Residential exposure to air pollution and incidence of leukaemia in the industrial area of Viadana, Northern Italy.

BACKGROUND: Exposure to air pollution has been proposed as one of the potential risk factors for leukaemia. Work-related formaldehyde exposure is suspected to cause leukaemia. METHODS: We conducted a nested register-based case-control study on leukaemia incidence in the Viadana district, an industrial area for particleboard production in Northern Italy. We recruited 115 cases and 496 controls, frequency-matched by age, between 1999 and 2014. We assigned estimated exposures to particulate matter (PM10, PM2.5), nitrogen dioxide (NO2), and formaldehyde at residential addresses, averaged over the susceptibility window 3rd to 10th year prior to the index date. We considered potential confounding by sex, age, nationality, socio-economic status, occupational exposures to benzene and formaldehyde, and prior cancer diagnoses. RESULTS: There was no association of exposures to PM10, PM2.5, and NO2 with leukaemia incidence. However, an indication of increased risk emerged for formaldehyde, despite wide statistical uncertainty (OR 1.46, 95%CI 0.65-3.25 per IQR-difference of 1.2 µg/m3). Estimated associations for formaldehyde were higher for acute (OR 2.07, 95%CI 0.70-6.12) and myeloid subtypes (OR 1.79, 95%CI 0.64-5.01), and in the 4-km buffer around the industrial facilities (OR 2.78, 95%CI 0.48-16.13), although they remained uncertain. CONCLUSIONS: This was the first study investigating the link between ambient formaldehyde exposure and leukaemia incidence in the general population. The evidence presented suggests an association, although it remains inconclusive, and a potential significance of emissions related to industrial activities in the district. Further research is warranted in larger populations incorporating data on other potential risk factors.

[Geocoding one million of addresses using API: a semiautomatic multistep procedure]. / Geocodificare un milione di indirizzi mediante l'utilizzo di API: una procedura semiautomatica a più step.

OBJECTIVES: to geocode all residence addresses from Lazio Health Information System in order to obtain a geographical regional database. DESIGN: a semiautomatic and multistep geocoding procedure using several tools and software. SETTING AND PARTICIPANTS: all residence addresses of resident population of Lazio Region (Central Italy) in 2020. MAIN OUTCOME MEASURES: geographic coordinates at residence addresses and accuracy level of geocoding procedure for more than 1 million of addresses. RESULTS: the 99% of residence addresses in the Lazio Region have been geocoded thanks to the purposed procedure; almost 94% of the addresses have been geocoded with a good level of accuracy (more than 56% at civic number level). In the province of Rome, the percentage of addresses geocoded with a good level of accuracy is higher (97.1%), while in the province of Rieti and Frosinone is lower (82.7% and 84.2%, respectively). CONCLUSIONS: this method is useful to obtain accurate geographic coordinates of residences of the entire regional population. This database will be useful for several epidemiological studies in the Region.

[Spatial and temporal variation of life expectancy at birth by socioeconomic position and district in Rome for the years 2006-2017]. / Variazione spazio-temporale dell'aspettativa di vita per livello socioeconomico e distretto sanitario a Roma negli anni 2006-2017.

OBJECTIVES: to evaluate the gap in life expectancy on the municipality of Rome, through the spatio-temporal changes in life expectancy at the birth and at 65 years old of residents in between 2006 and 2017, by gender, socioeconomic position, and health district. DESIGN: epidemiological study based on the construction of mortality tables describing age-specific mortality rates and life expectancy at birth and at 65 years old. SETTING AND PARTICIPANTS: from the Register of the Causes of Death (ReNCaM), between 2006 to 2017, 329,426 deaths of residents in Rome were selected. MAIN OUTCOME MEASURES: the variation in life expectancy at birth was estimated by gender, by socioeconomic position, and by health district for four triennial observation periods from 2006 to 2017. Temporal and socioeconomic position changes, through an indicator of deprivation of a small area specific for the city of Rome, and possible geographical patterns, by observing the variation in the 15 health districts, between 2006 and 2017 were observed. RESULTS: in Rome, between the first three-year period (2006-2008) and the last one (2015-2017), the life expectancy at birth increases, whit a gain of about 1.5 years among males (from 78.7 to 80.4 years) and just under 1 year among females (from 83.6 to 84.4 years). The increase in life expectancy, however, is not uniform in the population and the results show differences in socioeconomic position that increase in the most recent three years to 4 years for males and 2.2 years for females. The geographical analysis shows important differences in the life expectancy among health districts with differences up to about 3 years for males and 2.2 years for females at the beginning of the study period among districts in the historical centre and districts on the outskirts of the City of Rome, which are reduced to 2.7 years for males and 2.1 years for females in the most recent period. CONCLUSIONS: the analysis of geographical and socioeconomic differences of the life expectancy provides important information to identify the areas of the Municipality of Rome on which to strengthen prevention interventions and the actions to be taken for Objective 10 ("Reducing inequalities") of Agenda 2030 for sustainable development.

