You are currently viewing a new version of our website. To view the old version click .
Children
  • Article
  • Open Access

22 December 2025

Determinants of Asthma Control in Jordanian Children: The Role of Comorbidities and FeNO Levels

,
,
,
,
,
,
,
,
and
1
Department of Pediatrics, School of Medicine, University of Jordan, Queen Rania St., Amman 11942, Jordan
2
Department of Pharmacy, Faculty of Pharmacy, Al-Zaytoonah University of Jordan, Airport Street, Amman 11733, Jordan
3
Department of Psychology, School of Social Sciences, Humanities and Law, Teesside University, Borough Road, Middlesbrough TS1 3BX, UK
4
Department of Physiology and Biochemistry, School of Medicine, University of Jordan, Queen Rania St., Amman 11942, Jordan
This article belongs to the Section Pediatric Pulmonary and Sleep Medicine

Abstract

Background/Objectives: Asthma is a prevalent chronic respiratory disease in children, and poor asthma control remains a major clinical challenge worldwide. In Jordan, the rising prevalence of pediatric asthma highlights a need to better understand the factors influencing asthma control and to evaluate new assessment tools. Methods: This cross-sectional study aimed to identify predictors of asthma control and to assess the clinical utility of fractional exhaled nitric oxide (FeNO) as a supplementary biomarker. A total of 329 children with physician-diagnosed asthma, aged 7–17 years, were recruited from Jordan University Hospital. Clinical history, spirometry, FeNO measurements, and Asthma Control Test scores were collected. Results: Overall, 62.6% of participants had uncontrolled asthma. Logistic regression analysis revealed that comorbidities such as obstructive sleep apnea, gastroesophageal reflux disease, allergic rhinitis, and bronchiolitis obliterans were significantly associated with poorer asthma control. Antihistamine use and elevated FeNO levels were also linked to lower odds of asthma control. Conclusions: While FeNO showed promise as a non-invasive marker of airway inflammation, its clinical application remains limited due to variability and confounding factors. A comprehensive, individualized approach to asthma management, considering comorbidities and conventional assessments, is essential. Larger, longitudinal studies are needed to establish the role of FeNO in routine pediatric asthma care.

1. Introduction

Asthma is a major global health concern, affecting nearly 300 million individuals worldwide and causing approximately 1000 deaths each day [1]. In recent years, the prevalence of asthma among children has been rising rapidly [2], with detection rates reaching 10%, making it a pressing global public health issue [3,4]. In Jordan, the prevalence of asthma among children and adolescents has increased significantly, from 4.3% in 1996 to 12.3% in 2011 [5,6]. Despite this significant increase, local data on the factors influencing asthma control, particularly in pediatric populations, remain limited, hampering the ability to formulate evidence-based management plans.
Asthma has long been defined as a heterogeneous syndrome characterized by airway hyperresponsiveness, which manifests clinically as cough, wheezing, and shortness of breath, with various triggers causing exacerbations and disease progression [7]. Despite the extensive body of research and proposed treatment modalities for pediatric asthma, uncontrolled disease continues to impose a significant physical, mental, and socioeconomic burden on both affected individuals and caregivers [8]. The rates for uncontrolled asthma were significantly high among U.S and Swedish children at 50.3% and 31.0%, respectively [9,10]. Such public health concern is best manifested as a significant economic burden at a global scale [11,12]. The U.S annual costs for asthma are estimated to be $82 billion [13].
Uncontrolled asthma in pediatrics exhibits a far-reaching impact beyond its challenging spectrum of treatment as it impacts academic performance and quality of life [14,15]. A Jordanian study showed that about 70% of children with asthma missed school due to their condition [16]. Another cross-sectional study evaluating asthma care in U.S. children aged 5 to 17 found that adolescents with poorer asthma-related emotional quality of life experienced worse asthma control and increased school absences [17]. Moreover, a retrospective cohort study of asthma patients treated at King Abdullah University Hospital found that severe, uncontrolled asthma was associated with significantly higher total annual medical costs [18].
There are many factors known to influence asthma control, such as comorbid conditions and medication adherence [19,20]. Associated comorbidities include are but are not limited to obstructive sleep apnea (OSA), gastroesophageal reflux disease (GERD), rhinitis, sinusitis, and bronchiolitis. These conditions can affect asthma through different pathophysiological mechanisms; for instance, OSA may contribute to asthma through systemic inflammation, while GERD can worsen asthma by directly irritating the airways [21]. A meta-analysis examining the relationship between various comorbid conditions and asthma found a strong correlation between allergic rhinitis and asthma, with approximately 30% to 80% of asthmatic patients also having allergic rhinitis [19,20].
Assessment of asthma control is essential for effective disease management and the prevention of exacerbations. Validated questionnaires (e.g., Childhood Asthma Control Test) [22], spirometry-based calculations (e.g., Global Lung Initiative equations) [23,24,25], or surrogate biomarkers (e.g., Exhaled breath condensate, urinary cysteinyl leukotriene E4, eosinophilic cationic protein) [26], were developed as means of assessing asthma control to facilitate timely intervention.
Recently, fractional exhaled nitric oxide (FeNO) has been proposed as a promising non-invasive tool for identifying asthma phenotypes, determining the level of asthma control, predicting exacerbations, and assessing the potential need for medication [27]. It is considered a reliable biomarker for detecting type 2 inflammation in asthma [28]; therefore, it is currently being studied for both asthma diagnosis and disease monitoring [29]. Numerous studies evaluating FeNO use in asthmatic children have found elevated FeNO levels during exacerbations, supporting its role in identifying airway inflammation [30]. The National Institute for Health and Care Excellence (NICE) recommends considering FeNO measurements to manage symptomatic asthma in patients who continue to experience symptoms despite the use of inhaled corticosteroids [31]. Moreover, the American Thoracic Society (ATS) has recommended FeNO testing since 2021 as a strategy to reduce exacerbations by tailoring asthma treatment [32].
In light of what’s above, the present cross-sectional study aimed to identify the key factors influencing asthma control status, including comorbidities, medication use, and reliance on rescue drugs. In addition, our study examined the association between FeNO levels and asthma control. By addressing these factors, we hoped to contribute to improving asthma control in pediatric patients, particularly within the Jordanian healthcare context where tailored data and national guidelines are still developing.

