Abstract
Objectives
Since Korea is geographically close to China (the origin site for Asian sand dust [ASD]) the health influence of ASD event will be still greater in Korea. We aimed to evaluate the effect of PM10 (particulate matter with aerodynamic diameter <10 μm, below 150 μg/m3) on the clinical course of allergic rhinitis (AR).
Methods
We enrolled 47 healthy volunteers (group A) and 108 AR patients sensitized to house dust mites (group B). For 120 consecutive days (from February 1st to May 30th, 2012), all subjects reported their daily nasal symptoms and performed 2 peak flowmeter readings to measure peak nasal inspiratory flow (PNIF). We evaluated the correlation between the daily concentration of PM10, symptoms, and PNIF of patients. We also investigated changes in symptoms and PNIF 2 days before and after ‘dusty’ days (daily concentration of PM10 >100 μg/m3)
Asian sand dust (ASD) is originated from China, Mongolia, and Kazakhstan area and moves eastward to affect eastern China, Japan, and Korea. Occasionally, ASD can exert its influence on the United States across the Pacific Ocean [1,2]. ASD events are closely correlated with an increase in outpatient visits, admissions and mortality due to the aggravation of respiratory diseases [3-6].
Some researchers studied the correlation between PM10 (particulate matter with aerodynamic diameter <10 μm) exposure and airway diseases. Adamkiewicz et al. [7] suggested that there was a significantly increased risk for pulmonary obstruction after exposure to high concentrations of PM10. Clifford et al. [8] also suggested that geogenic exposure to PM10 could increase pulmonary inflammation and impair pulmonary function, and eventually exacerbate responses to respiratory virus infections.
There are still few studies regarding the effect of ASD on the clinical course of allergic disorders. Chang et al. [9] tried to analyze the correlation between the ASD storm and increases in clinic visit due to allergic rhinitis (AR), but found no significant correlation. Several researchers in Japan have tried to evaluate the correlation between ASD event and Japanese cedar pollinosis [10,11].
Since Korea is geographically so close to China, the origin area, we hypothesized that the influence of ASD events would be more significant in Korea than in any other nation. Because indoor allergens such as house dust mites are the most prevalent causative allergens in Korea, the characteristics of Korean patients are likely to differ significantly from those of Japanese ones. However, there are no studies that evaluated the effect of ASD on the clinical course of AR in Korea, to the best of our knowledge.
PM10 (particulate matter with less than a 10 μm aerodynamic diameter) comprises as much as 70% of ASD [12,13]. As PM10 is so tiny, it could directly infiltrate the upper and lower airway.
Therefore, we aimed to evaluate the effect of PM10 on the clinical course of AR by assessing: (1) the degree and change of nasal symptoms and (2) peak nasal inspiratory flow (PNIF) measured by peak flowmetry and their variability during 120-day period in patients with AR.
We planned to enroll 150 healthy volunteers and another 150 patients with allergic rhinitis before the beginning of ASD season (from October 1, 2011 through January 31, 2012). We enrolled 47 healthy volunteers with no nasal symptoms and negative results on the skin prick test (SPT) (group A, 19 males and 28 females, mean 25.4 years old). We enrolled another 108 patients who had suffered allergic rhinitis for more than 1 year (group B, 58 males and 50 females, mean 20 years old) between October 2011 and January 2012. All healthy volunteers and patients were living in Incheon city. Demographic variables such as gender and age were not significantly different between groups. In group B, the proportion of patients with mild, persistent disease according to the Allergic Rhinitis Impact on Asthma (ARIA) classification was 69.5%. We diagnosed allergic rhinitis if a patient had typical symptoms of allergic rhinitis and his SPT results were strongly positive to house dust mite (Dermatophagoides pteronyssinus and/or Dermatophagoides farinae, size of wheal larger than that of histamine). We performed the SPT using more than 40 antigens, including house dust mite, fungi, pet animals like cats and dogs, tree or weed pollens, and cockroaches (Lofarma, Milan, Italy). We excluded subjects who had used any anti-allergic drugs within 1 month, those with positive results to any allergens other than house dust mites, patients with unstable systemic disease, pregnant or lactating women, those who had nasal surgery within the past 3 months, and those with exposure to chemical irritants or smoking. We also excluded those with chronic rhinosinusitis and/or nasal polyposis upon nasal endoscopic examination.
Before enrollment, we obtained written informed consent from all patients after a full explanation about the aim of this study, and the study was approved by the Gachon University Gil Medical Center and Inha University Institutional Review Board Committee on Studies Involving Human Beings (IUH-IRB 11-2456).
All patients and healthy volunteers completed a daily symptom diary for consecutive 120 days (from February 1st to May 30th, 2012). They recorded their daily symptom score for nasal obstruction according to a modified 6-point Likert scale (from 0 [absolutely no discomfort] to 5 [the most troublesome]) [14]. Patients who needed anti-allergic medication used it and reported this using a diary (0, no medication; 1, oral anti-histamines; 2, intra-nasal steroids; and 3, oral corticosteroids). There was no loss of follow-up during the study period.
All subjects also measured PNIF daily using portable nasal inspiratory flow meter (Clement Clarke International Ltd., Harlow, UK). They were asked to breathe in with their maximal effort with masks firmly attached to their face. Subjects recorded their PNIF (L/min) twice a day, at the same time of the day.
We measured PM10 concentrations for 120 consecutive days (from February 1st to May 30th, 2012) in 15 areas in Incheon, Korea with help from Environmental Health Center for Allergic Rhinitis, Inha University Hospital. The mean value of 15 PM10 concentrations was defined as PM10 concentration of that day.
