Health impact of air pollution and air temperature in Italy: evidence for policy actions

OBJECTIVES: to estimate the impact (number of deaths and attributable fraction) of air pollution (chronic exposure to PM2.5 and NO2) and high summer temperatures (acute exposure) on mortality in Italy. DESIGN: observational study. Time series analysis (for estimating acute effects of air temperature), and computation of deaths attributable to heat/pollution using standard health impact assessment functions. SETTING AND PARTICIPANTS: for the assessment of the impact due to chronic exposure to air pollutants, the study period considered was 2016-2019. For the assessment of the acute effects of air temperature and related impacts, the municipal daily series of deaths from all causes relating to the period 2003-2015 were used. MAIN OUTCOME MEASURES: mortality for all causes (effects and impacts of acute exposure to air temperature), cause-specific mortality (impact of chronic exposure to pollution). RESULTS: concerning chronic exposure to PM2.5, each year during 2016-2019, 72,083 deaths (11.7%) were estimated to be attributable to annual mean levels of PM2.5 above 5 µg/m3 (WHO-2021 Air Quality Guideline value). Of these, 39,628 were estimated in the regions of the Po Valley and 10,232 in the 6 Italian cities with >500,000 inhabitants. With reference to acute effects of air temperature, over 14,500 deaths (2.3%) were estimated to be attributable to daily temperature increases from the 75th to the 99th percentile of the municipality-specific distribution for the year 2015. Conclusions: high air pollution concentrations and summer temperatures are two environmental risk factors extremely relevant for public health. Although the prevention and mitigation interventions carried out in recent years have contributed to reducing the exposure of the population, there are still alarming numbers of deaths attributable to high levels of particulate matter, nitrogen oxides, and air temperature in the Italian population.

[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.

[Long-term exposure to air pollution and incidence of coronary heart diseases and stroke in the longitudinal metropolitan studies (LMS) network: the BIGEPI project]. / Esposizione di lungo periodo all'inquinamento atmosferico e incidenza di malattia coronarica acuta e ictus nella rete degli studi longitudinali metropolitani: il progetto BIGEPI.

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.

[BIGEPI project: environmental and health data]. / Progetto BIGEPI: dati ambientali e dati sanitari.

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.

Atmospheric particulate matter effects on SARS-CoV-2 infection and spreading dynamics: A spatio-temporal point process model.

Particulate matter (PM) may play a role in differential distribution and transmission rates of SARS-CoV-2. For public health surveillance, identification of factors affecting the transmission dynamics concerning the endemic (persistent sporadic) and epidemic (rapidly clustered) component of infection can help to implement intervention strategies to reduce the disease burden. The aim of this study is to assess the effect of long-term residential exposure to outdoor PM ≤ 10 µm (PM10) concentrations on SARS-CoV-2 incidence and on its spreading dynamics in Marche region (Central Italy) during the first wave of the COVID-19 pandemic (February to May 2020), using the endemic-epidemic spatio-temporal regression model for individual-level data. Environmental and climatic factors were estimated at 10 km2 grid cells. 10-years average exposure to PM10 was associated with an increased risk of new endemic (Rate Ratio for 10 µg/m3 increase 1.14, 95%CI 1.04-1.24) and epidemic (Rate Ratio 1.15, 95%CI 1.08-1.22) infection. Male gender, older age, living in Nursing Homes and Long-Term Care Facilities residence and socio-economic deprivation index increased Rate Ratio (RR) in epidemic component. Lockdown increased the risk of becoming positive to SARS-CoV-2 as concerning endemic component while it reduced virus spreading in epidemic one. Increased temperature was associated with a reduction of endemic and epidemic infection. Results showed an increment of RR for exposure to increased levels of PM10 both in endemic and epidemic components. Targeted interventions are necessary to improve air quality in most polluted areas, where deprived populations are more likely to live, to minimize the burden of endemic and epidemic COVID-19 disease and to reduce unequal distribution of health risk.

