Next Article in Journal
Augmenting Patient Education in Hand Surgery—Evaluation of ChatGPT as an Informational Tool in Carpal Tunnel Syndrome
Previous Article in Journal
The Effect of HER2 Status on Gastric Cancer Survival and the Clinical Implications of the HER2-Low Definition: A Retrospective Study
Previous Article in Special Issue
Alternaria Allergy and Asthma in Children
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Medicina
Volume 61
Issue 9
10.3390/medicina61091676
medicina-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Aeroallergen IgE-Reactivity Patterns and Respiratory Allergy in Children and Adults: A Retrospective Study in 1711 Patients from the Central Poland Urban Area

by
Barbara Majkowska-Wojciechowska
*,
Maciej Kulma
and
Marcin Kurowski
*
Department of Immunology and Allergy, Medical University of Łódź, 90-419 Łódź, Poland
*
Authors to whom correspondence should be addressed.
Medicina 2025, 61(9), 1676; https://doi.org/10.3390/medicina61091676
Submission received: 14 July 2025 / Revised: 4 September 2025 / Accepted: 8 September 2025 / Published: 15 September 2025
(This article belongs to the Special Issue Chronic Respiratory Diseases: Updates on Pathophysiology, Symptoms, Diagnosis and Treatment)
Browse Figures
Versions Notes

Abstract

Background and Objectives: Effects of allergen exposure may be modified through endogenous and exogenous factors, resulting in heterogeneity of clinical features, time course and intensity of symptoms of allergic disease. This creates challenges in allergy diagnosis and management, yet studies addressing the variability of allergen reactivity in relation to potential modifying factors are not numerous. The aim of the study was to retrospectively analyze the frequency and profile of reactivity to inhalant allergen extracts in patients followed in a single center in the years 2017–2020, in relation to sex, age, clinical symptoms and final clinical diagnosis. Materials and Methods: This is a retrospective analysis of skin prick test (SPT) results in 1711 outpatients, performed with dust mites, pollen (alder, hazel, birch, grasses, rye, mugwort), cat, dog and Alternaria allergens. Reactivity profiles were assessed in the entire population divided into sex and age subgroups. Relationships between SPT results, age, sex and clinical diagnosis were assessed using factor analysis. Results: The highest reactivity frequencies were found for grass (60.5%), rye (57.22%), birch (47.34%), alder (42.5%) and Dermatophagoides pteronyssinus mites (41.8%). Monovalent reactivity was found mainly to mugwort (3.2%, n = 55), followed by cat and mites allergens. Reactivity to ≥1 allergen was more frequent in males. The risk of allergic rhinitis (AR) was significantly higher in subjects allergic to grass, rye, hazel and alder pollen, as compared to subjects non-sensitized to these allergens. Reactivity to perennial allergens (dog, cat and dust mites) was significantly associated with asthma diagnosis. The risk of developing atopic dermatitis was significantly associated with reactivity to birch and alder pollen. Conclusions: SPTs are a valuable tool for assessing the occurrence of atopy and allergy. Reactivity to specific aeroallergens may be associated with increased probability of development of a given atopic condition. This warrants further studies regarding the interplay between possible modifiers of allergen exposure effects.

1. Introduction

Allergies are common, non-infectious, chronic diseases affecting both children [1] and adults [2]. The growing number of respiratory diseases caused by inhaled allergens is a serious challenge for healthcare. Epidemiological studies indicate that about 40–50% of the world’s population suffers from one or more allergic disease [3,4]. Among them, allergic rhinitis (AR) is most frequent and considered a global health problem. AR can co-occur with other allergic manifestations, e.g., asthma or conjunctivitis, thereby significantly influencing different aspects of the daily quality of life [5,6]. A considerable diagnostic challenge may be encountered in cases of IgE-reactivity and allergic inflammation limited to local nasal mucosa with no ascertainable IgE’s, either in skin prick tests (SPTs) or in serum [7,8,9].
Multiple factors contributing to allergy pathogenesis and clearly differentiated clinical symptoms have already been identified. Although the relationship between allergic diseases and skin test results has already been investigated [10,11], in our opinion there is a lack of in-depth, detailed analyses of the number, spectrum and variability of sensitizing allergens and their relation to the sex and age of patients referred for allergy consultations. Therefore, we have decided to assess the distribution of the patterns of sensitizing allergens in the course of different allergic conditions. This cross-sectional, single-center study aimed to analyze the frequency of reactivity to allergens and its association with the presence of physician-diagnosed allergic disease in children and adults followed in an outpatient tertiary center.
The multinational ‘GAN’ Phase I study of the prevalence of rhinoconjunctivitis, asthma and eczema in children and adolescents in 25 countries showed a persistently high burden of these conditions and large differences in their prevalence between populations from different countries [12]. One of the most important risk factors for allergic rhinitis (AR) and asthma is IgE-dependent reactivity to one or more allergens [13].
Polish studies conducted in nine selected regions of the country indicate that the frequency of physician-diagnosed AR is 28.9%. The frequency of clinically confirmed asthma was 11.4% in children and 9.5% in adults [14]. In our previous study from Łódź and the Łódź Region (Central Poland), it was found that positive skin test results with at least one allergen from the standard airborne allergens panel were found in as many as 63.7% of urban children and 22.7% of children living in rural areas. At least one allergic disease was diagnosed in as many as 43.3% of urban children and 12.8% of rural children. Potential risk factors associated with the development of allergy differed significantly between urban and rural environments [15]. Clinical manifestations of allergy, their development, severity and progression result from the interplay of multiple factors, including maternal–fetal interactions, individual genetic and epigenetic status and environmental and ambient influence related to climate change, as well as dietary habits reflected in the microbiome [16,17,18,19].
Diagnosis of allergy is based on history taking, physical examination and diagnostic tests. During the diagnostic process, the use of appropriate tools to confirm IgE-dependent reactivity is necessary. Moreover, IgE-mediated reactivity results should be interpreted in the context of exposure to the presumed culprit allergen. Despite the broadening arsenal of molecular diagnostic tests, skin prick tests, which have a long history of utility in allergy practice, remain the core diagnostic tool in allergology, helpful in identifying environmental factors triggering allergy symptoms.
The use of standardized allergen extracts ensures reproducible results, as well as good specificity, sensitivity and low cost of testing. They also feature high safety with a low risk of systemic reactions. The results of skin tests usually show good correlation with the results of nasal, conjunctival, cutaneous, oral and bronchial provocations; however, in some cases discrepancies between symptoms’ history and seasonal presentation and the results of specific IgE measurement may pose a diagnostic challenge, as observed during allergic IgE-mediated reaction limited to local mucosa without systemic involvement [7,20]. SPTs (together with serum-specific IgE and basophil activation tests) may also be considered one of the tools helpful in predicting the clinical reaction upon exposure to allergen, thus contributing to increased safety and efficacy of allergy diagnosis [21,22,23,24]. In addition, complete allergy diagnosis with the use of SPTs and specific IgE to allergen components can be valuable in predicting response to allergen immunotherapy as well as in assessment of the clinical significance of given allergen in eliciting clinical symptoms of allergy [25,26,27,28,29,30,31].

2. Materials and Methods

2.1. Study Design and Location

This study is a retrospective analysis of the frequency and distribution of IgE-dependent reactivity to allergens included into a standard panel of inhalant allergen extracts used for initial diagnostic assessment of patients referred to a tertiary outpatient allergy center in Poland. The center is affiliated with the University Hospital in the third largest city of Poland in terms of number of inhabitants located in the center of the country. The city area is 293.3 km2 and the population, as of 30 June 2024, consisted of 645,700 inhabitants [32]. Data were further analyzed in relation to sex, age and final diagnoses, as established by an allergist and recorded in accordance with the ICD-10 classification [33]. The medical diagnoses considered in analyses included allergic rhinitis conjunctivitis, asthma, atopic dermatitis, chronic rhinitis, rhinopharyngitis, chronic sinusitis, nasal polyps, cough, urticaria, anaphylaxis and other unspecified. Data from patients with suspected allergies referred by primary physicians were screened for suitability. The analysis used data from the archived medical records of 1711 patients diagnosed and treated in the four-year period between 2017 and 2020. Patients attending the outpatient clinic were recruited, provided their respective medical records met the eligibility criteria, as listed below. No other specific selection criteria were employed. Criteria of data eligibility included detailed demographic description, complete description of symptoms’ history and results of skin prick testing with airborne allergens panel (see below). Patients whose medical records were analyzed were permanent residents of the city of Łódź or its urban agglomeration.

2.2. Skin Prick Tests

The IgE-reactivity profile was determines by skin prick tests using an allergen kit from Allergopharma (Reinbek bei Hamburg, Germany). The test panel included the following eleven extracts of inhalant allergens: house dust mites Dermatophagoides pteronyssinus and Dermatophagoides farinae, alder (Alnus glutinosa), hazel (Corylus avellana), birch (Betula verrucosa), grasses mix (Poaceae), rye (Secale cereale), mugwort (Artemisia vulgaris), cat (Felis domesticus), dog (Canis familiaris) and Alternaria alternata mold spores, along with positive (histamine) and negative (diluent) controls.
Selection of the eleven allergen extracts included in the study was mainly driven by local aerobiology, previous studies and availability of extracts. This panel of allergens is commonly used—with small variations—in most allergy centers in our country as the first-line diagnostic tool in the assessment of patients with a suspected respiratory allergy.
The SPT procedure was performed in accordance with the established guidelines [34]. Histamine dihydrochloride (10 mg/mL) was used as the positive control and the solvent of the extracts was the negative control. Wheal size of 3 mm or greater than the negative control was considered positive, as it is commonly accepted in allergy diagnosis recommendations [35,36].