[Spatial analysis for detecting clusters of cases during the COVID-19 emergency in Rome and in the Lazio Region (Central Italy)]. / Analisi spaziale per l'identificazione di cluster di casi durante l'emergenza COVID-19 a Roma e nel Lazio.

BACKGROUND: one of the most affected European countries by the COVID-19 epidemic is Italy; data show the strong geographical heterogeneity of the epidemic. OBJECTIVES: to propose an analysis strategy to ascertain the non-random nature of the spatial spread of COVID-19 cases infection and identify any territorial aggregations, in order to enhance contact tracing activities in specific areas of the Lazio Region (Central Italy) and a large urban area as Rome. METHODS: all cases of COVID-19 of the Lazio Region notified to the Regional Service for Epidemiology, Surveillance, and Control of Infectious Diseases (Seresmi) with daily updates from the beginning of the epidemic to April 27, 2020 were considered. The analyses were carried out considering two periods (the first from the beginning of the epidemic to April 6 and the second from the beginning of the epidemic to April 27) and two different levels of spatial aggregation: the entire Lazio region excluding the Municipality of Rome, where the 377 municipalities represent the area units, and the Municipality of Rome, where the area units under study are the 155 urban areas (ZUR). The Scan statistic of Kulldorff was used to ascertain the non-random nature of the spatial spread of infected cases and to identify any territorial aggregations of cases of COVID-19 infection, using a retrospective spatial analysis in two overlapping periods. RESULTS: analysis was conducted at regional level in the two survey periods and revealed the presence of 7 localized clusters. In the Municipality of Rome, a single cluster (Historic Centre) was identified in the first period which includes 7 urban areas, while in the second period two distinct clusters (Omo and Farnesina) were observed. CONCLUSIONS: Scan statistics are an important surveillance tool for monitoring disease outbreaks during the active phase of the epidemic and a useful contribution to epidemiological surveillance during the COVID-19 epidemic in a specific territory.

Effect of national and local lockdowns on the control of COVID-19 pandemic: a rapid review.

OBJECTIVES: to describe and compare the effectiveness of national and local lockdowns in controlling the spread of COVID-19. METHODS: a rapid review of published and grey literature on COVID-19 pandemic was conducted following predefined eligibility criteria by searching electronic databases, repositories of pre-print articles, websites and databases of international health, and research related institutions and organisations. RESULTS: of 584 initially identified records up to 5 July 2020, 19 articles met the inclusion criteria and were included in the review. Most of the studies (No. 11) used the reproduction  number (Rt) as a measure of effect and in all of them areduction of the estimated value at post-intervention period was found. The implementation of lockdown in 11 European countries was associated with an average 82% reduction of Rt, ranging from a  posterior Rt of 0.44 (95%CI 0.26-0.61) for Norway to a posterior Rt of 0.82 (95%CI 0.73- 0.93) for  Belgium. Changes in infection rates and transmission rates were estimated in 8 studies. Daily changes in infection rates ranged from -0.6% (Sweden) to -11.3% (Hubei and Guangdong provinces). Additionally, other studies reported a change in the trend of hospitalizations (Italy, Spain) and positive effects on the  doubling time of cases (Hubei, China) after lockdown. CONCLUSIONS: results of this rapid review suggest a positive effect of the containment measures on the spread of COVID-19 pandemic, with a major effect in  countries where lockdown started early and was more restrictive. Rigorous research is warranted to evaluate which approach is the most effective in each stage of the epidemic and in specific social contexts, in particular addressing if these approaches should be implemented on the whole population or target specific risk groups.

