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Journal of Peking University (Health Sciences) ›› 2020, Vol. 52 ›› Issue (3): 492-499. doi: 10.19723/j.issn.1671-167X.2020.03.015

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Monitoring metrics for short-term exposure to ambient ozone and pulmonary function and airway inflammation in healthy young adults

Jia-hui CHEN,Da-yu HU,Xu JIA,Wei NIU,Fu-rong DENG,Xin-biao GUO()   

  1. Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing 100191, China
  • Received:2020-02-11 Online:2020-06-18 Published:2020-06-30
  • Contact: Xin-biao GUO E-mail:guoxb@bjmu.edu.cn
  • Supported by:
    National Natural Science Foundation of China(81571130090);National Natural Science Foundation of China(91543112);Beijing Municipal Science and Technology Project(Z171100001417009)

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Abstract:

Objective: To assess the associations of different monitoring metrics for short-term exposure to ambient ozone (O3) with pulmonary function and airway inflammation in healthy young adults.Methods: A total of 97 healthy young college students were recruited and followed in a panel study conducted from December 2017 to June 2018. Each participant underwent 3 follow-up visits, and lung function and fractional exhaled nitric oxide (FeNO) were measured at each visit. Ambient air pollutant concentrations were obtained from the environment monitoring station of Beijing closest to the participant residences, and meteorological data were collected from China Meteorological Data Service Center. Linear mixed-effect models were applied to assess the associations between different monitoring metrics for ambient O3 short-term exposure with pulmonary function or airway inflammation in the healthy young adults.Results: During the study period, the P50 (P25, P75) values for ambient O3 concentration expressed as daily 1-hour maximum (O3-1 h max), daily maximum 8-hour average (O3-8 h max) and 24-hour average (O3-24 h avg) were 102.5 (76.8, 163.0) μg/m3, 91.1 (68.3, 154.3) μg/m3 and 61.6 (36.9, 81.7) μg/m3, respectively. The different monitoring metrics for short-term exposure to ambient O3 were significantly associated with reduced forced expiratory volume in the first second (FEV1) and increased FeNO. An interquartile range (IQR) increase in 6-d moving average of O3-1 h max (IQR=71.5 μg/m3) was associated with a 6.2% (95%CI: -11.8%, -0.5%) decrease in FEV1 and a 63.3% (95%CI: 13.8%, 134.3%) increase in FeNO. An IQR increase in 7-d moving average of O3-8 h max (IQR=62.0 μg/m3) was associated with a 6.2% (95%CI: -11.6%, -0.7%) decrease in FEV1and a 75.5% (95%CI: 19.3%, 158.0%) increase in FeNO. An IQR increase in 5-d moving average of O3-24 h avg (IQR=32.9 μg/m3) was associated with a 3.7% (95%CI: -7.1%, -0.2%) decrease in FEV1and a 25.3% (95%CI: 3.6%, 51.6%) increase in FeNO. There was no significant association between the three monitoring metrics for O3 exposure and peak expiratory flow (PEF).Conclusion: Short-term exposure to ambient O3 was associated with decreased lung function and increased airway inflammation among the healthy young adults, and daily 1-hour maximum was more sensitively to the respiratory effects of O3.

Key words: Ozone, Monitoring metrics, Lung function, Fractional exhaled nitric oxide

CLC Number: 

  • X5

Table 1

Demographic characteristics and health parames for the study participants"

Characteristics Male (n=65) Female (n=32) All (n=97)
x?±s Range x?±s Range x?±s Range
Age/years 24.6±2.0 20-26 23.8±2.7 18-26 24.4±2.2 18-26
BMI/(kg/m3) 25.2±4.0 18.1-33.2 23.6±4.6 17.9-30.8 24.7±4.3 17.9-33.2
FEV1/L 3.6±0.5 2.1-5.4 2.5±0.5 1.3-4.3 3.3±0.8 1.3-5.4
PEF/(L/min) 470.3±133.2 135-755 291.2±83.8 95-521 413.1±145.9 95-755
FeNO/(μg/m3) 19.2±10.7 2.7-68.3 15.1±8.4 1.3-36.2 17.8±10.2 1.3-68.3

