ABSTRACT
Air pollution is a major global environment and health concern. Recent studies have suggested an association between air pollution and COVID-19 mortality and morbidity. In this context, a close association between increased levels of air pollutants such as particulate matter ≤2.5 to 10 µM, ozone and nitrogen dioxide and SARS-CoV-2 infection, hospital admissions and mortality due to COVID 19 has been reported. Air pollutants can make individuals more susceptible to SARS-CoV-2 infection by inducing the expression of proteins such as angiotensin converting enzyme (ACE)2 and transmembrane protease, serine 2 (TMPRSS2) that are required for viral entry into the host cell, while causing impairment in the host defence system by damaging the epithelial barrier, muco-ciliary clearance, inhibiting the antiviral response and causing immune dysregulation. The aim of this review is to report the epidemiological evidence on impact of air pollutants on COVID 19 in an up-to-date manner, as well as to provide insights on in vivo and in vitro mechanisms.
ABSTRACT
The existing evidence on the association between greenness and respiratory outcomes remains inconclusive. We aimed at systematically summarizing existing literature on greenness exposure and respiratory outcomes in European children and adolescents, with a preliminary attempt to qualify the distribution of dominant tree species across different geographical areas and bioclimatic regions. Overall, 4049 studies were firstly identified by searching PubMed/MEDLINE, EMBASE, Scopus, Web of Science, GreenFile and CAB direct, up to 29 August 2023. Eighteen primary studies were included in the systematic review and six were meta-analyzed. No overall significant association was observed between the Normalized Difference Vegetation Index, assessed within 500-m buffers (i.e. NDVI-500), and the odds of asthma for 0.3-increase in the exposure (OR: 0.97, 95% CI from 0.53 to 1.78). Similarly, an overall exposure to the NDVI-300 highest tertile, as compared to the lowest tertile, was not significantly associated with asthma (OR: 0.65, 95% CI from 0.22 to 1.91): heterogeneity among studies was significant (p = 0.021). We delineated some key elements that might have mostly contributed to the lack of scientific consensus on this topic, starting from the urgent need of harmonized approaches for the operational definition of greenness. Additionally, the complex interplay between greenness and respiratory health may vary across different geographical regions and climatic conditions. At last, the inconsistent findings may reflect the heterogeneity and complexity of this relationship, rather than a lack of scientific consensus itself. Future research should compare geographical areas with similar bioclimatic parameters and dominant or potentially present vegetation species, in order to achieve a higher inter-study comparability.
Subject(s)
Asthma , Europe/epidemiology , Humans , Adolescent , Child , Asthma/epidemiology , Environmental ExposureABSTRACT
OBJECTIVES: the BIGEPI project, co-funded by INAIL, has used big data to identify the health risks associated with short and long-term exposure to air pollution, extreme temperatures and occupational exposures. DESIGN: the project consists of 5 specific work packages (WP) aimed at assessing: 1. the acute effects of environmental exposures over the national territory; 2. the acute effects of environmental exposures in contaminated areas, such as Sites of National Interest (SIN) and industrial sites; 3. the chronic effects of environmental exposures in 6 Italian longitudinal metropolitan studies; 4. the acute and chronic effects of environmental exposures in 7 epidemiological surveys on population samples; 5. the chronic effects of occupational exposures in the longitudinal metropolitan studies of Rome and Turin. SETTING AND PARTICIPANTS: BIGEPI analyzed environmental and health data at different levels of detail: the whole Italian population (WP1); populations living in areas contaminated by pollutants of industrial origin (WP2); the entire longitudinal cohorts of the metropolitan areas of Bologna, Brindisi, Rome, Syracuse, Taranto and Turin (WP3 and WP5); population samples participating in the epidemiological surveys of Ancona, Palermo, Pavia, Pisa, Sassari, Turin and Verona (WP4). MAIN OUTCOME MEASURES: environmental exposure: PM10, PM2,5, NO2 and O3 concentrations and air temperature at 1 Km2 resolution at national level. Occupational exposures: employment