1. Introduction
Asian sand dust (ASD) particles are an important air pollutant material that originates in East Asia from China and Mongolian Desert storms during the spring season (February–May) [
1,
2]. Additionally, most ASD particles include minerals and microorganisms [
2]; however, they also include many pollutants, particularly particulate matter <10 μm in aerodynamic diameter (PM
10). Moreover, the PM
10 concentration accounts for 53%–70% of total ASD particulate matter [
3,
4]. PM
10 particles are the major cause of respiratory system inflammatory reactions [
5,
6,
7].
The association between dust events and death from cardiovascular and respiratory causes is statistically significant for all pollutants [
8,
9,
10]. It has also been suggested that patients with advanced respiratory disease might be more susceptible to ASD events [
11,
12]. ASD stimulated chemical mediators and mucin production in an allergic murine model [
13,
14,
15]. This allergic inflammation was activated by mineral elements (mainly SiO
2), which increases interleukin-5 and monocyte chemotactic protein-3 expression levels [
16]. ASD also enhanced allergic reactions in guinea pigs repeatedly administered Japanese cedar pollen particles [
17]. PM
2.5 (fine particles with aerodynamic diameter < 2.5 μm) may enhance allergic sensitization through interactions with allergens [
18]. Many reports have demonstrated a relationship between air pollution and exacerbation of asthma and other allergic diseases [
19,
20,
21]. About 30% of adult patients with asthma show worsening of upper and/or lower respiratory, ocular, or cutaneous symptoms during ASD events [
22,
23].
Although some reports have suggested a possible negative effect of ASD on allergic diseases [
24,
25], no reports have determined whether ASD PM
10 influences allergy symptoms in patients with allergic rhinitis. In this study, we clarified the effects of PM
10 and pollen concentrations on allergy symptoms of patients with allergic rhinitis during the spring ASD season.
2. Patients
We evaluated 108 patients with allergic rhinitis and 47 controls without allergic rhinitis at the Gachon University Gil Medical Center and the Inha University Hospital. A total of 108 allergic patients, who were previously diagnosed and treated for allergic rhinitis with positive skin tests and Immunocap® tests for Dermatophagoides pteronysinus and Dermatophagoides farine, were enrolled. The allergic rhinitis severity level in these patients was classified into four groups according to criteria of the 2009 Allergic Rhinitis Impact on Asthma (ARIA) guidelines (I: mild intermittent, II: moderate to severe intermittent, III: mild persistent, and IV: moderate to severe persistent). We enrolled 47 volunteers as a control group and confirmed that they had no allergies by clinical history assessments, skin tests, and physical examinations. This study was approved by the institutional review boards from both institutions.
3. Methods
The allergy patient and control groups recorded their symptoms in a daily symptom diary. They checked for allergy symptoms by assessing rhinorrhea, nasal obstruction, sneezing, itching, and sleep disturbance levels using a modified six-point Likert scale (0: no symptoms, 5: most serious symptoms) for 120 days from 1 February to 30 May 2012 [
26]. We then evaluated the serial correlations between the symptom scores and PM
10 changes over 120 days (long-term observations). We also evaluated symptom changes during the 2 days before and after the 3 event days, when the daily PM
10 concentrations peaked at >100 μg/m
3 (short-term observations). The subjects also recorded their outdoor activity time in their diaries. The guidelines established by the National Health Environmental Research Center suggest that the sensitive group (the airway and cardiac disease patients) could be influenced by PM
10 concentrations of 81–120 μg/m
3. A questionnaire that assessed life quality, comorbid diseases, and ARIA levels was also evaluated.
PM
10 concentrations were evaluated in 10 areas of Incheon City using information made public by the Incheon City Health Environmental Research Center (
Table 1). This center publishes monthly data for five major air pollutants (PM
10, PM
2.5, SO
2, O
3, CO, and NO
2). Pollen concentrations were also evaluated in three areas inside Incheon City, including a number of tree and herb pollens (Needle Fir, Japanese Maple, Japanese Chestnut, Wind Spindle Tree, Chinese Bayberry, Japanese Red Pine, Oak, Korean Willow, Ragweed, Wormwood, Rice, and Trumpet Lily,
Figure 1).
Table 1.
PM10 concentrations measured in 15 areas of Incheon City.
Table 1.
PM10 concentrations measured in 15 areas of Incheon City.
