Evaluation of the association between pollen count and the outbreak of allergic disease

Ha-Na Kang; Hey Suk Yun; Young-Jin Choi; Jae-Won Oh; Ui-Young Min; Yoon-Sook Heo; Young-Seop Lee; Mijin Kim; Kyu Rang Kim; Baek-Jo Kim

doi:10.4168/aard.2016.4.6.415

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Kang, Yun, Choi, Oh, Min, Heo, Lee, Kim, Kim, and Kim: Evaluation of the association between pollen count and the outbreak of allergic disease

Original Article

Allergy, Asthma & Respiratory Disease 2016; 4(6): 415-422.

Published online: 30 November 2016

DOI: https://doi.org/10.4168/aard.2016.4.6.415

Evaluation of the association between pollen count and the outbreak of allergic disease

Ha-Na Kang¹, Hey Suk Yun¹, Young-Jin Choi¹, Jae-Won Oh¹

, Ui-Young Min², Yoon-Sook Heo², Young-Seop Lee², Mijin Kim³, Kyu Rang Kim³, Baek-Jo Kim³

¹Department of Pediatrics, Hanyang University College of Medicine, Seoul, Korea.

²Department of Statistics, Dongguk University, Seoul, Korea.

³Applied Meteorology Research Division, National Institute of Meteorological Research, Seogwipo, Korea.

Correspondence to: Jae-Won Oh. Department of Pediatrics, Hanyang University Guri Hospital, Hanyang University College of Medicine, 153 Gyeongchun-ro, Guri 11923, Korea. Tel: +82-31-560-2254, Fax: +82-31-552-9493, jaewonoh@hanyang.ac.kr

Received 18 May 2016 Revised 21 August 2016 Accepted 6 September 2016

(open-access):

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/).

Abstract

Purpose

This study focused on the evaluation of the relation between pollen concentration and the outbreak of allergic disease (symptom index), and this outcome would be necessary to upgrade risk grade for the pollen forecasting system.

Methods

Airborne particles carrying allergens, such as pollen, were collected daily at the Seoul and Guri area by using 7-day Burkard samplers for 6 years. A total of 596 Subjects were recruited from Hanyang University Seoul Hospital (n=144 for spring, n=139 for autumn), and Hanyang University Guri Hospital (n=157 for spring, n=156 for autumn). Symptom index was evaluated and recorded by phone calling to study subjects daily or asking questionnaire when they visit outpatient clinic every week. Statistical analysis of data was performed by using correlation coefficients and regression models with time series graph.

Results

Two peak seasons of pollen concentration were May and September in Korea. In skin prick tests, the sensitization rate to ragweed pollen was gradually increased in children. In the same period, sensitization rates to airborne pollen, especially oak, birch for spring, and Japanese hop for autumn were increased annually. There was a significantly relationship between symptom index of allergic patients and allergic pollen concentrations in this study. Especially symptom index was significantly correlated to the concentration of oak pollen of day 1 in spring and to the concentration of Japanese hop pollen of day 0 in autumn.

Conclusion

Sensitization rates to pollens increased annually. There is a significant relationship between allergy symptom index and pollen concentration. There remains to confirm the Korean own risk grade of pollen allergy.

Keywords: Pollen, Pollen allergy, Risk grade, Symptom index

Figures and Tables

Fig. 1

Sensitization rate to allergy pollen in this study (2010–2015).

Fig. 2

The correlation between allergic pollen count and symptom (Sx) index in Seoul (1. March to 15. November 2013). (A) Allergic pollen of tree, (B) pine pollen, (C) pollen of allergic plants except pine, and (D) allergic pollen of weeds.

Fig. 3

The correlation between allergic pollen count and symptom (Sx) index in Guri (1. March to 15. November 2013). (A) Allergic pollen of tree, (B) pine pollen, (C) pollen of allergic plants except pine, and (D) allergic pollen of weeds.