Health impact assessment should be based on correct methods.

The methodology of health impact assessment (HIA), originally proposed by WHO, is widely used to predict the potential health effects in a community living in a place in which a new project (e.g., an industrial plant) will be implemented. One of the key quantities to calculate the impact (i.e., the number of attributable cases) is the baseline (i.e., before the project implementation) rate of selected diseases in the community. In a recent paper on this journal, this methodology has been challenged. Specifically, the use of baseline rate has been questioned, proposing to use only the fraction of the baseline rate due to the exposures related to the project, and not the rate due to all risk factors for the disease. In this commentary, we argue that the proposal is logically and epidemiologically unsound, and devoid of scientific motivation. The conclusion that the traditional approach overestimates the health impact should be rejected as based on flawed assumptions. On the contrary, the proposal may produce a (seriously biased) underestimation of attributable cases.

[Health impact: considering only a plant assessment is not enough, an area assessment is also needed]. / Impatto sanitario: la valutazione del singolo impianto non è sufficiente, occorre anche una valutazione di area.

Environmental Impact Assessments (EIAs) often conclude with a "low" or at least "negligible" final health impact assessment (HIA) of the industrial plant under assessment. We explore the reasons for this - often simplistic - conclusion and offer suggestions on how to extend the assessment focus from just the plant to an appropriate impact area. For many assessments, the conclusions are easily predictable: the application of available risk functions to modest increases in pollution, in the presence of numerically small populations in the areas of greatest fallout and considering rather rare health outcomes, can only result in quantitatively modest health impacts. This is the classic situation of low sensitivity of the observation system due to the impossibility of containing the type II error (false negatives) since we cannot increase the exposed population at will. The risk is to give the green light to an industrial plant in which the apparently null or very limited damage is simply not properly detectable. There is hardly any trace of these elements in the HIA scoping phase. In environmental complex territories, the renewal or authorization of a new plant should consider not only the impact of the individual plant, but also the health profile of the population concerned and the context in which the industrial project is located. An 'HIA area' is therefore configured, aimed at the complex of environmental pressure factors that insist on the same area of impact of the plant. Epidemiology focuses on the exposed population, considers the 'current' state of health, hazard, and risk information from toxicology, and estimates individual exposure and the effects of exposure. The 'HIA area' can assess the impact of the complex of persistent emission sources, considering in the analysis the health status of the exposed population and the presence of specific vulnerabilities. The proposal is in line with what is already foreseen in the Essential levels of care and Environmental technical performance of the National Health Service.A basic condition is the establishment of functions dedicated to integrated environmental and health surveillance to update the health profile and carry out the 'HIA area' as an accompanying tool for local strategic planning. On these issues, the Italian Environment and Health Network (RIAS) has opened a discussion within the network and with any Italian regions.

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.

[Exposure assessment of air pollution in Italy 2016-2019 for future studies on air pollution and COVID-19]. / La valutazione dell'esposizione della popolazione italiana all'inquinamento atmosferico nel periodo 2016-2019 per lo studio della relazione tra inquinamento atmosferico e COVID-19.

Air pollution is one of the leading causes of death worldwide, with adverse effects related both to short-term and long-term exposure. It has also recently been linked to COVID-19 pandemic. To analyze this possible association in Italy, studies on the entire area of the peninsula are necessary, both urban and non-urban areas. Therefore, there is a need for a homogeneous and applicable exposure assessment tool throughout the country.Experiences of high spatio-temporal resolution models for Italian territory already exist for PM estimation, using space-time predictors, satellite data, air quality monitoring data.This work completes the availability of these estimations for the most recent years (2016-2019) and is also applied to nitrogen oxides and ozone. The spatial resolution is 1x1 km.The model confirms its capability of capturing most of PM variability (R2=0.78 and 0.74 for PM10 e PM2.5, respectively), and provides reliable estimates also for ozone (R2=0.76); for NO2 the model performance is lower (R2=0.57). The model estimations were used to calculate the PWE (population-weighted exposure) as the annual mean, weighted on the resident population in each individual cell, which represents the estimation of the Italian population's chronic exposure to air pollution.These estimates are ready 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.