2. Materials and Methods

2.1. Study Design

This cross-sectional study included asthmatic children aged 7 to 17 years who were diagnosed according to the GINA criteria and were followed by pediatric pulmonary specialists. Diagnosis of asthma was established by expert physicians based on the presence of variable asthma-related symptoms (e.g., wheezes, shortness of breath, cough) and variable expiratory airflow limitation. Indicators of variability include significant bronchodilator reversibility, significant average daily diurnal PEF variability, or FEV1 increases of ≥12% after 4 weeks of anti-inflammatory treatment.
Children younger than 7 or older than 17 years, as well as those unable to perform FeNO or pulmonary function testing (PFT), were excluded. Clinical history was collected through a questionnaire completed by the children or their parents. All medical reporting was cross-checked with clinical records to reduce bias. The questionnaire covered a range of topics, including medication history, such as the use of inhaled corticosteroids, inhaled salbutamol, montelukast, antihistamines, and oral steroids. Additionally, family history of asthma and social factors were assessed, including exposure to environmental tobacco smoke, pet ownership, and the presence of eczema. OSA diagnosis was established through clinical examination and the Pediatric Sleep Questionnaire [33].

2.2. Study Population

The study was conducted at Jordan University Hospital (JUH) between August 2023 and April 2024. It involved 329 children with asthma who visited the respiratory clinics at JUH in Amman, Jordan. For each participant, clinical history, FeNO, PFT, and Asthma Control Test (ACT) scores were recorded. To ensure the stability and generalizability of the stepwise logistic regression model, the number of required sample size was based on the number of predictor variables as stated by the Events Per Variable (EPV) rule. As the final model included 6 predictors, the smallest group should include more than 60 children.

2.3. FeNo Device

Spirometry and FeNO assessments were conducted in accordance with established international guidelines to ensure accurate and reliable pulmonary function measurements. Spirometry was performed using a calibrated portable spirometer, strictly following the recommendations of the American Thoracic Society and the European Respiratory Society (ATS/ERS) for standardized lung function testing. Children were instructed to perform forced expiratory maneuvers after proper demonstration and practice. Multiple attempts were allowed to obtain at least three acceptable and reproducible curves, from which the highest values of FEV1 and FVC were recorded.
FeNO testing was conducted using the NObreath® device (Kent, United Kingdom), in line with ATS guidelines for clinical FeNO measurement. Prior to testing, children were asked to refrain from eating, drinking, or engaging in strenuous physical activity for at least one hour. The test required a steady exhalation at a constant flow rate and was repeated if the exhalation did not meet the required criteria. All assessments were conducted under the supervision of trained personnel to ensure proper technique and adherence to procedural protocols.

2.4. Asthma Control

The severity of asthma was evaluated based on medical history prior to FeNO measurement. The ACT was used to assess asthma control. It includes five questions that evaluate the frequency of shortness of breath, nighttime asthma symptoms, functional limitations, use of rescue medications, and the patient’s self-assessment of their asthma control. Each question offers five response options, scored from 1 to 5. Based on the total score, asthma control was categorized as follows: well-controlled (20–25), partially controlled (15–19), and uncontrolled (5–14). Additionally, we used the GINA criteria, which assess asthma severity based on four questions regarding symptoms over the past four weeks. These include: (1) having daytime symptoms more than twice per week, (2) any nighttime waking due to asthma, (3) use of a short-acting beta-agonist (SABA) more than twice per week, and (4) any activity limitation due to asthma.
For analysis purposes, each “yes” response was scored as 1 point and each “no” as 0. Scores were then classified as: well-controlled (0 points), partly controlled (1–2 points), and uncontrolled (3–4 points).

2.5. Ethical Considerations

The study was conducted in compliance with the Declaration of Helsinki. The study protocol and proposal were reviewed and approved by the Institutional Review Board (IRB) of Jordan University Hospital (IRB #10562-2023, 11 July 2023). Written informed consent was obtained from the parents or legal guardians of all study participants.

2.6. Statistical Analysis

Data analysis was conducted using SPSS version 26 IBM Corp., Armonk, NY, USA. Descriptive statistics were reported as medians and interquartile ranges (25–75 percentiles) for continuous variables, while categorical variables were summarized using frequencies and percentages.
Bivariate analysis was performed to assess the association between various independent variables and asthma control status. The chi-square test was used for categorical variables, the Mann–Whitney U test for non-parametric continuous variables, and the t-test for normally distributed continuous variables.
A forward stepwise binary logistic regression model was used to identify factors significantly associated with asthma control, as measured by the ACT. Variables with a p-value ≤ 0.20 in the bivariate analysis were included as predictors in the model. A p-value of < 0.05 was considered statistically significant.

