on paediatric Emergency Department (ED) admissions were extracted from the electronic medical records of the University Children’s Hospital in Lublin. Records included the date of admission, diagnosis codes according to the International Classification of Diseases (ICD-10), and basic demographic information. The dataset comprised 2,572 patients aged 0–18 years who were admitted to the ED between January 2015 and December 2020 with a diagnosis of the common cold (J00) or acute upper respiratory tract infection of multiple and unspecified sites (J06). Daily concentrations of the selected air pollutants were obtained from the Chief Inspectorate for Environmental Protection’s certified ambient air monitoring station located on Obywatelska Street in Lublin (station code: PL507A). Although data were collected from a single monitoring site, this location was considered representative of urban background exposure for the city’s population. Lublin is the eighth largest city in Poland, with approximately 330,400 inhabitants. The region is characterized by a temperate climate, with average annual temperatures ranging between + 7.0°C and + 8.0°C. The warmest months are July and August (mean + 19°C), while the coldest are January and February (mean − 5.0°C). The province combines agricultural and industrial activities, with the food industry and vehicle manufacturing among the main sectors of the local economy. For statistical analysis, we used Stata BE 18 software (StataCorp LLC, Texas, USA). Univariate linear regression models were applied to assess the association between the daily concentrations of individual pollutants or season and the number of daily ED admissions for URTI. Subsequently, multiple regression analyses were performed to evaluate the combined effects of pollutants and seasonality, adjusting for potential confounding. A p-value ≤ 0.05 was considered statistically significant. To assess the relationship between air pollutant exposure and the frequency of upper respiratory tract infections (URTI), we performed a stratified visual analysis using exposure tertiles. For each of the six pollutants—PM2.5, PM10, carbon monoxide (CO), nitrogen dioxide (NO₂), ozone (O₃), and sulfur dioxide (SO₂)—daily values were divided into three equal-sized groups (tertiles) based on their distribution across the entire study period (2015–2020). The resulting categories represented low, medium, and high exposure levels for each pollutant. We then constructed boxplots showing the distribution of daily URTI-related Emergency Department (ED) visits across these tertile groups. This approach allowed for a comparative visualization of the variability and central tendency of case numbers under different levels of pollutant exposure. Days with missing pollutant or URTI data were excluded from the respective analysis. The plots were generated using the seaborn.catplot function in Python (version 3.12.6), with boxplot parameters displaying median, interquartile ranges (IQR), and potential outliers. Institutional approval for the use of anonymized patient data was obtained from the hospital director. According to national regulations, separate bioethics committee approval was not required for this retrospective analysis of routinely collected administrative data (decision of Bioethics Committee at the Medical University of Lublin No BKB/10/01/2025). Results The analysis included data from 2,572 children (mean age: 39 ± 48.9 months), with boys representing 57% of the study population (Table 1). Undifferentiated upper respiratory tract infections (URTI, ICD code J06) were diagnosed more frequently than the common cold (J00), accounting for 64% and 36% of all visits, respectively (Table 2). Table 1. Demographics of the study population. Group ( n = 2,572) Male/female 1,463(57%)/1,109(43%) Age (months) Mean ± standard deviation 39 ± 48.87 Minimum–maximum (median) 0.19–236 (18) Table 2. The diagnosis according to ICD classification: the common cold (J00) and undifferentiated upper respiratory tract infections (J06) in the study population. J00 J06 Female (n=1109) 412 (37% of girls) 697(63% of girls) Male (n=1463) 513(35%of boys) 950(65%of boys) Total 925(36%) 1647(64%) 35.96% 64.04% Annual trends in URTI-related ED visits The total number of pediatric Emergency Department (ED) visits due to URTI showed a consistent increase from 2015 to 2019, reaching a peak of 567 cases in 2019 (Figure 1). A decline was observed in 2020 (457 cases), likely attributable to public health restrictions during the COVID-19 pandemic. Seasonal variation in URTI incidence Respiratory infections were diagnosed more frequently during winter in each study year Fig. 1S). A statistically significant positive correlation was observed between season and daily number of URTI cases (Spearman’s rho = 0.23, p < 0.001) (Figure 2). Recurrent seasonal peaks were evident, aligning with winter months throughout the study period. Associations between pollutants and URTI incidence Across the study period (2015–2020), the mean concentrations of particulate matter exceeded World Health Organization (WHO) recommended limits, with average PM2.5 of 23.3 µg/m³ and PM10 of 30.4 µg/m³. Seasonal variation was observed, with higher concentrations of PM2.5, PM10, CO, and SO₂ during winter months, while ozone (O₃) levels peaked in summer. The magnitude of pollution varied between years, with peak winter PM2.5 levels reaching 40 µg/m³ in 2017, compared to 26.6 µg/m³ in 2020 (Figure 3). Non-parametric Kruskal-Wallis tests confirmed statistically significant differences in seasonal pollutant concentrations for all analyzed substances: PM2.5 (p < 1×10⁻¹¹³), PM10 (p < 1×10⁻⁵⁸), CO (p < 1×10⁻⁸⁷), NO₂ (p < 1×10⁻¹⁹), O₃ (p < 1×10⁻²³⁶), and SO₂ (p < 1×10⁻⁹⁸) (Supplementary Table 1S). Simple linear regression analyses revealed significant positive associations between daily concentrations of PM2.5, PM10, CO, O₃, and SO₂ and the number of pediatric URTI visits (Supplementary Table 2S). In multivariable regression models adjusting for seasonality, only CO and SO₂ remained independent predictors of URTI incidence (Table 3S). Spearman rank correlations confirmed weak positive associations for CO ( r = 0.13 ) and PM2.5 ( r = 0.10 ) with URTI visits, whereas O₃ showed a weak inverse correlation ( r = –0.12 ). Boxplots illustrating daily URTI visit counts across pollutant exposure tertiles are presented in Figure 4. Higher exposure levels of PM2.5, CO, and SO₂ were associated with increased median and variability of daily URTI cases. PM10 demonstrated a weaker positive trend, while O₃ exposure showed an inverse association with URTI incidence, likely reflecting its inverse seasonal pattern. NO₂ did not exhibit a clear trend. Monthly averaged data demonstrated clear seasonal patterns for both pollutant concentrations and pediatric URTI visits (Figure 5). Peaks in PM2.5, PM10, CO, and SO₂ levels coincided with winter months, during which ED visits for URTI were most frequent. In contrast, ozone (O₃) concentrations were higher during summer months, when respiratory infections were less prevalent. Nitrogen dioxide (NO₂) displayed more variable patterns, without a consistent monotonic association with URTI visits. Spearman’s rank correlation analysis confirmed statistically significant positive associations between daily concentrations of PM2.5 (ρ = 0.10, p < 0.001), CO (ρ = 0.13, p < 0.001), SO₂ (ρ = 0.11, p < 0.001), and PM10 (ρ = 0.08, p = 0.002) and the number of pediatric ED visits for URTI. O₃ showed a weak inverse correlation (ρ = −0.12, p < 0.001), while NO₂ did not reach statistical significance (ρ = 0.04, p = 0.072). Non-parametric Kruskal-Wallis tests indicated significant seasonal differences in pollutant levels for all six pollutants (all p < 0.001), with winter having the highest mean concentrations of PM2.5, PM10, CO, and SO₂. Univariate linear regression models identified PM2.5, PM10, CO, SO₂, and O₃ as significant predictors of daily URTI-related ED visits (all p < 0.05). However, in multivariable models adjusted for co-pollutant exposure and seasonality, only CO (β = 0.018, 95% CI: 0.010–0.026, p < 0.001) and SO₂ (β = 0.035, 95% CI: 0.020–0.051, p < 0.001) remained independent predictors of paediatric URTI incidence. Discussion This study demonstrated a significant association between exposure to ambient air pollutants and pediatric Emergency Department (ED) visits for upper respiratory tract infections (URTI). In single-pollutant regression models, we observed positive correlations for PM2.5, PM10, CO, and SO₂ with URTI incidence, whereas O₃ exhibited a weak inverse relationship. In multivariable models adjusting for seasonality and co-pollutant exposure, only CO and SO₂ remained independent predictors of pediatric ED visits. Both URTI incidence and air pollutant concentrations displayed clear seasonal variation, with pronounced peaks during winter months. Our results align with a study conducted in a Greek suburban region, where researchers observed that over the course of a year, PM 2.5 levels in both the central and surrounding areas of Volos frequently surpassed the WHO's recommended safety threshold, with the most significant air pollution occurring in the winter and spring seasons (Kanellopoulos et al. 2021 ). In these seasons a statistically significant increase in upper respiratory infections-related visits in ED was observed if PM2.5 levels were more than 25 µg/m3 (Kanellopoulos et al. 2021 ). The large-scale ESCAPE project demonstrated associations between exposure to NO₂, PM10, and increased respiratory infections in children (Gehring et al. 2010 ). Rodríguez-Fernández et al. ( 2019 ) described similar associations in Spain, and Ziou et al. ( 2022 ) confirmed via meta-analysis that particulate matter exposure increases URTI risk in children across Europe. Reports from the European Environment Agency ( 2023 ) and UNICEF ( 2023 ) emphasize that air pollution remains one of the leading environmental health risks for European children, contributing to higher rates of respiratory infections, asthma, and impaired lung growth. More data about the association between air pollution and respiratory diseases are available from China. These studies have