Ambient particulate matter, landscape fire smoke, and emergency ambulance dispatches in Sydney, Australia

doi:10.1016/j.envint.2016.11.018

Environment International

Volume 99, February 2017, Pages 208-212

https://doi.org/10.1016/j.envint.2016.11.018 Get rights and content

Highlights

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Daily emergency ambulance dispatches (EADs) were associated with ambient PM_2.5
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The associations were not different on days affected by landscape fire smoke
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EADs have potential utility in surveillance for the public health impacts of PM_2.5

Abstract

Background

Emergency ambulance dispatches (EAD) are a novel outcome for evaluating the public health impacts of air pollution. We assessed the relationships between ambient particulate matter (PM) from all sources, PM from landscape fire smoke (LFS), and EADs likely to be associated with cardiorespiratory problems in the Sydney greater metropolitan region for an 11-year period from 2004 to 2015.

Methods

EAD codes are assigned at the time of the call to emergency services using standard computer assisted algorithms. We assessed EADs coded as: breathing problems, chest pain, stroke or cerebrovascular accident (stroke), cardiac or respiratory arrest and death (arrest), and heart or defibrillator problems (other heart problems). Using a daily times series study design with a generalized linear Poisson regression model we quantified the association between EAD and daily PM_2.5 from all sources (PM_2.5,all) and PM_2.5 primarily due to LFS (PM_2.5,LFS).

Results

Increases of 10 μg·m^− 3 in PM_2.5,all were positively associated with same day EAD for breathing problems (RR = 1.03, 95% CI 1.02 to 1.04), arrest (RR = 1.03, 95% CI 1.00 to 1.06), and chest pain (RR = 1.01 CI 1.00 to 1.02) but not with other outcomes. Increases of 10 μg·m^− 3 PM_2.5,LFS were also positively associated with breathing problems on the same day (RR = 1.04, 95% CI 1.02 to 1.05) and other heart problems at lag of two days (RR = 1.05, 95% CI 1.01 to 1.09).

Conclusions

Emergency dispatches for breathing problems are associated with PM_2.5,all and PM_2.5,LFS and provide a sensitive end point for continued research and surveillance activities investigating the impacts of daily fluctuations in ambient PM_2.5.

Introduction

The association between ambient particulate matter (PM) and adverse health outcomes has been clearly established, yet evidence gaps remain. For example, the relative impacts of particles from different sources are still under active investigation, and some health outcomes have not been well characterised because relevant datasets are not readily available to researchers (Englert, 2004, Davidson et al., 2005, Pope and Dockery, 2006).

Sources of PM include traffic, industrial emissions, re-suspension of dust, sea salt, atmospheric formation of secondary particles, and biomass burning. The contribution of each source to the total PM concentration varies both spatially and temporally (Belis et al., 2013). Landscape fire smoke (LFS) is a major source of PM_2.5 (PM less than 2.5 μm in aerodynamic diameter) in many areas, with a global estimate of 340,000 premature deaths attributable to LFS each year (Johnston et al., 2012). However, studying the population health impacts of LFS is challenging for many reasons: (1) episodes of LFS are typically unpredictable and short-lived; (2) the spatial and temporal distributions of smoke impacts are much different from those of PM from other, well-monitored sources; (3) the exposure affects densely populated urban areas and sparsely populated rural areas; and (4) severe smoke events can cause much higher peak concentration than PM from other sources.

Many studies of LFS exposure have examined its association with emergency room visits, hospital admissions, or mortality. However, these data are not ideal for capturing the spatial and temporal variations in health status that might be associated with LFS, because the exposure location is not accurately geolocated and/or time-stamped. Furthermore, these data are typically not available in near-real-time, which limits their utility for public health surveillance of air quality events. Emergency ambulance dispatches (EAD) are systematically collected, centrally logged, geolocated, and time-stamped, making them potentially useful for both retrospective research and prospective surveillance related to LFS exposures. However, the utility of these data has been relatively unexplored with respect to air pollution, while they have been used in research and surveillance related to injuries and outbreak of infectious disease (Mostashari et al., 2003, Schuurman et al., 2008).