history of subjects working in at least one of 25 sectors with similar occupational exposures to chemicals/carcinogens; self-reported exposure to dust/fumes/gas in the workplace. Health data: cause-specific mortality/hospitalisation; symptoms/diagnosis of respiratory/allergic diseases; respiratory function and bronchial inflammation. RESULTS: BIGEPI analyzed data at the level of the entire Italian population, data on 2.8 million adults (>=30 yrs) in longitudinal metropolitan studies and on about 14,500 individuals (>=18 yrs) in epidemiological surveys on population samples. The population investigated in the longitudinal metropolitan studies had an average age of approximately 55 years and that of the epidemiological surveys was about 48 years; in both cases, 53% of the population was female. As regards environmental exposure, in the period 2013-2015, at national level average values for PM10, PM2.5, NO2 and summer O3 were: 21.1±13.6, 15.1±10.9, 14.7±9.1 and 80.3±17.3 µg/m3, for the temperature the average value was 13.9±7.2 °C. Data were analyzed for a total of 1,769,660 deaths from non-accidental causes as well as 74,392 incident cases of acute coronary event and 45,513 of stroke. Epidemiological investigations showed a high prevalence of symptoms/diagnoses of rhinitis (range: 14.2-40.5%), COPD (range: 4.7-19.3%) and asthma (range: 3.2-13.2%). The availability of these large datasets has made it possible to implement advanced statistical models for estimating the health effects of short- and long-term exposures to pollutants. The details are reported in the BIGEPI papers already published in other international journals and in those published in this volume of E&P. CONCLUSIONS: BIGEPI has confirmed the great potential of using big data in studies of the health effects of environmental and occupational factors, stimulating new directions of scientific research and confirming the need for preventive action on air quality and climate change for the health of the general population and the workers.
Subject(s)
Air Pollutants , Air Pollution , Environmental Pollutants , Respiratory Tract Diseases , Adult , Humans , Female , Middle Aged , Air Pollutants/adverse effects , Air Pollutants/analysis , Nitrogen Dioxide , Italy/epidemiology , Environmental Exposure/adverse effects , Environmental Exposure/analysis , Particulate Matter/adverse effects , Particulate Matter/analysisABSTRACT
OBJECTIVES: the health status of people living near industrial plants is often exposed to several environmental risk factors, including air pollution. The aim of this study is to assess the relationship between daily PM10 levels and cause-specific mortality in a selection of municipalities near two industrial plants from 2006 to 2015. DESIGN: a time-series design with Poisson regression adjusted for a predefined set of confounders was used to quantify the association between exposure, calculated as daily PM10 levels extrapolated from machine-learning models using satellite data, and cause-specific mortality. SETTING AND PARTICIPANTS: twenty municipalities near the thermal power plants in Civitavecchia and Brindisi were selected. The municipalities were then divided into three scenarios of chronic exposure derived from SPRAY simulation models of pollutant deposition. MAIN OUTCOME MEASURES: daily cause-specific non-accidental, cardiovascular, and respiratory deaths defined according to the International Classification of Diseases code at the municipality level. RESULTS: a total of 41,942 deaths were observed in the entire area (10,503 in the Civitavecchia area and 31,439 in the Brindisi area), of which approximately 41% were due to cardiovascular causes and 8% due to respiratory causes. The association showed an increase in shortterm effects in municipalities with higher chronic levels of pollution exposure. For example, risk estimates reported as percentage increases per 10-unit increase in PM10 were 6.7% (95% CI 0.9, 12.7%) in scenario 3 (highest exposure) compared to 4.2% (-1.2, 9.9%) and 2.7% (-4.2, 10.2%) in scenarios 2 and 1, respectively, in the area near the Civitavecchia plant. Similar effects were observed for the Brindisi area. CONCLUSIONS: despite the well-documented relationship between short-term pollution and mortality, it appears that greater chronic exposure to industrial pollutants leads to increased short-term effects of PM10. The limited number of events suggests that this study could serve as a starting point for a larger investigation.