Mar Day | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 |
---|
25 | 64 | 63 | 62 | 79 | 52 | 55 | 59 | 66 | 76 | 55 | 58 | 60 | 78 | 73 | 68 |
26 | 46 | 49 | 50 | 52 | 38 | 39 | 43 | 43 | 61 | 50 | 42 | 32 | 41 | 47 | 42 |
27 | 56 | 56 | 55 | 56 | 49 | 46 | 47 | 48 | 69 | 59 | 49 | 43 | 45 | 54 | 50 |
28 | 157 | 159 | 151 | 144 | 129 | 143 | 116 | 115 | 188 | 146 | 141 | 109 | 126 | 138 | 135 |
29 | 159 | 146 | 127 | 113 | 126 | 125 | 105 | 89 | 171 | 152 | 129 | 87 | 99 | 106 | 109 |
30 | 56 | 63 | 60 | 49 | 45 | 55 | 53 | 56 | 73 | 60 | 55 | 40 | 40 | 49 | 39 |
31 | 78 | 74 | 81 | 107 | 70 | 69 | 80 | 89 | 92 | 77 | 71 | 59 | 98 | 56 | 47 |
These data were supplied by the Environmental Health Center for Allergic Rhinitis (Inha University Hospital). They used a 7-day recording volumetric spore sampler (Burkard Manufacturing Co., Ltd., Hertfordshire, UK). Pollen was counted as the number of pollen particles in 1 m3 using Pan-American Aerobiology Association standardized protocols.
Figure 1.
Map of the monitoring station locations and basic area features. Circle: PM10 measurement area, Triangle: pollen measurement area.
Figure 1.
Map of the monitoring station locations and basic area features. Circle: PM10 measurement area, Triangle: pollen measurement area.
Statistical Analyses
The patient’s characteristics are described as proportions. We used a mixed regression model to evaluate the association between PM10 concentrations and allergy symptoms, which were measured consecutively for 120 days in allergic patients and normal subjects (analysis for long-term observations). We also used a mixed regression model to evaluate which factors, including pollen counts and time spent outdoors, were associated with allergy symptoms in allergic patients. In the mixed regression model, we corrected for within-subject covariance using a first-order autoregressive covariance structure. When there were days with >100 μg/m3 PM10 concentration (event days), we compared allergy symptom scores recorded before those 2 days with scores recorded after the event day in allergic patients and normal subjects using repeated-measures analysis of variance for a 120-day observation period (analysis for short-term observations). We conducted a correlation analysis with mean allergic nasal symptoms and PM10 concentrations with lag times (0, 1, 2 days) from event day to assess the relationship between the most-affected days after the event day and allergic nasal symptoms. All analyses were conducted using SAS 9.3 (SAS Institute, Cary, NC, USA).
4. Results
4.1. Patient Characteristics
We selected 108 allergic patients (58 male, 50 female) and 47 controls (19 male, 28 female) The average patient age was 20 years. No differences in age and sex distributions were observed between the patient and control groups. The main symptoms for the allergic patients were rhinorrhea, sneezing, nasal obstruction, and sleep disturbance. According to the ARIA guidelines, the mildly persistent patients were the most common group (
Table 2). ARIA class I: mild intermittent symptoms, II: moderate to severe intermittent symptoms, III: mildly persistent symptoms, IV: moderate to severe persistent symptoms.
4.2. PM10 and Pollen Count Measurements
We measured PM
10 concentrations continuously for 120 days (
Figure 2). In the past, the PM
10 concentration increased to >400 μg/m
3 for an average of 10 days during the ASD season (February–May); however, in 2012, PM
10 concentration did not rise that high. Specifically, the highest PM
10 concentration in 2012 was <150 μg/m
3. We evaluated the three event days when the PM
10 concentration was >100 μg/m
3. These three event days were 24 February (105.53 μg/m
3), 29 March (139.8 μg/m
3), and 5 May (116.13 μg/m
3). Additionally, pollen counts increased very significantly in May compared with those in February and March (
Figure 3).
Table 2.
Patient characteristics.
Table 2.
Patient characteristics.
Characteristics | Allergic Rhinitis Patients |
---|
Male/Female | 58/50 |
Age | 6–12: 28.7% |
13–18: 17.7% |
20–29: 22.5% |
30–39: 14% |
≥40: 17.1% |
ARIA class | I: 9.4% , II: 14.1%, III: 69.5%, IV: 7% |
Associated disease | Atopic dermatitis: 28.8% |
Asthma: 11.1% |
Sinusitis: 29.6% |
Allergy-related familial history | 54.4% |
Figure 2.
PM10 and pollen dispersions. The PM10 and pollen concentrations were measured consecutively for 120 days. PM10: PM10 concentration; FLO: pollen concentration. (Lt. bar: PM10 μg/m3; Rt bar unit: pollen particle/m3).
Figure 2.
PM10 and pollen dispersions. The PM10 and pollen concentrations were measured consecutively for 120 days. PM10: PM10 concentration; FLO: pollen concentration. (Lt. bar: PM10 μg/m3; Rt bar unit: pollen particle/m3).
Figure 3.
PM10 and pollen dispersions. The three event days when the PM10 was >100 µg/m3 were 24 February, 29 March, and 5 May. PM10, PM10 concentration; FLO, pollen concentration.