Environmental pollution and COVID-19: the molecular terms and predominant disease outcomes of their sweetheart agreement.

As the Coronavirus situation (COVID-19) continues to evolve, many questions concerning the factors relating to the diffusion and severity of the disease remain unanswered.Whilst opinions regarding the weight of evidence for these risk factors, and the studies published so far are often inconclusive or offer contrasting results, the role of comorbidities in the risk of serious adverse outcomes in patients affected with COVID-19 appears to be evident since the outset. Hypertension, diabetes, and obesity are under discussion as important factors affecting the severity of disease. Air pollution has been considered to play a role in the diffusion of the virus, in the propagation of the contagion, in the severity of symptoms, and in the poor prognosis. Accumulating evidence supports the hypothesis that environmental particulate matter (PM) can trigger inflammatory responses at molecular, cellular, and organ levels, sustaining respiratory, cardiovascular, and dysmetabolic diseases.To better understand the intricate relationships among pre-existing conditions, PM, and viral infection, we examined the response at the molecular level of T47D human breast adenocarcinoma cells exposed to different fractions of PM. T47D cells express several receptors, including the aryl hydrocarbon receptor (AhR), and ACE2, the main - but not the only - receptor for SARS-CoV-2 entry.PM samples were collected in an urban background site located in the Northern area of the City of Bologna (Emilia-Romagna Region, Northern Italy) during winter 2013. T47D cells were exposed to organic or aqueous (inorganic) extracts at the final concentration of 8 m3 for a 4-hour duration. Both the concentration and the exposure time were chosen to resemble an average outdoor exposure. RNA was extracted from cells, purified and hybridised on 66k microarray slides from Agilent.The lists of differentially expressed genes in PM organic extracts were evaluated by using Metacore, and an enrichment analysis was performed to identify pathways maps, process networks, and disease by biomarkers altered after T47D treatment.The analysis of the modulated genes gave evidence for the involvement of PM in dysmetabolic diseases, including diabetes and obesity, and hypertension through the activation of the aryl hydrocarbon receptor (AhR) canonical pathway.On the basis of current knowledge, existing data, and exploratory experimental evidence, we tease out the likely molecular interplay that can ultimately tip the disease outcome into severity. Looking beyond ACE2, several additional key markers are identified. Disruption of these targets worsens pre-existing conditions and/or exacerbates the adverse effects induced by SARS-CoV-2 infection. Whilst appropriately designed, epidemiological studies are very much needed to investigate these associations based on our hypothesis of investigation, by reviewing recent experimental and epidemiological evidence, here we speculate and provide new insights on the possible role of environmental pollution in the exacerbation of effects by SARS-CoV-2 and other respiratory viruses. This work is intended to assist in the development of appropriate investigative approaches to protect public health.

Methods and data needs to assess health impacts of chemicals in industrial contaminated sites.

BACKGROUND: human exposure to mixtures of chemicals of toxicological interest, typically found in industrial contaminated sites (ICSs), has been associated with a broad range of different health outcomes. Deprived population groups endure most of the burden of disease and premature death associated to the exposure to those pollutants. Characterising the impacts on health of an ICS is a challenging process. Currently the two main methodological approaches used are Human Health Risk Assessment (HHRA) and Environmental Epidemiological (EE) studies. OBJECTIVES: review existing guidance and scientific evidence for HHRA and EE studies applied to contaminated sites that orientate in selecting the most suitable methodological approach for characterising health impacts in ICSs according to the site characteristics, and the availability of environmental, health and sociodemographic data. RESULTS: HHRA has evolved into a more holistic approach, placing more emphasis in planning, community involvement and adapting the dimension of the assessment to the problem formulation and to the availability of resources. Many different HHRA guidelines for contaminated sites has been published worldwide, and although they share a similar framework, the scientific evidence used for deriving reference values and the variet of policy options can result in a wide variability of health risk estimates. This paper condenses different options with the recommendations to use those tools, default values for environmental and exposure levels and toxicological reference values that most suit to the population and characteristics of the ICSs under evaluation. CONCLUSIONS: the suitability to use one or another approach to assess the impact of ICSs on health depends on the availability of data, cost-benefit aspects and the kind of problem that needs to be answered. Risk assessment based on toxicological data can be very rapid and cheap, providing direct information when the intervention to protect the health of population is urgent and no suitable dose-response functions are available from epidemiological studies. Conducting EE studies provide a deeper insight into the problem of the exposure to industrial pollutants that do not require extrapolation from data obtained from toxicological studies or other population, addressing the community concern's more directly. Complementing the results obtained from different approaches, including those from public health surveillance systems, might provide an efficient and complete response to the impact of ICSs.