Subject(s)
Air Pollutants , Air Pollution , Environmental Pollutants , Humans , Air Pollutants/analysis , Cause of Death , Italy , Air Pollution/adverse effects , Air Pollution/analysis , Environmental Pollution , Particulate Matter/toxicity , Particulate Matter/analysis , Environmental Exposure/adverse effects , Environmental Exposure/analysisABSTRACT
OBJECTIVES: to estimate the impact of daily exposure to extreme air temperatures (heat and cold) on cause-specific mortality in Italy and to evaluate the differences in the association between urban, suburban and rural municipalities. DESIGN: time series analyses with two-stage approach were applied: in the first stage, multiple Poisson regression models and distributed lag non-linear models (DLNM) were used to define the association between temperature and mortality; in the second one, meta-analytic results were obtained by adopting BLUP (Best Linear Unbiased Prediction) coefficients at provincial level, which were then used to estimate the Attributable Fractions of cause-specific deaths. SETTING AND PARTICIPANTS: cause-specific deaths from 2006to 2015 in Italy have been analysed by region and overall. MAIN OUTCOME MEASURES: 5,648,299 total deaths included. Fractions (and relative 95% empirical confidence interval) of deaths attributable to increases from 75th to 99th percentiles of temperature, for heat, and decreases from 25th to 1st percentile, for cold. RESULTS: the overall impact of air temperature on causespecificmortality is higher for heat than for cold. When considering heat, the attributable fraction is higher for diseases of the central nervous system (3.6% 95% CI 1.9-4.9) and mental health disease (3.1% 95% CI 1.7-4.4), while considering cold, ischemic disease (1.3% 95% CI 1.1-1.6) and diabetes (1.3% 95% CI 0.7-1.8) showed the greater impact. By urbanization level, similar impacts were found for cold temperature, while for heat there was an indication of higher vulnerability in rural areas emerged. CONCLUSIONS: results are relevant for the implementation and promotion of preventive measures according to climate change related increase in temperature. The available evidence can provide the basis to identify vulnerable areas and population subgroups to which address current and future heat and cold adaptation plans in Italy.
Subject(s)
Cold Temperature , Hot Temperature , Humans , Italy/epidemiology , Temperature , Cities , MortalityABSTRACT
OBJECTIVES: appropriate assessment of exposure to air pollution is crucial for the estimation of adverse effects on human health, both in the short and long term. Within the BIGEPI project, different indicators of long-term exposure to air pollution, in association with mortality by cause, were tested within the Italian longitudinal metropolitan studies (LMS). This allowed an evaluation of differences in effect estimates using the different exposure indicators. DESIGN: closed cohort. SETTING AND PARTICIPANTS: subjects aged >=30, who took part in the 2011 census, residents in 5 cities (Turin, Bologna, Rome, Brindisi and Taranto). MAIN OUTCOME MEASURES: at the time of enrolment, residential exposure levels to particulate matter <=10 µm (PM10), PM <=2.5 µm (PM2.5), nitrogen dioxide (NO2) and ozone (O3) for the period April-September (O3 warm season) were obtained from models at different spatial resolutions, from 1x1km to 200x200m (from the BEEP project) to 100x100m (ELAPSE project). In addition, locally developed models were used in each area (FARM photochemical model at 1x1-km for the cities of Rome, Taranto and Brindisi, Land-Use Regression (LUR) model for the city of Turin, PESCO model for Bologna). Cox proportional hazards models were applied to assess the association between exposure to air pollution (assessed using different exposure indicators) and natural mortality, adjusting for both individual and area covariates. RESULTS: the exposure levels derived by the different models varied between pollutants, with differences between the averages ranging from 3 to 20% for PM10, from 1 to 23% for PM2.5, and from 3 to 28% for NO2; the results for O3 were more heterogeneous. A total of 267,350 deaths from natural causes were observed. There is low heterogeneity in the effect estimates calculated from different environmental models, while there is greater variability in average exposure values, with different behaviour depending on the model and the characteristics of the area investigated. Differences are more pronounced where local risk factors are relevant, e.g., in industrial cities, thus suggesting the need of considering industrial exposure separately from other sources. CONCLUSIONS: the numerous heterogeneities in the data used make it difficult to draw conclusions about the comparisons studied. Nevertheless, this study suggests that different approaches to the assessment of environmental exposure should be evaluated depending on the national or local level of interest, also according to the specifities of the investigated areas.