suggested significant association also between NO 2 concentration and URTI-related visits in ED. The study by Liu et al., which focused on pediatric hospital outpatients aged 0–14 years in Hefei, China, found that in single-pollutant models, PM10, PM2.5, SO2, NO 2 , and CO were all significantly associated with an increase in URTI cases. However, when considering all pollutants together in a full model, only NO 2 maintained a significant positive relationship with the number of outpatient visits for URTI (Li et al. 2018 ). The study of Wang et al. carried out in Kunshan showed significant associations with hospital visits and expenditures due to upper respiratory tract infections (URTI) both in children and adult, and PM2.5, PM10, SO 2 , and NO 2 concentration in ambient air. Additionally, sensitivity analyses revealed that the associations with PM2.5, PM10, and NO 2 were stronger in individuals aged 18 years and younger. The strength of these associations also fluctuated depending on the season (Wang et al. 2024 ). Choo et al. showed that increased O 3, SO 2 , and PM2.5 concentrations were positively associated with URTI case counts and they found that air pollutants were more important than meteorological factors (such as air temperature, humidity) (Choo et al. 2023 ). Similarly, the study of Zhang et al. conducted in Wuhan showed strong and significant association between clinic visits for URTI of college students due to URTI and PM2.5 (0.74% (95%CI: 0.05, 1.44), PM10 (0.61% (95%CI: 0.12, 1.11), O 3 (1.01% (95%CI: 0.24, 1.79), SO 2 (9.18% (95%CI: 3.27,15.42) and NO 2 (3.40% (95% CI:1.64, 5.19). Moreover PM10, SO 2 and NO 2 were independent factors increasing frequency of URTI-related visits (Zhang et al. 2021 ). The high association of each pollutant with hospital emergency visits was observed by Liu et al. in Lanzhou with PM2.5 (5.302% (95% CI:3.202, 7.445)), PM10 (0.808% (95% CI: 0.291, 1.328)), SO 2 (10.607% (95% CI: 5.819, 15.611)), and NO 2 (5.325% (95% CI: 2.379, 8.357)). The associations appeared to be stronger in the cold seasons (autumn and winter) than in the warm seasons (spring and summer) (Liu et al. 2022 ) as in our study. In the same place Zhai and Zhang conducted a study which revealed that PM2.5 had the most significant effect on the number of outpatient visits for upper respiratory tract infections (Zhai and Zhang 2023 ). Indian research (Fatima et al. 2022 ; Abudureyimu et al. 2023 ; Adhikary et al. 2024 ; Gupta 2019 ; George et al. 2024 ; Malamardi et al. 2022 , Ghosh et al. 2025) confirmed substantial increases in pediatric respiratory infections with elevated PM2.5 exposure, particularly during smog episodes and biomass burning events. Specifically, every 10 µg/m³ rise in PM2.5 concentration was linked to a 23% increase in the odds of acute respiratory tract infection among children (OR 1.23, 95% CI: 1.19–1.27) (Adhikary et al. 2024 ). Seasonal agricultural practices, particularly the burning of rice crop residues, have been identified as major contributors to elevated PM2.5 levels, leading to measurable declines in lung function among school-aged children exposed to such events (Gupta 2019 ). A large-scale, state-level analysis indicated a significant association between vegetation cover (NDVI index) and the prevalence of asthma attributable to PM2.5 exposure in children and adolescents (β = 0.144; 95% CI: 0.10–0.186; p < 0.0001) (Malamardi et al. 2022 ). Furthermore, research focusing on children under five years of age revealed a non-linear yet monotonic relationship between ambient PM2.5 concentrations and the occurrence of respiratory illnesses in this population (George et al. 2024 ). Regional differences in pollutant composition, industrial activity, and meteorological factors may explain heterogeneity in reported effect sizes worldwide. Although the government has taken many measures to improve the local air quality, the level of air pollutants concentration (the average annual PM2.5, PM10, and NO 2 concentrations during 2014–2018 in Lanzhou were 51.33 µg/m3, 120.50 µg/m3, 46.90 µg/m3, respectively) exceeded the daily or annual limit (Liu et al. 2022 ; Liu et al. 2021 ). Shabani et al. (2022) demonstrated that environmental conditions significantly influence the harmful effects of air pollution on infections. Their research took place in Kosovo, a mountainous region with limited air circulation, particularly in winter. The elevated pollution levels were attributed to factors such as residential heating, traffic, industrial activities, and coal-fired power plants. The study found that daily average PM2.5 concentrations ranged from 2.41 to 161.03 µg/m³, and an increase in PM2.5 levels was associated with a rise in the number of visits over the several days (Shabani et al. 2022). The occurrence of disasters such as wildfires are also a cause of the short-term deterioration of air. Ademu et al. observed significant associations between PM2.5, CO, NO 2 , and Air Quality Index (AQI) and confirmed cases of COVID-19 across 20 counties in California impacted by wildfires (Ademu et al. 2022 ). The mechanism of pollution-related respiratory tract diseases is multifactorial. Higher concentrations of human bacterial and viral pathogens were found in the atmosphere during burning of biomass (Pompilio 2020 ). Bioaerosols also represented a reservoir of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs). More pathogenic bacteria were observed in the airway of people from cities with high pollutant concentration (Monoson et al. 2023 ). Pollutant exposure is responsible for compromising the immunological system required to protect individuals from infections. The air pollutants alter cellular responses to respiratory infection disrupting the normal innate barrier, the epithelial lining fluid and mucociliary clearance. The data conducted with animals and people showed that after air pollution exposure components of innate immune response were altered such as defenses macrophage phagocytosis, secretion of antimicrobial peptides (e.g. β-defensin-2), number and function of neutrophils, T-cells and dendritic cells which can compromise the response to bacterial and viral infections. The air pollutants (PM2.5, O 3 , and NO 2 ) induce oxidative stress and ROS that damage tight-junctions allowing intraepithelial translocation of bacterial pathogens towards blood, and enhances bacterial adhesion and biofilm formation onto epithelial cells, as well as cell invasion. In addition, SO 2 reduced production or release of TNF-α. PM adsorb a relevant number of components on their surface, mainly organic compounds, nitrates, sulphates, metals, and biological particles such as bacteria. After being inhaled, this composition settles onto the airway epithelium where it is wetted by the epithelial lining fluid. Redox-active materials, as well as bacteria, are then released from the PM surface into the fluid where they trigger cell damage (Ma et al. 2020 ; Peden 2024 , Pompilio and Di Bonaventura 2020 , Silva et al. 2013 ; Dondi et al. 2023 ; Peden 2024 ). These mechanisms, demonstrated in experimental and clinical studies, explain observed increases in respiratory infection susceptibility in polluted environments. The data concerns association between air pollution and respiratory tract diseases as well as mechanisms responsible for these relationship are important to make a rigorous decision about limitation of pollution. CO and SO₂ emerged as independent predictors, underscoring the role of combustion-related emissions from traffic, heating, and industrial sources. Seasonal peaks in pollution and URTI incidence highlight the need for targeted interventions during winter months. Strengthening air quality regulations, aligning standards with WHO guidelines (WHO 2021 ; WHO 2022 ), and raising parental awareness are essential to reduce pediatric respiratory disease burden in Europe and globally (HEI 2010 ; European Environment Agency 2023 ; UNICEF 2023 ). Limitations Our study has certain limitations that should be acknowledged. Our analysis implemented the mean values of the measured pollutants levels in one ambient air monitoring station in Lublin, thus not accurately reflecting the individual exposure. Furthermore, as the diagnoses were performed in an emergency setting, it is possible that some of them were inaccurate, leading to misclassification. The data include all the cases only from one hospital in Lublin. Conclusion This study provides robust evidence that exposure to ambient air pollutants, particularly CO and SO₂, is associated with an increased frequency of pediatric ED visits for URTI. Seasonal variation plays a significant role, with winter peaks in pollutants corresponding to higher infection rates. Our findings align with European and global literature, supporting calls for stronger air quality interventions to protect children's respiratory health. It is also important to raise awareness among parents about the harmful effects of pollutants on their children. Year-specific Spearman’s rank correlation analyses revealed that the strength of the association between pollutant levels and daily URTI visits varied over time. The correlations were most pronounced in 2017–2018, particularly for PM2.5 (ρ = 0.22 in 2017), PM10 (ρ = 0.20 in 2017), CO (ρ = 0.21 in 2017), and SO₂ (ρ = 0.24 in 2018). In 2019, the correlation coefficients weakened despite higher URTI visit counts. Ozone consistently showed a weak inverse relationship with URTI visits (ρ from − 0.08 to − 0.19 across years), whereas NO₂ did not demonstrate a statistically meaningful association in any year. Declarations Competing Interests The authors have no relevant financial or non-financial interests to disclose. Ethics approval This is an retrospective study of data, no ethical approval is required. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Author Contribution All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by EWG, NMO, JM, DM and KG. The first draft of the manuscript was written by EWG and VOW prepared final version of manuscript, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Acknowledgement Manuscript preparation was supported during Harvard Medical School’s Polish Clinical Scholars Research Training Program, organised by the Agencja Badan Medycznych (ABM, English: Medical Research Agency, Warsaw, Poland Data Availability The datasets generated during and/or analysed during the current study are not publicly but are available from the corresponding author on reasonable request. References Abudureyimu K, Suryadhi MAH, Yorifuji T, Tsuda T (2023) Exposure to fine particulate matter and acute upper- and lower-respiratory tract infections (AURI and ALRI) in children under five years of age in India. Arch Environ Occup Health 78:1–6. https://doi.org/10.1080/19338244.2022.2047584 Ademu LO, Gao J, Thompson OP, Ademu LA (2022) Impact of Short-Term Air Pollution on Respiratory Infections: A Time-Series Analysis of COVID-19 Cases in California during the 2020 Wildfire Season. Int J Environ Res Public Health 21(9):5057 Adhikary M, Mal P, Saikia N (2024) Exploring the link between particulate matter pollution and acute respiratory infection risk in children using generalized estimating equations analysis: a robust statistical approach. Environ Health 23(1):1–11. https://doi.org/0.1186/S12940-024-01049-3 Bielska DE, Gomółka E, Kurpas D, Chlabicz S (205). Narazenie dzieci w wieku przedszkolnym na dym tytoniowy–badanie porównawcze [Exposure to environmental tobacco smoke in pre-school children–a comparative study]. Przegl Lek 72(10):505-8. in Polish Choo ELW, Janhavi A, Koo JR, Yim SHL, Dickens BL, Lim JT (2023) Association between ambient air pollutants and upper respiratory tract infection and pneumonia disease burden in Thailand from 2000 to 2022: a high frequency ecological analysis. BMC Infect Dis 6(1):379 Dondi A, Carbone C, Manieri E et al (2023) Outdoor air pollution and childhood respiratory disease: the role of oxidative stress. Int J Mol Sci 24(5):4345. https://doi.org/10.3390/ijms24054345 European Environment Agency (2023) Air pollution and children's health. EEA, Copenhagen. https://www.eea.europa.eu/publications/air-pollution-and-childrens-health Fatima S, Mishra SK, Ahlawat A, Dimri AP (2022) Physico-chemical properties and deposition potential of PM2.5 during severe smog event in Delhi, India. Int J Environ Res Public Health 19:15387. https://doi.org/10.3390/ijerph192215387 Gehring U, Wijga AH, Brauer M et al (2010) Traffic-related air pollution and the development of asthma and allergies during the first 8 years of life. Am J Respir Crit Care Med 181(6):596–603. https://doi.org/10.1164/rccm.200906-0858OC George PE, Thakkar N, Yasobant S et al (2024) Impact of ambient air pollution and socio-environmental factors on the health of children younger than 5 years in India: a population-based analysis. Lancet Reg Health Southeast Asia 20:100328. https://doi.org/10.1016/j.lansea.2023.100328 Ghosh S, Sinha D (2025) Indian perspective of PM2.5 attributed human health hazards during 2010–2025. https://doi.org/10.1007/s11869-025-01793-6 . Air Qual Atmos Health Goldizen FC, Sly PD, Knibbs LD (2016) Respiratory effects of air pollution on children. Pediatr Pulmonol 51(1):94–108 Gupta S (2019) Agriculture crop residue burning and its consequences on respiratory health of school-going children. Glob Pediatr Health 6:2333794X19874679. https://doi.org/10.1177/2333794X19874679 HEI (2010) Traffic-related air pollution: A critical review of the literature on emissions, exposure, and health effects. Health Effects Institute, Boston Kanellopoulos N, Pantazopoulos I, Mermiri M et al (2021) Effect of PM2.5 levels on respiratory pediatric ED visits in a semi-urban Greek peninsula. Int J Environ Res Public Health 18(12):6384. https://doi.org/10.3390/ijerph18126384 Li YR, Xiao CC, Li J, Tang J, Geng XY, Cui LJ et al (2018) Association between air pollution and upper respiratory tract infection in hospital outpatients aged 0–14 years in Hefei, China: a time series study. Public Health 156:92–100. https://doi.org/10.1016/j.puhe.2018.09.009 Liu L, Ma X, Wen W, Sun C, Jiao J (2021) Characteristics and potential sources of wintertime air pollution in Linfen, China. Environ Monit Assess 8(5):252 Liu Y, Wang Y, Dong J et al (2022) Association between air pollution and emergency department visits for upper respiratory tract infection in Lanzhou, China. Environ Sci Pollut Res Int 29(19):28816–28828. https://doi.org/10.1007/s11356-022-19019-y Ma Q, Qi Y, Shan Q et al (2020) Understanding the knowledge gaps between air pollution controls and health impacts including pathogen epidemic. Environ Res 189:109949. https://doi.org/10.1016/j.envres.2020.109949 Malamardi S, Lambert KA, Praveena AS et al (2022) Time trends of greenspaces, air pollution, and asthma prevalence among children and adolescents in India. Int J Environ Res Public Health 19:15273. https://doi.org/10.3390/ijerph192215273 Monoson A, Schott E, Ard K et al (2023) Air pollution and respiratory infections: the past, present, and future. Toxicol Sci 192(1):3–14. https://doi.org/10.1093/toxsci/kfad068 Peden DB (2024) Respiratory health effects of air pollutants. Immunol Allergy Clin North Am 44(1):15–33. https://doi.org/10.1016/j.iac.2023.09.001 Pompilio A, Di Bonaventura G (2020) Ambient air pollution and respiratory bacterial infections: epidemiology, underlying mechanisms, and future challenges. Crit Rev Microbiol 46(5):600–630. https://doi.org/10.1080/1040841X.2020.1804818 Rodríguez-Fernández P, Prat-Aymerich C, Domínguez J (2019) Interaction between environmental pollution and respiratory infections. Arch Bronconeumol (Engl Ed) 55(7):351–352. https://doi.org/10.1016/j.arbres.2018.12.014 Shabani Isenaj Z, Berisha M, Gjorgjev D, Dimovska M, Moshammer H, Ukëhaxhaj A (2022) Air Pollution in Kosovo: Short Term Effects on Hospital Visits of Children Due to Respiratory Health Diagnoses. Int J Environ Res Public Health 16(16):10141 Silva DR, Viana VP, Müller AM et al (2013) Epidemiological aspects of respiratory symptoms treated in the emergency room of a tertiary care hospital. J Bras Pneumol 39(2):164–172. https://doi.org/10.1590/S1806-37132013000200008 UNICEF (2023) Breathless beginnings: The impact of air pollution on children in Europe. UNICEF Regional Office for Europe and Central Asia. https://www.unicef.org/eca/reports/breathless-beginnings Wang H, Qian G, Shi J et al (2024) Association between short-term exposure to ambient air pollution and upper respiratory tract infection in Kunshan. Int J Biometeorol 68(2):189–197. https://doi.org/10.1007/s00484-023-02546-1 Wawryk-Gawda E, Emeryk A, Chojęta A (2021) differential diagnosis of respiratory viral infections in children during the COVID-19 pandemic. Fam Med Prim Care Rev 23(4):501–507. https://doi.org/10.5114/fmpcr.2021.110372 WHO (2021) WHO global air quality guidelines. World Health Organization, Geneva. https://www.who.int/publications/i/item/9789240034228 WHO (2022) Ambient (outdoor) air pollution. World Health Organization, Geneva. https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health Wiesner A, Pfeifer S, Merkel M, Tuch T, Weinhold K, Wiedensohler A (2021) Real World Vehicle Emission Factors for Black Carbon Derived from Longterm In-Situ Measurements and Inverse Modelling. 12(1):31Atmosphere. Zhai G, Zhang L (2023) Impact of fine particulate matter 2.5 on hospitalization for upper respiratory tract infections in Lanzhou urban industrial area, China. Ann Agric Environ Med 30(3):462–467. https://doi.org/10.26444/aaem/167729 Zhang F, Zhang H, Wu C et al (2021) Acute effects of ambient air pollution on clinic visits of college students for upper respiratory tract infection in Wuhan, China. Environ Sci Pollut Res Int 28(23):29820–29830. https://doi.org/10.1007/s11356-021-12814-3 Ziou M, Tham R, Wheeler AJ, Zosky GR, Stephens N, Johnston FH (2022) Outdoor particulate matter exposure and upper respiratory tract infections in children and adolescents: A systematic review and meta-analysis. Environ Res 210:112969. https://doi.org/10.1016/j.envres.2022.112969 Additional Declarations No competing interests reported. Supplementary Files SuppTable1S.docx Cite Share Download PDF Status: Published Journal Publication published 13 Nov, 2025 Read the published version in European Journal of Pediatrics → Version 1 posted Editorial decision: Revision requested 02 Sep, 2025 Reviews received at journal 02 Sep, 2025 Reviews received at journal 25 Aug, 2025 Reviews received at journal 23 Aug, 2025 Reviewers agreed at journal 14 Aug, 2025 Reviewers agreed at journal 13 Aug, 2025 Reviewers agreed at journal 13 Aug, 2025 Reviewers invited by journal 11 Aug, 2025 Editor assigned by journal 04 Aug, 2025 Submission checks completed at journal 04 Aug, 2025 First submitted to journal 02 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7280297","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":500723386,"identity":"71d47b69-7879-4fcd-902d-61478e9b88a2","order_by":0,"name":"Ewelina Wawryk-Gawda","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYHACxgMJcPYBG4gIIT3IWtIgFEEtSMzDhLXwSyQfOPBwhx2DwfEzZp95zpxP3M7AewCvFskZaQkHEs8kMxicyTGezXPjduLOBr4EvFoMbucYHEhsY2YwO5C7mZnnw+3cDQd4DPBqsb+d/wGopZ7B7PxbkJZzhLUYSOcwALUcZjC7AbLlxgHCWiTuPwM57DiP/Y33nxnnnEmu39lMwC/8PYcfPvzZVi0n2Z+WzPDmmJ2xOXvvwQf4tMAAD4hgApEGzDzEaIACxh8gLQykaBkFo2AUjIKRAACACldTeNwi4AAAAABJRU5ErkJggg==","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":true,"prefix":"","firstName":"Ewelina","middleName":"","lastName":"Wawryk-Gawda","suffix":""},{"id":500723389,"identity":"f14d7409-7e57-4ba6-a77c-4a1c5f2a616f","order_by":1,"name":"Nadia Miga-Orczykowska","email":"","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Nadia","middleName":"","lastName":"Miga-Orczykowska","suffix":""},{"id":500723390,"identity":"f60ee73e-75a3-40d5-8d79-7fa30aad8583","order_by":2,"name":"Joanna Matusiak","email":"","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Joanna","middleName":"","lastName":"Matusiak","suffix":""},{"id":500723392,"identity":"1f2c11a5-ae0b-457c-8b8e-256317b00f3e","order_by":3,"name":"Dominika Mańdziuk","email":"","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Dominika","middleName":"","lastName":"Mańdziuk","suffix":""},{"id":500723393,"identity":"8da80dc8-1b24-4c2b-9ea8-ce2b4a4d1477","order_by":4,"name":"Kamila Giżewska","email":"","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Kamila","middleName":"","lastName":"Giżewska","suffix":""},{"id":500723395,"identity":"a2068f70-cfc6-4165-80cb-d6c1ffa07327","order_by":5,"name":"Violetta Opoka-Winiarska","email":"","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Violetta","middleName":"","lastName":"Opoka-Winiarska","suffix":""}],"badges":[],"createdAt":"2025-08-02 20:53:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7280297/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7280297/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00431-025-06572-0","type":"published","date":"2025-11-13T15:57:19+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89453971,"identity":"584b1e22-2f43-4d40-ad4e-1c82d40c3eff","added_by":"auto","created_at":"2025-08-20 06:44:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":44624,"visible":true,"origin":"","legend":"\u003cp\u003eAnnual number of pediatric ED visits for common cold (J00) and undifferentiated URTI (J06) between 2015 and 2020.