Allergic Rhinitis as an Independent Risk Factor for Pneumonia in Children: A Large-Scale Database Analysis

Allergic Rhinitis as an Independent Risk Factor for Pneumonia in Children: A Large-Scale Database Analysis | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 5 February 2026 V1 Latest version Share on Allergic Rhinitis as an Independent Risk Factor for Pneumonia in Children: A Large-Scale Database Analysis Authors : Hsin-Yu Chiang , Wan-Ting Huang , Chia-Hsin Hou , Ling-Chin Hsieh , Kuo-Huang Lee , and Chuang-Ming Wang [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.177028210.02777576/v1 257 views 79 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Background: While allergic rhinitis (AR) is linked to upper airway complications, its independent association with pneumonia, particularly after excluding asthma, remains insufficiently characterized in large pediatric populations. Objective: To evaluate the risk of pneumonia in children with AR and assess the independent effect of AR by accounting for asthma and other comorbidities. Methods: Using the TriNetX global research network, we conducted a retrospective cohort study of children aged 2–18 years newly diagnosed with AR. A control group without AR was matched 1:1 using propensity score matching (PSM) for demographics and comorbidities. The primary outcome was pneumonia incidence during 3–12 month and 1–3 year follow-up windows. Subgroup analyses were performed for non-asthmatic cohorts and regional networks (US and APAC). Results: Each cohort included 163,149 matched patients. Children with AR faced a significantly higher risk of pneumonia compared to controls at 3–12 months (HR 3.70; 95% CI 3.37–4.07) and 1–3 years (HR 2.98; 95% CI 2.77–3.20). Notably, in the non-asthmatic subgroup, the risk was even more pronounced (HR 4.56 at 3–12 months). Within the AR cohort, comorbid asthma further increased pneumonia risk (HR 1.54). Results remained consistent in sensitivity analyses using elevated IgE levels and across both US and APAC networks. Conclusion: Allergic rhinitis is a potent independent risk factor for pneumonia in children, regardless of asthma status. These findings underscore the importance of early AR management to potentially mitigate lower respiratory complications. Full Title: Allergic Rhinitis as an Independent Risk Factor for Pneumonia in Children: A Large-Scale Database Analysis Authors: Hsin-Yu Chiang a ; Wan-Ting Huang b ; Chia-Hsin Hou a ; Ling-Chin Hsieh a ; Kuo-Huang Lee a ; Chuang-Ming Wang a * Affiliations: a Department of Pediatrics, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan b Clinical Medical Research Center, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan Running title: Allergic Rhinitis and Pediatric Pneumonia Risk Corresponding Author: Chuang-Ming Wang, MD Department of Pediatrics, Ditmanson Medical Foundation Chia-Yi Christian Hospital No. 539, Zhongxiao Rd., East Dist., Chiayi City 60002, Taiwan Email: [email protected] Phone: +886-5-2765041 Word Count (Abstract): 248 words Word Count (Main Text): Approx. 3080words Number of Figures: 2 Number of Tables: 4 Conflict of Interest Statement: The authors declare no conflicts of interest associated with this study. Funding Source: This work was supported by a grant from the Ditmanson Medical Foundation Chia-Yi Christian Hospital Research Program (R111-60). Abstract Background: While allergic rhinitis (AR) is linked to upper airway complications, its independent association with pneumonia, particularly after excluding asthma, remains insufficiently characterized in large pediatric populations. Objective: To evaluate the risk of pneumonia in children with AR and assess the independent effect of AR by accounting for asthma and other comorbidities. Methods: Using the TriNetX global research network, we conducted a retrospective cohort study of children aged 2–18 years newly diagnosed with AR. A control group without AR was matched 1:1 using propensity score matching (PSM) for demographics and comorbidities. The primary outcome was pneumonia incidence during 3–12 month and 1–3 year follow-up windows. Subgroup analyses were performed for non-asthmatic cohorts and regional networks (US and APAC). Results: Each cohort included 163,149 matched patients. Children with AR faced a significantly higher risk of pneumonia compared to controls at 3–12 months (HR 3.70; 95% CI 3.37–4.07) and 1–3 years (HR 2.98; 95% CI 2.77–3.20). Notably, in the non-asthmatic