3. Results

3.1. Sociodemographic Characteristics

Table 1 presents the sociodemographic characteristics of the 329 children with asthma included in the study. Fifty-nine percent were male, and the median age was 11 years (interquartile range: 9–13 years). Most children were born at term (91.2%), and 50.5% had a healthy weight status. More than half of the participants had a family history of asthma (56.8%) and had been previously hospitalized due to asthma (59%). Additionally, 74.5% of the children were diagnosed with obstructive sleep apnea (OSA), and the median duration since asthma diagnosis was 12 months (range: 2–48 months).
Table 1. Sociodemographic characteristics of the sample.

3.2. Comorbidities and Medication Use

Table 2 summarizes the comorbidities and medications reported by study participants. The majority had allergic rhinitis (67.2%), and 53% had suppurative lung disease (wet cough). Most children were using antihistamines (71.1%), and 50.5% had received oral steroids in the past year. Additionally, 57.1% of participants used short-acting beta-agonist (SABA) inhalers. About 26% of SABA users reported needing them 1 to 2 times per day during the last 7 days. Additionally, 45.9% of included participants used Fluticasone Propionate (i.e., Flixotide), which was the most commonly used inhaled corticosteroid/long-acting beta-agonist (ICS/LABA) medication.
Table 2. Comorbidities and medication use among study participants.
Table 3 presents the results of the medical tests conducted in this study. Based on ACT scores, 62.2% of children had uncontrolled asthma, while 42.6% had a positive skin prick test. The median FEV1% was 89.82 (interquartile range: 77.92–100.95), and the median FEV1/FVC ratio was 84% (77.2–91.1). The median FeNO level was 14 parts per billion (ppb), with a range of 9–26 ppb. Per ATS guidelines, the included cohort was distributed as follows: 62.9% (n = 207, FeNO < 20 [Low]), 19.5% (n = 64, 20 < FeNO < 35 [Middle]), and 17.6% (n = 58, FeNO > 35 [High]).
Table 3. Results of medical tests among study participants.

3.3. Factors Associated with Asthma Control

A stepwise binary logistic regression model was used to identify significant predictors of asthma control status (Table 4). Children without OSA had significantly higher odds of being in the controlled asthma group compared to those with OSA (OR = 4.825, 95% CI: 2.648–8.790, p < 0.001). Similarly, children without GERD (OR = 7.275, 95% CI: 1.277–41.437, p = 0.025), allergic rhinitis (OR = 1.750, 95% CI: 1.006–3.046, p = 0.048), or bronchiolitis obliterans (OR = 3.577, 95% CI: 1.947–6.573, p < 0.001) also had significantly greater odds of asthma control.
Table 4. Binary regression of the variables associated with participants’ asthma control (Uncontrolled vs. Controlled).
In addition, children who did not use antihistamines had increased odds of being in the controlled group (OR = 2.021, 95% CI: 1.142–3.575, p = 0.016). Finally, higher FeNO levels were associated with lower odds of asthma control (OR = 0.983, 95% CI: 0.970–0.997, p = 0.014).

