Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 72
Filter
1.
Int J Environ Res Public Health ; 19(5)2022 03 06.
Article in English | MEDLINE | ID: covidwho-1742425

ABSTRACT

Air pollution exposure has become ubiquitous and is increasingly detrimental to human health. Small Particulate matter (PM) is one of the most harmful forms of air pollution. It can easily infiltrate the lungs and trigger several respiratory diseases, especially in vulnerable populations such as children and elderly people. In this work, we start by leveraging a retrospective study of 416 children suffering from respiratory diseases. The study revealed that asthma prevalence was the most common among several respiratory diseases, and that most patients suffering from those diseases live in areas of high traffic, noise, and greenness. This paved the way to the construction of the MOREAIR dataset by combining feature abstraction and micro-level scale data collection. Unlike existing data sets, MOREAIR is rich in context-specific components, as it includes 52 temporal or geographical features, in addition to air-quality measurements. The use of Random Forest uncovered the most important features for the understanding of air-quality distribution in Moroccan urban areas. By linking the medical data and the MOREAIR dataset, we observed that the patients included in the medical study come mostly from neighborhoods that are characterized by either high average or high variations of pollution levels.


Subject(s)
Air Pollutants , Air Pollution , Respiration Disorders , Aged , Air Pollutants/analysis , Air Pollution/analysis , Child , Environmental Exposure/analysis , Humans , Particulate Matter/analysis , Retrospective Studies
2.
Int J Environ Res Public Health ; 19(5)2022 Mar 01.
Article in English | MEDLINE | ID: covidwho-1715371

ABSTRACT

The large availability of both air pollution and COVID-19 data, and the simplicity to make geographical correlations between them, led to a proliferation of ecological studies relating the levels of pollution in administrative areas to COVID-19 incidence, mortality or lethality rates. However, the major drawback of these studies is the ecological fallacy that can lead to spurious associations. In this frame, an increasing concern has been addressed to clarify the possible role of contextual variables such as municipalities' characteristics (including urban, rural, semi-rural settings), those of the resident communities, the network of social relations, the mobility of people, and the responsiveness of the National Health Service (NHS), to better clarify the dynamics of the phenomenon. The objective of this paper is to identify and collect the municipalities' and community contextual factors and to synthesize their information content to produce suitable indicators in national environmental epidemiological studies, with specific emphasis on assessing the possible role of air pollution on the incidence and severity of the COVID-19 disease. A first step was to synthesize the content of spatial information, available at the municipal level, in a smaller set of "summary indexes" that can be more easily viewed and analyzed. For the 7903 Italian municipalities (1 January 2020-ISTAT), 44 variables were identified, collected, and grouped into five information dimensions a priori defined: (i) geographic characteristics of the municipality, (ii) demographic and anthropogenic characteristics, (iii) mobility, (iv) socio-economic-health area, and (v) healthcare offer (source: ISTAT, EUROSTAT or Ministry of Health, and further ad hoc elaborations (e.g., OpenStreetMaps)). Principal component analysis (PCA) was carried out for the five identified dimensions, with the aim of reducing the large number of initial variables into a smaller number of components, limiting as much as possible the loss of information content (variability). We also included in the analysis PM2.5, PM10 and NO2 population weighted exposure (PWE) values obtained using a four-stage approach based on the machine learning method, "random forest", which uses space-time predictors, satellite data, and air quality monitoring data estimated at the national level. Overall, the PCA made it possible to extract twelve components: three for the territorial characteristics dimension of the municipality (variance explained 72%), two for the demographic and anthropogenic characteristics dimension (variance explained 62%), three for the mobility dimension (variance explained 83%), two for the socio-economic-health sector (variance explained 58%) and two for the health offer dimension (variance explained 72%). All the components of the different dimensions are only marginally correlated with each other, demonstrating their potential ability to grasp different aspects of the spatial distribution of the COVID-19 pathology. This work provides a national repository of contextual variables at the municipality level collapsed into twelve informative factors suitable to be used in studies on the association between chronic exposure to air pollution and COVID-19 pathology, as well as for investigations on the role of air pollution on the health of the Italian population.


Subject(s)
Air Pollution , COVID-19 , Air Pollution/adverse effects , Air Pollution/analysis , COVID-19/epidemiology , Environmental Exposure/analysis , Epidemiologic Studies , Humans , SARS-CoV-2 , State Medicine
3.
Int J Environ Res Public Health ; 19(3)2022 01 26.
Article in English | MEDLINE | ID: covidwho-1686732