Table 2

Data of ambient air pollutants and meteorological parameters in Dec. 2017 to Jun. 2018"

Variables n x?±s P50(P25, P75)
Air pollutants
O3-1 h max/ (μg/m3) 212 121.0±64.6 102.5 (76.8, 163.0)
O3-8 h max/ (μg/m3) 212 109.8±60.1 91.1 (68.3, 154.3)
O3-24 h avg/ (μg/m3) 212 63.8±35.2 61.6 (36.9, 81.7)
NO2/ (μg/m3) 212 50.4±22.8 48.9 (34.5, 63.6)
SO2/ (μg/m3) 212 7.4±5.4 6.1 (3.3, 10.1)
PM2.5/ (μg/m3) 212 54.9±44.2 40.9 (21.8, 72.0)
Meteorological parameters
Temperature/ ℃ 207 9.6±11.8 5.5 (-0.9, 20.6)
Relative humidity/ % 207 41.2±15.9 38 (28.5, 51.0)

Table 3

Spearman correlation coefficients between ambient air pollutants and meteorological parameters during study period"

O3-1 h max O3-8 h max O3-24 h avg NO2 SO2 PM2.5 Temperature Relative humidity
O3-1 h max 1
O3-8 h max 0.97# 1
O3-24 h avg 0.87# 0.90# 1
NO2 0.00 -0.08 -0.37# 1
SO2 -0.21# -0.28# -0.41# 0.65# 1
PM2.5 0.24# 0.17* 0.04 0.73# 0.56# 1
Temperature 0.85# 0.86# 0.72# 0.07 -0.28# 0.27# 1
Relative humidity 0.24# 0.20# 0.06 0.36# 0.12 0.64# 0.35# 1

Figure 1

Estimated changes with 95% confidence intervals in pulmonary function and FeNO percentage deviations (%) associated with an IQR increase of O3 monitoring metrics in single pollutant model Estimated changes were adjusted for age, gender, BMI, long-term time trend, temperature, and relative humidity. Estimated changes with 95% CIs in FEV1, PEF and FeNO associated with an interquartile range (IQR) increase of O3monitoring metrics in single pollutant mixed-effects models.The IQRs of the monitoring metrics were 71.5 μg/m3 for O3-1 h max, 62.0 μg/m3 for O3-8 h max, 32.9 μg/m3 for O3-24 h avg."

Table 4

Estimated changes with 95% confidence intervals in FEV1 and FeNO percentage deviations(%) associated with an IQR increase of O3 monitoring metrics in different pollutant models /%(95%CI)"

Pollutant models O3-1 h max, Avg6 O3-8 h max, Avg7 O3-24 h avg, Avg5
FEV1 Single pollutant -6.2(-11.8, -0.5)* -6.2(-11.6, -0.7)* -3.7(-7.1, -0.2)*
+PM2.5 -6.3(-13.0, 0.3) -5.8(-12.1, 0.5) -3.7(-7.2, -0.2)*
+SO2 -7.6(-13.6, -1.6)* -9.1(-15.3, -2.9)* -3.7(-7.2, -0.2)*
+NO2 -6.3(-12.0, -0.6)* -6.3(-11.8, -0.8)* -4.0(-7.8, -0.3)*
FeNO Single pollutant 63.3(13.8, 134.3)* 75.5(19.3, 158)* 25.3(3.6,51.6)*
+PM2.5 87.7(26.8, 177.7)* 86.1(26.2, 174.3)* 25.2(3.2,51.8)*
+SO2 48.3(0.7, 118.4)* 68.7(10.6, 157.2)* 0.6(-20.1,26.7)
+NO2 60.3(11.2, 131)* 75.7(19.3, 158.7)* 9.5(-14.0,39.5)

Figure 2

Smoothed curve showing changes from mean predicted pulmonary function and FeNO deviation according to O3 at 1 d moving average Estimated changes were adjusted for age, gender, BMI, long-term time trend, temperature, and humidity. Loess Smother was used for curve fitting."