Air Pollution Exposure During Pregnancy and Symptoms of Attention Deficit and Hyperactivity Disorder in Children in Europe.

BACKGROUND: Exposure to air pollution during pregnancy may increase attention-deficit/hyperactivity disorder (ADHD) symptoms in children, but findings have been inconsistent. We aimed to study this association in a collaborative study of eight European population-based birth/child cohorts, including 29,127 mother-child pairs. METHODS: Air pollution concentrations (nitrogen dioxide [NO2] and particulate matter [PM]) were estimated at the birth address by land-use regression models based on monitoring campaigns performed between 2008 and 2011. We extrapolated concentrations back in time to exact pregnancy periods. Teachers or parents assessed ADHD symptoms at 3-10 years of age. We classified children as having ADHD symptoms within the borderline/clinical range and within the clinical range using validated cutoffs. We combined all adjusted area-specific effect estimates using random-effects meta-analysis and multiple imputations and applied inverse probability-weighting methods to correct for loss to follow-up. RESULTS: We classified a total of 2,801 children as having ADHD symptoms within the borderline/clinical range, and 1,590 within the clinical range. Exposure to air pollution during pregnancy was not associated with a higher odds of ADHD symptoms within the borderline/clinical range (e.g., adjusted odds ratio [OR] for ADHD symptoms of 0.95, 95% confidence interval [CI] = 0.89, 1.01 per 10 µg/m increase in NO2 and 0.98, 95% CI = 0.80, 1.19 per 5 µg/m increase in PM2.5). We observed similar associations for ADHD within the clinical range. CONCLUSIONS: There was no evidence for an increase in risk of ADHD symptoms with increasing prenatal air pollution levels in children aged 3-10 years. See video abstract at, http://links.lww.com/EDE/B379.

Traffic-related air pollution and childhood obesity in an Italian birth cohort.

BACKGROUND: Air pollution is associated with several adverse health outcomes in children, such as respiratory illnesses and cognitive development impairment. There are suggestions of an effect of traffic-related air pollution on the occurrence of childhood obesity, but the results are not consistent. OBJECTIVES: The aim of the study is to analyse whether air pollution and vehicular traffic exposure, during the first four years of life, influence obesity- related measures among 4 and 8-year-old children from a prospective birth cohort in Rome. METHODS: A cohort of newborns, enrolled in 2003-2004 within the GASPII project, was followed at 4 and 8 years of age with parental interviews and clinical examinations. Air pollution was assessed at residential address using Land Use Regression models (for NO2, NOx, PM10, PM2.5, PMcoarse, PM2.5 absorbance and one traffic variable (Total traffic load of all roads in a 100m buffer)). The outcomes under study were body mass index (BMI Z-scores according to WHO recommendations, considered both categorical and continuous) measured at 4 and 8 years, and, waist circumference, waist-to-hip ratio, total and HDL cholesterol measured at 8 years. The associations were evaluated through both cross-sectional and longitudinal approaches, using logistic regression models, Generalized Estimating Equation models (GEE) and linear regression models, as appropriate. Moreover, Inverse Probability Weighting (IPW) methodology was used to account for selection bias at enrolment and at follow-up. RESULTS: A total of 719 infants were enrolled and 581 (80.8%) and 499 (69.4%) were followed at 4 and 8 years, respectively. The prevalence of overweight/obesity was 9.3% and 36.9% at 4 and 8 years. No evidence of an association was found between vehicular traffic and being overweight/obese. Similarly, there was no evidence of an association between exposure to air pollutants and all other ponderal excess parameters. CONCLUSIONS: The study shows no association between exposure to vehicular traffic and exposure to pollutants on obesity related parameters such as BMI, blood lipids and abdominal adiposity during childhood. Overall evidence of air pollution being obesogenic remains limited.

[Big data in environmental epidemiology. Satellite and land use data for the estimation of environmental exposures at national level]. / Big data in epidemiologia ambientale. Dati satellitari e uso del territorio per la stima delle esposizioni a livello nazionale.