2.3. Statistical Methods

Allergic sensitization profiles were assessed in all subjects and further analyzed in subgroups created basing on sex and age. Wheal diameters in SPTs with each allergen were considered initial explained variables. They were subsequently reduced to four independent principal components using factor analysis.
These served as explanatory variables for testing within the gender and age of the participants. Two-way analysis of variance was used for this purpose.
Generalized methods (binomial distribution with a linking logit function) were used to assess the differences between proportions in the prevalence of allergic rhinitis and allergic asthma by gender and age categories of subjects.
Wherever there were more than two comparisons, an appropriate correction was applied (e.g., Benjamini–Hochberg corrects). However, all comparisons concerning proportions (chi-square and generalized linear/non-linear methods) in the binomial distribution are equivalent to testing proportions, so there is no need to test odds ratios (ORs). Odds ratios (ORs)—where applicable—were estimated with confidence intervals.
Factor analysis was used to reduce the number of variables. Principal components were selected as factors. Eleven dependent variables (positive SPTs) were reduced to four independent factors: PC1, PC2, PC3 and PC4. These factors replaced the variables with which they are most strongly related through factor loadings. Factors were named according to factor loading values ≥ 0.7. This method of variable reduction does not result in a loss of explained variability. Another advantage of principal components is that they are independent of each other, which cannot be said for the original variables.
Statistical significance was assumed at the level of α = 0.05 and the confidence interval at the level of 0.95. In the case of more than two categories, the Benjamini–Hochberg post hoc test was performed using PQStat Software 2023 v1.8.6 (PQStat Software, Poznań, Poland). All other calculations were performed using Statistica 13.3 (StatSoft Polska, Kraków, Poland).
Chi-square tests were then performed between the disease entities determined by the allergists and the SPT results. Additionally, odds ratios with confidence intervals were calculated.

3. Results

3.1. Distribution of Sex and Age Groups

The studied population was characterized with the following sex and age distribution. Females accounted for 49% (n = 840) and males for 51% (n = 871) of patents. The mean age in the entire study group was 30.25 ± 6.95 years (age range: 2.57–86.42). The mean ages of males and females in the analyzed population were 27.90 ± 6.35 (age range: min.: 2.92; max.: 86.42) and 32.69 ± 17.2 (age range: min.: 2.57; max.: 77.97) years, respectively. Males were significantly more likely to be sensitized to grass pollen and house dust mites (Figure 1).
For further analysis, subjects were subdivided into three age subgroups, as presented in Table 1. The age distribution shows a predominance of patients aged 10 through 50 years, who constituted 74.81% of the group, followed by the age group 50 years and older, accounting for 14.1% of the studied population. Further details regarding the study group are provided in Table 1.

3.2. Reactivity Profiles in the Entire Study Group

The highest IgE-reactivity frequencies were observed in cases of allergens of grass, rye, birch and alder pollen, and of Dermatophagoides pteronyssinus mite. The lowest frequencies of reactivity were found for allergens of dog and Alternaria. A detailed summary of the frequency of reactivity profiles and average wheal diameter are presented in Figure 2.
Wheal diameters in SPTs were also higher with regard to allergens with which the SPT results were positive most frequently. In the entire study group, as shown in Figure 3, a significant positive correlation has been observed between the mean wheal diameter of positive SPTs with a given allergen extract and the percentage of positive SPT results with that allergen.

3.3. Monovalent and Polyvalent Reactivity

3.3.1. Monovalent Reactivity Profiles

Monovalent reactivity was found in 13.73% of the participants. As shown in Figure 4, the most common monovalent IgE-reactivity reactions in the entire study group were found in the following order: to mugwort pollen: 3.26% (n = 55) followed by cat allergens: 2.9% (n = 49) D. pteronyssinus mites. 1.84% (n = 31), grass pollen 1,48%, Alternaria 1,42%, birch pollen 1.12%, dog 0.95%, D. farinae mites 0,89% and alder pollen 0,006%. The number of monovalent reactivity was highest in age group II (10–50 years) and differed significantly from the remaining age groups (χ2. = 52.5, df = 1, p = 0.000001, OR = 3.16 (2.29–4.36). Distribution of monovalent reactivity among age groups is presented in Table 2.

3.3.2. Polyvalent Reactivity Profiles

As many as 98.7% of the studied population had one or more positive SPT results. Polyvalent reactivity to two or more allergen extracts was found in 86% of subjects. Most often, in 17.8% of subjects, two positive SPT results were ascertained. Reactivity to all eleven allergen extracts was found in 1% of patients (Figure 5).

3.4. Factor Analysis

Data reduction using factor analysis allowed for the extraction of four principal components (factors) described below, which were considered as explained variables.
  • Factor I was associated with positive SPT results to tree pollen extracts (alder, hazel, birch).
  • Factor II characterized allergy to mites (Dermatophagoides pteronyssinus and Dermatophagoides farinae).
  • Factor III was associated with allergies to grass pollen extracts: mix and rye.
  • Factor IV determined allergies to animal allergens: dog and cat.
Sex and age were considered as explanatory variables.
The four independent principal components identified in the factor analysis allowed us to conclude that the wheal diameters for grass/cereals and mites were higher in men (p < 0.0001). For mites, the largest wheal diameter was obtained in age group II (10–50 years). It was significantly different from age group I (<10 years (p = 0.0045) and age group III (>50 years) (p = 0.006). The results of the factor analysis are presented in Table 3 and Figure 6.

3.4.1. Testing of the Four Extracted Factors in Relation to Age, Sex and the Extracted Age Categories

Factor I—Allergy to Tree Pollen
The highest wheal diameters to tree pollen extracts were found in the age group 50+. They were significantly higher than in the youngest patients (p = 0.0048) than in the members of the age group 10–50 years (p = 0.000003). No significant differences were found in relation to the sex of the subjects (Figure S1).
Factor II—Allergy to House Dust Mites
For factor II, i.e., mite extracts, the highest reactivity rates were found in 10–50-year-olds. Statistically significant differences were noted with the youngest group (p = 0.045) and the oldest group (p = 0.016) (Figure S2A). Significantly higher values of wheal diameters were also noted in males (Figure S2B).
Factor III—Allergy to Grass and Rye Pollen
In cases of grass and rye pollen allergens, the highest value of wheal diameter was observed in age group II. Statistically significant differences occurred between all age categories: between category I and II (p = 0.0004); between II and III (p = 0.00002), and between I and III (p = 0.0026). Positive reactivity was significantly more frequent in men (p > 0000001) (Figure S3A,B).
Factor IV—Allergy to Pet Allergens
In cases of reactivity to pet allergens (dog/cat), the highest frequency was found for age category II (10–50-year-olds). Significant differences were obtained between age groups I and II, as well as II and III: p = 0.023 and p = 0.019, respectively. No significant differences were noted between the sexes (Figure S4).

3.5. Frequency of Clinical Diagnoses According to the ICD-10 Classification

From the archival patient charts, information was obtained that all patients included in the study were diagnosed with atopic diseases of atopic origin. These were allergic rhinitis, conjunctivitis, bronchial asthma and atopic dermatitis. Some patients were diagnosed with chronic rhinopharyngitis, chronic sinusitis, nasal polyps, cough, urticaria and other unspecified. The association of disease entities with the studied reactivity to specific inhalant allergens was estimated using the odds ratio (OR ± 95% CI). Detailed results are presented in Table S1.

3.6. Clinical Diagnoses in Relation to SPT Results

3.6.1. Allergic Rhinitis (AR)

In the study group, the chance of developing AR (J30) was more than three times higher in the case of grass allergy [OR = 3.24 (2.58–4.05), p < 0.000001] and more than two times with regard to rye, hazel and alder pollen allergens than in subjects without such reactivity.
It was found that the risk of allergic rhinitis had a significant relationship with reactivity to all extracts of inhalant allergens. It was most strongly associated with grass and rye pollen allergy, respectively, OR = 3.24 (2.58–4.05), p = 0.000001 and OR = 2.92 (2.33–3.65), p = 0.000001, followed by hazel pollen, OR = 2.26 (1.77–2.82), p = 0.000001, and alder, OR = 2.22 (1.75–2.82), p = 0.000001, as well as Alternaria, birch, cat and mites (Table S1). Regarding sex and age groups, AR diagnosis was significantly associated with male sex (Figure S5) and age group >50 years, as compared with the other age groups (Figure S6).

3.6.2. Asthma

The risk of developing asthma was associated to the highest extent with reactivity to allergens coming from dog (OR = 2.28 (1.75–2.98), p < 0.000001), cat (OR = 1.96 (1.60–2.41), p < 0.000001) and house dust mites (OR = 1.49 (1.21–1.82)). Regarding sex and age groups, asthma was significantly associated with female sex (Figure S5) and age groups 10–50 years and >50 years, as compared with the youngest group (Figure S6).

