Short-term associations of ambient air pollution and cause-specific emergency department visits in Guangzhou, China
Graphical abstract
Introduction
An increasing number of studies have documented the elevated risk of cardiovascular diseases linked to the exposure to ambient concentrations of particulate matter (PM) in recent years (Huang et al., 2016, Alessandrini et al., 2013, Kan et al., 2008, Wang et al., 2014). However, with respect to the association between the exposure to PM and the morbidity and mortality of cardiovascular disease, significant heterogeneity in risk estimates were suggested (Alessandrini et al., 2013, Slaughter et al., 2005, Szyszkowicz, 2009, Kloog et al., 2012). In China, recent studies from Beijing city have investigated the effects of elevated concentrations of PM, sulfur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3) on the emergency hospital admissions for diseases such as stroke and hypertension, and identified the adverse health effects of air pollution (Huang et al., 2016, Guo et al., 2010). Another study conducted in three northeastern Chinese cities found significant associations between PM with aerodynamic diameter ≤ 10 μm (PM10) and SO2 levels and stroke prevalence (Dong et al., 2013).
As for southern Chinese cities, several epidemiologic studies examined the effects of ambient air pollutants on daily mortality in Guangzhou (Yu et al., 2012, Yang et al., 2012, Li et al., 2016). These early time-series studies mainly focused daily mortality of diseases as outcome events to examine the adverse health effects of ambient air pollution. However, more precise effect estimates of air pollution exposure on the attack risks of different diseases have been limited by study size and available air quality data in China. Although early air pollution studies conducted in China identified evidence of adverse health effects of air pollution, more refined assessment including analysis of subgroups defined by specific illness or of air pollution components has been limited by routinely available health outcome and air-quality datasets. Hence, the overall epidemiologic evidence of adverse health effects of air pollution based on a relatively large number and high quality of daily air pollution surveillance and health outcome records are needed to enhance our understanding of air pollution–related health effects in China.
Guangzhou, a provincial capital, has a population of roughly 13.5 million in 2015 and one of the most densely populated cities in China. As industrial production and traffic within Guangzhou continue to increase, more people are suffering from shortness of breath, coughing, dizziness and related diseases. Guangzhou is a coastal urban city on the boundary region of the Asian continent and the Pacific Ocean. Waste gas pollution from all kinds of vehicles has become one of the main atmospheric polluters in Guangzhou, and its air pollution levels are generally worse than ambient air quality standards for USA, Hong Kong and European Union (Zhou et al., 2007), posing a serious public health threat for the local residents. In Guangzhou, air pollution components originate from several major emissions, such as motor vehicles, petrochemical, automobile and electronics manufacturing units in the densely industrialized Pearl River Delta region (Verma et al., 2010). However, individual air pollution components responsible for adverse health effects and thorough assessment including analysis of subgroups defined by specific illness have rarely been examined in Guangzhou.
Therefore, this present study aimed to investigate short-term associations between exposures to ambient air pollutants including PM with aerodynamic diameter ≤ 2.5 μm (PM2.5), PM10, O3, SO2 and NO2 and daily cause-specific emergency department visits using a large-scale multicenter database involving a total of 65 sentinel hospitals as monitoring sites in Guangzhou, China, during 2013–2015.
Section snippets
Data
Daily air pollution data on PM2.5, PM10, SO2, NO2 and O3 were obtained from the Daily Quality Report of the Guangzhou Environmental Protection Bureau between January 1, 2013, and December 31, 2015. 24-hour samples of PM2.5, PM10, SO2 and NO2 and 8-hour samples of O3 were collected at 36 general air quality monitoring stations (Fig. 1). Daily 24-hour average concentrations of PM2.5, PM10, SO2 and NO2 and the maximum 8-hour mean concentration of ozone were calculated at the same monitoring
Results
Over the 3-year study period, we identified 97,608 neurologic, 26,400 respiratory and circulatory 38,763 emergency department visits in Guangzhou, which are equivalent to 89 (standard deviation, SD: 13), 24 (SD: 7) and 35 (SD: 8) visits per day, respectively (Table 1). The mean daily average wind speed, relative humidity and temperature were 2.29 m/s, 79.08% and 21.85 °C, respectively. The daily mean level for PM2.5, PM10, SO2, NO2 and O3 was 45.75 μg/m3, 69.16 μg/m3, 18.66 μg/m3, 48.01 μg/m3 and
Discussion
This time-series study of cause-specific emergency department visits provided a rare opportunity to examine associations of an extensive suite of air pollutant exposures with specific neurologic, respiratory and circulatory diseases in Guangzhou, China. This is one of the few studies on short-term effects of ambient air pollutants (PM2.5, PM10, SO2, NO2 and O3) on emergency department visits based on a large-scale multicenter registry database for specific conditions in China so far. In the a
Conclusions
In summary, we found evidence that the exposure to ambient SO2 was significantly associated with emergency department visits for neurologic and circulatory conditions in Guangzhou, the most densely-populated city in south China, in the presence of PMs and other gaseous pollutants, particularly during the cold season. This study lends support to the growing body of literature concerning the adverse effects of ambient SO2, and also provides insight into the planning of clinical services and
Competing interest
The authors declare no conflict of interest.
Author contributions
Conceived of or designed study: PG, WRF and LZ.
Performed research: PG, WRF, MRZ, JYL, WL, YHZ, GFL, YTZ, CYD, TXS, PDL.
Analysed data: PG and WRF.
Wrote the paper: PG, WRF and LZ.
Acknowledgments
We would like to acknowledge the funding of the Science and Technology Plan Projects of Guangzhou (NO. 2014J4100070). We thank all the enrollees who participated in the study. We also thank the Guangzhou Environmental Protection Bureau, the China Meteorological Data Sharing System and Guangzhou Emergency Medical Command Center for providing data used in this study.
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These authors contributed equally in this work and they are co-first authors.