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Special Issue "Morbidity and Mortality Related to Air Pollution and Extreme Temperatures"

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Environmental Health".

Deadline for manuscript submissions: 31 August 2019

Special Issue Editor

Guest Editor
Prof. Dr. Youn-Hee Lim

Institute of Environmental Medicine, Seoul National University College of Medicine, Seoul, Korea
Website | E-Mail
Interests: health effects of air pollution and extreme temperatures

Special Issue Information

Dear Colleagues,

Air pollution and extreme temperatures are the most common consequences of climate change. The health effects of climate change have appeared in many areas, regardless of their location, whether in the south or in the north hemisphere. Therefore, more studies are needed to estimate the health effects and impacts of the exposure to these factors. Novel methods to study health effects may consider new definitions of exposure, additional health outcomes, and novel analytical methods. Previous studies used absolute values of exposure to different factors (e.g., absolute temperature or lagged temperature). However, the variance related to these values in those studies was small. Developing new methods to predict mortality and morbidity will improve the preventive strategies. Defining susceptible populations—by evaluating pre-exiting health conditions, socioeconomic status, or other factors—and newly identified diseases due to air pollution and extreme temperatures may be considered. In addition, more studies are needed to develop novel methods to assess the health impact of the exposure to air pollution and extreme temperatures. A comparison with traditional techniques may be carried out. Various approaches, including disability-adjusted life expectancy (DALY) and attributable mortality counts or fraction, may be employed. Papers addressing novel methods for the study of the health effects of air pollution and extreme temperatures are invited for this Special Issue.

Prof. Dr. Youn-Hee Lim
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Air pollution
  • Health impact assessment
  • Health effects
  • Meteorology
  • Mortality
  • Morbidity
  • Temperature

Published Papers (3 papers)