4. Discussion

This study investigated asthma control and its determinants among children attending respiratory clinics at Jordan University Hospital. A high proportion (62.6%) had uncontrolled asthma, emphasizing the clinical burden and the importance of understanding contributing factors, as the main goal of asthma care is to achieve and maintain control [34]. The rate of uncontrolled asthma aligns with findings from Saudi Arabia (59–84%) [35], the US (46%) [36], and Southeast Nigeria (64.4%) [37], but contrasts with lower rates reported in other settings; 18% in another Nigerian centre [38], 31% in Ethiopia [39], and 40% in a multiethnic Dutch sample [40]. These differences may reflect variations in healthcare access, parental awareness, environmental exposures, asthma severity, and the tools used to assess control [40,41,42,43]. Consistent with previous studies, bronchial asthma was more prevalent in males under 14 years [44]; in our sample, 59% were boys. Although the reasons remain uncertain, genetic, environmental, and behavioural factors are likely involved.
As in prior research, comorbid conditions were strongly associated with poorer asthma control. OSA, present in 74.5% of our sample, significantly reduced the likelihood of asthma control. This differs from findings in a small US study of non-obese African American children (1.9% OSA prevalence), which reported no association [45]. GERD was also linked to poor control, likely due to reflux-related airway inflammation [46].
Allergic rhinitis, found in 67% of participants, is a well-established asthma comorbidity. It has been shown to worsen asthma symptoms, particularly when untreated [47]. In our study, its presence was significantly associated with uncontrolled asthma. This is consistent with research by Adams et al. [48], who found that over 22% of children with asthma also had both allergic rhinitis and eczema.
Bronchiolitis obliterans, identified in one-third of participants, was another significant factor. Prior studies have linked bronchiolitis in early childhood to subsequent asthma development and poor control [49,50]. Our findings support this association and highlight the long-term implications of early respiratory illness. Multiple reports indicate the overlapping clinical, functional, radiological, and atopic characteristics between bronchiolitis obliterans and asthma, which may lead to misdiagnosis and worse treatment outcomes [51,52]. In our cohort, both disease entities coexisted and were associated with poor asthma control. We believe that such relationship stems from similar pathological mechanisms, particularly those related to Th17 immune function, Regulatory T cells, and neutrophil dysfunction; all of which are commonly observed in both disease entities [53]. Similarly, pulmonary immune profiling demonstrated a link between suppurative lung disease and childhood wheezing [54]. Ruffles et al., demonstrated that among children affected with protracted bacterial bronchitis, the mildest manifestation of suppurative lung disease, about 25% developed asthma with two thirds demonstrated bronchodilator reversibility [55]. Immune phenomenon linking both disease entities include neutrophilic infiltration, elevated signatures of the IL-4/IL-13 pathways, and Th2 dysregulation [56].
Antihistamine use was associated with poorer asthma control in our sample. While antihistamines may improve outcomes in children with allergic asthma [57], they may be less effective, or even harmful, in those with non-allergic phenotypes, potentially increasing airway constriction and inflammation [58]. Nonetheless, the association between antihistamines and asthma in our cohort could be attributed to the confounding by indication bias due to the high rates of allergic rhinitis, which is also associated with antihistamine usage. Interestingly, the predictive value of antihistamines remained significant across all steps of the multivariate model; thus, indicating some form of statistical independence. As per the 2022 GINA guidelines, antihistamines are not considered as a viable management option for asthma and is only reserved for when it co-exists with other allergic comorbidities [59].
FeNO levels were another key factor. Children with elevated FeNO had significantly lower odds of asthma control. FeNO is a sensitive marker of eosinophilic inflammation and has been shown to predict exacerbations. Our findings are consistent with a Thai study, where children with higher FeNO and a history of exacerbations were more likely to experience future episodes [60].
Within the Jordanian healthcare context, FeNO could serve as a cost-effective non-invasive adjuvant diagnostic and monitoring measure for pediatric patients with asthma. While FeNO adds value to asthma assessment, its interpretation can be influenced by atopy, infections, and other variables [28,29]. Therefore, FeNO should complement—not replace—symptom-based tools such as the ACT and spirometry. Moreover, cut-off values should be psychometrically validated against a Jordanian normative data as current FeNO thresholds significant vary between guidelines (e.g., NICE, GINA, EPR-4) and are mostly influenced by the characteristics of the cohorts on which they were calculated [29].
The utility of FeNO is bound to a number of other technical and clinical challenges. Kim et al., demonstrated in their review that FeNO is sensitive to a number of factors including age, gender, race, smoking, and environmental pollution [61]. Moreover, changes in FeNO are not specific to a single atopic condition, let alone all phenotypes of asthma [62]. On the other hand, while the measurement of FeNO has standardized guidelines, younger pediatric patients (i.e., <5 years old) may not be as compliant.
Nevertheless, FeNO could be utilized in the diagnosis pathway of steroid-naïve pediatrics, of whom symptoms and signs after inconclusive after standard spirometry or bronchodilator reversibility testing [1]. However, the GINA 2024 report still considers FeNO as an inconclusive tool in terms of its diagnostic prowess [27]. Moreover, FeNO could be used as a measure of adherence to ICS therapy or during step-down decisions from ICS therapy [27]. FeNO could also be used to assess phenotypic eligibility and predict response for a number of biologic agents in cases of severe asthma [63].
In summary, this study reinforces the complexity of asthma control in children and the multifactorial nature of poor control. Comorbidities including OSA, GERD, allergic rhinitis, and bronchiolitis obliterans, as well as medication use (e.g., antihistamines) and elevated FeNO levels, were all associated with poorer outcomes. Our findings point to the importance of a tailored, multidisciplinary approach to asthma management in pediatric populations, especially in settings like Jordan, where local data have been limited.

Strengths, Limitations, and Future Directions

This study is among the first in Jordan to examine asthma control in children using both clinical assessments and validated symptom-based tools. Its strengths include a relatively large sample and detailed evaluation of comorbidities and medication use, which enhance the reliability of findings.
However, the cross-sectional design limits causal inference. We also lacked detailed data on medication adherence and duration, which may have influenced outcomes. Moreover, it hampered our ability to investigate the relationship between FeNO levels and level of adherence. FeNO levels can be affected by allergic sensitization, previous medications, infections, environmental factors, and demographic differences; all of which were not fully accounted for. Asthma control was established by the ACT tool. Despite its reliability, it is a subjective measure of control that could be influenced by parental bias or recall bias of older participants. Finally, as the study was conducted in a single tertiary centre, generalisability to broader pediatric populations, including those in primary care or rural settings, is limited.
Future research should use longitudinal, multicentre designs with more diverse samples to clarify causal relationships and improve external validity. Studies should also monitor medication use more closely and explore the biological pathways linking comorbidities such as OSA, GERD, and allergic rhinitis to asthma control.

5. Conclusions

This study found that higher FeNO levels were significantly associated with poorer asthma control in children, supporting its potential as a supplementary biomarker of airway inflammation. However, its clinical use remains limited due to variability and the influence of confounding factors.
Comorbid conditions such as OSA, GERD, allergic rhinitis, and bronchiolitis obliterans were also strongly linked to uncontrolled asthma. These findings highlight the importance of a comprehensive and multidisciplinary approach to asthma management. The association between antihistamine use and poor asthma control further suggests that treatment should be tailored to individual clinical profiles.
FeNO may be useful in identifying eosinophilic inflammation and guiding targeted therapy, but it should be used alongside, rather than instead of, established tools such as the ACT, GINA criteria, and spirometry. Its integration into routine care in Jordan could be beneficial if applied within a broader clinical context.
Overall, effective pediatric asthma management requires an individualized strategy that incorporates symptom assessment, clinical history, pulmonary function testing, and careful evaluation of comorbidities. Larger, longitudinal studies are needed to validate FeNO thresholds and clarify its predictive value for long-term outcomes.