subgroup, the risk was even more pronounced (HR 4.56 at 3–12 months). Within the AR cohort, comorbid asthma further increased pneumonia risk (HR 1.54). Results remained consistent in sensitivity analyses using elevated IgE levels and across both US and APAC networks. Conclusion: Allergic rhinitis is a potent independent risk factor for pneumonia in children, regardless of asthma status. These findings underscore the importance of early AR management to potentially mitigate lower respiratory complications. Keywords: Allergic rhinitis, Pneumonia, Children, Asthma, TriNetX, One airway Allergic Rhinitis as an Independent Risk Factor for Pneumonia in Children: A Large-Scale Database Analysis Introduction Allergic rhinitis (AR) is a prevalent chronic inflammatory disorder of the upper airway, affecting as much as 30% of the population in Taiwan. It frequently coexists with other atopic conditions, forming part of the ”atopic march” alongside asthma and atopic dermatitis. 1 While the association between AR and upper respiratory tract complications—such as rhinosinusitis and otitis media—is well-documented, 2,3 its specific role in the development of lower respiratory tract infections, particularly pneumonia, remains poorly defined in pediatric populations. Although the clinical symptoms of AR are primarily localized to the nasal mucosa, the underlying immunopathology often extends beyond the upper airways. 4 AR is characterized by a type 2 helper T cell (Th2)-dominant immune response, marked by elevated levels of cytokines such as interleukin (IL)-4, IL-5, and IL-13. Notably, IL-13 has been shown to impair mucociliary clearance by reducing ciliary beat frequency in airway epithelial cells, which facilitates microbial adhesion and increases overall susceptibility to infection. 5 Furthermore, this Th2-skewed environment is associated with suppressed antiviral and antibacterial defenses, including the downregulation of interferon-γ and IL-17 pathways, both of which are essential for mucosal immunity and pathogen clearance. 6,7 Structural and functional abnormalities associated with chronic AR—such as sinus ostial obstruction or Eustachian tube dysfunction—may also create biological reservoirs for pathogen colonization, potentially leading to downstream dissemination into the lower respiratory tract. 2 In addition, inadequate management of AR, particularly the underuse of intranasal corticosteroids, can exacerbate mucosal inflammation and compromise epithelial barrier integrity, further increasing vulnerability to respiratory infections. 3 Epidemiological evidence increasingly supports a link between allergic diseases and heightened infection risk. Both asthma and AR have been associated with higher rates of recurrent respiratory infections (RRI) and various lower respiratory tract diseases. 8 Additionally, IgE sensitization is correlated with an elevated risk of asthma, chronic airway disease, and pneumonia. 9 Interestingly, this relationship may be bidirectional; pneumonia itself has been linked to a heightened incidence of allergic conditions such as asthma and wheezing in children. 10 While serious pneumococcal disease has shown significant associations with a history of asthma and atopic dermatitis, previous findings regarding AR and hay fever have often failed to reach statistical significance, likely due to sample size limitations in smaller cohorts. 11,12 A pooled meta-analysis recently demonstrated increased odds of several infections in individuals with atopy, though it did not identify a specific link to pneumonia. 13 Given these gaps in the literature, this retrospective cohort study leverages the extensive TriNetX Research Network data to determine whether children with AR face an increased risk of pneumonia. Data Source This study utilized data from the TriNetX Research Network, a global federated health research network providing access to de-identified electronic medical records (EMRs) from over 120 participating healthcare organizations (HCOs) worldwide. The network encompasses approximately 250 million individuals and includes patient-level data on demographics, diagnoses (ICD-9-CM and ICD-10-CM), procedures (CPT, ICD-9-PCS, and ICD-10-PCS), medications, laboratory results, healthcare utilization, and vital signs. All data within TriNetX are de-identified in accordance with the Health Insurance Portability and Accountability Act (HIPAA) and relevant institutional privacy regulations. As the