3.6.3. Other Atopic Conditions

The risk of the diagnosis of allergic conjunctivitis was associated with reactivity to hazel [OR = 1.86 (1.29–2.70); 0.0025], alder [OR = 1.86 (1.29–2.70)] and birch [OR = 1.54 (1.07–2.24)]. Regarding diagnosis of atopic dermatitis, its risk was highest in subject allergic to birch [(OR = 2.12 (1.36–3.25), p < 0.001) and alder (OR = 1.70 (1.11–2.60), p = 0.014)]. Negative associations between reactivity to different allergens and the risk of being diagnosed with a given condition were found with regard to chronic rhinopharyngitis (ICD-10: J31), chronic sinusitis (J32), nasal polyps (J33) and cough (R05). For example, in people with nasal polyps, the chance of being allergic to grasses was estimated to be four times lower than in people without polyps (Table S1). For ICD-10 codes, L50 (urticaria) and T78 (adverse effects, not elsewhere classified—which includes among others, anaphylactic shock, food hypersensitivity, different forms of angioedema and unspecified allergy), no significant associations were ascertained.

4. Discussion

In our retrospective study, we considered the results of skin prick tests and physicians’ diagnoses in 1711 patients referred by primary physicians due to suspected immediate-type allergy. It should be emphasized and taken into account that these data come from a tertiary clinic and, as such, may overrepresent more severe allergy cases compared to the general population. In this analysis, we looked at the SPT results from different perspectives. Our cross-sectional studies, based on medical records, indicate that using SPTs is a valuable first-line approach in the assessment of subjects with suspected allergy to airborne allergens. According to Szmyd et al. [37], there are strong positive correlations between positive SPT results and serum-specific IgE concentrations, which allows for the diagnosis of inhalant allergy in 95% of cases. In addition, SPT results show good correlation with the results of nasal, conjunctival and other provocation tests [38].
In our group, the high prevalence of reactivity to pollen extracts, mainly grasses and rye, is quite surprising. In previous studies from our city and province, the highest frequency of reactivity was seen with regard to house dust mites, both in urban and rural pediatric populations. Similar results were also obtained by other researchers from our country. The highest prevalence of dust mite reactivity was found in studies of children and adults from the city of Krakow and among adult patients from the city of Bydgoszcz and the surrounding area [39,40]. Additionally, in patients with AD, the most common positive SPT result was observed during testing with D. pteronyssinus and D. farinae, while reactivity to grasses was the third most frequently ascertained [41]. It is suspected that such discrepancies result from differences in the recruitment of the studied groups. Diagnostic screening studies and epidemiological studies show, however, a high degree of repeatability [42].
The allergic reactivity profiles observed in this study indicate the greatest significance of grass pollen allergens in causing IgE-reactivity in the population of central Poland. These results are consistent with the results of the nationwide ECAP study conducted in the general population, where grass pollen allergens were shown to be the clinically most important group of aeroallergens in Poland. In the ECAP study, it was found that 21% of participants had positive SPTs to grass extracts, and 16% of them reported suggestive symptoms during the pollen season [43]. The Poaceae (grass) pollen seems to increase its expansiveness and is currently considered to be the leading biological pollutant in atmospheric air and the main cause of pollen allergy in Europe and the world [44,45]. The grass allergens described so far (13 groups) have been divided into water-insoluble ones, which seem to play a role in the centrally mediated inflammatory response, and water-soluble allergens, which are probably involved in the peripheral humoral response [46,47]. Pollen NADPH oxidase (which induces pollen tube growth) has also been shown to have a pro-inflammatory effect, independent of adaptive immune responses [48]. Animal studies have shown that activation of pollen NADPH affects the generation of reactive oxygen species and played an important role in the pathogenesis of allergy [49]. Additionally, air pollution and other biotic (e.g., microorganisms and viruses) and abiotic factors may influence pollen allergenicity. For example, they may contribute to oxidative stress, both to pollen and to human epithelial cells, which may promote allergy to grass and other plant pollen [50]. It has also been shown that pollen lipids can be internalized by dendritic cells presented by CD1 to NKT cells, which release IL-4 and promote the differentiation of Th0 lymphocytes into Th2 cells [51].
In addition, the allergen extracts used during SPTs contain proteins that have not yet been characterized, and so far we do not have the ability to assess their reactivity with IgE from patient sera. For example, recent proteomic analyses indicate the presence of up to 3000 newly identified proteins for each pollen taxon, which may contribute to their different allergenic potential [52].

4.1. Monovalent Reactivity

It is interesting that the most common monovalent reactivity was found to mugwort extract (Artemisia), with a general frequency of reactivity of 3.2% in the entire study group. Mugwort is a common plant in Poland, blooming from July to September, together with grasses and other weeds [53,54,55,56], which complicates management of allergy with reactivity to this taxon. The participation of mugwort pollen in the aeroplankton of the atmospheric air in our city has never been high during more than 20 years of pollen monitoring. Its influence on the development of IgE-reactivity has not been analyzed in more detail either. However, reports from Asian countries indicate that mugwort pollen allergens are considered clinically significant in the context of allergic disease development. For example, the frequency of reactivity to mugwort in northern China was estimated at 26–48% [57,58]. So far, seven potential mugwort pollen allergens with IgE binding ability have been identified [59]. The high cross-reactivity of mugwort allergens is also known. Available studies show that some allergen components of mugwort and ragweed may be mutually cross-reactive (e.g., Art v 1 with Amb a 4 and Art v 4 with Amb a 8) [60,61]. Aerobiological studies conducted in our city have indicated generally low exposure to ragweed pollen, which comes from long-distance transport, mainly from southern and eastern Europe, and showed that the pollen seasons for mugwort and ragweed are separated [55,62]. It may, therefore, be speculated that, in our region, reactivity to the Art v 1 mugwort pollen component can be a proverbial Trojan horse that would promote reactivity to the Amb a 4 ragweed pollen component.
In our population, we have identified a notable difference between the amount of monoreactivity to D. farinae and D. pteronyssinus mites. Considering the fact that allergens coming from these mites are highly cross-reactive, this difference may seem unexpected and discrepant. We can, however, speculate that it is associated with the influence of external factors (e.g., housing conditions and some biotic and abiotic indoor factors, including humidity, temperature and presence of microscopic fungi) upon the composition of the local acarofauna [63]. Our unpublished research shows that D. pteronyssinus is represented to a higher extent in the house dust samples collected in our city’s apartments, compared to D. farinae. Other published data [64] show that in Poland, generally, older buildings and furnaces are more conducive to the presence of D. pteronyssinus, while new buildings with central heating systems are more favorable milieu for D. farinae. Nevertheless, in our city D. pteronyssinus mites were the dominant taxon. One may, therefore, assume that the rate of specific IgE-reactivity to either house dust mite can be associated with the level of exposure and reflect features of local acarofauna resulting from housing conditions and external modifying factors, as mentioned above.
Employing only skin prick testing to allergen extracts, and not the assessment of reactivity to allergen components, may be considered a limitation of the study. At the time when the patients had been assessed, component-resolved diagnostics was much less common and accessible in routine diagnostic management; therefore, the number of performed assessments of the levels of IgE specific to allergen components was not considerable and could not be subject to extensive analysis. Basing the assessment of mono- and polyreactivity solely on SPT positivity leaves out possible cross-reactivity between allergenic components belonging to the same groups and represented in different allergen sources, such as trees and furry animals. (e.g., PR-10, profilins, lipocalins). In this context, it should be taken into account that IgE-reactivity to alder and hazel allergen extracts may be in large part due to cross-reactivity of their allergens with birch allergens, whereas the majority of subjects apparently allergic to hazel and/or alder are, in fact, primarily reactive to birch pollen.
Cross-reactivity as a plausible explanation of apparent polysensitization to tree allergens is further supported by significant gamma-correlations between the compared frequencies of positive SPTs to alder and hazel, alder and birch and birch and hazel pollen (p < 0.00001). However, with regard to mugwort pollen, a very weak correlation was found between the number of positive SPTs with mugwort and the number of positive SPT results with all of the trees present in the allergens panel. Results of the additional gamma-correlation analysis between positive SPTs with extracts of potentially cross-reactive allergen sources are presented in the Supplementary Material as Table S2.
This issue requires a broadened and deepened separate analysis. Considering this, patient diagnostics should be enriched with an assessment of clinical significance, molecular studies and determination of possible cross-reactions.

4.2. Reactivity and Age

The division into three age groups made in this study showed heterogeneity in the allergy profiles. Surprisingly, the identification of three age clusters showed that in subjects aged over 50, the highest frequencies of allergies to grass and rye were observed. This is difficult to explain using known immunological mechanisms. Several studies show that in senior age groups a progressive loss of the ability to respond to antigen stimulation as well as immune dysfunction are observed [65,66].