OBJECTIVES: to define a national geographic domain, with high spatial (1 km²) and temporal (daily) resolution, and to build a list of georeferenced environmental and temporal indicators useful for environmental epidemiology applications at national level. DESIGN: geographic study. SETTING AND PARTICIPANTS: study domain: Italian territory divided into 307,635 1-km² grid cells; study period: 2006-2012, divided into 2,557 daily time windows. MAIN OUTCOME MEASURES: for each grid cell and day, an extensive number of indicators has been computed. These indicators include spatial (administrative layers, resident population, presence of water bodies, climatic zones, land use variables, impervious surfaces, orography, viability, point and areal emissions of air pollutants) and spatio-temporal predictors (particulate matter data from monitoring stations, meteorological parameters, desert dust advection episodes, aerosol optical depth, normalized difference vegetation index, planetary boundary layer) potentially useful to characterize population environmental exposures and to estimate their health effects, at national level. RESULTS AND CONCLUSIONS: this study represents the first example of relational big data in environmental epidemiology at national level, where multiple sources of data (satellite, environmental, meteorology, land use, population) have been linked on a common spatial and temporal domain, aimed at promoting environmental epidemiology applications at national and local level.

Air Pollution and Cognitive Development at Age 7 in a Prospective Italian Birth Cohort.

BACKGROUND: Early life exposure to air pollution has been linked with cognitive impairment in children, but the results have not been conclusive. We analyzed the association between traffic-related air pollution and cognitive function in a prospective birth cohort in Rome. METHODS: A cohort of 719 newborns was enrolled in 2003-2004 as part of the GASPII project. At age 7 years, 474 children took the Wechsler Intelligence Scale for Children-III to assess their cognitive development in terms of IQ composite scores. Exposure to air pollutants (NO2, PMcoarse, PM2.5, PM2.5 absorbance) at birth was assessed using land use regression models. We also considered variables indicating traffic intensity. The effect of environmental pollution on IQ was evaluated performing a linear regression model for each outcome, adjusting for gender, child age at cognitive test, maternal age at delivery, parental educational level, siblings, socio-economic status, maternal smoking during pregnancy, and tester. To account for selection bias at enrollment and during follow-up, the regression models were weighted for the inverse probabilities of participation and follow-up. RESULTS: A 10 µg/m³ higher NO2 exposure during pregnancy was associated with 1.4 fewer points (95% confidence interval = -2.6, -0.20) of verbal IQ, and 1.4 fewer points (95% confidence interval = -2.7, -0.20) of verbal comprehension IQ. Similar associations were found for traffic intensity in a 100 m buffer around home. Other pollutants showed negative associations with larger confidence intervals. CONCLUSIONS: Consistent with previous evidence, this study suggests an association of exposure to NO2 and traffic intensity with the verbal area of cognitive development.See Video Abstract at http://links.lww.com/EDE/B12.

Long-term Exposure to Particulate Matter Constituents and the Incidence of Coronary Events in 11 European Cohorts.

BACKGROUND: Long-term exposure to particulate matter (PM) has been associated with increased cardiovascular morbidity and mortality but little is known about the role of the chemical composition of PM. This study examined the association of residential long-term exposure to PM components with incident coronary events. METHODS: Eleven cohorts from Finland, Sweden, Denmark, Germany, and Italy participated in this analysis. 5,157 incident coronary events were identified within 100,166 persons followed on average for 11.5 years. Long-term residential concentrations of PM < 10 µm (PM10), PM < 2.5 µm (PM2.5), and a priori selected constituents (copper, iron, nickel, potassium, silicon, sulfur, vanadium, and zinc) were estimated with land-use regression models. We used Cox proportional hazard models adjusted for a common set of confounders to estimate cohort-specific component effects with and without including PM mass, and random effects meta-analyses to pool cohort-specific results. RESULTS: A 100 ng/m³ increase in PM10 K and a 50 ng/m³ increase in PM2.5 K were associated with a 6% (hazard ratio and 95% confidence interval: 1.06 [1.01, 1.12]) and 18% (1.18 [1.06, 1.32]) increase in coronary events. Estimates for PM10 Si and PM2.5 Fe were also elevated. All other PM constituents indicated a positive association with coronary events. When additionally adjusting for PM mass, the estimates decreased except for K. CONCLUSIONS: This multicenter study of 11 European cohorts pointed to an association between long-term exposure to PM constituents and coronary events, especially for indicators of road dust.

