The Role of Traffic-Related Air Pollution in Neurodegenerative Diseases in Older People: An Epidemiological Perspective

2021 ◽  
Author(s):  
Rachel Tham ◽  
Tamara Schikowski
Keyword(s):  
At Risk ◽  
Air Pollution ◽  
Environmental Factors ◽  
Neurodegenerative Diseases ◽  
Environmental Epidemiology ◽  
Risk Groups ◽  
Air Pollutant ◽  
Pollution Levels ◽  
Health Burdens

Traffic-related air pollution is ubiquitous and almost impossible to avoid. It is important to understand the role that traffic-related air pollution may play in neurodegenerative diseases, such as dementia, Alzheimer’s disease, and Parkinson’s disease, particularly among older populations and at-risk groups. There is a growing interest in this area among the environmental epidemiology literature and the body of evidence identifying this role is emerging and strengthening. This review focuses on the principal components of traffic-related air pollutants (particulate matter and nitrogen oxides) and the epidemiological evidence of their contribution to common neurodegenerative diseases. All studies reported are currently observational in nature and there are mixed findings depending on the study design, assessment of traffic-related air pollutant levels, assessment of the neurodegenerative disease outcome, time period of assessment, and the role of confounding environmental factors and at-risk genetic characteristics. All current studies have been conducted in income-rich countries where traffic-related air pollution levels are relatively low. Additional longer-term studies are needed to confirm the levels of risk, consider other contributing environmental factors and to be conducted in settings where air pollution exposures are higher and at-risk populations reside and work. Better understanding of these relationships will help inform the development of preventive measures and reduce chronic cognitive and physical health burdens (cost, quality of life) at personal and societal levels.

The Role of Traffic-Related Air Pollution on Neurodegenerative Diseases in Older People: An Epidemiological Perspective

2020 ◽  
pp. 1-11
Author(s):  
Rachel Tham ◽  
Tamara Schikowski
Keyword(s):  
At Risk ◽  
Air Pollution ◽  
Environmental Factors ◽  
Neurodegenerative Diseases ◽  
Risk Groups ◽  
Air Pollutant ◽  
The Body ◽  
Design Assessment ◽  
Genetic Characteristics

Traffic-related air pollution is ubiquitous and almost impossible to avoid. It is important to understand the role that traffic-related air pollution may play in neurodegenerative diseases, such as dementia, Alzheimer’s disease, and Parkinson’s disease, particularly among older populations and at-risk groups. There is a growing interest in this area among the environmental epidemiology literature and the body of evidence identifying this role is emerging and strengthening. This review focuses on the principal components of traffic-related air pollutants (particulate matter and nitrogen oxides) and the epidemiological evidence of their contribution to common neurodegenerative diseases. All studies reported are currently observational in nature and there are mixed findings depending on the study design, assessment of traffic-related air pollutant levels, assessment of the neurodegenerative disease outcome, time period of assessment, and the role of confounding environmental factors and at-risk genetic characteristics. All current studies have been conducted in income-rich countries where traffic-related air pollution levels are relatively low. Additional longer-term studies are needed to confirm the levels of risk, consider other contributing environmental factors and to be conducted in settings where air pollution exposures are higher and at-risk populations reside and work. Better understanding of these relationships will help inform the development of preventive measures and reduce chronic cognitive and physical health burdens (cost, quality of life) at personal and societal levels.

scholarly journals TUBE Project: Transport-Derived Ultrafines and the Brain Effects

2021 ◽  
Vol 19 (1) ◽  
pp. 311
Author(s):  
Maria-Viola Martikainen ◽  
Päivi Aakko-Saksa ◽  
Lenie van den Broek ◽  
Flemming R. Cassee ◽  
Roxana O. Carare ◽  
...  
Keyword(s):  
Air Pollution ◽  
Health Effects ◽  
Air Pollutants ◽  
Experimental Studies ◽  
Air Pollutant ◽  
Adverse Health Effects ◽  
Adverse Health ◽  
Organ Systems ◽  
The Brain

The adverse effects of air pollutants on the respiratory and cardiovascular systems are unquestionable. However, in recent years, indications of effects beyond these organ systems have become more evident. Traffic-related air pollution has been linked with neurological diseases, exacerbated cognitive dysfunction, and Alzheimer’s disease. However, the exact air pollutant compositions and exposure scenarios leading to these adverse health effects are not known. Although several components of air pollution may be at play, recent experimental studies point to a key role of ultrafine particles (UFPs). While the importance of UFPs has been recognized, almost nothing is known about the smallest fraction of UFPs, and only >23 nm emissions are regulated in the EU. Moreover, the role of the semivolatile fraction of the emissions has been neglected. The Transport-Derived Ultrafines and the Brain Effects (TUBE) project will increase knowledge on harmful ultrafine air pollutants, as well as semivolatile compounds related to adverse health effects. By including all the major current combustion and emission control technologies, the TUBE project aims to provide new information on the adverse health effects of current traffic, as well as information for decision makers to develop more effective emission legislation. Most importantly, the TUBE project will include adverse health effects beyond the respiratory system; TUBE will assess how air pollution affects the brain and how air pollution particles might be removed from the brain. The purpose of this report is to describe the TUBE project, its background, and its goals.