Author Contributions

Conceptualization, E.A.-Z. and W.A.-Q.; methodology, W.A.-Q. and E.A.-Z.; formal analysis, W.A.-Q.; investigation, E.A.-Z., E.A., A.M.E., R.A., M.A.A., M.F.A.-W., F.F.A.-W., L.A.S.R., J.A.K. and M.A.-I.; data curation, E.A.-Z., E.A., A.M.E., R.A. and M.A.A.; writing—original draft preparation, M.F.A.-W., M.A.-I. and J.A.K.; writing—review and editing, J.E., A.H., and M.A.A.; supervision, E.A.-Z.; project administration, E.A.-Z.; validation, W.A.-Q. and E.A.-Z. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Researchers Supporting Project number (10562-2023), The University of Jordan, Amman, Jordan.

Institutional Review Board Statement

The study was conducted in compliance with the Declaration of Helsinki. The study protocol and proposal were reviewed and approved by the Institutional Review Board (IRB) of Jordan University Hospital (IRB #10562-2023, 11 July 2023).

Data Availability Statement

The dataset supporting the conclusions of this article is available in the Zenodo repository, https://doi.org/10.5281/zenodo.15294818.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Oh, J.; Kim, S.; Kim, M.S.; Abate, Y.H.; Abd ElHafeez, S.; Abdelkader, A.; Abdi, P.; Abdulah, D.M.; Aboagye, R.G.; Abolhassani, H.; et al. Global, regional, and national burden of asthma and atopic dermatitis, 1990–2021, and projections to 2050: A systematic analysis of the Global Burden of Disease Study 2021. Lancet Respir. Med. 2025, 13, 425–446. [Google Scholar] [CrossRef]
  2. Conrad, L.A.; Cabana, M.D.; Rastogi, D. Defining pediatric asthma: Phenotypes to endotypes and beyond. Pediatr. Res. 2021, 90, 45–51. [Google Scholar] [CrossRef] [PubMed]
  3. GBD 2021 Forecasting Collaborators. Burden of disease scenarios for 204 countries and territories, 2022–2050: A forecasting analysis for the Global Burden of Disease Study 2021. Lancet 2024, 403, 2204–2256. [Google Scholar] [CrossRef] [PubMed]
  4. Zhou, W.; Tang, J. Prevalence and risk factors for childhood asthma: A systematic review and meta-analysis. BMC Pediatr. 2025, 25, 50. [Google Scholar] [CrossRef] [PubMed]
  5. Al-sheyab, N.; Gallagher, R.; Crisp, J.; Shah, S. Peer-led education for adolescents with asthma in Jordan: A cluster-randomized controlled trial. Pediatrics 2012, 129, e106–e112. [Google Scholar] [CrossRef]
  6. Abuekteish, F.; Alwash, R.; Hassan, M.; Daoud, A.S. Prevalence of asthma and wheeze in primary school children in Northern Jordan. Ann. Trop. Paediatr. 1996, 16, 227–231. [Google Scholar] [CrossRef]
  7. Mims, J.W. Asthma: Definitions and pathophysiology. Int. Forum Allergy Rhinol. 2015, 5, S2–S6. [Google Scholar] [CrossRef]
  8. Pickard-Michels, T.; Adderley, N.J.; Nagakumar, P.; Simms-Williams, N.; Sitch, A.; Thayakaran, R.; Punyadasa, D.; Nirantharakumar, K.; Haroon, S. Association between mental health disorders and asthma exacerbations in adults: A retrospective cohort study in UK primary care. BMJ Open Respir. Res. 2025, 12, e003244. [Google Scholar] [CrossRef]
  9. Stridsman, C.; Martinsen, Ø.; Selberg, S.; Ödling, M.; Konradsen, J.R. Uncontrolled asthma in school-aged children-a nationwide specialist care study. J. Allergy Clin. Immunol. Glob. 2024, 3, 100227. [Google Scholar] [CrossRef]
  10. Centers for Disease Control and Prevention. Uncontrolled Asthma Among Children, 2012–2014. July 2019. Available online: https://archive.cdc.gov/www_cdc_gov/asthma/asthma_stats/uncontrolled-asthma-children.htm (accessed on 13 November 2025).
  11. Perry, R.; Braileanu, G.; Palmer, T.; Stevens, P. The Economic Burden of Pediatric Asthma in the United States: Literature Review of Current Evidence. Pharmacoeconomics 2019, 37, 155–167. [Google Scholar] [CrossRef]
  12. Wang, N. Sociodemographic Factors of Asthma Prevalence and Costs Among Children and Adolescents in the United States, 2016–2021. Prev. Chronic Dis. 2024, 21, 230449. Available online: https://www.cdc.gov/pcd/issues/2024/23_0449.htm (accessed on 2 December 2025).
  13. Hutter, N.; Knecht, A.; Baumeister, H. Health care costs in persons with asthma and comorbid mental disorders: A systematic review. General. Hosp. Psychiatry 2011, 33, 443–453. [Google Scholar] [CrossRef] [PubMed]