Mortality and morbidity in a population exposed to multiple sources of air pollution: A retrospective cohort study using air dispersion models.

BACKGROUND AND AIMS: A landfill, an incinerator, and a refinery plant have been operating since the early 1960s in a contaminated site located in the suburb of Rome (Italy). To evaluate their potential health effects, a population-based retrospective cohort study was conducted using dispersion modeling for exposure assessment. METHODS: A fixed cohort was enrolled in the Rome Longitudinal Study in 2001, mortality and hospitalizations were followed-up until 2010. Exposure assessments to the landfill (H2S), the incinerator (PM10), and the refinery plant (SOX) were performed for each subject using a Lagrangian dispersion model. Individual and small-area variables were available (including exposures levels to NO2 from traffic and diesel trucks). Cox regression analysis was performed (hazard ratios, HRs, 95% CI) using linear terms for the exposures (5th-95th percentiles difference). Single and bi-pollutant models were run. RESULTS: The cohort included 85,559 individuals. The estimated annual average exposures levels were correlated. H2S from the landfill was associated with cardiovascular hospital admissions in both genders (HR 1.04 95% CI 1.00-1.09 in women); PM10 from the incinerator was associated with pancreatic cancer mortality in both genders (HR 1.40 95% CI 1.03-1.90 in men, HR 1.47 95% CI 1.12-1.93 in women) and with breast morbidity in women (HR 1.13 95% CI 1.00-1.27). SOx from the refinery was associated with laryngeal cancer mortality in women (HR 4.99 95% CI 1.64-15.9) and respiratory hospital admissions (HR 1.13 95% CI 1.01-1.27). CONCLUSIONS: We found an association of the pollution sources with some cancer forms and cardio-respiratory diseases. Although there was a high correlation between the estimated exposures, an indication of specific effects from the different sources emerged.

Air pollution during pregnancy and childhood cognitive and psychomotor development: six European birth cohorts.

BACKGROUND: Accumulating evidence from laboratory animal and human studies suggests that air pollution exposure during pregnancy affects cognitive and psychomotor development in childhood. METHODS: We analyzed data from 6 European population-based birth cohorts-GENERATION R (The Netherlands), DUISBURG (Germany), EDEN (France), GASPII (Italy), RHEA (Greece), and INMA (Spain)-that recruited mother-infant pairs from 1997 to 2008. Air pollution levels-nitrogen oxides (NO2, NOx) in all regions and particulate matter (PM) with diameters of <2.5, <10, and 2.5-10 µm (PM2.5, PM10, and PMcoarse, respectively) and PM2.5 absorbance in a subgroup-at birth addresses were estimated by land-use regression models, based on monitoring campaigns performed primarily between 2008 and 2011. Levels were back-extrapolated to exact pregnancy periods using background monitoring sites. Cognitive and psychomotor development was assessed between 1 and 6 years of age. Adjusted region-specific effect estimates were combined using random-effects meta-analysis. RESULTS: A total of 9482 children were included. Air pollution exposure during pregnancy, particularly NO2, was associated with reduced psychomotor development (global psychomotor development score decreased by 0.68 points [95% confidence interval = -1.25 to -0.11] per increase of 10 µg/m in NO2). Similar trends were observed in most regions. No associations were found between any air pollutant and cognitive development. CONCLUSIONS: Air pollution exposure during pregnancy, particularly NO2 (for which motorized traffic is a major source), was associated with delayed psychomotor development during childhood. Due to the widespread nature of air pollution exposure, the public health impact of the small changes observed at an individual level could be considerable.

Exposure to air pollution and respiratory symptoms during the first 7 years of life in an Italian birth cohort.