ABSTRACT

Humans are exposed to a diverse mixture of chemical and non-chemical exposures across their lifetimes. Well-designed epidemiology studies as well as sophisticated exposure science and related technologies enable the investigation of the health impacts of mixtures. While existing statistical methods can address the most basic questions related to the association between environmental mixtures and health endpoints, there were gaps in our ability to learn from mixtures data in several common epidemiologic scenarios, including high correlation among health and exposure measures in space and/or time, the presence of missing observations, the violation of important modeling assumptions, and the presence of computational challenges incurred by current implementations. To address these and other challenges, NIEHS initiated the Powering Research through Innovative methods for Mixtures in Epidemiology (PRIME) program, to support work on the development and expansion of statistical methods for mixtures. Six independent projects supported by PRIME have been highly productive but their methods have not yet been described collectively in a way that would inform application. We review 37 new methods from PRIME projects and summarize the work across previously published research questions, to inform methods selection and increase awareness of these new methods. We highlight important statistical advancements considering data science strategies, exposure-response estimation, timing of exposures, epidemiological methods, the incorporation of toxicity/chemical information, spatiotemporal data, risk assessment, and model performance, efficiency, and interpretation. Importantly, we link to software to encourage application and testing on other datasets. This review can enable more informed analyses of environmental mixtures. We stress training for early career scientists as well as innovation in statistical methodology as an ongoing need. Ultimately, we direct efforts to the common goal of reducing harmful exposures to improve public health.


Subject(s)
National Institute of Environmental Health Sciences (U.S.) , Research Design , Environmental Exposure/analysis , Epidemiologic Methods , Epidemiologic Studies , Humans , Risk Assessment , United States
4.
Environ Res ; 208: 112758, 2022 05 15.
Article in English | MEDLINE | ID: covidwho-1637740

ABSTRACT

BACKGROUND: Air pollution exposure may make people more vulnerable to COVID-19 infection. However, previous studies in this area mostly focused on infection before May 2020 and long-term exposure. OBJECTIVE: To assess both long-term and short-term exposure to air pollution and COVID-19 incidence across four case surges from 03/1/2020 to 02/28/2021. METHODS: The cohort included 4.6 million members from a large integrated health care system in southern California with comprehensive electronic medical records (EMR). COVID-19 cases were identified from EMR. Incidence of COVID-19 was computed at the census tract-level among members. Prior 1-month and 1-year averaged air pollutant levels (PM2.5, NO2, and O3) at the census tract-level were estimated based on hourly and daily air quality data. Data analyses were conducted by each wave: 3/1/2020-5/31/2020, 6/1/202-9/30/2020, 10/1/2020-12/31/2020, and 1/1/2021-2/28/2021 and pooled across waves using meta-analysis. Generalized linear mixed effects models with Poisson distribution and spatial autocorrelation were used with adjustment for meteorological factors and census tract-level social and health characteristics. Results were expressed as relative risk (RR) per 1 standard deviation. RESULTS: The cohort included 446,440 COVID-19 cases covering 4609 census tracts. The pooled RRs (95% CI) of COVID-19 incidence associated with 1-year exposures to PM2.5, NO2, and O3 were 1.11 (1.04, 1.18) per 2.3 µg/m3,1.09 (1.02, 1.17) per 3.2 ppb, and 1.06 (1.00, 1.12) per 5.5 ppb respectively. The corresponding RRs (95% CI) associated with prior 1-month exposures were 1.11 (1.03, 1.20) per 5.2 µg/m3 for PM2.5, 1.09 (1.01, 1.17) per 6.0 ppb for NO2 and 0.96 (0.85, 1.08) per 12.0 ppb for O3. CONCLUSION: Long-term PM2.5 and NO2 exposures were associated with increased risk of COVID-19 incidence across all case surges before February 2021. Short-term PM2.5 and NO2 exposures were also associated. Our findings suggest that air pollution may play a role in increasing the risk of COVID-19 infection.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollutants/toxicity , Air Pollution/analysis , COVID-19/epidemiology , Environmental Exposure/analysis , Humans , Incidence , Particulate Matter/analysis , Particulate Matter/toxicity , SARS-CoV-2
5.
Int J Environ Res Public Health ; 19(2)2022 Jan 14.
Article in English | MEDLINE | ID: covidwho-1625572

ABSTRACT

According to the World Bank Group, 36 of the 50 most polluted cities in the European Union are in Poland. Thus, ambient air pollution and its detrimental health effects are a matter of immense importance in Poland. This narrative review aims to analyse current findings on air pollution and health in Poland, with a focus on respiratory diseases, including COVID-19, as well as the Poles' awareness of air pollution. PubMed, Scopus and Google Scholar databases were searched. In total, results from 71 research papers were summarized qualitatively. In Poland, increased air pollution levels are linked to increased general and respiratory disease mortality rates, higher prevalence of respiratory diseases, including asthma, lung cancer and COVID-19 infections, reduced forced expiratory volume in one second (FEV1) and forced vital capacity (FVC). The proximity of high traffic areas exacerbates respiratory health problems. People living in more polluted regions (south of Poland) and in the winter season have a higher level of air pollution awareness. There is an urgent need to reduce air pollution levels and increase public awareness of this threat. A larger number of multi-city studies are needed in Poland to consistently track the burden of diseases attributable to air pollution.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollutants/toxicity , Air Pollution/analysis , Air Pollution/statistics & numerical data , Environmental Exposure/analysis , Environmental Exposure/statistics & numerical data , Humans , Particulate Matter/analysis , Particulate Matter/toxicity , Poland/epidemiology , SARS-CoV-2
6.
Environ Int ; 159: 107022, 2022 01 15.
Article in English | MEDLINE | ID: covidwho-1616484