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7280297/v1/dbb0759aab44903d971f33b3.png"},{"id":89453977,"identity":"afe590d4-d1ad-4943-9054-d9b8c0a07a77","added_by":"auto","created_at":"2025-08-20 06:44:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":139117,"visible":true,"origin":"","legend":"\u003cp\u003eTime series plot of daily ED visits for pediatric URTI (2015–2020) with a 30-day rolling mean (red line). Background shading indicates meteorological seasons: winter (gray), spring (green), summer (yellow), and autumn (orange). Seasonal fluctuations are visible, with recurrent peaks during winter periods, aligning with increased URTI incidence.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7280297/v1/def8f46c93c517bf729fbbfc.png"},{"id":89455144,"identity":"f2798f82-c974-4230-8e31-04470220fdf2","added_by":"auto","created_at":"2025-08-20 06:52:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":106790,"visible":true,"origin":"","legend":"\u003cp\u003eSeasonal variation in air pollutant concentrations measured from 2015 to 2020. Boxplots represent daily mean values for PM2.5, PM10, CO, NO₂, O₃, and SO₂ across four seasons. Kruskal-Wallis tests indicated statistically significant differences for all pollutants (p \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7280297/v1/5c47d86bb181cc1b8e59868f.png"},{"id":89456169,"identity":"8578b241-72b4-4d73-aba1-65289377bf2b","added_by":"auto","created_at":"2025-08-20 07:00:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":65369,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of daily pediatric URTI visits across exposure tertiles for PM2.5, PM10, CO, NO₂, O₃, and SO₂. Higher exposure levels of PM2.5, CO, and SO₂ corresponded with increased URTI incidence, whereas O₃ exposure showed an inverse trend.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7280297/v1/4bb5c0a99ed033571e25d8ae.png"},{"id":89453978,"identity":"03e27901-74ae-412e-bd0d-83aa99ace8da","added_by":"auto","created_at":"2025-08-20 06:44:31","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":292260,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly mean concentrations of air pollutants (blue bars) and paediatric ED visits for URTI in 2015–2021 (red line). Background shading represents meteorological seasons: winter (grey), spring (green), summer (yellow), and autumn (orange).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7280297/v1/f2da4112642cf2b3106caaee.png"},{"id":96105796,"identity":"274bb56c-c0d0-4db7-80f6-03c6223c7539","added_by":"auto","created_at":"2025-11-17 16:11:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1147793,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7280297/v1/4a8a8f97-64c9-4d65-bc46-2c8191ceefb8.pdf"},{"id":89453970,"identity":"0620d2aa-4778-4b5e-9af9-db115eaaa51e","added_by":"auto","created_at":"2025-08-20 06:44:31","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":25399,"visible":true,"origin":"","legend":"","description":"","filename":"SuppTable1S.docx","url":"https://assets-eu.researchsquare.com/files/rs-7280297/v1/91f0fe01ed5a2e791c850e64.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Air pollution exposure and the burden of paediatric upper respiratory tract infections in Emergency Departments","fulltext":[{"header":"Introduction","content":"\u003cp\u003eUpper respiratory tract infections (URTI) are among the most common reasons for Emergency Department (ED) visits in children and have become a significant public health concern. These infections, predominantly of viral origin, are influenced by multiple factors, including age, staying in large groups, anatomical and immunological predisposition and exposure to both household and outdoor air pollution (Wawryk-Gawda et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Silva et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAir pollutants comprise a complex mixture of chemical and biological substances released into the atmosphere, forming dynamic blends of gases and particulate matter. Their sources and composition vary considerably across regions and over time (Silva et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Dondi et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Choo et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Exposure to particulate matter with diameters of 2.5 \u0026micro;m and 10 \u0026micro;m (PM2.5, PM10), carbon monoxide (CO), nitrogen oxides (NOx, NO2), ozone (O3), and sulfur dioxide (SO2) is known to pose significant health risks. The World Health Organization\u0026rsquo;s Global Air Quality Guidelines provide reference thresholds and recommended limits for these substances (WHO \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wiesner et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; WHO \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eChildren are particularly vulnerable to the effects of air pollution. They spend more time outdoors engaged in physical activities, which increases their exposure to higher doses of pollutants. Due to their shorter stature, children inhale air closer to the ground, where concentrations of many toxicants are greater. Physiological characteristics such as higher rates of mouth breathing, higher minute ventilation relative to body size, and less effective filtration in the nasal passages further facilitate pollutant penetration into the respiratory tract. In addition, children\u0026rsquo;s smaller airways, underdeveloped mucociliary clearance, and immature immune and detoxification systems amplify the potential for harm and can interfere with normal respiratory development (Wawryk-Gawda et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Goldizen et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Rodr\u0026iacute;guez-Fern\u0026aacute;ndez et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough the relationship between air pollution and respiratory infections has been extensively studied in some regions, data specific to European pediatric populations remain limited (Ziou et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; HEI \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Bielska et al. 2015). While parents and healthcare professionals often focus on medications, vaccinations, nutrition, and supplementation to prevent infections, less attention is given to environmental exposures. In some households, children continue to be exposed to passive smoking, further compounding respiratory risks (Bielska et al. 2015; Peden \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe present study aimed to investigate the association between ambient air pollutant levels and the number of paediatric ED admissions due to upper respiratory tract infections. We hypothesized that higher concentrations of PM2.5, PM10, CO, NOx, NO2, O3, and SO2 would be significantly associated with an increased frequency of ED visits for URTI, independently of seasonal variation.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis retrospective observational study focused on key ambient air pollutants, including particulate matter (PM2.5 and PM10), carbon monoxide (CO), nitrogen oxides (NOx and NO2), ozone (O3), and sulphur dioxide (SO2). Data on paediatric Emergency Department (ED) admissions were extracted from the electronic medical records of the University Children\u0026rsquo;s Hospital in Lublin. Records included the date of admission, diagnosis codes according to the International Classification of Diseases (ICD-10), and basic demographic information. The dataset comprised 2,572 patients aged 0\u0026ndash;18 years who were admitted to the ED between January 2015 and December 2020 with a diagnosis of the common cold (J00) or acute upper respiratory tract infection of multiple and unspecified sites (J06). Daily concentrations of the selected air pollutants were obtained from the Chief Inspectorate for Environmental Protection\u0026rsquo;s certified ambient air monitoring station located on Obywatelska Street in Lublin (station code: PL507A). Although data were collected from a single monitoring site, this location was considered representative of urban background exposure for the city\u0026rsquo;s population. Lublin is the eighth largest city in Poland, with approximately 330,400 inhabitants. The region is characterized by a temperate climate, with average annual temperatures ranging between +\u0026thinsp;7.0\u0026deg;C and +\u0026thinsp;8.0\u0026deg;C. The warmest months are July and August (mean\u0026thinsp;+\u0026thinsp;19\u0026deg;C), while the coldest are January and February (mean \u0026minus;\u0026thinsp;5.0\u0026deg;C). The province combines agricultural and industrial activities, with the food industry and vehicle manufacturing among the main sectors of the local economy.