Table 1

The contents of questionnaire to patients (symptom index)

Question	None	A little	Mild	Moderate	Severe
1. Nasal itching	10	20	30	40	50
2. Sneezing	10	20	30	40	50
3. Nasal obstruction	10	20	30	40	50
4. Rhinorrhea	10	20	30	40	50
5. Usage of antihistamine	50	-	-	-

If patients have usage of antihistamine because of their allergic symptoms, they are given 50 points as considering the severity of symptoms.

Table 2

Correlation coefficient between total spring pollen and symptom index (SI)

	SI	Pollen	Pollen_t-1	Pollen_t-2	Pollen_t-3
SI	1	0.080062	0.024321	−0.00169	0.00573
Pollen	0.080062	1	0.532246	0.387034	0.237386
Pollent_-1	0.024321	0.532246	1	0.534655	0.389724
Pollent_-2	−0.00169	0.387034	0.534655	1	0.542898
Pollent_-3	0.00573	0.237386	0.389724	0.542898	1

t-1 indicates the day before symptoms occurred; t-2 indicates 2 days before symptoms occurred; t-3 indicates 3 days before symptoms occurred.

Table 3

Correlation coefficient between spring pollen and symptom index (SI)

	SI	Birch	Birch_t-1	Birch_t-2	Birch_t-3	Oak	Oak_t-1	Oak_t-2	Oak_t-3	Pine	Pine_t-1	Pine_t-2	Pine_t-3
SI	1	0.061395	0.066825	0.058075	0.070378	0.195226	0.174946	0.144327	0.163774	0.161036	0.105343	0.070997	0.061421
Birch	0.061395	1	0.274508	0.10003	0.004464	0.211534	0.069572	0.000137	−0.00924	0.132264	0.02617	−0.06828	−0.04433
Birch_t-1	0.066825	0.274508	1	0.27321	0.113785	0.078621	0.216363	0.073787	0.00594	−0.02015	0.139731	0.02634	−0.06342
Birch_t-2	0.058075	0.10003	0.27321	1	0.266068	0.070208	0.083126	0.220503	0.079804	−0.02613	−0.01784	0.141236	0.029744
Birch_t-3	0.070378	0.004464	0.113785	0.266068	1	0.023013	0.085982	0.112608	0.239206	−0.04458	−0.06464	−0.03231	0.092283
Oak	0.195226	0.211534	0.078621	0.070208	0.023013	1	0.416302	0.21252	0.143044	0.211599	0.018084	−0.11249	−0.12251
Oak_t-1	0.174946	0.069572	0.216363	0.083126	0.085982	0.416302	1	0.416664	0.213938	0.061582	0.217449	0.020636	−0.10759
Oak_t-2	0.144327	0.000137	0.073787	0.220503	0.112608	0.21252	0.416664	1	0.418006	−0.01575	0.06693	0.222669	0.025066
Oak_t-3	0.163774	−0.00924	0.00594	0.079804	0.239206	0.143044	0.213938	0.418006	1	0.039384	−0.00731	0.077678	0.227809
Pine	0.161036	0.132264	−0.02015	−0.02613	−0.04458	0.211599	0.061582	−0.01575	0.039384	1	0.435787	0.301921	0.203481
Pine_t-1	0.105343	0.02617	0.139731	−0.01784	−0.06464	0.018084	0.217449	0.06693	−0.00731	0.435787	1	0.439696	0.296002
Pine_t-2	0.070997	−0.06828	0.02634	0.141236	−0.03231	−0.11249	0.020636	0.222669	0.077678	0.301921	0.439696	1	0.453492
Pine_t-3	0.061421	−0.04433	−0.06342	0.029744	0.092283	−0.12251	−0.10759	0.025066	0.227809	0.203481	0.296002	0.453492	1

t-1 indicates the day before symptoms occurred; t-2 indicates 2 days before symptoms occurred; t-3 indicates 3 days before symptoms occurred.