ABSTRACT

BACKGROUND: Under-5 mortality rate is an important indicator in Millennium Development Goals and Sustainable Development Goals. To date, no nationally representative studies have examined the effects of fine particulate matter (PM2.5) air pollution on under-5 mortality. OBJECTIVE: To investigate the association of short-term exposure to PM2.5 with under-5 mortality from total and specific causes in China. METHODS: We used the national Maternal and Child Health Surveillance System to identify under-5 mortality cases during the study period of 2009 to 2019. We adopted a time-stratified case-crossover study design at the individual level to capture the effect of short-term exposure to daily PM2.5 on under-5 mortality, using conditional logistic regression models. RESULTS: A total of 61,464 under-5 mortality cases were included. A 10 µg/m3 increase in concentrations of PM2.5 on lag 0-1 d was significantly associated with a 1.15% (95%confidence interval: 0.65%, 1.65%) increase in under-5 mortality. Mortality from diarrhea, pneumonia, digestive diseases, and preterm birth were significantly associated with exposure to PM2.5. The effect estimates were larger for neonatal mortality (<28 days), female children, and in warm seasons. We observed steeper slopes in lower ranges (<50 µg/m3) of the concentration-response curve between PM2.5 and under-5 mortality, and positive associations remained below the 24-h PM2.5 concentration limit recommended by WHO Air Quality Guidelines and China Air Quality Standards. CONCLUSIONS: This nationwide case-crossover study in China demonstrated that acute exposure to PM2.5 may significantly increase the risk of under-5 mortality, with larger effects for neonates, female children, and during warm seasons. Relevant control strategies are needed to remove this roadblock to achieving under-5 mortality targets in developing countries.


Subject(s)
Air Pollutants , Air Pollution , Premature Birth , Air Pollutants/adverse effects , Air Pollutants/analysis , Air Pollution/adverse effects , Air Pollution/analysis , Child, Preschool , China/epidemiology , Cross-Over Studies , Environmental Exposure/adverse effects , Environmental Exposure/analysis , Female , Humans , Infant , Infant, Newborn , Mortality , Particulate Matter/adverse effects , Particulate Matter/analysis
7.
Environ Sci Process Impacts ; 24(1): 17-31, 2022 Jan 26.
Article in English | MEDLINE | ID: covidwho-1541261

ABSTRACT

Microplastics (MPs) are a group of emerging contaminants that have attracted increasing scientific and societal attention over the past decade due to their ubiquitous detection in all environmental compartments. So far, most studies on MPs focus on characterizing their occurrence, fate, and impact in the aquatic environment. Therefore, very little is known about the magnitude, patterns, and associated risks of human exposure to MPs, particularly indoors. This is a significant research gap given that people spend most of their time (up to 90%) indoors, which is exacerbated over the past year by COVID-19 lockdown measures. Critical evaluation of the existing literature revealed the presence of MPs at higher concentrations in indoor air and dust (from homes and offices) compared to outdoors. This was attributed to several factors including: indoor MPs sources (e.g. furniture, textiles), increased deposition of atmospheric MPs indoors, and less atmospheric mixing and dilution compared to outdoor air. Current understanding is that indoor human exposure to MPs occurs via a combination of inhalation, ingestion, and dermal contact. Dietary intake was considered the major pathway of human exposure to MPs until recent studies revealed potential high exposure via inhalation. Moreover, exposure via inadvertent dust ingestion and dermal contact cannot be neglected, particularly for young children. This is alarming due to the potential toxic implications of MPs exposure. Early toxicological evidence indicates that small MPs (<20 µm) can cause oxidative stress and inflammation, while particles <5 µm can be engulfed by cells and translocated to accumulate in different organs. Also, there is increasing concern over potential leaching of toxic chemicals used as plastic additives (e.g. plasticizers and flame retardants) upon exposure to MPs due to their large surface area. However, MPs exposure and risk assessment in humans is still in its infancy and more research is necessary to provide the knowledge base required for regulations to protect human health and environment against MPs.