  14. Rhee, H.; Wenzel, J.; Steeves, R.H. Adolescents’ psychosocial experiences living with asthma: A focus group study. J. Pediatr. Health Care 2007, 21, 99–107. [Google Scholar] [CrossRef]
  15. Bender, B.G. Depression symptoms and substance abuse in adolescents with asthma. Ann. Allergy Asthma Immunol. 2007, 99, 319–324. [Google Scholar] [CrossRef] [PubMed]
  16. Almomani, B.A.; Mayyas, R.K.; Ekteish, F.A.; Ayoub, A.M.; Ababneh, M.A.; Alzoubi, S.A. The effectiveness of clinical pharmacist’s intervention in improving asthma care in children and adolescents: Randomized controlled study in Jordan. Patient Educ. Couns. 2017, 100, 728–735. [Google Scholar] [CrossRef] [PubMed]
  17. Okelo, S.O.; Wu, A.W.; Krishnan, J.A.; Rand, C.S.; Skinner, E.A.; Diette, G.B. Emotional quality-of-life and outcomes in adolescents with asthma. J. Pediatr. 2004, 145, 523–529. [Google Scholar] [CrossRef]
  18. Alefan, Q.; Nawasrah, A.; Almomani, B.; Al-Issa, E.T. Direct Medical Cost of Pediatric Asthma in Jordan: A Cost-of-Illness Retrospective Cohort Study. Value Health Reg. Issues 2022, 31, 10–17. [Google Scholar] [CrossRef]
  19. Pearce, C.J.; Fleming, L. Adherence to medication in children and adolescents with asthma: Methods for monitoring and intervention. Expert. Rev. Clin. Immunol. 2018, 14, 1055–1063. [Google Scholar] [CrossRef]
  20. Rogliani, P.; Laitano, R.; Ora, J.; Beasley, R.; Calzetta, L. Strength of association between comorbidities and asthma: A meta-analysis. Eur. Respir. Rev. 2023, 32, 220202. [Google Scholar] [CrossRef]
  21. Boulet, L.-P.; Boulay, M.-È. Asthma-related comorbidities. Expert. Rev. Respir. Med. 2011, 5, 377–393. [Google Scholar] [CrossRef]
  22. Jia, C.E.; Zhang, H.P.; Lv, Y.; Liang, R.; Jiang, Y.Q.; Powell, H.; Fu, J.J.; Wang, L.; Gibson, P.G.; Wang, G. The Asthma Control Test and Asthma Control Questionnaire for assessing asthma control: Systematic review and meta-analysis. J. Allergy Clin. Immunol. 2013, 131, 695–703. [Google Scholar] [CrossRef]
  23. Dinakar, C.; Chipps, B.E. Section on allergy and immunology, section on pediatric pulmonology and sleep medicine. Clinical Tools to Assess Asthma Control in Children. Pediatrics 2017, 139, e20163438. [Google Scholar] [CrossRef] [PubMed]
  24. Ben Saad, H.; El Attar, M.N.; Hadj Mabrouk, K.; Ben Abdelaziz, A.; Abdelghani, A.; Bousarssar, M.; Limam, K.; Maatoug, C.; Bouslah, H.; Charrada, A.; et al. The recent multi-ethnic global lung initiative 2012 (GLI2012) reference values don’t reflect contemporary adult’s North African spirometry. Respir. Med. 2013, 107, 2000–2008. [Google Scholar] [CrossRef] [PubMed]
  25. Bowerman, C.; Bhakta, N.R.; Brazzale, D.; Cooper, B.R.; Cooper, J.; Gochicoa-Rangel, L.; Haynes, J.; Kaminsky, D.A.; Lan, L.T.T.; Masekela, R.; et al. A Race-neutral Approach to the Interpretation of Lung Function Measurements. Am. J. Respir. Crit. Care Med. 2023, 207, 768–774. [Google Scholar] [CrossRef] [PubMed]
  26. Bime, C.; Nguyen, J.; Wise, R.A. Measures of asthma control. Curr. Opin. Pulm. Med. 2012, 18, 48–56. [Google Scholar] [CrossRef]
  27. Dweik, R.A.; Boggs, P.B.; Erzurum, S.C.; Irvin, C.G.; Leigh, M.W.; Lundberg, J.O.; Olin, A.-C.; Plummer, A.L.; Taylor, D.R. An Official ATS Clinical Practice Guideline: Interpretation of Exhaled Nitric Oxide Levels (FeNO) for Clinical Applications. Am. J. Respir. Crit. Care Med. 2011, 184, 602–615. [Google Scholar] [CrossRef]
  28. Alzayadneh, E.M.; Al Bdour, S.A.; Elayeh, E.R.; Ababneh, M.M.; Al-Ani, R.A.; Shatanawi, A.; Al-Iede, M.; Al-Zayadneh, E. Assessment of Fraction of Exhaled Nitric Oxide and Soluble Receptor for Advanced Glycation End Products Biomarkers for Jordanian Asthmatic Children. J. Asthma Allergy 2023, 16, 793–811. [Google Scholar] [CrossRef]
  29. Murugesan, N.; Saxena, D.; Dileep, A.; Adrish, M.; Hanania, N.A.; Murugesan, N.; Saxena, D.; Dileep, A.; Adrish, M.; Hanania, N.A. Update on the Role of FeNO in Asthma Management. Diagnostics 2023, 13, 1428. Available online: https://www.mdpi.com/2075-4418/13/8/1428 (accessed on 2 December 2025).
  30. Baraldi, E.; Dario, C.; Ongaro, R.; Scollo, M.; Azzolin, N.M.; Panza, N.; Paganini, N.; Zacchello, F. Exhaled nitric oxide concentrations during treatment of wheezing exacerbation in infants and young children. Am. J. Respir. Crit. Care Med. 1999, 159, 1284–1288. [Google Scholar] [CrossRef]