Industrial contaminated sites and health: results of a European survey.

BACKGROUND: industrially contaminated sites (ICSs) have been recognised as a major public health concern since they involve exposure to multiple environmental stressors, normally distributed unevenly within population. The COST Action on Industrially Contaminated Sites and Health Network (ICSHNet) comprises a European network of experts and institutions to clarify needs and priorities for better characterising the impact on environment and health of ICS. OBJECTIVES: evaluate the availability of information and studies concerning selected ICSs in participating Countries within the ICSHNet, with particular consideration on the accessibility to environmental, health and demographic data, and research and assessment tools. METHODS: to evaluate the availability of data, an Action Questionnaire (AQ) was developed based on previous questionnaires used in different European projects and on expert consultation. The AQ, with 84 items organised in eight sections, was adapted to an on-line version using the software LimeSurvey. The survey was sent to 47 participants within the ICSHNet, to report over a list of 99 ICSs previously identified. RESULTS: information was gathered from 81 sites out of the initially selected 99, reported by 45 participants from 27 Countries (82% of Countries in the ICSHNet). The predominant polluting activities were waste disposal (46%) and chemical industries (37%), affecting all environmental media, but more extensively surface and groundwater (70%) and soil (68%). Main categories of contaminants affecting different media were heavy metals and chlorinated hydrocarbons, but also BTEX (benzene, toluene, ethylbenzene, and xylene) and ambient air pollutants (e.g., particulate matter, SOx). Human health risk assessment was the most prevalent methodological approach for characterising impacts on health (32%), followed by epidemiological studies (26%), and health impact assessment (12%). The low reporting, both referring to data availability or methodologies, could be due to absence of data, or to the fact that the reporting person (many of them from the public health sector) did not know how to reach the environmental information. CONCLUSIONS: survey findings suggest that improving the collection and access to specific environmental, health and demographic data related to ICSs is crucial to meet the methodological requirement to better analyse the health impact of ICSs.

[The Integrated Environmental Health Impact of emissions from a steel plant in Taranto and from a power plant in Brindisi, (Apulia Region, Southern Italy)]. / L'impatto ambientale e sanitario delle emissioni dell'impianto siderurgico di Taranto e della centrale termoelettrica di Brindisi.