A limited number of studies published to date suggest that data collected by ambulance services, including EAD codes, paramedic assessment codes, and specific clinical data could be endpoints sensitive to ambient air quality. For example, Michikawa et al. (2014) and Zauli Sajani et al. (2014) observed a positive association between increased PM and EAD for non-traumatic causes, especially for respiratory causes. Youngquist et al. (2016) found associations between ambient PM_2.5 and diabetic symptoms and fainting. More specifically, Dennekamp et al. (2015), Haikerwal et al. (2015) examined data from the cardiac arrest registry of the Victorian Ambulance Service and identified clear positive associations between LFS, PM_2.5 and out-of-hospital cardiac arrests. In this study we aimed to (1) evaluate the sensitivity of different EAD codes to ambient PM_2.5 from all sources (PM_2.5,all) and ambient PM_2.5 predominantly derived from LFS (PM_2.5,LFS) and (2) quantify the association between PM_2.5,all and PM_2.5,LFS with dispatch codes most likely to be associated with cardiovascular or respiratory problems.

Section snippets

Study population and outcome data

Sydney, the capital of the state of New South Wales (NSW), is the largest city in Australia with a population of approximately 4.9 million in the greater Sydney metropolitan region. We received EAD data from the Ambulance Service of NSW for 1 January 2004 through 31 December 2014. Information extracted from the EAD included the date and time of the call, geographical coordinates of the event, and the reason for the call. Calls were recorded following the Medical Priority Dispatch System (MPDS),

Results

A total of 86 LFS days were detected during the whole study period, with about 70% occurring from September through to December. On average, LFS events occurred on days with relatively higher temperatures and lower RH. The average daily PM_2.5 concentrations on LFS and non-LFS days were 16.4 μg·m^− 3 and 6.8 μg·m^− 3, respectively (Table 1).

Breathing problems and chest pain were the most common reasons for ambulance dispatches codes evaluated, with averages of approximately 100 and 70 dispatches per

Discussion

We found that PM_2.5,all and PM_2.5,LFS were associated with EAD for breathing problems on the same and following day, and with other heart problems at a lag of two days. PM_2.5,all was also associated with same day arrest and chest pain. Results for PM_2.5 related to LFS were generally similar to those for PM_2.5 from all sources. The confidence intervals associated with the PM_2.5,LFS were wider, especially for the less frequent EAD codes of stroke, other heart problems, and arrest. These

Conclusions

In this work EAD data were analysed in a time series study design to assess the effects of PM_2.5 from all sources and PM_2.5 primarily due to LFS on human health. We have shown that emergency dispatches for breathing problems, other heart problems, chest pain and cardiac arrest may be sensitive end points for continued research and surveillance activities investigating the impacts of ambient PM_2.5.

Acknowledgments

This work was supported by the Australian Research Council (ARC) through project grants LP130100146 and DE130100924. We would also like to thank Ambulance Service of NSW, NSW Office of Environment and Heritage and NSW Environment Protection Authority (EPA) for providing us with EAD, air quality and meteorological data.

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Ambient particulate matter, landscape fire smoke, and emergency ambulance dispatches in Sydney, Australia

Highlights

Abstract

Background

Methods

Results

Conclusions

Introduction

Section snippets

Study population and outcome data

Results

Discussion

Conclusions

Acknowledgments

Atmos. Environ.

Toxicol. Lett.

Environ. Res.

Epidemiological time series studies of PM2.5 and daily mortality and hospital admissions: a systematic review and meta-analysis

Thorax

Dispatcher recognition of stroke using the National Academy Medical Priority Dispatch System

Stroke

Profile of emergency medical dispatch calls for breathing problems within the medical priority dispatch system protocol

Prehosp. Disaster Med.

Airborne particulate matter and human health: a review

Aerosol Sci. Technol.

Outdoor air pollution as a trigger for out-of-hospital cardiac arrests

Epidemiology

Forest fire smoke exposures and out-of-hospital cardiac arrests in Melbourne, Australia: a case-crossover study

Environ. Health Perspect.

Short-term effects of particulate matter on mortality during forest fires in Southern Europe: results of the MED-PARTICLES Project

Occup. Environ. Med.

Sensitivity and specificity of the medical priority dispatch system in detecting cardiac arrest emergency calls in Melbourne

Prehospital and Disaster Medicine

Impact of fine particulate matter (PM2.5) exposure during wildfires on cardiovascular health outcomes

J. Am. Heart Assoc.

Review of receptor modeling methods for source apportionment

J. Air Waste Manage. Assoc.

Epidemiological time series studies of PM_2.5 and daily mortality and hospital admissions: a systematic review and meta-analysis