The impact of air pollution on COVID-19 pandemic varied within different cities in South America using different models.
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ABSTRACT:
SUBMITTER: Huang H
PROVIDER: S-EPMC8325399 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The sanitary measures implemented to control and prevent an increase in infections due to the COVID-19 pandemic have produced an improvement in the air quality of many urban areas around the world. We assessed air quality during the COVID-19 pandemic for particulate matter (PM2.5 and PM10), NO2 and O3 in in metropolitan area of Lima, Peru between pre-lockdown period (February 1 and March 15 of 2020), historical period (March 16 to April 30 2017-2019) and lockdown period (March 16 to April 30, 2020). The complete national lockdown that was implemented in Peru produced statistically significant reductions in the in-air pollutant (PM10 (-40% and -58%), PM2.5 (-31% and -43%) and NO2 (-46% and -48%)), as recorded by the by the ground-based air quality monitoring network throughout the metropolitan area, compared with the corresponding concentrations for the previous weeks and over the same period for 2017-2019. Analysis of the spatial Distribution of satellite data also show decreases in the concentrations of PM10, PM2.5 and NO2 as a result of the containment measures and suspension of activities implemented by the Peruvian government. The concentrations of O3 significantly increased (11% and 170%) as a result of the decrease in the concentration of NO2, confirming that the study area is a hydrocarbon-limited system, as previously reported. The results obtained contribute to the assessment by the regulatory agencies of the possible strategies of control and monitoring of air pollution in the study area.Graphical abstractSupplementary informationThe online version contains supplementary material available at 10.1007/s11869-021-00990-3.
| S-EPMC7859720 | biostudies-literature
Project description:Recent cohort studies have relied on exposure prediction models to estimate individuallevel air pollution concentrations because individual air pollution measurements are not available for cohort locations. For such prediction models, geographic variables related to pollution sources are important inputs. We demonstrated the computation process of geographic variables mostly recorded in 2010 at regulatory air pollution monitoring sites in South Korea. On the basis of previous studies, we finalized a list of 313 geographic variables related to air pollution sources in eight categories including traffic, demographic characteristics, land use, transportation facilities, physical geography, emissions, vegetation, and altitude. We then obtained data from different sources such as the Statistics Geographic Information Service and Korean Transport Database. After integrating all available data to a single database by matching coordinate systems and converting non-spatial data to spatial data, we computed geographic variables at 294 regulatory monitoring sites in South Korea. The data integration and variable computation were performed by using ArcGIS version 10.2 (ESRI Inc., Redlands, CA, USA). For traffic, we computed the distances to the nearest roads and the sums of road lengths within different sizes of circular buffers. In addition, we calculated the numbers of residents, households, housing buildings, companies, and employees within the buffers. The percentages of areas for different types of land use compared to total areas were calculated within the buffers. For transportation facilities and physical geography, we computed the distances to the closest public transportation depots and the boundary lines. The vegetation index and altitude were estimated at a given location by using satellite data. The summary statistics of geographic variables in Seoul across monitoring sites showed different patterns between urban background and urban roadside sites. This study provided practical knowledge on the computation process of geographic variables in South Korea, which will improve air pollution prediction models and contribute to subsequent health analyses.
| S-EPMC4662093 | biostudies-literature
Project description:We simulated commuter routes and long-term exposure to traffic-related air pollution during commute in a representative population sample in Basel (Switzerland), and evaluated three air pollution models with different spatial resolution for estimating commute exposures to nitrogen dioxide (NO2) as a marker of long-term exposure to traffic-related air pollution. Our approach includes spatially and temporally resolved data on actual commuter routes, travel modes and three air pollution models. Annual mean NO2 commuter exposures were similar between models. However, we found more within-city and within-subject variability in annual mean (±SD) NO2 commuter exposure with a high resolution dispersion model (40 ± 7 µg m(-3), range: 21-61) than with a dispersion model with a lower resolution (39 ± 5 µg m(-3); range: 24-51), and a land use regression model (41 ± 5 µg m(-3); range: 24-54). Highest median cumulative exposures were calculated along motorized transport and bicycle routes, and the lowest for walking. For estimating commuter exposure within a city and being interested also in small-scale variability between roads, a model with a high resolution is recommended. For larger scale epidemiological health assessment studies, models with a coarser spatial resolution are likely sufficient, especially when study areas include suburban and rural areas.
