PM10

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Petr75
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Re: PM10

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2021 Feb 9
College of Medicine, Seoul National University Hospital, Seoul, South Korea
Association of Particulate Matter with Autoimmune Rheumatic Diseases among Adults in South Korea
https://pubmed.ncbi.nlm.nih.gov/33560298/
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Re: PM10

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2021 Feb 6
School of Environmental Science and Engineering, Indian Institute of Technology Kharagpur, India
Association of air pollution and meteorological variables with COVID-19 incidence: Evidence from five megacities in India
https://pubmed.ncbi.nlm.nih.gov/33561448/

Abstract

Although lockdown of the industrial and transport sector and stay at home advisories to counter the COVID-19 pandemic have shown that the air quality has improved during this time, very little is known about the role of ambient air pollutants and meteorology in facilitating its transmission. This paper presents the findings from a study that was conducted to evaluate whether air quality index (AQI), three primary pollutants (PM2.5, PM10 and CO), Ground level ozone (O3) and three meteorological variables (temperature, relative humidity, wind speed) have promoted the COVID-19 transmission in five megacities of India. The results show significant correlation of PM2.5, PM10, CO, O3 concentrations, AQI and meteorological parameters with the confirmed cases and deaths during the lockdown period. Among the meteorological variables considered, temperature strongly correlated with the COVID-19 cases and deaths during the lockdown (r=0.54;0.25) and unlock period (r=0.66;0.25). Among the pollutants, ozone, and among the meteorological variables, temperature, explained the highest variability, up to 34% and 30% respectively, for COVID-19 confirmed cases and deaths. AQI was not a significant parameter for explaining the variations in confirmed and death cases. WS and RH could explain 10-11% and 4-6% variations of COVID-19 cases. A GLM model could explain 74% and 35% variability for confirmed cases and deaths during the lockdown and 66% and 19% variability during the unlock period. The results suggest that meteorological parameters may have promoted the COVID-19 incidences, especially the confirmed cases. Our findings may encourage future studies to explore more about the role of ambient air pollutants and meteorology on transmission of COVID-19 and similar infectious diseases.
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Petr75
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Re: PM10

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2021 Jan 29
Department of Biological and Environmental Sciences and Technology, University of Salento, Lecce, Italy
Early-Life Exposure to Environmental Air Pollution and Autism Spectrum Disorder: A Review of Available Evidence
https://pubmed.ncbi.nlm.nih.gov/33572907/

Abstract

The number of children diagnosed with Autism Spectrum Disorder (ASD) has rapidly increased globally. Genetic and environmental factors both contribute to the development of ASD. Several studies showed linkage between prenatal, early postnatal air pollution exposure and the risk of developing ASD. We reviewed the available literature concerning the relationship between early-life exposure to air pollutants and ASD onset in childhood. We searched on Medline and Scopus for cohort or case-control studies published in English from 1977 to 2020. A total of 20 articles were selected for the review. We found a strong association between maternal exposure to particulate matter (PM) during pregnancy or in the first years of the children's life and the risk of the ASD. This association was found to be stronger with PM2.5 and less evident with the other pollutants. Current evidence suggest that pregnancy is the period in which exposure to environmental pollutants seems to be most impactful concerning the onset of ASD in children. Air pollution should be considered among the emerging risk factors for ASD. Further epidemiological and toxicological studies should address molecular pathways involved in the development of ASD and determine specific cause-effect associations.
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2020 Jan
Jiann-Ping Hsu College of Public Health, Georgia Southern University, USA
Maternal exposure to air pollution and risk of autism in children: A systematic review and meta-analysis
https://pubmed.ncbi.nlm.nih.gov/31733973/
Last edited by Petr75 on Sun Jun 13, 2021 5:30 am, edited 1 time in total.
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Petr75
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Re: PM10

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2021 Feb 12
Department of Neuroscience Rita Levi-Montalcini, University of Turin, Italy; Neuroscience Institute Cavalieri Ottolenghi (NICO), University of Turin, Italy
Exposure to fine particulate matter (PM 2.5) hampers myelin repair in a mouse model of white matter demyelination
https://pubmed.ncbi.nlm.nih.gov/33587955/