OBJECTIVES: to estimate the environmental and health impact attributable to PM2.5 emissions from the ex-ILVA steel plant in Taranto and the ENEL power plant in Brindisi (Apulia Region, Southern Italy). DESIGN: a SPRAY Lagrangian dispersion model was used to estimate PM2.5 concentrations and population weighted exposures following the requirements of the Integrated Environmental Authorization (IEA) of the two plants under study. Available concentration-response functions (OMS/HRAPIE and updates) were used to estimate the number of attributable premature deaths. SETTING AND PARTICIPANTS: residents in the 40 municipalities of the domains of the VDS (assessment of health damage, according to the Regional Law n. 21/2012) of Brindisi (source: Italian National Institute of Statistics 2011 Census) and residents in Taranto, Statte, and Massafra (source: cohort study). MAIN OUTCOME MEASURES: mortality from natural causes, cardiovascular and respiratory diseases, and lung cancer attributable to PM2.5. Incremental lifetime cumulative risks (ILCRs) for lung cancer associated to PM2.5 exposure. RESULTS: there was a reduction of the estimated impacts from the pre to the post IEA-scenarios in both Taranto and Brindisi. In Taranto, ILCRs greater than 1x10-4; were estimated in 2010 and 2012; the ILCR was greater than 1x10-4; in the district of Tamburi (near the plant) also for the 2015 scenario. ILCRs estimated for Brindisi were between 1x10-6; and 4x10-5;. CONCLUSIONS: the Integrated Environmental Health Impact Assessment confirmed the results of the VDS conducted according to the toxicological risk assessment approach. An unacceptable risk was estimated for Tamburi also for the 2015 scenario, characterized by a production of 4.7 million tons of steel, about half compared to one foreseen by the IEA (8 mt.).

[SENTIERI: Epidemiological Study of Residents in National Priority Contaminated Sites. Fifth Report]. / SENTIERI: Studio epidemiologico nazionale dei territori e degli insediamenti esposti a rischio da inquinamento. Quinto Rapporto.