| S-EPMC4053908 | biostudies-other
Project description:BackgroundThe systematic evaluation of the results of time-series studies of air pollution is challenged by differences in model specification and publication bias.MethodsWe evaluated the associations of inhalable particulate matter (PM) with an aerodynamic diameter of 10 ?m or less (PM10) and fine PM with an aerodynamic diameter of 2.5 ?m or less (PM2.5) with daily all-cause, cardiovascular, and respiratory mortality across multiple countries or regions. Daily data on mortality and air pollution were collected from 652 cities in 24 countries or regions. We used overdispersed generalized additive models with random-effects meta-analysis to investigate the associations. Two-pollutant models were fitted to test the robustness of the associations. Concentration-response curves from each city were pooled to allow global estimates to be derived.ResultsOn average, an increase of 10 ?g per cubic meter in the 2-day moving average of PM10 concentration, which represents the average over the current and previous day, was associated with increases of 0.44% (95% confidence interval [CI], 0.39 to 0.50) in daily all-cause mortality, 0.36% (95% CI, 0.30 to 0.43) in daily cardiovascular mortality, and 0.47% (95% CI, 0.35 to 0.58) in daily respiratory mortality. The corresponding increases in daily mortality for the same change in PM2.5 concentration were 0.68% (95% CI, 0.59 to 0.77), 0.55% (95% CI, 0.45 to 0.66), and 0.74% (95% CI, 0.53 to 0.95). These associations remained significant after adjustment for gaseous pollutants. Associations were stronger in locations with lower annual mean PM concentrations and higher annual mean temperatures. The pooled concentration-response curves showed a consistent increase in daily mortality with increasing PM concentration, with steeper slopes at lower PM concentrations.ConclusionsOur data show independent associations between short-term exposure to PM10 and PM2.5 and daily all-cause, cardiovascular, and respiratory mortality in more than 600 cities across the globe. These data reinforce the evidence of a link between mortality and PM concentration established in regional and local studies. (Funded by the National Natural Science Foundation of China and others.).
| S-EPMC7891185 | biostudies-literature
Project description:Health behavior is a critical measure in controlling the coronavirus disease 2019 (COVID-19) pandemic. We estimated the effect of health behaviors against air pollution on reducing the risk of COVID-19 during the initial phase of the pandemic. The attack rates of COVID-19 in 159 mainland Chinese cities during the first 2 weeks after the closure of major cities was estimated; air pollution level as a surrogate indicator of the mask-wearing rate. Data on air pollution levels and meteorologic factors 2 weeks prior to the closure were obtained. The attack rate was compared with the level of air pollution using a generalized linear model after adjusting for confounders. When fine particulates (PM2.5) and nitrogen dioxide (NO2) levels increased by one unit of air quality index (AQI), the infection risk decreased by 0.7% and 3.4%, respectively. When PM2.5 levels exceeded 150 (level 4), the infection risk decreased (relative risk, RR = 0.635, 95% confidence interval, CI: 0.442 to 0.912 for level 4; RR = 0.529, 95% CI: 0.337 to 0.830 for level 5; respectively). After controlling for the number of high-speed railway routes, when PM2.5 and NO2 levels increased by one AQI, relative risk for PM2.5 and NO2 was 0.990 (95% CI, 0.984 to 0.997) and 0.946 (95% CI, 0.911 to 0.982), respectively, demonstrating a consistently negative association. It is postulated that, during the early phase of the pandemic, the cities with higher air pollution levels may represent the higher practice of mask-wearing to protect from air pollution, which could have acted as a barrier to the transmission of the virus. This study highlights the importance of health behaviors, including mask-wearing for preventing infections.
| S-EPMC7967675 | biostudies-literature
Project description:Studying weekend-weekday variation in ground-level ozone (O3) allows one to better understand O3 formation conditions, with a potential for developing effective strategies for O3 control. Reducing inappropriately the O3 precursors emissions can either produce no reduction or increase surface O3 concentrations. This paper analyzes the weekend-weekday differences of O3 at 300 rural and 808 urban background stations worldwide from 2005 to 2014, in order to investigate the O3 weekend effect over time and assess the effectiveness of the precursors emissions control policies for reducing O3 levels. Data were analyzed with the non-parametric Mann-Kendall test and Theil-Sen estimator. Rural sites typically did not experience a weekend-weekday effect. In all urban stations, the mean O3 concentration on the weekend was 12% higher than on weekdays. Between 2005 and 2014, the annual mean of daily O3 concentrations increased at 74% of urban sites worldwide (+ 0.41 ppb year-1) and decreased in the United Kingdom (- 0.18 ppb year-1). Over this time period, emissions of O3 precursors declined significantly. However, a greater decline in nitrogen oxides (NOx) emissions caused an increase in Volatile Organic Compounds (VOCs) to NOx ratios leading to O3 formation. In France, South Korea and the United Kingdom, most urban stations showed a significant upward trend (+ 1.15% per year) for O3 weekend effect. Conversely, in Canada, Germany, Japan, Italy and the United States, the O3 weekend effect showed a significant downward trend (- 0.26% per year). Further or inappropriate control of anthropogenic emissions in Canada, Southern Europe, Japan, South Korea and the United States might result in increased daily O3 levels in urban areas.