Abstract

Epidemiological studies show a strong association between exposure to air pollution - and particularly to particulate matter (PM) -, increased prevalence of Multiple Sclerosis (MS) and higher rates of hospital admissions for MS and MS relapses. Besides having immunomodulatory effects and sustaining a systemic oxidative-inflammatory response, PM may participate in MS pathogenesis by targeting also Central Nervous System (CNS)-specific processes, such as myelin repair. Here we show that, in a mouse model of lysolecithin-induced demyelination of the subcortical white matter, post-injury exposure to fine PM hampers remyelination, disturbs oligodendroglia differentiation dynamics and promotes astroglia and microglia reactivity. These findings support the view that exposure to fine PM can contribute to demyelinating pathologies by targeting the endogenous regenerative capability of the CNS tissue.
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Petr75
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Re: PM10

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2021 Mar 1
Department of Public Health, College of Health Sciences, Kaohsiung Medical University, Taiwan
The Association of White Blood Cells and Air Pollutants-A Population-Based Study
https://pubmed.ncbi.nlm.nih.gov/33804362/

Abstract

The links of air pollutants to health hazards have been revealed in literature and inflammation responses might play key roles in the processes of diseases. WBC count is one of the indexes of inflammation, however the l iterature reveals inconsistent opinions on the relationship between WBC counts and exposure to air pollutants. The goal of this population-based observational study was to examine the associations between multiple air pollutants and WBC counts. This study recruited community subjects from Kaohsiung city. WBC count, demographic and health hazard habit data were collected. Meanwhile, air pollutants data (SO2, NO2, CO, PM10, and O3) were also obtained. Both datasets were merged for statistical analysis. Single- and multiple-pollutants models were adopted for the analysis. A total of 10,140 adults (43.2% males; age range, 33~86 years old) were recruited. Effects of short-term ambient concentrations (within one week) of CO could increase counts of WBC, neutrophils, monocytes, and lymphocytes. However, SO2 could decrease counts of WBC, neutrophils, and monocytes. Gender, BMI, and smoking could also contribute to WBC count increases, though their effects are minor when compared to CO. Air pollutants, particularly SO2, NO2 and CO, may thus be related to alterations of WBC counts, and this would imply air pollution has an impact on human systematic inflammation.


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Petr75
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Re: PM10

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2021 Apr 3
Karunya Institute of Technology and Sciences, Coimbatore, India
Strong link between coronavirus count and bad air: a case study of India
https://pubmed.ncbi.nlm.nih.gov/33841040/

Abstract

The present study aims to highlight the contrast relationship between COVID-19 (Coronavirus Disease-2019) infections and air pollutants for the Indian region. The COVID-19 data (cumulative, confirmed cases and deaths), air pollutants (PM10, PM2.5, NO2 and SO2) and meteorological data (temperature and relative humidity) were collected from January 2020 to August 2020 for all 28 states and the union territory of India during the pandemic. Now, to understand the relationship between air pollutant concentration, meteorological factor, and COVID-19 cases, the nonparametric Spearman's and Kendall's rank correlation were used. The COVID-19 shows a favourable temperature (0.55-0.79) and humidity (0.14-0.52) over the Indian region. The PM2.5 and PM10 gave a strong and negative correlation with COVID-19 cases in the range of 0.64-0.98. Similarly, the NO2 shows a strong and negative correlation in the range of 0.64-0.98. Before the lockdown, the concentration of pollution parameters is high due to the shallow boundary layer height. But after lockdown, the overall reduction was reported up to 33.67% in air quality index (AQI). The background metrological parameters showed a crucial role in the variation of pollutant parameters (SO2, NO2, PM10 and PM2.5) and the COVID-19 infection with the economic aspects. The European Centre for Medium-Range Weather Forecasts derived monthly average wind speed was also plotted. It can see that January and February of 2020 show the least variation of air mass in the range of 1-2 m/s. The highest wind speed was reported during July and August 2020. India's western and southern parts experienced an air mass in the range of 4-8 m/s. The precipitation/wet deposition of atmospheric aerosols further improves the AQI over India. According to a study, the impact of relative humidity among all other metrological parameters is positively correlated with Cases and death. Outcomes of the proposed work had the aim of supporting national and state governance for healthcare policymakers.
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Petr75
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Re: PM10

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2021 Apr 15
Department of Chemistry, University of Milan, Italian Society of Environmental Medicine, (SIMA), Milan, Italy
Improving indoor air quality through an air purifier able to reduce aerosol particulate matter (PM) and volatile organic compounds (VOCs): Experimental Results
https://pubmed.ncbi.nlm.nih.gov/33865819/