4.3. Atopy and Sex

In our study, the frequency of one or more positive SPT responses was higher among males compared to females in each decade of life. This contrast suggests that factors other than type I hypersensitivity reactions are responsible for the differences. Numerous scientific studies have analyzed multidimensional immunological and inflammatory mechanisms. Sex differences can manifest themselves at different levels, mainly genetic, anatomical and endocrine. Many researchers emphasize that sex hormones, such as estrogen and testosterone, can affect respiratory diseases [67,68], but their effects are multifactorial, e.g., dependent on age, menopause, obesity, stage of the menstrual cycle, etc. It is known that sex hormones mediate cellular and humoral immune pathways and may partially explain the increased frequency of inflammation in women compared to men. Studies indicate that estrogen may contribute to airway inflammation in women with asthma, while testosterone may have a protective effect in men [69].
In the National Health and Nutrition Examination Survey (NHANES), serum testosterone levels were found to be inversely associated with the risk of developing current asthma in both sexes [70]. In males, it was reported that each 1-unit increase in testosterone levels reduced the odds of developing asthma by 11%. In general, testosterone in men may reduce Th2 airway inflammation by reducing IL-13 expression and eosinophil infiltration in the airways [71].

4.4. SPT Results and Allergic Diseases

It should be emphasized that reactivity to hazel, alder and birch pollen is positively associated with conjunctivitis. In the context of newer studies, the eye cannot be neglected or omitted in the context of allergic diseases and conjunctival symptoms, as a complication of allergic rhinitis should be given more recognition. It was found that proteases from hazel and birch pollen, as well as the grains of other taxa, can induce both IgE-dependent and IgE-independent reactions [72]. They can contribute to the decomposition of tear fluid proteins and damage to the epithelial cells, in particular in polluted urban environments [73].
It is believed that the development of allergies may be influenced by various exogenous—mainly environmental—factors, e.g., progressive urbanization, lifestyle changes, increased exposure to air pollution and allergens [74]. Our previous studies show that exposure to pollen seems to be of particular importance in already sensitized subjects. However, it must be underlined that clinical symptoms mainly occur when the level of exposure exceeds the individual threshold level. Additional factors may also contribute to the development of allergy symptoms. For example, Olivieri et al. [75] showed interactions between atopy, seasonal exposure to pollen, and FeNO, total IgE and FEV1/FVC levels, which were of a dose-response nature.
Our studies show that the risk of allergic rhinitis, conjunctivitis and atopic eczema was strongly associated with reactivity to pollen of locally flowering plants. Although seasonal exposure to birch pollen in our region is almost twice as high, but shorter in duration than grass pollen (unpublished data), grass and rye allergens turned out to be the most aggressive, more often promoting allergy symptoms in our group.
In parallel to diagnostic and epidemiological studies, our center conducts aerobiological studies in the city center. The main grass pollen season in Poland lasts about 80–90 days between the end of May, throughout June until mid-July. Data from the years 2003–2024 indicate a significant increase in grass pollen concentrations over a more than twenty-year period (p = 0.045; r2 = 0.186; unpublished data), while birch pollen concentrations show two-year fluctuations, but without a significant increase in concentrations over the last 22 seasons.
A recent study by Klangkalya et al. [76] indicated that, in children, only the cut-off value of the wheal in SPTs of 6.6 mm provided 100% specificity for predicting AR induced by HDM. However, in our work, the wheal size criterion of the positive SPT result was assumed at ≥3 mm. Perhaps in future studies different values may be used as criteria for analyses.
It should again be emphasized that the risk of developing allergies depends on many factors, including genetic, epigenetic, prenatal, perinatal and environmental ones, and their mutual interactions [15,77]. Growing up in a polluted urban environment confers an increased risk of developing allergies in early childhood. In our previous studies, differences in the frequency of allergies in children were found depending on the region of residence within the same city. They were significantly higher in the downtown district compared to districts located far from the city center [78]. Similar findings, i.e., differences in pediatric asthma incidence between districts of the same town differing in terms of proximity to industrial facilities, have recently been described in another region of Poland [79].
In addition, the results of the study by Stelmach et al. [80], conducted in our city among children living in an orphanage, indicated a low frequency of atopy (12.5% positive SPT) and atopic diseases. For example, seasonal allergic rhinitis was found in only 2.5% (3 out of 120) of children. Similarly, in children living in foster care homes the presence of atopic diseases was observed in 11.3%, which is almost half as many as in the control population, in children living with their parents (26%), despite the fact that all children came from the same area of the city. The authors suggest that exceptionally difficult living conditions and multiple infections in early childhood may lead to lower reactivity in later life [81].
In our study, we have not addressed or interpreted the data on symptoms occurring upon exposure to allergens. Similarly, the severity of symptoms of allergic disease has not been interpreted in the exposure or SPT result context. This study focused on the association between IgE-reactivity and the presence of diagnosis of given condition, as per available medical records. Such an approach, i.e., based on the presence of given diagnosis in medical records, always bears the possibility of bias or error. However, retrospective data from large populations are likely to be recorded in a non-standardized manner, unless a uniform scheme of their collection is established beforehand. This was not the case here, which should be considered as a factor influencing further clinical interpretation of these data.

5. Conclusions

Our study is representative of the urban population of central Poland and offers a platform for the assessment of the relationships between IgE-reactivity and allergic disease. Identification of sensitizing allergens, i.e., exposure risk factors for the development of symptoms, is crucial for allergy diagnostics. Reactivity profiles determined using a basic panel of skin tests may vary depending on sex, age groups and individual disease entities of allergic origin. The results of our study can serve as an objective reference to the frequency of allergen occurrence in the urban environment in central Poland, but also in similar climate and geographical conditions. Accurate diagnosis combined with optimal therapy requires the use of appropriate tests confirming allergen reactivity and obtaining detailed information on exposure to the presumed culprit allergen.
The results of this study can, therefore, be summarized in the following main points:
  • According to the results of SPTs, the most important sensitizing allergens in allergic subjects in central Poland were the pollen from grass (60.5%), rye (57.22%) and birch (47.34%).
  • The most common monovalent reactivity found was that to mugwort pollen.
  • The frequency of one or more positive SPT results was higher among males.
  • The age distribution shows the highest reactivity of allergies in the age group 10–50 years, with male predominance
  • In patients with clinically diagnosed AR, the probability of developing symptoms was higher in those sensitized to grass pollen, rye, alder, hazel, Alternaria, birch, cat, D. pteronyssinus and D. farinae allergens.
  • Higher odds of developing asthma were associated with positive SPT results with dog, cat and dust mite allergens.
  • Higher odds of developing atopic dermatitis were associated with positive SPT results with birch and alder pollen allergens.
  • Higher odds of developing allergic conjunctivitis were associated with positive SPT results with alder, hazel and birch pollen allergens.
Due to the high prevalence of allergic diseases in Poland and worldwide, there is an urgent need to study the spectra of reactivity and their relationship with allergy. Identification of the most frequent reactivity profiles associated with target-organ manifestations of allergic disease in a given geographical area may provide valuable descriptive data with regard to a description of clinical phenotypes of allergy. Trends in the prevalence of reactivity to specific allergens depending on age and physician-diagnosed allergic disease in Poland have rarely been studied in both children and adults. Our research focuses on the reactivity profiles in individual allergic diseases, as well as age- and sex-related differences in patients diagnosed and treated in an outpatient allergy clinic. In this context, it adds to the current state of knowledge on the epidemiology and distribution of reactivity to the most common airborne allergens in Central Europe. Further studies in this geographical area are needed in order to cover a broader spectrum of reactivity and to analyze possible variations and fluctuations in allergen reactivity profiles over longer periods. This aspect of studies on allergen reactivity profiles deserves particular recognition in the light of climate changes, which may affect the extent and patterns of exposure to seasonal airborne allergens. We can foresee that climate change-associated shifts in the IgE-reactivity profile extended over longer periods may incur modifications in recommended immunotherapy schemes and enforce changes in routine diagnostic work-up with regard to allergen reactivity assessed through SPT and serum-specific IgE concentrations.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/medicina61091676/s1, Figure S1. Comparison of variance in mean wheal size between age categories with regard to tree (birch, hazel, alder) pollen allergens sensitization (Factor I). * p = 0.0048; ** p = 0.00003. Figure S2. Comparison of variance in mean wheal size in SPTs with house dust mites (D. pteronyssinus, D. farinae) allergens between age groups (panel A) and sexes (panel B); * p = 0.045; ** p = 0.016; *** p = 0.00008. Figure S3. Comparison of variance in mean wheal size in SPT with grass pollen allergens between age groups (panel A) and sexes (panel B); * p = 0.026; ** p = 0.0004; *** p = 0.00002; **** p = 0.00000005. Figure S4. Comparison of variance in mean wheal size in SPTs with cat and dog allergens (Factor IV) between age groups. * p = 0.023; ** p = 0.019. Figure S5: Differences between proportions in the prevalence of allergic rhinitis and asthma by sex categories of subjects. Figure S6. Differences between proportions in the prevalence of allergic rhinitis and asthma by age categories of subjects. Table S1. Associations between physician-diagnosed allergic/atopic conditions (as retrieved from archival patients’ charts) and allergic sensitization ascertained by skin prick tests (SPTs). Table S2. Gamma correlations for compared frequencies of positive SPT results (positive result defined as a wheal ≥3 mm diameter).