Figure 3.
PM10 and pollen dispersions. The three event days when the PM10 was >100 µg/m3 were 24 February, 29 March, and 5 May. PM10, PM10 concentration; FLO, pollen concentration.
4.3. The Effect of PM10 on Allergy Symptoms
We collected and classified all types of pollen (
Table 3). The long-term observations demonstrated that the daily PM
10 changes were not significantly correlated with changes in allergy symptoms, including nasal obstruction (
p = 0.6137), rhinorrhea (
p = 0.9427), sneezing (
p = 0.9032), itching (
p = 0.1536), sleep disturbance (
p = 0.5946), or total symptom score (
p = 0.6176). No significant changes were observed in the control group. These results demonstrate that the nasal symptoms of the patients with allergy were not influenced by PM
10 concentrations <150 μg/m
3 during the spring season (
Table 4). However, significant correlations between total nasal symptom scores and outdoor activity time (
p < 0.001) was observed. These data indicate that allergy symptoms were significantly aggravated by an increase in outdoor exposure time. Temperature had a significant effect in both groups (
Table 5).
Table 3.
Pollen counts. Total pollen counts were measured in three areas of Incheon city.
Table 3.
Pollen counts. Total pollen counts were measured in three areas of Incheon city.
Pollen | Scientific Name | Genus Name |
---|
Tree | Abies | Needle Fir |
Acer | Japanese Maple |
Castanea | Japanese Chestnut |
Euonymus | Wind Spindle Tree |
Myrica | Chinese Bayberry |
Pinus | Japanese Red Pine |
Quercus | Oak |
Salix | Korean Willow |
Ambrosia | Ragweed |
Herb | Artemisia | Wormwood |
Gramineae | Rice |
Lilyaceae | Trumpet Lily |
Table 4.
The effects of PM10 on allergy symptoms according to the long-term observations (p-value).
Table 4.
The effects of PM10 on allergy symptoms according to the long-term observations (p-value).
Effect | Estimate | Standard Error | p-value |
---|
Rhinorrhea | allergy group | −0.00041 | 0.000306 | 0.1787 |
control group | −0.000018 | 0.000254 | 0.9425 |
Itching | allergy group | −0.00037 | 0.000294 | 0.1201 |
control group | 0.00010 | 0.000163 | 0.5210 |
Nasal Obstruction | allergy group | −0.00008 | 0.000320 | 0.7948 |
control group | −0.00023 | 0.000340 | 0.4951 |
Sneezing | allergy group | −0.00033 | 0.000311 | 0.2240 |
control group | −0.00005 | 0.000276 | 0.8623 |
Sleep disturbance | allergy group | −0.00037 | 0.000213 | 0.0809 |
control group | 0.000047 | 0.000111 | 0.6729 |
Total symptom score | allergy group | −0.00160 | 0.000884 | 0.0694 |
control group | −0.00069 | 0.000724 | 0.3377 |
Table 5.
The relationships of pollen concentration and time outside with total nasal symptom scores.
Table 5.
The relationships of pollen concentration and time outside with total nasal symptom scores.
Effect | Allergy Group | Control Group |
---|
Estimate | Standard error | p-value | Estimate | Standard error | p-value |
---|
FLO | −0.00028 | 0.000172 | 0.1015 | −0.00004 | 0.000083 | 0.6335 |
OUT | 0.1243 | 0.007797 | <0.001 | 0.05990 | 0.007874 | <0.0001 |
HUMID | −0.00055 | 0.001404 | 0.6973 | −0.00114 | 0.001249 | 0.3620 |
TEMP | −0.00575 | 0.007319 | 0.4318 | −0.01008 | 0.006282 | 0.1087 |
No specific changes in the allergy symptom scores before and after the event days were detected in the short-term observations (event days) (
Table 6).
Table 6.
The effects of PM10 on allergy symptoms and drug use according to the short-term observations (p-value).
Table 6.
The effects of PM10 on allergy symptoms and drug use according to the short-term observations (p-value).
Effect | 24 February | 29 March | 5 May |
---|
Rhinorrhea | 0.88 | 0.41 | 0.72 |
Itching | 0.88 | 0.67 | 0.24 |
Nasal obstruction | 0.19 | 0.65 | 0.52 |
Sneezing | 0.19 | 0.66 | 0.19 |
Sleep disturbance | 0.67 | 0.72 | 0.48 |
Total nasal score | 0.53 | 0.95 | 0.15 |
Drug use | 0.49 | 0.53 | 0.49 |
We also investigated the number of most-affected days after high PM
10 concentration exposures. Compared with lag0 (the increased day) symptoms, the lag1 (the next day) and lag2 (day 2) symptoms were not aggravated (
Table 7).
Table 7.
The relationship between the most-affected days after high PM10 concentration exposures and allergic nasal symptoms.
Table 7.