Subject(s)
Air Pollution, Indoor , COVID-19 , Flame Retardants , Air Pollution, Indoor/analysis , Child, Preschool , Communicable Disease Control , Dust/analysis , Environmental Exposure/analysis , Environmental Monitoring , Flame Retardants/analysis , Humans , Microplastics , Plastics , SARS-CoV-2
8.
Environ Health Perspect ; 129(11): 117003, 2021 11.
Article in English | MEDLINE | ID: covidwho-1523382

ABSTRACT

BACKGROUND: Emerging evidence links ambient air pollution with coronavirus 2019 (COVID-19) disease, an association that is methodologically challenging to investigate. OBJECTIVES: We examined the association between long-term exposure to air pollution with SARS-CoV-2 infection measured through antibody response, level of antibody response among those infected, and COVID-19 disease. METHODS: We contacted 9,605 adult participants from a population-based cohort study in Catalonia between June and November 2020; most participants were between 40 and 65 years of age. We drew blood samples from 4,103 participants and measured immunoglobulin M (IgM), IgA, and IgG antibodies against five viral target antigens to establish infection to the virus and levels of antibody response among those infected. We defined COVID-19 disease using self-reported hospital admission, prior positive diagnostic test, or more than three self-reported COVID-19 symptoms after contact with a COVID-19 case. We estimated prepandemic (2018-2019) exposure to fine particulate matter [PM with an aerodynamic diameter of ≤2.5µm (PM2.5)], nitrogen dioxide (NO2), black carbon (BC), and ozone (O3) at the residential address using hybrid land-use regression models. We calculated log-binomial risk ratios (RRs), adjusting for individual- and area-level covariates. RESULTS: Among those tested for SARS-CoV-2 antibodies, 743 (18.1%) were seropositive. Air pollution levels were not statistically significantly associated with SARS-CoV-2 infection: Adjusted RRs per interquartile range were 1.07 (95% CI: 0.97, 1.18) for NO2, 1.04 (95% CI: 0.94, 1.14) for PM2.5, 1.00 (95% CI: 0.92, 1.09) for BC, and 0.97 (95% CI: 0.89, 1.06) for O3. Among infected participants, exposure to NO2 and PM2.5 were positively associated with IgG levels for all viral target antigens. Among all participants, 481 (5.0%) had COVID-19 disease. Air pollution levels were associated with COVID-19 disease: adjusted RRs=1.14 (95% CI: 1.00, 1.29) for NO2 and 1.17 (95% CI: 1.03, 1.32) for PM2.5. Exposure to O3 was associated with a slightly decreased risk (RR=0.92; 95% CI: 0.83, 1.03). Associations of air pollution with COVID-19 disease were more pronounced for severe COVID-19, with RRs=1.26 (95% CI: 0.89, 1.79) for NO2 and 1.51 (95% CI: 1.06, 2.16) for PM2.5. DISCUSSION: Exposure to air pollution was associated with a higher risk of COVID-19 disease and level of antibody response among infected but not with SARS-CoV-2 infection. https://doi.org/10.1289/EHP9726.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Adult , Aged , Air Pollutants/adverse effects , Air Pollutants/analysis , Air Pollution/analysis , Antibody Formation , Cohort Studies , Environmental Exposure/analysis , Humans , Middle Aged , Nitrogen Dioxide/analysis , Particulate Matter/adverse effects , Particulate Matter/analysis , SARS-CoV-2 , Spain/epidemiology
9.
Biomed J ; 44(6S1): S25-S36, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1520728

ABSTRACT

BACKGROUND: Atmospheric contamination, especially particulate matter (PM), can be associated viral infections connected with respiratory failure. Literature data indicates that intensity of SARS-CoV-2 infections worldwide can be associated with PM pollution levels. OBJECTIVES: The aim of the study was to examine the relationship between atmospheric contamination, measured as PM2.5 and PM10 levels, and the number of COVID-19 cases and related deaths in Poland in a one-year observation study. METHODS: Number and geographical distribution of COVID-19 incidents and related deaths, as well as PM2.5 and PM10 exposure levels in Poland were obtained from publicly accessible databases. Average monthly values of these parameters for individual provinces were calculated. Multiple regression analysis was performed for the period between March 2020 and February 2021, taking into account average monthly exposure to PM2.5 and PM10, monthly COVID-19 incidence and mortality rates per 100,000 inhabitants and the population density across Polish provinces. RESULTS: Only December 2020 the number of new infections was significantly related to the three analyzed factors: PM2.5, population density and the number of laboratory COVID-19 tests (R2 = 0.882). For COVID-19 mortality, a model with all three significant factors: PM10, population density and number of tests was obtained as significant only in November 2020 (R2 = 0.468). CONCLUSION: The distribution of COVID-19 incidents across Poland was independent from annual levels of particulate matter concentration in provinces. Exposure to PM2.5 and PM10 was associated with COVID-19 incidence and mortality in different provinces only in certain months. Other cofactors such as population density and the number of performed COVID-19 tests also corresponded with both COVID-19-related infections and deaths only in certain months. Particulate matter should not be treated as the sole determinant of the spread and severity of the COVID-19 pandemic but its importance in the incidence of infectious diseases should not be forgotten.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollutants/toxicity , Air Pollution/statistics & numerical data , COVID-19/epidemiology , Environmental Exposure/analysis , Environmental Exposure/statistics & numerical data , Humans , Pandemics , Particulate Matter/toxicity , Poland/epidemiology , SARS-CoV-2
10.
Sci Total Environ ; 804: 149986, 2022 Jan 15.
Article in English | MEDLINE | ID: covidwho-1525947