study exclusively utilized anonymized data, it was exempt from formal Institutional Review Board (IRB) review. Nevertheless, the study protocol was approved by the Institutional Review Board of Chia-Yi Christian Hospital, Taiwan (IRB No. 2025091). Data analyses were conducted in December 2025, covering a study period from January 1, 2002, to December 31, 2022. Study Design and Population In this retrospective cohort study, we evaluated whether children with AR have an increased risk of developing pneumonia. We identified children aged 2–18 years newly diagnosed with AR, defined by ICD-9-CM code 477 or ICD-10-CM codes J30.1, J30.2, J30.5, J30.81, J30.89, and J30.9. To ensure diagnostic accuracy, patients were required to have at least two AR diagnoses within a 90-day period. The index date was defined as the date of the initial qualifying AR diagnosis. Exclusion criteria included a prior diagnosis of pneumonia (ICD-9-CM 483; ICD-10-CM J12–J18) before the index date, age outside the 2–18 range, a history of cystic fibrosis (E84), or congenital anomalies (Q89.7, Q89.9). A control cohort of children without any AR diagnosis was selected and matched to the AR cohort in a 1:1 ratio using propensity score matching (PSM) based on age, sex, and selected comorbidities. Definition of Covariates and Subgroups To minimize confounding, covariates including demographics (age and sex) and race (White, Black or African American, Asian, American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, and Other/Unknown) were recorded. Comorbidities were defined as dichotomous variables based on diagnoses prior to the index date, including asthma (ICD-9-CM: 493; ICD-10-CM: J45), atopic dermatitis (ICD-10-CM: L20.x), food allergy (ICD-10-CM: Z91.01, T78.0, T78.1), gastroesophageal reflux disease (GERD; ICD-10-CM: K21), atopic conjunctivitis (ICD-10-CM: H10.1), diabetes mellitus (ICD-10-CM: E08–E13), systemic lupus erythematosus (SLE; ICD-10-CM: M32), Sjögren syndrome (ICD-10-CM: M35.0), chronic kidney disease (ICD-10-CM: N18), and overweight or obesity (ICD-10-CM: E66). Subgroup analyses were conducted based on age—preschool (2–5 years), school-aged (6–11 years), and adolescents (12–18 years)—and race. Additional analyses were performed after excluding patients with asthma to assess the independent effect of AR. Outcome and Sensitivity Analyses The primary outcome was defined as the first occurrence of pneumonia between 90 days and 1 year following the index date. Pneumonia cases were identified through inpatient diagnoses using ICD-9-CM code 483 or ICD-10-CM codes J12–J18. To evaluate the robustness and generalizability of the results, several sensitivity analyses were performed. First, we applied alternative follow-up windows ranging from 1 to 3 years after the index date to assess the long-term persistence of the observed risks. Second, the primary analyses were replicated using data from the TriNetX U.S. and APAC (Asia-Pacific) Research Networks, employing identical cohort definitions and propensity score matching strategies. Additionally, a specific sensitivity analysis was conducted using a more stringent definition of AR characterized by elevated immunoglobulin E (IgE) levels. In this context, high IgE was defined as >100 IU/mL or >240 μg/L for participants aged 2–18 years Statistical Analysis Continuous variables were presented as means with standard deviations (SDs) and compared between groups using the Student’s t-test. Categorical variables were summarized as counts and percentages, with differences assessed using the chi-square test. Following PSM, Cox proportional hazards regression models were employed to estimate the association between allergic rhinitis and the risk of pneumonia. The results of these models were expressed as hazard ratios (HRs) with corresponding 95% confidence intervals (CIs). The proportional hazards assumption was rigorously evaluated using Schoenfeld residuals, and no violations were identified within the fitted Cox models. Furthermore, Kaplan–Meier survival curves were generated to estimate the cumulative incidence of pneumonia, with differences between the cohorts assessed using the log-rank test. All statistical analyses were two-sided, and a P value of less than 0.05 was considered to indicate statistical significance. Results Demographic Characteristics Figure 1 illustrates the selection process for the study cohorts. We initially identified 194,544 children aged 2–18 years with a