We used SAS ver. 9.3 (SAS Institute, Cary, NC, USA) for all statistical analyses. We used a mixed regression model in evaluate the association between daily allergic symptoms and the PM10 concentration for each day, correcting within-subject covariance using a 1st-order autoregressive covariance structure. We also used linear correlation analysis. All data was expressed as mean±standard deviation and the P-value<0.05 was considered as statistically significant.
The concentration of PM10 throughout the study period was significantly below 200 μg/m3 (cf. the criteria for yellow-dust warning: which is above 400 μg/m3). There was no definite correlation between PM10 concentration and each nasal symptoms during the study period (P>0.05) (Table 1).
Throughout the 120-day period, we found 3 ‘dusty’ days when PM10 concentration was above 100 μg/m3 (February 24th, 105.53 μg/m3; March 29th, 139.8 μg/m3; May 5th, 116.13 μg/m3). We compared each nasal symptoms 2 days before and 3 days after these ‘dusty’ days, and group A (healthy volunteers) and group B (allergic group) had no significant aggravation of nasal symptoms (P>0.05).
There was no definite correlation between PM10 concentration and daily PNIF (measured in the afternoon) during the study period (P>0.05) (Table 2). We compared PNIF values 2 days before and after ‘dusty’ days (February 24th, March 29th, and May 5th), group A (healthy volunteers) and group B (allergic group) had no significant aggravation of nasal symptoms (P>0.05).
When we defined PNIF variability as: (the difference between morning PNIF and afternoon PNIF)/(mean PNIF)×100%, PNIF variability significantly decreased as the PM10 concentration was increased (P=0.041) (Table 3).
We did not identify a significant correlation between the PM10 concentration and nasal symptoms of AR patients in this study. In fact, Chang et al. [9] tried to evaluate the association between ASD storm events and increases in daily clinic visits in Taiwan. However, they also failed to find any significant correlation [9]. The most important reason for our negative finding is the relatively low PM10 concentration (below 150 μg/m3) throughout the 120-day period. This lower PM10 concentration may be insufficient to provoke any symptoms. Although we set 3 ‘dusty’ days, 2 of them were below the criteria for ‘particulate matter warning’ (criteria for warning is daily concentration above 120 μg/m3 or above 200 μg/m3 for 2 consecutive hours in Korea).
Furthermore, as we enrolled patients when they visited the clinic while suffering from symptoms of AR, their symptoms were already moderate to severe. Therefore, aggravation of symptoms by PM10 could be masked by the more powerful influence of causative allergens (house dust mites, in our study). Ogi et al. [10] suggested that in patients with Japanese cedar pollinosis, patients suffered from aggravated symptoms before the pollen season. However, during the pollen season, they reported no difference in their symptom in spite of ASD event. Therefore, further studies should be designed to enroll symptom-free patients with formerly diagnosed AR.
PNIF has many advantages in that it is non-invasive, inexpensive, and easy to perform. Furthermore, its results are quite well correlated with those of rhinomanometry, and with subjective feeling of patients about their nasal patency [15-19]. Cho et al. [20] suggested that as PNIF had good reproducibility, it could be used in various epidemiologic studies that evaluate the effect of air pollutants on the upper and lower airway. To the best of our knowledge, this is the first study which evaluated the effect of PM10 on the clinical course of AR using objective parameters such as PNIF. However, PNIF showed no significant differences according to the concentration of PM10. Considering that PNIF is well-correlated with patients’ subject feeling of nasal obstruction [16], it is natural that PNIF was not decreased in patients whose feeling of nasal obstruction was not aggravated. Further studies with higher PM10 concentration and symptom-free AR patients could yield more meaningful results.
In spite of these all negative findings, we found that as the PM10 increased, the variability of PNIF was significantly decreased. This may be due to persistent turbinate hypertrophy as PM10 increases. As the inferior turbinate gets congested consistently, there is little change in the patent nasal airway and less variation of PNIF as a result. Procedures to measure the actual change of dimension and volume of the nasal cavity, such as acoustic rhinometry, could confirm this hypothesis.
The clinical course of AR is also affected by various pollens. In order to minimize the confounding effect of pollens, we selected patients whose skin prick test result was only positive to house dust mites. We excluded any patients who showed a positive result for pollens. Furthermore, we gained information about the concentration of 12 pollens in Incheon, with the help of Incheon City Health Environmental Research Center. When performing statistical analysis, we excluded the effect of pollen concentration as a confounding variable.
One of the limitations in our study is that we did not include other clinical data such as endoscopic findings in the nasal cavity, any accompanying allergic/sinonasal disorders, and/or clinical laboratory findings. And, during the enrollment period, young volunteers and patients had actively participated in this study. Therefore, the mean age of both groups is relatively young. In further study, we hope we will be able to evaluate the effect of PM10 in many different age groups.
In conclusion, low concentration PM10 did not have significant effect on symptoms and PNIF of AR patients.
ACKNOWLEDGMENTS
This research was supported by a fund (2011E3302600) by Research of Korea Centers for Disease Control and Prevention, Cheongju, Korea.
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Table 1.
Table 2.
Effect | Estimate | Standard error | P-value |
---|---|---|---|
Intercept | 74.873 | 11.508 | <0.001 |
Group | –3.972 | 6.153 | 0.520 |
PM10 | –0.003 | 0.012 | 0.818 |
Age | 0.372 | 0.178 | 0.038 |
Sex | –5.054 | 5.765 | 0.382 |