\u003c/p\u003e\u003cp\u003eFor statistical analysis, we used Stata BE 18 software (StataCorp LLC, Texas, USA). Univariate linear regression models were applied to assess the association between the daily concentrations of individual pollutants or season and the number of daily ED admissions for URTI. Subsequently, multiple regression analyses were performed to evaluate the combined effects of pollutants and seasonality, adjusting for potential confounding. A p-value\u0026thinsp;\u0026le;\u0026thinsp;0.05 was considered statistically significant. To assess the relationship between air pollutant exposure and the frequency of upper respiratory tract infections (URTI), we performed a stratified visual analysis using exposure tertiles. For each of the six pollutants\u0026mdash;PM2.5, PM10, carbon monoxide (CO), nitrogen dioxide (NO₂), ozone (O₃), and sulfur dioxide (SO₂)\u0026mdash;daily values were divided into three equal-sized groups (tertiles) based on their distribution across the entire study period (2015\u0026ndash;2020). The resulting categories represented low, medium, and high exposure levels for each pollutant. We then constructed boxplots showing the distribution of daily URTI-related Emergency Department (ED) visits across these tertile groups. This approach allowed for a comparative visualization of the variability and central tendency of case numbers under different levels of pollutant exposure. Days with missing pollutant or URTI data were excluded from the respective analysis. The plots were generated using the seaborn.catplot function in Python (version 3.12.6), with boxplot parameters displaying median, interquartile ranges (IQR), and potential outliers. Institutional approval for the use of anonymized patient data was obtained from the hospital director. According to national regulations, separate bioethics committee approval was not required for this retrospective analysis of routinely collected administrative data (decision of Bioethics Committee at the Medical University of Lublin No BKB/10/01/2025).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe analysis included data from 2,572 children (mean age: 39 \u0026plusmn; 48.9 months), with boys representing 57% of the study population (Table 1). Undifferentiated upper respiratory tract infections (URTI, ICD code J06) were diagnosed more frequently than the common cold (J00), accounting for 64% and 36% of all visits, respectively (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Demographics of the study population.\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eGroup (\u003cem\u003en\u003c/em\u003e = 2,572)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMale/female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1,463(57%)/1,109(43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge (months)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; standard deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39 \u0026plusmn; 48.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMinimum\u0026ndash;maximum (median)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.19\u0026ndash;236 (18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e The diagnosis according to ICD classification: the common cold (J00) and undifferentiated upper respiratory tract infections (J06) in the study population.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"3\" cellpadding=\"0\" width=\"71%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eJ00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003eJ06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eFemale (n=1109)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e412 (37% of girls)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e697(63% of girls)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eMale (n=1463)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e513(35%of boys)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e950(65%of boys)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e925(36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e1647(64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e35.96%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e64.04%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAnnual trends in URTI-related ED visits\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe total number of pediatric Emergency Department (ED) visits due to URTI showed a consistent increase from 2015 to 2019, reaching a peak of 567 cases in 2019 (Figure 1). A decline was observed in 2020 (457 cases), likely attributable to public health restrictions during the COVID-19 pandemic.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSeasonal variation in URTI incidence\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eRespiratory infections were diagnosed more frequently during winter in each study year Fig. 1S). A statistically significant positive correlation was observed between season and daily number of URTI cases (Spearman\u0026rsquo;s rho = 0.23, p \u0026lt; 0.001) (Figure 2). Recurrent seasonal peaks were evident, aligning with winter months throughout the study period.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAssociations between pollutants and URTI incidence\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAcross the study period (2015\u0026ndash;2020), the mean concentrations of particulate matter exceeded World Health Organization (WHO) recommended limits, with average PM2.5 of 23.3 \u0026micro;g/m\u0026sup3; and PM10 of 30.4 \u0026micro;g/m\u0026sup3;. Seasonal variation was observed, with higher concentrations of PM2.5, PM10, CO, and SO₂ during winter months, while ozone (O₃) levels peaked in summer. The magnitude of pollution varied between years, with peak winter PM2.5 levels reaching 40 \u0026micro;g/m\u0026sup3; in 2017, compared to 26.6 \u0026micro;g/m\u0026sup3; in 2020 (Figure 3).\u003c/p\u003e\n\u003cp\u003eNon-parametric Kruskal-Wallis tests confirmed statistically significant differences in seasonal pollutant concentrations for all analyzed substances: PM2.5 (p \u0026lt; 1\u0026times;10⁻\u0026sup1;\u0026sup1;\u0026sup3;), PM10 (p \u0026lt; 1\u0026times;10⁻⁵⁸), CO (p \u0026lt; 1\u0026times;10⁻⁸⁷), NO₂ (p \u0026lt; 1\u0026times;10⁻\u0026sup1;⁹), O₃ (p \u0026lt; 1\u0026times;10⁻\u0026sup2;\u0026sup3;⁶), and SO₂ (p \u0026lt; 1\u0026times;10⁻⁹⁸) (Supplementary Table 1S).\u003c/p\u003e\n\u003cp\u003eSimple linear regression analyses revealed significant positive associations between daily concentrations of PM2.5, PM10, CO, O₃, and SO₂ and the number of pediatric URTI visits (Supplementary Table 2S). In multivariable regression models adjusting for seasonality, only CO and SO₂ remained independent predictors of URTI incidence (Table 3S).\u003c/p\u003e\n\u003cp\u003eSpearman rank correlations confirmed weak positive associations for CO (\u003cstrong\u003er = 0.13\u003c/strong\u003e) and PM2.5 (\u003cstrong\u003er = 0.10\u003c/strong\u003e) with URTI visits, whereas O₃ showed a weak inverse correlation (\u003cstrong\u003er = \u0026ndash;0.12\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eBoxplots illustrating daily URTI visit counts across pollutant exposure tertiles are presented in Figure 4. Higher exposure levels of PM2.5, CO, and SO₂ were associated with increased median and variability of daily URTI cases. PM10 demonstrated a weaker positive \u0026nbsp;trend, while O₃ exposure showed an inverse association with URTI incidence, likely reflecting its inverse seasonal pattern. NO₂ did not exhibit a clear trend.\u003c/p\u003e\n\u003cp\u003eMonthly averaged data demonstrated clear seasonal patterns for both pollutant concentrations and pediatric URTI visits (Figure 5). Peaks in PM2.5, PM10, CO, and SO₂ levels coincided with winter months, during which ED visits for URTI were most frequent. In contrast, ozone (O₃) concentrations were higher during summer months, when respiratory infections were less prevalent. Nitrogen dioxide (NO₂) displayed more variable patterns, without a consistent monotonic association with URTI visits. Spearman\u0026rsquo;s rank correlation analysis confirmed statistically significant positive associations between daily concentrations of PM2.5 (\u0026rho; = 0.10, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), CO (\u0026rho; = 0.13, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), SO₂ (\u0026rho; = 0.11, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), and PM10 (\u0026rho; = 0.08, \u003cem\u003ep\u003c/em\u003e = 0.002) and the number of pediatric ED visits for URTI. O₃ showed a weak inverse correlation (\u0026rho; = \u0026minus;0.12, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), while NO₂ did not reach statistical significance (\u0026rho; = 0.04, \u003cem\u003ep\u003c/em\u003e = 0.072). Non-parametric Kruskal-Wallis tests indicated significant seasonal differences in pollutant levels for all six pollutants (all \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), with winter having the highest mean concentrations of PM2.5, PM10, CO, and SO₂. Univariate linear regression models identified PM2.5, PM10, CO, SO₂, and O₃ as significant predictors of daily URTI-related ED visits (all \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). However, in multivariable models adjusted for co-pollutant exposure and seasonality, only CO (\u0026beta; = 0.018, 95% CI: 0.010\u0026ndash;0.026, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) and SO₂ (\u0026beta; = 0.035, 95% CI: 0.020\u0026ndash;0.051, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) remained independent predictors of paediatric URTI incidence.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study demonstrated a significant association between exposure to ambient air pollutants and pediatric Emergency Department (ED) visits for upper respiratory tract infections (URTI). In single-pollutant regression models, we observed positive correlations for PM2.5, PM10, CO, and SO₂ with URTI incidence, whereas O₃ exhibited a weak inverse relationship. In multivariable models adjusting for seasonality and co-pollutant exposure, only CO and SO₂ remained independent predictors of pediatric ED visits. Both URTI incidence and air pollutant concentrations displayed clear seasonal variation, with pronounced peaks during winter months.