BACKGROUND: Ambient air pollution has been consistently associated with exacerbation of respiratory diseases in schoolchildren, but the role of early exposure to traffic-related air pollution in the first occurrence of respiratory symptoms and asthma is not yet clear. METHODS: We assessed the association between indexes of exposure to traffic-related air pollution during different periods of life and respiratory outcomes in a birth cohort of 672 newborns (Rome, Italy). Direct interviews of the mother were conducted at birth and at 6, 15 months, 4 and 7 years. Exposure to traffic-related air pollution was assessed for each residential address during the follow-up period using a Land-Use Regression model (LUR) for nitrogen dioxide (NO2) and a Geographic Information System (GIS) variable of proximity to high-traffic roads (HTR) (>10 000vehicles/day). We used age-specific NO2 levels to develop indices of exposure at birth, current, and lifetime time-weighted average. The association of NO2 and traffic proximity with respiratory disorders were evaluated using logistic regression in a longitudinal approach (Generalised Estimating Equation). The exposure indexes were used as continuous and categorical variables (cut-off points based on the 75th percentile for NO2 and the 25th percentile for distance from HTRs). RESULTS: The average NO2 exposure level at birth was 37.2 µg/m(3) (SD 7.2, 10-90th range 29.2-46.1). There were no statistical significant associations between the exposure indices and the respiratory outcomes in the longitudinal model. The odds ratios for a 10-µg/m(3) increase in time-weighted average NO2 exposure were: asthma incidence OR=1.09; 95 CI% 0.78 to 1.52, wheezing OR=1.07; 95 CI% 0.90 to 1.28, shortness of breath with wheezing OR=1.16; 95 CI% 0.94 to 1.43, cough or phlegm apart from cold OR=1.11; 95 CI% 0.92 to 1.33, and otitis OR=1.08; 95 CI% 0.89 to 1.32. Stronger but not significant associations were found considering the 75th percentile of the NO2 distribution as a cut-off, especially for incidence of asthma and prevalence of wheeze (OR=1.41; 95 CI% 0.88 to 2.28 and OR=1.27; 95 CI% 0.95 to 1.70, respectively); the highest OR was found for wheezing (OR=2.29; 95 CI% 1.15 to 4.56) at the 7-year follow-up. No association was found with distance from HTRs. CONCLUSIONS: Exposure to traffic-related air pollution is only weakly associated with respiratory symptoms in young children in the first 7 years of life.

[Morbidity in a population living close to urban waste incinerator plants in Lazio Region (Central Italy): a retrospective cohort study using a before-after design]. / Stato di salute della popolazione residente nei pressi dei termovalorizzatori del Lazio: uno studio di coorte retrospettivo con approccio pre-post.

BACKGROUND: the body of evidence on health effects of residential exposure to urban waste incinerators suggests association with reproductive outcomes and some cancers, but the overall evidence is still limited. OBJECTIVES: we evaluated the impact of two incinerators on hospital admissions for respiratory and cardiovascular diseases in a cohort of people living nearby two incineration plants in Lazio Region (Central Italy) using a before-and-after design. METHODS: the study area was defined as the 7-km radius around the incinerators. People who were resident in the area from 1996 to 2008 were enrolled in a retrospective longitudinal study. All addresses were geocoded. A Lagrangian dispersion model (SPRAY) for PM10 (ng/m³) was used for incinerators exposure assessment. Average annual concentration of background PM10 (µg/m³) was estimated on a regional basis by means of RAMS and FARM models. Both PM10 exposures were estimated at the residential address. All subjects were followed for hospital admissions in the period before (1996-2002) and after (2003-2008) the activation of the plants. The association between exposure to emissions from incinerators and hospitalizations in the two periods was estimated using the multivariate Cox model (for repeated events), adjusting for age, area-level socioeconomic status, distance from industries, traffic roads and highways. An interaction term between the period of follow-up (before or after the activation of the plants) and the exposure levels was used to test the effect of the incinerators. RESULTS: 47,192 subjects resident in the study area were enrolled. No clear association between pollution exposure from incinerators and cause-specific morbidity of residents in highest concentration areas was found when compared to the reference group. However, an effect of PM10 on respiratory diseases and chronic obstructive pulmonary disease was suggested. The effect was due to excesses of hospitalizations for the same causes among men living in highest exposure areas in respect to the reference group (hazard ratio - HR: 1.26; 95%CI 0.99-1.60, and HR: 1.86; 95%CI 1.04-3.33, respectively). There were associations between exposure to background pollution from other sources and hospitalizations for diseases of the circulatory system (HR: 1.08; 95%CI 1.03-1.13) and respiratory diseases (HR: 1.07; 95%CI 1.02-1.11) (for a unitary increment of PM10, µg/m³). CONCLUSIONS: living in areas with high PM10 levels due to incinerators was associated with increased morbidity levels for respiratory disorders among men. The study area is critical from an environmental point of view, hence an epidemiological surveillance is recommended.

