Air Pollution and Mortality in Seven Million Adults: The Dutch Environmental Longitudinal Study (DUELS)

Fischer, Paul; Marra, Marten; Ameling, Caroline; Hoek, Gerard; Beelen, Rob; Hoogh, Kees de; Breugelmans, Oscar; Kruize, Hanneke; Janssen, Nicole; Houthuijs, Danny

doi:10.1289/ehp.1408254

Cited by 206 publications

(154 citation statements)

References 32 publications

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“…After determining the PM 2.5 concentrations at the sampled points, data truncation is necessary because some predicted values may differ substantially from the true values (i.e., the predicted values are outside the predicted data range). The data range is set as 60% of the observed minimum value to 120% of the observed maximum value for each monitoring site (which is applied in [39,45]). …”

Section: Self-adaptive Revised Lur Modelmentioning

confidence: 99%

“…However, the most commonly used predictor variables in LUR models are land use (green land, residential land, and construction land), transportation, water, and terrain data. In addition, researchers [39] have applied POI data, such as restaurant data, crossroads, bus stops, etc. Third, most studies have used linear regressions as prediction models because they are easy to implement.…”

Section: Self-adaptive Revised Lur Modelmentioning

confidence: 99%

“…For example, the LUR was used to determine the association between natural mortality and mortality due to long-term exposure to the elemental components of particulate matter [11]. In addition, a national LUR model was generated to evaluate the associations between long-term exposure to air pollution and non-accidental mortality and the mortality resulting from specific causes in the Netherlands [39].…”

Section: Introductionmentioning

confidence: 99%

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Self-Adaptive Revised Land Use Regression Models for Estimating PM2.5 Concentrations in Beijing, China

Ji-ping

Zongyi

2016

Sustainability

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Heavy air pollution, especially fine particulate matter (PM 2.5 ), poses serious challenges to environmental sustainability in Beijing. Epidemiological studies and the identification of measures for preventing serious air pollution both require accurate PM 2.5 spatial distribution data. Land use regression (LUR) models are promising for estimating the spatial distribution of PM 2.5 at a high spatial resolution. However, typical LUR models have a limited sampling point explanation rate (SPER, i.e., the rate of the sampling points with reasonable predicted concentrations to the total number of sampling points) and accuracy. Hence, self-adaptive revised LUR models are proposed in this paper for improving the SPER and accuracy of typical LUR models. The self-adaptive revised LUR model combines a typical LUR model with self-adaptive LUR model groups. The typical LUR model was used to estimate the PM 2.5 concentrations, and the self-adaptive LUR model groups were constructed for all of the sampling points removed from the typical LUR model because they were beyond the prediction data range, which was from 60% of the minimum observation to 120% of the maximum observation. The final results were analyzed using three methods, including an accuracy analysis, and were compared with typical LUR model results and the spatial variations in Beijing. The accuracy satisfied the demands of the analysis, and the accuracies at the different monitoring sites indicated spatial variations in the accuracy of the self-adaptive revised LUR model. The accuracy was high in the central area and low in suburban areas. The comparison analysis showed that the self-adaptive LUR model increased the SPER from 75% to 90% and increased the accuracy (based on the root-mean-square error) from 20.643 µg/m 3 to 17.443 µg/m 3 for the PM 2.5 concentrations during the winter of 2014 in Beijing. The spatial variation analysis for Beijing showed that the PM 2.5 concentrations were low in the north, especially in the northwest region, and high in the southern and central portions of Beijing. This spatial variation was consistent with the fact that the northern region is mountainous and has fewer people and less traffic, which results in lower air pollution, than in the central region, which has a high population density and heavy traffic. Moreover, the southern region is adjacent to Hebei province, which contains many polluting enterprises; thus, this area exhibits higher air pollution levels than Beijing. Therefore, the self-adaptive revised LUR model is effective and reliable.

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Section: Self-adaptive Revised Lur Modelmentioning

confidence: 99%

Section: Self-adaptive Revised Lur Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Self-Adaptive Revised Land Use Regression Models for Estimating PM2.5 Concentrations in Beijing, China

Ji-ping

Zongyi

2016

Sustainability

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“…Epidemiological studies have shown positive associations between air pollutants such as particulate matter of aerodynamic diameter less than 10 µm (PM 10 ), nitrogen dioxide (NO 2 ), sulphur dioxide (SO 2 ), ozone (O 3 ) and carbon monoxide (CO) and adverse health outcomes (Goldberg et al, 2013;Crouse et al, 2015;Fischer et al, 2015;Liu et al, 2015;Wong et al, 2015;Yorifuji et al, 2016). Many studies have been conducted to assess the health impacts of air pollution in various cities of the world (Boldo et al, 2006;Fattore et al, 2011;Orru et al, 2012;Allen et al, 2013), including Iranian cities (Naddafi et al, 2012a;Gholampour et al, 2014;Ghozikali et al, 2016;Mohammadi et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Estimation of Mortality and Hospital Admissions Attributed to Criteria Air Pollutants in Tehran Metropolis, Iran (2013-2016)

Hadei

Hopke

Nazari

et al. 2017

Aerosol Air Qual. Res.