Author Contributions

Conceptualization, B.M.-W. and M.K. (Maciej Kulma); methodology, B.M.-W.; formal analysis, B.M.-W.; investigation, B.M.-W.; data curation, B.M.-W., M.K. (Maciej Kulma) and M.K. (Marcin Kurowski); writing—original draft preparation, B.M.-W. and M.K. (Maciej Kulma); writing—review and editing, B.M.-W. and M.K. (Marcin Kurowski); supervision, B.M.-W.; All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

In accordance with the following laws of the Republic of Poland, (1) Act on the Profession of Medical Doctor and Dentist announced 5 December 1996 (Journal of Laws of the Republic of Poland 2024 no. 1287); (2) Regulation of the Minister of Health of 26 January 2023, on the Bioethics Committee and the Appeals Bioethics Committee 1996 (Journal of Laws of the Republic of Poland 2023 no. 218), retrospective studies of past medical records are not considered medical experiments involving human subjects and, as such, do not require assessment and approval from the bioethics committee. Approval for the analysis of retrospective patient data was obtained from the university hospital management, as per internal procedures.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available upon reasonable request from the corresponding author (B.M.-W.).

Acknowledgments

The authors would like to acknowledge Zbigniew Wojciechowski for his contribution and help with statistical analysis of data.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
SPTSkin prick test
ARAllergic rhinitis
ICD-10International Statistical Classification of Diseases and Related Health Problems, Tenth Revision
NADPHNicotinamide Adenine Dinucleotide Phosphate
OROdds ratio
CI Confidence interval
ILInterleukin
HDMHouse dust mite(s)
FeNOFractional exhaled nitric oxide
FEV1Forced expiratory volume in one second
FVCForced vital capacity