ABSTRACT

BACKGROUND: Long-term exposure to ambient air pollution was linked to depression incidence, although the results were limited and inconsistent. OBJECTIVES: To investigate the effects of long-term air pollution exposure on depression risk prospectively in China. METHODS: The present study used data from Yinzhou Cohort on adults without depression at baseline, and followed up until April 2020. Two-year moving average concentrations of particulate matter with a diameter ≤ 2.5 µm (PM2.5), ≤10 µm (PM10) and nitrogen dioxide (NO2) were measured using land-use regression (LUR) models for each participant. Depression cases were ascertained using the Health Information System (HIS) of the local health administration by linking the unique identifiers. We conducted Cox regression models with time-varying exposures to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) of depression with each pollutant, after adjusting for a sequence of individual covariates as demographic characteristics, lifestyles, and comorbidity. Besides, physical activity, baseline potential depressive symptoms, cancer status, COVID-19 pandemic, different outcome definitions and air pollution exposure windows were considered in sensitivity analyses. RESULTS: Among the 30,712 adults with a mean age of 62.22 ± 11.25, 1024 incident depression cases were identified over totaling 98,619 person-years of observation. Interquartile range increments of the air pollutants were associated with increased risks of depression, and the corresponding HRs were 1.59 (95%CI: 1.46, 1.72) for PM2.5, 1.49 (95%CI: 1.35, 1.64) for PM10 and 1.58 (95%CI: 1.42, 1.77) for NO2. Subgroup analyses suggested that participants without taking any protective measures towards air pollution were more susceptible. The results remained robust in all sensitivity analyses. CONCLUSIONS: Long-term exposure to ambient air pollution was identified as a risk factor for depression onset. Strategies to reduce air pollution are necessary to decrease the disease burden of depression.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Adult , Air Pollutants/adverse effects , Air Pollutants/analysis , Air Pollution/adverse effects , Air Pollution/analysis , China/epidemiology , Cohort Studies , Depression/epidemiology , Environmental Exposure/analysis , Humans , Incidence , Nitrogen Dioxide/analysis , Pandemics , Particulate Matter/adverse effects , Particulate Matter/analysis , SARS-CoV-2
12.
Chemosphere ; 286(Pt 1): 131615, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1509647

ABSTRACT

BACKGROUND: Systematic evaluations of the cumulative effects and mortality displacement of ambient particulate matter (PM) pollution on deaths are lacking. We aimed to discern the cumulative effect profile of PM exposure, and investigate the presence of mortality displacement in a large-scale population. METHODS: We conducted a time-series analysis with different exposure-lag models on 13 cities in Jiangsu, China, to estimate the effects of PM pollution on non-accidental, cardiovascular, and respiratory mortality (2015-2019). Over-dispersed Poisson generalized additive models were integrated with distributed lag models to estimate cumulative exposure effects, and assess mortality displacement. RESULTS: Pooled cumulative effect estimates with lags of 0-7 and 0-14 days were substantially larger than those with single-day and 2-day moving average lags. For each 10 µg/m3 increment in PM2.5 concentration with a cumulative lag of 0-7 days, we estimated an increase of 0.50 % (95 % CI: 0.29, 0.72), 0.63 % (95 % CI: 0.38, 0.88), and 0.50 % (95 % CI: 0.01, 1.01) in pooled estimates of non-accidental, cardiovascular, and respiratory mortality, respectively. Both PM10 and PM2.5 were associated with significant increases in non-accidental and cardiovascular mortality with a cumulative lag of 0-14 days. We observed mortality displacement within 30 days for non-accidental, cardiovascular, and respiratory deaths. CONCLUSIONS: Our findings suggest that risk assessment based on single-day or 2-day moving average lag structures may underestimate the adverse effects of PM pollution. The cumulative effects of PM exposure on non-accidental and cardiovascular mortality can last up to 14 days. Evidence of mortality displacement for non-accidental, cardiovascular, and respiratory deaths was found.


Subject(s)
Air Pollutants , Air Pollution , Cardiovascular Diseases , Air Pollutants/analysis , Air Pollutants/toxicity , Air Pollution/analysis , Air Pollution/statistics & numerical data , Cardiovascular Diseases/epidemiology , China/epidemiology , Environmental Exposure/analysis , Environmental Exposure/statistics & numerical data , Humans , Mortality , Particulate Matter/analysis , Particulate Matter/toxicity
13.
Environ Health ; 20(1): 65, 2021 05 27.
Article in English | MEDLINE | ID: covidwho-1496182