new diagnosis of AR who had at least two AR diagnoses within a 90-day period. After exclusion and PSM, each cohort included 163,149 patients. The mean (SD) age was 8.59 (±4.68) years in the AR cohort and 8.59 (±4.79) years in the control cohort after exclusion and PSM. Following PSM, the AR cohort consisted of 91,972 males (56.37%), with a racial distribution of 70,160 White (43.00%), 28,252 Black or African American (17.32%), 9,730 Asian (5.96%), and 44,866 of unknown race (27.50%). All variables achieved statistical balance with a standardized mean difference (SMD) below 0.1. Detailed demographic characteristics before and after matching are summarized in Table 1. Main Outcomes The risk of pneumonia was significantly higher in children with AR compared to the matched control cohort across both follow-up periods. During the first year (3–12 months), children with AR had a 3.7-fold increased risk (HR 3.70; 95% CI: 3.37–4.07), which remained elevated at 2.98 (95% CI: 2.77–3.20) during the 1–3 year follow-up (Table 2; Figure 2A, 2B). Notably, the risk was most pronounced in the subgroup of children with AR but without asthma, exhibiting a hazard ratio of 4.56 (95% CI: 3.98–5.23) in the first year and 3.20 (95% CI: 2.90–3.54) in the 1–3 year period. These findings suggest that AR itself serves as a potent independent risk factor for pneumonia. Subgroup Analyses Subgroup analyses consistently demonstrated increased pneumonia risk across all age groups and major racial categories. Children aged 2–5, 6–11, and 12–18 years revealed hazard ratios of 3.86, 4.68, and 4.01, respectively, during the 3–12 month period, and 2.67, 3.09, and 3.21 during the 1–3 year follow-up (Table 2). Racial subgroup analyses also showed elevated risks, with hazard ratios of 3.85 (95% CI: 3.28–4.53) for White, 2.70 (95% CI: 2.15–3.40) for Black or African American, 3.54 (95% CI: 2.51–4.99) for Asian, and 5.57 (95% CI: 2.97–10.44) for children of unknown race during the 3–12 month window. Internal comparison within the AR cohort further revealed that patients with comorbid asthma faced a significantly higher risk compared to those with AR alone (HR 1.54 at 3–12 months; 95% CI: 1.36–1.74), suggesting that the presence of asthma further compounds the vulnerability to lower respiratory tract infections (Table 3). Sensitivity Analyses Sensitivity analyses corroborated the robustness of the primary findings. In children with elevated IgE levels, pneumonia risk was significantly increased with hazard ratios of 3.37 and 3.29 for the 3–12 month and 1–3 year periods, respectively (Table 4; Figure 2C, 2D). Consistent with the non-asthmatic AR cohort, the risk remained higher for those without asthma, with hazard ratios of 4.01 and 3.73 during the respective follow-up periods (Table 4). Results from the US network corroborated the global trend, with hazard ratios of 2.64 (95% CI: 2.38–2.92) and 2.14 (95% CI: 1.98–2.31) for short-term and long-term follow-ups (e Table 2). Furthermore, analysis within the APAC region showed hazard ratios of 2.95 (95% CI: 2.46–3.53) for the 3–12 month period and 1.75 (95% CI: 1.51–2.02) for the 1–3 year period (e Table 3). Discussion: This retrospective cohort study leveraged the TriNetX global database to evaluate the incidence of pneumonia in children with AR relative to a PSM control group. Our findings demonstrate that the risk of pneumonia was significantly elevated in the AR cohort across both the 3–12 month and 1–3 year follow-up periods. This increased risk remained robust and consistent across all subgroup analyses when stratified by age and race. Furthermore, children with AR who exhibited elevated IgE levels were found to have a significantly higher susceptibility to pneumonia. Notably, children with AR in the absence of comorbid asthma faced a markedly higher risk of pneumonia compared to the matched control cohort. These results strongly suggest that AR itself serves as a potent independent risk factor for lower respiratory tract infections, irrespective of concomitant asthmatic conditions. AR is strongly associated with RRIs, defined as frequent episodes of illness that can progressively involve the lower airways. 8 . Evidence indicates that allergic children experience a significantly higher frequency and longer duration of respiratory infections compared to their non-allergic counterparts. 7 Clinical research has identified that a high number of prior upper respiratory tract infections serves as an independent risk factor for community-acquired pneumonia (CAP). 