References

  1. Rezwan, T.; Perez, M.; Jacobs, S.; Shafik, J.; Mitchell, W.B.; Conrad, L.A.; Soshnick, S.H. Correlation between Total IgE Level and Asthma Symptom Severity in Hospitalized Children. J. Allergy Clin. Immunol. Glob. 2025, 4, 100452. [Google Scholar] [CrossRef]
  2. Scelo, G.; Torres-Duque, C.A.; Maspero, J.; Tran, T.N.; Murray, R.; Martin, N.; Menzies-Gow, A.N.; Hew, M.; Peters, M.J.; Gibson, P.G.; et al. Analysis of Comorbidities and Multimorbidity in Adult Patients in the International Severe Asthma Registry. Ann. Allergy Asthma Immunol. 2024, 132, 42–53. [Google Scholar] [CrossRef]
  3. Wang, H.; Li, X.-B.; Chu, X.-J.; Cao, N.-W.; Wu, H.; Huang, R.-G.; Li, B.-Z.; Ye, D.-Q. Ambient Air Pollutants Increase the Risk of Immunoglobulin E–Mediated Allergic Diseases: A Systematic Review and Meta-Analysis. Environ. Sci. Pollut. Res. 2022, 29, 49534–49552. [Google Scholar] [CrossRef]
  4. Guo, Y.; Cai, S.; Deng, J.; Li, J.; Qiu, L.; Sun, Q.; Cui, Y.; Li, L.; Yu, L.; Yin, H.; et al. Trends and Hotspots of Acupuncture for Allergic Rhinitis: A Bibliometric Analysis from 2002 to 2022. Complement. Ther. Med. 2023, 78, 102984. [Google Scholar] [CrossRef]
  5. Cingi, C.; Gevaert, P.; Mösges, R.; Rondon, C.; Hox, V.; Rudenko, M.; Muluk, N.B.; Scadding, G.; Manole, F.; Hupin, C.; et al. Multi-Morbidities of Allergic Rhinitis in Adults: European Academy of Allergy and Clinical Immunology Task Force Report. Clin. Transl. Allergy 2017, 7, 17. [Google Scholar] [CrossRef]
  6. Seys, S.F.; Quirce, S.; Agache, I.; Akdis, C.A.; Alvaro-Lozano, M.; Antolín-Amérigo, D.; Bjermer, L.; Bobolea, I.; Bonini, M.; Bossios, A.; et al. Severe Asthma: Entering an Era of New Concepts and Emerging Therapies: Highlights of the 4th International Severe Asthma Forum, Madrid, 2018. Allergy 2019, 74, 2244–2248. [Google Scholar] [CrossRef] [PubMed]
  7. Mortada, M.M.; Kurowski, M. Challenges in Local Allergic Rhinitis Diagnosis, Management, and Research: Current Concepts and Future Perspectives. Medicina 2023, 59, 929. [Google Scholar] [CrossRef]
  8. Krzych-Fałta, E.; Wojas, O. Local Allergic Rhinitis or Local Allergic Conjunctivitis? Alergol. Pol. Pol. J. Allergol. 2023, 10, 310–314. [Google Scholar] [CrossRef]
  9. Berghi, O.; Dumitru, M.; Cergan, R.; Musat, G.; Serboiu, C.; Vrinceanu, D. Local Allergic Rhinitis—A Challenge for Allergology and Otorhinolaryngology Cooperation (Scoping Review). Life 2024, 14, 965. [Google Scholar] [CrossRef] [PubMed]
  10. Testera-Montes, A.; Jurado, R.; Salas, M.; Eguiluz-Gracia, I.; Mayorga, C. Diagnostic Tools in Allergic Rhinitis. Front. Allergy 2021, 2, 721851. [Google Scholar] [CrossRef]
  11. Riggioni, C.; Ricci, C.; Moya, B.; Wong, D.; Van Goor, E.; Bartha, I.; Buyuktiryaki, B.; Giovannini, M.; Jayasinghe, S.; Jaumdally, H.; et al. Systematic Review and Meta-analyses on the Accuracy of Diagnostic Tests for IgE-mediated Food Allergy. Allergy 2024, 79, 324–352. [Google Scholar] [CrossRef]
  12. García-Marcos, L.; Asher, M.I.; Pearce, N.; Ellwood, E.; Bissell, K.; Chiang, C.-Y.; El Sony, A.; Ellwood, P.; Marks, G.B.; Mortimer, K.; et al. The Burden of Asthma, Hay Fever and Eczema in Children in 25 Countries: GAN Phase I Study. Eur. Respir. J. 2022, 60, 2102866. [Google Scholar] [CrossRef] [PubMed]
  13. Romano, M.R.; James, S.; Farrington, E.; Perry, R.; Elliott, L. The Impact of Perennial Allergic Rhinitis with/without Allergic Asthma on Sleep, Work and Activity Level. Allergy Asthma Clin. Immunol. 2019, 15, 81. [Google Scholar] [CrossRef]
  14. Krzych-Fałta, E.; Wojas, O.; Raciborski, F.; Furmańczyk, K.; Chrzanowska, M.; Samoliński, B.; Lipiec, A.; Piekarska, B.; Gujski, M. Specificity and Sensitivity of Questionnaires in the Diagnosis of Allergic Diseases. Adv. Dermatol. Allergol. 2024, 41, 594–603. [Google Scholar] [CrossRef]
  15. Majkowska-Wojciechowska, B.; Pełka, J.; Korzon, L.; Kozłowska, A.; Kaczała, M.; Jarzebska, M.; Gwardys, T.; Kowalski, M.L. Prevalence of Allergy, Patterns of Allergic Sensitization and Allergy Risk Factors in Rural and Urban Children. Allergy 2007, 62, 1044–1050. [Google Scholar] [CrossRef] [PubMed]
  16. Pereira, R.N.; Rodrigues, R.M.; Madalena, D.A.; Vicente, A. Tackling Food Allergens—The Role of Food Processing on Proteins’ Allergenicity. In Advances in Food and Nutrition Research; Elsevier: Amsterdam, The Netherlands, 2023; Volume 106, pp. 317–351. ISBN 978-0-443-19304-0. [Google Scholar]
  17. Aldakheel, F.M. Allergic Diseases: A Comprehensive Review on Risk Factors, Immunological Mechanisms, Link with COVID-19, Potential Treatments, and Role of Allergen Bioinformatics. Int. J. Environ. Res. Public Health 2021, 18, 12105. [Google Scholar] [CrossRef] [PubMed]
  18. Finn, P.W.; Perkins, D.L. Born to Wheeze or Learned When We Were Young: Maternal and Environmental Factors Influence Atopic Risk. Trans. Am. Clin. Climatol. Assoc. 2023, 133, 181–192. [Google Scholar]
  19. Fujimura, K.E.; Sitarik, A.R.; Havstad, S.; Lin, D.L.; Levan, S.; Fadrosh, D.; Panzer, A.R.; LaMere, B.; Rackaityte, E.; Lukacs, N.W.; et al. Neonatal Gut Microbiota Associates with Childhood Multisensitized Atopy and T Cell Differentiation. Nat. Med. 2016, 22, 1187–1191. [Google Scholar] [CrossRef]
  20. Wang, H.; Jiang, X.; Zhang, P.; Li, Y.; Wang, Y.; Li, X. Allergen-Specific IgE in the Tear Fluid of Chinese Patients with Common Allergic Conjunctivitis in Autumn and Winter. Int. Ophthalmol. 2023, 43, 4541–4549. [Google Scholar] [CrossRef]
  21. Satnarine, T.; Makkoukdji, N.; Pundit, V.; Vignau, A.; Sharma, P.; Warren, D.; Kleiner, G.; Gans, M. Peanut Allergy Diagnosis: Current Practices, Emerging Technologies, and Future Directions. Allergies 2025, 5, 4. [Google Scholar] [CrossRef]
  22. Haidar, L.; Bănărescu, C.F.; Uța, C.; Moldovan, S.I.; Zimbru, E.-L.; Zimbru, R.-I.; Ciurariu, E.; Georgescu, M.; Panaitescu, C. Pollen–Food Allergy Syndrome: Allergens, Clinical Insights, Diagnostic and Therapeutic Challenges. Appl. Sci. 2024, 15, 66. [Google Scholar] [CrossRef]
  23. Gawryjołek, J.; Krogulska, A. Diagnostics of Peanut Allergy—Part I. Alergol. Pol. Pol. J. Allergol. 2022, 9, 160–169. [Google Scholar] [CrossRef]
  24. Krupka Olek, M.; Bożek, A.; Foks Ciekalska, A.; Grzanka, A.; Kawczyk-Krupka, A. Assessment of Hypersensitivity to House Dust Mites in Selected Skin Diseases Using the Basophil Activation Test: A Preliminary Study. Medicina 2024, 60, 1608. [Google Scholar] [CrossRef] [PubMed]
  25. Izmailovich, M.; Semenova, Y.; Abdushukurova, G.; Mukhamejanova, A.; Dyussupova, A.; Faizova, R.; Gazaliyeva, M.; Akhvlediani, L.; Glushkova, N.; Kalmakhanov, S.; et al. Molecular Aspects of Allergen-Specific Immunotherapy in Patients with Seasonal Allergic Rhinitis. Cells 2023, 12, 383. [Google Scholar] [CrossRef] [PubMed]
  26. Połomska, J.; Dydak, P.; Sozańska, B.; Sikorska-Szaflik, H. Peanut Allergy and Component-Resolved Diagnostics Possibilities—What Are the Benefits? Nutrients 2023, 15, 5132. [Google Scholar] [CrossRef] [PubMed]
  27. Wąsik, J.; Likońska, A.; Kurowski, M. IgE-Mediated Allergy and Asymptomatic Sensitization to Cannabis Allergens—Review of Current Knowledge and Presentation of Six Cases. Medicina 2024, 60, 954. [Google Scholar] [CrossRef]
  28. Jankowski, W.; Przychodniak, D.; Kurowski, M. LTP Syndrome and Edible Insect Allergy in a Patient with Recurrent Anaphylaxis Incidents. Alergol. Pol. Pol. J. Allergol. 2024, 12, 138–139. [Google Scholar] [CrossRef]
  29. Zhang, J.; Tang, Y.; Yang, D.; Yu, J. Investigating Allergen-Specific IgE Distribution and Correlations in Chronic Urticaria: A Retrospective Study in Shanghai, China. Eur. J. Med. Res. 2025, 30, 182. [Google Scholar] [CrossRef]
  30. Liu, M.; Liu, L.; Qi, W.; Zheng, X.; Chen, J.; Yao, J.; Li, Y.; Lin, J.; Li, X.; Hu, X.; et al. Interpreting Epidemiologic Distribution of Total and Specific IgE Levels for Food Allergy in Southern China from 2004 to 2023: Understanding the Mechanisms and Focusing on Prevention. BMC Public Health 2024, 24, 3022. [Google Scholar] [CrossRef]
  31. Wang, J.; Xu, B.; Jia, X.; He, Y.; Jia, B.; Li, J.; Xu, M. Predictive Value of Der p 2-Specific IgE for Subcutaneous Immunotherapy in Children with Allergic Rhinitis. Sci. Rep. 2024, 14, 25467. [Google Scholar] [CrossRef]
  32. Łódź Raport o Stanie Miasta. BS_p25_120_20250530. PDF. Available online: https://bip.uml.lodz.pl/ (accessed on 7 September 2025).
  33. World Health Organization. International Statistical Classification of Diseases and Related Health Problems 10th Revision 2019. World Health Organization: Geneva, Switzerland, 2019. [Google Scholar]
  34. Bousquet, J.; Heinzerling, L.; Bachert, C.; Papadopoulos, N.G.; Bousquet, P.J.; Burney, P.G.; Canonica, G.W.; Carlsen, K.H.; Cox, L.; Haahtela, T.; et al. Practical Guide to Skin Prick Tests in Allergy to Aeroallergens. Allergy 2012, 67, 18–24. [Google Scholar] [CrossRef] [PubMed]
  35. Wallace, D.V.; Bahna, S.L.; Goldstein, S.; Hamilton, R.G.; Cohn, J.R. American Academy of Allergy, Asthma & Immunology Work Group Report: Allergy Diagnosis in Clinical Practice. J. Allergy Clin. Immunol. 2007, 120, 967–969. [Google Scholar] [CrossRef] [PubMed][Green Version]
  36. Kowalski, M.L.; Ansotegui, I.; Aberer, W.; Al-Ahmad, M.; Akdis, M.; Ballmer-Weber, B.K.; Beyer, K.; Blanca, M.; Brown, S.; Bunnag, C.; et al. Risk and Safety Requirements for Diagnostic and Therapeutic Procedures in Allergology: World Allergy Organization Statement. World Allergy Organ. J. 2016, 9, 33. [Google Scholar] [CrossRef] [PubMed]
  37. Szmyd, B.; Biedrzycka, M.; Rogut, M.; Daszkiewicz, G.; Hałucha, J.; Kaszkowiak, M.; Kowalski, M.L.; Kurowski, M. Assessment of Skin Prick Tests and sIgE Measurement Performance in the Diagnosis of Food and Inhalat Allergy. Alerg. Astma Immunol. 2020, 25, 104–110. (In Polish) [Google Scholar]
  38. Ansotegui, I.J.; Melioli, G.; Canonica, G.W.; Caraballo, L.; Villa, E.; Ebisawa, M.; Passalacqua, G.; Savi, E.; Ebo, D.; Gómez, R.M.; et al. IgE Allergy Diagnostics and Other Relevant Tests in Allergy, a World Allergy Organization Position Paper. World Allergy Organ. J. 2020, 13, 100080. [Google Scholar] [CrossRef]
  39. Czarnobilska, E.; Klimaszewska-Rembiasz, M.; Gaweł, B.; Obtułowicz, A. Prevalence of Allergic Diseases in Primary School Children in Cracow and Surroundings—An Attempt to Define Main Risk Factors. Przegląd Lekarski 2002, 59, 422–426. (In Polish) [Google Scholar]
  40. Wojciechowska, M.; Hnatyszyn-Dzikowska, A.; Bartuzi, Z. Sensitization to Haptens, Inhalant and Food Allergensamong Patients Diagnosed for Contact Allergy. Alerg. Astma Immunol. 2016, 21, 110–120. (In Polish) [Google Scholar]
  41. Sybilski, A.J.; Raciborski, F.; Lipiec, A.; Tomaszewska, A.; Lusawa, A.; Samel-Kowalik, P.; Walkiewicz, A.; Krzych-Fałta, E.; Samoliński, B. Epidemiology of Atopic Dermatitis in Poland According to the Epidemiology of Allergic Disorders in Poland (ECAP) Study. J. Dermatol. 2015, 42, 140–147. [Google Scholar] [CrossRef]
  42. Antico, A.; Lima, G.; Arisi, M.; Ostan, A.; Morrica, B. Assay of Prick Test Inoculum Volume. II. Average Values and Individual Variability. Ann. Allergy Asthma Immunol. 2000, 85, 145–149. [Google Scholar] [CrossRef]
  43. Samoliński, B.; Raciborski, F.; Lipiec, A.; Tomaszewska, A.; Krzych-Fałta, E.; Samel-Kowalik, P.; Walkiewicz, A.; Lusawa, A.; Borowicz, J.; Komorowski, J.; et al. Epidemiology of allergic diseases in Poland. Alergol. Pol. Pol. J. Allergol. 2014, 1, 10–18. (In Polish) [Google Scholar] [CrossRef]
  44. Worm, M.; Lee, H.; Kostev, K. Prevalence and Treatment Profile of Patients with Grass Pollen and House Dust Mite Allergy. JDDG J. Dtsch. Dermatol. Ges. 2013, 11, 653–661. [Google Scholar] [CrossRef] [PubMed]
  45. García-Mozo, H. Poaceae Pollen as the Leading Aeroallergen Worldwide: A Review. Allergy 2017, 72, 1849–1858. [Google Scholar] [CrossRef]
  46. Dramburg, S.; Hilger, C.; Santos, A.F.; de Las Vecillas, L.; Aalberse, R.C.; Acevedo, N.; Aglas, L.; Altmann, F.; Arruda, K.L.; Asero, R.; et al. EAACI Molecular Allergology User’s Guide 2.0. Pediatr. Allergy Immunol. 2023, 34 (Suppl. 28), e13854. [Google Scholar] [CrossRef] [PubMed]
  47. Abou Chakra, O.R.; Sutra, J.-P.; Poncet, P.; Lacroix, G.; Sénéchal, H. Key Role of Water-Insoluble Allergens of Pollen Cytoplasmic Granules in Biased Allergic Response in a Rat Model. World Allergy Organ. J. 2011, 4, 4–12. [Google Scholar] [CrossRef] [PubMed]
  48. Dharajiya, N.; Boldogh, I.; Cardenas, V.; Sur, S. Role of Pollen NAD(P)H Oxidase in Allergic Inflammation. Curr. Opin. Allergy Clin. Immunol. 2008, 8, 57–62. [Google Scholar] [CrossRef]
  49. Wang, X.-L.; Takai, T.; Kamijo, S.; Gunawan, H.; Ogawa, H.; Okumura, K. NADPH Oxidase Activity in Allergenic Pollen Grains of Different Plant Species. Biochem. Biophys. Res. Commun. 2009, 387, 430–434. [Google Scholar] [CrossRef]
  50. Visez, N.; De Nadaï, P.; Choël, M.; Farah, J.; Hamzé, M.; Sénéchal, H.; Pauwels, M.; Frérot, H.; Thibaudon, M.; Poncet, P. Biochemical Composition of Phleum Pratense Pollen Grains: A Review. Mol. Immunol. 2021, 136, 98–109. [Google Scholar] [CrossRef]
  51. Raith, M.; Swoboda, I. Birch Pollen—The Unpleasant Herald of Spring. Front. Allergy 2023, 4, 1181675. [Google Scholar] [CrossRef]
  52. Darnhofer, B.; Tomin, T.; Liesinger, L.; Schittmayer, M.; Tomazic, P.V.; Birner-Gruenberger, R. Comparative Proteomics of Common Allergenic Tree Pollens of Birch, Alder, and Hazel. Allergy 2021, 76, 1743–1753. [Google Scholar] [CrossRef]
