[Long-term exposure to ambient air pollution and the incidence of SARS-CoV-2 infections in Italy: The EpiCovAir study]. / Esposizione a lungo termine a inquinamento dell'aria ambiente e incidenza di infezioni di SARS-CoV-2 in Italia: lo studio EpiCovAir.

BACKGROUND: after the outbreak of the SARS-CoV-2 pandemic in 2020, several waves of pandemic cases have occurred in Italy. The role of air pollution has been hypothesized and investigated in several studies. However, to date, the role of chronic exposure to air pollutants in increasing incidence of SARS-CoV-2 infections is still debated. OBJECTIVES: to investigate the association between long-term exposure to air pollutants and the incidence of SARS-CoV-2 infections in Italy. DESIGN: a satellite-based air pollution exposure model with 1-km2 spatial resolution for entire Italy was applied and 2016-2019 mean population-weighted concentrations of particulate matter < 10 micron (PM10), PM <2.5 micron (PM2.5), and nitrogen dioxide (NO2) was calculated to each municipality as estimates of chronic exposures. A principal component analysis (PCA) approach was applied to 50+ area-level covariates (geography and topography, population density, mobility, population health, socioeconomic status) to account for the major determinants of the spatial distribution of incidence rates of SARS-CoV-2 infection. Detailed information was further used on intra- and inter-municipal mobility during the pandemic period. Finally, a mixed longitudinal ecological design with the study units consisting of individual municipalities in Italy was applied. Generalized negative binomial models controlling for age, gender, province, month, PCA variables, and population density were estimated. SETTING AND PARTICIPANTS: individual records of diagnosed SARS-2-CoV-2 infections in Italy from February 2020 to June 2021 reported to the Italian Integrated Surveillance of COVID-19 were used. MAIN OUTCOME MEASURES: percentage increases in incidence rate (%IR) and corresponding 95% confidence intervals (95% CI) per unit increase in exposure. RESULTS: 3,995,202 COVID-19 cases in 7,800 municipalities were analysed (total population: 59,589,357 inhabitants). It was found that long-term exposure to PM2.5, PM10, and NO2 was significantly associated with the incidence rates of SARS-CoV-2 infection. In particular, incidence of COVID-19 increased by 0.3% (95%CI 0.1%-0.4%), 0.3% (0.2%-0.4%), and 0.9% (0.8%-1.0%) per 1 µg/m3 increment in PM2.5, PM10 and NO2, respectively. Associations were higher among elderly subjects and during the second pandemic wave (September 2020-December 2020). Several sensitivity analyses confirmed the main results. The results for NO2 were especially robust to multiple sensitivity analyses. CONCLUSIONS: evidence of an association between long-term exposure to ambient air pollutants and the incidence of SARS-CoV-2 infections in Italy was found.

[Long-term exposure to air pollution and natural mortality: variations related to the use of different exposure indicators in the cohorts of BIGEPI project]. / Esposizione di lungo periodo all'inquinamento atmosferico e mortalità naturale: variazioni legate all'utilizzo di diversi indicatori di esposizione nelle coorti del progetto BIGEPI.

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.

A Methodological Approach to Use Contextual Factors for Epidemiological Studies on Chronic Exposure to Air Pollution and COVID-19 in Italy.

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.

Source-related components of fine particulate matter and risk of adverse birth outcomes in Northern Italy.

BACKGROUND/AIM: The aim of the present study was to assess the association between PM2.5, its sources, and preterm birth (PTB), low birth weight (LBW), and small for gestational age (SGA) in a large open residential cohort (Supersito Project in the Emilia-Romagna Region - Northern Italy). METHODS: We collected 2012-2014 pregnancy and childbirth data from Birth Assistance Certificates and selected the pregnancies of interest. PTBs (gestational age < 37 weeks), LBW (weight < 2500 g), and SGA (newborns weighing ≤ 10th age and pregnancy week-specific percentile) were considered. Three-year measurements of daily concentrations and constituents of PM2.5 were available at four sites and were analyzed through a source apportionment approach identifying 6 sources (traffic, biomass burning, oil combustion, anthropogenic mix, and two secondary factors). Exposure to PM2.5 and sources was calculated at address level. Using logistic regression models, associations between exposure and outcomes were derived, applying single-pollutant and two-pollutant models, to verify the independent effect of each source. RESULTS: The study included 23,708 neonates born to 23,415 women, among whom 1,311 PTB, 424 LBW, and 1,354 SGA occurred. PTB was the only outcome associated with PM2.5 mass (OR 1.03, 95% CI 1.002-1.058 per 1 µg/m3). Traffic, oil combustion and secondary sulfates and organics showed independent effects on PTB. Exposure to secondary nitrates was associated with a lower risk of PTB. There was no association between LBW or SGA and source-specific PM2.5 components or the residual PM2.5 related to all other sources. CONCLUSION: This study found an association between PTB and PM2.5. Traffic, secondary sulfates, and organic and oil combustion were the sources with most consistent association.