14 Consequently, by increasing the frequency of URTIs, AR indirectly elevates the likelihood of an infection progressing to pneumonia. In addition, the relationship between AR and asthma is well-documented, with up to 40% of AR patients reporting asthma symptoms and approximately 80% of asthmatic individuals presenting with symptomatic AR. 15 Rhinitis is an independent risk factor for the development of asthma 16 . Rhinitis itself is recognized as an independent risk factor for the subsequent development of asthma. 14 Given that asthma is an established independent risk factor for CAP in both pediatric and adult populations, AR acts as a precursor that predisposes patients to a higher-risk category for pneumonia. While our primary analysis established AR as an independent risk factor for pneumonia, our internal comparison within the AR cohort demonstrated that comorbid asthma further compounds this vulnerability, increasing the risk with a hazard ratio of 1.54 during the 3–12 month follow-up period. This finding aligns with the ”one airway” concept, suggesting that the presence of synchronized inflammation in both the upper and lower respiratory tracts creates a more severe clinical profile and greater susceptibility to infectious complications Allergic diseases such as AR are characterized by Th2-polarization, which establishes a systemic environment that impairs the host’s ability to eradicate pathogens. 6 The induction of the Th2 pathway often leads to a concomitant reduction in the Th1 response, which is crucial for effective host defense. Interferon-gamma (IFN–γ), a prototypical Th1 cytokine, is essential for combating infections; 17 however, atopic patients frequently exhibit diminished levels of these protective cytokines, thereby increasing their susceptibility to severe respiratory infections. 6 The primary receptor for rhinovirus, intercellular adhesion molecule-1 (ICAM-1), also plays a significant role in this susceptibility. In allergic subjects, exposure to allergens has been shown to upregulate ICAM-1 expression within nasal epithelial cells. 18 This makes it easier for viruses to colonize the airway, and viral infections are known precursors that can lead to bacterial pneumonia. 7 Furthermore, chronic allergic inflammation and eosinophilia in AR patients have been linked to a significant loss of epithelial integrity. Patients with defective nasal tissue repair programs may be particularly predisposed to developing more severe lower airway diseases. 19 This weakened respiratory epithelial barrier reduces the structural defense against microbial threats, making it easier for pathogens to adhere to and invade the respiratory mucosa, ultimately increasing the risk of pulmonary infection. AR is characterized by Th2-mediated inflammation, which triggers goblet cell hyperplasia and metaplasia, leading to the overproduction of altered, hyperviscous mucus. 20 In pediatric patients, this thick secretion increases the risk of airway obstruction and provides an ideal ”niche” or breeding ground for microbial colonization. 21 Besides, high levels of the Th2 cytokine IL-13 can induce a structural loss of ciliated cells and the mis-localization of basal bodies, which are essential for anchoring cilia. 22 The chronic inflammation associated with AR further leads to the deterioration of ciliary structures and a significant reduction in ciliary beat frequency . This reduction in ciliary beat frequency impairs the mechanical clearance of pathogens, allowing bacteria such as Streptococcus pneumoniae to resist expulsion and colonize the respiratory tract. 23 Given that the nasal mucosa acts as the primary portal for air filtration, children with AR exhibit a significantly prolonged nasal mucociliary clearance time. 21 When the upper airway fails to effectively filter and trap airborne contaminants, these pathogens may descend through the trachea into the bronchi and alveoli, ultimately facilitating the development of pneumonia. Large-scale cohort studies have indicated that children with AR face a nearly two-fold increased risk of developing new-onset GERD. 24 GERD itself is recognized as a significant independent risk factor for highly recurrent community-acquired pneumonia in pediatric populations. 25 This association is largely attributed to the cardinal symptoms of AR, such as posterior nasal drip and persistent throat itching, which lead to a significantly increased frequency of swallowing. 