  53. Rapiejko, J.; Puc, M.; Piotrowska-Weryszko, K.; Myszkowska, D.; Chodkowski, J.; Malkiewicz, M.; Jurkiewicz, D.; Siergiejko, G.; Chłopek, K.; Lipiec, A. Analysis of Artemisia Pollen Season in Selected Cities of Poland in 2022. Alergoprofil 2023, 19, 13–19. [Google Scholar] [CrossRef]
  54. Majkowska–Wojciechowska, B.; Balwierz, Z.; Kowalski, M. Pollen Counts Analysis in the Atmosphere of Lodz (Poland) during Vegetation in 2008. Alerg. Astma Immunol. 2008, 13, 250–263. [Google Scholar]
  55. Majkowska-Wojciechowska, B.; Balwierz, Z.; Kowalski, M.L. Changes in the Concentration of Pollen over an 11-Year Period in a Polish Urban Environment. Acta Agrobot. 2016, 69, 1–11. [Google Scholar] [CrossRef][Green Version]
  56. Majkowska-Wojciechowska, B.; Balwierz, Z.; Kowalski, M. Pollen and Spores of Microscopic Fungi in Atmospheric Air Lodz in 2013. Alerg. Astma Immunol. 2015, 20, 192–198. (In Polish) [Google Scholar][Green Version]
  57. Ma, T.; Wang, H.; Chen, Y.; Zhuang, Y.; Shi, H.; Yu, R.; Guo, M.; Yin, J.; Wang, X. Sensitization Spectrum of Inhaled Allergens in Outpatients in Beijing Area. Chin. J. Allergy Clin Immunol. 2021, 15, 136–143. (In Chinese) [Google Scholar][Green Version]
  58. Yu, Y.; Yan, X.; Wang, L.; Dong, L.; Song, D.; Liu, J.; Gao, X. Investigation and Analysis of Inhalant Allergens in Patients with Allergic Rhinitis in Yinchuan, China. Int. Arch. Allergy Immunol. 2024, 186, 445–453. [Google Scholar] [CrossRef]
  59. Wang, M.; Ma, J.; Yang, Z.; Wang, W.; Sa, Y.; Ma, F.; Zhang, W.; He, X.; Chen, G.; Ma, X. Immunoproteomic Analysis and Identification of Possible Allergenic Proteins in Artemisia Annua Pollen. Int. Immunopharmacol. 2025, 146, 113837. [Google Scholar] [CrossRef]
  60. Asero, R. Is the Strange Case of Mugwort Sensitivity in Ragweed-Allergic Subjects Coming Eventually to a Solution? Eur. Ann. Allergy Clin. Immunol. 2011, 43, 67–68. [Google Scholar]
  61. Pablos, I.; Eichhorn, S.; Machado, Y.; Briza, P.; Neunkirchner, A.; Jahn-Schmid, B.; Wildner, S.; Soh, W.T.; Ebner, C.; Park, J.-W.; et al. Distinct Epitope Structures of Defensin-like Proteins Linked to Proline-rich Regions Give Rise to Differences in Their Allergenic Activity. Allergy 2018, 73, 431–441. [Google Scholar] [CrossRef]
  62. Stępalska, D.; Myszkowska, D.; Piotrowicz, K.; Kluska, K.; Chłopek, K.; Grewling, Ł.; Lafférsová, J.; Majkowska-Wojciechowska, B.; Malkiewicz, M.; Piotrowska-Weryszko, K.; et al. High Ambrosia Pollen Concentrations in Poland Respecting the Long Distance Transport (LDT). Sci. Total Environ. 2020, 736, 139615. [Google Scholar] [CrossRef]
  63. Bergmann, K.-C. Biology of House Dust Mites and Storage Mites. Allergo J. Int. 2022, 31, 272–278. [Google Scholar] [CrossRef]
  64. Solarz, K. Risk of Exposure to House Dust Pyroglyphid Mites in Poland. Ann. Agric. Environ. Med. AAEM 2001, 8, 11–24. [Google Scholar]
  65. Lee, K.-A.; Flores, R.R.; Jang, I.H.; Saathoff, A.; Robbins, P.D. Immune Senescence, Immunosenescence and Aging. Front. Aging 2022, 3, 900028. [Google Scholar] [CrossRef]
  66. Ventura, M.T.; Scichilone, N.; Paganelli, R.; Minciullo, P.L.; Patella, V.; Bonini, M.; Passalacqua, G.; Lombardi, C.; Simioni, L.; Ridolo, E.; et al. Allergic Diseases in the Elderly: Biological Characteristics and Main Immunological and Non-Immunological Mechanisms. Clin. Mol. Allergy 2017, 15, 2. [Google Scholar] [CrossRef] [PubMed]
  67. Warren, K.J.; Deering-Rice, C.; Huecksteadt, T.; Trivedi, S.; Venosa, A.; Reilly, C.; Sanders, K.; Clayton, F.; Wyatt, T.A.; Poole, J.A.; et al. Steady-State Estradiol Triggers a Unique Innate Immune Response to Allergen Resulting in Increased Airway Resistance. Biol. Sex Differ. 2023, 14, 2. [Google Scholar] [CrossRef] [PubMed]
  68. Harvey, B.J.; McElvaney, N.G. Sex Differences in Airway Disease: Estrogen and Airway Surface Liquid Dynamics. Biol. Sex Differ. 2024, 15, 56. [Google Scholar] [CrossRef] [PubMed]
  69. Cephus, J.-Y.; Stier, M.T.; Fuseini, H.; Yung, J.A.; Toki, S.; Bloodworth, M.H.; Zhou, W.; Goleniewska, K.; Zhang, J.; Garon, S.L.; et al. Testosterone Attenuates Group 2 Innate Lymphoid Cell-Mediated Airway Inflammation. Cell Rep. 2017, 21, 2487–2499. [Google Scholar] [CrossRef]
  70. Han, Y.-Y.; Yan, Q.; Yang, G.; Chen, W.; Forno, E.; Celedon, J.C. Serum Free Testosterone and Asthma, Asthma Hospitalisations and Lung Function in British Adults. Thorax 2020, 75, 849–854. [Google Scholar] [CrossRef]
  71. Trivedi, S.; Deering-Rice, C.E.; Aamodt, S.E.; Huecksteadt, T.P.; Myers, E.J.; Sanders, K.A.; Paine, R.; Warren, K.J. Progesterone Amplifies Allergic Inflammation and Airway Pathology in Association with Higher Lung ILC2 Responses. Am. J. Physiol.-Lung Cell. Mol. Physiol. 2024, 327, L65–L78. [Google Scholar] [CrossRef]
  72. Dou, X.; Zhang, W.; Zhang, X. Exploring the Immunological Underpinnings of Allergic Conjunctivitis: The Role of CD4 + T Cells and SLAM Expression in Ocular Surface Disease. Int. Ophthalmol. 2025, 45, 77. [Google Scholar] [CrossRef]
  73. Rabensteiner, D.F.; Rabensteiner, J.; Horwath-Winter, J.; Lang-Loidolt, D.; Wedrich, A.; Heidinger, A.; Schwantzer, G.; Schmut, O. Extracts of Different Pollen Species and Their Effect on Human Tear Fluid and an Epithelial Cell Line. Cutan. Ocul. Toxicol. 2019, 38, 93–103. [Google Scholar] [CrossRef]
  74. Montoro, J.; Antolín-Amérigo, D.; Izquierdo-Domínguez, A.; Zapata, J.; García-Gallardo, M.; González, R.; Armentia, A.; Rondón, C.; Fernández, M.; Pedrero, S.; et al. Climate Change–Associated Environmental Factors and Pollutants: Impact on Allergic Diseases, Epidemiology, Severity, and Health Care Burden. J. Investig. Allergy Clin. Immunol. 2025, 35, 240–250. [Google Scholar] [CrossRef]
  75. Olivieri, M.; Marchetti, P.; Murgia, N.; Nicolis, M.; Torroni, L.; Spiteri, G.; Ferrari, M.; Marcon, A.; Verlato, G. Natural Pollen Exposure Increases in a Dose-dependent Way Fraction of Exhaled Nitric Oxide (FeNO) Levels in Patients Sensitized to One or More Pollen Species. Clin. Transl. Allergy 2022, 12, e12096. [Google Scholar] [CrossRef] [PubMed]
  76. Klangkalya, N.; Watcharoot, K.; Adithep, S.; Potjanee, K.; Wanlapa, J.; Wiparat, M. Skin Prick Test and Serum Specific IgE in Predicting Dust Mite-Induced Allergic Rhinitis Diagnosed from Nasal Provocation Test in Chronic Rhinitis Children. Asian Pac. J. Allergy Immunol. 2025, 42, 354–360. [Google Scholar] [CrossRef]
  77. Kurowski, M.; Majkowska-Wojciechowska, B.; Wardzyńska, A.; Kowalski, M.L. Associations of Allergic Sensitization and Clinical Phenotypes with Innate Immune Response Genes Polymorphisms Are Modified by House Dust Mite Allergen Exposure. Arch. Med. Sci. 2011, 6, 1029–1036. [Google Scholar] [CrossRef]
  78. Majkowska-Wojciechowska, B.; Laskowska, B.; Wojciechowski, Z.; Kowlaski, M. Występowanie Alergii Wśród Dzieci Łódzkich Szkół Podstawowych: Związek z Warunkami Środowiska Domowego i Szkolnego. Alerg. Astma Immunol. 2000, 5, 115–122. [Google Scholar]
  79. Góra, D.J.; Kupiec, J. Analysis of the Incidence of Asthma among Pupils of Primary Schools in Bielsko-Biala Located in Areas with Various Degrees of Industrialization. Alergol. Pol. Pol. J. Allergol. 2024, 11, 211–216. [Google Scholar] [CrossRef]
  80. Stelmach, I.; Smejda, K.; Kaczmarek, J.; Stelmach, W.; Kuna, P. Prevalence of Atopy and Atopic Diseases in Children Living in an Orphanage in Lodz Area Pilot Study. Pol. Merkur. Lekarski 2006, 20, 531–534. (In Polish) [Google Scholar]
  81. Stelmach, I.; Smejda, K.; Jerzynska, J.; Stelmach, W.; Majak, P.; Stelmach, P.; Kuna, P. Decreased Markers of Atopy in Children with Presumed Early Exposure to Allergens, Unhygienic Conditions, and Infections. Ann. Allergy Asthma Immunol. 2007, 99, 170–177. [Google Scholar] [CrossRef]
Medicina 61 01676 g001
Figure 1. Sex differences in likelihood ratio of grass pollen reactivity and house dust mites reactivity in the entire study group. HDM, house dust mites.
Figure 1. Sex differences in likelihood ratio of grass pollen reactivity and house dust mites reactivity in the entire study group. HDM, house dust mites.
Medicina 61 01676 g001
Medicina 61 01676 g002
Figure 2. Panel (A) Diameters of wheal in skin prick tests with airborne allergens from the standard panel. Mean values (in mm) are shown as numerical values; 95% confidence intervals are indicated with whiskers. Panel (B) Frequency of positive skin prick test results with airborne allergens from the standard panel in the entire study group (n = 1711). D. pter., Dermatophagoides pteronyssinus; D. far., Dermatophagoides farinae.
Figure 2. Panel (A) Diameters of wheal in skin prick tests with airborne allergens from the standard panel. Mean values (in mm) are shown as numerical values; 95% confidence intervals are indicated with whiskers. Panel (B) Frequency of positive skin prick test results with airborne allergens from the standard panel in the entire study group (n = 1711). D. pter., Dermatophagoides pteronyssinus; D. far., Dermatophagoides farinae.
Medicina 61 01676 g002
Medicina 61 01676 g003
Figure 3. Results of the Pearson correlation between mean wheal diameter in skin prick tests with a given allergen in the entire study group (n = 1711) and percent of positive skin prick results with the same allergen (r = 0.9927, r2 = 0.9855, p < 0.000001).
Figure 3. Results of the Pearson correlation between mean wheal diameter in skin prick tests with a given allergen in the entire study group (n = 1711) and percent of positive skin prick results with the same allergen (r = 0.9927, r2 = 0.9855, p < 0.000001).
Medicina 61 01676 g003
Medicina 61 01676 g004
Figure 4. Distribution of the numbers of monovalent reactivity to airborne allergen extracts in the entire study group (n = 1711). No monovalent sensitization was observed in the case of rye pollen and hazel pollen. The percentage profiles is given in Section 3.3.1.
Figure 4. Distribution of the numbers of monovalent reactivity to airborne allergen extracts in the entire study group (n = 1711). No monovalent sensitization was observed in the case of rye pollen and hazel pollen. The percentage profiles is given in Section 3.3.1.
Medicina 61 01676 g004
Medicina 61 01676 g005
Figure 5. Distribution of the numbers of reactivity (lower X axis) in skin prick test panel in the entire group (n = 1711). Number of subjects with given number of reactivity is indicated on the Y axis with percentage of the total group indicated above each column.
Figure 5. Distribution of the numbers of reactivity (lower X axis) in skin prick test panel in the entire group (n = 1711). Number of subjects with given number of reactivity is indicated on the Y axis with percentage of the total group indicated above each column.
Medicina 61 01676 g005
Medicina 61 01676 g006
Figure 6. Graphical representation of the results from Table 3 for the first two factors PC1 and PC2, which explain the most variability. The charges marked with a dashed line characterize four distinct reactivity groups.
Figure 6. Graphical representation of the results from Table 3 for the first two factors PC1 and PC2, which explain the most variability. The charges marked with a dashed line characterize four distinct reactivity groups.
Medicina 61 01676 g006
Table 1. Basic characteristics of the entire study group, as per division into age groups. SD, standard deviation.
Table 1. Basic characteristics of the entire study group, as per division into age groups. SD, standard deviation.
Group I
<10 years		Group II
≥10–50 years		Group III
>50 years
Number
of subjects (n)		1901280241
Mean age
± SD		6.87 ± 2.028.11 ± 11.0660.02 ± 6.65
Age range
(years)		2.57–9.9910.04–49.9650.28–86.42
% of the total population11.1%74.81%14.09%
Table 2. Monovalent reactivity as per division into age groups.
Table 2. Monovalent reactivity as per division into age groups.
Number of Subjects with Monovalent Reactivity in a Given GroupPercentage of Subjects with Monovalent Reactivity in a Given Group
Group I
<10 years (n = 190)		2613.68%
Group II
≥10–50 years (n = 1280)		14010.94%
Group III
>50 years (n = 241)		6928.63%
Total (n = 1711)23513.73%
Table 3. Results of the factor analysis of SPT positive results with regard to four principal components (as described in Section 2.3). SPT, skin prick test; PC, principal component.
Table 3. Results of the factor analysis of SPT positive results with regard to four principal components (as described in Section 2.3). SPT, skin prick test; PC, principal component.
VariablesFactor Loadings
Extraction Principal Components (PC). Marked Loadings > 0.7
PC1_Trees Pollen
1		PC2_ House Dust Mites
2		PC3_Grass Pollen
3		PC4_Pets
4
1.D. farinae−0.0107300.9483300.0140720.080939
2.D. pteronyssinus−0.0130670.9493400.0446770.050046
3.Alder0.9358160.0044890.1902700.099719
4.Hazel0.918262−0.0100660.2016670.092477
5.Birch0.927786−0.0145250.1539300.102391
6.Timothy0.142750−0.0209500.9297280.084068
7.Rye0.114222−0.0137040.9356310.101022
8.Mugwort0.1923020.0692460.3714630.048909
9.Dog0.1423260.1702010.0218740.715538
10.Cat0.2355080.1869210.0806630.712500
11.Alternaria−0.087785−0.1854420.1221410.588676
Explained variance2.7338601.9046272.0024491.423891
Proportion of variance0.2485330.1731480.1820410.129445
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.