ABSTRACT

BACKGROUND: Alzheimer's disease (AD) and other dementias currently represent the fifth most common cause of death in the world, according to the World Health Organization, with a projected future increase as the proportion of the elderly in the population is growing. Air pollution has emerged as a plausible risk factor for AD, but studies estimating dementia cases attributable to exposure to fine particulate matter (PM2.5) air pollution and resulting monetary estimates are lacking. METHODS: We used data on average population-weighted exposure to ambient PM2.5 for the entire population of Sweden above 30 years of age. To estimate the annual number of dementia cases attributable to air pollution in the Swedish population above 60 years of age, we used the latest concentration response functions (CRF) between PM2.5 exposure and dementia incidence, based on ten longitudinal cohort studies, for the population above 60 years of age. To estimate the monetary burden of attributable cases, we calculated total costs related to dementia, including direct and indirect lifetime costs and intangible costs by including quality-adjusted life years (QALYs) lost. Two different monetary valuations of QALYs in Sweden were used to estimate the monetary value of reduced quality-of-life from two different payer perspectives. RESULTS: The annual number of dementia cases attributable to PM2.5 exposure was estimated to be 820, which represents 5% of the annual dementia cases in Sweden. Direct and indirect lifetime average cost per dementia case was estimated to correspond € 213,000. A reduction of PM2.5 by 1 µg/m3 was estimated to yield 101 fewer cases of dementia incidences annually, resulting in an estimated monetary benefit ranging up to 0.01% of the Swedish GDP in 2019. CONCLUSION: This study estimated that 5% of annual dementia cases could be attributed to PM2.5 exposure, and that the resulting monetary burden is substantial. These findings suggest the need to consider airborne toxic pollutants associated with dementia incidence in public health policy decisions.


Subject(s)
Dementia , Environmental Exposure , Environmental Pollutants , Particulate Matter , Aged , Aged, 80 and over , Cost of Illness , Dementia/economics , Dementia/epidemiology , Environmental Exposure/adverse effects , Environmental Exposure/analysis , Environmental Exposure/economics , Environmental Pollutants/adverse effects , Environmental Pollutants/analysis , Environmental Pollutants/economics , Humans , Incidence , Middle Aged , Particulate Matter/adverse effects , Particulate Matter/analysis , Particulate Matter/economics , Quality of Life , Sweden/epidemiology
14.
Sci Data ; 8(1): 287, 2021 10 28.
Article in English | MEDLINE | ID: covidwho-1493154

ABSTRACT

Exposure to poor air quality is considered a major influence on the occurrence of cardiovascular and respiratory diseases. Air pollution has also been linked to the severity of the effects of epidemics such as COVID-19 caused by the SARS-CoV-2 virus. Epidemiological studies require datasets of the long-term exposure to air pollution. We present the APExpose_DE dataset, a long-term (2010-2019) dataset providing ambient air pollution metrics at yearly time resolution for NO2, NO, O3, PM10 and PM2.5 at the NUTS-3 spatial resolution level for Germany (corresponding to the Landkreis or Kreisfreie Stadt in Germany, 402 in total).


Subject(s)
Air Pollution/analysis , Environmental Exposure/analysis , Air Pollutants/analysis , COVID-19 , Germany , Humans , Particulate Matter/analysis
15.
Environ Pollut ; 290: 118118, 2021 Dec 01.
Article in English | MEDLINE | ID: covidwho-1474528

ABSTRACT

The health impact of changes in particulate matter with an aerodynamic diameter <2.5 µm (PM2.5) pollution associated with the COVID-19 lockdown has aroused great interest, but the estimation of the long-term health effects is difficult because of the lack of an annual mean air pollutant concentration under a whole-year lockdown scenario. We employed a time series decomposition method to predict the monthly PM2.5 concentrations in urban cities under permanent lockdown in 2020. The premature mortality attributable to long-term exposure to ambient PM2.5 was quantified by the risk factor model from the latest epidemiological studies. Under a whole-year lockdown scenario, annual mean PM2.5 concentrations in cites ranged from 5.4 to 68.0 µg m-3, and the national mean concentration was reduced by 32.2% compared to the 2015-2019 mean. The Global Exposure Mortality Model estimated that 837.3 (95% CI: 699.8-968.4) thousand people in Chinese cities would die prematurely from illnesses attributable to long-term exposure to ambient PM2.5. Compared to 2015-2019 mean levels, 140.2 (95% CI: 122.2-156.0) thousand premature deaths (14.4% of the annual mean deaths from 2015 to 2019) attributable to long-term exposure to PM2.5 were avoided. Because PM2.5 concentrations were still high under the whole-year lockdown scenario, the health benefit is limited, indicating that continuous emission-cutting efforts are required to reduce the health risks of air pollution. Since a similar scenario may be achieved through promotion of electric vehicles and the innovation of industrial technology in the future, the estimated long-term health impact under the whole year lockdown scenario can establish an emission-air quality-health impact linkage and provide guidance for future emission control strategies from a health protection perspective.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , China , Cities , Communicable Disease Control , Environmental Exposure/analysis , Humans , Particulate Matter/analysis , SARS-CoV-2
16.
Environ Int ; 157: 106862, 2021 12.
Article in English | MEDLINE | ID: covidwho-1474522