26 When gastric contents reach the laryngopharyngeal region as a result of reflux, the risk of micro-aspiration of these contents into the respiratory tract increases. 27 Chronic upper airway conditions associated with AR, such as rhinosinusitis with posterior nasal drip, can serve as a biological reservoir for bacterial pathogens. Micro-aspiration provides a vehicle for these pathogens to enter the lower airways chronically. 28 Consequently, the promotion of GERD by AR, combined with the aspiration of pathogens from upper airway reservoirs, creates an environment highly susceptible to both acute and recurrent pulmonary infections. This study possesses several key strengths. First, it provides large-scale real-world evidence by leveraging the TriNetX global federated health research network, which encompasses a diverse study population of approximately 250 million individuals. This allowed for a massive cohort of over 163,000 matched pairs, providing exceptional statistical power for both primary and subgroup analyses. Second, we employed rigorous PSM to achieve a high degree of balance across a comprehensive set of baseline variables, including age, sex, race, and various comorbidities such as GERD and obesity, thereby minimizing the impact of potential confounders. Third, by specifically analyzing children with AR without comorbid asthma, we successfully isolated the independent effect of allergic rhinitis on pneumonia risk, addressing a major confounding factor in respiratory research. Finally, our findings were further validated through sensitivity analyses involving children with elevated IgE levels and across different regional networks (APAC and US), which enhances the biological plausibility and generalizability of our results. However, several limitations should be considered when interpreting these findings. As a retrospective study based on EMRs, the results are inherently subject to potential coding inaccuracies or omissions by healthcare providers. Additionally, the TriNetX database lacks granular data on certain environmental risk factors, such as socioeconomic status, housing conditions, or environmental tobacco smoke exposure, which may act as residual confounders. Furthermore, since the control cohort was defined by the absence of a recorded AR diagnosis, the inclusion of undiagnosed or very mild AR cases in the control group could potentially lead to an underestimation of the true hazard ratios. Lastly, while the overall sample size was large, certain rare demographic subgroups, such as the American Indian or Alaska Native population, had insufficient event counts in some follow-up windows, which limited our ability to generate reliable estimates for these specific groups. In conclusion, this large-scale retrospective cohort study utilizing the TriNetX global research network demonstrates that children with AR face a significantly increased risk of developing pneumonia. This association remains robust across both short-term (3–12 months) and long-term (1–3 years) follow-up periods, with the most substantial risk observed within the first year of diagnosis. Importantly, our findings indicate that AR serves as a potent independent risk factor, as the increased risk persists regardless of asthma status. Moreover, the elevated risk was consistently observed across various age groups and racial categories, and was further validated in sensitivity analyses of children with elevated IgE levels and across different regional healthcare networks (APAC and US). These results underscore the critical importance of early diagnosis and effective management of AR in the pediatric population. Clinicians should maintain a high index of suspicion for lower respiratory complications in children with AR to ensure timely intervention and improve long-term respiratory outcomes. Acknowledgments The authors thank the assistance provided by Chun Lee from the Clinical Data Center, Ditmanson Medical Foundation Chia-Yi Christian Hospital, for administrative and technical consultation regarding the TriNetX database. Key Message: • Children with AR face a significantly higher risk of pneumonia compared to matched controls at both 3–12 months (HR 3.70) and 1–3 years (HR 2.98) follow-up. • Notably, the risk remains potent in the non-asthmatic subgroup , with a hazard ratio of 4.56 during the first year, confirming that AR is an independent risk factor. • The increased risk was consistent across different age groups, races, and regional networks (US and APAC). • Sensitivity analyses using elevated IgE levels ( >100 IU/mL) further corroborated the robustness of these findings. AI Disclosure: During the preparation of this work, the authors used Gemini (Google) to assist in refining the language and improving the structural flow of the manuscript. The authors reviewed and edited the content as needed and take full responsibility for the final version of the manuscript References 1. Wang CM, Yang ST, Yang CC, et al. 