The relationship between the most-affected days after high PM10 concentration exposures and allergic nasal symptoms.
Days | Rhinorrhea | Sneezing | Nasal Obstruction | Itching | Sleep Disturbance | Total Score |
---|
Lag0 |
p-value | 0.744 | 0.704 | 0.747 | 0.578 | 0.603 | 0.888 |
Correlation | 0.030 | 0.035 | −0.030 | −0.051 | −0.048 | −0.013 |
Lag1 |
p-value | 0.937 | 0.567 | 0.642 | 0.924 | 0.979 | 0.717 |
Correlation | −0.007 | −0.053 | −0.043 | −0.009 | −0.002 | −0.033 |
Lag2 |
p-value | 0.902 | 0.482 | 0.432 | 0.837 | 0.793 | 0.658 |
Correlation | 0.011 | −0.065 | −0.073 | 0.019 | −0.024 | −0.041 |
No differences in the change in symptoms were observed according to ARIA classification (data not shown). Additionally, children (subjects <13 years old) who were more sensitive did not have different total symptom scores compared with older subjects. Moreover, no differences were detected between the sexes (
Table 8).
Table 8.
The relationship between total symptom scores, age (<13 years) and sex.
Table 8.
The relationship between total symptom scores, age (<13 years) and sex.
Effect | Estimate | Standard Error | p-value |
---|
PM10 | −0.00217 | 0.001398 | 0.1198 |
Age | 0.01169 | 0.2142 | 0.9567 |
Sex | 0.05494 | 0.8565 | 0.9492 |
5. Discussion
The PM10 concentration frequently increases during the spring ASD season in Korea, and we hypothesized that increased PM10 during the ASD might play a role in aggravating allergy symptoms. PM10 concentrations have increased >400 μg/m3 in the past 10 years, and most people have experienced aggravated respiratory symptoms during the ASD season. However, our results demonstrate that PM10 concentrations <150 μg/m3 did not aggravate allergy symptoms in patients with allergic rhinitis.
A significant increase in the variation in pulmonary function has been observed during Asian dust days compared with control days [
11,
24]. Additionally, exercise-induced bronchial reactivity, atopic asthma, and skin prick tests positive for indoor allergens increased significantly along with PM
2.5 concentrations in primary school children [
18]. Personal PM
2.5 levels in asthmatic allergic children living in urban areas are correlated with the percentages of nasal eosinophils [
19]. Additionally, children living <50 m from a heavily trafficked road were more likely to develop asthma. This study also reported a possible link between developing asthma and increased PM
10 concentration. However, the International Study of Asthma and Allergies in Childhood (ISAAC) reported a weak negative association between PM
10 and various outcomes [
25]. These findings suggest that the urban PM
10 background has little or no association with the prevalence of childhood asthma, rhinoconjunctivitis, or eczema [
26]. In contrast to previous studies, our data show similar results to those of the ISAAC study.
In another study, subjects reported significantly higher respiratory symptom frequency during Asian dust days compared with that during control days. The effects of dust storms on asthma admissions were prominent two days after the event (8%); however, this association was not statistically significant [
27]. In our study, we evaluated the effects of PM
10 on allergy symptoms two days before and again after event days, and we found that increased PM
10 did not influence the changes in allergy symptoms. This result suggests that allergic patients were not affected by PM
10 concentrations <150 μg/m
3. ASD concentrations frequently increase to 400–800 μg/m
3 during the ASD season in Korea; however, the PM
10 concentration during the current season was not sufficient to stimulate allergy symptoms.
Our data demonstrate that outdoor activity time was significantly correlated with allergic symptom scores. This result suggests that outdoor exposure time has a more meaningful impact on allergy symptoms than does PM10 concentration. These results also emphasize that we cannot suggest that pollen and PM10 concentrations have a synergistic effect aggravating symptom scores.
We hypothesized that those with higher ARIA grade might be more influenced by the increased PM10 concentration. However, our data did not show a positive correlation with the ARIA grades. The PM10 concentration in this study was associated with a suboptimal level that is capable of inducing symptom changes in most symptomatic patients with allergic rhinitis.
6. Conclusions
Our data demonstrated no correlation between PM10 and allergy symptom scores in patients with allergic rhinitis when the PM10 concentration was <150 μg/m3.
Acknowledgments
This study was supported by a 2011 grant from the Korea Centers for Disease Control and Prevention.
Author Contributions
Il Gyu Kang conceived the idea of the study, Joo Hyun Jung, Young Hyo Kim, Tae Young Jang and Youn Hee Ju collected the data, Kwang Pil Ko and Dae Kyu Oh analyzed the data, Dae Hyun Lim and Jeong Hee Kim provided the pollen counts and Seon Tae Kim drafted the manuscript and approved the final manuscript.
Conflicts of Interest
The authors declare no conflict of interest.
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