ABSTRACT

BACKGROUND: Air pollution exposure has been associated with increased risk of COVID-19 incidence and mortality by ecological analyses. Few studies have investigated the specific effect of traffic-related air pollution on COVID-19 severity. OBJECTIVE: To investigate the associations of near-roadway air pollution (NRAP) exposure with COVID-19 severity and mortality using individual-level exposure and outcome data. METHODS: The retrospective cohort includes 75,010 individuals (mean age 42.5 years, 54% female, 66% Hispanic) diagnosed with COVID-19 at Kaiser Permanente Southern California between 3/1/2020-8/31/2020. NRAP exposures from both freeways and non-freeways during 1-year prior to the COVID-19 diagnosis date were estimated based on residential address history using the CALINE4 line source dispersion model. Primary outcomes include COVID-19 severity defined as COVID-19-related hospitalizations, intensive respiratory support (IRS), intensive care unit (ICU) admissions within 30 days, and mortality within 60 days after COVID-19 diagnosis. Covariates including socio-characteristics and comorbidities were adjusted for in the analysis. RESULT: One standard deviation (SD) increase in 1-year-averaged non-freeway NRAP (0.5 ppb NOx) was associated with increased odds of COVID-19-related IRS and ICU admission [OR (95% CI): 1.07 (1.01, 1.13) and 1.11 (1.04, 1.19) respectively] and increased risk of mortality (HR = 1.10, 95% CI = 1.03, 1.18). The associations of non-freeway NRAP with COVID-19 outcomes were largely independent of the effect of regional fine particulate matter and nitrogen dioxide exposures. These associations were generally consistent across age, sex, and race/ethnicity subgroups. The associations of freeway and total NRAP with COVID-19 severity and mortality were not statistically significant. CONCLUSIONS: Data from this multiethnic cohort suggested that NRAP, particularly non-freeway exposure in Southern California, may be associated with increased risk of COVID-19 severity and mortality among COVID-19 infected patients. Future studies are needed to assess the impact of emerging COVID-19 variants and chemical components from freeway and non-freeway NRAP.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Adult , Air Pollutants/analysis , Air Pollutants/toxicity , Air Pollution/adverse effects , Air Pollution/analysis , COVID-19 Testing , California/epidemiology , Cohort Studies , Environmental Exposure/adverse effects , Environmental Exposure/analysis , Female , Humans , Male , Retrospective Studies , SARS-CoV-2
17.
Environ Int ; 158: 106930, 2022 01.
Article in English | MEDLINE | ID: covidwho-1466318

ABSTRACT

BACKGROUND: Age, sex, race and comorbidities are insufficient to explain why some individuals remain asymptomatic after SARS-CoV-2 infection, while others die. In this sense, the increased risk caused by the long-term exposure to air pollution is being investigated to understand the high heterogeneity of the COVID-19 infection course. OBJECTIVES: We aimed to assess the underlying effect of long-term exposure to NO2 and PM10 on the severity and mortality of COVID-19. METHODS: A retrospective observational study was conducted with 2112 patients suffering COVID-19 infection. We built two sets of multivariate predictive models to assess the relationship between the long-term exposure to NO2 and PM10 and COVID-19 outcome. First, the probability of either death or severe COVID-19 outcome was predicted as a function of all the clinical variables together with the pollutants exposure by means of two regularized logistic regressions. Subsequently, two regularized linear regressions were constructed to predict the percentage of dead or severe patients. Finally, odds ratios and effects estimates were calculated. RESULTS: We found that the long-term exposure to PM10 is a more important variable than some already stated comorbidities (i.e.: COPD/Asthma, diabetes, obesity) in the prediction of COVID-19 severity and mortality. PM10 showed the highest effects estimates (1.65, 95% CI 1.32-2.06) on COVID-19 severity. For mortality, the highest effect estimates corresponded to age (3.59, 95% CI 2.94-4.40), followed by PM10 (2.37, 95% CI 1.71-3.32). Finally, an increase of 1 µg/m3 in PM10 concentration causes an increase of 3.06% (95% CI 1.11%-4.25%) of patients suffering COVID-19 as a severe disease and an increase of 2.68% (95% CI 0.53%-5.58%) of deaths. DISCUSSION: These results demonstrate that long-term PM10 burdens above WHO guidelines exacerbate COVID-19 health outcomes. Hence, WHO guidelines, the air quality standard established by the Directive 2008/50/EU, and that of the US-EPA should be updated accordingly to protect human health.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollutants/toxicity , Air Pollution/adverse effects , Air Pollution/analysis , Environmental Exposure/adverse effects , Environmental Exposure/analysis , Humans , Particulate Matter/analysis , Particulate Matter/toxicity , SARS-CoV-2 , Time Factors , World Health Organization
18.
Spat Spatiotemporal Epidemiol ; 39: 100443, 2021 11.
Article in English | MEDLINE | ID: covidwho-1459135