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Research

Open AccessArticle
Value Assessment of Health Losses Caused by PM2.5 Pollution in Cities of Atmospheric Pollution Transmission Channel in the Beijing–Tianjin–Hebei Region, China
Int. J. Environ. Res. Public Health 2019, 16(6), 1012; https://doi.org/10.3390/ijerph16061012
Received: 24 January 2019 / Revised: 15 March 2019 / Accepted: 18 March 2019 / Published: 20 March 2019
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Abstract
A set of exposure–response coefficients between fine particulate matter (PM2.5) pollution and different health endpoints were determined through the meta-analysis method based on 2254 studies collected from the Web of Science database. With data including remotely-sensed PM2.5 concentration, demographic data, [...] Read more.
A set of exposure–response coefficients between fine particulate matter (PM2.5) pollution and different health endpoints were determined through the meta-analysis method based on 2254 studies collected from the Web of Science database. With data including remotely-sensed PM2.5 concentration, demographic data, health data, and survey data, a Poisson regression model was used to assess the health losses and their economic value caused by PM2.5 pollution in cities of atmospheric pollution transmission channel in the Beijing–Tianjin–Hebei region, China. The results showed the following: (1) Significant exposure–response relationships existed between PM2.5 pollution and a set of health endpoints, including all-cause death, death from circulatory disease, death from respiratory disease, death from lung cancer, hospitalization for circulatory disease, hospitalization for respiratory disease, and outpatient emergency treatment. Each increase of 10 μg/m3 in PM2.5 concentration led to an increase of 5.69% (95% CI (confidence interval): 4.12%, 7.85%), 6.88% (95% CI: 4.94%, 9.58%), 4.71% (95% CI: 2.93%, 7.57%), 9.53% (95% CI: 6.84%, 13.28%), 5.33% (95% CI: 3.90%, 7.27%), 5.50% (95% CI: 4.09%, 7.38%), and 6.35% (95% CI: 4.71%, 8.56%) for above-mentioned health endpoints, respectively. (2) PM2.5 pollution posed a serious threat to residents’ health. In 2016, the number of deaths, hospitalizations, and outpatient emergency visits induced by PM2.5 pollution in cities of atmospheric pollution transmission channel in the Beijing–Tianjin–Hebei region reached 309,643, 1,867,240, and 47,655,405, respectively, accounting for 28.36%, 27.02% and 30.13% of the total number of deaths, hospitalizations, and outpatient emergency visits, respectively. (3) The economic value of health losses due to PM2.5 pollution in the study area was approximately $28.1 billion, accounting for 1.52% of the gross domestic product. The economic value of health losses was higher in Beijing, Tianjin, Shijiazhuang, Zhengzhou, Handan, Baoding, and Cangzhou, but lower in Taiyuan, Yangquan, Changzhi, Jincheng, and Hebi. Full article
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Open AccessArticle
Comparison of Frequentist and Bayesian Generalized Additive Models for Assessing the Association between Daily Exposure to Fine Particles and Respiratory Mortality: A Simulation Study
Int. J. Environ. Res. Public Health 2019, 16(5), 746; https://doi.org/10.3390/ijerph16050746
Received: 1 January 2019 / Revised: 25 February 2019 / Accepted: 26 February 2019 / Published: 1 March 2019
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Abstract
Objective: To compare the performance of frequentist and Bayesian generalized additive models (GAMs) in terms of accuracy and precision for assessing the association between daily exposure to fine particles and respiratory mortality using simulated data based on a real time-series study. Methods: [...] Read more.
Objective: To compare the performance of frequentist and Bayesian generalized additive models (GAMs) in terms of accuracy and precision for assessing the association between daily exposure to fine particles and respiratory mortality using simulated data based on a real time-series study. Methods: In our study, we examined the estimates from a fully Bayesian GAM using simulated data based on a genuine time-series study on fine particles with a diameter of 2.5 μm or less (PM2.5) and respiratory deaths conducted in Shanghai, China. The simulation was performed by multiplying the observed daily death with a random error. The underlying priors for Bayesian analysis are estimated using the real world time-series data. We also examined the sensitivity of Bayesian GAM to the choice of priors and to true parameter. Results: The frequentist GAM and Bayesian GAM show similar means and variances of the estimates of the parameters of interest. However, the estimates from Bayesian GAM show relatively more fluctuation, which to some extent reflects the uncertainty inherent in Bayesian estimation. Conclusions: Although computationally intensive, Bayesian GAM would be a better solution to avoid potentially over-confident inferences. With the increasing computing power of computers and statistical packages available, fully Bayesian methods for decision making may become more widely applied in the future. Full article
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Open AccessArticle
Effects of Cardiorespiratory Exercise on Cognition in Older Women Exposed to Air Pollution
Int. J. Environ. Res. Public Health 2019, 16(2), 245; https://doi.org/10.3390/ijerph16020245
Received: 12 December 2018 / Revised: 8 January 2019 / Accepted: 12 January 2019 / Published: 16 January 2019
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Abstract
The aim was to analyze the effects of cardiorespiratory exercise and air pollution on cognition and cardiovascular markers in four groups of older women: the active/clean air group (AC), the active/polluted air group (AP), the sedentary/clean air group (SC), and the sedentary/polluted air [...] Read more.
The aim was to analyze the effects of cardiorespiratory exercise and air pollution on cognition and cardiovascular markers in four groups of older women: the active/clean air group (AC), the active/polluted air group (AP), the sedentary/clean air group (SC), and the sedentary/polluted air group (SP). Active groups performed a training task based on progressive walking. Prior to and after the experiment, the following parameters were assessed: cognition, by Mini Mental State Examination (MMSE); maximum oxygen uptake (VO2max), estimated by the Six-Minute Walk Test (6mWT); heart rate (HR); and oxygen saturation (SpO2). There were significant differences (p < 0.05) between the AC and the SP in all the MMSE dimensions except “Registration”, and in all the physiological variables (VO2max, SpO2, HR). Aerobic exercise may be a protective factor against the effects that pollution have on cognition and on the mechanisms of oxygen transport. Full article
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Int. J. Environ. Res. Public Health EISSN 1660-4601 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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