scholarly journals Application of quantile regression in environmental epidemiology

2019 ◽  
Vol 129 (3) ◽  
pp. 72-74
Author(s):  
Mieczysław Szyszkowicz
Keyword(s):  
Air Pollution ◽  
Environmental Factors ◽  
Quantile Regression ◽  
Negative Relationship ◽  
Environmental Epidemiology ◽  
Ambient Air ◽  
Emergency Department Visits ◽  
Ambient Air Pollution ◽  
Mortality Data ◽  
Weather Factors

Abstract Introduction. Among many problems present in studies evaluating associations between health conditions and exposure to ambient air pollution, there is the correlation between environmental factors. These issues are usually resolved by providing a correlation matrix for the parameters of interest. Aim. To explore correlations between environmental factors. Material and methods. As sample data we use environmental factors presented in Milan mortality data (Italy, 1980-1989) and emergency department visits for asthma in Windsor (Canada, 2004-2010). Here, we propose to use a series of quantile regression evaluations to emphasize and identify dependency among environmental factors. Results. This presentation outlines an important role to investigate the potential correlations among ambient air pollutants, weather factors, and the values of the Canadian Air Quality Health Index (AQHI). In environmental epidemiology studies, these components are usually used in a common statistical model. Their correlations affect the values of the estimated relative risks, odds ratios or other estimated health effects. The presented approach examines associations among the factors as well as changes in correlations along quantiles. The examples used in this study explain various environmental phenomena; for example, the negative relationship between ambient ozone and nitrogen dioxide. Conclusions. By a consequence, this work can aid in further developing policies aimed at reducing the health impacts of air pollution as it allows to identify highly correlated factors in the constructed models.

Air Pollution and Climate Change

2019 ◽  
pp. 1-45 ◽  
Author(s):  
Ashok Kumar ◽  
Hamid Omidvarborna ◽  
Kaushik K. Shandilya
Keyword(s):  
Climate Change ◽  
Air Pollution ◽  
Particulate Matters ◽  
Major Contributor ◽  
Air Contaminants ◽  
Pollution Levels ◽  
State Of The Science ◽  
Fine Particulate Matters ◽  
Emerging Topics

Climate records kept worldwide clearly show that ongoing changes are happening in our eco-systems. Such climate changes include temperature, precipitation, or sea level, all of which are expected to keep changing well into the future, thereby affecting human health, the environment, and the economy. The natural causes by themselves are not able to describe these changes, so to understand these, scientists are using a combination of state-of-the-science measurements and models. Human activities are a major contributor due to the release of different air contaminants through various activities. Air pollution is one case-in-point, a human-made factor that contributes to climate change by affecting the amount of incoming sunlight that is either reflected or absorbed by the atmosphere. An overview of modeling techniques used to relate air quality and climate change is presented. The discussion includes the role of air pollution levels affecting the climate. Emerging topics such as black carbon (BC), fine particulate matters (PMs), role of cook stove, and risk assessment are also covered.

Time series regression to identifying the relationship between air pollution and health in Vietnam

2020 ◽  
Vol 04 (04) ◽  
pp. 40-52
Author(s):  
Thuy Linh Nguyen ◽  
◽  
Tu Le ◽  
Thi Kim Ngan Nguyen ◽  
Thi Bich Lien Nguyen ◽  
...  
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Hospital Admissions ◽  
Environmental Epidemiology ◽  
Ambient Air ◽  
Outcome Data ◽  
Ambient Air Pollution ◽  
Short Term ◽  
Time Series Regression ◽  
Pollution Levels

Time series has been widely used in environmental epidemiology; especially in identifying the short-term associations between ambient air pollution and health outcomes. For both exposure and outcome, data are available at regular time intervals (daily hospital admissions and pollution levels) to explore short-term associations between them. In this article, we described main steps to conduct time series regression and highlighted some key ideas when applying this technique. A sample data was used to investigate short-term association between PM10 and daily hospital admission among children in Hanoi between 2008 and 2016. This analysis was conducted with R software. Keywords: time series, air pollution, short-term effect