[Health impact assessment of policies for municipal solid waste management: findings of the SESPIR Project]. / Impatto sulla salute delle politiche di gestione dei rifiuti solidi urbani: i risultati del Progetto SESPIR.

The SESPIR Project (Epidemiological Surveillance of Health Status of Resident Population Around the Waste Treatment Plants) assessed the impact on health of residents nearby incinerators, landfills and mechanical biological treatment plants in five Italian regions (Emilia-Romagna, Piedmont, Lazio, Campania, and Sicily). The assessment procedure took into account the available knowledge on health effects of waste disposal facilities. Analyses were related to three different scenarios: a Baseline scenario, referred to plants active in 2008-2009; the regional future scenario, with plants expected in the waste regional plans; a virtuous scenario (Green 2020), based on a policy management of municipal solid waste (MSW) through the reduction of production and an intense recovery policy. Facing with a total population of around 24 million for the 5 regions, the residents nearby the plants were more than 380,000 people at Baseline. Such a population is reduced to approximately 330.000 inhabitants and 170.000 inhabitants in the regional and Green 2020 scenarios, respectively. The health impact was assessed for the period 2008-2040. At Baseline, 1-2 cases per year of cancer attributable to MSW plants were estimated, as well as 26 cases per year of adverse pregnancy outcomes (including low birth weight and birth defects), 102 persons with respiratory symptoms, and about a thousand affected from annoyance caused by odours. These annual estimates are translated into 2,725 years of life with disability (DALYs) estimated for the entire period. The DALYs are reduced by approximately 20% and 80% in the two future scenarios. Even in these cases, health impact is given by the greater effects on pregnancy and the annoyance associated with the odours of plants. In spite of the limitations due to the inevitable assumptions required by the present exercise, the proposed methodology is suitable for a first approach to assess different policies that can be adopted in regional planning in the field of waste management. The greatest reduction in health impact is achieved with a virtuous policy of reducing waste production and a significant increase in the collection and recycling of waste.

[Residential cohort approach in industrial contaminated sites: the ERAS Lazio project]. / Lo studio di coorte di popolazione in aree a forte pressione ambientale: il programma ERAS Lazio.

The population-based cohort study is the best design for assessing the possible health effects resulting fromliving in contaminated sites. The ERAS (Epidemiology,Waste disposal, Environment and Health) Project was established to study the health of people living in close proximity to urban solid waste treatment (RU) plants in Lazio. It was conducted using an integrated approach, which consisted in studying mortality and hospital discharges of residential cohorts surrounding urban waste treatment plants. The level of exposure of each address was assigned using pollution dispersion models and studying the effects on mortality and hospital discharges. Further studies were conducted on residents of areas adjacent to waste disposal sites (includingMalagrotta in Rome), incinerators andmechanical biological treatment plants. The final version of the ERAS Report is available at www.eraslazio.it. The residential cohort approach and the combination of environmental and health-related information proved invaluable in the assessment of the health impact of solid waste treatment in Lazio.

[Long-term health effects of air pollution: results of the European project ESCAPE]. / Gli effetti di lungo termine dell´inquinamento atmosferico sulla salute.

Air pollution has been recently classified among the top ten risk factors for mortality worldwide. The evidence on the long-term effects of air pollutants is mounting, mostly from multi-centre American studies or longitudinal studies conducted in single European cohorts. Recently, the EU-funded project ESCAPE (European Study of Cohorts for Air Pollution Effects) involved more than 30 cohort studies with the aim of producing pooled estimates of the long-term health effects of ambient air pollution at European level. The project developed a standardized and flexible methodology to estimate chronic exposure to several air pollutants, applied such estimates to existing cohorts in Europe, and analyzed the exposure-response relationships with different health endpoints, including adverse pregnancy outcomes, respiratory diseases among children, cardio-respiratory diseases among adults, cause-specific mortality and lung cancer incidence. One of the most important results has been the detection of relevant health effects of particulate matter at concentrations below the current air quality limit values in Europe.