Share and Cite

MDPI and ACS Style

Majkowska-Wojciechowska, B.; Kulma, M.; Kurowski, M. Aeroallergen IgE-Reactivity Patterns and Respiratory Allergy in Children and Adults: A Retrospective Study in 1711 Patients from the Central Poland Urban Area. Medicina 2025, 61, 1676. https://doi.org/10.3390/medicina61091676

AMA Style

Majkowska-Wojciechowska B, Kulma M, Kurowski M. Aeroallergen IgE-Reactivity Patterns and Respiratory Allergy in Children and Adults: A Retrospective Study in 1711 Patients from the Central Poland Urban Area. Medicina. 2025; 61(9):1676. https://doi.org/10.3390/medicina61091676

Chicago/Turabian Style

Majkowska-Wojciechowska, Barbara, Maciej Kulma, and Marcin Kurowski. 2025. "Aeroallergen IgE-Reactivity Patterns and Respiratory Allergy in Children and Adults: A Retrospective Study in 1711 Patients from the Central Poland Urban Area" Medicina 61, no. 9: 1676. https://doi.org/10.3390/medicina61091676

APA Style

Majkowska-Wojciechowska, B., Kulma, M., & Kurowski, M. (2025). Aeroallergen IgE-Reactivity Patterns and Respiratory Allergy in Children and Adults: A Retrospective Study in 1711 Patients from the Central Poland Urban Area. Medicina, 61(9), 1676. https://doi.org/10.3390/medicina61091676

Article Metrics

Back to TopTop