Estimating deaths attributable to airborne particles: sensitivity of the results to different exposure assessment approaches.

BACKGROUND: Epidemiological evidences support the existence of an effect of airborne particulate on population health. However, few studies evaluated the robustness of the results to different exposure assessment approaches. In this paper, we estimated short term effects and impacts of high levels of particulate matter with aerodynamic diameter ≤10 µm (PM10) and ≤2.5 µm (PM2.5) in the Emilia-Romagna region (Northern Italy), one of the most polluted areas in Europe, in the period 2006-2010, and checked if the results changed when different exposure definitions were used. METHODS: Short-term impact of particles on population mortality was assessed, both considering the 9 provincial capitals of the Emilia-Romagna and the region as a whole. We estimated the effects of PM10 and PM2.5 on natural mortality by combining city-specific results in a Bayesian random-effects meta-analysis, and we used these estimates to calculate impacts in terms of attributable deaths. For PM10, we considered different definitions of exposure, based on the use of the air pollutant levels measured by different monitoring stations (background or traffic monitors) or predicted by a dispersion model. RESULTS: Annual average concentrations of PM10 and PM2.5 exceeding the WHO limits of 20 and 10 µg/m3 were respectively responsible for 5.9 and 3.0 deaths per 100 000 inhabitants per year in the provincial capitals, during the period 2006-2010. The total impact in the region in 2010 amounted to 4.4 and 2.8 deaths per 100 000 for PM10 and PM2.5, respectively. The impact estimates for PM10 did not substantially change when the exposure levels were derived from background or traffic monitoring stations, or arose from the dispersion model, in particular when the counterfactual value of 20 µg/m3 was considered. The effect estimates appeared more sensitive to the exposure definition. CONCLUSIONS: A reduction in particle concentrations could have produced significant health benefits in the region. This general conclusion did not change when different exposure definitions were used, provided that the same exposure assessment approach was used for both effect and impact estimations. Caution is therefore recommended when using effect estimates from the literature to assess health impacts of air pollution in actual contexts.

Association Between Short-Term Exposure to PM2.5 and PM10 and Mortality in Susceptible Subgroups: A Multisite Case-Crossover Analysis of Individual Effect Modifiers.

We performed a multisite study to evaluate demographic and clinical conditions as potential modifiers of the particulate matter (PM)-mortality association. We selected 228,619 natural deaths of elderly persons (ages ≥65 years) that occurred in 12 Italian cities during the period 2006-2010. Individual data on causes of death, age, sex, location of death, and preexisting chronic and acute conditions from the previous 5 years' hospitalizations were collected. City-specific conditional logistic regression models were applied within the case-crossover "time-stratified" framework, followed by random-effects meta-analysis. Particulate matter less than or equal to 2.5 µm in aerodynamic diameter (PM2.5) and particulate matter less than or equal to 10 µm in aerodynamic diameter (PM10) were positively associated with natural mortality (1.05% and 0.74% increases in mortality risk for increments of 10 µg/m3 and 14.4 µg/m3, respectively), with greater effects being seen among older people, those dying out-of-hospital or during the warm season, and those affected by 2 or more chronic diseases. Limited associations were found among persons with no previous hospital admissions. Diabetes (1.98%, 95% confidence interval (CI): 0.54, 3.44) and cardiac arrhythmia (1.65%, 95% CI: 0.37, 2.95) increased risk of PM2.5-related mortality, while heart conduction disorders increased risk of mortality related to both PM2.5 (4.22%, 95% CI: 0.15, 8.46) and PM10 (4.19%, 95% CI: 0.38, 8.14). Among acute conditions, recent hospital discharge for heart failure modified the PM10-mortality association. The study found increases in natural mortality from PM exposure among people with chronic morbidity; diabetes and cardiac disorders were the main susceptibility factors.