  31. Gao, Y.; Li, Z.; Wu, N.; Jiang, C.; Liu, Y.; Zhou, S.; Ning, A.; Li, S.; Chu, M.; Chang, Q. The change of FeNO is correlated with asthma control and lung function. Heliyon 2024, 10, e38875. [Google Scholar] [CrossRef]
  32. Celis-Preciado, C.A.; Lachapelle, P.; Couillard, S. Exhaled nitric oxide (FeNO): Bridging a knowledge gap in asthma diagnosis and treatment. Clin. Exp. Allergy 2023, 53, 791–793. [Google Scholar] [CrossRef]
  33. Umano, G.R.; Rondinelli, G.; Luciano, M.; Pennarella, A.; Aiello, F.; Mangoni di Santo Stefano, G.S.R.C.; Di Sessa, A.; Marzuillo, P.; Papparella, A.; Miraglia del Giudice, E. Pediatric Sleep Questionnaire Predicts Moderate-to-Severe Obstructive Sleep Apnea in Children and Adolescents with Obesity. Children 2022, 9, 1303. [Google Scholar] [CrossRef]
  34. Pavord, I.D.; Beasley, R.; Agusti, A.; Anderson, G.P.; Bel, E.; Brusselle, G.; Cullinan, P.; Custovic, A.; Ducharme, F.M.; Fahy, J.V.; et al. After asthma: Redefining airways diseases. Lancet 2018, 391, 350–400. [Google Scholar] [CrossRef] [PubMed]
  35. BinSaeed, A.A.; Torchyan, A.A.; Alsadhan, A.A.; Almidani, G.M.; Alsubaie, A.A.; Aldakhail, A.A.; AlRashed, A.A.; AlFawaz, M.A.; Alsaadi, M.M. Determinants of asthma control among children in Saudi Arabia. J. Asthma 2014, 51, 435–439. [Google Scholar] [CrossRef] [PubMed]
  36. Liu, A.H.; Gilsenan, A.W.; Stanford, R.H.; Lincourt, W.; Ziemiecki, R.; Ortega, H. Status of asthma control in pediatric primary care: Results from the pediatric Asthma Control Characteristics and Prevalence Survey Study (ACCESS). J. Pediatr. 2010, 157, 276–281.e3. [Google Scholar] [CrossRef] [PubMed]
  37. Gandhi, P.K.; Kenzik, K.M.; Thompson, L.A.; DeWalt, D.A.; Revicki, D.A.; Shenkman, E.A.; Huang, I.-C. Exploring factors influencing asthma control and asthma-specific health-related quality of life among children. Respir. Res. 2013, 14, 26. [Google Scholar] [CrossRef]
  38. Kuti, B.P.; Omole, K.O.; Kuti, D.K. Factors associated with childhood asthma control in a resource-poor center. J. Fam. Med. Prim. Care 2017, 6, 222–230. [Google Scholar] [CrossRef]
  39. Kasse, T.; Zenebe, S.; Agegnehu, Y.; Lonsako, A.A. Factors influencing health-related quality of life in children with asthma: Insights from Addis Ababa public hospitals. Front. Public. Health 2025, 12, 1478707. [Google Scholar] [CrossRef]
  40. Bloomberg, G.R.; Banister, C.; Sterkel, R.; Epstein, J.; Bruns, J.; Swerczek, L.; Wells, S.; Yan, Y.; Garbutt, J.M. Socioeconomic, family, and pediatric practice factors that affect level of asthma control. Pediatrics 2009, 123, 829–835. [Google Scholar] [CrossRef]
  41. van Dellen, Q.M.; Stronks, K.; Bindels, P.J.E.; Ory, F.G.; Bruil, J.; van Aalderen, W.M.C. PEACE Study Group Predictors of asthma control in children from different ethnic origins living in Amsterdam. Respir. Med. 2007, 101, 779–785. [Google Scholar] [CrossRef]
  42. Dick, S.; Doust, E.; Cowie, H.; Ayres, J.G.; Turner, S. Associations between environmental exposures and asthma control and exacerbations in young children: A systematic review. BMJ Open 2014, 4, e003827. [Google Scholar] [CrossRef]
  43. Chen, E.; Bloomberg, G.R.; Fisher, E.B., Jr.; Strunk, R.C. Predictors of repeat hospitalization in children with asthma: The role of psychosocial and socioenvironmental factors. Health Psychol. 2003, 22, 12–18. [Google Scholar] [CrossRef]
  44. Liao, M.-F.; Liao, M.-N.; Lin, S.-N.; Chen, J.-Y.; Huang, J.-L. Prevalence of allergic diseases of schoolchildren in central taiwan. From ISAAC surveys 5 years apart. J. Asthma 2009, 46, 541–545. [Google Scholar] [CrossRef] [PubMed]
  45. Rogers, V.E.; Bollinger, M.E.; Tulapurkar, M.E.; Zhu, S.; Hasday, J.D.; Pereira, K.D.; Scharf, S.M. Inflammation and asthma control in children with comorbid obstructive sleep apnea. Pediatr. Pulmonol. 2018, 53, 1200–1207. [Google Scholar] [CrossRef] [PubMed]
  46. Gaude, G.S. Pulmonary manifestations of gastroesophageal reflux disease. Ann. Thorac. Med. 2009, 4, 115–123. [Google Scholar] [CrossRef] [PubMed]