\u003c/p\u003e\u003cp\u003eOur results align with a study conducted in a Greek suburban region, where researchers observed that over the course of a year, PM 2.5 levels in both the central and surrounding areas of Volos frequently surpassed the WHO's recommended safety threshold, with the most significant air pollution occurring in the winter and spring seasons (Kanellopoulos et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In these seasons a statistically significant increase in upper respiratory infections-related visits in ED was observed if PM2.5 levels were more than 25 \u0026micro;g/m3 (Kanellopoulos et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The large-scale ESCAPE project demonstrated associations between exposure to NO₂, PM10, and increased respiratory infections in children (Gehring et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Rodr\u0026iacute;guez-Fern\u0026aacute;ndez et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) described similar associations in Spain, and Ziou et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) confirmed via meta-analysis that particulate matter exposure increases URTI risk in children across Europe. Reports from the European Environment Agency (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and UNICEF (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) emphasize that air pollution remains one of the leading environmental health risks for European children, contributing to higher rates of respiratory infections, asthma, and impaired lung growth.\u003c/p\u003e\u003cp\u003eMore data about the association between air pollution and respiratory diseases are available from China. These studies have suggested significant association also between NO\u003csub\u003e2\u003c/sub\u003e concentration and URTI-related visits in ED. The study by Liu et al., which focused on pediatric hospital outpatients aged 0\u0026ndash;14 years in Hefei, China, found that in single-pollutant models, PM10, PM2.5, SO2, NO\u003csub\u003e2\u003c/sub\u003e, and CO were all significantly associated with an increase in URTI cases. However, when considering all pollutants together in a full model, only NO\u003csub\u003e2\u003c/sub\u003e maintained a significant positive relationship with the number of outpatient visits for URTI (Li et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe study of Wang et al. carried out in Kunshan showed significant associations with hospital visits and expenditures due to upper respiratory tract infections (URTI) both in children and adult, and PM2.5, PM10, SO\u003csub\u003e2\u003c/sub\u003e, and NO\u003csub\u003e2\u003c/sub\u003e concentration in ambient air. Additionally, sensitivity analyses revealed that the associations with PM2.5, PM10, and NO\u003csub\u003e2\u003c/sub\u003e were stronger in individuals aged 18 years and younger. The strength of these associations also fluctuated depending on the season (Wang et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eChoo et al. showed that increased O\u003csub\u003e3,\u003c/sub\u003e SO\u003csub\u003e2\u003c/sub\u003e, and PM2.5 concentrations were positively associated with URTI case counts and they found that air pollutants were more important than meteorological factors (such as air temperature, humidity) (Choo et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSimilarly, the study of Zhang et al. conducted in Wuhan showed strong and significant association between clinic visits for URTI of college students due to URTI and PM2.5 (0.74% (95%CI: 0.05, 1.44), PM10 (0.61% (95%CI: 0.12, 1.11), O\u003csub\u003e3\u003c/sub\u003e (1.01% (95%CI: 0.24, 1.79), SO\u003csub\u003e2\u003c/sub\u003e (9.18% (95%CI: 3.27,15.42) and NO\u003csub\u003e2\u003c/sub\u003e (3.40% (95% CI:1.64, 5.19). Moreover PM10, SO\u003csub\u003e2\u003c/sub\u003e and NO\u003csub\u003e2\u003c/sub\u003e were independent factors increasing frequency of URTI-related visits (Zhang et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe high association of each pollutant with hospital emergency visits was observed by Liu et al. in Lanzhou with PM2.5 (5.302% (95% CI:3.202, 7.445)), PM10 (0.808% (95% CI: 0.291, 1.328)), SO\u003csub\u003e2\u003c/sub\u003e (10.607% (95% CI: 5.819, 15.611)), and NO\u003csub\u003e2\u003c/sub\u003e (5.325% (95% CI: 2.379, 8.357)). The associations appeared to be stronger in the cold seasons (autumn and winter) than in the warm seasons (spring and summer) (Liu et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) as in our study. In the same place Zhai and Zhang conducted a study which revealed that PM2.5 had the most significant effect on the number of outpatient visits for upper respiratory tract infections (Zhai and Zhang \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Indian research (Fatima et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Abudureyimu et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Adhikary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Gupta \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; George et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Malamardi et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Ghosh et al. 2025) confirmed substantial increases in pediatric respiratory infections with elevated PM2.5 exposure, particularly during smog episodes and biomass burning events. Specifically, every 10 \u0026micro;g/m\u0026sup3; rise in PM2.5 concentration was linked to a 23% increase in the odds of acute respiratory tract infection among children (OR 1.23, 95% CI: 1.19\u0026ndash;1.27) (Adhikary et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Seasonal agricultural practices, particularly the burning of rice crop residues, have been identified as major contributors to elevated PM2.5 levels, leading to measurable declines in lung function among school-aged children exposed to such events (Gupta \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). A large-scale, state-level analysis indicated a significant association between vegetation cover (NDVI index) and the prevalence of asthma attributable to PM2.5 exposure in children and adolescents (β\u0026thinsp;=\u0026thinsp;0.144; 95% CI: 0.10\u0026ndash;0.186; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Malamardi et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Furthermore, research focusing on children under five years of age revealed a non-linear yet monotonic relationship between ambient PM2.5 concentrations and the occurrence of respiratory illnesses in this population (George et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Regional differences in pollutant composition, industrial activity, and meteorological factors may explain heterogeneity in reported effect sizes worldwide. Although the government has taken many measures to improve the local air quality, the level of air pollutants concentration (the average annual PM2.5, PM10, and NO\u003csub\u003e2\u003c/sub\u003e concentrations during 2014\u0026ndash;2018 in Lanzhou were 51.33 \u0026micro;g/m3, 120.50 \u0026micro;g/m3, 46.90 \u0026micro;g/m3, respectively) exceeded the daily or annual limit (Liu et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eShabani et al. (2022) demonstrated that environmental conditions significantly influence the harmful effects of air pollution on infections. Their research took place in Kosovo, a mountainous region with limited air circulation, particularly in winter. The elevated pollution levels were attributed to factors such as residential heating, traffic, industrial activities, and coal-fired power plants. The study found that daily average PM2.5 concentrations ranged from 2.41 to 161.03 \u0026micro;g/m\u0026sup3;, and an increase in PM2.5 levels was associated with a rise in the number of visits over the several days (Shabani et al. 2022). The occurrence of disasters such as wildfires are also a cause of the short-term deterioration of air. Ademu et al. observed significant associations between PM2.5, CO, NO\u003csub\u003e2\u003c/sub\u003e, and Air Quality Index (AQI) and confirmed cases of COVID-19 across 20 counties in California impacted by wildfires (Ademu et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe mechanism of pollution-related respiratory tract diseases is multifactorial. Higher concentrations of human bacterial and viral pathogens were found in the atmosphere during burning of biomass (Pompilio \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Bioaerosols also represented a reservoir of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs). More pathogenic bacteria were observed in the airway of people from cities with high pollutant concentration (Monoson et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePollutant exposure is responsible for compromising the immunological system required to protect individuals from infections. The air pollutants alter cellular responses to respiratory infection disrupting the normal innate barrier, the epithelial lining fluid and mucociliary clearance. The data conducted with animals and people showed that after air pollution exposure components of innate immune response were altered such as defenses macrophage phagocytosis, secretion of antimicrobial peptides (e.g. β-defensin-2), number and function of neutrophils, T-cells and dendritic cells which can compromise the response to bacterial and viral infections. The air pollutants (PM2.5, O\u003csub\u003e3\u003c/sub\u003e, and NO\u003csub\u003e2\u003c/sub\u003e) induce oxidative stress and ROS that damage tight-junctions allowing intraepithelial translocation of bacterial pathogens towards blood, and enhances bacterial adhesion and biofilm formation onto epithelial cells, as well as cell invasion. In addition, SO\u003csub\u003e2\u003c/sub\u003e reduced production or release of TNF-α. PM adsorb a relevant number of components on their surface, mainly organic compounds, nitrates, sulphates, metals, and biological particles such as bacteria. After being inhaled, this composition settles onto the airway epithelium where it is wetted by the epithelial lining fluid. Redox-active materials, as well as bacteria, are then released from the PM surface into the fluid where they trigger cell damage (Ma et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Peden \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, Pompilio and Di Bonaventura \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Silva et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Dondi et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Peden \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These mechanisms, demonstrated in experimental and clinical studies, explain observed increases in respiratory infection susceptibility in polluted environments.