Using spatio-temporal modeling for exposure assessment in an investigation of fine particulate air pollution and cardiovascular mortality

Dabass, Arvind; Talbott, Evelyn O.; Bilonick, Richard A.; Rager, Judith R.; Venkat, Arvind; Marsh, Gary M.; Duan, Chunzhe; Xue, Tao

doi:10.1016/j.envres.2016.08.024

Cited by 26 publications

(12 citation statements)

References 23 publications

(19 reference statements)

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“…We argue that pregnant populations exposed to air pollution should be reclassified as at‐risk populations under the current NAAQS. In non‐gravid human populations, exposure to pollutants such as PM has been associated with increased cardiovascular mortality (Dabass et al, ; Krewski et al, ; Miller et al, ; Pope, Burnett, & Thurston, ) and morbidity, including onset of atrial fibrillation (Lin, Liu, Le, & Hwang, ) and decrease in high density lipoprotein functionality (Ramanathan et al, ). Similarly, ozone exposure has been associated with increased cardiovascular mortality among humans (Cakmak, Hebbern, Vanos, Crouse, & Burnett, ).…”

Section: Introductionmentioning

confidence: 99%

Examining Joint Effects of Air Pollution Exposure and Social Determinants of Health in Defining “At‐Risk” Populations Under the Clean Air Act: Susceptibility of Pregnant Women to Hypertensive Disorders of Pregnancy

Koman¹,

Hogan²,

Sampson³

et al. 2018

World Med & Health Policy

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Pregnant women are uniquely susceptible to adverse effects of air pollution exposure due to vulnerabilities and health consequences during pregnancy (e.g., hypertensive disorders of pregnancy [HDP]) compared to the general population. Because the Clean Air Act (CAA) creates a duty to protect at-risk groups, the regulatory assessment of at-risk populations has both policy and scientific foundations. Previously, pregnant women have not been specially protected in establishing the margin of safety for the ozone and particulate matter (PM) standards. Due to physiological changes, pregnant women can be at greater risk of adverse effects of air pollution and should be considered an at-risk population. Women with preexisting conditions, women experiencing poverty, and groups that suffer systematic discrimination may be particularly susceptible to cardiac effects of air pollutants during pregnancy. We rigorously reviewed 11 studies of over 1.3 million pregnant women in the United States to characterize the relationship between ozone or PM exposure and HDP. Findings were generally mixed, with a few studies reporting a joint association between ozone or PM and social determinants or pre-existing chronic health conditions related to HDP. Adequate evidence associates exposure to PM with an adverse effect of HDP among pregnant women not evident among non-gravid populations.

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Section: Introductionmentioning

confidence: 99%

Examining Joint Effects of Air Pollution Exposure and Social Determinants of Health in Defining “At‐Risk” Populations Under the Clean Air Act: Susceptibility of Pregnant Women to Hypertensive Disorders of Pregnancy

Koman¹,

Hogan²,

Sampson³

et al. 2018

World Med & Health Policy

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show abstract

“…8,12,13 Many health assessment studies showed an association between ambient PM 2.5 levels and their impacts on cardio-respiratory mortality. [14][15][16][17][18] A long-term exposure to ambient PM 2.5 can cause deaths for ischemic heart diseases and chronic obstructive pulmonary diseases. 19,20 The ischemic heart diseases (IHD) is a cardiovascular condition characterized by inability of cardiac muscles to function effectively due to poor blood circulation caused by atherosclerosis.…”

Section: Introductionmentioning

confidence: 99%

Long-term exposure to ambient PM2.5 and impacts on health in Rome, Italy

Amoatey

Sicard

Marco

et al. 2020

Clinical Epidemiology and Global Health

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The aim of this study was to estimate the impact of long-term exposure to PM 2.5 on residents of Rome, Italy in terms of ischemic heart diseases (IHD), chronic obstructive pulmonary diseases (COPD), lung cancer (LC), stroke and the number of working days lost (WDL). Methods: In this study, we estimated human health impacts from long-term exposure to ambient PM 2.5 through application of linear RR and integrated exposure-response (IER) functions and the AirQ + software. Results: In 2014, on average 1189, 348, 43, 301 and 387 cases of IHD, COPD, LC, stroke and WDL, respectively could be avoided in Rome if the annual mean PM 2.5 concentration was reduced from 15.6 to 10.0 μg m −3. In 2014, 27.67% of IHD, 15.9% of COPD, 9.5% of LC, 19.9% of stroke as well as 2.5% of WDL are attributed to the long-term exposure to PM 2.5 concentrations exceeding 10 μg m −3. Conclusion: This may be achieved through adoption of stringent air pollution regulations and sustainable city planning. Increase in urban green infrastructures and improving road transportation will reduce PM 2.5 levels in urban environment, thereby safeguarding human health from air pollution and improving citizens' well-being.

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“…Jost et al [12,13] used an interpolation method to determine the distribution of a forest ecosystem and the water storage layer near the desert; their method can assist groundwater managers to make correct decisions. Park et al [14,15] used the spatiotemporal kriging method to more accurately estimate the spread of air pollutants and the distribution of infectious diseases, adding to omissions in the data collection process.…”

Section: Introductionmentioning

confidence: 99%

Implementation of a Parallel GPU-Based Space-Time Kriging Framework

Zhang

Zheng

Wang

et al. 2018

IJGI

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In the study of spatiotemporal geographical phenomena, the space-time interpolation method is widely applied, and the demands for computing speed and accuracy are increasing. For nonprofessional modelers, utilizing the space-time interpolation method quickly is a challenge. To solve this problem, the classical ordinary kriging algorithm was selected and expanded to a spatiotemporal kriging algorithm. Using the OpenCL framework to integrate central processing unit (CPU) and graphic processing unit (GPU) computing resources, a parallel spatiotemporal kriging algorithm was implemented, and three experiments were conducted in this work to verify the results. The results indicated the following: (1) when the size of the prediction point dataset is consistent, the performance of the method is robust with the increasing size of the observation point dataset; (2) the acceleration effect of the parallel method increases with an increased number of predicted points. Compared with the original sequential program, the implementation of the improved parallel framework showed a 3.23 speedup, which obviously shortens the interpolation time; (3) when cross-validating the temperature data in the Beijing Tianjin Hebei region, the space-time acceleration model provides a better fit than traditional pure space interpolation.

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Using spatio-temporal modeling for exposure assessment in an investigation of fine particulate air pollution and cardiovascular mortality

Cited by 26 publications

References 23 publications

Examining Joint Effects of Air Pollution Exposure and Social Determinants of Health in Defining “At‐Risk” Populations Under the Clean Air Act: Susceptibility of Pregnant Women to Hypertensive Disorders of Pregnancy

Examining Joint Effects of Air Pollution Exposure and Social Determinants of Health in Defining “At‐Risk” Populations Under the Clean Air Act: Susceptibility of Pregnant Women to Hypertensive Disorders of Pregnancy

Long-term exposure to ambient PM2.5 and impacts on health in Rome, Italy

Implementation of a Parallel GPU-Based Space-Time Kriging Framework

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