Air Pollution and Climate Change

2022 ◽  
pp. 1066-1102
Author(s):  
Ashok Kumar ◽  
Hamid Omidvarborna ◽  
Kaushik K. Shandilya
Keyword(s):  
Climate Change ◽  
Air Pollution ◽  
Particulate Matters ◽  
Major Contributor ◽  
Air Contaminants ◽  
Pollution Levels ◽  
State Of The Science ◽  
Fine Particulate Matters ◽  
Emerging Topics

Climate records kept worldwide clearly show that ongoing changes are happening in our eco-systems. Such climate changes include temperature, precipitation, or sea level, all of which are expected to keep changing well into the future, thereby affecting human health, the environment, and the economy. The natural causes by themselves are not able to describe these changes, so to understand these, scientists are using a combination of state-of-the-science measurements and models. Human activities are a major contributor due to the release of different air contaminants through various activities. Air pollution is one case-in-point, a human-made factor that contributes to climate change by affecting the amount of incoming sunlight that is either reflected or absorbed by the atmosphere. An overview of modeling techniques used to relate air quality and climate change is presented. The discussion includes the role of air pollution levels affecting the climate. Emerging topics such as black carbon (BC), fine particulate matters (PMs), role of cook stove, and risk assessment are also covered.

scholarly journals The role of meteorological conditions and pollution control strategies in reducing air pollution in Beijing during APEC 2014 and Victory Parade 2015

2017 ◽  
Vol 17 (22) ◽  
pp. 13921-13940 ◽  
Author(s):  
Pengfei Liang ◽  
Tong Zhu ◽  
Yanhua Fang ◽  
Yingruo Li ◽  
Yiqun Han ◽  
...  
Keyword(s):  
Air Pollution ◽  
Pollution Control ◽  
Air Pollutants ◽  
Meteorological Parameters ◽  
Control Strategies ◽  
Meteorological Conditions ◽  
Air Pollutant ◽  
Pollutant Concentrations ◽  
Air Pollutant Concentrations

Abstract. To control severe air pollution in China, comprehensive pollution control strategies have been implemented throughout the country in recent years. To evaluate the effectiveness of these strategies, the influence of meteorological conditions on levels of air pollution needs to be determined. Using the intensive air pollution control strategies implemented during the Asia-Pacific Economic Cooperation Forum in 2014 (APEC 2014) and the 2015 China Victory Day Parade (Victory Parade 2015) as examples, we estimated the role of meteorological conditions and pollution control strategies in reducing air pollution levels in Beijing. Atmospheric particulate matter of aerodynamic diameter  ≤ 2.5 µm (PM2.5) samples were collected and gaseous pollutants (SO2, NO, NOx, and O3) were measured online at a site in Peking University (PKU). To determine the influence of meteorological conditions on the levels of air pollution, we first compared the air pollutant concentrations during days with stable meteorological conditions. However, there were few days with stable meteorological conditions during the Victory Parade. As such, we were unable to estimate the level of emission reduction efforts during this period. Finally, a generalized linear regression model (GLM) based only on meteorological parameters was built to predict air pollutant concentrations, which could explain more than 70 % of the variation in air pollutant concentration levels, after incorporating the nonlinear relationships between certain meteorological parameters and the concentrations of air pollutants. Evaluation of the GLM performance revealed that the GLM, even based only on meteorological parameters, could be satisfactory to estimate the contribution of meteorological conditions in reducing air pollution and, hence, the contribution of control strategies in reducing air pollution. Using the GLM, we found that the meteorological conditions and pollution control strategies contributed 30 and 28 % to the reduction of the PM2.5 concentration during APEC and 38 and 25 % during the Victory Parade, respectively, based on the assumption that the concentrations of air pollutants are only determined by meteorological conditions and emission intensities. We also estimated the contribution of meteorological conditions and control strategies in reducing the concentrations of gaseous pollutants and PM2.5 components with the GLMs, revealing the effective control of anthropogenic emissions.

scholarly journals The Role of Meteorological Conditions and Pollution Control Strategies in Reducing Air Pollution in Beijing during APEC 2014 and Parade 2015

2017 ◽  
Author(s):  
Pengfei Liang ◽  
Tong Zhu ◽  
Yanhua Fang ◽  
Yingruo Li ◽  
Yiqun Han ◽  
...  
Keyword(s):  
Air Pollution ◽  
Pollution Control ◽  
Meteorological Parameters ◽  
Control Strategies ◽  
Meteorological Conditions ◽  
Air Pollutant ◽  
Pollutant Concentrations ◽  
Air Pollutant Concentrations ◽  
Pm2.5 Concentration