[1] Dales R, Chen L, Frescura AM, et al. Acute effects of outdoor air pollution on forced expiratory volume in 1 s: a panel study of schoolchildren with asthma[J]. Eur Respir J, 2009,34(2):316-323.
doi: 10.1183/09031936.00138908
[2] 邸沂遥. 空气污染对哮喘患者肺功能、FeNO和血清IgE水平的影响[D]. 石家庄: 河北医科大学, 2016.
[3] Sinharay R, Gong J, Barratt B, et al. Respiratory and cardiovascular responses to walking down a traffic-polluted road compared with walking in a traffic-free area in participants aged 60 years and older with chronic lung or heart disease and age-matched healthy controls: a randomised, crossover study[J]. Lancet, 2018,391(10118):339-349.
doi: 10.1016/S0140-6736(17)32643-0 pmid: 29221643
[4] Yoda Y, Otani N, Sakurai S, et al. Acute effects of summer air pollution on pulmonary function and airway inflammation in healthy young women[J]. J Epidemiol, 2014,24(4):312-320.
pmid: 24857953
[5] Bai L, Su X, Zhao D, et al. Exposure to traffic-related air pollution and acute bronchitis in children: season and age as modifiers[J]. J Epidemiol Community Health, 2018,72(5):426-433.
pmid: 29440305
[6] Cohen AJ, Brauer M, Burnett R, et al. Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: an analysis of data from the Global Burden of Diseases Study 2015[J]. Lancet, 2017,389(10082):1907-1918.
doi: 10.1016/S0140-6736(17)30505-6 pmid: 28408086
[7] 崔娟, 王黎君. 1990年与2013年中国大气臭氧污染导致慢性阻塞性肺疾病的疾病负担分析[J]. 中华预防医学杂志, 2016,50(5):391-396.
[8] Guo Y, Zeng H, Zheng R, et al. The association between lung cancer incidence and ambient air pollution in China: a spatiotemporal analysis[J]. Environ Res, 2016,144(Pt A):60-65.
pmid: 26562043
[9] Yang C, Yang H, Guo S, et al. Alternative ozone metrics and daily mortality in Suzhou: the China air pollution and health effects study (CAPES)[J]. Sci Total Environ, 2012,426:83-89.
doi: 10.1016/j.scitotenv.2012.03.036 pmid: 22521098
[10] Tolbert PE, Klein M, Metzger KB, et al. Interim results of the study of particulates and health in Atlanta (SOPHIA)[J]. J Expo Anal Environ Epidemiol, 2000,10(5):446-460.
[11] Li H, Wu S, Pan L, et al. Short-term effects of various ozone metrics on cardiopulmonary function in chronic obstructive pulmonary disease patients: results from a panel study in Beijing, China[J]. Environ Pollut, 2018,232:358-366.
doi: 10.1016/j.envpol.2017.09.030 pmid: 28987568
[12] Bell ML, Dominici F, Samet JM. A meta-analysis of time-series studies of ozone and mortality with comparison to the national morbidity, mortality, and air pollution study[J]. Epidemiology, 2005,16(4):436-445.
doi: 10.1097/01.ede.0000165817.40152.85 pmid: 15951661
[13] Thurston GD, Ito K. Epidemiological studies of acute ozone exposures and mortality[J]. J Expo Anal Environ Epidemiol, 2001,11(4):286-294.
pmid: 11571608
[14] Anderson GB, Bell ML. Does one size fit all? The suitability of standard ozone exposure metric conversion ratios and implications for epidemiology[J]. J Expo Sci Environ Epidemiol, 2010,20(1):2-11.
doi: 10.1038/jes.2008.69 pmid: 18985076