| S-EPMC7483290 | biostudies-literature
Project description:Leiomyomas (LMs) are the most frequent uterine benign tumors, representing the leading cause of hysterectomy indications worldwide. They are highly associated with women's reproductive complications, and endocrine disruptors may influence their etiology. In this sense, air pollution represents a relevant hormonal disruptor that acts on key signaling pathways, resulting in tumor development and infertility. Our goal was to evaluate submucosal LM samples from patients living in the metropolitan and Sao Paulo city regions, focusing on genes involved in tumor development and infertility features. Twenty-four patients were selected based on their region of residence and clinical information availability. Several genes were differentially expressed between women living in metropolitan areas and Sao Paulo city. Significant associations were observed between BCL-2, DVL1, FGFR3, and WNT5b downregulation and contraceptive use in the samples from women living in Sao Paulo city. ESR1 and HHAT downregulation was associated with ethnicity. WNT5b and GREM were associated with LM treatment and related pathologies, respectively. In the samples from women living in other cities of the metropolitan region, abortion occurrence was associated with BMP4 upregulation. Although further studies may be necessary, our results showed that air pollution exposure influences the expression of genes related to LM development and female reproductive features.
| S-EPMC9917088 | biostudies-literature
Project description:Objectives To estimate the short term effect of particulate air pollution (particle diameter <10 ?m, or PM10) on mortality and explore the heterogeneity of particulate air pollution effects in major cities in China.Design Generalised linear models with different lag structures using time series data.Setting 38 of the largest cities in 27 provinces of China (combined population >200 million).Participants 350?638 deaths (200?912 in males, 149?726 in females) recorded in 38 city districts by the Disease Surveillance Point System of the Chinese Center for Disease Control and Prevention from 1 January 2010 to 29 June 2013.Main outcome measure Daily numbers of deaths from all causes, cardiorespiratory diseases, and non-cardiorespiratory diseases and among different demographic groups were used to estimate the associations between particulate air pollution and mortality.Results A 10 µg/m3 change in concurrent day PM10 concentrations was associated with a 0.44% (95% confidence interval 0.30% to 0.58%) increase in daily number of deaths. Previous day and two day lagged PM10 levels decreased in magnitude by one third and two thirds but remained statistically significantly associated with increased mortality. The estimate for the effect of PM10 on deaths from cardiorespiratory diseases was 0.62% (0.43% to 0.81%) per 10 µg/m3 compared with 0.26% (0.09% to 0.42%) for other cause mortality. Exposure to PM10 had a greater impact on females than on males. Adults aged 60 and over were more vulnerable to particulate air pollution at high levels than those aged less than 60. The PM10 effect varied across different cities and marginally decreased in cities with higher PM10 concentrations.Conclusion Particulate air pollution has a greater impact on deaths from cardiorespiratory diseases than it does on other cause mortality. People aged 60 or more have a higher risk of death from particulate air pollution than people aged less than 60. The estimates of the effect varied across cities and covered a wide range of domain.
| S-EPMC6287590 | biostudies-literature
Project description:Comparison of genome-wide gene expression between humans living in areas of high levels of air pollution and less polluted areas. Keywords: Comparison of genome-wide gene expression between different conditions
2008-04-17 | GSE7543 | GEO
Project description:Meniere's disease is thought to be a disorder of the inner ear function, affected by genetic and environmental factors. Several recent studies have shown that air pollution could affect middle and inner ear diseases. The purpose of this study was to investigate the relationship between the Meniere's disease occurrence and air pollution status in Korea. This study used a time-stratified case-crossover design. Hospital visit data by Meniere's disease were collected from the Korea National Health Insurance Service-National Sample Cohort (NHIS-NSC) database. Daily air pollution data for sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and particulate matter (PM10: ≤ 10 μm in diameter, and PM2.5: ≤ 2.5 μm in diameter) were collected from the National Ambient air quality Monitoring Information System (NAMIS) database. We used two-stage analysis to assess the association between degree of air pollution and the occurrence of Meniere's disease. In the first stage, region-specific analysis was conducted to estimate the odds ratios (ORs) of Meniere's disease risk associated with each air pollutant exposure by using conditional logistic regression for matched case-control sets in 16 regions. In the second stage, region-specific ORs from the first stage were combined and the pooled effect estimates were derived through fixed and random effect meta-analysis. Subgroup analysis was conducted for age, sex, seasonality, and urbanization of residence. In total, 29,646 (32.1% males and 67.9% females) Meniere's disease cases were identified from Korea NHIS-NSC database between 2008 and 2015. Overall, SO2, NO2, CO, and PM10 showed significant correlation with Meniere's disease risk at immediate lags, and weaker correlation at delayed lags, whereas O3 showed slightly negative correlation at the immediate lag (lag0) and PM2.5 did not show strong correlation (SO2: 1.04 [95% confidence interval: 1.01, 1.06]; NO2: 1.08 [1.06, 1.11]; CO: 1.04 [1.02, 1.06]; O3: 0.96 [0.93, 0.99]: statistically significant ORs at lag0 are listed). These positive and negative associations between Meniere's disease and each air pollutant were generally stronger in the age of 40-64, female, summer (June-August) season, and urban subgroups. Our results showed that hospital visits for Meniere's disease were associated with the measured concentrations of ambient air pollutants SO2, NO2, CO, and PM10. Further studies are required to confirm these associations and find their mechanisms.
| S-EPMC8222348 | biostudies-literature