Subject(s)
Air Pollutants , Air Pollution , Humans , Air Pollutants/toxicity , Air Pollutants/analysis , Nitrogen Dioxide/adverse effects , Italy/epidemiology , Air Pollution/adverse effects , Air Pollution/analysis , Particulate Matter/adverse effects , Particulate Matter/analysis , Environmental Exposure/adverse effects , Environmental Exposure/analysisABSTRACT
OBJECTIVES: to assess the association between the occupational sector and respiratory mortality in the metropolitan longitudinal studies of Rome and Turin. DESIGN: retrospective cohort study. SETTING AND PARTICIPANTS: the 2011 census cohorts of residents of Rome and Turin aged 30 years and older who had worked for at least one year in the private sector between 1970s and 2011 was analysed. The individuals included in the study were followed from 9 October 2011 to 31 December 2018. Occupational history was obtained from archives of private sector contributions at the National Social Insurance Agency (INPS) and then was linked to data from the longitudinal studies. MAIN OUTCOME MEASURES: the study outcome was non-malignant respiratory mortality. The exposure of interest was whether or not individuals had worked in one of the 25 occupational sectors considered (agriculture and fishing, steel industry, paper and printing, pharmaceuticals, manufacturing, textile, energy and water, food and tobacco industry, non-metal mining, glass & cement industry, metal processing, electrical construction, footwear and wood industry, construction, trade, hotel and restaurants, transportation, insurance, healthcare, services, laundries, waste management, hairdressing, cleaning services, and gas stations). The association between the occupational sector and respiratory mortality, adjusted for potential confounders (age, marital status, place of birth, educational level), was estimated using Cox models. All analyses were stratified by sex and city. RESULTS: a total of 910,559 people were analysed in Rome and 391,541 in Turin. During the eight years of follow-up, 4,133 people in Rome and 2,772 people in Turin died from respiratory causes. The sectors associated with high respiratory mortality in both cities among men were footwear and wood industry (adjusted HR for age: 1.37 (95%CI 1.07-1.76) and 1.48 (95%CI 1.08-2.03) in Rome and Turin, respectively), construction (HR: 1.31 (95%CI 1.20-1.44) in Rome and 1.51 (95%CI 1.31-1.74) in Turin), hotel and restaurant sector (HR: 1.25 (95%CI 1.07-1.46) in Rome and 1.68 (95%CI 1.20-2.33) in Turin), and cleaning services (HR: 1.57 (95%CI 1.19-2.06) in Rome and 1.97 (95%CI 1.51-2.58) in Turin). Some sectors had high respiratory mortality only in one of the two cities: in Rome, the food& tobacco industry, and gas stations, while in Turin, the metal processing industry. Among female workers, the cleaning services sector was associated with higher respiratory mortality in both Rome and Turin (HR: 1.52, 95%CI 1.27-1.82, e 1.58, 95%CI 1.17-2.12, respectively). CONCLUSIONS: the data confirm the previously known associations between occupational sectors and respiratory mortality for exposures characteristic of specific sectors, such as construction, hotel and restaurant sector, and cleaning services. The differences reported between the two cities reflect the different composition of the workforce and the size of the two study populations. Administrative social insurance data can provide helpful information for epidemiological studies of occupational exposure.