ABSTRACT

The study of the impacts of air pollution on COVID-19 has gained increasing attention. However, most of the existing studies are based on a single country, with a high degree of variation in the results reported in different papers. We attempt to inform the debate about the long-term effects of air pollution on COVID-19 by conducting a multi-country analysis using a spatial ecological design, including Canada, Italy, England and the United States. The model allows the residual spatial autocorrelation after accounting for covariates. It is concluded that the effects of PM2.5 and NO2 are inconsistent across countries. Specifically, NO2 was not found to be an important factor affecting COVID-19 infection, while a large effect for PM2.5 in the US is not found in the other three countries. The Population Attributable Fraction for COVID-19 incidence ranges from 3.4% in Canada to 45.9% in Italy, although with considerable uncertainty in these estimates.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollutants/toxicity , Air Pollution/analysis , Air Pollution/statistics & numerical data , Environmental Exposure/analysis , Environmental Exposure/statistics & numerical data , Humans , Particulate Matter/analysis , Particulate Matter/toxicity , SARS-CoV-2 , United States/epidemiology
19.
PLoS One ; 16(9): e0258070, 2021.
Article in English | MEDLINE | ID: covidwho-1448578

ABSTRACT

BACKGROUND: Air pollution is the largest environmental health risk in the United Kingdom, and an issue of concern amongst outdoor workers. Road transport is a major source producing the largest amount of nitrogen dioxide (NO2) and ozone (O3) (as a secondary pollutant). Hundreds of vehicles enter and exit the Tidworth Camp's main gate daily, potentially producing these pollutants. However, the air pollution exposure experienced by personnel on guard duty is unknown. This study aimed to determine and compare background NO2 and O3 levels experienced by personnel on guard duty. METHODS: Cross-sectional data was collected using a static sampling technic on randomly selected days of the week. Data analysis was done using IBM-SPSS-26 and a p-value of <0.05 was considered statistically significant. RESULTS: The background concentration of NO2 and O3 pollutants were within recommended limits. There was no significant difference between mean morning and afternoon exposure levels for both pollutants. However, NO2 and O3 levels were significantly higher during weekdays compared to weekends (M = -0.022, SD = 0.007, t(6) = -8.672, p <0.0001 and M = -0.016, SD = 0.008, t(6) = -5.040, p = 0.002 respectively). Both pollutants showed no significant differences in exposure levels when only weekdays were compared. NO2 levels showed a weak positive correlation during weekdays (r = 0.04) and a strong positive correlation during weekends (r = 0.96). O3 levels had a positive correlation on both weekdays and weekends; however, levels on Monday showed a negative correlation (r = -0.55). Linear regression analysis showed that outside temperature was a significant predictor of O3 levels (p = 0.026). CONCLUSION: Personnel on guard duty experienced higher pollution levels during weekdays compared to weekends; however, air pollution levels for both pollutants were within recommended limits. Further studies are recommended over hotter months using a personal sampling technic to measure personal air pollution exposure levels in order to minimise any health and safety risks.


Subject(s)
Air Pollutants/analysis , Air Pollution/analysis , Nitrogen Dioxide/analysis , Occupational Exposure/analysis , Ozone/analysis , Cross-Sectional Studies , Environmental Exposure/analysis , Environmental Monitoring , Humans , Military Personnel , United Kingdom
20.
Environ Res ; 207: 112131, 2022 05 01.
Article in English | MEDLINE | ID: covidwho-1446616

ABSTRACT

Back in December 2019, the novel coronavirus disease 2019 (Covid-19) started rapidly spreading worldwide, especially in Italy that was among the most affected countries. The geographical distribution of air pollution and Covid-19 mortality in Italy suggested atmospheric pollution as a worsening factor of severe Covid-19 health outcomes. The present nationwide ecological study focused on all 107 Italian territorial areas, aiming to assess the potential association between Particulate Matter concentration, less than 2.5 µm in diameter (exposure), and Covid-19 mortality rate (outcome) throughout 2020, by looking at 28 potential confounders. A potential positive association between exposure and outcome was observed when performing a multivariate regression analysis with a Negative Binomial model, suggesting that an increase of 1 µg/m3 in the exposure is associated with an increase of 9.0% (95% CI: 6.5%-11.6%) in the average Covid-19 mortality rate, conditional on all 28 potential confounders. A sensitivity analysis, based on the E-value, shows that a hypothetical unmeasured confounder would have to be associated with both PM2.5 concentration and Covid-19 mortality rate by a rate ratio of at least 1.40-fold each to explain away the exposure-outcome association, conditional on all 28 covariates included in the main analysis model. Moreover, the Observed Covariate E-value (OCE) was reported to provide a contextualization of the E-value on the observed covariates included in the study. The OCE sensitivity analysis shows that a set of unknown confounders similar in size and magnitude to the set of the considered climatic factors could potentially explain away the estimated exposure-outcome association. Consequently, the role of climatic factors in the Covid-19 pandemic is worth of further investigation.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollutants/toxicity , Air Pollution/analysis , Air Pollution/statistics & numerical data , Environmental Exposure/analysis , Environmental Exposure/statistics & numerical data , Humans , Italy/epidemiology , Pandemics , Particulate Matter/analysis , Particulate Matter/toxicity , SARS-CoV-2
SELECTION OF CITATIONS
SEARCH DETAIL