INTRODUCTION AND OBJECTIVES: This volume provides an update of the health status of the populations living in the National Priority Contaminated Sites (NPCSs) included in the SENTIERI Project. This update is part of an epidemiological surveillance programme carried out in NPCSs, promoted by the Italian Ministry of Health as a further step of a project started in 2006, when the health status of residents in contaminated sites was first addressed within the National Strategic Program "Environment and Health". The Report focuses on five health outcomes: mortality, cancer incidence, hospital discharges, congenital anomalies, and children, adolescents and young adults' health. A key element of SENTIERI project is the a priori evaluation of the epidemiological evidence of a causal association between the considered cause of disease and the exposure. When an a priori evidence is identified, it is given a greater importance in the comment of the study findings. METHODS: The present update of the SENTIERI Project concerns 45 NPCSs including in all 319 Italian Municipalities (out of over 8,000 Municipalities), with an overall population of 5,900,000 inhabitants at the 2011 Italian Census. Standardized Mortality Ratios (SMRs) and Standardized Hospitalization Ratios (SHRs), referring to a time window of 2006-2013, were computed for all the 45 NPCSs, using as a reference the corresponding mortality and hospitalization rates of the Regions where each NCPS is located. Standardized Incidence Ratios (SIRs) were computed by the Italian Association of Cancer Registries (AIRTUM) for the 22 NPCSs served by a Cancer Registry. AIRTUM covers about 56% of Italy, with partly different time-windows. SIRs have been estimated using as reference population the 4 macroareas in which Italy is divided (North-West, North-East, Centre, South). Prevalence of congenital anomalies was computed for 15 NPCSs. RESULTS: An all-cause excess of 5,267 and 6,725 deaths was observed, respectively, in men and women; the cancer death excess was of 3,375 in men and 1,910 in women. It was estimated an excess of cancer incidence of 1,220 case in men and 1,425 in women over a five-year time window. With regard to the diseases with an a priori environmental aetiological validity, an excess for malignant mesothelioma, lung, colon, and gastric cancer, and for non-malignant respiratory diseases was observed. Cancer excess mainly affected NPCSs with presence of chemical and petrochemical plants, oil refineries, and dumping hazardous wastes. An excess of non-malignant respiratory disease was also detected in NPCSs in which steel industries and thermoelectric plants were present. An excess of mesothelioma was observed in NPCSs characterized by presence of asbestos and fluoro-edenite; it was also observed where the presence of asbestos was not reported in the legislative national decrees which define the NPCS areas. It is worth noting that, even if the presence of asbestos is not reported in many NPCSs legislative decrees, petrochemical plants and steel industries, for instance, are often characterized by the presence of a large amount of this mineral that, in the past, was extensively used as an insulating material. For the first time, the present Report includes a focus on the health status of children and adolescents (1,160,000 subjects, aged 0-19 years), and young adults (660,000 subjects, aged 20-29 years). Among infants (0-1 year), an excess of 7,000 hospitalizations was observed, 2,000 of which due to conditions of perinatal origin. In the age class 0-14, an excess of 22,000 hospitalizations for all causes was observed; 4,000 of them were due to acute respiratory diseases, and 2,000 to asthma. Data on cancer incidence for subjects aged 0-24 years were derived from general population cancer registries for twenty NPCSs, and from children cancer registries (age group: 0-19 years) for six NPCSs; 666 cases where diagnosed in the age group 0-24 years, corresponding to an excess of 9%. The main contributions to this excess are from soft tissue sarcomas in children (aged 0-14 years), acute myeloid leukaemia in children (aged 0-14 years) and in the age group 0-29 years, non-Hodgkin lymphoma and testicular cancer in young adults (aged 20-29 years). In seven out of 15 NPCSs, an excess prevalence rate of overall congenital anomalies at birth was observed. Congenital anomalies excesses included the following sites: genital organs, heart, limbs, nervous system, digestive system, and urinary system. CONCLUSIONS: The main findings of SENTIERI Project have been the detection of excesses for the diseases which showed an a priori epidemiological evidence of a causal association with the environmental exposures specific for each considered NPCS. These observations are valuable within public health, because they contribute to priority health promotion activities. Looking ahead, the health benefits of an improved environmental quality might be appreciated in terms of reduction of the occurrence of adverse health effects attributable to each Site major pollutant agents. Due to the methodological approach of the present study, it was not possible to adjust for several confounding factors reported to be risk factors for the studied diseases (e.g., smoking, alcohol consumption, obesity). Even if excesses of mortality, hospitalization, cancer incidence, and prevalence of congenital anomalies were found in several NPCSs, the study design and the multifactorial aetiology of the considered diseases do not permit, for all of them, to draw conclusions in terms of causal links with environmental contamination. Moreover, it must be taken into consideration that economic factors and the availability of health services may also play a relevant role in a diseases outcome. A few observations regarding some methodological limitations of SENTIERI Project should be made. There is not a uniform environmental characterisation of the studied NPCSs in term of quality and detection of the pollutants, because this information is present in different databases which at present are not adequately connected. Moreover, the recognition of a contaminated site as a National Priority Site is based on soil and groundwater pollution, and the available information on air quality is currently sparse and not homogenous. Another limitation, in term of statistical power, is the small population size of many NPCSs and the low frequency of several health outcomes. A special caution must be paid in data interpretation when considering the correspondence between the contaminated areas and the municipality boundaries, as they do not always coincide perfectly: in some cases, a small municipality with a large industrial site, while in other settings only a part of the municipality is exposed to the sources of pollution. Furthermore, all available health information systems are currently accessible at municipality level. The real breakthrough is essentially comprised of the development and fostering of a networking system involving all local health authorities and regional environmental protection agencies operating in the areas under study. The possibility to integrate the geographic approach of SENTIERI Project with a set of ad hoc analytic epidemiological investigations, such as residential cohort studies, case control studies, children health surveys, biomonitoring surveys, and with socioepidemiological studies, might greatly contribute to the identification of health priorities for environmental remediation activities. Finally, as discussed in the last section of the report, there is a need to adopt, in each NPCS, a two-way oriented communication plan involving public health authorities, scientific community, and resident population, taking into account that the history, the cultural frame and the network of relationships specific of each local context play a major role in the risk perception perspective.

Human biomonitoring as a tool for exposure assessment in industrially contaminated sites (ICSs). Lessons learned within the ICS and Health European Network.

