Spatiotemporal influence of temperature, air quality, and urban environment on cause-specific mortality during hazy days
Introduction
Air pollution has been associated with a heavy burden of mortality and morbidity (Qiu et al., 2014, Shang et al., 2013). During an extreme pollution event, negative changes in air quality can severely increase human health risks (Brook et al., 2016). Previous studies have focused on studying the short-term mortality effects of isolated extreme events, for example, dust storms and wildfire smoke (Crooks et al., 2016, Johnston et al., 2011, Othman et al., 2014, Tobías et al., 2011, Wong et al., 2017). These studies have observed significantly more deaths during extreme events compared to days with baseline air pollution (e.g. traffic-related pollution). However, there have been no studies attempting to investigate the influence of haze on daily mortality, and only a few studies have explored the relationship between haze and morbidity risk (Kunii et al., 2002, Zhang et al., 2014, Zhang et al., 2015), despite the fact that haze is a common meteorological phenomenon that can cause heavy air pollution (Tao et al., 2014). Alternatively, some environmental health studies have used high daily particulate matter concentrations (PM) as a measure of hazy dust (Liu et al., 2014), but such studies cannot separate the health impacts of haze from the other types of air pollution such as wildfire dust events and dust storms. Therefore, those results cannot directly represent the morbidity and mortality risks during a hazy day. In summary, it is necessary to conduct a comprehensive study to estimate the relationship between haze and mortality, in order to target vulnerable populations and high-risk areas for health interventions.
Haze is commonly observed in Asia due to rapid industrialization and urbanization (Huang et al., 2014), and is usually associated with low visibility (Q. Zhang et al., 2015). While the major component of haze can be particulate matters (PM) (Tao et al., 2014), temperature and humidity can also influence a haze event, resulting in lower visibility and higher air pollution on a hazy day (Deng et al., 2016). This complex system of haze formation has been studied from a climatological perspective (Tan et al., 2009, Tao et al., 2014). However, no studies have included this atmospheric interaction in an environmental health study. Previous studies on haze and health have applied simple biostatistical analyses to describe the general health risk of haze (Kunii et al., 2002, Zhang et al., 2014, Zhang et al., 2015). These studies were unable to provide evidence of how interactions between different components of the geophysical environment, such as temperature, ground-level ozone, and the built environment, can enhance the effect of hazy days on mortality risk. In addition, these studies have explored the relationship between haze events and only cardiovascular and respiratory diseases attributable to air pollution. None of them have investigated the relationship between haze and mental disorders, although adverse mental health conditions have been recently found to be associated with extreme weather (Ding et al., 2015, Rataj et al., 2016, Wang et al., 2014).
Therefore, it is essential to develop an innovative study investigating the spatiotemporal influence of temperature, air pollution, and urban environment on haze mortality. The aim of this study is to apply a data-driven technique to comprehensively analyze the short-term mortality risk after a haze event, for the purpose of better developing public health protocols. The specific objectives of this study include: 1) to estimate the short-term cause-specific mortality risk during days with haze; 2) to compare the short-term mortality risk during hazy days with different temperature and air quality, and; 3) to evaluate haze mortality in areas with different urban environments based on delineations of spatial data.
Hong Kong was selected as the setting for this study, due to multiple hazy days having been observed between 2007 and 2014. In addition, the high-density built environment of this city can reduce air ventilation, thereby increasing air pollution across urban areas (Wong et al., 2011).
Section snippets
Temporal data
We obtained mortality data for 2007 to 2014 (inclusive) from the Hong Kong Census and Statistics Department. This mortality dataset includes decedents with the following information: 1) date of death; 2) cause of death classified by the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10), and; 3) the location of residence registered by the 2006 Tertiary Planning Unit (TPU) of Hong Kong. An hourly report of haze was obtained from the
Data summary
After exclusion of all data with a missing death date or missing location of residence, a total of 284,477 decedents were recorded in 2007 through 2014. Based on 50th percentiles of all decedents above, we identified TPUs with average SVF lower than 0.675 as areas with high-density environment (Fig. 1). In addition, TPUs with percentage of vegetation < 49.57%, average anthropogenic heat flux ≥ 52.25 W/M2, and average PM2.5 ≥ 52.05 ppm were the districts with low vegetation cover (Fig. 2), high
Discussion
In this study, we examined the effect of haze on cause-specific mortality in Hong Kong. We found that a regular hazy day (lag 0) has significant association with higher all-cause mortality (OR: 1.029 [1.009, 1.049]). We also found that the effects of haze on short-term mortality varied for days with different temperatures and air quality, and these specific hazy events can particularly affect cause-specific mortality. While a haze event, especially a cold hazy day, significantly increased the
Conclusions
We developed a time series case-only analysis with a spatial delineation approach to examine the effects of different types of haze events on short-term mortality, and the additional effect on mortality during a haze event associated with urban environmental factors. Our study found that haze has significant influences on mortality risk, especially for populations with mental and behavioral disorders or diseases of the nervous system. Our results also indicated that extreme weather can interact
Acknowledgements
We thank Dr. P.W. Chan of Hong Kong Observatory for providing data support to this study. This research was supported in part by a grant from the General Research Fund (Project ID: 15205515); a grant from the Hong Kong Polytechnic University (Grant PolyU 1-ZE24); and a grant PolyU 1-ZVFD from the Research Institute for Sustainable Urban Development, the Hong Kong Polytechnic University. We also thank the support from the Hong Kong Census and Statistics Department, the Hong Kong Environmental
References (66)
- et al.
Short-term effects of air temperature on mortality and effect modification by air pollution in three cities of Bavaria, Germany: a time-series analysis
Sci. Total Environ.
(2014) - et al.
Megacities air pollution problems: Mexico City Metropolitan Area critical issues on the central nervous system pediatric impact
Environ. Res.
(2015) - et al.
Impact of relative humidity on visibility degradation during a haze event: a case study
Sci. Total Environ.
(2016) - et al.
Mortality risk attributable to high and low ambient temperature: a multicountry observational study
Lancet
(2015) Review on urban vegetation and particle air pollution–deposition and dispersion
Atmos. Environ.
(2015)- et al.
Extreme air pollution events from bushfires and dust storms and their association with mortality in Sydney, Australia 1994–2007
Environ. Res.
(2011) - et al.
Ambient air pollution, climate change, and population health in China
Environ. Int.
(2012) - et al.
The Heat Exposure Integrated Deprivation Index (HEIDI): a data-driven approach to quantifying neighborhood risk during extreme hot weather
Environ. Int.
(2017) - et al.
Pollution and skin: from epidemiological and mechanistic studies to clinical implications
J. Dermatol. Sci.
(2014) - et al.
The effects of dust–haze on mortality are modified by seasons and individual characteristics in Guangzhou, China
Environ. Pollut.
(2014)