Table 4

Correlation coefficient between total fall pollen and symptom index (SI)

	SI	Pollen	Pollen_t-1	Pollen_t-2	Pollen_t-3
SI	1	0.3263	0.3041	0.2527	0.2001
Pollen	0.3263	1	0.5344	0.4647	0.3896
Pollen_t-1	0.3041	0.5344	1	0.5363	0.4663
Pollen_t-2	0.2527	0.4647	0.5363	1	0.5075
Pollen_t-3	0.2001	0.3896	0.4663	0.5075	1

t-1 indicates the day before symptoms occurred; t-2 indicates 2 days before symptoms occurred; t-3 indicates 3 days before symptoms occurred.

Table 5

Correlation coefficient between fall pollen and symptom index (SI)

	SI	RW	RW_t-1	RW_t-2	RW_t-3	AR	AR_t-1	AR_t-2	AR_t-3	JP	JP_t-1	JP_t-2	JP_t-3
SI	1	0.3101	0.2919	0.2593	0.2058	0.1131	0.1004	0.0614	0.0237	0.3355	0.3140	0.2646	0.2202
RW	0.3101	1	0.5259	0.4991	0.4576	0.3095	0.1157	0.1135	0.0807	0.7363	0.4998	0.4642	0.4168
RW_t-1	0.2919	0.5259	1	0.5274	0.5002	0.2040	0.3105	0.1176	0.1147	0.4552	0.7372	0.5012	0.4658
RW_t-2	0.2593	0.4991	0.5274	1	0.5287	0.2231	0.2056	0.3116	0.1186	0.4246	0.4570	0.7383	0.5029
RW_t-3	0.2058	0.4576	0.5002	0.5287	1	0.1534	0.2245	0.2071	0.3120	0.3587	0.4259	0.4581	0.7389
AR	0.1131	0.3095	0.2040	0.2231	0.1534	1	0.3818	0.2308	0.1388	0.4245	0.2257	0.1645	0.1544
AR_t-1	0.1004	0.1157	0.3105	0.2056	0.2245	0.3818	1	0.3831	0.2318	0.1791	0.4259	0.2275	0.1666
AR_t-2	0.0614	0.1135	0.1176	0.3116	0.2071	0.2308	0.3831	1	0.3839	0.1435	0.1812	0.4270	0.2290
AR_t-3	0.0237	0.0807	0.1147	0.1186	0.3120	0.1388	0.2318	0.3839	1	0.0899	0.1444	0.1821	0.4276
JP	0.3355	0.7363	0.4552	0.4246	0.3587	0.4245	0.1791	0.1435	0.0899	1	0.5270	0.4610	0.3946
JP_t-1	0.3140	0.4998	0.7372	0.4570	0.4259	0.2257	0.4259	0.1812	0.1444	0.5270	1	0.5287	0.4625
JP_t-2	0.2646	0.4642	0.5012	0.7383	0.4581	0.1645	0.2275	0.4270	0.1821	0.4610	0.5287	1	0.5297
JP_t-3	0.2202	0.4168	0.4658	0.5029	0.7389	0.1544	0.1666	0.2290	0.4276	0.3946	0.4625	0.5297	1

t-1 indicates the day before symptoms occurred; t-2 indicates 2 days before symptoms occurred; t-3 indicates 3 days before symptoms occurred.

RW, Ragweed; AR, Artemisia; JP, Japanese hop.

References

1. Asher MI, Montefort S, Björkstén B, Lai CK, Strachan DP, Weiland SK, et al. Worldwide time trends in the prevalence of symptoms of asthma, allergic rhinoconjunctivitis, and eczema in childhood: ISAAC Phases One and Three repeat multicountry cross-sectional surveys. Lancet. 2006; 368:733–743.

2. Hwang SH, Jung SY, Lim DH, Son BK, Kim JH, Yang JM, et al. Epidemiology of allergic rhinitis in Korean children. Allergy Asthma Respir Dis. 2013; 1:321–332.

3. Beggs PJ. Impacts of climate change on aeroallergens: past and future. Clin Exp Allergy. 2004; 34:1507–1513.

4. Smith M, Emberlin J. A 30-day-ahead forecast model for grass pollen in north London, United Kingdom. Int J Biometeorol. 2006; 50:233–242.