Abstract

The adverse effects of fine particulate matter and many volatile organic substances on human health are well known. Fine particles are, in fact, those most capable of penetrating in depth into the respiratory system. People spend most of their time indoors where concentrations of some pollutants are sometimes higher than outdoors. Therefore, there is the need to ensure a healthy indoor environment and for this purpose the use of an air purifier can be a valuable aid especially now since it was demonstrated that indoor air quality has a high impact on spreading of viral infections such as that due to SARS-COVID19. In this study, we tested a commercial system that can be used as an air purifier. In particular it was verified its efficiency in reducing concentrations of PM10 (particles with aerodynamic diameter less than 10 μm), PM2.5 (particles with aerodynamic diameter less than 2.5 μm), PM1 (particles with aerodynamic diameter less than 1 μm), and particle number in the range 0.3 μm -10 μm. Furthermore, its capacity in reducing VOCs (Volatile Organic Compounds) concentration was also checked. PM measurements were carried out by means of a portable optical particle counter (OPC) instrument simulating the working conditions typical of a household environment. In particular we showed that the tested air purifier significantly reduced both PM10 and PM2.5 by 16.8 and 7.25 times respectively that corresponds to a reduction of over 90% and 80%. A clear reduction of VOCs concentrations was also observed since a decrease of over 50% of these gaseous substances was achieved.
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Petr75
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Re: PM10

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2021 Apr 19
Department of Epidemiology and Biostatistics, Zhejiang University School of Public Health, Hangzhou, China
Air pollution, surrounding green, road proximity and Parkinson's disease: a prospective cohort study
https://pubmed.ncbi.nlm.nih.gov/33887274/

Abstract

Background: Though growing evidence has linked air pollution to Parkinson's disease (PD), the results remain inconsistent. Less is known about the relevance of road proximity and surrounding green. We aimed to investigate the individual and joint associations of air pollution, road proximity and surrounding green with the incidence of PD in a prospective cohort study.

Methods: We used data from a prospective cohort of 47,516 participants recruited from July 2015 to January 2018 in Ningbo, China. Long-term exposure to particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5) and ≤10 μm (PM10) and nitrogen dioxide (NO2) estimated by land-use regression models, road proximity and surrounding green assessed by Normalized Difference Vegetation Index (NDVI) were calculated based on the residential address for each participant. Cox proportional hazard models were used to analyze the individual and joint effects of air pollution, road proximity, and surrounding green on PD.

Results: In single-exposure models, PM2.5, PM10, NO2 and road proximity was associated with increased risk of PD (e.g. Hazard Ratio (HR)=1.51, 95%CI:1.02, 2.24 per interquartile range (IQR) increase for PM2.5) while surrounding green was associated with decreased risk of PD (e.g. HR=0.80, 95%CI:0.65, 0.98 per IQR increase for NDVI in 300m buffer). In two-exposure models, the associations of PM2.5 and surrounding green persisted while the associations of NO2 and road proximity attenuated towards unity.

Conclusions: We found that PM2.5 were associated with increased risk of incident PD while surrounding green was associated with decreased risk of PD. Future studies about PD etiology may benefit from including multiple environmental exposures to address potential joint associations.

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Petr75
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Re: PM10

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2021 Apr 23
Centre for Genomics and Child Health, Blizard Institute, Queen Mary University of London, UK
Confocal microscopy 3D imaging of diesel particulate matter
https://pubmed.ncbi.nlm.nih.gov/33890224/

Abstract

To date, diesel particulate matter (DPM) has been described as aggregates of spherule particles with a smooth appearing surface. We have used a new colour confocal microscope imaging method to study the 3D shape of diesel particulate matter (DPM); we observed that the particles can have sharp jagged appearing edges and consistent with these findings, 2D light microscopy demonstrated that DPM adheres to human lung epithelial cells. Importantly, the slide preparation and confocal microscopy method applied avoids possible alteration to the particles' surfaces and enables colour 3D visualisation of the particles. From twenty-one PM10 particles, the mean (standard deviation) major axis length was 5.6 (2.25) μm with corresponding values for the minor axis length of 3.8 (1.25) μm. These new findings may help explain why air pollution particulate matter (PM) has the ability to infiltrate human airway cells, potentially leading to respiratory tract, cardiovascular and neurological disease.
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Petr75
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Re: PM10