BACKGROUND: the mixed and complex nature of industrially contaminated sites (ICSs) leads to heterogeneity in exposure and health risk of residents living nearby. Health, environment, and social aspects are strongly interconnected in ICSs, and local communities are often concerned about potential health impact and needs for remediation. The use of human biomonitoring (HBM) for impact assessment of environmental exposure is increasing in Europe. The COST Action IS1408 on Industrially Contaminated Sites and Health Network (ICSHNet) decided to reflect on the potential and limitations of HBM to assess exposure and early health effects associated with living near ICSs. OBJECTIVES: to discuss challenges and lessons learned for addressing environmental health impact near ICSs with HBM in order to identify needs and priorities for HBM guidelines in European ICSs. METHODS: based on the experience of the ICSHNet research team, six case studies from different European regions that applied HBM at ICSs were selected. The case studies were systematically compared distinguishing four phases: the preparatory phase; study design; study results; the impact of the results at scientific, societal, and political levels. RESULTS: all six case studies identified opportunities and challenges for applying HBM in ICS studies. A smart choice of (a combination of) sample matrices for biomarker analysis produced information about relevant time-windows of exposure which matched with the activities of the ICSs. Combining biomarkers of exposure with biomarkers of (early) biological effects, data from questionnaires or environmental data enabled fine-tuning of the results and allowed for more targeted remediating actions aimed to reduce exposure. Open and transparent communication of study results with contextual information and involvement of local stakeholders throughout the study helped to build confidence in the study results, gained support for remediating actions, and facilitated sharing of responsibilities. Using HBM in these ICS studies helped in setting priorities in policy actions and in further research. Limitations were the size of the study population, difficulties in recruiting vulnerable target populations, availability of validated biomarkers, and coping with exposure to mixtures of chemicals. CONCLUSIONS: based on the identified positive experiences and challenges, the paper concludes with formulating recommendations for a European protocol and guidance document for HBM in ICS. This could advance the use of HBM in local environmental health policy development and evaluation of exposure levels, and promote coordination and collaboration between researchers and risk managers.

Air pollution and incidence of cancers of the stomach and the upper aerodigestive tract in the European Study of Cohorts for Air Pollution Effects (ESCAPE).

Air pollution has been classified as carcinogenic to humans. However, to date little is known about the relevance for cancers of the stomach and upper aerodigestive tract (UADT). We investigated the association of long-term exposure to ambient air pollution with incidence of gastric and UADT cancer in 11 European cohorts. Air pollution exposure was assigned by land-use regression models for particulate matter (PM) below 10 µm (PM10 ), below 2.5 µm (PM2.5 ), between 2.5 and 10 µm (PMcoarse ), PM2.5 absorbance and nitrogen oxides (NO2 and NOX ) as well as approximated by traffic indicators. Cox regression models with adjustment for potential confounders were used for cohort-specific analyses. Combined estimates were determined with random effects meta-analyses. During average follow-up of 14.1 years of 305,551 individuals, 744 incident cases of gastric cancer and 933 of UADT cancer occurred. The hazard ratio for an increase of 5 µg/m3 of PM2.5 was 1.38 (95% CI 0.99; 1.92) for gastric and 1.05 (95% CI 0.62; 1.77) for UADT cancers. No associations were found for any of the other exposures considered. Adjustment for additional confounders and restriction to study participants with stable addresses did not influence markedly the effect estimate for PM2.5 and gastric cancer. Higher estimated risks of gastric cancer associated with PM2.5 was found in men (HR 1.98 [1.30; 3.01]) as compared to women (HR 0.85 [0.5; 1.45]). This large multicentre cohort study shows an association between long-term exposure to PM2.5 and gastric cancer, but not UADT cancers, suggesting that air pollution may contribute to gastric cancer risk.

Land use regression models for the oxidative potential of fine particles (PM2.5) in five European areas.