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Allergy. 2010;65(11):1351-1356.18. Ciprandi G, Buscaglia S, Pesce G, Villaggio B, Bagnasco M, Canonica GW. Allergic subjects express intercellular adhesion molecule–1 (ICAM-1 or CD54) on epithelial cells of conjunctiva after allergen challenge. J Allergy Clin Immunol. 1993;91(3):783-792.19. Samitas K, Carter A, Kariyawasam HH, Xanthou G. Upper and lower airway remodelling mechanisms in asthma, allergic rhinitis and chronic rhinosinusitis: The one airway concept revisited. Allergy. 2018;73(5):993-1002.20. Steelant B, Seys SF, Van Gerven L, et al. Histamine and T helper cytokine-driven epithelial barrier dysfunction in allergic rhinitis. J Allergy Clin Immunol. 2018;141(3):951-963 e958.21. Batmaz SB, Alicura Tokgoz S. Relationship between nasal mucociliary clearance and disease severity in children with allergic rhinitis: A comparative cross-sectional study. Allergol Immunopathol (Madr). 2020;48(2):137-141.22. Adivitiya, Kaushik MS, Chakraborty S, Veleri S, Kateriya S. Mucociliary Respiratory Epithelium Integrity in Molecular Defense and Susceptibility to Pulmonary Viral Infections. Biology (Basel). 2021;10(2).23. Fliegauf M, Sonnen AF, Kremer B, Henneke P. Mucociliary clearance defects in a murine in vitro model of pneumococcal airway infection. PLoS One. 2013;8(3):e59925.24. Feng MC, Tsai YG, Chang YH, Kuo CH, Lin YC, Hung CH. Allergic rhinitis as a key factor for the development of gastroesophageal reflux disease in children. J Microbiol Immunol Infect. 2021;54(6):1167-1174.25. Patria F, Longhi B, Tagliabue C, et al. Clinical profile of recurrent community-acquired pneumonia in children. BMC Pulm Med. 2013;13:60.26. Kung YM, Tsai PY, Chang YH, et al. Allergic rhinitis is a risk factor of gastro-esophageal reflux disease regardless of the presence of asthma. Sci Rep. 2019;9(1):15535.27. Iov DE, Barboi OB, Floria M, Neamtu A, Iliescu R, Drug VL. Pepsin and the Lung-Exploring the Relationship between Micro-Aspiration and Respiratory Manifestations of Gastroesophageal Reflux Disease. J Pers Med. 2022;12(8).28. Patria MF, Longhi B, Lelii M, et al. Children with recurrent pneumonia and non-cystic fibrosis bronchiectasis. Ital J Pediatr. 2016;42:13. Figure Legend Figure 1. Study Population Enrollment Flowchart. Figure 2. Cumulative incidence of pneumonia in children with AR and matched controls. Kaplan–Meier survival curves show cumulative incidence across subgroups. (A) Short-term primary cohorts (3–12 months). (B) Long-term primary cohorts (1–3 years). (C) Short-term elevated IgE sensitivity subgroup. (D) Long-term elevated IgE sensitivity subgroup. In all analyses, AR patients exhibited higher pneumonia incidence (P < 0.001) before matching PS matching AR cohort Control cohort P value Std diff. AR cohort Control cohort P value Std diff. n=163551 n=26670197 n=163149 n=163149 Age at index, y <0.001 0.029 0.825 <0.001 Mean±SD 8.59±4.67 8.74±5.54 8.59±4.68 8.59±4.79 Gender, n(%) <0.001 0.119 0.013 0.009 Male 92158(56.35) 13449189(50.43) 91972(56.37) 91269(55.94) Female 71393(43.65) 13221008(49.57) 71177(43.63) 71880(44.06) Race White 70335(43.01) 11653326(43.69) <0.001 0.014 70160(43.00) 70919(43.47) <0.001 0.009 Black or African American 28343(17.33) 3134959(11.76) <0.001 0.159 28252(17.32) 22292(13.66) <0.001 0.101 Unknoen Race 44943(27.48) 8667028(32.50) <0.001 0.110 44866(27.50) 50102(30.71) <0.001 0.071 Asian 9752(5.96) 962972(3.61) <0.001 0.110 9730(5.96) 5264(3.23) <0.001 0.131 Other Race 8630(5.28) 1981885(7.43) <0.001 0.088 8598(5.27) 12584(7.71) <0.001 0.099 Native Hawaiian or Other Pacific Islander 736(0.45) 149653(0.56) <0.001 0.016 732(0.45) 1283(0.79) <0.001 0.043 American Indian or Alaska Native 812(0.50) 120374(0.45) 0.007 0.007 811(0.50) 705(0.43) 0.006 0.010 Asthma(J45) 55889(11.61) 180397(0.68) 0.999 <0.001 Atopic dermatitis(L20) 18989(11.61) 195398(0.73) <0.001 0.464 18945(11.61) 