[Uncertainty in estimating short-term health effects of air pollution in small- and medium-size cities]. / Incertezza delle stime degli effetti sanitari a breve termine dell'inquinamento atmosferico in città di medio-piccole dimensioni.

Over the years, a growing number of small- and medium-size cities have been included in meta-analytic studies on short-term health effects of air pollution in order to increase the statistical power of these studies. This has produced an increase in the precision of meta-analytic estimates, but also a growing interest in city-specific results. As a consequence, relevant differences in the estimates have been frequently found, even for nearby cities with similar environmental and sociodemographic characteristics. This article aims at showing the variability of effect estimates for small- to medium-size cities in relation to the extent of the considered time frame, highlighting quantitatively the caution that must be taken in interpreting and communicating the results derived from short time series of data. The study was based on the analysis of the data from two cities in Emilia-Romagna Region (Northern Italy): Ravenna and Reggio Emilia.

[Environmental indicators in EpiAir2 project: air quality data for epidemiological surveillance]. / Indicatori ambientali nello studio EpiAir2: i dati di qualità dell'aria per la sorveglianza epidemiologica.

OBJECTIVE: construction of environmental indicators of air pollution suitable for epidemiological surveillance in 25 Italian cities for EpiAir2 project (2006-2010) and presentation of the results from a 10 years of surveillance system (2001-2010) in 10 Italian cities. DESIGN: data on particulate matter (PM10 and its fine fraction PM2.5), nitrogen dioxide (NO2), and ozone (O3), measured in the 2006-2010 calendar period, were collected. Meteorological data needed to estimate unbiased measures of the effect of pollutants are: temperature, relative humidity (estimated "apparent temperature"), and barometric pressure. In continuity with the previous EpiAir project, the same criteria for the selection of monitoring stations were applied and standard methods to estimate daily environmental indicators were used. Furthermore, it was checked the adequacy of the selected data to represent the population exposure. SETTING AND PARTICIPANTS: EpiAir2 project, relative to the period 2006-2010, involves the cities of Milano, Mestre-Venezia, Torino, Bologna, Firenze, Pisa, Roma, Taranto, Cagliari, and Palermo, already included in the previous study. The city of Treviso, Trieste, Padova, Rovigo, Piacenza, Parma, Ferrara, Reggio Emilia, Modena, Genova, Rimini, Ancona, Bari, Brindisi, and Napoli are added to the previous group. RESULTS: particulate matter concentrations have decreased in most cities during the study period, while concentrations of NO2 and ozone do not show a similar clear trend. The analysis of the trend showed annual mean values of PM10 higher than 40 µg/m(3) in some areas of the Po Valley, and annual mean values of NO2 higher than 40 µg/m(3) in the cities of Trieste, Milano, Padova, Torino, Modena, Bologna, Roma, and Napoli. CONCLUSION: the enlargement of the EpiAir project to 13 other cities has highlighted critical issues related to the different geographical areas under study. Results of EpiAir2 project point out the need of a monitoring system of air pollution concentrations in both urban and industrial sites, in order to obtain reliable estimates of exposure for resident populations and to evaluate the related time trend.

[Air pollution and urgent hospital admissions in 25 Italian cities: results from the EpiAir2 project]. / Inquinamento atmosferico e ricoveri ospedalieri urgenti in 25 città italiane: risultati del progetto EpiAir2.