Oxidative potential (OP) of particulate matter (PM) is proposed as a biologically-relevant exposure metric for studies of air pollution and health. We aimed to evaluate the spatial variability of the OP of measured PM2.5 using ascorbate (AA) and (reduced) glutathione (GSH), and develop land use regression (LUR) models to explain this spatial variability. We estimated annual average values (m-3) of OPAA and OPGSH for five areas (Basel, CH; Catalonia, ES; London-Oxford, UK (no OPGSH); the Netherlands; and Turin, IT) using PM2.5 filters. OPAA and OPGSH LUR models were developed using all monitoring sites, separately for each area and combined-areas. The same variables were then used in repeated sub-sampling of monitoring sites to test sensitivity of variable selection; new variables were offered where variables were excluded (p > .1). On average, measurements of OPAA and OPGSH were moderately correlated (maximum Pearson's maximum Pearson's R = = .7) with PM2.5 and other metrics (PM2.5absorbance, NO2, Cu, Fe). HOV (hold-out validation) R2 for OPAA models was .21, .58, .45, .53, and .13 for Basel, Catalonia, London-Oxford, the Netherlands and Turin respectively. For OPGSH, the only model achieving at least moderate performance was for the Netherlands (R2 = .31). Combined models for OPAA and OPGSH were largely explained by study area with weak local predictors of intra-area contrasts; we therefore do not endorse them for use in epidemiologic studies. Given the moderate correlation of OPAA with other pollutants, the three reasonably performing LUR models for OPAA could be used independently of other pollutant metrics in epidemiological studies.

Associations of greenness, greyness and air pollution exposure with children's health: a cross-sectional study in Southern Italy.

BACKGROUND: Due to the complex interplay among different urban-related exposures, a comprehensive approach is advisable to estimate the health effects. We simultaneously assessed the effect of "green", "grey" and air pollution exposure on respiratory/allergic conditions and general symptoms in schoolchildren. METHODS: This study involved 219 schoolchildren (8-10 years) of the Municipality of Palermo, Italy. Data were collected through questionnaires self-administered by parents and children. Exposures to greenness and greyness at the home addresses were measured using the normalized difference vegetation index (NDVI), residential surrounding greyness (RSG) and the CORINE land-cover classes (CLC). RSG was defined as the percentage of buffer covered by either industrial, commercial and transport units, or dump and construction sites, or urban fabric related features. Two specific categories of CLC, namely "discontinuous urban fabric - DUF" - and "continuous urban fabric - CUF" - areas were found. Exposure to traffic-related nitrogen dioxide (NO2) was assessed using a Land-Use Regression model. A symptom score ranging from 0 to 22 was built by summing affirmative answers to twenty-two questions on symptoms. To avoid multicollinearity, multiple Logistic and Poisson ridge regression models were applied to assess the relationships between environmental factors and self-reported symptoms. RESULTS: A very low exposure to NDVI ≤0.15 (1st quartile) had a higher odds of nasal symptoms (OR = 1.47, 95% CI [1.07-2.03]). Children living in CUF areas had higher odds of ocular symptoms (OR = 1.49, 95% CI [1.10-2.03]) and general symptoms (OR = 1.18, 95% CI [1.00-1.48]) than children living in DUF areas. Children living in proximity (≤200 m) to High Traffic Roads (HTRs) had increased odds of ocular (OR = 1.68, 95% CI [1.31-2.17]) and nasal symptoms (OR = 1.49, 95% CI [1.12-1.98]). A very high exposure to NO2 ≥ 60 µg/m3 (4th quartile) was associated with a higher odds of general symptoms (OR = 1.28, 95% CI [1.10-1.48]). No associations were found with RGS. A Poisson ridge regression model on the symptom score showed that children living in proximity to HTRs (≤200 m) had a higher symptoms score (RR = 1.09, 95% CI [1.02-1.17]) than children living > 200 m from HTRs. Children living in CUF areas had a higher symptoms score (RR = 1.11, 95% CI [1.03-1.19]) than children living in DUF areas. CONCLUSIONS: Multiple exposures related to greenness, greyness (measured by CORINE) and air pollution within the urban environment are associated with respiratory/allergic and general symptoms in schoolchildren. No associations were found when considering the individual exposure to greyness measured using the RSG indicator.