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2020 Feb 11
Department of Immunobiology and Environment Microbiology, Faculty of Health Sciences, Medical University of Gdańsk, Gdańsk, Poland
Gaseous Pollutants and Particulate Matter (PM) in Ambient Air and the Number of New Cases of Type 1 Diabetes in Children and Adolescents in the Pomeranian Voivodeship, Poland
https://pubmed.ncbi.nlm.nih.gov/32099842/


Abstract

The increase in type 1 diabetes mellitus (T1DM) incidence in children is worrying and not yet fully explored. It is suggested that probably air pollution exposure could contribute to the development of T1DM. The aim of the study was to investigate the relationship between the concentration of gaseous pollutants including, nitrogen dioxide (NO2), nitric oxides (NOx), sulphur dioxide (SO2), carbon monoxide (CO), and particulate matter (PM) in the air, and the number of new cases of T1DM in children. The number of new cases of T1DM was obtained from the Clinic of Paediatrics, Diabetology, and Endocrinology, Medical University of Gdańsk. The number of children of 0-18 years old in Pomeranian Voivodeship was acquired from the Statistical Yearbook. The concentrations of PM10 absorbance, NO2, NOx, SO2, and CO were measured at 41 measuring posts, between 1 January 2015 and 31 December 2016. It was detected that the average annual concentration of PM10 was higher than the value acceptable to the WHO. Furthermore, the average 24-hour concentration of PM10 was 92 μg/m3 and was higher compared to the acceptable value of 50 μg/m3 (acc. to EU and WHO). Moreover, the number of new cases of T1DM showed a correlation with the annual average concentration of PM10 (β = 2.396, p < 0.001), SO2 (β = 2.294, p < 0.001), and CO (β = 2.452, p < 0.001). High exposure to gaseous pollutants and particulate matter in ambient air may be one of the factors contributing to the risk of developing T1DM in children. Therefore, it is important to take action to decrease air pollutant emissions in Poland. It is crucial to gradually but consistently eliminate the use of solid fuels, such as coal and wood in households, in favour of natural gas and electricity. The development of new technologies to improve air quality, such as "best available techniques" (BAT) or renewable energy sources (water, wind, and solar generation) is of critical importance as well.


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Type 1 diabetes and susceptibility to multiple sclerosis: What is the truth?
https://www.msard-journal.com/article/S ... 7/fulltext
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Petr75
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Re: PM10

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2021 Apr 19
Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, China
Association between Ambient Air Pollution and MRI-Defined Brain Infarcts in Health Examinations in China
https://pubmed.ncbi.nlm.nih.gov/33921763/

Abstract

The study aimed to evaluate the relationships between air pollutants and risk of magnetic resonance imaging (MRI)-defined brain infarcts (BI). We used data from routine health examinations of 1,400,503 participants aged ≥18 years who underwent brain MRI scans in 174 cities in 30 provinces in China in 2018. We assessed exposures to particulate matter (PM)2.5, PM10, nitrogen dioxide (NO2), and carbon monoxide (CO) from 2015 to 2017. MRI-defined BI was defined as lesions ≥3 mm in diameter. Air pollutants were associated with a higher risk of MRI-defined BI. The odds ratio (OR) (95% CI) for MRI-defined BI comparing the highest with the lowest tertiles of air pollutant concentrations was 2.00 (1.96-2.03) for PM2.5, 1.68 (1.65-1.71) for PM10, 1.58 (1.55-1.61) for NO2, and 1.57 (1.54-1.60) for CO. Each SD increase in air pollutants was associated with 16-42% increases in the risk of MRI-defined BI. The associations were stronger in the elderly subgroup. This is the largest survey to evaluate the association between air pollution and MRI-defined BI. Our findings indicate that ambient air pollution was significantly associated with a higher risk of MRI-defined BI.
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Petr75
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Re: PM10

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2021 May 6
Department of Endocrinology, The First Hospital of Lanzhou University, Lanzhou, China
Association between outdoor particulate air pollution and the risk of osteoporosis: a systematic review and meta-analysis
https://pubmed.ncbi.nlm.nih.gov/33954814/