\u003c/p\u003e\u003cp\u003eThe data concerns association between air pollution and respiratory tract diseases as well as mechanisms responsible for these relationship are important to make a rigorous decision about limitation of pollution. CO and SO₂ emerged as independent predictors, underscoring the role of combustion-related emissions from traffic, heating, and industrial sources. Seasonal peaks in pollution and URTI incidence highlight the need for targeted interventions during winter months. Strengthening air quality regulations, aligning standards with WHO guidelines (WHO \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; WHO \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and raising parental awareness are essential to reduce pediatric respiratory disease burden in Europe and globally (HEI \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; European Environment Agency \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; UNICEF \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOur study has certain limitations that should be acknowledged. Our analysis implemented the mean values of the measured pollutants levels in one ambient air monitoring station in Lublin, thus not accurately reflecting the individual exposure. Furthermore, as the diagnoses were performed in an emergency setting, it is possible that some of them were inaccurate, leading to misclassification. The data include all the cases only from one hospital in Lublin.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides robust evidence that exposure to ambient air pollutants, particularly CO and SO₂, is associated with an increased frequency of pediatric ED visits for URTI. Seasonal variation plays a significant role, with winter peaks in pollutants corresponding to higher infection rates. Our findings align with European and global literature, supporting calls for stronger air quality interventions to protect children's respiratory health. It is also important to raise awareness among parents about the harmful effects of pollutants on their children. Year-specific Spearman\u0026rsquo;s rank correlation analyses revealed that the strength of the association between pollutant levels and daily URTI visits varied over time. The correlations were most pronounced in 2017\u0026ndash;2018, particularly for PM2.5 (ρ\u0026thinsp;=\u0026thinsp;0.22 in 2017), PM10 (ρ\u0026thinsp;=\u0026thinsp;0.20 in 2017), CO (ρ\u0026thinsp;=\u0026thinsp;0.21 in 2017), and SO₂ (ρ\u0026thinsp;=\u0026thinsp;0.24 in 2018). In 2019, the correlation coefficients weakened despite higher URTI visit counts. Ozone consistently showed a weak inverse relationship with URTI visits (ρ from \u0026minus;\u0026thinsp;0.08 to \u0026minus;\u0026thinsp;0.19 across years), whereas NO₂ did not demonstrate a statistically meaningful association in any year.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting Interests\u003c/h2\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003ch2\u003eEthics approval\u003c/h2\u003e\n\u003cp\u003eThis is an retrospective study of data, no ethical approval is required.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by EWG, NMO, JM, DM and KG. The first draft of the manuscript was written by EWG and VOW prepared final version of manuscript, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eManuscript preparation was supported during Harvard Medical School\u0026rsquo;s Polish Clinical Scholars Research Training Program, organised by the Agencja Badan Medycznych (ABM, English: Medical Research Agency, Warsaw, Poland\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are not publicly but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbudureyimu K, Suryadhi MAH, Yorifuji T, Tsuda T (2023) Exposure to fine particulate matter and acute upper- and lower-respiratory tract infections (AURI and ALRI) in children under five years of age in India. Arch Environ Occup Health 78:1\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/19338244.2022.2047584\u003c/span\u003e\u003cspan address=\"10.1080/19338244.2022.2047584\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAdemu LO, Gao J, Thompson OP, Ademu LA (2022) Impact of Short-Term Air Pollution on Respiratory Infections: A Time-Series Analysis of COVID-19 Cases in California during the 2020 Wildfire Season. Int J Environ Res Public Health 21(9):5057\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAdhikary M, Mal P, Saikia N (2024) Exploring the link between particulate matter pollution and acute respiratory infection risk in children using generalized estimating equations analysis: a robust statistical approach. Environ Health 23(1):1\u0026ndash;11. https://doi.org/0.1186/S12940-024-01049-3\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBielska DE, Gom\u0026oacute;łka E, Kurpas D, Chlabicz S (205). Narazenie dzieci w wieku przedszkolnym na dym tytoniowy\u0026ndash;badanie por\u0026oacute;wnawcze [Exposure to environmental tobacco smoke in pre-school children\u0026ndash;a comparative study]. Przegl Lek 72(10):505-8. in Polish\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChoo ELW, Janhavi A, Koo JR, Yim SHL, Dickens BL, Lim JT (2023) Association between ambient air pollutants and upper respiratory tract infection and pneumonia disease burden in Thailand from 2000 to 2022: a high frequency ecological analysis. BMC Infect Dis 6(1):379\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDondi A, Carbone C, Manieri E et al (2023) Outdoor air pollution and childhood respiratory disease: the role of oxidative stress. Int J Mol Sci 24(5):4345. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijms24054345\u003c/span\u003e\u003cspan address=\"10.3390/ijms24054345\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEuropean Environment Agency (2023) Air pollution and children's health. EEA, Copenhagen. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.eea.europa.eu/publications/air-pollution-and-childrens-health\u003c/span\u003e\u003cspan address=\"https://www.eea.europa.eu/publications/air-pollution-and-childrens-health\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFatima S, Mishra SK, Ahlawat A, Dimri AP (2022) Physico-chemical properties and deposition potential of PM2.5 during severe smog event in Delhi, India. Int J Environ Res Public Health 19:15387. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph192215387\u003c/span\u003e\u003cspan address=\"10.3390/ijerph192215387\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGehring U, Wijga AH, Brauer M et al (2010) Traffic-related air pollution and the development of asthma and allergies during the first 8 years of life. Am J Respir Crit Care Med 181(6):596\u0026ndash;603. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1164/rccm.200906-0858OC\u003c/span\u003e\u003cspan address=\"10.1164/rccm.200906-0858OC\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGeorge PE, Thakkar N, Yasobant S et al (2024) Impact of ambient air pollution and socio-environmental factors on the health of children younger than 5 years in India: a population-based analysis. Lancet Reg Health Southeast Asia 20:100328. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.lansea.2023.100328\u003c/span\u003e\u003cspan address=\"10.1016/j.lansea.2023.100328\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGhosh S, Sinha D (2025) Indian perspective of PM2.5 attributed human health hazards during 2010\u0026ndash;2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11869-025-01793-6\u003c/span\u003e\u003cspan address=\"10.1007/s11869-025-01793-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Air Qual Atmos Health\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGoldizen FC, Sly PD, Knibbs LD (2016) Respiratory effects of air pollution on children. Pediatr Pulmonol 51(1):94\u0026ndash;108\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGupta S (2019) Agriculture crop residue burning and its consequences on respiratory health of school-going children. Glob Pediatr Health 6:2333794X19874679. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/2333794X19874679\u003c/span\u003e\u003cspan address=\"10.1177/2333794X19874679\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHEI (2010) Traffic-related air pollution: A critical review of the literature on emissions, exposure, and health effects. Health Effects Institute, Boston\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKanellopoulos N, Pantazopoulos I, Mermiri M et al (2021) Effect of PM2.5 levels on respiratory pediatric ED visits in a semi-urban Greek peninsula. Int J Environ Res Public Health 18(12):6384. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph18126384\u003c/span\u003e\u003cspan address=\"10.3390/ijerph18126384\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi YR, Xiao CC, Li J, Tang J, Geng XY, Cui LJ et al (2018) Association between air pollution and upper respiratory tract infection in hospital outpatients aged 0\u0026ndash;14 years in Hefei, China: a time series study. Public Health 156:92\u0026ndash;100. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.puhe.2018.09.009\u003c/span\u003e\u003cspan address=\"10.1016/j.puhe.2018.09.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu L, Ma X, Wen W, Sun C, Jiao J (2021) Characteristics and potential sources of wintertime air pollution in Linfen, China. Environ Monit Assess 8(5):252\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu Y, Wang Y, Dong J et al (2022) Association between air pollution and emergency department visits for upper respiratory tract infection in Lanzhou, China. Environ Sci Pollut Res Int 29(19):28816\u0026ndash;28828. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11356-022-19019-y\u003c/span\u003e\u003cspan address=\"10.1007/s11356-022-19019-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMa Q, Qi Y, Shan Q et al (2020) Understanding the knowledge gaps between air pollution controls and health impacts including pathogen epidemic. Environ Res 189:109949. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envres.2020.109949\u003c/span\u003e\u003cspan address=\"10.1016/j.envres.2020.109949\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMalamardi S, Lambert KA, Praveena AS et al (2022) Time trends of greenspaces, air pollution, and asthma prevalence among children and adolescents in India. Int J Environ Res Public Health 19:15273. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph192215273\u003c/span\u003e\u003cspan address=\"10.3390/ijerph192215273\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMonoson A, Schott E, Ard K et al (2023) Air pollution and respiratory infections: the past, present, and future. Toxicol Sci 192(1):3\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/toxsci/kfad068\u003c/span\u003e\u003cspan address=\"10.1093/toxsci/kfad068\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePeden DB (2024) Respiratory health effects of air pollutants. Immunol Allergy Clin North Am 44(1):15\u0026ndash;33. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.iac.2023.09.001\u003c/span\u003e\u003cspan address=\"10.1016/j.iac.2023.09.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePompilio A, Di Bonaventura G (2020) Ambient air pollution and respiratory bacterial infections: epidemiology, underlying mechanisms, and future challenges. Crit Rev Microbiol 46(5):600\u0026ndash;630. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/1040841X.2020.1804818\u003c/span\u003e\u003cspan address=\"10.1080/1040841X.2020.1804818\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRodr\u0026iacute;guez-Fern\u0026aacute;ndez P, Prat-Aymerich C, Dom\u0026iacute;nguez J (2019) Interaction between environmental pollution and respiratory infections. Arch Bronconeumol (Engl Ed) 55(7):351\u0026ndash;352. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.arbres.2018.12.014\u003c/span\u003e\u003cspan address=\"10.1016/j.arbres.2018.12.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShabani Isenaj Z, Berisha M, Gjorgjev D, Dimovska M, Moshammer H, Uk\u0026euml;haxhaj A (2022) Air Pollution in Kosovo: Short Term Effects on Hospital Visits of Children Due to Respiratory Health Diagnoses. Int J Environ Res Public Health 16(16):10141\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSilva DR, Viana VP, M\u0026uuml;ller AM et al (2013) Epidemiological aspects of respiratory symptoms treated in the emergency room of a tertiary care hospital. J Bras Pneumol 39(2):164\u0026ndash;172. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/S1806-37132013000200008\u003c/span\u003e\u003cspan address=\"10.1590/S1806-37132013000200008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUNICEF (2023) Breathless beginnings: The impact of air pollution on children in Europe. UNICEF Regional Office for Europe and Central Asia. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.unicef.org/eca/reports/breathless-beginnings\u003c/span\u003e\u003cspan address=\"https://www.unicef.org/eca/reports/breathless-beginnings\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang H, Qian G, Shi J et al (2024) Association between short-term exposure to ambient air pollution and upper respiratory tract infection in Kunshan. Int J Biometeorol 68(2):189\u0026ndash;197. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00484-023-02546-1\u003c/span\u003e\u003cspan address=\"10.1007/s00484-023-02546-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWawryk-Gawda E, Emeryk A, Chojęta A (2021) differential diagnosis of respiratory viral infections in children during the COVID-19 pandemic. Fam Med Prim Care Rev 23(4):501\u0026ndash;507. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5114/fmpcr.2021.110372\u003c/span\u003e\u003cspan address=\"10.5114/fmpcr.2021.110372\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWHO (2021) WHO global air quality guidelines. World Health Organization, Geneva. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/9789240034228\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/9789240034228\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWHO (2022) Ambient (outdoor) air pollution. World Health Organization, Geneva. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health\u003c/span\u003e\u003cspan address=\"https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWiesner A, Pfeifer S, Merkel M, Tuch T, Weinhold K, Wiedensohler A (2021) Real World Vehicle Emission Factors for Black Carbon Derived from Longterm In-Situ Measurements and Inverse Modelling. 12(1):31Atmosphere.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhai G, Zhang L (2023) Impact of fine particulate matter 2.5 on hospitalization for upper respiratory tract infections in Lanzhou urban industrial area, China. Ann Agric Environ Med 30(3):462\u0026ndash;467. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.26444/aaem/167729\u003c/span\u003e\u003cspan address=\"10.26444/aaem/167729\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang F, Zhang H, Wu C et al (2021) Acute effects of ambient air pollution on clinic visits of college students for upper respiratory tract infection in Wuhan, China. Environ Sci Pollut Res Int 28(23):29820\u0026ndash;29830. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11356-021-12814-3\u003c/span\u003e\u003cspan address=\"10.1007/s11356-021-12814-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZiou M, Tham R, Wheeler AJ, Zosky GR, Stephens N, Johnston FH (2022) Outdoor particulate matter exposure and upper respiratory tract infections in children and adolescents: A systematic review and meta-analysis. Environ Res 210:112969. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.envres.2022.112969\u003c/span\u003e\u003cspan address=\"10.1016/j.envres.2022.112969\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejpe","sideBox":"Learn more about [European Journal of Pediatrics](https://www.springer.com/journal/431)","snPcode":"431","submissionUrl":"https://submission.nature.com/new-submission/431/3","title":"European Journal of Pediatrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"air pollution, Emergency Department, upper respiratory tract infections, pediatrics, children, hospitalization","lastPublishedDoi":"10.21203/rs.3.rs-7280297/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7280297/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUpper respiratory tract infections (URTI) are a major public health problem and a leading cause of pediatric Emergency Department (ED) visits. Approximately 81% of emergency outpatient visits in children are due to URTI, and respiratory diseases account for 12% of all deaths worldwide. Air pollution is considered an important factor contributing to the increased incidence of respiratory infections.\u003c/p\u003e\n\u003cp\u003eThe aim of this study was to examine the association between ambient air pollutant concentrations and the number of pediatric ED admissions for URTI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e. We conducted a retrospective analysis including 2,572 children admitted to the ED between 2015 and 2020 with a diagnosis of URTI. Daily concentrations of particulate matter (PM2.5 and PM10), carbon monoxide (CO), nitrogen oxides (NOx and NO2), ozone (O3), and sulfur dioxide (SO2) were obtained from a certified environmental monitoring station.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e. The highest number of URTI-related visits was observed in winter 2019, coinciding with the peak levels of air pollutants. In univariate analyses, higher concentrations of PM2.5, PM10, CO, and SO2 were significantly associated with increased ED admissions. After adjusting for seasonality in multivariable models, only CO and SO2 remained independent predictors of higher URTI incidence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e. Our findings indicate that air pollution is strongly associated with the frequency of pediatric URTI-related ED visits. While seasonality plays an important role, CO and SO2 appear to be key independent factors driving this association.\u003c/p\u003e","manuscriptTitle":"Air pollution exposure and the burden of paediatric upper respiratory tract infections in Emergency Departments","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-20 06:44:26","doi":"10.21203/rs.3.rs-7280297/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-02T21:50:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-02T18:09:01+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-25T12:42:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-23T18:18:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"48250927855084766363730255109316818006","date":"2025-08-14T20:45:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"107870530239612078333907344371408834704","date":"2025-08-13T09:45:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"287688140459889990351911669252990165540","date":"2025-08-13T08:10:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-11T21:02:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-04T11:17:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-04T11:14:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Pediatrics","date":"2025-08-02T20:44:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejpe","sideBox":"Learn more about [European Journal of Pediatrics](https://www.springer.com/journal/431)","snPcode":"431","submissionUrl":"https://submission.nature.com/new-submission/431/3","title":"European Journal of Pediatrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"74afe641-77f9-48f5-8791-4df7efb28989","owner":[],"postedDate":"August 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-17T16:08:49+00:00","versionOfRecord":{"articleIdentity":"rs-7280297","link":"https://doi.org/10.1007/s00431-025-06572-0","journal":{"identity":"european-journal-of-pediatrics","isVorOnly":false,"title":"European Journal of Pediatrics"},"publishedOn":"2025-11-13 15:57:19","publishedOnDateReadable":"November 13th, 2025"},"versionCreatedAt":"2025-08-20 06:44:26","video":"","vorDoi":"10.1007/s00431-025-06572-0","vorDoiUrl":"https://doi.org/10.1007/s00431-025-06572-0","workflowStages":[]},"version":"v1","identity":"rs-7280297","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7280297","identity":"rs-7280297","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}