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. 2022 Apr 4:10:865798.
doi: 10.3389/fpubh.2022.865798. eCollection 2022.

Association Between Air Pollutants and Pediatric Respiratory Outpatient Visits in Zhoushan, China

Wen-Yi Liu  1   2   3 , Jing-Ping Yi  4 , Leiyu Shi  1 , Tao-Hsin Tung  5
Affiliations

Association Between Air Pollutants and Pediatric Respiratory Outpatient Visits in Zhoushan, China

Wen-Yi Liu et al. Front Public Health. .

Abstract

Objective: This study aimed to explore the time-series relationship between air pollutants and the number of children's respiratory outpatient visits in coastal cities.

Methods: We used time series analysis to investigate the association between air pollution levels and pediatric respiratory outpatient visits in Zhoushan city, China. The population was selected from children aged 0-18 who had been in pediatric respiratory clinics for eight consecutive years from 2014 to 2020. After describing the population and weather characteristics, a lag model was used to explore the relationship between outpatient visits and air pollution.

Results: We recorded annual outpatient visits for different respiratory diseases in children. The best synergy lag model found a 10 μg/m3 increase in PM2.5 for every 4-10% increase in the number of pediatric respiratory outpatient visits (P < 0.05). The cumulative effect of an increase in the number of daily pediatric respiratory clinics with a lag of 1-7 days was the best model.

Conclusions: PM2.5 is significantly related to the number of respiratory outpatient visits of children, which can aid in formulating policies for health resource allocation and health risk assessment strategies.

Keywords: air pollutant; children; lag pattern; outpatients; respiratory diseases.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Heatmap of spearman correlation coefficients between daily ambient air pollutants.
Figure 2
Figure 2
Relative risk and 95% confidence intervals for daily pediatric respiratory outpatients with per unit increase of PM2.5, PM10, SO2, O3, NO2 and CO in hot, cold, transition seasons. Cold Season: November to March; Hot Season: June to August; Transition Season: April, May, September, and October.
Figure 3
Figure 3
Relative risk and 95% confidence intervals for daily pediatric respiratory outpatients with per unit increase of PM2.5 at different cumulation lag days.
Figure 4
Figure 4
Relative risk for daily pediatric respiratory outpatients with per unit increase of PM2.5 at different cumulation lag days.
See this image and copyright information in PMC

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References

    1. Liu W, Xu Z, Yang T. Health effects of air pollution in China. Int J Environ Res Public Health. (2018) 15:1471. 10.3390/ijerph15071471 - DOI - PMC - PubMed
    1. Huang RJ, Zhang Y, Bozzetti C, Ho KF, Cao JJ, Han Y, et al. . High secondary aerosol contribution to particulate pollution during haze events in China. Nature. (2014) 514:218–22. 10.1038/nature13774 - DOI - PubMed
    1. Yang D, Yang X, Deng F, Guo X. Ambient air pollution and biomarkers of health effect. Adv Exp Med Biol. (2017) 1017:59–102. 10.1007/978-981-10-5657-4_4 - DOI - PubMed
    1. DeVries R, Kriebel D, Sama S. Outdoor air pollution and COPD-Related emergency department visits, hospital admissions, and mortality: a meta-analysis. COPD. (2017) 14:113–21. 10.1080/15412555.2016.1216956 - DOI - PMC - PubMed
    1. Hao Y, Zhao M, Lu ZN. What is the health cost of haze pollution? Evidence from China. Int J Health Plann Manage. (2019) 34:1290–303. 10.1002/hpm.2791 - DOI - PubMed