Chronic burden of near-roadway traffic pollution in 10 European cities (APHEKOM network).

Recent epidemiological research suggests that near road traffic-related pollution may cause chronic disease, as well as exacerbation of related pathologies, implying that the entire "chronic disease progression" should be attributed to air pollution, no matter what the proximate cause was. We estimated the burden of childhood asthma attributable to air pollution in 10 European cities by calculating the number of cases of 1) asthma caused by near road traffic-related pollution, and 2) acute asthma events related to urban air pollution levels. We then expanded our approach to include coronary heart diseases in adults. Derivation of attributable cases required combining concentration-response function between exposures and the respective health outcome of interest (obtained from published literature), an estimate of the distribution of selected exposures in the target population, and information about the frequency of the assessed morbidities. Exposure to roads with high vehicle traffic, a proxy for near road traffic-related pollution, accounted for 14% of all asthma cases. When a causal relationship between near road traffic-related pollution and asthma is assumed, 15% of all episodes of asthma symptoms were attributable to air pollution. Without this assumption, only 2% of asthma symptoms were attributable to air pollution. Similar patterns were found for coronary heart diseases in older adults. Pollutants along busy roads are responsible for a large and preventable share of chronic disease and related acute exacerbations in European urban areas.

Development of land use regression models for particle composition in twenty study areas in Europe.

Land Use Regression (LUR) models have been used to describe and model spatial variability of annual mean concentrations of traffic related pollutants such as nitrogen dioxide (NO2), nitrogen oxides (NOx) and particulate matter (PM). No models have yet been published of elemental composition. As part of the ESCAPE project, we measured the elemental composition in both the PM10 and PM2.5 fraction sizes at 20 sites in each of 20 study areas across Europe. LUR models for eight a priori selected elements (copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)) were developed. Good models were developed for Cu, Fe, and Zn in both fractions (PM10 and PM2.5) explaining on average between 67 and 79% of the concentration variance (R(2)) with a large variability between areas. Traffic variables were the dominant predictors, reflecting nontailpipe emissions. Models for V and S in the PM10 and PM2.5 fractions and Si, Ni, and K in the PM10 fraction performed moderately with R(2) ranging from 50 to 61%. Si, NI, and K models for PM2.5 performed poorest with R(2) under 50%. The LUR models are used to estimate exposures to elemental composition in the health studies involved in ESCAPE.

A spatial indicator of environmental and climatic vulnerability in Rome.

BACKGROUND: Urban areas are disproportionately affected by multiple pressures from overbuilding, traffic, air pollution, and heat waves that often interact and are interconnected in producing health effects. A new synthetic tool to summarize environmental and climatic vulnerability has been introduced for the city of Rome, Italy, to provide the basis for environmental and health policies. METHODS: From a literature overview and based on the availability of data, several macro-dimensions were identified on 1,461 grid cells with a width of 1 km2 in Rome: land use, roads and traffic-related exposure, green space data, soil sealing, air pollution (PM2.5, PM10, NO2, C6H6, SO2), urban heat island intensity. The Geographically Weighted Principal Component Analysis (GWPCA) method was performed to produce a composite spatial indicator to describe and interpret each spatial feature by integrating all environmental dimensions. The method of natural breaks was used to define the risk classes. A bivariate map of environmental and social vulnerability was described. RESULTS: The first three components explained most of the variation in the data structure with an average of 78.2% of the total percentage of variance (PTV) explained by the GWPCA, with air pollution and soil sealing contributing most in the first component; green space in the second component; road and traffic density and SO2 in the third component. 56% of the population lives in areas with high or very high levels of environmental and climatic vulnerability, showing a periphery-centre trend, inverse to the deprivation index. CONCLUSIONS: A new environmental and climatic vulnerability indicator for the city of Rome was able to identify the areas and population at risk in the city, and can be integrated with other vulnerability dimensions, such as social deprivation, providing the basis for risk stratification of the population and for the design of policies to address environmental, climatic and social injustice.