Subject(s)
Employment , Respiratory Tract Diseases , Male , Humans , Female , Infant , Retrospective Studies , Rome/epidemiology , Italy , Longitudinal StudiesABSTRACT
OBJECTIVES: occupational exposure to vapours, gases, dusts and fumes (VGDF) plays an important role in the development and exacerbation of respiratory diseases. The aim of this study is to evaluate the possible association of occupational exposure to airborne pollutants and chronic respiratory diseases. DESIGN: multicase-control study. SETTING AND PARTICIPANTS: cases of chronic respiratory diseases and controls from the Italian multicentric study Gene Environment Interaction in Respiratory Diseases (GEIRD). MAIN OUTCOME MEASURES: the occurrence of rhinitis, asthma, chronic bronchitis/chronic obstructive pulmonary disease (COPD), asthma severity, spirometry data, exhaled nitric oxide (FeNO) were examined in relation to chronic and acute occupational exposures to airborne pollutants using multiple regression models. RESULTS: 2,943 subjects were enrolled in the study. Regularm exposure to VGDF was associated with a higher prevalence of chronic bronchitis/COPD (OR 1.40, 95%CI 0.98-1.99), especially in those also having asthma (OR 1.80, 95%CI 1.14-2.85), a lower prevalence of remittent asthma (OR 0.53, 95%CI 0.29-0.96) and, in those with asthma, an increased activity of the disease (severity score) (OR 1.77, 95%CI 1.20-2.60). No associations were observed between occupational exposure and prevalence of rhinitis, spirometry and FeNO data. Finally, an association was found between acute exposure to airborne pollutants (occupational and non-occupational) and the respiratory diseases investigated, in particular active asthma and asthma associated chronic bronchitis/BPCO. CONCLUSIONS: these data confirm a significant role of occupational exposure to airborne pollutants on respiratory health, underlying the importance of workplace exposure prevention, in particular for more susceptible subjects, as those with respiratory diseases.
Subject(s)
Asthma , Bronchitis, Chronic , Environmental Pollutants , Occupational Diseases , Occupational Exposure , Pulmonary Disease, Chronic Obstructive , Respiration Disorders , Rhinitis , Humans , Bronchitis, Chronic/epidemiology , Bronchitis, Chronic/etiology , Prevalence , Risk Factors , Occupational Diseases/epidemiology , Occupational Diseases/etiology , Italy/epidemiology , Pulmonary Disease, Chronic Obstructive/epidemiology , Pulmonary Disease, Chronic Obstructive/etiology , Asthma/epidemiology , Asthma/etiology , Occupational Exposure/adverse effects , Workplace , GasesABSTRACT
OBJECTIVES: to assess the potential of using longitudinal metropolitan studies (LMS) to study the association between long-term exposure to air pollution and the incidence of acute coronary events and stroke. DESIGN: closed cohort. SETTING AND PARTICIPANTS: subjects aged >=30 years, who took part in the 2011 census, residents in 5 cities (Turin, Bologna, Rome, Brindisi and Taranto). Annual concentrations of particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2) and warm-season ozone (O3) (annual O3 in Taranto and Brindisi), estimated through satellite (Turin, Bologna, Rome) or photochemical models (Taranto and Brindisi) with a spatial resolution of 1 km2, were assigned to the census address. MAIN OUTCOME MEASURES: incidence of coronary heart disease (CHD) and stroke until 31.12.2018 (2019 in Bologna). Cohort-specific Hazard Ratios (HRs), estimated using Cox regression models progressively adjusting for individual and contextual covariates, were pooled with random-effect meta-analysis. RESULTS: there were 71,872 incident CHD cases and 43,884 incident cases of stroke in almost 18 million person-years. No association was observed between the exposures studied and incidence of CHD and stroke, except for an increase in the incidence of CHD associated with warm-season O3 exposure (HR 1.034 per 5 µg/m3 increase). Some positive associations were found in specific cities (both outcomes in Brindisi with PM10 exposure and in Taranto with NO2 exposure, stroke in Rome with both PM10 and PM2.5), although estimates were not significant in some instances. CONCLUSIONS: LMS are a high potential tool for the study of comparative medium- and long-term effects of air pollution. Their further development (different definitions of exposure, outcomes, characteristics of the urban areas and extension to other LMS) may make them even more valuable tools for monitoring and planning public health interventions.