Abstract

Air pollution is a major threat to global health, which is associated with several adverse health outcomes and increased mortality. Few studies have investigated the association between air pollution and osteoporosis, and their findings were inconclusive. Our objective is to determine whether exposure to outdoor air pollution is causally associated with risk of osteoporosis. A systematic literature search of PubMed, Web of Science, Embase, and Cochrane Library for publications up to December 2020 was conducted for studies reporting the association between air pollution and osteoporosis. Meta-analysis was performed to estimate the pooled effect size of air pollution on osteoporosis using the relative risk (RR) and 95% confidence intervals (95% CI). Quality assessment was conducted, and all statistical analyses were performed by RevMan 5.3 software. Our search identified 9 eligible studies involving 9,371,212 patients. Meta-analysis revealed that there was an increased risk of osteoporosis (total body BMD and hip fracture) as a result of exposure to air pollution including PM2.5 and NO2. However, no significant excess risk of osteoporosis was found regardless of PM10, NO, and O3. In spite of a few number of epidemiological studies selected in the present literature review, this study indicated that the increased exposure to air pollutants was positively associated with high risk of osteoporosis. Further cohort studies with large sample sizes are needed to investigate different constituents and the duration of exposure of air pollutants.

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September 2, 2014
Multiple Sclerosis and Osteoporosis: What's the Connection?
https://www.healthline.com/health-news/ ... ion-080214
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Petr75
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Re: PM10

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2021 May 4
Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
Long-term exposure to particulate matter and residential greenness in relation to androgen and progesterone levels among rural Chinese adults
https://pubmed.ncbi.nlm.nih.gov/33962270/

...Conclusions:
Our study suggested that long-term exposure to PM was positively associated with serum testosterone in males but negatively associated with progesterone levels in both genderssin. In addition, positive associations of residential greenness with serum testosterone and progesterone levels were observed, but they were modified by high levels of PM. Furthermore, the estimated effects of residential greenness on testosterone levels were partly mediated by physical activity.

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January 2012
Multiple sclerosis: Neuroprotective alliance of estrogen–progesterone and gender
https://www.sciencedirect.com/science/a ... 2212000027
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Petr75
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Re: PM10

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May 01, 2016
Type 1 diabetes and susceptibility to multiple sclerosis: What is the truth?
https://www.msard-journal.com/article/S ... 7/fulltext
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2020 Jan
doi: 10.1016/j.envint.2019.105333. Epub 2019 Nov 24.
The impact of air pollution on the incidence of diabetes and survival among prevalent diabetes cases
https://pubmed.ncbi.nlm.nih.gov/31775094/
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Petr75
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Re: PM10

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2021 May 17
Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
Association of NO2 and Other Air Pollution Exposures With the Risk of Parkinson Disease
https://pubmed.ncbi.nlm.nih.gov/33999109/


Abstract

Importance: The development of Parkinson disease (PD) may be promoted by exposure to air pollution.

Objective: To investigate the potential association between exposure to particulate matters (PM2.5 and PM10), nitrogen dioxide (NO2), ozone (O3), sulfur dioxide (SO2), and carbon monoxide (CO) and the risk of incident PD.

Design, setting, and participants: This retrospective cohort study used data from the Korean National Health Insurance Service. Among the 1 021 208 Korean individuals in the database, those who had lived in Seoul from January 2002 to December 2006 (n = 176 875) were screened for eligibility. A total of 78 830 adults older than 40 years without PD and who lived in Seoul between January 2002 and December 2006 were included in this study. Individuals diagnosed with PD before 2006 (n = 159) and individuals 40 years or younger (n = 97 886) were excluded. Each participant was followed up with annually from January 2007 to December 2015, thereby adding up to 757 704 total person-years of follow-up. Data were analyzed from January to September 2020.

Exposures: Individual exposure levels to PM2.5, PM10, NO2, O3, SO2, and CO were estimated based on the participants' residential address at the district level. To evaluate long-term exposure to air pollution, time-varying 5-year mean air pollutant exposure was calculated for each participant.

Main outcomes and measures: The outcome measure was the association between air pollution and the risk of incident PD measured as hazard ratios after adjusting for demographic factors, socioeconomic factors, and medical comorbidities.

Results: At baseline, the mean (SD) age of the 78 830 participants was 54.4 (10.7) years, and 41 070 (52.1%) were female. A total of 338 individuals with newly diagnosed PD were identified during the study period. Exposure to NO2 was associated with an increase in risk of PD (hazard ratio for highest vs lowest quartile, 1.41; 95% CI, 1.02-1.95; P for trend = .045). No statistically significant associations between exposure to PM2.5, PM10, O3, SO2, or CO and PD incidence were found.
Conclusions and relevance: In this large cohort study, a statistically significant association between NO2 exposure and PD risk was identified. This finding suggests the role of air pollutants in PD development, advocating for the need to implement a targeted public health policy.
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