Abstract. To control severe air pollution in China, comprehensive pollution control strategies have been implemented throughout the country in recent years. To evaluate the effectiveness of these strategies, the influence of meteorological conditions on levels of air pollution needs to be determined. We therefore developed a generalized linear regression model (GLM) to establish the relationship between the concentrations of air pollutants and meteorological parameters. Using the intensive air pollution control strategies implemented during the Asia-Pacific Economic Cooperation Forum in 2014 (APEC 2014) and the Victory Parade for the Commemoration of the 70th Anniversary of the Chinese Anti-Japanese War and the World Anti-Fascist War in 2015 (Parade 2015) as examples, we estimated the role of meteorological conditions and pollution control strategies in reducing air pollution levels in Beijing. During the APEC (1 October to 31 December 2014) and Parade (1 August to 31 December 2015) sampling periods, atmospheric particulate matter of aerodynamic diameter ≤ 2.5 μm (PM2.5) samples were collected and gaseous pollutants (SO2, NO, NOx, and O3) were measured online at a site in Peking University (PKU). The concentrations of all pollutants except ozone decreased dramatically (by more than 20 %) during both events, compared with the levels during non-control periods. To determine the influence of meteorological conditions on the levels of air pollution, we first compared the air pollutant concentrations during days with stable meteorological conditions (i.e. when the daily average wind speed (WS) was less than 2.50 m s−1 and planetary boundary layer (PBL) height was lower than 290 m). We found that the average PM2.5 concentration during APEC decreased by 45.7 % compared with the period before APEC and by 44.4 % compared with the period after APEC. This difference was attributed to emission reduction efforts during APEC. However, there were few days with stable meteorological conditions during Parade. As such, we were unable to estimate the level of emission reduction efforts during this period. Finally, GLMs based only on meteorological parameters were built to predict air pollutant concentrations, which could explain more than 70 % of the variation in air pollutant concentration levels, after incorporating the nonlinear relationships between certain meteorological parameters and the concentrations of air pollutants. Evaluation of the GLM performance revealed that the GLM, even based only on meteorological parameters, could be satisfactory to estimate the contribution of meteorological conditions in reducing air pollution, and hence the contribution of control strategies in reducing air pollution. Using the GLM, we found that the meteorological conditions and pollution control strategies contributed 30 % and 28 % to the reduction of the PM2.5 concentration during APEC 2014, and 38 % and 25 % during Parade 2015. We also estimated the contribution of meteorological conditions and control strategies implemented during the two events in reducing the concentrations of gaseous pollutants and PM2.5 components with the GLMs, revealing the effective control of anthropogenic emissions.

scholarly journals Role of atmospheric pollution on the natural history of idiopathic pulmonary fibrosis

Thorax ◽  
2017 ◽  
Vol 73 (2) ◽  
pp. 145-150 ◽  
Author(s):  
Lucile Sesé ◽  
Hilario Nunes ◽  
Vincent Cottin ◽  
Shreosi Sanyal ◽  
Morgane Didier ◽  
...  
Keyword(s):  
Air Pollution ◽  
Natural History ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Disease Progression ◽  
Air Pollutant ◽  
Rapid Decline ◽  
History Of ◽  
The Impact

IntroductionIdiopathic pulmonary fibrosis (IPF) has an unpredictable course corresponding to various profiles: stability, physiological disease progression and rapid decline. A minority of patients experience acute exacerbations (AEs). A recent study suggested that ozone and nitrogen dioxide might contribute to the occurrence of AE. We hypothesised that outdoor air pollution might influence the natural history of IPF.MethodsPatients were selected from the French cohort COhorte FIbrose (COFI), a national multicentre longitudinal prospective cohort of IPF (n=192). Air pollutant levels were assigned to each patient from the air quality monitoring station closest to the patient’s geocoded residence. Cox proportional hazards model was used to evaluate the impact of air pollution on AE, disease progression and death.ResultsOnset of AEs was significantly associated with an increased mean level of ozone in the six preceding weeks, with an HR of 1.47 (95% CI 1.13 to 1.92) per 10 µg/m3 (p=0.005). Cumulative levels of exposure to particulate matter PM10 and PM2.5 were above WHO recommendations in 34% and 100% of patients, respectively. Mortality was significantly associated with increased levels of exposure to PM10 (HR=2.01, 95% CI 1.07 to 3.77) per 10 µg/m3 (p=0.03), and PM2.5 (HR=7.93, 95% CI 2.93 to 21.33) per 10 µg/m3 (p<0.001).ConclusionThis study suggests that air pollution has a negative impact on IPF outcomes, corroborating the role of ozone on AEs and establishing, for the first time, the potential role of long-term exposure to PM10 and PM2.5 on overall mortality.

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