OBJECTIVE: to evaluate the relationship between air pollution and hospital admissions in 25 Italian cities that took part in the EpiAir (Epidemiological surveillance of air pollution effects among Italian cities) project. DESIGN: study of time series with case-crossover methodology, with adjustment for meteorological and time-dependent variables. The association air pollution hospitalisation was analyzed in each of the 25 cities involved in the study; the overall estimates of effect were obtained subsequently by means of a meta-analysis. The pollutants considered were PM10, PM2.5 (in 13 cities only), NO2 and ozone (O3); this last pollutant restricted to the summer season (April-September). SETTING AND PARTICIPANTS: the study has analyzed 2,246,448 urgent hospital admissions for non-accidental diseases in 25 Italian cities during the period 2006- 2010; 10 out of 25 cities took part also in the first phase of the project (2001-2005). MAIN OUTCOME MEASURES: urgent hospital admissions for cardiac, cerebrovascular and respiratory diseases, for all age groups, were considered. The respiratory hospital admissions were analysed also for the 0-14-year subgroup. Percentage increases risk of hospitalization associated with increments of 10 µg/m(3) and interquartile range (IQR) of the concentration of each pollutant were calculated. RESULTS: reported results were related to an increment of 10 µg/m(3) of air pollutant. The percent increase for PM10 for cardiac causes was 0.34% at lag 0 (95%CI 0.04-0.63), for respiratory causes 0.75% at lag 0-5 (95%CI 0.25-1.25). For PM2.5, the percent increase for respiratory causes was 1.23% at lag 0- 5 (95%CI 0.58-1.88). For NO2, the percent increase for cardiac causes was 0.57% at lag 0 (95%CI 0.13-1.02); 1.29% at lag 0-5 (95%CI 0.52-2.06) for respiratory causes. Ozone (O3) did not turned out to be positively associated neither with cardiac nor with respiratory causes as noted in the previous period (2001-2005). CONCLUSION: the results of the study confirm an association between PM10, PM2.5, and NO2 on hospital admissions among 25 Italian cities. No positive associations for ozone was noted in this period.

[Air pollution and mortality in twenty-five Italian cities: results of the EpiAir2 Project]. / Inquinamento atmosferico e mortalità in venticinque città italiane: risultati del progetto EpiAir2.

OBJECTIVES: this study aims at presenting the results from the Italian EpiaAir2 Project on the short-term effects of air pollution on adult population (35+ years old) in 25 Italian cities. DESIGN: the short-term effects of air pollution on resident people died in their city were analysed adopting the time series approach. The association between increases in 10µg/m(3) in PM10, PM2.5, NO2 and O3 air concentration and natural, cardiac, cerebrovascular and respiratory mortality was studied. City-specific Poisson models were fitted to estimate the association of daily concentrations of pollutants with daily counts of deaths. The analysis took into account temporal and meteorological factors to control for potential confounding effect. Pooled estimates have been derived from random effects meta-analysis, evaluating the presence of heterogeneity in the city specific results. SETTING AND PARTICIPANTS: it was analysed 422,723 deaths in the 25 cities of the project among people aged 35 years or more, resident in each city during the period 2006-2010. MAIN OUTCOME MEASURES: daily counts of natural, cardiac, cerebrovascular, and respiratory mortality, obtained from the registries of each city. Demographic information were obtained by record linkage procedure with the civil registry of each city. RESULTS: mean number of deaths for natural causes ranged from 513 in Rovigo to 20,959 in Rome. About 25% of deaths are due to cardiac diseases, 10% to cerebrovascular diseases, and 7% to respiratory diseases. It was found an immediate effect of PM10 on natural mortality (0.51%; 95%CI 0.16-0.86; lag 0-1). More relevant and prolonged effects (lag 0-5) have been found for PM2.5 (0.78%; 95%CI 0.12-1.46) and NO2 (1.10%; 95%CI 0.63-1.58). Increases in cardiac mortality are associated with PM10 (0.93%; 95%CI 0.16-1.70) and PM2.5 (1.25%; 95%CI 0.17-2.34), while for respiratory mortality exposure to NO2 has an important role (1.67%; 95%CI 0.23-3.13; lag 2-5), as well as PM10 (1.41%; 95%CI - 0.23;+3.08). Results are strongly homogeneous among cities, except for respiratory mortality. No effect has been found for cerebrovascular mortality and weak evidence of association has been observed between ozone and mortality. CONCLUSIONS: a clear increase in mortality associated to air pollutants was observed. More important are the effects of NO2 (on natural mortality), mostly associated with traffic emissions, and of PM2.5 (on cardiac and respiratory mortality). Nitrogen dioxide shows an independent effect from the particulate matter, as observed in the bi-pollutant models.