  47. Soto-Martínez, M.E.; Yock-Corrales, A.; Camacho-Badilla, K.; Abdallah, S.; Duggan, N.; Avila-Benedictis, L.; Romero, J.J.; Soto-Quirós, M.E. The current prevalence of asthma, allergic rhinitis, and eczema related symptoms in school-aged children in Costa Rica. J. Asthma 2019, 56, 360–368. [Google Scholar] [CrossRef]
  48. Adams, R.J.; Fuhlbrigge, A.; Finkelstein, J.A.; Lozano, P.; Livingston, J.M.; Weiss, K.B.; Weiss, S.T. Impact of inhaled antiinflammatory therapy on hospitalization and emergency department visits for children with asthma. Pediatrics 2001, 107, 706–711. [Google Scholar] [CrossRef]
  49. Azzari, C.; Baraldi, E.; Bonanni, P.; Bozzola, E.; Coscia, A.; Lanari, M.; Manzoni, P.; Mazzone, T.; Sandri, F.; Checcucci Lisi, G.; et al. Epidemiology and prevention of respiratory syncytial virus infections in children in Italy. Ital. J. Pediatr. 2021, 47, 198. [Google Scholar] [CrossRef]
  50. Binns, E.; Tuckerman, J.; Licciardi, P.V.; Wurzel, D. Respiratory syncytial virus, recurrent wheeze and asthma: A narrative review of pathophysiology, prevention and future directions. J. Paediatr. Child. Health 2022, 58, 1741–1746. [Google Scholar] [CrossRef]
  51. Mazenq, J.; Dubus, J.-C.; Chanez, P.; Gras, D. Post viral bronchiolitis obliterans in children: A rare and potentially devastating disease. Paediatr. Respir. Rev. 2024, 52, 58–65. [Google Scholar] [CrossRef]
  52. Pae, S.; Bastian, J.; Hoffman, H.; Ebbeling, W.; Lim, M. Bronchiolitis obliterans masquerading as severe persistent asthma in two children. J. Allergy Clin. Immunol. 2004, 113, S287. [Google Scholar] [CrossRef]
  53. Deng, K.; Lu, G. Immune dysregulation as a driver of bronchiolitis obliterans. Front. Immunol. 2024, 15, 1455009. Available online: https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2024.1455009/full (accessed on 2 December 2025). [CrossRef]
  54. Neeland, M.R.; Gubbels, L.; Wong, A.T.C.; Walker, H.; Ranganathan, S.C.; Shanthikumar, S. Pulmonary immune profiling reveals common inflammatory endotypes of childhood wheeze and suppurative lung disease. Mucosal Immunol. 2024, 17, 359–370. [Google Scholar] [CrossRef] [PubMed]
  55. Ruffles, T.J.C.; Marchant, J.M.; Masters, I.B.; Yerkovich, S.T.; Wurzel, D.F.; Gibson, P.G.; Busch, G.; Baines, K.J.; Simpson, J.L.; Smith-Vaughan, H.C.; et al. Outcomes of protracted bacterial bronchitis in children: A 5-year prospective cohort study. Respirology 2021, 26, 241–248. [Google Scholar] [CrossRef] [PubMed]
  56. Brusselle, G.G.; Koppelman, G.H. Biologic Therapies for Severe Asthma. New Engl. J. Med. 2022, 386, 157–171. [Google Scholar] [CrossRef] [PubMed]
  57. Yamauchi, K.; Ogasawara, M. The Role of Histamine in the Pathophysiology of Asthma and the Clinical Efficacy of Antihistamines in Asthma Therapy. Int. J. Mol. Sci. 2019, 20, 1733. [Google Scholar] [CrossRef]
  58. Yu, C.-L.; Huang, W.-T.; Wang, C.-M. Treatment of allergic rhinitis reduces acute asthma exacerbation risk among asthmatic children aged 2–18 years. J. Microbiol. Immunol. Infect. 2019, 52, 991–999. [Google Scholar] [CrossRef]
  59. Linton, S.; Hossenbaccus, L.; Ellis, A.K. Evidence-based use of antihistamines for treatment of allergic conditions. Ann. Allergy Asthma Immunol. 2023, 131, 412–420. [Google Scholar] [CrossRef]
  60. Visitsunthorn, N.; Mahawichit, N.; Maneechotesuwan, K. Association between levels of fractional exhaled nitric oxide and asthma exacerbations in Thai children. Respirology 2017, 22, 71–77. [Google Scholar] [CrossRef]
  61. Kim, H.-B.; Eckel, S.P.; Kim, J.H.; Gilliland, F.D. Exhaled NO: Determinants and Clinical Application in Children With Allergic Airway Disease. Allergy Asthma Immunol. Res. 2016, 8, 12–21. [Google Scholar] [CrossRef]
  62. Barański, K.; Zejda, J.E. Screening Accuracy of FeNO Measurement for Childhood Asthma in a Community Setting. Children 2022, 9, 858. [Google Scholar] [CrossRef]
  63. Menzies-Gow, A.; Mansur, A.H.; Brightling, C.E. Clinical utility of fractional exhaled nitric oxide in severe asthma management. Eur. Respir. J. 2020, 55, 1901633. Available online: https://publications.ersnet.org/content/erj/55/3/1901633 (accessed on 2 December 2025). [CrossRef]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Article Metrics

Citations

Article Access Statistics

Article metric data becomes available approximately 24 hours after publication online.