2634(1.61) <0.001 0.411 GERD(K21) 11003(6.73) 229211(0.86) <0.001 0.311 10974(6.73) 3576(2.19) <0.001 0.221 Food allergy(Z91.01) 8912(5.45) 52138(0.20) <0.001 0.321 8876(5.44) 693(0.43) <0.001 0.301 Other adverse food reactions, not elsewhere classified(T78.1) 2945(1.80) 15868(0.06) <0.001 0.182 2935(1.80) 185(0.11) <0.001 0.174 Anaphylactic reaction due to food(T78.0) 1263(0.77) 5435(0.02) <0.001 0.120 1258(0.77) 163(0.10) <0.001 0.102 Acute atopic conjunctivitis(H10.1) 7397(4.52) 6403(0.02) <0.001 0.305 7377(4.52) 158(0.10) <0.001 0.298 Diabetes mellitus(E08-E13) 637(0.39) 10153(0.04) <0.001 0.076 637(0.39) 238(0.15) <0.001 0.047 SLE(M32) 239(0.15) 447(0.00) <0.001 0.053 239(0.15) 10(0.01) <0.001 0.051 Sjögren syndrome(M35.0) 82(0.05) 60(0.00) <0.001 0.032 82(0.05) 10(0.01) <0.001 0.026 Chronic kidney disease(N18) 274(0.17) 5567(0.02) <0.001 0.048 274(0.17) 53(0.03) <0.001 0.043 Overweight/obesity(E66) 9748(5.96) 27410(0.10) <0.001 0.347 9705(5.95) 1368(0.84) <0.001 0.285 PS matching, propensity score matching. Matched for age at index, sex and asthma. 3–12 Months 1-3 years Event HR 95%CI Event HR 95%CI AR cohort vs. Control cohort 2469 vs. 511 3.70 3.37-4.07 3480 vs. 897 2.98 2.77-3.20 AR cohort without asthma vs. Control cohort without asthma 1481 vs. 240 4.56 3.98-5.23 2068 vs. 471 3.20 2.90-3.54 Age 2-5 1450 vs. 291 3.86 3.40-4.38 1893 vs. 553 2.67 2.43-2.93 6-11 786 vs. 126 4.68 3.88-5.65 1238 vs. 300 3.09 2.72-3.50 12-18 274 vs. 52 4.01 2.98-5.39 562 vs. 132 3.21 2.65-3.87 Race White 852 vs. 177 3.85 3.28-4.53 1441 vs. 375 2.98 2.66-3.34 Black or African American 320 vs. 94 2.70 2.15-3.40 490 vs. 141 2.70 2.24-3.26 Asian 178 vs. 40 3.54 2.51-4.99 248 vs. 61 3.23 2.44-4.28 Other Race 84 vs. 11 5.57 2.97-10.44 143 vs.23 4.36 2.81-6.77 Native Hawaiian or Other Pacific Islander – – American Indian or Alaska Native – – AR, allergic rhinitis; HR, hazard ratio; CI, confidence interval; PSM, propensity score matching. – Hazard ratio could not be calculated due to small cohorts or infrequent outcomes. 3–12 Months 1-3 years Event HR 95%CI Event HR 95%CI AR cohort with asthma vs. AR cohort without asthma 638 vs. 391 1.54 1.36-1.74 899 vs. 602 1.36 1.23-1.51 Age 2-5 vs. 6-11 1393 vs. 588 2.41 2.19-2.66 1806 vs. 969 1.96 1.81-2.12 2-5 vs. 12-18 1533 vs. 291 5.23 4.61-5.93 2029 vs. 618 3.33 3.04-3.64 6-11 vs. 12-18 595 vs. 263 2.26 1.95-2.61 961 vs. 563 1.68 1.51-1.86 *Adjusted for sex and all baseline comorbidities through propensity score matching. 3–12 Months 1-3 years Event HR 95%CI Event HR 95%CI AR cohort vs. Control cohort 1056 238 3.37 2.92-3.87 1750 vs.385 3.29 2.95-3.68 AR cohort without asthma vs. Control cohort withoutasthma 497 vs. 91 4.01 3.20-5.01 854 vs. 158 3.73 3.15-4.42 Age 2-5 638 vs. 145 3.32 2.78-3.98 1018 vs. 247 2.96 2.57-3.40 6-11 424 vs. 94 3.59 2.87-4.49 776 vs. 236 2.49 2.15-2.88 12-18 136 vs. 28 4.17 2.77-6.26 315 vs. 89 2.93 2.32-3.71 Race White 332 vs. 109 2.41 1.94-2.99 607 vs. 177 2.62 2.21-3.09 Black or African American 266 vs. 59 3.56 2.68-4.72 – Asian 152 vs. 32 3.84 2.62-5.62 266 vs. 75 2.80 2.17-3.62 Other Race 50 vs. 3822 4.20 3.18-5.55 109 vs. 23 3.28 2.09-5.14 Native Hawaiian or Other Pacific Islander – – American Indian or Alaska Native – – AR, allergic rhinitis; HR, hazard ratio; CI, confidence interval; PSM, propensity score matching. – Hazard ratio could not be calculated due to small cohorts or infrequent outcomes. 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Authors Affiliations Hsin-Yu Chiang Ditmanson Medical Foundation Chia-Yi Christian Hospital View all articles by this author Wan-Ting Huang Ditmanson Medical Foundation Chia-Yi Christian Hospital View all articles by this author Chia-Hsin Hou Ditmanson Medical Foundation Chia-Yi Christian Hospital View all articles by this author Ling-Chin Hsieh Ditmanson Medical Foundation Chia-Yi Christian Hospital View all articles by this author Kuo-Huang Lee Ditmanson Medical Foundation Chia-Yi Christian Hospital View all articles by this author Chuang-Ming Wang [email protected] Ditmanson Medical Foundation Chia-Yi Christian Hospital View all articles by this author Metrics & Citations Metrics Article Usage 257 views 79 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Hsin-Yu Chiang, Wan-Ting Huang, Chia-Hsin Hou, et al. Allergic Rhinitis as an Independent Risk Factor for Pneumonia in Children: A Large-Scale Database Analysis. Authorea . 05 February 2026. 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