5. Vázquez LM, Galán C, Domínguez-Vilches E. Influence of meteorological parameters on Olea pollen concentrations in Córdoba (south-western Spain). Int J Biometeorol. 2003; 48:83–90.

6. Kim JH, Oh JW, Lee HB, Kim SW, Chung HL, Kook MH, et al. Evaluation of the association of vegetation of allergenic plants and pollinosis with meteorological changes. Allergy Asthma Respir Dis. 2014; 2:48–58.

7. Oh YC, Kim HA, Kang IJ, Cheong JT, Kim SW, Kook MH, et al. Evaluation of the Relationship between Pollen Count and the Outbreak of Allergic Diseases. Pediatr Allergy Respir Dis. 2009; 19:354–364.

8. Oh JW, Lee HB, Kang IJ, Kim SW, Park KS, Kook MH, et al. The revised edition of korean calendar for allergenic pollens. Allergy Asthma Immunol Res. 2012; 4:5–11.

9. Ariano R, Canonica GW, Passalacqua G. Possible role of climate changes in variations in pollen seasons and allergic sensitizations during 27 years. Ann Allergy Asthma Immunol. 2010; 104:215–222.

10. Garcia-Mozo H, Galan C, Jato V, Belmonte J, de la Guardia C, Fernandez D, et al. Quercus pollen season dynamics in the Iberian peninsula: response to meteorological parameters and possible consequences of climate change. Ann Agric Environ Med. 2006; 13:209–224.

11. Teranishi H, Kenda Y, Katoh T, Kasuya M, Oura E, Taira H. Possible role of climate change in the pollen scatter of Japanese cedar Cryptomeria japonica in Japan. Clim Res. 2000; 14:65–70.

12. Kim JH, Oh JW, Lee HB, Kim SW, Kang IJ, Kook MH, et al. Changes in sensitization rate to weed allergens in children with increased weeds pollen counts in Seoul metropolitan area. J Korean Med Sci. 2012; 27:350–355.

13. Ziska LH, Epstein PR, Schlesinger WH. Rising CO(2), climate change, and public health: exploring the links to plant biology. Environ Health Perspect. 2009; 117:155–158.

14. Wayne P, Foster S, Connolly J, Bazzaz F, Epstein P. Production of allergenic pollen by ragweed (Ambrosia artemisiifolia L.) is increased in CO2-enriched atmospheres. Ann Allergy Asthma Immunol. 2002; 88:279–282.

15. Ziska LH, Gebhard DE, Frenz DA, Faulkner S, Singer BD, Straka JG. Cities as harbingers of climate change: common ragweed, urbanization, and public health. J Allergy Clin Immunol. 2003; 111:290–295.

16. Park HJ, Lee JH, Park KH, Kim KR, Han MJ, Choe H, et al. A six-year study on the changes in airborne pollen counts and skin positivity rates in Korea: 2008-2013. Yonsei Med J. 2016; 57:714–720.

17. Adkinson NF Jr, Middleton E Jr. Middleton's allergy principles and practice. 6th ed. Philadelphia: Mosby;2003.

18. Gonzalez-Barcala FJ, Aboal-Viñas J, Aira MJ, Regueira-Méndez C, Valdes-Cuadrado L, Carreira J, et al. Influence of pollen level on hospitalizations for asthma. Arch Environ Occup Health. 2013; 68:66–71.

19. Feo Brito F, Mur Gimeno P, Carnés J, Fernández-Caldas E, Lara P, Alonso AM, et al. Grass pollen, aeroallergens, and clinical symptoms in Ciudad Real, Spain. J Investig Allergol Clin Immunol. 2010; 20:295–302.

20. Annesi-Maesano I, Rouve S, Desqueyroux H, Jankovski R, Klossek JM, Thibaudon M, et al. Grass pollen counts, air pollution levels and allergic rhinitis severity. Int Arch Allergy Immunol. 2012; 158:397–404.

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ORCID iDs: Jae-Won Oh
https://orcid.org/http://orcid.org/0000-0003-2714-0065
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