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Health impact assessments are useful for governmental authorities and decision-makers to determine the need for action and address potential public health problems arising from exposure to air pollution. The present study was conducted to assess the short-term health impacts of ambient air pollution in Tehran using the AirQ 2.2.3 model for March 2013-March 2016. Hourly concentrations of PM 10 , PM 2.5 , O 3 , NO 2 and SO 2 were acquired from the Department of Environment (DOE) and Tehran Air Quality Control Company (TAQCC). Air pollution data was validated according to the USEPA criteria, and only valid monitoring stations for each of the three years were entered to the AirQ 2.2.3 model. The pollutant concentrations were lower in the March 2015-March 2016 period compared to the previous years. The three-year average (± standard deviation) of PM 10 and PM 2.5 concentrations were 80.21 (± 34.21) and 39.17 (± 17.26) µg m -3 , respectively. The three-year averages (± standard deviation) for ozone (O 3 ), nitrogen dioxide (NO 2 ), and sulphur dioxide (SO 2 ) were 54.88 (± 24.15), 103.97 (± 25.88) and 39.84 (± 11.17) µg m -3 , respectively. The total estimated number of deaths attributed to PM 10 , PM 2.5 , O 3 , NO 2 and SO 2 over these three years were 4192, 4336, 1363, 2830, and 1216, respectively. The health impacts attributed to all pollutants except for PM 10 were estimated to decrease in 2016, compared to the prior years. However, the air quality in Tehran still poses significant risks to public health. In conclusion, urgent efforts are needed such as mandating the replacing of old and poorly functioning vehicles from the roadways in order to reduce the health burden that air pollution is currently imposing on this city.

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“…are determined to be associated with different health outcomes. Epidemiological studies have been conducted in various countries to investigate this relationship precisely (4)(5)(6)(7)(8). Particulate matter of 2.5 micrometers or smaller (PM 2.5 ) is a part of particulate matter, but is able to enter the alveolar lung region, a place to exchange the blood.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Gender-Specific Lung Cancer Deaths due to Exposure to PM2.5 in 10 Cities of Iran During 2013 - 2016: A Modeling Approach

et al. 2017

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Background: Various epidemiological studies have related fine particles (PM2.5) to incidence of lung cancer. In addition, particulate air pollution has been classified as Group 1 carcinogen by international agency for research on cancer (IARC) in 2013. Objectives: The aim of this study was to quantify the number of gender-specific lung cancer deaths due to exposure to PM2.5 among individuals aged over 30 years using WHO AirQ+ model in 10 cities of Iran during March 2013-March 2016. Methods: Hourly concentrations of PM2.5 were obtained from department of environment (DOE) of Iran and Tehran air quality control company (TAQCC). Demographic information and baseline incidence (BI) were acquired from statistical center of Iran, ministry of health and medical education, respectively. AirQ+ model was used to quantify the lung cancer deaths among males and females aged over 30 years. Results: The highest lung cancer deaths were in Tehran with approximately 407 cases of death during the whole three-year period. The total deaths among men and women in the whole period were 433 and 431 cases, respectively. The sum of lung cancer deaths due to PM2.5 exposure in all the 10 cities during these 3 years were estimated 864 cases. In addition, the attributable proportion of lung cancer due to PM2.5 exposure in each city was estimated. Despite the high number of lung cancer deaths in Tehran, higher AP values were observed in cities such as Isfahan, Ahvaz, Khoram Abad and Arak, reflecting the higher risk of death per unit of population. Conclusions:The results of this study could be used by authorities for making air pollution reduction strategies and plans. Furthermore, any reduction in attributed mortality and hospitalization reduces financial burden in health organizations.

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Air Pollution and Mortality in Seven Million Adults: The Dutch Environmental Longitudinal Study (DUELS)

Cited by 206 publications

References 32 publications

Self-Adaptive Revised Land Use Regression Models for Estimating PM2.5 Concentrations in Beijing, China

Self-Adaptive Revised Land Use Regression Models for Estimating PM2.5 Concentrations in Beijing, China

Estimation of Mortality and Hospital Admissions Attributed to Criteria Air Pollutants in Tehran Metropolis, Iran (2013-2016)

Estimation of Gender-Specific Lung Cancer Deaths due to Exposure to PM2.5 in 10 Cities of Iran During 2013 - 2016: A Modeling Approach

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