[15] Miller MR, Hankinson J, Brusasco V, et al. Standardisation of spirometry[J]. Eur Respir J, 2005,26(2):319-338.
doi: 10.1183/09031936.05.00034805 pmid: 16055882
[16] ATS/ERS recommendations for standardized procedures for the online and offline measurement of exhaled lower respiratory nitric oxide and nasal nitric oxide, 2005[J]. Am J Respir Crit Care Med, 2005,171(8):912-930.
doi: 10.1164/rccm.200406-710ST pmid: 15817806
[17] 王亭槐. 生理学[M]. 9版. 北京: 人民卫生出版社, 2018: 156.
[18] Adman MA, Hashim JH, Manaf MRA, et al. Associations between air pollutants and peak expiratory flow and fractional exhaled nitric oxide in students[J]. Int J Tuberc Lung Dis, 2020,24(2):189-195.
doi: 10.5588/ijtld.19.0096 pmid: 32127103
[19] 杨克敌. 环境卫生学[M]. 8版. 北京: 人民卫生出版社, 2017: 95.
[20] Huang J, Song Y, Chu M, et al. Cardiorespiratory responses to low-level ozone exposure: the in door ozone study in children (DOSE)[J]. Environ Int, 2019,131:105021.
pmid: 31349208
[21] Altug H, Gaga EO, Dogeroglu T, et al. Effects of ambient air pollution on respiratory tract complaints and airway inflammation in primary school children[J]. Sci Total Environ, 2014,479/480:201-209.
doi: 10.1016/j.scitotenv.2014.01.127
[22] 张嘉尧. 臭氧对人群的急性健康影响研究[D]. 南京: 南京医科大学, 2019.
[23] Zhang J, Sun H, Chen Q, et al. Effects of individual ozone exposure on lung function in the elderly: a cross-sectional study in China[J]. Environ Sci Pollut Res Int, 2019,26(12):11690-11695.
doi: 10.1007/s11356-019-04324-w pmid: 30806931
[24] Devlin RB, Duncan KE, Jardim M, et al. Controlled exposure of healthy young volunteers to ozone causes cardiovascular effects[J]. Circulation, 2012,126(1):104-111.
doi: 10.1161/CIRCULATIONAHA.112.094359 pmid: 22732313
[25] Kariisa M, Foraker R, Pennell M, et al. Short- and long-term effects of ambient ozone and fine particulate matter on the respiratory health of chronic obstructive pulmonary disease subjects[J]. Arch Environ Occup Health, 2015,70(1):56-62.
doi: 10.1080/19338244.2014.932753 pmid: 25136856
[26] 赵丽敏, 马利军. 呼出气一氧化氮检测及临床意义[J]. 中华实用诊断与治疗杂志, 2011,25(5):422-423.
[27] Nickmilder M, de Burbure C, Carbonnelle S, et al. Increase of exhaled nitric oxide in children exposed to low levels of ambient ozone[J]. J Toxicol Environ Health A, 2007,70(3-4):270-274.
doi: 10.1080/15287390600884834 pmid: 17365589
[28] Berhane K, Zhang Y, Linn WS, et al. The effect of ambient air pollution on exhaled nitric oxide in the children’s health study[J]. Eur Respir J, 2011,37(5):1029-1036.
doi: 10.1183/09031936.00081410 pmid: 20947676
[29] Day DB, Xiang J, Mo J, et al. Association of ozone exposure with cardiorespiratory pathophysiologic mechanisms in healthy adults[J]. JAMA Intern Med, 2017,177(9):1344-1353.
doi: 10.1001/jamainternmed.2017.2842 pmid: 28715576
[30] Bell ML, Hobbs BF, Ellis H. Metrics matter: conflicting air quality rankings from different indices of air pollution[J]. J Air Waste Manag Assoc, 2005,55(1):97-106.
doi: 10.1080/10473289.2005.10464596 pmid: 15704544
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